WorldWideScience

Sample records for human cancer classification

  1. On the International Agency for Research on Cancer classification of glyphosate as a probable human carcinogen.

    Science.gov (United States)

    Tarone, Robert E

    2018-01-01

    The recent classification by International Agency for Research on Cancer (IARC) of the herbicide glyphosate as a probable human carcinogen has generated considerable discussion. The classification is at variance with evaluations of the carcinogenic potential of glyphosate by several national and international regulatory bodies. The basis for the IARC classification is examined under the assumptions that the IARC criteria are reasonable and that the body of scientific studies determined by IARC staff to be relevant to the evaluation of glyphosate by the Monograph Working Group is sufficiently complete. It is shown that the classification of glyphosate as a probable human carcinogen was the result of a flawed and incomplete summary of the experimental evidence evaluated by the Working Group. Rational and effective cancer prevention activities depend on scientifically sound and unbiased assessments of the carcinogenic potential of suspected agents. Implications of the erroneous classification of glyphosate with respect to the IARC Monograph Working Group deliberative process are discussed.

  2. Identifying colon cancer risk modules with better classification performance based on human signaling network.

    Science.gov (United States)

    Qu, Xiaoli; Xie, Ruiqiang; Chen, Lina; Feng, Chenchen; Zhou, Yanyan; Li, Wan; Huang, Hao; Jia, Xu; Lv, Junjie; He, Yuehan; Du, Youwen; Li, Weiguo; Shi, Yuchen; He, Weiming

    2014-10-01

    Identifying differences between normal and tumor samples from a modular perspective may help to improve our understanding of the mechanisms responsible for colon cancer. Many cancer studies have shown that signaling transduction and biological pathways are disturbed in disease states, and expression profiles can distinguish variations in diseases. In this study, we integrated a weighted human signaling network and gene expression profiles to select risk modules associated with tumor conditions. Risk modules as classification features by our method had a better classification performance than other methods, and one risk module for colon cancer had a good classification performance for distinguishing between normal/tumor samples and between tumor stages. All genes in the module were annotated to the biological process of positive regulation of cell proliferation, and were highly associated with colon cancer. These results suggested that these genes might be the potential risk genes for colon cancer. Copyright © 2013. Published by Elsevier Inc.

  3. Classification of human cancers based on DNA copy number amplification modeling

    Directory of Open Access Journals (Sweden)

    Knuutila Sakari

    2008-05-01

    Full Text Available Abstract Background DNA amplifications alter gene dosage in cancer genomes by multiplying the gene copy number. Amplifications are quintessential in a considerable number of advanced cancers of various anatomical locations. The aims of this study were to classify human cancers based on their amplification patterns, explore the biological and clinical fundamentals behind their amplification-pattern based classification, and understand the characteristics in human genomic architecture that associate with amplification mechanisms. Methods We applied a machine learning approach to model DNA copy number amplifications using a data set of binary amplification records at chromosome sub-band resolution from 4400 cases that represent 82 cancer types. Amplification data was fused with background data: clinical, histological and biological classifications, and cytogenetic annotations. Statistical hypothesis testing was used to mine associations between the data sets. Results Probabilistic clustering of each chromosome identified 111 amplification models and divided the cancer cases into clusters. The distribution of classification terms in the amplification-model based clustering of cancer cases revealed cancer classes that were associated with specific DNA copy number amplification models. Amplification patterns – finite or bounded descriptions of the ranges of the amplifications in the chromosome – were extracted from the clustered data and expressed according to the original cytogenetic nomenclature. This was achieved by maximal frequent itemset mining using the cluster-specific data sets. The boundaries of amplification patterns were shown to be enriched with fragile sites, telomeres, centromeres, and light chromosome bands. Conclusions Our results demonstrate that amplifications are non-random chromosomal changes and specifically selected in tumor tissue microenvironment. Furthermore, statistical evidence showed that specific chromosomal features

  4. Visualization and tissue classification of human breast cancer images using ultrahigh-resolution OCT (Conference Presentation)

    Science.gov (United States)

    Yao, Xinwen; Gan, Yu; Chang, Ernest W.; Hibshoosh, Hanina; Feldman, Sheldon; Hendon, Christine P.

    2017-02-01

    We employed a home-built ultrahigh resolution (UHR) OCT system at 800nm to image human breast cancer sample ex vivo. The system has an axial resolution of 2.72µm and a lateral resolution of 5.52µm with an extended imaging range of 1.78mm. Over 900 UHR OCT volumes were generated on specimens from 23 breast cancer cases. With better spatial resolution, detailed structures in the breast tissue were better defined. Different types of breast cancer as well as healthy breast tissue can be well delineated from the UHR OCT images. To quantitatively evaluate the advantages of UHR OCT imaging of breast cancer, features derived from OCT intensity images were used as inputs to a machine learning model, the relevance vector machine. A trained machine learning model was employed to evaluate the performance of tissue classification based on UHR OCT images for differentiating tissue types in the breast samples, including adipose tissue, healthy stroma and cancerous region. For adipose tissue, grid-based local features were extracted from OCT intensity data, including standard deviation, entropy, and homogeneity. We showed that it was possible to enhance the classification performance on distinguishing fat tissue from non-fat tissue by using the UHR images when compared with the results based on OCT images from a commercial 1300 nm OCT system. For invasive ductal carcinoma (IDC) and normal stroma differentiation, the classification was based on frame-based features that portray signal penetration depth and tissue reflectivity. The confusing matrix indicated a sensitivity of 97.5% and a sensitivity of 77.8%.

  5. Fluorescently labeled bevacizumab in human breast cancer: defining the classification threshold

    Science.gov (United States)

    Koch, Maximilian; de Jong, Johannes S.; Glatz, Jürgen; Symvoulidis, Panagiotis; Lamberts, Laetitia E.; Adams, Arthur L. L.; Kranendonk, Mariëtte E. G.; Terwisscha van Scheltinga, Anton G. T.; Aichler, Michaela; Jansen, Liesbeth; de Vries, Jakob; Lub-de Hooge, Marjolijn N.; Schröder, Carolien P.; Jorritsma-Smit, Annelies; Linssen, Matthijs D.; de Boer, Esther; van der Vegt, Bert; Nagengast, Wouter B.; Elias, Sjoerd G.; Oliveira, Sabrina; Witkamp, Arjen J.; Mali, Willem P. Th. M.; Van der Wall, Elsken; Garcia-Allende, P. Beatriz; van Diest, Paul J.; de Vries, Elisabeth G. E.; Walch, Axel; van Dam, Gooitzen M.; Ntziachristos, Vasilis

    2017-07-01

    In-vivo fluorescently labelled drug (bevacizumab) breast cancer specimen where obtained from patients. We propose a new structured method to determine the optimal classification threshold in targeted fluorescence intra-operative imaging.

  6. Mimicking human texture classification

    NARCIS (Netherlands)

    Rogowitz, B.E.; van Rikxoort, Eva M.; van den Broek, Egon; Pappas, T.N.; Schouten, Theo E.; Daly, S.J.

    2005-01-01

    In an attempt to mimic human (colorful) texture classification by a clustering algorithm three lines of research have been encountered, in which as test set 180 texture images (both their color and gray-scale equivalent) were drawn from the OuTex and VisTex databases. First, a k-means algorithm was

  7. Clinical classification of cancer cachexia: phenotypic correlates in human skeletal muscle.

    Directory of Open Access Journals (Sweden)

    Neil Johns

    Full Text Available BACKGROUND: Cachexia affects the majority of patients with advanced cancer and is associated with a reduction in treatment tolerance, response to therapy, and duration of survival. One impediment towards the effective treatment of cachexia is a validated classification system. METHODS: 41 patients with resectable upper gastrointestinal (GI or pancreatic cancer underwent characterisation for cachexia based on weight-loss (WL and/or low muscularity (LM. Four diagnostic criteria were used >5%WL, >10%WL, LM, and LM+>2%WL. All patients underwent biopsy of the rectus muscle. Analysis included immunohistochemistry for fibre size and type, protein and nucleic acid concentration, Western blots for markers of autophagy, SMAD signalling, and inflammation. FINDINGS: Compared with non-cachectic cancer patients, patients with LM or LM+>2%WL, mean muscle fibre diameter was reduced by about 25% (p = 0.02 and p = 0.001 respectively. No significant difference in fibre diameter was observed if patients had WL alone. Regardless of classification, there was no difference in fibre number or proportion of fibre type across all myosin heavy chain isoforms. Mean muscle protein content was reduced and the ratio of RNA/DNA decreased in patients with either >5%WL or LM+>2%WL. Compared with non-cachectic patients, SMAD3 protein levels were increased in patients with >5%WL (p = 0.022 and with >10%WL, beclin (p = 0.05 and ATG5 (p = 0.01 protein levels were increased. There were no differences in phospho-NFkB or phospho-STAT3 levels across any of the groups. CONCLUSION: Muscle fibre size, biochemical composition and pathway phenotype can vary according to whether the diagnostic criteria for cachexia are based on weight loss alone, a measure of low muscularity alone or a combination of the two. For intervention trials where the primary end-point is a change in muscle mass or function, use of combined diagnostic criteria may allow identification of a more

  8. A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Jessica Roelands

    2018-02-01

    Full Text Available The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB. In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list.

  9. Proteomic classification of breast cancer.

    LENUS (Irish Health Repository)

    Kamel, Dalia

    2012-11-01

    Being a significant health problem that affects patients in various age groups, breast cancer has been extensively studied to date. Recently, molecular breast cancer classification has advanced significantly with the availability of genomic profiling technologies. Proteomic technologies have also advanced from traditional protein assays including enzyme-linked immunosorbent assay, immunoblotting and immunohistochemistry to more comprehensive approaches including mass spectrometry and reverse phase protein lysate arrays (RPPA). The purpose of this manuscript is to review the current protein markers that influence breast cancer prediction and prognosis and to focus on novel advances in proteomic classification of breast cancer.

  10. Gastric cancer: epidemiology, prevention, classification, and treatment

    Directory of Open Access Journals (Sweden)

    Sitarz R

    2018-02-01

    Full Text Available Robert Sitarz,1–3 Małgorzata Skierucha,1,2 Jerzy Mielko,1 G Johan A Offerhaus,3 Ryszard Maciejewski,2 Wojciech P Polkowski1 1Department of Surgical Oncology, Medical University of Lublin, Lublin, Poland; 2Department of Human Anatomy, Medical University of Lublin, Lublin, Poland; 3Department of Pathology, University Medical Centre, Utrecht, The Netherlands Abstract: Gastric cancer is the second most common cause of cancer-related deaths in the world, the epidemiology of which has changed within last decades. A trend of steady decline in gastric cancer incidence rates is the effect of the increased standards of hygiene, conscious nutrition, and Helicobacter pylori eradication, which together constitute primary prevention. Avoidance of gastric cancer remains a priority. However, patients with higher risk should be screened for early detection and chemoprevention. Surgical resection enhanced by standardized lymphadenectomy remains the gold standard in gastric cancer therapy. This review briefly summarizes the most important aspects of gastric cancers, which include epidemiology, risk factors, classification, diagnosis, prevention, and treatment. The paper is mostly addressed to physicians who are interested in updating the state of art concerning gastric carcinoma from easily accessible and credible source. Keywords: gastric cancer, epidemiology, classification, risk factors, treatment

  11. Cancer classification in the genomic era: five contemporary problems.

    Science.gov (United States)

    Song, Qingxuan; Merajver, Sofia D; Li, Jun Z

    2015-10-19

    Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here, we discuss the classification of cancer and the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., "lung cancer" designates a tumor originating in lung structures. Within each organ-specific major type, finer subgroups can be defined based on patient age, cell type, histological grades, and sometimes molecular markers, e.g., hormonal receptor status in breast cancer or microsatellite instability in colorectal cancer. In the past 15+ years, high-throughput technologies have generated rich new data regarding somatic variations in DNA, RNA, protein, or epigenomic features for many cancers. These data, collected for increasingly large tumor cohorts, have provided not only new insights into the biological diversity of human cancers but also exciting opportunities to discover previously unrecognized cancer subtypes. Meanwhile, the unprecedented volume and complexity of these data pose significant challenges for biostatisticians, cancer biologists, and clinicians alike. Here, we review five related issues that represent contemporary problems in cancer taxonomy and interpretation. (1) How many cancer subtypes are there? (2) How can we evaluate the robustness of a new classification system? (3) How are classification systems affected by intratumor heterogeneity and tumor evolution? (4) How should we interpret cancer subtypes? (5) Can multiple classification systems co-exist? While related issues have existed for a long time, we will focus on those aspects that have been magnified by the recent influx of complex multi-omics data. Exploration of these problems is essential for data-driven refinement of cancer classification

  12. Molecular Classification and Correlates in Colorectal Cancer

    OpenAIRE

    Ogino, Shuji; Goel, Ajay

    2008-01-01

    Molecular classification of colorectal cancer is evolving. As our understanding of colorectal carcinogenesis improves, we are incorporating new knowledge into the classification system. In particular, global genomic status [microsatellite instability (MSI) status and chromosomal instability (CIN) status] and epigenomic status [CpG island methylator phenotype (CIMP) status] play a significant role in determining clinical, pathological and biological characteristics of colorectal cancer. In thi...

  13. Novelty detection for breast cancer image classification

    Science.gov (United States)

    Cichosz, Pawel; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał; Oleszkiewicz, Witold

    2016-09-01

    Using classification learning algorithms for medical applications may require not only refined model creation techniques and careful unbiased model evaluation, but also detecting the risk of misclassification at the time of model application. This is addressed by novelty detection, which identifies instances for which the training set is not sufficiently representative and for which it may be safer to restrain from classification and request a human expert diagnosis. The paper investigates two techniques for isolated instance identification, based on clustering and one-class support vector machines, which represent two different approaches to multidimensional outlier detection. The prediction quality for isolated instances in breast cancer image data is evaluated using the random forest algorithm and found to be substantially inferior to the prediction quality for non-isolated instances. Each of the two techniques is then used to create a novelty detection model which can be combined with a classification model and used at the time of prediction to detect instances for which the latter cannot be reliably applied. Novelty detection is demonstrated to improve random forest prediction quality and argued to deserve further investigation in medical applications.

  14. IDM-PhyChm-Ens: intelligent decision-making ensemble methodology for classification of human breast cancer using physicochemical properties of amino acids.

    Science.gov (United States)

    Ali, Safdar; Majid, Abdul; Khan, Asifullah

    2014-04-01

    Development of an accurate and reliable intelligent decision-making method for the construction of cancer diagnosis system is one of the fast growing research areas of health sciences. Such decision-making system can provide adequate information for cancer diagnosis and drug discovery. Descriptors derived from physicochemical properties of protein sequences are very useful for classifying cancerous proteins. Recently, several interesting research studies have been reported on breast cancer classification. To this end, we propose the exploitation of the physicochemical properties of amino acids in protein primary sequences such as hydrophobicity (Hd) and hydrophilicity (Hb) for breast cancer classification. Hd and Hb properties of amino acids, in recent literature, are reported to be quite effective in characterizing the constituent amino acids and are used to study protein foldings, interactions, structures, and sequence-order effects. Especially, using these physicochemical properties, we observed that proline, serine, tyrosine, cysteine, arginine, and asparagine amino acids offer high discrimination between cancerous and healthy proteins. In addition, unlike traditional ensemble classification approaches, the proposed 'IDM-PhyChm-Ens' method was developed by combining the decision spaces of a specific classifier trained on different feature spaces. The different feature spaces used were amino acid composition, split amino acid composition, and pseudo amino acid composition. Consequently, we have exploited different feature spaces using Hd and Hb properties of amino acids to develop an accurate method for classification of cancerous protein sequences. We developed ensemble classifiers using diverse learning algorithms such as random forest (RF), support vector machines (SVM), and K-nearest neighbor (KNN) trained on different feature spaces. We observed that ensemble-RF, in case of cancer classification, performed better than ensemble-SVM and ensemble-KNN. Our

  15. The classification of secondary colorectal liver cancer in human biopsy samples using angular dispersive x-ray diffraction and multivariate analysis

    International Nuclear Information System (INIS)

    Theodorakou, Chrysoula; Farquharson, Michael J

    2009-01-01

    The motivation behind this study is to assess whether angular dispersive x-ray diffraction (ADXRD) data, processed using multivariate analysis techniques, can be used for classifying secondary colorectal liver cancer tissue and normal surrounding liver tissue in human liver biopsy samples. The ADXRD profiles from a total of 60 samples of normal liver tissue and colorectal liver metastases were measured using a synchrotron radiation source. The data were analysed for 56 samples using nonlinear peak-fitting software. Four peaks were fitted to all of the ADXRD profiles, and the amplitude, area, amplitude and area ratios for three of the four peaks were calculated and used for the statistical and multivariate analysis. The statistical analysis showed that there are significant differences between all the peak-fitting parameters and ratios between the normal and the diseased tissue groups. The technique of soft independent modelling of class analogy (SIMCA) was used to classify normal liver tissue and colorectal liver metastases resulting in 67% of the normal tissue samples and 60% of the secondary colorectal liver tissue samples being classified correctly. This study has shown that the ADXRD data of normal and secondary colorectal liver cancer are statistically different and x-ray diffraction data analysed using multivariate analysis have the potential to be used as a method of tissue classification.

  16. Cancer classification using the Immunoscore: a worldwide task force.

    Science.gov (United States)

    Galon, Jérôme; Pagès, Franck; Marincola, Francesco M; Angell, Helen K; Thurin, Magdalena; Lugli, Alessandro; Zlobec, Inti; Berger, Anne; Bifulco, Carlo; Botti, Gerardo; Tatangelo, Fabiana; Britten, Cedrik M; Kreiter, Sebastian; Chouchane, Lotfi; Delrio, Paolo; Arndt, Hartmann; Asslaber, Martin; Maio, Michele; Masucci, Giuseppe V; Mihm, Martin; Vidal-Vanaclocha, Fernando; Allison, James P; Gnjatic, Sacha; Hakansson, Leif; Huber, Christoph; Singh-Jasuja, Harpreet; Ottensmeier, Christian; Zwierzina, Heinz; Laghi, Luigi; Grizzi, Fabio; Ohashi, Pamela S; Shaw, Patricia A; Clarke, Blaise A; Wouters, Bradly G; Kawakami, Yutaka; Hazama, Shoichi; Okuno, Kiyotaka; Wang, Ena; O'Donnell-Tormey, Jill; Lagorce, Christine; Pawelec, Graham; Nishimura, Michael I; Hawkins, Robert; Lapointe, Réjean; Lundqvist, Andreas; Khleif, Samir N; Ogino, Shuji; Gibbs, Peter; Waring, Paul; Sato, Noriyuki; Torigoe, Toshihiko; Itoh, Kyogo; Patel, Prabhu S; Shukla, Shilin N; Palmqvist, Richard; Nagtegaal, Iris D; Wang, Yili; D'Arrigo, Corrado; Kopetz, Scott; Sinicrope, Frank A; Trinchieri, Giorgio; Gajewski, Thomas F; Ascierto, Paolo A; Fox, Bernard A

    2012-10-03

    Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J

  17. Pathological Bases for a Robust Application of Cancer Molecular Classification

    Directory of Open Access Journals (Sweden)

    Salvador J. Diaz-Cano

    2015-04-01

    Full Text Available Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classification of human cancer must refer to the current gold standard (histological classification and try to improve it with key prognosticators for metastatic potential, staging and grading. Although organ-specific examples have been published based on proteomics, transcriptomics and genomics evaluations, the most popular approach uses gene expression analysis as a direct correlate of cellular differentiation, which represents the key feature of the histological classification. RNA is a labile molecule that varies significantly according with the preservation protocol, its transcription reflect the adaptation of the tumor cells to the microenvironment, it can be passed through mechanisms of intercellular transference of genetic information (exosomes, and it is exposed to epigenetic modifications. More robust classifications should be based on stable molecules, at the genetic level represented by DNA to improve reliability, and its analysis must deal with the concept of intratumoral heterogeneity, which is at the origin of tumor progression and is the byproduct of the selection process during the clonal expansion and progression of neoplasms. The simultaneous analysis of multiple DNA targets and next generation sequencing offer the best practical approach for an analytical genomic classification of tumors.

  18. Human gender classification: a review

    NARCIS (Netherlands)

    Lin, F.; Wu, Y.; Zhuang, Y.; Long, X.; Xu, W.

    2016-01-01

    The gender recognition is essential and critical for many applications in the commercial domains such as applications of human-computer interaction and computer-aided physiological or psychological analysis, since it contains a wide range of information regarding the characteristics difference

  19. EPA`s program for risk assessment guidelines: Cancer classification issues

    Energy Technology Data Exchange (ETDEWEB)

    Wiltse, J. [Environmental Protection Agency, Washington, DC (United States)

    1990-12-31

    Issues presented are related to classification of weight of evidence in cancer risk assessments. The focus in this paper is on lines of evidence used in constructing a conclusion about potential human carcinogenicity. The paper also discusses issues that are mistakenly addressed as classification issues but are really part of the risk assessment process. 2 figs.

  20. Cancer classification using the Immunoscore: a worldwide task force

    Directory of Open Access Journals (Sweden)

    Galon Jérôme

    2012-10-01

    Full Text Available Abstract Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification summarizes data on tumor burden (T, presence of cancer cells in draining and regional lymph nodes (N and evidence for metastases (M. However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the ‘Immunoscore’ into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of

  1. Lauren classification and individualized chemotherapy in gastric cancer

    OpenAIRE

    MA, JUNLI; SHEN, HONG; KAPESA, LINDA; ZENG, SHAN

    2016-01-01

    Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histol...

  2. Gastric cancer: epidemiology, prevention, classification, and treatment

    OpenAIRE

    Sitarz, Robert; Skierucha, Małgorzata; Mielko, Jerzy; Offerhaus, G Johan A; Maciejewski, Ryszard; Polkowski, Wojciech P

    2018-01-01

    Robert Sitarz,1–3 Małgorzata Skierucha,1,2 Jerzy Mielko,1 G Johan A Offerhaus,3 Ryszard Maciejewski,2 Wojciech P Polkowski1 1Department of Surgical Oncology, Medical University of Lublin, Lublin, Poland; 2Department of Human Anatomy, Medical University of Lublin, Lublin, Poland; 3Department of Pathology, University Medical Centre, Utrecht, The Netherlands Abstract: Gastric cancer is the second most common cause of cancer-related deaths in the world, the epidemiology of which has ch...

  3. Lauren classification and individualized chemotherapy in gastric cancer.

    Science.gov (United States)

    Ma, Junli; Shen, Hong; Kapesa, Linda; Zeng, Shan

    2016-05-01

    Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histological subtypes of gastric cancer proposed by the Lauren classification exhibit a number of distinct clinical and molecular characteristics, including histogenesis, cell differentiation, epidemiology, etiology, carcinogenesis, biological behaviors and prognosis. Gastric cancer exhibits varied sensitivity to chemotherapy drugs and significant heterogeneity; therefore, the disease may be a target for individualized therapy. The Lauren classification may provide the basis for individualized treatment for advanced gastric cancer, which is increasingly gaining attention in the scientific field. However, few studies have investigated individualized treatment that is guided by pathological classification. The aim of the current review is to analyze the two major histological subtypes of gastric cancer, as proposed by the Lauren classification, and to discuss the implications of this for personalized chemotherapy.

  4. The classification of osteonecrosis in patients with cancer: validation of a new radiological classification system

    International Nuclear Information System (INIS)

    Niinimäki, T.; Niinimäki, J.; Halonen, J.; Hänninen, P.; Harila-Saari, A.; Niinimäki, R.

    2015-01-01

    Aim: To validate a new, non-joint-specific radiological classification system that is suitable regardless of the site of the osteonecrosis (ON) in patients with cancer. Material and methods: Critical deficiencies in the existing ON classification systems were identified and a new, non-joint-specific radiological classification system was developed. Seventy-two magnetic resonance imaging (MRI) images of patients with cancer and ON lesions were graded, and the validation of the new system was performed by assessing inter- and intra-observer reliability. Results: Intra-observer reliability of ON grading was good or very good, with kappa values of 0.79–0.86. Interobserver agreement was lower but still good, with kappa values of 0.62–0.77. Ninety-eight percent of all intra- or interobserver differences were within one grade. Interobserver reliability of assessing the location of ON was very good, with kappa values of 0.93–0.98. Conclusion: All the available radiological ON classification systems are joint specific. This limitation has spurred the development of multiple systems, which has led to the insufficient use of classifications in ON studies among patients with cancer. The introduced radiological classification system overcomes the problem of joint-specificity, was found to be reliable, and can be used to classify all ON lesions regardless of the affected site. - Highlights: • Patients with cancer may have osteonecrosis lesions at multiple sites. • There is no non-joint-specific osteonecrosis classification available. • We introduced a new non-joint-specific osteonecrosis classification. • The validation was performed by assessing inter- and intra-observer reliability. • The classification was reliable and could be used regardless of the affected site.

  5. Human Breast Cancer Histoid

    Science.gov (United States)

    Kaur, Pavinder; Ward, Brenda; Saha, Baisakhi; Young, Lillian; Groshen, Susan; Techy, Geza; Lu, Yani; Atkinson, Roscoe; Taylor, Clive R.; Ingram, Marylou

    2011-01-01

    Progress in our understanding of heterotypic cellular interaction in the tumor microenvironment, which is recognized to play major roles in cancer progression, has been hampered due to unavailability of an appropriate in vitro co-culture model. The aim of this study was to generate an in vitro 3-dimensional human breast cancer model, which consists of cancer cells and fibroblasts. Breast cancer cells (UACC-893) and fibroblasts at various densities were co-cultured in a rotating suspension culture system to establish co-culture parameters. Subsequently, UACC-893, BT.20, or MDA.MB.453 were co-cultured with fibroblasts for 9 days. Co-cultures resulted in the generation of breast cancer histoid (BCH) with cancer cells showing the invasion of fibroblast spheroids, which were visualized by immunohistochemical (IHC) staining of sections (4 µm thick) of BCH. A reproducible quantitative expression of C-erbB.2 was detected in UACC-893 cancer cells in BCH sections by IHC staining and the Automated Cellular Imaging System. BCH sections also consistently exhibited qualitative expression of pancytokeratins, p53, Ki-67, or E-cadherin in cancer cells and that of vimentin or GSTPi in fibroblasts, fibronectin in the basement membrane and collagen IV in the extracellular matrix. The expression of the protein analytes and cellular architecture of BCH were markedly similar to those of breast cancer tissue. PMID:22034518

  6. NIM: A Node Influence Based Method for Cancer Classification

    Directory of Open Access Journals (Sweden)

    Yiwen Wang

    2014-01-01

    Full Text Available The classification of different cancer types owns great significance in the medical field. However, the great majority of existing cancer classification methods are clinical-based and have relatively weak diagnostic ability. With the rapid development of gene expression technology, it is able to classify different kinds of cancers using DNA microarray. Our main idea is to confront the problem of cancer classification using gene expression data from a graph-based view. Based on a new node influence model we proposed, this paper presents a novel high accuracy method for cancer classification, which is composed of four parts: the first is to calculate the similarity matrix of all samples, the second is to compute the node influence of training samples, the third is to obtain the similarity between every test sample and each class using weighted sum of node influence and similarity matrix, and the last is to classify each test sample based on its similarity between every class. The data sets used in our experiments are breast cancer, central nervous system, colon tumor, prostate cancer, acute lymphoblastic leukemia, and lung cancer. experimental results showed that our node influence based method (NIM is more efficient and robust than the support vector machine, K-nearest neighbor, C4.5, naive Bayes, and CART.

  7. A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs.

    Science.gov (United States)

    Li, Feifei; Piao, Minghao; Piao, Yongjun; Li, Meijing; Ryu, Keun Ho

    2014-10-01

    Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification.

  8. A Classification Framework Applied to Cancer Gene Expression Profiles

    Directory of Open Access Journals (Sweden)

    Hussein Hijazi

    2013-01-01

    Full Text Available Classification of cancer based on gene expression has provided insight into possible treatment strategies. Thus, developing machine learning methods that can successfully distinguish among cancer subtypes or normal versus cancer samples is important. This work discusses supervised learning techniques that have been employed to classify cancers. Furthermore, a two-step feature selection method based on an attribute estimation method (e.g., ReliefF and a genetic algorithm was employed to find a set of genes that can best differentiate between cancer subtypes or normal versus cancer samples. The application of different classification methods (e.g., decision tree, k-nearest neighbor, support vector machine (SVM, bagging, and random forest on 5 cancer datasets shows that no classification method universally outperforms all the others. However, k-nearest neighbor and linear SVM generally improve the classification performance over other classifiers. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and gene expression increase the prediction accuracy as compared to using gene expression alone.

  9. Magnetic resonance imaging texture analysis classification of primary breast cancer

    International Nuclear Information System (INIS)

    Waugh, S.A.; Lerski, R.A.; Purdie, C.A.; Jordan, L.B.; Vinnicombe, S.; Martin, P.; Thompson, A.M.

    2016-01-01

    Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

  10. Magnetic resonance imaging texture analysis classification of primary breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Waugh, S.A.; Lerski, R.A. [Ninewells Hospital and Medical School, Department of Medical Physics, Dundee (United Kingdom); Purdie, C.A.; Jordan, L.B. [Ninewells Hospital and Medical School, Department of Pathology, Dundee (United Kingdom); Vinnicombe, S. [University of Dundee, Division of Imaging and Technology, Ninewells Hospital and Medical School, Dundee (United Kingdom); Martin, P. [Ninewells Hospital and Medical School, Department of Clinical Radiology, Dundee (United Kingdom); Thompson, A.M. [University of Texas MD Anderson Cancer Center, Department of Surgical Oncology, Houston, TX (United States)

    2016-02-15

    Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

  11. Human papillomaviruses and cancer

    International Nuclear Information System (INIS)

    Haedicke, Juliane; Iftner, Thomas

    2013-01-01

    Human papillomaviruses (HPV) are small oncogenic DNA viruses of which more than 200 types have been identified to date. A small subset of these is etiologically linked to the development of anogenital malignancies such as cervical cancer. In addition, recent studies established a causative relationship between these high-risk HPV types and tonsillar and oropharyngeal cancer. Clinical management of cervical cancer and head and neck squamous cell carcinomas (HNSCCs) is largely standardized and involves surgical removal of the tumor tissue as well as adjuvant chemoradiation therapy. Notably, the response to therapeutic intervention of HPV-positive HNSCCs has been found to be better as compared to HPV-negative tumors. Although the existing HPV vaccine is solely licensed for the prevention of cervical cancer, it might also have prophylactic potential for the development of high-risk HPV-associated HNSCCs. Another group of viruses, which belongs to the beta-HPV subgroup, has been implicated in nonmelanoma skin cancer, however, the etiology remains to be established. Treatment of HPV-induced nonmelanoma skin cancer is based on local excision. However, topically applied immune-modulating substances represent non-surgical alternatives for the management of smaller cutaneous tumors. In this review we present the current knowledge of the role of HPV in cancer development and discuss clinical management options as well as targets for the development of future intervention therapies

  12. Influence of nuclei segmentation on breast cancer malignancy classification

    Science.gov (United States)

    Jelen, Lukasz; Fevens, Thomas; Krzyzak, Adam

    2009-02-01

    Breast Cancer is one of the most deadly cancers affecting middle-aged women. Accurate diagnosis and prognosis are crucial to reduce the high death rate. Nowadays there are numerous diagnostic tools for breast cancer diagnosis. In this paper we discuss a role of nuclear segmentation from fine needle aspiration biopsy (FNA) slides and its influence on malignancy classification. Classification of malignancy plays a very important role during the diagnosis process of breast cancer. Out of all cancer diagnostic tools, FNA slides provide the most valuable information about the cancer malignancy grade which helps to choose an appropriate treatment. This process involves assessing numerous nuclear features and therefore precise segmentation of nuclei is very important. In this work we compare three powerful segmentation approaches and test their impact on the classification of breast cancer malignancy. The studied approaches involve level set segmentation, fuzzy c-means segmentation and textural segmentation based on co-occurrence matrix. Segmented nuclei were used to extract nuclear features for malignancy classification. For classification purposes four different classifiers were trained and tested with previously extracted features. The compared classifiers are Multilayer Perceptron (MLP), Self-Organizing Maps (SOM), Principal Component-based Neural Network (PCA) and Support Vector Machines (SVM). The presented results show that level set segmentation yields the best results over the three compared approaches and leads to a good feature extraction with a lowest average error rate of 6.51% over four different classifiers. The best performance was recorded for multilayer perceptron with an error rate of 3.07% using fuzzy c-means segmentation.

  13. Classification system for reporting events involving human malfunctions

    International Nuclear Information System (INIS)

    Rasmussen, J.; Pedersen, O.M.; Mancini, G.

    1981-01-01

    The report describes a set of categories for reporting industrial incidents and events involving human malfunction. The classification system aims at ensuring information adequate for improvement of human work situations and man-machine interface systems and for attempts to quantify ''human error'' rates. The classification system has a multifacetted non-hierarchical structure and its compatibility with Ispra's ERDS classification is described. The collection of the information in general and for quantification purposes are discussed. 24 categories, 12 of which being human factors-oriented, are listed with their respective subcategories, and comments are given. Underlying models of human data process and their typical malfuntions and of a human decision sequence are described. The work reported is a joint contribution to the CSNI Group of Experts on Human Error Data and Assessment

  14. Classification system for reporting events involving human malfunctions

    International Nuclear Information System (INIS)

    Rasmussen, J.; Pedersen, O.M.; Mancini, G.; Carnino, A.; Griffon, M.; Gagnolet, P.

    1981-03-01

    The report describes a set of categories for reporting industrial incidents and events involving human malfunction. The classification system aims at ensuring information adequate for improvement of human work situations and man-machine interface systems and for attempts to quantify ''human error'' rates. The classification system has a multifacetted non-hierarchial structure and its compatibility with Ispra's ERDS classification is described. The collection of the information in general and for quantification purposes are discussed. 24 categories, 12 of which being human factors oriented, are listed with their respective subcategories, and comments are given. Underlying models of human data processes and their typical malfunctions and of a human decision sequence are described. (author)

  15. Classification system for reporting events involving human malfunctions

    DEFF Research Database (Denmark)

    Rasmussen, Jens; Pedersen, O.M.; Mancini, G.

    1981-01-01

    The report describes a set of categories for reporting indus-trial incidents and events involving human malfunction. The classification system aims at ensuring information adequate for improvement of human work situations and man-machine interface systems and for attempts to quantify "human error......" rates. The classification system has a multifacetted non-hierarchical struc-ture and its compatibility with Isprals ERDS classification is described. The collection of the information in general and for quantification purposes are discussed. 24 categories, 12 of which being human factors oriented......, are listed with their respective subcategories, and comments are given. Underlying models of human data processes and their typical malfunc-tions and of a human decision sequence are described....

  16. Bladder cancer: Analysis of the 2004 WHO classification in ...

    African Journals Online (AJOL)

    Objectives: Bladder cancer (BCA) is aworldwide disease and shows a wide range of geographical variation. The aim of this study is to analyze the prevalence of schistosomal and non-schistosomal associated BCA as well as compare our findings with the 2004 WHO consensus classification of urothelial neoplasms and ...

  17. Classification of mitocans, anti-cancer drugs acting on mitochondria

    Czech Academy of Sciences Publication Activity Database

    Neužil, Jiří; Dong, L. F.; Rohlena, Jakub; Truksa, Jaroslav; Ralph, S. J.

    2013-01-01

    Roč. 13, č. 3 (2013), s. 199-208 ISSN 1567-7249 Institutional research plan: CEZ:AV0Z50520701 Keywords : Mitocans * Anti-cancer therapeutics * Classification Subject RIV: EB - Gene tics ; Molecular Biology Impact factor: 3.524, year: 2013

  18. Classification of mitocans, anti-cancer drugs acting on mitochondria

    Czech Academy of Sciences Publication Activity Database

    Neužil, Jiří; Dong, L. F.; Rohlena, Jakub; Truksa, Jaroslav; Ralph, S. J.

    2013-01-01

    Roč. 13, č. 3 (2013), s. 199-208 ISSN 1567-7249 Institutional research plan: CEZ:AV0Z50520701 Keywords : Mitocans * Anti-cancer therapeutics * Classification Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.524, year: 2013

  19. Human papilloma virus in oral cancer.

    Science.gov (United States)

    Kim, Soung Min

    2016-12-01

    Cervical cancer is the second most prevalent cancer among women, and it arises from cells that originate in the cervix uteri. Among several causes of cervical malignancies, infection with some types of human papilloma virus (HPV) is well known to be the greatest cervical cancer risk factor. Over 150 subtypes of HPV have been identified; more than 40 types of HPVs are typically transmitted through sexual contact and infect the anogenital region and oral cavity. The recently introduced vaccine for HPV infection is effective against certain subtypes of HPV that are associated with cervical cancer, genital warts, and some less common cancers, including oropharyngeal cancer. Two HPV vaccines, quadrivalent and bivalent types that use virus-like particles (VLPs), are currently used in the medical commercial market. While the value of HPV vaccination for oral cancer prevention is still controversial, some evidence supports the possibility that HPV vaccination may be effective in reducing the incidence of oral cancer. This paper reviews HPV-related pathogenesis in cancer, covering HPV structure and classification, trends in worldwide applications of HPV vaccines, effectiveness and complications of HPV vaccination, and the relationship of HPV with oral cancer prevalence.

  20. Association between gastric cancer and the Kyoto classification of gastritis.

    Science.gov (United States)

    Shichijo, Satoki; Hirata, Yoshihiro; Niikura, Ryota; Hayakawa, Yoku; Yamada, Atsuo; Koike, Kazuhiko

    2017-09-01

    Histological gastritis is associated with gastric cancer, but its diagnosis requires biopsy. Many classifications of endoscopic gastritis are available, but not all are useful for risk stratification of gastric cancer. The Kyoto Classification of Gastritis was proposed at the 85th Congress of the Japan Gastroenterological Endoscopy Society. This cross-sectional study evaluated the usefulness of the Kyoto Classification of Gastritis for risk stratification of gastric cancer. From August 2013 to September 2014, esophagogastroduodenoscopy was performed and the gastric findings evaluated according to the Kyoto Classification of Gastritis in a total of 4062 patients. The following five endoscopic findings were selected based on previous reports: atrophy, intestinal metaplasia, enlarged folds, nodularity, and diffuse redness. A total of 3392 patients (1746 [51%] men and 1646 [49%] women) were analyzed. Among them, 107 gastric cancers were diagnosed. Atrophy was found in 2585 (78%) and intestinal metaplasia in 924 (27%). Enlarged folds, nodularity, and diffuse redness were found in 197 (5.8%), 22 (0.6%), and 573 (17%), respectively. In univariate analyses, the severity of atrophy, intestinal metaplasia, diffuse redness, age, and male sex were associated with gastric cancer. In a multivariate analysis, atrophy and male sex were found to be independent risk factors. Younger age and severe atrophy were determined to be associated with diffuse-type gastric cancer. Endoscopic detection of atrophy was associated with the risk of gastric cancer. Thus, patients with severe atrophy should be examined carefully and may require intensive follow-up. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  1. Classification of neuropathic pain in cancer patients

    DEFF Research Database (Denmark)

    Brunelli, Cinzia; Bennett, Michael I; Kaasa, Stein

    2014-01-01

    and on the relevance of patient-reported outcome (PRO) descriptors for the screening of NP in this population. An international group of 42 experts was invited to participate in a consensus process through a modified 2-round Internet-based Delphi survey. Relevant topics investigated were: peculiarities of NP...... in patients with cancer, IASP NeuPSIG diagnostic criteria adaptation and assessment, and standardized PRO assessment for NP screening. Median consensus scores (MED) and interquartile ranges (IQR) were calculated to measure expert consensus after both rounds. Twenty-nine experts answered, and good agreement...... was proposed. Clinical research on PRO in the screening phase and on the application of the algorithm will be needed to examine their effectiveness in classifying NP in cancer patients....

  2. Colon cancer associated transcripts in human cancers.

    Science.gov (United States)

    Chen, Yincong; Xie, Haibiao; Gao, Qunjun; Zhan, Hengji; Xiao, Huizhong; Zou, Yifan; Zhang, Fuyou; Liu, Yuchen; Li, Jianfa

    2017-10-01

    Long non-coding RNAs serve as important regulators in complicated cellular activities, including cell differentiation, proliferation and death. Dysregulation of long non-coding RNAs occurs in the formation and progression of cancers. The family of colon cancer associated transcripts, long non-coding RNAs colon cancer associated transcript-1 and colon cancer associated transcript-2 are known as oncogenes involved in various cancers. Colon cancer associated transcript-1 is a novel lncRNA located in 8q24.2, and colon cancer associated transcript-2 maps to the 8q24.21 region encompassing rs6983267. Colon cancer associated transcripts have close associations with clinical characteristics, such as lymph node metastasis, high TNM stage and short overall survival. Knockdown of them can reverse the malignant phenotypes of cancer cells, including proliferation, migration, invasion and apoptosis. Moreover, they can increase the expression level of c-MYC and oncogenic microRNAs via activating a series of complex mechanisms. In brief, the family of colon cancer associated transcripts may serve as potential biomarkers or therapeutic targets for human cancers. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  3. Integrating human and machine intelligence in galaxy morphology classification tasks

    Science.gov (United States)

    Beck, Melanie R.; Scarlata, Claudia; Fortson, Lucy F.; Lintott, Chris J.; Simmons, B. D.; Galloway, Melanie A.; Willett, Kyle W.; Dickinson, Hugh; Masters, Karen L.; Marshall, Philip J.; Wright, Darryl

    2018-06-01

    Quantifying galaxy morphology is a challenging yet scientifically rewarding task. As the scale of data continues to increase with upcoming surveys, traditional classification methods will struggle to handle the load. We present a solution through an integration of visual and automated classifications, preserving the best features of both human and machine. We demonstrate the effectiveness of such a system through a re-analysis of visual galaxy morphology classifications collected during the Galaxy Zoo 2 (GZ2) project. We reprocess the top-level question of the GZ2 decision tree with a Bayesian classification aggregation algorithm dubbed SWAP, originally developed for the Space Warps gravitational lens project. Through a simple binary classification scheme, we increase the classification rate nearly 5-fold classifying 226 124 galaxies in 92 d of GZ2 project time while reproducing labels derived from GZ2 classification data with 95.7 per cent accuracy. We next combine this with a Random Forest machine learning algorithm that learns on a suite of non-parametric morphology indicators widely used for automated morphologies. We develop a decision engine that delegates tasks between human and machine and demonstrate that the combined system provides at least a factor of 8 increase in the classification rate, classifying 210 803 galaxies in just 32 d of GZ2 project time with 93.1 per cent accuracy. As the Random Forest algorithm requires a minimal amount of computational cost, this result has important implications for galaxy morphology identification tasks in the era of Euclid and other large-scale surveys.

  4. Molecular classification of gastric cancer: a new paradigm.

    Science.gov (United States)

    Shah, Manish A; Khanin, Raya; Tang, Laura; Janjigian, Yelena Y; Klimstra, David S; Gerdes, Hans; Kelsen, David P

    2011-05-01

    Gastric cancer may be subdivided into 3 distinct subtypes--proximal, diffuse, and distal gastric cancer--based on histopathologic and anatomic criteria. Each subtype is associated with unique epidemiology. Our aim is to test the hypothesis that these distinct gastric cancer subtypes may also be distinguished by gene expression analysis. Patients with localized gastric adenocarcinoma being screened for a phase II preoperative clinical trial (National Cancer Institute, NCI #5917) underwent endoscopic biopsy for fresh tumor procurement. Four to 6 targeted biopsies of the primary tumor were obtained. Macrodissection was carried out to ensure more than 80% carcinoma in the sample. HG-U133A GeneChip (Affymetrix) was used for cDNA expression analysis, and all arrays were processed and analyzed using the Bioconductor R-package. Between November 2003 and January 2006, 57 patients were screened to identify 36 patients with localized gastric cancer who had adequate RNA for expression analysis. Using supervised analysis, we built a classifier to distinguish the 3 gastric cancer subtypes, successfully classifying each into tightly grouped clusters. Leave-one-out cross-validation error was 0.14, suggesting that more than 85% of samples were classified correctly. Gene set analysis with the false discovery rate set at 0.25 identified several pathways that were differentially regulated when comparing each gastric cancer subtype to adjacent normal stomach. Subtypes of gastric cancer that have epidemiologic and histologic distinctions are also distinguished by gene expression data. These preliminary data suggest a new classification of gastric cancer with implications for improving our understanding of disease biology and identification of unique molecular drivers for each gastric cancer subtype. ©2011 AACR.

  5. Integrating Human and Machine Intelligence in Galaxy Morphology Classification Tasks

    Science.gov (United States)

    Beck, Melanie Renee

    The large flood of data flowing from observatories presents significant challenges to astronomy and cosmology--challenges that will only be magnified by projects currently under development. Growth in both volume and velocity of astrophysics data is accelerating: whereas the Sloan Digital Sky Survey (SDSS) has produced 60 terabytes of data in the last decade, the upcoming Large Synoptic Survey Telescope (LSST) plans to register 30 terabytes per night starting in the year 2020. Additionally, the Euclid Mission will acquire imaging for 5 x 107 resolvable galaxies. The field of galaxy evolution faces a particularly challenging future as complete understanding often cannot be reached without analysis of detailed morphological galaxy features. Historically, morphological analysis has relied on visual classification by astronomers, accessing the human brains capacity for advanced pattern recognition. However, this accurate but inefficient method falters when confronted with many thousands (or millions) of images. In the SDSS era, efforts to automate morphological classifications of galaxies (e.g., Conselice et al., 2000; Lotz et al., 2004) are reasonably successful and can distinguish between elliptical and disk-dominated galaxies with accuracies of 80%. While this is statistically very useful, a key problem with these methods is that they often cannot say which 80% of their samples are accurate. Furthermore, when confronted with the more complex task of identifying key substructure within galaxies, automated classification algorithms begin to fail. The Galaxy Zoo project uses a highly innovative approach to solving the scalability problem of visual classification. Displaying images of SDSS galaxies to volunteers via a simple and engaging web interface, www.galaxyzoo.org asks people to classify images by eye. Within the first year hundreds of thousands of members of the general public had classified each of the 1 million SDSS galaxies an average of 40 times. Galaxy Zoo

  6. A Preliminary Classification of Human Functional Sexual Disorders

    Science.gov (United States)

    Sharpe, Lawrence; And Others

    1976-01-01

    A preliminary classification is presented for functional human sexual disorders. This system is based on objective behavior and reports of distress. Five categories of sexual disorders are proposed, including the behavioral, psychological and informational components of sexual functioning in the individual and the couple. (Author)

  7. A Classification of Human-to-Human Communication during the Use of Immersive Teleoperation Interfaces

    DEFF Research Database (Denmark)

    Kraus, Martin; Kibsgaard, Martin

    2015-01-01

    We propose a new classification of the human-to-human communication during the use of immersive teleoperation interfaces based on real-life examples. While a large body of research is concerned with communication in collaborative virtual environments (CVEs), less research focuses on cases where...... of the proposed classification to real environments can offer useful reference cases. Using this extended classification not only allows us to discuss and understand differences and similarities of various forms of communication in a more systematic way, but it also provides guidelines and reference cases...... for the design of immersive teleoperation interfaces that support human-to-human communication....

  8. Using fuzzy association rule mining in cancer classification

    International Nuclear Information System (INIS)

    Mahmoodian, Hamid; Marhaban, M.H.; Abdulrahim, Raha; Rosli, Rozita; Saripan, Iqbal

    2011-01-01

    Full text: The classification of the cancer tumors based on gene expression profiles has been extensively studied in numbers of studies. A wide variety of cancer datasets have been implemented by the various methods of gene selec tion and classification to identify the behavior of the genes in tumors and find the relationships between them and outcome of diseases. Interpretability of the model, which is developed by fuzzy rules and linguistic variables in this study, has been rarely considered. In addition, creating a fuzzy classifier with high performance in classification that uses a subset of significant genes which have been selected by different types of gene selection methods is another goal of this study. A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. At first, different subset of genes which have been selected by different methods, were used to generate primary fuzzy classifiers separately and then proposed algorithm was implemented to mix the genes which have been associated in the primary classifiers and generate a new classifier. The results show that fuzzy classifier can classify the tumors with high performance while presenting the relationships between the genes by linguistic variables

  9. [New molecular classification of colorectal cancer, pancreatic cancer and stomach cancer: Towards "à la carte" treatment?].

    Science.gov (United States)

    Dreyer, Chantal; Afchain, Pauline; Trouilloud, Isabelle; André, Thierry

    2016-01-01

    This review reports 3 of recently published molecular classifications of the 3 main gastro-intestinal cancers: gastric, pancreatic and colorectal adenocarcinoma. In colorectal adenocarcinoma, 6 independent classifications were combined to finally hold 4 molecular sub-groups, Consensus Molecular Subtypes (CMS 1-4), linked to various clinical, molecular and survival data. CMS1 (14% MSI with immune activation); CMS2 (37%: canonical with epithelial differentiation and activation of the WNT/MYC pathway); CMS3 (13% metabolic with epithelial differentiation and RAS mutation); CMS4 (23%: mesenchymal with activation of TGFβ pathway and angiogenesis with stromal invasion). In gastric adenocarcinoma, 4 groups were established: subtype "EBV" (9%, high frequency of PIK3CA mutations, hypermetylation and amplification of JAK2, PD-L1 and PD-L2), subtype "MSI" (22%, high rate of mutation), subtype "genomically stable tumor" (20%, diffuse histology type and mutations of RAS and genes encoding integrins and adhesion proteins including CDH1) and subtype "tumors with chromosomal instability" (50%, intestinal type, aneuploidy and receptor tyrosine kinase amplification). In pancreatic adenocarcinomas, a classification in four sub-groups has been proposed, stable subtype (20%, aneuploidy), locally rearranged subtype (30%, focal event on one or two chromosoms), scattered subtype (36%,200 structural variation events, defects in DNA maintenance). Although currently away from the care of patients, these classifications open the way to "à la carte" treatment depending on molecular biology. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

  10. X-ray diagnosis of esophageal cancer and application of Borrmann's classification

    International Nuclear Information System (INIS)

    Chin, Soo Yil

    1985-01-01

    In 126 cases and who were diagnosed as esophageal cancer and treated by radiation at Cancer Research Hospital, K. A. E. R. I., from January 1974 to July 1979, a study on the x-ray diagnosis of esophageal cancer was carried out mainly as to the type classification. The ordinary classification od esophageal cancer by x-ray picture was reviewed and Borrmann's classification using gastric cancer was tried to apply to the macroscopic classification of esophageal cancer, and also the application of this classification to x-ray diagnosis was discussed. And the effect of radiotherapy as to each type of cancer according to the ordinary x-ray classification and Borrmann's classification was studied too. The results were as follows: 1. The ordinary x-ray classification was not simple, because the degree of progression of cancer, difference of mural invasion, and position and method of radiography could make misinterpretation of the type of cancer and the therapeutic effect by radiation as to each type according to this classification did not represent a significant characteristic too, although the radiation was most effective in the polypoidal type and least effective in funnel type. 2. The Borrmann's classification was relatively easy even on the radiogram because of little overlapping between each type and the type became more evident on the resected specimen after operation. And also some correlation was recognized between the type of Borrmann's classification and radiotherapeutic effect. The effect was best in type I and It was gradually decreased in type II, III, and IV in the other. The radiotherapy was ineffective in about three quarters of type IV. 3. The Borrmann's classification is now employed to the carcinoma of large bowel, as well as to the gastric cancer. If it is applied to the esophageal cancer, the macroscopic classification for the cancer of digestive tract can be systemized and it will be convenient in clinical study.

  11. Classification of breast cancer cytological specimen using convolutional neural network

    Science.gov (United States)

    Żejmo, Michał; Kowal, Marek; Korbicz, Józef; Monczak, Roman

    2017-01-01

    The paper presents a deep learning approach for automatic classification of breast tumors based on fine needle cytology. The main aim of the system is to distinguish benign from malignant cases based on microscopic images. Experiment was carried out on cytological samples derived from 50 patients (25 benign cases + 25 malignant cases) diagnosed in Regional Hospital in Zielona Góra. To classify microscopic images, we used convolutional neural networks (CNN) of two types: GoogLeNet and AlexNet. Due to the very large size of images of cytological specimen (on average 200000 × 100000 pixels), they were divided into smaller patches of size 256 × 256 pixels. Breast cancer classification usually is based on morphometric features of nuclei. Therefore, training and validation patches were selected using Support Vector Machine (SVM) so that suitable amount of cell material was depicted. Neural classifiers were tuned using GPU accelerated implementation of gradient descent algorithm. Training error was defined as a cross-entropy classification loss. Classification accuracy was defined as the percentage ratio of successfully classified validation patches to the total number of validation patches. The best accuracy rate of 83% was obtained by GoogLeNet model. We observed that more misclassified patches belong to malignant cases.

  12. Pathohistological classification systems in gastric cancer: diagnostic relevance and prognostic value.

    Science.gov (United States)

    Berlth, Felix; Bollschweiler, Elfriede; Drebber, Uta; Hoelscher, Arnulf H; Moenig, Stefan

    2014-05-21

    Several pathohistological classification systems exist for the diagnosis of gastric cancer. Many studies have investigated the correlation between the pathohistological characteristics in gastric cancer and patient characteristics, disease specific criteria and overall outcome. It is still controversial as to which classification system imparts the most reliable information, and therefore, the choice of system may vary in clinical routine. In addition to the most common classification systems, such as the Laurén and the World Health Organization (WHO) classifications, other authors have tried to characterize and classify gastric cancer based on the microscopic morphology and in reference to the clinical outcome of the patients. In more than 50 years of systematic classification of the pathohistological characteristics of gastric cancer, there is no sole classification system that is consistently used worldwide in diagnostics and research. However, several national guidelines for the treatment of gastric cancer refer to the Laurén or the WHO classifications regarding therapeutic decision-making, which underlines the importance of a reliable classification system for gastric cancer. The latest results from gastric cancer studies indicate that it might be useful to integrate DNA- and RNA-based features of gastric cancer into the classification systems to establish prognostic relevance. This article reviews the diagnostic relevance and the prognostic value of different pathohistological classification systems in gastric cancer.

  13. Side effects of cancer therapies. International classification and documentation systems

    International Nuclear Information System (INIS)

    Seegenschmiedt, M.H.

    1998-01-01

    The publication presents and explains verified, international classification and documentation systems for side effects induced by cancer treatments, applicable in general and clinical practice and clinical research, and covers in a clearly arranged manner the whole range of treatments, including acute and chronic side effects of chemotherapy and radiotherapy, surgery, or combined therapies. The book fills a long-felt need in tumor documentation and is a major contribution to quality assurance in clinical oncology in German-speaking countries. As most parts of the book are bilingual, presenting German and English texts and terminology, it satisfies the principles of interdisciplinarity and internationality. The tabulated form chosen for presentation of classification systems and criteria facilitate the user's approach as well as application in daily work. (orig./CB) [de

  14. Classification of breast cancer histology images using Convolutional Neural Networks.

    Directory of Open Access Journals (Sweden)

    Teresa Araújo

    Full Text Available Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods designed for a specific problem based on field-knowledge. To overcome the many difficulties of the feature-based approaches, deep learning methods are becoming important alternatives. A method for the classification of hematoxylin and eosin stained breast biopsy images using Convolutional Neural Networks (CNNs is proposed. Images are classified in four classes, normal tissue, benign lesion, in situ carcinoma and invasive carcinoma, and in two classes, carcinoma and non-carcinoma. The architecture of the network is designed to retrieve information at different scales, including both nuclei and overall tissue organization. This design allows the extension of the proposed system to whole-slide histology images. The features extracted by the CNN are also used for training a Support Vector Machine classifier. Accuracies of 77.8% for four class and 83.3% for carcinoma/non-carcinoma are achieved. The sensitivity of our method for cancer cases is 95.6%.

  15. Application of machine learning on brain cancer multiclass classification

    Science.gov (United States)

    Panca, V.; Rustam, Z.

    2017-07-01

    Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics of medical data: extremely many features (genes) and only a few number of samples. The application of machine learning on microarray gene expression dataset mainly consists of two steps: feature selection and classification. In this paper, the features are selected using a method based on support vector machine recursive feature elimination (SVM-RFE) principle which is improved to solve multiclass classification, called multiple multiclass SVM-RFE. Instead of using only the selected features on a single classifier, this method combines the result of multiple classifiers. The features are divided into subsets and SVM-RFE is used on each subset. Then, the selected features on each subset are put on separate classifiers. This method enhances the feature selection ability of each single SVM-RFE. Twin support vector machine (TWSVM) is used as the method of the classifier to reduce computational complexity. While ordinary SVM finds single optimum hyperplane, the main objective Twin SVM is to find two non-parallel optimum hyperplanes. The experiment on the brain cancer microarray gene expression dataset shows this method could classify 71,4% of the overall test data correctly, using 100 and 1000 genes selected from multiple multiclass SVM-RFE feature selection method. Furthermore, the per class results show that this method could classify data of normal and MD class with 100% accuracy.

  16. HUMAN PROSTATE CANCER RISK FACTORS

    Science.gov (United States)

    Prostate cancer has the highest prevalence of any non-skin cancer in the human body, with similar likelihood of neoplastic foci found within the prostates of men around the world regardless of diet, occupation, lifestyle, or other factors. Essentially all men with circulating an...

  17. Classification of Cancer-related Death Certificates using Machine Learning

    Directory of Open Access Journals (Sweden)

    Luke Butt

    2013-05-01

    Full Text Available BackgroundCancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities.AimsIn this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated.Method A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes.ResultsDeath certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM classifier achieved best performance with an overall F-measure of 0.9866 when evaluated on a set of 5,000 free-text death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032 and false negative rate (0.0297 while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers.ConclusionThe selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with

  18. A transient search using combined human and machine classifications

    Science.gov (United States)

    Wright, Darryl E.; Lintott, Chris J.; Smartt, Stephen J.; Smith, Ken W.; Fortson, Lucy; Trouille, Laura; Allen, Campbell R.; Beck, Melanie; Bouslog, Mark C.; Boyer, Amy; Chambers, K. C.; Flewelling, Heather; Granger, Will; Magnier, Eugene A.; McMaster, Adam; Miller, Grant R. M.; O'Donnell, James E.; Simmons, Brooke; Spiers, Helen; Tonry, John L.; Veldthuis, Marten; Wainscoat, Richard J.; Waters, Chris; Willman, Mark; Wolfenbarger, Zach; Young, Dave R.

    2017-12-01

    Large modern surveys require efficient review of data in order to find transient sources such as supernovae, and to distinguish such sources from artefacts and noise. Much effort has been put into the development of automatic algorithms, but surveys still rely on human review of targets. This paper presents an integrated system for the identification of supernovae in data from Pan-STARRS1, combining classifications from volunteers participating in a citizen science project with those from a convolutional neural network. The unique aspect of this work is the deployment, in combination, of both human and machine classifications for near real-time discovery in an astronomical project. We show that the combination of the two methods outperforms either one used individually. This result has important implications for the future development of transient searches, especially in the era of Large Synoptic Survey Telescope and other large-throughput surveys.

  19. Human papillomavirus associated oropharyngeal cancer

    International Nuclear Information System (INIS)

    Stefanicka, P.

    2015-01-01

    Recently, there is substantial epidemiological, molecular-pathological and experimental evidence indicating that some of the high-risk human papillomavirus (HR-HPV), especially HPV type 16, are etiologically related to a subset of head and neck squamous cell carcinomas, in particular, those arising from the oropharynx. Incidence of oropharyngeal cancer is increasing in direct opposition to a decreasing incidence of all other head and neck cancers. The prognosis of patients with HPV associated oropharyngeal cancer is significantly better compare to patients with non associated oropharyngeal cancers. Patients with HPV-positive oropharyngeal cancer respond better to radiotherapy, surgery, chemoradiotherapy. Therefore, the presence of HPV in tumor is the most important prognostic factor in patients with oropharyngeal cancers. These findings have prompted the need for change of treatment strategies in these patients. The goal is selective de-intensified treatment stratified for HPV status. (author)

  20. Breast cancer molecular subtype classification using deep features: preliminary results

    Science.gov (United States)

    Zhu, Zhe; Albadawy, Ehab; Saha, Ashirbani; Zhang, Jun; Harowicz, Michael R.; Mazurowski, Maciej A.

    2018-02-01

    Radiogenomics is a field of investigation that attempts to examine the relationship between imaging characteris- tics of cancerous lesions and their genomic composition. This could offer a noninvasive alternative to establishing genomic characteristics of tumors and aid cancer treatment planning. While deep learning has shown its supe- riority in many detection and classification tasks, breast cancer radiogenomic data suffers from a very limited number of training examples, which renders the training of the neural network for this problem directly and with no pretraining a very difficult task. In this study, we investigated an alternative deep learning approach referred to as deep features or off-the-shelf network approach to classify breast cancer molecular subtypes using breast dynamic contrast enhanced MRIs. We used the feature maps of different convolution layers and fully connected layers as features and trained support vector machines using these features for prediction. For the feature maps that have multiple layers, max-pooling was performed along each channel. We focused on distinguishing the Luminal A subtype from other subtypes. To evaluate the models, 10 fold cross-validation was performed and the final AUC was obtained by averaging the performance of all the folds. The highest average AUC obtained was 0.64 (0.95 CI: 0.57-0.71), using the feature maps of the last fully connected layer. This indicates the promise of using this approach to predict the breast cancer molecular subtypes. Since the best performance appears in the last fully connected layer, it also implies that breast cancer molecular subtypes may relate to high level image features

  1. Involvement of Machine Learning for Breast Cancer Image Classification: A Survey

    OpenAIRE

    Nahid, Abdullah-Al; Kong, Yinan

    2017-01-01

    Breast cancer is one of the largest causes of women’s death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors’ and physicians’ time. Despite the various publications on breast image classification, very few review papers are available w...

  2. A dictionary learning approach for human sperm heads classification.

    Science.gov (United States)

    Shaker, Fariba; Monadjemi, S Amirhassan; Alirezaie, Javad; Naghsh-Nilchi, Ahmad Reza

    2017-12-01

    To diagnose infertility in men, semen analysis is conducted in which sperm morphology is one of the factors that are evaluated. Since manual assessment of sperm morphology is time-consuming and subjective, automatic classification methods are being developed. Automatic classification of sperm heads is a complicated task due to the intra-class differences and inter-class similarities of class objects. In this research, a Dictionary Learning (DL) technique is utilized to construct a dictionary of sperm head shapes. This dictionary is used to classify the sperm heads into four different classes. Square patches are extracted from the sperm head images. Columnized patches from each class of sperm are used to learn class-specific dictionaries. The patches from a test image are reconstructed using each class-specific dictionary and the overall reconstruction error for each class is used to select the best matching class. Average accuracy, precision, recall, and F-score are used to evaluate the classification method. The method is evaluated using two publicly available datasets of human sperm head shapes. The proposed DL based method achieved an average accuracy of 92.2% on the HuSHeM dataset, and an average recall of 62% on the SCIAN-MorphoSpermGS dataset. The results show a significant improvement compared to a previously published shape-feature-based method. We have achieved high-performance results. In addition, our proposed approach offers a more balanced classifier in which all four classes are recognized with high precision and recall. In this paper, we use a Dictionary Learning approach in classifying human sperm heads. It is shown that the Dictionary Learning method is far more effective in classifying human sperm heads than classifiers using shape-based features. Also, a dataset of human sperm head shapes is introduced to facilitate future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Gene selection for cancer classification with the help of bees.

    Science.gov (United States)

    Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel

    2016-08-10

    Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnoses. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is believed to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating the concept of pheromones which is one of the major components of Ant Colony Optimization (ACO) algorithm and a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are tuned scientifically with one of the datasets. Obtained results are compared to other works that used the same datasets. The performance of the proposed method is proved to be superior. The method presented in this paper can provide subset of genes leading to more accurate classification results while the number of selected genes is smaller. Additionally, the proposed modified Artificial Bee Colony Algorithm could conceivably be applied to problems in other areas as well.

  4. Human Prostate Cancer Hallmarks Map

    Science.gov (United States)

    Datta, Dipamoy; Aftabuddin, Md.; Gupta, Dinesh Kumar; Raha, Sanghamitra; Sen, Prosenjit

    2016-01-01

    Human prostate cancer is a complex heterogeneous disease that mainly affects elder male population of the western world with a high rate of mortality. Acquisitions of diverse sets of hallmark capabilities along with an aberrant functioning of androgen receptor signaling are the central driving forces behind prostatic tumorigenesis and its transition into metastatic castration resistant disease. These hallmark capabilities arise due to an intense orchestration of several crucial factors, including deregulation of vital cell physiological processes, inactivation of tumor suppressive activity and disruption of prostate gland specific cellular homeostasis. The molecular complexity and redundancy of oncoproteins signaling in prostate cancer demands for concurrent inhibition of multiple hallmark associated pathways. By an extensive manual curation of the published biomedical literature, we have developed Human Prostate Cancer Hallmarks Map (HPCHM), an onco-functional atlas of human prostate cancer associated signaling and events. It explores molecular architecture of prostate cancer signaling at various levels, namely key protein components, molecular connectivity map, oncogenic signaling pathway map, pathway based functional connectivity map etc. Here, we briefly represent the systems level understanding of the molecular mechanisms associated with prostate tumorigenesis by considering each and individual molecular and cell biological events of this disease process. PMID:27476486

  5. HCSD: the human cancer secretome database

    DEFF Research Database (Denmark)

    Feizi, Amir; Banaei-Esfahani, Amir; Nielsen, Jens

    2015-01-01

    The human cancer secretome database (HCSD) is a comprehensive database for human cancer secretome data. The cancer secretome describes proteins secreted by cancer cells and structuring information about the cancer secretome will enable further analysis of how this is related with tumor biology...... database is limiting the ability to query the increasing community knowledge. We therefore developed the Human Cancer Secretome Database (HCSD) to fulfil this gap. HCSD contains >80 000 measurements for about 7000 nonredundant human proteins collected from up to 35 high-throughput studies on 17 cancer...

  6. Human papillomavirus and genital cancer

    Directory of Open Access Journals (Sweden)

    Rapose Alwyn

    2009-01-01

    Full Text Available Human papillomavirus (HPV is one of the most common sexually transmitted infections world-wide. Low-risk HPV-types are associated with genital warts. Persistent infection with high-risk HPV-types is associated with genital cancers. Smoking and HIV infection have consistently been associated with longer duration of HPV infection and risk for genital cancer. There is an increasing incidence of anal cancers, and a close association with HPV infection has been demonstrated. Receptive anal sex and HIV-positive status are associated with a high risk for anal cancer. Two HPV vaccines are now available and offer protection from infection by the HPV-types included in the vaccine. This benefit is maximally seen in young women who were uninfected prior to vaccination.

  7. Quantitative analysis and classification of AFM images of human hair.

    Science.gov (United States)

    Gurden, S P; Monteiro, V F; Longo, E; Ferreira, M M C

    2004-07-01

    The surface topography of human hair, as defined by the outer layer of cellular sheets, termed cuticles, largely determines the cosmetic properties of the hair. The condition of the cuticles is of great cosmetic importance, but also has the potential to aid diagnosis in the medical and forensic sciences. Atomic force microscopy (AFM) has been demonstrated to offer unique advantages for analysis of the hair surface, mainly due to the high image resolution and the ease of sample preparation. This article presents an algorithm for the automatic analysis of AFM images of human hair. The cuticular structure is characterized using a series of descriptors, such as step height, tilt angle and cuticle density, allowing quantitative analysis and comparison of different images. The usefulness of this approach is demonstrated by a classification study. Thirty-eight AFM images were measured, consisting of hair samples from (a) untreated and bleached hair samples, and (b) the root and distal ends of the hair fibre. The multivariate classification technique partial least squares discriminant analysis is used to test the ability of the algorithm to characterize the images according to the properties of the hair samples. Most of the images (86%) were found to be classified correctly.

  8. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  9. Three-class classification in computer-aided diagnosis of breast cancer by support vector machine

    Science.gov (United States)

    Sun, Xuejun; Qian, Wei; Song, Dansheng

    2004-05-01

    Design of classifier in computer-aided diagnosis (CAD) scheme of breast cancer plays important role to its overall performance in sensitivity and specificity. Classification of a detected object as malignant lesion, benign lesion, or normal tissue on mammogram is a typical three-class pattern recognition problem. This paper presents a three-class classification approach by using two-stage classifier combined with support vector machine (SVM) learning algorithm for classification of breast cancer on mammograms. The first classification stage is used to detect abnormal areas and normal breast tissues, and the second stage is for classification of malignant or benign in detected abnormal objects. A series of spatial, morphology and texture features have been extracted on detected objects areas. By using genetic algorithm (GA), different feature groups for different stage classification have been investigated. Computerized free-response receiver operating characteristic (FROC) and receiver operating characteristic (ROC) analyses have been employed in different classification stages. Results have shown that obvious performance improvement in both sensitivity and specificity was observed through proposed classification approach compared with conventional two-class classification approaches, indicating its effectiveness in classification of breast cancer on mammograms.

  10. DBGC: A Database of Human Gastric Cancer

    Science.gov (United States)

    Wang, Chao; Zhang, Jun; Cai, Mingdeng; Zhu, Zhenggang; Gu, Wenjie; Yu, Yingyan; Zhang, Xiaoyan

    2015-01-01

    The Database of Human Gastric Cancer (DBGC) is a comprehensive database that integrates various human gastric cancer-related data resources. Human gastric cancer-related transcriptomics projects, proteomics projects, mutations, biomarkers and drug-sensitive genes from different sources were collected and unified in this database. Moreover, epidemiological statistics of gastric cancer patients in China and clinicopathological information annotated with gastric cancer cases were also integrated into the DBGC. We believe that this database will greatly facilitate research regarding human gastric cancer in many fields. DBGC is freely available at http://bminfor.tongji.edu.cn/dbgc/index.do PMID:26566288

  11. Development of Human Factor Management Requirements and Human Error Classification for the Prevention of Railway Accident

    International Nuclear Information System (INIS)

    Kwak, Sang Log; Park, Chan Woo; Shin, Seung Ryoung

    2008-08-01

    Railway accident analysis results show that accidents cased by human factors are not decreasing, whereas H/W related accidents are steadily decreasing. For the efficient management of human factors, many expertise on design, conditions, safety culture and staffing are required. But current safety management activities on safety critical works are focused on training, due to the limited resource and information. In order to improve railway safety, human factors management requirements for safety critical worker and human error classification is proposed in this report. For this accident analysis, status of safety measure on human factor, safety management system on safety critical worker, current safety planning is analysis

  12. Detection and classification of Breast Cancer in Wavelet Sub-bands of Fractal Segmented Cancerous Zones.

    Science.gov (United States)

    Shirazinodeh, Alireza; Noubari, Hossein Ahmadi; Rabbani, Hossein; Dehnavi, Alireza Mehri

    2015-01-01

    Recent studies on wavelet transform and fractal modeling applied on mammograms for the detection of cancerous tissues indicate that microcalcifications and masses can be utilized for the study of the morphology and diagnosis of cancerous cases. It is shown that the use of fractal modeling, as applied to a given image, can clearly discern cancerous zones from noncancerous areas. In this paper, for fractal modeling, the original image is first segmented into appropriate fractal boxes followed by identifying the fractal dimension of each windowed section using a computationally efficient two-dimensional box-counting algorithm. Furthermore, using appropriate wavelet sub-bands and image Reconstruction based on modified wavelet coefficients, it is shown that it is possible to arrive at enhanced features for detection of cancerous zones. In this paper, we have attempted to benefit from the advantages of both fractals and wavelets by introducing a new algorithm. By using a new algorithm named F1W2, the original image is first segmented into appropriate fractal boxes, and the fractal dimension of each windowed section is extracted. Following from that, by applying a maximum level threshold on fractal dimensions matrix, the best-segmented boxes are selected. In the next step, the segmented Cancerous zones which are candidates are then decomposed by utilizing standard orthogonal wavelet transform and db2 wavelet in three different resolution levels, and after nullifying wavelet coefficients of the image at the first scale and low frequency band of the third scale, the modified reconstructed image is successfully utilized for detection of breast cancer regions by applying an appropriate threshold. For detection of cancerous zones, our simulations indicate the accuracy of 90.9% for masses and 88.99% for microcalcifications detection results using the F1W2 method. For classification of detected mictocalcification into benign and malignant cases, eight features are identified and

  13. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  14. Convolutional Neural Network Achieves Human-level Accuracy in Music Genre Classification

    OpenAIRE

    Dong, Mingwen

    2018-01-01

    Music genre classification is one example of content-based analysis of music signals. Traditionally, human-engineered features were used to automatize this task and 61% accuracy has been achieved in the 10-genre classification. However, it's still below the 70% accuracy that humans could achieve in the same task. Here, we propose a new method that combines knowledge of human perception study in music genre classification and the neurophysiology of the auditory system. The method works by trai...

  15. Feature Importance for Human Epithelial (HEp-2 Cell Image Classification

    Directory of Open Access Journals (Sweden)

    Vibha Gupta

    2018-02-01

    Full Text Available Indirect Immuno-Fluorescence (IIF microscopy imaging of human epithelial (HEp-2 cells is a popular method for diagnosing autoimmune diseases. Considering large data volumes, computer-aided diagnosis (CAD systems, based on image-based classification, can help in terms of time, effort, and reliability of diagnosis. Such approaches are based on extracting some representative features from the images. This work explores the selection of the most distinctive features for HEp-2 cell images using various feature selection (FS methods. Considering that there is no single universally optimal feature selection technique, we also propose hybridization of one class of FS methods (filter methods. Furthermore, the notion of variable importance for ranking features, provided by another type of approaches (embedded methods such as Random forest, Random uniform forest is exploited to select a good subset of features from a large set, such that addition of new features does not increase classification accuracy. In this work, we have also, with great consideration, designed class-specific features to capture morphological visual traits of the cell patterns. We perform various experiments and discussions to demonstrate the effectiveness of FS methods along with proposed and a standard feature set. We achieve state-of-the-art performance even with small number of features, obtained after the feature selection.

  16. Cancer Classification Based on Support Vector Machine Optimized by Particle Swarm Optimization and Artificial Bee Colony.

    Science.gov (United States)

    Gao, Lingyun; Ye, Mingquan; Wu, Changrong

    2017-11-29

    Intelligent optimization algorithms have advantages in dealing with complex nonlinear problems accompanied by good flexibility and adaptability. In this paper, the FCBF (Fast Correlation-Based Feature selection) method is used to filter irrelevant and redundant features in order to improve the quality of cancer classification. Then, we perform classification based on SVM (Support Vector Machine) optimized by PSO (Particle Swarm Optimization) combined with ABC (Artificial Bee Colony) approaches, which is represented as PA-SVM. The proposed PA-SVM method is applied to nine cancer datasets, including five datasets of outcome prediction and a protein dataset of ovarian cancer. By comparison with other classification methods, the results demonstrate the effectiveness and the robustness of the proposed PA-SVM method in handling various types of data for cancer classification.

  17. Mycotoxins as human carcinogens-the IARC Monographs classification.

    Science.gov (United States)

    Ostry, Vladimir; Malir, Frantisek; Toman, Jakub; Grosse, Yann

    2017-02-01

    Humans are constantly exposed to mycotoxins (e.g. aflatoxins, ochratoxins), mainly via food intake of plant and animal origin. The health risks stemming from mycotoxins may result from their toxicity, in particular their carcinogenicity. In order to prevent these risks, the International Agency for Research on Cancer (IARC) in Lyon (France)-through its IARC Monographs programme-has performed the carcinogenic hazard assessment of some mycotoxins in humans, on the basis of epidemiological data, studies of cancer in experimental animals and mechanistic studies. The present article summarizes the carcinogenic hazard assessments of those mycotoxins, especially aflatoxins (aflatoxin B 1 , B 2 , G 1 , G 2 and M 1 ), fumonisins (fumonisin B 1 and B 2 ) and ochratoxin A (OTA). New information regarding the genotoxicity of OTA (formation of OTA-DNA adducts), the role of OTA in oxidative stress and the identification of epigenetic factors involved in OTA carcinogenesis-should they indeed provide strong evidence that OTA carcinogenicity is mediated by a mechanism that also operates in humans-could lead to the reclassification of OTA.

  18. Cancer survival classification using integrated data sets and intermediate information.

    Science.gov (United States)

    Kim, Shinuk; Park, Taesung; Kon, Mark

    2014-09-01

    Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a machine learning (ML) approach to integrate different data sets, and developed a novel method based on feature selection with Cox proportional hazard regression model (FSCOX) to improve the prediction of cancer survival time. FSCOX provides us with intermediate survival information, which is usually discarded when separating survival into 2 groups (short- and long-term), and allows us to perform survival analysis. We used an ML-based protocol for feature selection, integrating information from miRNA and mRNA expression profiles at the feature level. To predict survival phenotypes, we used the following classifiers, first, existing ML methods, support vector machine (SVM) and random forest (RF), second, a new median-based classifier using FSCOX (FSCOX_median), and third, an SVM classifier using FSCOX (FSCOX_SVM). We compared these methods using 3 types of cancer tissue data sets: (i) miRNA expression, (ii) mRNA expression, and (iii) combined miRNA and mRNA expression. The latter data set included features selected either from the combined miRNA/mRNA profile or independently from miRNAs and mRNAs profiles (IFS). In the ovarian data set, the accuracy of survival classification using the combined miRNA/mRNA profiles with IFS was 75% using RF, 86.36% using SVM, 84.09% using FSCOX_median, and 88.64% using FSCOX_SVM with a balanced 22 short-term and 22 long-term survivor data set. These accuracies are higher than those using miRNA alone (70.45%, RF; 75%, SVM; 75%, FSCOX_median; and 75%, FSCOX_SVM) or mRNA alone (65.91%, RF; 63.64%, SVM; 72.73%, FSCOX_median; and 70.45%, FSCOX_SVM). Similarly in the glioblastoma multiforme data, the accuracy of miRNA/mRNA using IFS

  19. KITENIN is associated with tumor progression in human gastric cancer.

    Science.gov (United States)

    Ryu, Ho-Seong; Park, Young-Lan; Park, Su-Jin; Lee, Ji-Hee; Cho, Sung-Bum; Lee, Wan-Sik; Chung, Ik-Joo; Kim, Kyung-Keun; Lee, Kyung-Hwa; Kweon, Sun-Seog; Joo, Young-Eun

    2010-09-01

    KAI1 COOH-terminal interacting tetraspanin (KITENIN) promotes tumor cell migration, invasion and metastasis in colon, bladder, head and neck cancer. The aims of current study were to evaluate whether KITENIN affects tumor cell behavior in human gastric cancer cell line and to document the expression of KITENIN in a well-defined series of gastric tumors, including complete long-term follow-up, with special reference to patient prognosis. To evaluate the impact of KITENIN knockdown on behavior of a human gastric cancer cell line, AGS, migration, invasion and proliferation assays using small-interfering RNA were performed. The expression of activator protein-1 (AP-1) target genes and AP-1 transcriptional activity were evaluated by reverse transcription-polymerase chain reaction (RT-PCR) and luciferase reporter assay. The expression of KITENIN and AP-1 target genes by RT-PCR and Western blotting or immunohistochemistry was also investigated in human gastric cancer tissues. The knockdown of KITENIN suppressed tumor cell migration, invasion and proliferation in AGS cells. The mRNA expression of matrix metalloproteinase-1 (MMP-1), MMP-3, cyclooxygenase-2 (COX-2), and CD44 was reduced by knockdown of KITENIN in AGS. AP-1 transcriptional activity was significantly decreased by knockdown of KITENIN in AGS cells. KITENIN expression was significantly increased in human cancer tissues at RNA and protein levels. Expression of MMP-1, MMP-3, COX-2 and CD44 were significantly increased in human gastric cancer tissues. Immunostaining of KITENIN was predominantly identified in the cytoplasm of cancer cells. Expression of KITENIN was significantly associated with tumor size, Lauren classification, depth of invasion, lymph node metastasis, tumor stage and poor survival. These results indicate that KITENIN plays an important role in human gastric cancer progression by AP-1 activation.

  20. Efficacy of hidden markov model over support vector machine on multiclass classification of healthy and cancerous cervical tissues

    Science.gov (United States)

    Mukhopadhyay, Sabyasachi; Kurmi, Indrajit; Pratiher, Sawon; Mukherjee, Sukanya; Barman, Ritwik; Ghosh, Nirmalya; Panigrahi, Prasanta K.

    2018-02-01

    In this paper, a comparative study between SVM and HMM has been carried out for multiclass classification of cervical healthy and cancerous tissues. In our study, the HMM methodology is more promising to produce higher accuracy in classification.

  1. Involvement of Machine Learning for Breast Cancer Image Classification: A Survey

    Directory of Open Access Journals (Sweden)

    Abdullah-Al Nahid

    2017-01-01

    Full Text Available Breast cancer is one of the largest causes of women’s death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors’ and physicians’ time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN, Logic Based classifiers such as the Random Forest (RF algorithm, Support Vector Machines (SVM, Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.

  2. Involvement of Machine Learning for Breast Cancer Image Classification: A Survey.

    Science.gov (United States)

    Nahid, Abdullah-Al; Kong, Yinan

    2017-01-01

    Breast cancer is one of the largest causes of women's death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors' and physicians' time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN) method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN), Logic Based classifiers such as the Random Forest (RF) algorithm, Support Vector Machines (SVM), Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.

  3. Rule-guided human classification of Volunteered Geographic Information

    Science.gov (United States)

    Ali, Ahmed Loai; Falomir, Zoe; Schmid, Falko; Freksa, Christian

    2017-05-01

    During the last decade, web technologies and location sensing devices have evolved generating a form of crowdsourcing known as Volunteered Geographic Information (VGI). VGI acted as a platform of spatial data collection, in particular, when a group of public participants are involved in collaborative mapping activities: they work together to collect, share, and use information about geographic features. VGI exploits participants' local knowledge to produce rich data sources. However, the resulting data inherits problematic data classification. In VGI projects, the challenges of data classification are due to the following: (i) data is likely prone to subjective classification, (ii) remote contributions and flexible contribution mechanisms in most projects, and (iii) the uncertainty of spatial data and non-strict definitions of geographic features. These factors lead to various forms of problematic classification: inconsistent, incomplete, and imprecise data classification. This research addresses classification appropriateness. Whether the classification of an entity is appropriate or inappropriate is related to quantitative and/or qualitative observations. Small differences between observations may be not recognizable particularly for non-expert participants. Hence, in this paper, the problem is tackled by developing a rule-guided classification approach. This approach exploits data mining techniques of Association Classification (AC) to extract descriptive (qualitative) rules of specific geographic features. The rules are extracted based on the investigation of qualitative topological relations between target features and their context. Afterwards, the extracted rules are used to develop a recommendation system able to guide participants to the most appropriate classification. The approach proposes two scenarios to guide participants towards enhancing the quality of data classification. An empirical study is conducted to investigate the classification of grass

  4. Prognostic classifications of lymph node involvement in lung cancer and current International Association for the Study of Lung Cancer descriptive classification in zones.

    Science.gov (United States)

    Riquet, Marc; Arame, Alex; Foucault, Christophe; Le Pimpec Barthes, Françoise

    2010-09-01

    The lymphatic drainage of solid organ tumors crosses through the lymph nodes (LNs) whose tumoral involvement may still be considered as local disease. Concerning lung cancer, LN involvement may be intrapulmonary (N1), and mediastinal and/or extra-thoracic. More than 30 years ago, mediastinal involved LNs were all considered as N2, and outside the scope of surgery. In 1978, Naruke presented an original article entitled 'Lymph node mapping and curability at various levels of metastasis in resected lung cancer', demonstrating that N2 was not a contraindication to surgery in all patients. The map permitted to localize the favorable N2 on the lung cancer ipsilateral side of the mediastinum. Several maps ensued aiming to discriminate between right and left involvement (1983), and to distinguish N2 (ipsilateral) and N3 (contralateral) mediastinal LN involvement (1983, 1986). The last map (1997 regional LN classification) was recently replaced by a descriptive classification in anatomical zones. This new LN map of the TNM classification for lung cancer is a step toward using anatomical view points which might be the best way to better understand lung cancer lymphatic spread. Nowadays, the LNs are easily identified by current radiological imaging, and their resectability may be anticipated. Each LN chain may be removed by en-bloc lymphadenectomy performed during radical lung resection, a safe procedure which seems to be more oncological based than sampling, and which avoids the source of discrepancies pointed out during the labeling of LN stations by surgeons.

  5. Evolving cancer classification in the era of personalized medicine: A primer for radiologists

    Energy Technology Data Exchange (ETDEWEB)

    O' Neill, Alibhe C.; Jagannathan, Jyothi P.; Ramaiya, Nikhil H. [Dept. of of Imaging, Dana Farber Cancer Institute, Boston (United States)

    2017-01-15

    Traditionally tumors were classified based on anatomic location but now specific genetic mutations in cancers are leading to treatment of tumors with molecular targeted therapies. This has led to a paradigm shift in the classification and treatment of cancer. Tumors treated with molecular targeted therapies often show morphological changes rather than change in size and are associated with class specific and drug specific toxicities, different from those encountered with conventional chemotherapeutic agents. It is important for the radiologists to be familiar with the new cancer classification and the various treatment strategies employed, in order to effectively communicate and participate in the multi-disciplinary care. In this paper we will focus on lung cancer as a prototype of the new molecular classification.

  6. Classification of cancerous cells based on the one-class problem approach

    Science.gov (United States)

    Murshed, Nabeel A.; Bortolozzi, Flavio; Sabourin, Robert

    1996-03-01

    One of the most important factors in reducing the effect of cancerous diseases is the early diagnosis, which requires a good and a robust method. With the advancement of computer technologies and digital image processing, the development of a computer-based system has become feasible. In this paper, we introduce a new approach for the detection of cancerous cells. This approach is based on the one-class problem approach, through which the classification system need only be trained with patterns of cancerous cells. This reduces the burden of the training task by about 50%. Based on this approach, a computer-based classification system is developed, based on the Fuzzy ARTMAP neural networks. Experimental results were performed using a set of 542 patterns taken from a sample of breast cancer. Results of the experiment show 98% correct identification of cancerous cells and 95% correct identification of non-cancerous cells.

  7. Automatic detection and classification of human epicardial atrial unipolar electrograms

    International Nuclear Information System (INIS)

    Dubé, B; Vinet, A; Xiong, F; Yin, Y; LeBlanc, A-R; Pagé, P

    2009-01-01

    This paper describes an unsupervised signal processing method applied to three-channel unipolar electrograms recorded from human atria. These were obtained by epicardial wires sutured on the right and left atria after coronary artery bypass surgery. Atrial (A) and ventricular (V) activations had to be detected and identified on each channel, and gathered across the channels when belonging to the same global event. The algorithm was developed and optimized on a training set of 19 recordings of 5 min. It was assessed on twenty-seven 2 h recordings taken just before the onset of a prolonged atrial fibrillation for a total of 1593697 activations that were validated and classified as normal atrial or ventricular activations (A, V) and premature atrial or ventricular activations (PAA, PVA). 99.93% of the activations were detected, and amongst these, 99.89% of the A and 99.75% of the V activations were correctly labelled. In the subset of the 39705 PAA, 99.83% were detected and 99.3% were correctly classified as A. The false positive rate was 0.37%. In conclusion, a reliable fully automatic detection and classification algorithm was developed that can detect and discriminate A and V activations from atrial recordings. It can provide the time series needed to develop a monitoring system aiming to identify dynamic predictors of forthcoming cardiac events such as postoperative atrial fibrillation

  8. Efficacy of the Kyoto Classification of Gastritis in Identifying Patients at High Risk for Gastric Cancer.

    Science.gov (United States)

    Sugimoto, Mitsushige; Ban, Hiromitsu; Ichikawa, Hitomi; Sahara, Shu; Otsuka, Taketo; Inatomi, Osamu; Bamba, Shigeki; Furuta, Takahisa; Andoh, Akira

    2017-01-01

    Objective The Kyoto gastritis classification categorizes the endoscopic characteristics of Helicobacter pylori (H. pylori) infection-associated gastritis and identifies patterns associated with a high risk of gastric cancer. We investigated its efficacy, comparing scores in patients with H. pylori-associated gastritis and with gastric cancer. Methods A total of 1,200 patients with H. pylori-positive gastritis alone (n=932), early-stage H. pylori-positive gastric cancer (n=189), and successfully treated H. pylori-negative cancer (n=79) were endoscopically graded according to the Kyoto gastritis classification for atrophy, intestinal metaplasia, fold hypertrophy, nodularity, and diffuse redness. Results The prevalence of O-II/O-III-type atrophy according to the Kimura-Takemoto classification in early-stage H. pylori-positive gastric cancer and successfully treated H. pylori-negative cancer groups was 45.1%, which was significantly higher than in subjects with gastritis alone (12.7%, pgastritis scores of atrophy and intestinal metaplasia in the H. pylori-positive cancer group were significantly higher than in subjects with gastritis alone (all pgastritis classification may thus be useful for detecting these patients.

  9. Two-Stage Classification Approach for Human Detection in Camera Video in Bulk Ports

    Directory of Open Access Journals (Sweden)

    Mi Chao

    2015-09-01

    Full Text Available With the development of automation in ports, the video surveillance systems with automated human detection begun to be applied in open-air handling operation areas for safety and security. The accuracy of traditional human detection based on the video camera is not high enough to meet the requirements of operation surveillance. One of the key reasons is that Histograms of Oriented Gradients (HOG features of the human body will show great different between front & back standing (F&B and side standing (Side human body. Therefore, the final training for classifier will only gain a few useful specific features which have contribution to classification and are insufficient to support effective classification, while using the HOG features directly extracted by the samples from different human postures. This paper proposes a two-stage classification method to improve the accuracy of human detection. In the first stage, during preprocessing classification, images is mainly divided into possible F&B human body and not F&B human body, and then they were put into the second-stage classification among side human and non-human recognition. The experimental results in Tianjin port show that the two-stage classifier can improve the classification accuracy of human detection obviously.

  10. An enhanced topologically significant directed random walk in cancer classification using gene expression datasets

    Directory of Open Access Journals (Sweden)

    Choon Sen Seah

    2017-12-01

    Full Text Available Microarray technology has become one of the elementary tools for researchers to study the genome of organisms. As the complexity and heterogeneity of cancer is being increasingly appreciated through genomic analysis, cancerous classification is an emerging important trend. Significant directed random walk is proposed as one of the cancerous classification approach which have higher sensitivity of risk gene prediction and higher accuracy of cancer classification. In this paper, the methodology and material used for the experiment are presented. Tuning parameter selection method and weight as parameter are applied in proposed approach. Gene expression dataset is used as the input datasets while pathway dataset is used to build a directed graph, as reference datasets, to complete the bias process in random walk approach. In addition, we demonstrate that our approach can improve sensitive predictions with higher accuracy and biological meaningful classification result. Comparison result takes place between significant directed random walk and directed random walk to show the improvement in term of sensitivity of prediction and accuracy of cancer classification.

  11. Human Cancer Models Initiative | Office of Cancer Genomics

    Science.gov (United States)

    The Human Cancer Models Initiative (HCMI) is an international consortium that is generating novel human tumor-derived culture models, which are annotated with genomic and clinical data. In an effort to advance cancer research and more fully understand how in vitro findings are related to clinical biology, HCMI-developed models and related data will be available as a community resource for cancer research.

  12. Socializing the human factors analysis and classification system: incorporating social psychological phenomena into a human factors error classification system.

    Science.gov (United States)

    Paletz, Susannah B F; Bearman, Christopher; Orasanu, Judith; Holbrook, Jon

    2009-08-01

    The presence of social psychological pressures on pilot decision making was assessed using qualitative analyses of critical incident interviews. Social psychological phenomena have long been known to influence attitudes and behavior but have not been highlighted in accident investigation models. Using a critical incident method, 28 pilots who flew in Alaska were interviewed. The participants were asked to describe a situation involving weather when they were pilot in command and found their skills challenged. They were asked to describe the incident in detail but were not explicitly asked to identify social pressures. Pressures were extracted from transcripts in a bottom-up manner and then clustered into themes. Of the 28 pilots, 16 described social psychological pressures on their decision making, specifically, informational social influence, the foot-in-the-door persuasion technique, normalization of deviance, and impression management and self-consistency motives. We believe accident and incident investigations can benefit from explicit inclusion of common social psychological pressures. We recommend specific ways of incorporating these pressures into theHuman Factors Analysis and Classification System.

  13. A New Feature Ensemble with a Multistage Classification Scheme for Breast Cancer Diagnosis

    Directory of Open Access Journals (Sweden)

    Idil Isikli Esener

    2017-01-01

    Full Text Available A new and effective feature ensemble with a multistage classification is proposed to be implemented in a computer-aided diagnosis (CAD system for breast cancer diagnosis. A publicly available mammogram image dataset collected during the Image Retrieval in Medical Applications (IRMA project is utilized to verify the suggested feature ensemble and multistage classification. In achieving the CAD system, feature extraction is performed on the mammogram region of interest (ROI images which are preprocessed by applying a histogram equalization followed by a nonlocal means filtering. The proposed feature ensemble is formed by concatenating the local configuration pattern-based, statistical, and frequency domain features. The classification process of these features is implemented in three cases: a one-stage study, a two-stage study, and a three-stage study. Eight well-known classifiers are used in all cases of this multistage classification scheme. Additionally, the results of the classifiers that provide the top three performances are combined via a majority voting technique to improve the recognition accuracy on both two- and three-stage studies. A maximum of 85.47%, 88.79%, and 93.52% classification accuracies are attained by the one-, two-, and three-stage studies, respectively. The proposed multistage classification scheme is more effective than the single-stage classification for breast cancer diagnosis.

  14. Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

    Science.gov (United States)

    Wutsqa, D. U.; Marwah, M.

    2017-06-01

    In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

  15. Comparative Study of Classification Techniques on Breast Cancer FNA Biopsy Data

    Directory of Open Access Journals (Sweden)

    George Rumbe

    2010-12-01

    Full Text Available Accurate diagnostic detection of the cancerous cells in a patient is critical and may alter the subsequent treatment and increase the chances of survival rate. Machine learning techniques have been instrumental in disease detection and are currently being used in various classification problems due to their accurate prediction performance. Various techniques may provide different desired accuracies and it is therefore imperative to use the most suitable method which provides the best desired results. This research seeks to provide comparative analysis of Support Vector Machine, Bayesian classifier and other Artificial neural network classifiers (Backpropagation, linear programming, Learning vector quantization, and K nearest neighborhood on the Wisconsin breast cancer classification problem.

  16. Optimization of human cancer radiotherapy

    CERN Document Server

    Swan, George W

    1981-01-01

    The mathematical models in this book are concerned with a variety of approaches to the manner in which the clinical radiologic treatment of human neoplasms can be improved. These improvements comprise ways of delivering radiation to the malignan­ cies so as to create considerable damage to tumor cells while sparing neighboring normal tissues. There is no unique way of dealing with these improvements. Accord­ ingly, in this book a number of different presentations are given. Each presentation has as its goal some aspect of the improvement, or optimization, of radiotherapy. This book is a collection of current ideas concerned with the optimization of human cancer radiotherapy. It is hoped that readers will build on this collection and develop superior approaches for the understanding of the ways to improve therapy. The author owes a special debt of thanks to Kathy Prindle who breezed through the typing of this book with considerable dexterity. TABLE OF CONTENTS Chapter GENERAL INTRODUCTION 1. 1 Introduction 1...

  17. Classification of treatment-related mortality in children with cancer

    DEFF Research Database (Denmark)

    Alexander, Sarah; Pole, Jason D; Gibson, Paul

    2015-01-01

    Treatment-related mortality is an important outcome in paediatric cancer clinical trials. An international group of experts in supportive care in paediatric cancer developed a consensus-based definition of treatment-related mortality and a cause-of-death attribution system. The reliability and va...

  18. Pathogenesis of Gastric Cancer: Genetics and Molecular Classification.

    Science.gov (United States)

    Figueiredo, Ceu; Camargo, M C; Leite, Marina; Fuentes-Pananá, Ezequiel M; Rabkin, Charles S; Machado, José C

    Gastric cancer is the fifth most incident and the third most common cause of cancer-related death in the world. Infection with Helicobacter pylori is the major risk factor for this disease. Gastric cancer is the final outcome of a cascade of events that takes decades to occur and results from the accumulation of multiple genetic and epigenetic alterations. These changes are crucial for tumor cells to expedite and sustain the array of pathways involved in the cancer development, such as cell cycle, DNA repair, metabolism, cell-to-cell and cell-to-matrix interactions, apoptosis, angiogenesis, and immune surveillance. Comprehensive molecular analyses of gastric cancer have disclosed the complex heterogeneity of this disease. In particular, these analyses have confirmed that Epstein-Barr virus (EBV)-positive gastric cancer is a distinct entity. The identification of gastric cancer subtypes characterized by recognizable molecular profiles may pave the way for a more personalized clinical management and to the identification of novel therapeutic targets and biomarkers for screening, prognosis, prediction of response to treatment, and monitoring of gastric cancer progression.

  19. Prevalence of Human Papillomavirus in endometrial cancer

    DEFF Research Database (Denmark)

    Olesen, Tina Bech; Svahn, Malene Frøsig; Faber, Mette Tuxen

    2014-01-01

    HPV is a common sexually transmitted infection and is considered to be a necessary cause of cervical cancer. The anatomical proximity to the cervix has led researchers to investigate whether Human Papillomavirus (HPV) has a role in the etiology of endometrial cancer.......HPV is a common sexually transmitted infection and is considered to be a necessary cause of cervical cancer. The anatomical proximity to the cervix has led researchers to investigate whether Human Papillomavirus (HPV) has a role in the etiology of endometrial cancer....

  20. IARC use of oxidative stress as key mode of action characteristic for facilitating cancer classification: Glyphosate case example illustrating a lack of robustness in interpretative implementation.

    Science.gov (United States)

    Bus, James S

    2017-06-01

    The International Agency for Research on Cancer (IARC) has formulated 10 key characteristics of human carcinogens to incorporate mechanistic data into cancer hazard classifications. The analysis used glyphosate as a case example to examine the robustness of IARC's determination of oxidative stress as "strong" evidence supporting a plausible cancer mechanism in humans. The IARC analysis primarily relied on 14 human/mammalian studies; 19 non-mammalian studies were uninformative of human cancer given the broad spectrum of test species and extensive use of formulations and aquatic testing. The mammalian studies had substantial experimental limitations for informing cancer mechanism including use of: single doses and time points; cytotoxic/toxic test doses; tissues not identified as potential cancer targets; glyphosate formulations or mixtures; technically limited oxidative stress biomarkers. The doses were many orders of magnitude higher than human exposures determined in human biomonitoring studies. The glyphosate case example reveals that the IARC evaluation fell substantially short of "strong" supporting evidence of oxidative stress as a plausible human cancer mechanism, and suggests that other IARC monographs relying on the 10 key characteristics approach should be similarly examined for a lack of robust data integration fundamental to reasonable mode of action evaluations. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI

    Energy Technology Data Exchange (ETDEWEB)

    Dikaios, Nikolaos; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit [University College London, Centre for Medical Imaging, London (United Kingdom); University College London Hospital, Departments of Radiology, London (United Kingdom); Alkalbani, Jokha; Sidhu, Harbir Singh [University College London, Centre for Medical Imaging, London (United Kingdom); Abd-Alazeez, Mohamed; Ahmed, Hashim U.; Emberton, Mark [University College London, Research Department of Urology, Division of Surgery and Interventional Science, London (United Kingdom); Kirkham, Alex [University College London Hospital, Departments of Radiology, London (United Kingdom); Freeman, Alex [University College London Hospital, Department of Histopathology, London (United Kingdom)

    2015-09-15

    To assess the interchangeability of zone-specific (peripheral-zone (PZ) and transition-zone (TZ)) multiparametric-MRI (mp-MRI) logistic-regression (LR) models for classification of prostate cancer. Two hundred and thirty-one patients (70 TZ training-cohort; 76 PZ training-cohort; 85 TZ temporal validation-cohort) underwent mp-MRI and transperineal-template-prostate-mapping biopsy. PZ and TZ uni/multi-variate mp-MRI LR-models for classification of significant cancer (any cancer-core-length (CCL) with Gleason > 3 + 3 or any grade with CCL ≥ 4 mm) were derived from the respective cohorts and validated within the same zone by leave-one-out analysis. Inter-zonal performance was tested by applying TZ models to the PZ training-cohort and vice-versa. Classification performance of TZ models for TZ cancer was further assessed in the TZ validation-cohort. ROC area-under-curve (ROC-AUC) analysis was used to compare models. The univariate parameters with the best classification performance were the normalised T2 signal (T2nSI) within the TZ (ROC-AUC = 0.77) and normalized early contrast-enhanced T1 signal (DCE-nSI) within the PZ (ROC-AUC = 0.79). Performance was not significantly improved by bi-variate/tri-variate modelling. PZ models that contained DCE-nSI performed poorly in classification of TZ cancer. The TZ model based solely on maximum-enhancement poorly classified PZ cancer. LR-models dependent on DCE-MRI parameters alone are not interchangeable between prostatic zones; however, models based exclusively on T2 and/or ADC are more robust for inter-zonal application. (orig.)

  2. Significance and Application of Digital Breast Tomosynthesis for the BI-RADS Classification of Breast Cancer.

    Science.gov (United States)

    Cai, Si-Qing; Yan, Jian-Xiang; Chen, Qing-Shi; Huang, Mei-Ling; Cai, Dong-Lu

    2015-01-01

    Full-field digital mammography (FFDM) with dense breasts has a high rate of missed diagnosis, and digital breast tomosynthesis (DBT) could reduce organization overlapping and provide more reliable images for BI-RADS classification. This study aims to explore application of COMBO (FFDM+DBT) for effect and significance of BI-RADS classification of breast cancer. In this study, we selected 832 patients who had been treated from May 2013 to November 2013. Classify FFDM and COMBO examination according to BI-RADS separately and compare the differences for glands in the image of the same patient in judgment, mass characteristics display and indirect signs. Employ Paired Wilcoxon rank sum test was used in 79 breast cancer patients to find differences between two examine methods. The results indicated that COMBO pattern is able to observe more details in distribution of glands when estimating content. Paired Wilcoxon rank sum test showed that overall classification level of COMBO is higher significantly compared to FFDM to BI-RADS diagnosis and classification of breast (PBI-RADS classification in breast cancer in clinical.

  3. Development and test of a classification scheme for human factors in incident reports

    International Nuclear Information System (INIS)

    Miller, R.; Freitag, M.; Wilpert, B.

    1997-01-01

    The Research Center System Safety of the Berlin University of Technology conducted a research project on the analysis of Human Factors (HF) aspects in incident reported by German Nuclear Power Plants. Based on psychological theories and empirical studies a classification scheme was developed which permits the identification of human involvement in incidents. The classification scheme was applied in an epidemiological study to a selection of more than 600 HF - relevant incidents. The results allow insights into HF related problem areas. An additional study proved that the application of the classification scheme produces results which are reliable and independent from raters. (author). 13 refs, 1 fig

  4. Stepwise classification of cancer samples using clinical and molecular data

    Directory of Open Access Journals (Sweden)

    Obulkasim Askar

    2011-10-01

    Full Text Available Abstract Background Combining clinical and molecular data types may potentially improve prediction accuracy of a classifier. However, currently there is a shortage of effective and efficient statistical and bioinformatic tools for true integrative data analysis. Existing integrative classifiers have two main disadvantages: First, coarse combination may lead to subtle contributions of one data type to be overshadowed by more obvious contributions of the other. Second, the need to measure both data types for all patients may be both unpractical and (cost inefficient. Results We introduce a novel classification method, a stepwise classifier, which takes advantage of the distinct classification power of clinical data and high-dimensional molecular data. We apply classification algorithms to two data types independently, starting with the traditional clinical risk factors. We only turn to relatively expensive molecular data when the uncertainty of prediction result from clinical data exceeds a predefined limit. Experimental results show that our approach is adaptive: the proportion of samples that needs to be re-classified using molecular data depends on how much we expect the predictive accuracy to increase when re-classifying those samples. Conclusions Our method renders a more cost-efficient classifier that is at least as good, and sometimes better, than one based on clinical or molecular data alone. Hence our approach is not just a classifier that minimizes a particular loss function. Instead, it aims to be cost-efficient by avoiding molecular tests for a potentially large subgroup of individuals; moreover, for these individuals a test result would be quickly available, which may lead to reduced waiting times (for diagnosis and hence lower the patients distress. Stepwise classification is implemented in R-package stepwiseCM and available at the Bioconductor website.

  5. Classification of normal and abnormal images of lung cancer

    Science.gov (United States)

    Bhatnagar, Divyesh; Tiwari, Amit Kumar; Vijayarajan, V.; Krishnamoorthy, A.

    2017-11-01

    To find the exact symptoms of lung cancer is difficult, because of the formation of the most cancers tissues, wherein large structure of tissues is intersect in a different way. This problem can be evaluated with the help of digital images. In this strategy images will be examined with basic operation of PCA Algorithm. In this paper, GLCM method is used for pre-processing of the snap shots and function extraction system and to test the level of diseases of a patient in its premature stage get to know it is regular or unusual. With the help of result stage of cancer will be evaluated. With the help of dataset and result survival rate of cancer patient can be estimated. Result is based totally on the precise and wrong arrangement of the patterns of tissues.

  6. Immunogenomic Classification of Colorectal Cancer and Therapeutic Implications

    NARCIS (Netherlands)

    Roelands, Jessica; Kuppen, Peter J. K.; Vermeulen, Louis; Maccalli, Cristina; Decock, Julie; Wang, Ena; Marincola, Francesco M.; Bedognetti, Davide; Hendrickx, Wouter

    2017-01-01

    The immune system has a substantial effect on colorectal cancer (CRC) progression. Additionally, the response to immunotherapeutics and conventional treatment options (e.g., chemotherapy, radiotherapy and targeted therapies) is influenced by the immune system. The molecular characterization of

  7. Sensor Data Acquisition and Processing Parameters for Human Activity Classification

    Directory of Open Access Journals (Sweden)

    Sebastian D. Bersch

    2014-03-01

    Full Text Available It is known that parameter selection for data sampling frequency and segmentation techniques (including different methods and window sizes has an impact on the classification accuracy. For Ambient Assisted Living (AAL, no clear information to select these parameters exists, hence a wide variety and inconsistency across today’s literature is observed. This paper presents the empirical investigation of different data sampling rates, segmentation techniques and segmentation window sizes and their effect on the accuracy of Activity of Daily Living (ADL event classification and computational load for two different accelerometer sensor datasets. The study is conducted using an ANalysis Of VAriance (ANOVA based on 32 different window sizes, three different segmentation algorithm (with and without overlap, totaling in six different parameters and six sampling frequencies for nine common classification algorithms. The classification accuracy is based on a feature vector consisting of Root Mean Square (RMS, Mean, Signal Magnitude Area (SMA, Signal Vector Magnitude (here SMV, Energy, Entropy, FFTPeak, Standard Deviation (STD. The results are presented alongside recommendations for the parameter selection on the basis of the best performing parameter combinations that are identified by means of the corresponding Pareto curve.

  8. Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

    Directory of Open Access Journals (Sweden)

    Eils Roland

    2005-11-01

    Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

  9. Looking at the ICF and human communication through the lens of classification theory.

    Science.gov (United States)

    Walsh, Regina

    2011-08-01

    This paper explores the insights that classification theory can provide about the application of the International Classification of Functioning, Disability and Health (ICF) to communication. It first considers the relationship between conceptual models and classification systems, highlighting that classification systems in speech-language pathology (SLP) have not historically been based on conceptual models of human communication. It then overviews the key concepts and criteria of classification theory. Applying classification theory to the ICF and communication raises a number of issues, some previously highlighted through clinical application. Six focus questions from classification theory are used to explore these issues, and to propose the creation of an ICF-related conceptual model of communicating for the field of communication disability, which would address some of the issues raised. Developing a conceptual model of communication for SLP purposes closely articulated with the ICF would foster productive intra-professional discourse, while at the same time allow the profession to continue to use the ICF for purposes in inter-disciplinary discourse. The paper concludes by suggesting the insights of classification theory can assist professionals to apply the ICF to communication with the necessary rigour, and to work further in developing a conceptual model of human communication.

  10. Human papilloma virus in oral cancer

    OpenAIRE

    Kim, Soung Min

    2016-01-01

    Cervical cancer is the second most prevalent cancer among women, and it arises from cells that originate in the cervix uteri. Among several causes of cervical malignancies, infection with some types of human papilloma virus (HPV) is well known to be the greatest cervical cancer risk factor. Over 150 subtypes of HPV have been identified; more than 40 types of HPVs are typically transmitted through sexual contact and infect the anogenital region and oral cavity. The recently introduced vaccine ...

  11. Recursive Partitioning Analysis for New Classification of Patients With Esophageal Cancer Treated by Chemoradiotherapy

    International Nuclear Information System (INIS)

    Nomura, Motoo; Shitara, Kohei; Kodaira, Takeshi; Kondoh, Chihiro; Takahari, Daisuke; Ura, Takashi; Kojima, Hiroyuki; Kamata, Minoru; Muro, Kei; Sawada, Satoshi

    2012-01-01

    Background: The 7th edition of the American Joint Committee on Cancer staging system does not include lymph node size in the guidelines for staging patients with esophageal cancer. The objectives of this study were to determine the prognostic impact of the maximum metastatic lymph node diameter (ND) on survival and to develop and validate a new staging system for patients with esophageal squamous cell cancer who were treated with definitive chemoradiotherapy (CRT). Methods: Information on 402 patients with esophageal cancer undergoing CRT at two institutions was reviewed. Univariate and multivariate analyses of data from one institution were used to assess the impact of clinical factors on survival, and recursive partitioning analysis was performed to develop the new staging classification. To assess its clinical utility, the new classification was validated using data from the second institution. Results: By multivariate analysis, gender, T, N, and ND stages were independently and significantly associated with survival (p < 0.05). The resulting new staging classification was based on the T and ND. The four new stages led to good separation of survival curves in both the developmental and validation datasets (p < 0.05). Conclusions: Our results showed that lymph node size is a strong independent prognostic factor and that the new staging system, which incorporated lymph node size, provided good prognostic power, and discriminated effectively for patients with esophageal cancer undergoing CRT.

  12. Evaluation Methodology between Globalization and Localization Features Approaches for Skin Cancer Lesions Classification

    Science.gov (United States)

    Ahmed, H. M.; Al-azawi, R. J.; Abdulhameed, A. A.

    2018-05-01

    Huge efforts have been put in the developing of diagnostic methods to skin cancer disease. In this paper, two different approaches have been addressed for detection the skin cancer in dermoscopy images. The first approach uses a global method that uses global features for classifying skin lesions, whereas the second approach uses a local method that uses local features for classifying skin lesions. The aim of this paper is selecting the best approach for skin lesion classification. The dataset has been used in this paper consist of 200 dermoscopy images from Pedro Hispano Hospital (PH2). The achieved results are; sensitivity about 96%, specificity about 100%, precision about 100%, and accuracy about 97% for globalization approach while, sensitivity about 100%, specificity about 100%, precision about 100%, and accuracy about 100% for Localization Approach, these results showed that the localization approach achieved acceptable accuracy and better than globalization approach for skin cancer lesions classification.

  13. A Mouse Model for Human Anal Cancer

    Science.gov (United States)

    Stelzer, Marie K.; Pitot, Henry C.; Liem, Amy; Schweizer, Johannes; Mahoney, Charles; Lambert, Paul F.

    2010-01-01

    Human anal cancers are associated with high-risk human papillomaviruses (HPVs) that cause other anogenital cancers and head and neck cancers. As with other cancers, HPV16 is the most common high-risk HPV in anal cancers. We describe the generation and characterization of a mouse model for human anal cancer. This model makes use of K14E6 and K14E7 transgenic mice in which the HPV16 E6 and E7 genes are directed in their expression to stratified squamous epithelia. HPV16 E6 and E7 possess oncogenic properties including but not limited to their capacity to inactivate the cellular tumor suppressors p53 and pRb, respectively. Both E6 and E7 were found to be functionally expressed in the anal epithelia of K14E6/K14E7 transgenic mice. To assess the susceptibility of these mice to anal cancer, mice were treated topically with dimethylbenz[a]anthracene (DMBA), a chemical carcinogen that is known to induce squamous cell carcinomas in other sites. Nearly 50% of DMBA-treated HPV16 E6/E7 transgenic mice showed overt signs of tumors; whereas, none of the like treated non-transgenic mice showed tumors. Histopathological analyses confirmed that the HPV16 transgenic mice were increased in their susceptibility to anal cancers and precancerous lesions. Biomarker analyses demonstrated that these mouse anal cancers exhibit properties that are similar to those observed in HPV-positive precursors to human anal cancer. This is the first mouse model for investigating the contributions of viral and cellular factors in anal carcinogenesis, and should provide a platform for assessing new therapeutic modalities for treating and/or preventing this type of cancer. PMID:20947489

  14. Breast cancer tumor classification using LASSO method selection approach

    International Nuclear Information System (INIS)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M.

    2016-10-01

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  15. Breast cancer tumor classification using LASSO method selection approach

    Energy Technology Data Exchange (ETDEWEB)

    Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, Col. Centro, 98000 Zacatecas, Zac. (Mexico)

    2016-10-15

    Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

  16. Examining applying high performance genetic data feature selection and classification algorithms for colon cancer diagnosis.

    Science.gov (United States)

    Al-Rajab, Murad; Lu, Joan; Xu, Qiang

    2017-07-01

    This paper examines the accuracy and efficiency (time complexity) of high performance genetic data feature selection and classification algorithms for colon cancer diagnosis. The need for this research derives from the urgent and increasing need for accurate and efficient algorithms. Colon cancer is a leading cause of death worldwide, hence it is vitally important for the cancer tissues to be expertly identified and classified in a rapid and timely manner, to assure both a fast detection of the disease and to expedite the drug discovery process. In this research, a three-phase approach was proposed and implemented: Phases One and Two examined the feature selection algorithms and classification algorithms employed separately, and Phase Three examined the performance of the combination of these. It was found from Phase One that the Particle Swarm Optimization (PSO) algorithm performed best with the colon dataset as a feature selection (29 genes selected) and from Phase Two that the Support Vector Machine (SVM) algorithm outperformed other classifications, with an accuracy of almost 86%. It was also found from Phase Three that the combined use of PSO and SVM surpassed other algorithms in accuracy and performance, and was faster in terms of time analysis (94%). It is concluded that applying feature selection algorithms prior to classification algorithms results in better accuracy than when the latter are applied alone. This conclusion is important and significant to industry and society. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Call for a Computer-Aided Cancer Detection and Classification Research Initiative in Oman.

    Science.gov (United States)

    Mirzal, Andri; Chaudhry, Shafique Ahmad

    2016-01-01

    Cancer is a major health problem in Oman. It is reported that cancer incidence in Oman is the second highest after Saudi Arabia among Gulf Cooperation Council countries. Based on GLOBOCAN estimates, Oman is predicted to face an almost two-fold increase in cancer incidence in the period 2008-2020. However, cancer research in Oman is still in its infancy. This is due to the fact that medical institutions and infrastructure that play central roles in data collection and analysis are relatively new developments in Oman. We believe the country requires an organized plan and efforts to promote local cancer research. In this paper, we discuss current research progress in cancer diagnosis using machine learning techniques to optimize computer aided cancer detection and classification (CAD). We specifically discuss CAD using two major medical data, i.e., medical imaging and microarray gene expression profiling, because medical imaging like mammography, MRI, and PET have been widely used in Oman for assisting radiologists in early cancer diagnosis and microarray data have been proven to be a reliable source for differential diagnosis. We also discuss future cancer research directions and benefits to Oman economy for entering the cancer research and treatment business as it is a multi-billion dollar industry worldwide.

  18. Alternative Polyadenylation Patterns for Novel Gene Discovery and Classification in Cancer

    Directory of Open Access Journals (Sweden)

    Oguzhan Begik

    2017-07-01

    Full Text Available Certain aspects of diagnosis, prognosis, and treatment of cancer patients are still important challenges to be addressed. Therefore, we propose a pipeline to uncover patterns of alternative polyadenylation (APA, a hidden complexity in cancer transcriptomes, to further accelerate efforts to discover novel cancer genes and pathways. Here, we analyzed expression data for 1045 cancer patients and found a significant shift in usage of poly(A signals in common tumor types (breast, colon, lung, prostate, gastric, and ovarian compared to normal tissues. Using machine-learning techniques, we further defined specific subsets of APA events to efficiently classify cancer types. Furthermore, APA patterns were associated with altered protein levels in patients, revealed by antibody-based profiling data, suggesting functional significance. Overall, our study offers a computational approach for use of APA in novel gene discovery and classification in common tumor types, with important implications in basic research, biomarker discovery, and precision medicine approaches.

  19. EMT is the dominant program in human colon cancer

    Directory of Open Access Journals (Sweden)

    Tollenaar Rob AEM

    2011-01-01

    Full Text Available Abstract Background Colon cancer has been classically described by clinicopathologic features that permit the prediction of outcome only after surgical resection and staging. Methods We performed an unsupervised analysis of microarray data from 326 colon cancers to identify the first principal component (PC1 of the most variable set of genes. PC1 deciphered two primary, intrinsic molecular subtypes of colon cancer that predicted disease progression and recurrence. Results Here we report that the most dominant pattern of intrinsic gene expression in colon cancer (PC1 was tightly correlated (Pearson R = 0.92, P -135 with the EMT signature-- both in gene identity and directionality. In a global micro-RNA screen, we further identified the most anti-correlated microRNA with PC1 as MiR200, known to regulate EMT. Conclusions These data demonstrate that the biology underpinning the native, molecular classification of human colon cancer--previously thought to be highly heterogeneous-- was clarified through the lens of comprehensive transcriptome analysis.

  20. [The physiological classification of human thermal states under high environmental temperatures].

    Science.gov (United States)

    Bobrov, A F; Kuznets, E I

    1995-01-01

    The paper deals with the physiological classification of human thermal states in a hot environment. A review of the basic systems of classifications of thermal states is given, their main drawbacks are discussed. On the basis of human functional state research in a broad range of environmental temperatures the system of evaluation and classification of human thermal states is proposed. New integral one-dimensional multi-parametric criteria for evaluation are used. For the development of these criteria methods of factor, cluster and canonical correlation analyses are applied. Stochastic nomograms capable of identification of human thermal state for different intensity of influence are given. In this case evaluation of intensity is estimated according to one-dimensional criteria taking into account environmental temperature, physical load and time of man's staying in overheating conditions.

  1. Immunogenomic Classification of Colorectal Cancer and Therapeutic Implications

    Directory of Open Access Journals (Sweden)

    Jessica Roelands

    2017-10-01

    Full Text Available The immune system has a substantial effect on colorectal cancer (CRC progression. Additionally, the response to immunotherapeutics and conventional treatment options (e.g., chemotherapy, radiotherapy and targeted therapies is influenced by the immune system. The molecular characterization of colorectal cancer (CRC has led to the identification of favorable and unfavorable immunological attributes linked to clinical outcome. With the definition of consensus molecular subtypes (CMSs based on transcriptomic profiles, multiple characteristics have been proposed to be responsible for the development of the tumor immune microenvironment and corresponding mechanisms of immune escape. In this review, a detailed description of proposed immune phenotypes as well as their interaction with different therapeutic modalities will be provided. Finally, possible strategies to shift the CRC immune phenotype towards a reactive, anti-tumor orientation are proposed per CMS.

  2. Environmental and genetic interactions in human cancer

    International Nuclear Information System (INIS)

    Paterson, M.C.

    Humans, depending upon their genetic make-up, differ in their susceptibility to the cancer-causing effects of extrinsic agents. Clinical and laboratory studies on the hereditary disorder, ataxia telangiectasia (AT) show that persons afflicted with this are cancer-prone and unusually sensitive to conventional radiotherapy. Their skin cells, when cultured, are hypersensitive to killing by ionizing radiation, being defective in the enzymatic repair of radiation-induced damange to the genetic material, deoxyribonucleic acid (DNA). This molecular finding implicates DNA damage and its imperfect repair as an early step in the induction of human cancer by radiation and other carcinogens. The parents of AT patients are clincally normal but their cultured cells are often moderately radiosensitive. The increased radiosensitivity of cultured cells offers a means of identifying a presumed cancer-prone subpopulation that should avoid undue exposure to certain carcinogens. The radioresponse of cells from patients with other cancer-associated genetic disorders and persons suspected of being genetically predisposed to radiation-induced cancer has also been measured. Increased cell killing by γ-rays appears in the complex genetic disease, tuberous sclerosis. Cells from cancer-stricken members of a leukemia-prone family are also radiosensitive, as are cells from one patient with radiation-associated breast cancer. These radiobiological data, taken together, strongly suggest that genetic factors can interact with extrinsic agents and thereby play a greater causative role in the development of common cancers in man than previously thought. (L.L.)

  3. Human pancreatic cancer xenografts recapitulate key aspects of cancer cachexia.

    Science.gov (United States)

    Delitto, Daniel; Judge, Sarah M; Delitto, Andrea E; Nosacka, Rachel L; Rocha, Fernanda G; DiVita, Bayli B; Gerber, Michael H; George, Thomas J; Behrns, Kevin E; Hughes, Steven J; Wallet, Shannon M; Judge, Andrew R; Trevino, Jose G

    2017-01-03

    Cancer cachexia represents a debilitating syndrome that diminishes quality of life and augments the toxicities of conventional treatments. Cancer cachexia is particularly debilitating in patients with pancreatic cancer (PC). Mechanisms responsible for cancer cachexia are under investigation and are largely derived from observations in syngeneic murine models of cancer which are limited in PC. We evaluate the effect of human PC cells on both muscle wasting and the systemic inflammatory milieu potentially contributing to PC-associated cachexia. Specifically, human PC xenografts were generated by implantation of pancreatic cancer cells, L3.6pl and PANC-1, either in the flank or orthotopically within the pancreas. Mice bearing orthotopic xenografts demonstrated significant muscle wasting and atrophy-associated gene expression changes compared to controls. Further, despite the absence of adaptive immunity, splenic tissue from orthotopically engrafted mice demonstrated elevations in several pro-inflammatory cytokines associated with cancer cachexia, including TNFα, IL1β, IL6 and KC (murine IL8 homologue), when compared to controls. Therefore, data presented here support further investigation into the complexity of cancer cachexia in PC to identify potential targets for this debilitating syndrome.

  4. Impact of full field digital mammography on the classification and mammographic characteristics of interval breast cancers

    Energy Technology Data Exchange (ETDEWEB)

    Knox, Mark, E-mail: marktknox@gmail.com; O’Brien, Angela, E-mail: angelaobrien@doctors.org.uk; Szabó, Endre, E-mail: endrebacsi@freemail.hu; Smith, Clare S., E-mail: csmith@mater.ie; Fenlon, Helen M., E-mail: helen.fenlon@cancerscreening.ie; McNicholas, Michelle M., E-mail: michelle.mcnicholas@cancerscreening.ie; Flanagan, Fidelma L., E-mail: fidelma.flanagan@cancerscreening.ie

    2015-06-15

    Highlights: • Digital mammography has changed the presentation of interval breast cancer. • Less interval breast cancers are associated with microcalcifications following FFDM. • Interval breast cancer audit remains a key feature of any breast screening program. - Abstract: Objective: Full field digital mammography (FFDM) is increasingly replacing screen film mammography (SFM) in breast screening programs. Interval breast cancers are an issue in all screening programs and the purpose of our study is to assess the impact of FFDM on the classification of interval breast cancers at independent blind review and to compare the mammographic features of interval cancers at FFDM and SFM. Materials and methods: This study included 138 cases of interval breast cancer, 76 following an FFDM screening examination and 62 following screening with SFM. The prior screening mammogram was assessed by each of five consultant breast radiologists who were blinded to the site of subsequent cancer. Subsequent review of the diagnostic mammogram was performed and cases were classified as missed, minimal signs, occult or true interval. Mammographic features of the interval cancer at diagnosis and any abnormality identified on the prior screening mammogram were recorded. Results: The percentages of cancers classified as missed at FFDM and SFM did not differ significantly, 10.5% (8 of 76) at FFDM and 8.1% (5 of 62) at SFM (p = .77). There were significantly less interval cancers presenting as microcalcifications (alone or in association with another abnormality) following screening with FFDM, 16% (12 of 76) than following a SFM examination, 32% (20 of 62) (p = .02). Conclusion: Interval breast cancers continue to pose a problem at FFDM. The switch to FFDM has changed the mammographic presentation of interval breast cancer, with less interval cancers presenting in association with microcalcifications.

  5. Impact of full field digital mammography on the classification and mammographic characteristics of interval breast cancers

    International Nuclear Information System (INIS)

    Knox, Mark; O’Brien, Angela; Szabó, Endre; Smith, Clare S.; Fenlon, Helen M.; McNicholas, Michelle M.; Flanagan, Fidelma L.

    2015-01-01

    Highlights: • Digital mammography has changed the presentation of interval breast cancer. • Less interval breast cancers are associated with microcalcifications following FFDM. • Interval breast cancer audit remains a key feature of any breast screening program. - Abstract: Objective: Full field digital mammography (FFDM) is increasingly replacing screen film mammography (SFM) in breast screening programs. Interval breast cancers are an issue in all screening programs and the purpose of our study is to assess the impact of FFDM on the classification of interval breast cancers at independent blind review and to compare the mammographic features of interval cancers at FFDM and SFM. Materials and methods: This study included 138 cases of interval breast cancer, 76 following an FFDM screening examination and 62 following screening with SFM. The prior screening mammogram was assessed by each of five consultant breast radiologists who were blinded to the site of subsequent cancer. Subsequent review of the diagnostic mammogram was performed and cases were classified as missed, minimal signs, occult or true interval. Mammographic features of the interval cancer at diagnosis and any abnormality identified on the prior screening mammogram were recorded. Results: The percentages of cancers classified as missed at FFDM and SFM did not differ significantly, 10.5% (8 of 76) at FFDM and 8.1% (5 of 62) at SFM (p = .77). There were significantly less interval cancers presenting as microcalcifications (alone or in association with another abnormality) following screening with FFDM, 16% (12 of 76) than following a SFM examination, 32% (20 of 62) (p = .02). Conclusion: Interval breast cancers continue to pose a problem at FFDM. The switch to FFDM has changed the mammographic presentation of interval breast cancer, with less interval cancers presenting in association with microcalcifications

  6. From Molecular Classification to Targeted Therapeutics: The Changing Face of Systemic Therapy in Metastatic Gastroesophageal Cancer

    Directory of Open Access Journals (Sweden)

    Adrian Murphy

    2015-01-01

    Full Text Available Histological classification of adenocarcinoma or squamous cell carcinoma for esophageal cancer or using the Lauren classification for intestinal and diffuse type gastric cancer has limited clinical utility in the management of advanced disease. Germline mutations in E-cadherin (CDH1 or mismatch repair genes (Lynch syndrome were identified many years ago but given their rarity, the identification of these molecular alterations does not substantially impact treatment in the advanced setting. Recent molecular profiling studies of upper GI tumors have added to our knowledge of the underlying biology but have not led to an alternative classification system which can guide clinician’s therapeutic decisions. Recently the Cancer Genome Atlas Research Network has proposed four subtypes of gastric cancer dividing tumors into those positive for Epstein-Barr virus, microsatellite unstable tumors, genomically stable tumors, and tumors with chromosomal instability. Unfortunately to date, many phase III clinical trials involving molecularly targeted agents have failed to meet their survival endpoints due to their use in unselected populations. Future clinical trials should utilize molecular profiling of individual tumors in order to determine the optimal use of targeted therapies in preselected patients.

  7. A protein and mRNA expression-based classification of gastric cancer.

    Science.gov (United States)

    Setia, Namrata; Agoston, Agoston T; Han, Hye S; Mullen, John T; Duda, Dan G; Clark, Jeffrey W; Deshpande, Vikram; Mino-Kenudson, Mari; Srivastava, Amitabh; Lennerz, Jochen K; Hong, Theodore S; Kwak, Eunice L; Lauwers, Gregory Y

    2016-07-01

    The overall survival of gastric carcinoma patients remains poor despite improved control over known risk factors and surveillance. This highlights the need for new classifications, driven towards identification of potential therapeutic targets. Using sophisticated molecular technologies and analysis, three groups recently provided genetic and epigenetic molecular classifications of gastric cancer (The Cancer Genome Atlas, 'Singapore-Duke' study, and Asian Cancer Research Group). Suggested by these classifications, here, we examined the expression of 14 biomarkers in a cohort of 146 gastric adenocarcinomas and performed unsupervised hierarchical clustering analysis using less expensive and widely available immunohistochemistry and in situ hybridization. Ultimately, we identified five groups of gastric cancers based on Epstein-Barr virus (EBV) positivity, microsatellite instability, aberrant E-cadherin, and p53 expression; the remaining cases constituted a group characterized by normal p53 expression. In addition, the five categories correspond to the reported molecular subgroups by virtue of clinicopathologic features. Furthermore, evaluation between these clusters and survival using the Cox proportional hazards model showed a trend for superior survival in the EBV and microsatellite-instable related adenocarcinomas. In conclusion, we offer as a proposal a simplified algorithm that is able to reproduce the recently proposed molecular subgroups of gastric adenocarcinoma, using immunohistochemical and in situ hybridization techniques.

  8. An NRG Oncology/GOG study of molecular classification for risk prediction in endometrioid endometrial cancer.

    Science.gov (United States)

    Cosgrove, Casey M; Tritchler, David L; Cohn, David E; Mutch, David G; Rush, Craig M; Lankes, Heather A; Creasman, William T; Miller, David S; Ramirez, Nilsa C; Geller, Melissa A; Powell, Matthew A; Backes, Floor J; Landrum, Lisa M; Timmers, Cynthia; Suarez, Adrian A; Zaino, Richard J; Pearl, Michael L; DiSilvestro, Paul A; Lele, Shashikant B; Goodfellow, Paul J

    2018-01-01

    The purpose of this study was to assess the prognostic significance of a simplified, clinically accessible classification system for endometrioid endometrial cancers combining Lynch syndrome screening and molecular risk stratification. Tumors from NRG/GOG GOG210 were evaluated for mismatch repair defects (MSI, MMR IHC, and MLH1 methylation), POLE mutations, and loss of heterozygosity. TP53 was evaluated in a subset of cases. Tumors were assigned to four molecular classes. Relationships between molecular classes and clinicopathologic variables were assessed using contingency tests and Cox proportional methods. Molecular classification was successful for 982 tumors. Based on the NCI consensus MSI panel assessing MSI and loss of heterozygosity combined with POLE testing, 49% of tumors were classified copy number stable (CNS), 39% MMR deficient, 8% copy number altered (CNA) and 4% POLE mutant. Cancer-specific mortality occurred in 5% of patients with CNS tumors; 2.6% with POLE tumors; 7.6% with MMR deficient tumors and 19% with CNA tumors. The CNA group had worse progression-free (HR 2.31, 95%CI 1.53-3.49) and cancer-specific survival (HR 3.95; 95%CI 2.10-7.44). The POLE group had improved outcomes, but the differences were not statistically significant. CNA class remained significant for cancer-specific survival (HR 2.11; 95%CI 1.04-4.26) in multivariable analysis. The CNA molecular class was associated with TP53 mutation and expression status. A simple molecular classification for endometrioid endometrial cancers that can be easily combined with Lynch syndrome screening provides important prognostic information. These findings support prospective clinical validation and further studies on the predictive value of a simplified molecular classification system. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Modeling Human Cancers in Drosophila.

    Science.gov (United States)

    Sonoshita, M; Cagan, R L

    2017-01-01

    Cancer is a complex disease that affects multiple organs. Whole-body animal models provide important insights into oncology that can lead to clinical impact. Here, we review novel concepts that Drosophila studies have established for cancer biology, drug discovery, and patient therapy. Genetic studies using Drosophila have explored the roles of oncogenes and tumor-suppressor genes that when dysregulated promote cancer formation, making Drosophila a useful model to study multiple aspects of transformation. Not limited to mechanism analyses, Drosophila has recently been showing its value in facilitating drug development. Flies offer rapid, efficient platforms by which novel classes of drugs can be identified as candidate anticancer leads. Further, we discuss the use of Drosophila as a platform to develop therapies for individual patients by modeling the tumor's genetic complexity. Drosophila provides both a classical and a novel tool to identify new therapeutics, complementing other more traditional cancer tools. © 2017 Elsevier Inc. All rights reserved.

  10. AN ADABOOST OPTIMIZED CCFIS BASED CLASSIFICATION MODEL FOR BREAST CANCER DETECTION

    Directory of Open Access Journals (Sweden)

    CHANDRASEKAR RAVI

    2017-06-01

    Full Text Available Classification is a Data Mining technique used for building a prototype of the data behaviour, using which an unseen data can be classified into one of the defined classes. Several researchers have proposed classification techniques but most of them did not emphasis much on the misclassified instances and storage space. In this paper, a classification model is proposed that takes into account the misclassified instances and storage space. The classification model is efficiently developed using a tree structure for reducing the storage complexity and uses single scan of the dataset. During the training phase, Class-based Closed Frequent ItemSets (CCFIS were mined from the training dataset in the form of a tree structure. The classification model has been developed using the CCFIS and a similarity measure based on Longest Common Subsequence (LCS. Further, the Particle Swarm Optimization algorithm is applied on the generated CCFIS, which assigns weights to the itemsets and their associated classes. Most of the classifiers are correctly classifying the common instances but they misclassify the rare instances. In view of that, AdaBoost algorithm has been used to boost the weights of the misclassified instances in the previous round so as to include them in the training phase to classify the rare instances. This improves the accuracy of the classification model. During the testing phase, the classification model is used to classify the instances of the test dataset. Breast Cancer dataset from UCI repository is used for experiment. Experimental analysis shows that the accuracy of the proposed classification model outperforms the PSOAdaBoost-Sequence classifier by 7% superior to other approaches like Naïve Bayes Classifier, Support Vector Machine Classifier, Instance Based Classifier, ID3 Classifier, J48 Classifier, etc.

  11. Novel innate cancer killing activity in humans

    Directory of Open Access Journals (Sweden)

    Lovato James

    2011-08-01

    Full Text Available Abstract Background In this study, we pilot tested an in vitro assay of cancer killing activity (CKA in circulating leukocytes of 22 cancer cases and 25 healthy controls. Methods Using a human cervical cancer cell line, HeLa, as target cells, we compared the CKA in circulating leukocytes, as effector cells, of cancer cases and controls. The CKA was normalized as percentages of total target cells during selected periods of incubation time and at selected effector/target cell ratios in comparison to no-effector-cell controls. Results Our results showed that CKA similar to that of our previous study of SR/CR mice was present in human circulating leukocytes but at profoundly different levels in individuals. Overall, males have a significantly higher CKA than females. The CKA levels in cancer cases were lower than that in healthy controls (mean ± SD: 36.97 ± 21.39 vs. 46.28 ± 27.22. Below-median CKA was significantly associated with case status (odds ratio = 4.36; 95% Confidence Interval = 1.06, 17.88 after adjustment of gender and race. Conclusions In freshly isolated human leukocytes, we were able to detect an apparent CKA in a similar manner to that of cancer-resistant SR/CR mice. The finding of CKA at lower levels in cancer patients suggests the possibility that it may be of a consequence of genetic, physiological, or pathological conditions, pending future studies with larger sample size.

  12. Computed tomography and the TNM classification of lung cancer

    International Nuclear Information System (INIS)

    Sparup, J.; Friis, M.; Brenoee, J.; Vejlsted, H.; Villumsen, B.; Olesen, K.P.; Borgeskov, S.; Bertelsen, S.

    1990-01-01

    Computed tomography (CT)of the thorax and upper abdomen was prospectively evaluated in 84 patients with potentially operable lung cancer. Invasion into the thoracic wall and the mediastinal structures was not accurately demonstrated by CT. For metastatic mediastinal lymph nodes, the sensitivity and specificity of CT were, respectively, 86 per cent and 61 per cent and the positive and negative predictive indices 49 per cent and 91 per cent. For T1, T2 and T3 tumours the negative indices were 100 per cent, 96 per cent and 71 per cent. Positive predictive index did not differ between squamous cell carcinoma and adenocarcinoma. Adrenal metastases were CT-suspected in 17 cases and liver metastases in eight, but were verified by ultrasonography in only one and four cases. CT should be used in preoperative investigation of lung cancer, irrespective of stage. Demonstration of thoracic-wall or mediastinal invasion need not exclude tumour resection. Preoperative mediastinoscopy is indicated if CT shows nodal metastases or if there are signs of tumour invasion, but not in CT-negative T1 or T2 tumour. Abdominal metastases indicated by CT should be investigated with CT-guided needle biopsy. (authors)

  13. FEATURE EXTRACTION BASED WAVELET TRANSFORM IN BREAST CANCER DIAGNOSIS USING FUZZY AND NON-FUZZY CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Pelin GORGEL

    2013-01-01

    Full Text Available This study helps to provide a second eye to the expert radiologists for the classification of manually extracted breast masses taken from 60 digital mammıgrams. These mammograms have been acquired from Istanbul University Faculty of Medicine Hospital and have 78 masses. The diagnosis is implemented with pre-processing by using feature extraction based Fast Wavelet Transform (FWT. Afterwards Adaptive Neuro-Fuzzy Inference System (ANFIS based fuzzy subtractive clustering and Support Vector Machines (SVM methods are used for the classification. It is a comparative study which uses these methods respectively. According to the results of the study, ANFIS based subtractive clustering produces ??% while SVM produces ??% accuracy in malignant-benign classification. The results demonstrate that the developed system could help the radiologists for a true diagnosis and decrease the number of the missing cancerous regions or unnecessary biopsies.

  14. A novel method for human age group classification based on

    Directory of Open Access Journals (Sweden)

    Anuradha Yarlagadda

    2015-10-01

    Full Text Available In the computer vision community, easy categorization of a person’s facial image into various age groups is often quite precise and is not pursued effectively. To address this problem, which is an important area of research, the present paper proposes an innovative method of age group classification system based on the Correlation Fractal Dimension of complex facial image. Wrinkles appear on the face with aging thereby changing the facial edges of the image. The proposed method is rotation and poses invariant. The present paper concentrates on developing an innovative technique that classifies facial images into four categories i.e. child image (0–15, young adult image (15–30, middle-aged adult image (31–50, and senior adult image (>50 based on correlation FD value of a facial edge image.

  15. Cross-Disciplinary Analysis of Lymph Node Classification in Lung Cancer on CT Scanning.

    Science.gov (United States)

    El-Sherief, Ahmed H; Lau, Charles T; Obuchowski, Nancy A; Mehta, Atul C; Rice, Thomas W; Blackstone, Eugene H

    2017-04-01

    Accurate and consistent regional lymph node classification is an important element in the staging and multidisciplinary management of lung cancer. Regional lymph node definition sets-lymph node maps-have been created to standardize regional lymph node classification. In 2009, the International Association for the Study of Lung Cancer (IASLC) introduced a lymph node map to supersede all preexisting lymph node maps. Our aim was to study if and how lung cancer specialists apply the IASLC lymph node map when classifying thoracic lymph nodes encountered on CT scans during lung cancer staging. From April 2013 through July 2013, invitations were distributed to all members of the Fleischner Society, Society of Thoracic Radiology, General Thoracic Surgical Club, and the American Association of Bronchology and Interventional Pulmonology to participate in an anonymous online image-based and text-based 20-question survey regarding lymph node classification for lung cancer staging on CT imaging. Three hundred thirty-seven people responded (approximately 25% participation). Respondents consisted of self-reported thoracic radiologists (n = 158), thoracic surgeons (n = 102), and pulmonologists who perform endobronchial ultrasonography (n = 77). Half of the respondents (50%; 95% CI, 44%-55%) reported using the IASLC lymph node map in daily practice, with no significant differences between subspecialties. A disparity was observed between the IASLC definition sets and their interpretation and application on CT scans, in particular for lymph nodes near the thoracic inlet, anterior to the trachea, anterior to the tracheal bifurcation, near the ligamentum arteriosum, between the bronchus intermedius and esophagus, in the internal mammary space, and adjacent to the heart. Use of older lymph node maps and inconsistencies in interpretation and application of definitions in the IASLC lymph node map may potentially lead to misclassification of stage and suboptimal management of lung

  16. The Future of Asset Management for Human Space Exploration: Supply Classification and an Integrated Database

    Science.gov (United States)

    Shull, Sarah A.; Gralla, Erica L.; deWeck, Olivier L.; Shishko, Robert

    2006-01-01

    One of the major logistical challenges in human space exploration is asset management. This paper presents observations on the practice of asset management in support of human space flight to date and discusses a functional-based supply classification and a framework for an integrated database that could be used to improve asset management and logistics for human missions to the Moon, Mars and beyond.

  17. Human papilloma viruses (HPV and breast cancer.

    Directory of Open Access Journals (Sweden)

    James Sutherland Lawson

    2015-12-01

    Full Text Available Purpose: Human papillomaviruses (HPV may have a role in some breast cancers. The purpose of this study is to fill important gaps in the evidence. These gaps are: (i confirmation of the presence of high risk for cancer HPVs in breast cancers, (ii evidence of HPV infections in benign breast tissues prior to the development of HPV positive breast cancer in the same patients, (iii evidence that HPVs are biologically active and not harmless passengers in breast cancer.Methods: RNA-seq data from The Cancer Genome Atlas (TCGA was used to identify HPV RNA sequences in breast cancers. We also conducted a retrospective cohort study based on polymerase chain reaction (PCR analyses to identify HPVs in archival specimens from Australian women with benign breast biopsies who later developed breast cancer. To assess whether HPVs in breast cancer were biologically active, the expression of the oncogenic protein HPV E7 was assessed by immunohistochemistry (IHC.Results: Thirty (3.5% low risk and 20 (2.3% high risk HPV types were identified in 855 breast cancers from the TCGA data base. The high risk types were HPV 18 (48%, HPV 113 (24%, HPV 16 (10%, HPV 52 (10%. Data from the PCR cohort study, indicated that HPV type 18 was the most common type identified in breast cancer specimens (55% of 40 breast cancer specimens followed by HPV 16 (13%. The same HPV type was identified in both the benign and subsequent breast cancer in 15 patients. HPV E7 proteins were identified in 72% of benign breast specimens and 59% of invasive breast cancer specimens.Conclusions: There were 4 observations of particular interest: (i confirmation by both NGS and PCR of the presence of high risk HPV gene sequences in breast cancers, (ii a correlation between high risk HPV in benign breast specimens and subsequent HPV positive breast cancer in the same patient, (iii HPVs in breast cancer are likely to be biologically active (as shown by transcription of HPV DNA to RNA plus the expression of

  18. Prevalence of Telomerase Activity in Human Cancer

    Directory of Open Access Journals (Sweden)

    Chi-Hau Chen

    2011-05-01

    Full Text Available Telomerase activity has been measured in a wide variety of cancerous and non-cancerous tissue types, and the vast majority of clinical studies have shown a direct correlation between it and the presence of cancerous cells. Telomerase plays a key role in cellular immortality and tumorigenesis. Telomerase is activated in 80–90% of human carcinomas, but not in normal somatic cells, therefore, its detection holds promise as a diagnostic marker for cancer. Measurable levels of telomerase have been detected in malignant cells from various samples: tissue from gestational trophoblastic neoplasms; squamous carcinoma cells from oral rinses; lung carcinoma cells from bronchial washings; colorectal carcinoma cells from colonic luminal washings; bladder carcinoma cells from urine or bladder washings; and breast carcinoma or thyroid cancer cells from fine needle aspirations. Such clinical tests for telomerase can be useful as non-invasive and cost-effective methods for early detection and monitoring of cancer. In addition, telomerase activity has been shown to correlate with poor clinical outcome in late-stage diseases such as non-small cell lung cancer, colorectal cancer, and soft tissue sarcomas. In such cases, testing for telomerase activity can be used to identify patients with a poor prognosis and to select those who might benefit from adjuvant treatment. Our review of the latest medical advances in this field reveals that telomerase holds great promise as a biomarker for early cancer detection and monitoring, and has considerable potential as the basis for developing new anticancer therapies.

  19. Radiobiology of human cancer radiotherapy

    International Nuclear Information System (INIS)

    Andrews, J.R.

    1978-01-01

    The author has systematically collected and collated the scientific literature correlating the basic and clinical sciences in this field in order to produce a definitive treatise. The book thoroughly reviews the biology and biochemistry relevant to radiobiology and describes the critical locus for the extinction of cell reproductive capacity. Extensive coverage is given to oxygen effect, hyperthermia, high linear energy transfer, cell populations, and similar topics. Separate sections cover time, dose, and fractionation; radiation hematology; cancer chemotherapy; and cancer immunology. The book also contains invaluable discussions of techniques for optimizing radiotherapy alone and in combination with other therapies

  20. Rough set soft computing cancer classification and network: one stone, two birds.

    Science.gov (United States)

    Zhang, Yue

    2010-07-15

    Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article.

  1. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

    DEFF Research Database (Denmark)

    Hoadley, Katherine A; Yau, Christina; Wolf, Denise M

    2014-01-01

    Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform...... on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset...

  2. Classification of alarm processing techniques and human performance issues

    International Nuclear Information System (INIS)

    Kim, I.S.; O'Hara, J.M.

    1993-01-01

    Human factors reviews indicate that conventional alarm systems based on the one sensor, one alarm approach, have many human engineering deficiencies, a paramount example being too many alarms during major disturbances. As an effort to resolve these deficiencies, various alarm processing systems have been developed using different techniques. To ensure their contribution to operational safety, the impacts of those systems on operating crew performance should be carefully evaluated. This paper briefly reviews some of the human factors research issues associated with alarm processing techniques and then discusses a framework with which to classify the techniques. The dimensions of this framework can be used to explore the effects of alarm processing systems on human performance

  3. Classification of alarm processing techniques and human performance issues

    Energy Technology Data Exchange (ETDEWEB)

    Kim, I.S.; O' Hara, J.M.

    1993-01-01

    Human factors reviews indicate that conventional alarm systems based on the one sensor, one alarm approach, have many human engineering deficiencies, a paramount example being too many alarms during major disturbances. As an effort to resolve these deficiencies, various alarm processing systems have been developed using different techniques. To ensure their contribution to operational safety, the impacts of those systems on operating crew performance should be carefully evaluated. This paper briefly reviews some of the human factors research issues associated with alarm processing techniques and then discusses a framework with which to classify the techniques. The dimensions of this framework can be used to explore the effects of alarm processing systems on human performance.

  4. Classification of alarm processing techniques and human performance issues

    Energy Technology Data Exchange (ETDEWEB)

    Kim, I.S.; O`Hara, J.M.

    1993-05-01

    Human factors reviews indicate that conventional alarm systems based on the one sensor, one alarm approach, have many human engineering deficiencies, a paramount example being too many alarms during major disturbances. As an effort to resolve these deficiencies, various alarm processing systems have been developed using different techniques. To ensure their contribution to operational safety, the impacts of those systems on operating crew performance should be carefully evaluated. This paper briefly reviews some of the human factors research issues associated with alarm processing techniques and then discusses a framework with which to classify the techniques. The dimensions of this framework can be used to explore the effects of alarm processing systems on human performance.

  5. Early detection of lung cancer from CT images: nodule segmentation and classification using deep learning

    Science.gov (United States)

    Sharma, Manu; Bhatt, Jignesh S.; Joshi, Manjunath V.

    2018-04-01

    Lung cancer is one of the most abundant causes of the cancerous deaths worldwide. It has low survival rate mainly due to the late diagnosis. With the hardware advancements in computed tomography (CT) technology, it is now possible to capture the high resolution images of lung region. However, it needs to be augmented by efficient algorithms to detect the lung cancer in the earlier stages using the acquired CT images. To this end, we propose a two-step algorithm for early detection of lung cancer. Given the CT image, we first extract the patch from the center location of the nodule and segment the lung nodule region. We propose to use Otsu method followed by morphological operations for the segmentation. This step enables accurate segmentation due to the use of data-driven threshold. Unlike other methods, we perform the segmentation without using the complete contour information of the nodule. In the second step, a deep convolutional neural network (CNN) is used for the better classification (malignant or benign) of the nodule present in the segmented patch. Accurate segmentation of even a tiny nodule followed by better classification using deep CNN enables the early detection of lung cancer. Experiments have been conducted using 6306 CT images of LIDC-IDRI database. We achieved the test accuracy of 84.13%, with the sensitivity and specificity of 91.69% and 73.16%, respectively, clearly outperforming the state-of-the-art algorithms.

  6. Subtype classification for prediction of prognosis of breast cancer from a biomarker panel: correlations and indications

    Directory of Open Access Journals (Sweden)

    Chen C

    2014-02-01

    Full Text Available Chuang Chen,1 Jing-Ping Yuan,2,3 Wen Wei,1 Yi Tu,1 Feng Yao,1 Xue-Qin Yang,4 Jin-Zhong Sun,1 Sheng-Rong Sun,1 Yan Li2 1Department of Breast and Thyroid Surgery, Wuhan University, Renmin Hospital, Wuhan, 2Department of Oncology, Zhongnan Hospital of Wuhan University and Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, Wuhan, 3Department of Pathology, The Central Hospital of Wuhan, Wuhan, 4Medical School of Jingchu University of Technology, Jingmen, People’s Republic of China Background: Hormone receptors, including the estrogen receptor and progesterone receptor, human epidermal growth factor receptor 2 (HER2, and other biomarkers like Ki67, epidermal growth factor receptor (EGFR, also known as HER1, the androgen receptor, and p53, are key molecules in breast cancer. This study evaluated the relationship between HER2 and hormone receptors and explored the additional prognostic value of Ki67, EGFR, the androgen receptor, and p53. Methods: Quantitative determination of HER2 and EGFR was performed in 240 invasive breast cancer tissue microarray specimens using quantum dot (QD-based nanotechnology. We identified two subtypes of HER2, ie, high total HER2 load (HTH2 and low total HER2 load (LTH2, and three subtypes of hormone receptor, ie, high hormone receptor (HHR, low hormone receptor (LHR, and no hormone receptor (NHR. Therefore, breast cancer patients could be divided into five subtypes according to HER2 and hormone receptor status. Ki67, p53, and the androgen receptor were determined by traditional immunohistochemistry techniques. The relationship between hormone receptors and HER2 was investigated and the additional value of Ki67, EGFR, the androgen receptor, and p53 for prediction of 5-year disease-free survival was assessed. Results: In all patients, quantitative determination showed a statistically significant (P<0.001 negative correlation between HER2 and the hormone receptors and a significant

  7. Classification of breast cancer patients using somatic mutation profiles and machine learning approaches.

    Science.gov (United States)

    Vural, Suleyman; Wang, Xiaosheng; Guda, Chittibabu

    2016-08-26

    The high degree of heterogeneity observed in breast cancers makes it very difficult to classify the cancer patients into distinct clinical subgroups and consequently limits the ability to devise effective therapeutic strategies. Several classification strategies based on ER/PR/HER2 expression or the expression profiles of a panel of genes have helped, but such methods often produce misleading results due to their dynamic nature. In contrast, somatic DNA mutations are relatively stable and lead to initiation and progression of many sporadic cancers. Hence in this study, we explore the use of gene mutation profiles to classify, characterize and predict the subgroups of breast cancers. We analyzed the whole exome sequencing data from 358 ethnically similar breast cancer patients in The Cancer Genome Atlas (TCGA) project. Somatic and non-synonymous single nucleotide variants identified from each patient were assigned a quantitative score (C-score) that represents the extent of negative impact on the gene function. Using these scores with non-negative matrix factorization method, we clustered the patients into three subgroups. By comparing the clinical stage of patients, we identified an early-stage-enriched and a late-stage-enriched subgroup. Comparison of the mutation scores of early and late-stage-enriched subgroups identified 358 genes that carry significantly higher mutations rates in the late stage subgroup. Functional characterization of these genes revealed important functional gene families that carry a heavy mutational load in the late state rich subgroup of patients. Finally, using the identified subgroups, we also developed a supervised classification model to predict the stage of the patients. This study demonstrates that gene mutation profiles can be effectively used with unsupervised machine-learning methods to identify clinically distinguishable breast cancer subgroups. The classification model developed in this method could provide a reasonable

  8. Long-term Prostate-specific Antigen Velocity in Improved Classification of Prostate Cancer Risk and Mortality

    DEFF Research Database (Denmark)

    Ørsted, David Dynnes; Bojesen, Stig E; Kamstrup, Pia R

    2013-01-01

    BACKGROUND: It remains unclear whether adding long-term prostate-specific antigen velocity (PSAV) to baseline PSA values improves classification of prostate cancer (PCa) risk and mortality in the general population. OBJECTIVE: To determine whether long-term PSAV improves classification of PCa risk...

  9. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  10. Setting a generalized functional linear model (GFLM for the classification of different types of cancer

    Directory of Open Access Journals (Sweden)

    Miguel Flores

    2016-11-01

    Full Text Available This work aims to classify the DNA sequences of healthy and malignant cancer respectively. For this, supervised and unsupervised classification methods from a functional context are used; i.e. each strand of DNA is an observation. The observations are discretized, for that reason different ways to represent these observations with functions are evaluated. In addition, an exploratory study is done: estimating the mean and variance of each functional type of cancer. For the unsupervised classification method, hierarchical clustering with different measures of functional distance is used. On the other hand, for the supervised classification method, a functional generalized linear model is used. For this model the first and second derivatives are used which are included as discriminating variables. It has been verified that one of the advantages of working in the functional context is to obtain a model to correctly classify cancers by 100%. For the implementation of the methods it has been used the fda.usc R package that includes all the techniques of functional data analysis used in this work. In addition, some that have been developed in recent decades. For more details of these techniques can be consulted Ramsay, J. O. and Silverman (2005 and Ferraty et al. (2006.

  11. Training ANFIS structure using genetic algorithm for liver cancer classification based on microarray gene expression data

    Directory of Open Access Journals (Sweden)

    Bülent Haznedar

    2017-02-01

    Full Text Available Classification is an important data mining technique, which is used in many fields mostly exemplified as medicine, genetics and biomedical engineering. The number of studies about classification of the datum on DNA microarray gene expression is specifically increased in recent years. However, because of the reasons as the abundance of gene numbers in the datum as microarray gene expressions and the nonlinear relations mostly across those datum, the success of conventional classification algorithms can be limited. Because of these reasons, the interest on classification methods which are based on artificial intelligence to solve the problem on classification has been gradually increased in recent times. In this study, a hybrid approach which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS and Genetic Algorithm (GA are suggested in order to classify liver microarray cancer data set. Simulation results are compared with the results of other methods. According to the results obtained, it is seen that the recommended method is better than the other methods.

  12. Apparent diffusion coefficient value of gastric cancer by diffusion-weighted imaging: Correlations with the histological differentiation and Lauren classification

    International Nuclear Information System (INIS)

    Liu, Song; Guan, Wenxian; Wang, Hao; Pan, Liang; Zhou, Zhuping; Yu, Haiping; Liu, Tian; Yang, Xiaofeng; He, Jian; Zhou, Zhengyang

    2014-01-01

    Highlights: • Gastric cancers’ ADC values were significantly lower than normal gastric wall. • Gastric adenocarcinomas with different differentiation had different ADC values. • Gastric adenocarcinomas’ ADC values correlated with histologic differentiations. • Gastric cancers’ ADC values correlated with Lauren classifications. • Mean ADC value was better than min ADC value in characterizing gastric cancers. - Abstract: Objective: The purpose of this study was to evaluate the correlations between histological differentiation and Lauren classification of gastric cancer and the apparent diffusion coefficient (ADC) value of diffusion weighted imaging (DWI). Materials and methods: Sixty-nine patients with gastric cancer lesions underwent preoperative magnetic resonance imaging (MRI) (3.0T) and surgical resection. DWI was obtained with a single-shot, echo-planar imaging sequence in the axial plane (b values: 0 and 1000 s/mm 2 ). Mean and minimum ADC values were obtained for each gastric cancer and normal gastric walls by two radiologists, who were blinded to the histological findings. Histological type, degree of differentiation and Lauren classification of each resected specimen were determined by one pathologist. Mean and minimum ADC values of gastric cancers with different histological types, degrees of differentiation and Lauren classifications were compared. Correlations between ADC values and histological differentiation and Lauren classification were analyzed. Results: The mean and minimum ADC values of gastric cancers, as a whole and separately, were significantly lower than those of normal gastric walls (all p values <0.001). There were significant differences in the mean and minimum ADC values among gastric cancers with different histological types, degrees of differentiation and Lauren classifications (p < 0.05). Mean and minimum ADC values correlated significantly (all p < 0.001) with histological differentiation (r = 0.564, 0.578) and Lauren

  13. Vision-based Human Action Classification Using Adaptive Boosting Algorithm

    KAUST Repository

    Zerrouki, Nabil; Harrou, Fouzi; Sun, Ying; Houacine, Amrane

    2018-01-01

    Precise recognition of human action is a key enabler for the development of many applications including autonomous robots for medical diagnosis and surveillance of elderly people in home environment. This paper addresses the human action recognition based on variation in body shape. Specifically, we divide the human body into five partitions that correspond to five partial occupancy areas. For each frame, we calculated area ratios and used them as input data for recognition stage. Here, we consider six classes of activities namely: walking, standing, bending, lying, squatting, and sitting. In this paper, we proposed an efficient human action recognition scheme, which takes advantages of superior discrimination capacity of AdaBoost algorithm. We validated the effectiveness of this approach by using experimental data from two publicly available databases fall detection databases from the University of Rzeszow’s and the Universidad de Málaga fall detection datasets. We provided comparisons of the proposed approach with state-of-the-art classifiers based on the neural network, K-nearest neighbor, support vector machine and naïve Bayes and showed that we achieve better results in discriminating human gestures.

  14. Vision-based Human Action Classification Using Adaptive Boosting Algorithm

    KAUST Repository

    Zerrouki, Nabil

    2018-05-07

    Precise recognition of human action is a key enabler for the development of many applications including autonomous robots for medical diagnosis and surveillance of elderly people in home environment. This paper addresses the human action recognition based on variation in body shape. Specifically, we divide the human body into five partitions that correspond to five partial occupancy areas. For each frame, we calculated area ratios and used them as input data for recognition stage. Here, we consider six classes of activities namely: walking, standing, bending, lying, squatting, and sitting. In this paper, we proposed an efficient human action recognition scheme, which takes advantages of superior discrimination capacity of AdaBoost algorithm. We validated the effectiveness of this approach by using experimental data from two publicly available databases fall detection databases from the University of Rzeszow’s and the Universidad de Málaga fall detection datasets. We provided comparisons of the proposed approach with state-of-the-art classifiers based on the neural network, K-nearest neighbor, support vector machine and naïve Bayes and showed that we achieve better results in discriminating human gestures.

  15. An Analysis of Machine- and Human-Analytics in Classification.

    Science.gov (United States)

    Tam, Gary K L; Kothari, Vivek; Chen, Min

    2017-01-01

    In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that may be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics.

  16. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    Directory of Open Access Journals (Sweden)

    Reinders Marcel JT

    2009-11-01

    Full Text Available Abstract Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical

  17. Human antimicrobial peptides and cancer.

    Science.gov (United States)

    Jin, Ge; Weinberg, Aaron

    2018-05-30

    Antimicrobial peptides (AMPs) have long been a topic of interest for entomologists, biologists, immunologists and clinicians because of these agents' intriguing origins in insects, their ubiquitous expression in many life forms, their capacity to kill a wide range of bacteria, fungi and viruses, their role in innate immunity as microbicidal and immunoregulatory agents that orchestrate cross-talk with the adaptive immune system, and, most recently, their association with cancer. We and others have theorized that surveillance through epithelial cell-derived AMPs functions to keep the natural flora of microorganisms in a steady state in different niches such as the skin, the intestines, and the mouth. More recently, findings related to specific activation pathways of some of these AMPs have led investigators to associate them with pro-tumoral activity; i.e., contributing to a tumorigenic microenvironment. This area is still in its infancy as there are intriguing yet contradictory findings demonstrating that while some AMPs have anti-tumoral activity and are under-expressed in solid tumors, others are overexpressed and pro-tumorigenic. This review will introduce a new paradigm in cancer biology as it relates to AMP activity in neoplasia to address the following questions: Is there evidence that AMPs contribute to tumor promoting microenvironments? Can an anti-AMP strategy be of use in cancer therapy? Do AMPs, expressed in and released from tumors, contribute to compositional shifting of bacteria in cancerous lesions? Can specific AMP expression characteristics be used one day as early warning signs for solid tumors? Copyright © 2018 Elsevier Ltd. All rights reserved.

  18. Genetic Characterization and Classification of Human and Animal Sapoviruses.

    Directory of Open Access Journals (Sweden)

    Tomoichiro Oka

    Full Text Available Sapoviruses (SaVs are enteric caliciviruses that have been detected in multiple mammalian species, including humans, pigs, mink, dogs, sea lions, chimpanzees, and rats. They show a high level of diversity. A SaV genome commonly encodes seven nonstructural proteins (NSs, including the RNA polymerase protein NS7, and two structural proteins (VP1 and VP2. We classified human and animal SaVs into 15 genogroups (G based on available VP1 sequences, including three newly characterized genomes from this study. We sequenced the full length genomes of one new genogroup V (GV, one GVII and one GVIII porcine SaV using long range RT-PCR including newly designed forward primers located in the conserved motifs of the putative NS3, and also 5' RACE methods. We also determined the 5'- and 3'-ends of sea lion GV SaV and canine GXIII SaV. Although the complete genomic sequences of GIX-GXII, and GXV SaVs are unavailable, common features of SaV genomes include: 1 "GTG" at the 5'-end of the genome, and a short (9~14 nt 5'-untranslated region; and 2 the first five amino acids (M [A/V] S [K/R] P of the putative NS1 and the five amino acids (FEMEG surrounding the putative cleavage site between NS7 and VP1 were conserved among the chimpanzee, two of five genogroups of pig (GV and GVIII, sea lion, canine, and human SaVs. In contrast, these two amino acid motifs were clearly different in three genogroups of porcine (GIII, GVI and GVII, and bat SaVs. Our results suggest that several animal SaVs have genetic similarities to human SaVs. However, the ability of SaVs to be transmitted between humans and animals is uncertain.

  19. Classification of Breast Cancer Subtypes by combining Gene Expression and DNA Methylation Data

    Directory of Open Access Journals (Sweden)

    List Markus

    2014-06-01

    Full Text Available Selecting the most promising treatment strategy for breast cancer crucially depends on determining the correct subtype. In recent years, gene expression profiling has been investigated as an alternative to histochemical methods. Since databases like TCGA provide easy and unrestricted access to gene expression data for hundreds of patients, the challenge is to extract a minimal optimal set of genes with good prognostic properties from a large bulk of genes making a moderate contribution to classification. Several studies have successfully applied machine learning algorithms to solve this so-called gene selection problem. However, more diverse data from other OMICS technologies are available, including methylation. We hypothesize that combining methylation and gene expression data could already lead to a largely improved classification model, since the resulting model will reflect differences not only on the transcriptomic, but also on an epigenetic level. We compared so-called random forest derived classification models based on gene expression and methylation data alone, to a model based on the combined features and to a model based on the gold standard PAM50. We obtained bootstrap errors of 10-20% and classification error of 1-50%, depending on breast cancer subtype and model. The gene expression model was clearly superior to the methylation model, which was also reflected in the combined model, which mainly selected features from gene expression data. However, the methylation model was able to identify unique features not considered as relevant by the gene expression model, which might provide deeper insights into breast cancer subtype differentiation on an epigenetic level.

  20. Automatic classification of ovarian cancer types from cytological images using deep convolutional neural networks.

    Science.gov (United States)

    Wu, Miao; Yan, Chuanbo; Liu, Huiqiang; Liu, Qian

    2018-06-29

    Ovarian cancer is one of the most common gynecologic malignancies. Accurate classification of ovarian cancer types (serous carcinoma, mucous carcinoma, endometrioid carcinoma, transparent cell carcinoma) is an essential part in the different diagnosis. Computer-aided diagnosis (CADx) can provide useful advice for pathologists to determine the diagnosis correctly. In our study, we employed a Deep Convolutional Neural Networks (DCNN) based on AlexNet to automatically classify the different types of ovarian cancers from cytological images. The DCNN consists of five convolutional layers, three max pooling layers, and two full reconnect layers. Then we trained the model by two group input data separately, one was original image data and the other one was augmented image data including image enhancement and image rotation. The testing results are obtained by the method of 10-fold cross-validation, showing that the accuracy of classification models has been improved from 72.76 to 78.20% by using augmented images as training data. The developed scheme was useful for classifying ovarian cancers from cytological images. © 2018 The Author(s).

  1. Naïve and Robust: Class-Conditional Independence in Human Classification Learning

    Science.gov (United States)

    Jarecki, Jana B.; Meder, Björn; Nelson, Jonathan D.

    2018-01-01

    Humans excel in categorization. Yet from a computational standpoint, learning a novel probabilistic classification task involves severe computational challenges. The present paper investigates one way to address these challenges: assuming class-conditional independence of features. This feature independence assumption simplifies the inference…

  2. Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules

    International Nuclear Information System (INIS)

    Teschendorff, Andrew E; Gomez, Sergio; Arenas, Alex; El-Ashry, Dorraya; Schmidt, Marcus; Gehrmann, Mathias; Caldas, Carlos

    2010-01-01

    Elucidating the activation pattern of molecular pathways across a given tumour type is a key challenge necessary for understanding the heterogeneity in clinical response and for developing novel more effective therapies. Gene expression signatures of molecular pathway activation derived from perturbation experiments in model systems as well as structural models of molecular interactions ('model signatures') constitute an important resource for estimating corresponding activation levels in tumours. However, relatively few strategies for estimating pathway activity from such model signatures exist and only few studies have used activation patterns of pathways to refine molecular classifications of cancer. Here we propose a novel network-based method for estimating pathway activation in tumours from model signatures. We find that although the pathway networks inferred from cancer expression data are highly consistent with the prior information contained in the model signatures, that they also exhibit a highly modular structure and that estimation of pathway activity is dependent on this modular structure. We apply our methodology to a panel of 438 estrogen receptor negative (ER-) and 785 estrogen receptor positive (ER+) breast cancers to infer activation patterns of important cancer related molecular pathways. We show that in ER negative basal and HER2+ breast cancer, gene expression modules reflecting T-cell helper-1 (Th1) and T-cell helper-2 (Th2) mediated immune responses play antagonistic roles as major risk factors for distant metastasis. Using Boolean interaction Cox-regression models to identify non-linear pathway combinations associated with clinical outcome, we show that simultaneous high activation of Th1 and low activation of a TGF-beta pathway module defines a subtype of particularly good prognosis and that this classification provides a better prognostic model than those based on the individual pathways. In ER+ breast cancer, we find that

  3. Classification of Dukes' B and C colorectal cancers using expression arrays

    DEFF Research Database (Denmark)

    Frederiksen, C.M.; Knudsen, Steen; Laurberg, S.

    2003-01-01

    Purpose. Colorectal cancer is one of the most common malignancies. Substaging of the cancer is of importance not only to prognosis but also to treatment. Classification of substages based on DNA microarray technology is currently the most promising approach. We therefore investigated if gene...... expression microarrays could be used to classify colorectal tumors. Methods. We used the Affymetrix oligonucleotide arrays to analyze the expression of more than 5,000 genes in samples from the sigmoid and upper rectum of the left colon. Five samples were from normal mucosa and five samples from each...... expression of one of the most common malignancies, colorectal cancer, now seems to be within reach. The data indicates that it is possible at least to classify Dukes' B and C colorectal tumors with microarrays....

  4. Artificial neural networks as classification and diagnostic tools for lymph node-negative breast cancers

    Energy Technology Data Exchange (ETDEWEB)

    Eswari J, Satya; Chandrakar, Neha [National Institute of Technology Raipur, Raipur (India)

    2016-04-15

    Artificial neural networks (ANNs) can be used to develop a technique to classify lymph node negative breast cancer that is prone to distant metastases based on gene expression signatures. The neural network used is a multilayered feed forward network that employs back propagation algorithm. Once trained with DNA microarraybased gene expression profiles of genes that were predictive of distant metastasis recurrence of lymph node negative breast cancer, the ANNs became capable of correctly classifying all samples and recognizing the genes most appropriate to the classification. To test the ability of the trained ANN models in recognizing lymph node negative breast cancer, we analyzed additional idle samples that were not used beforehand for the training procedure and obtained the correctly classified result in the validation set. For more substantial result, bootstrapping of training and testing dataset was performed as external validation. This study illustrates the potential application of ANN for breast tumor diagnosis and the identification of candidate targets in patients for therapy.

  5. [Classification and characteristics of interval cancers in the Principality of Asturias's Breast Cancer Screening Program].

    Science.gov (United States)

    Prieto García, M A; Delgado Sevillano, R; Baldó Sierra, C; González Díaz, E; López Secades, A; Llavona Amor, J A; Vidal Marín, B

    2013-09-01

    To review and classify the interval cancers found in the Principality of Asturias's Breast Cancer Screening Program (PDPCM). A secondary objective was to determine the histological characteristics, size, and stage of the interval cancers at the time of diagnosis. We included the interval cancers in the PDPCM in the period 2003-2007. Interval cancers were classified according to the breast cancer screening program protocol, with double reading without consensus, without blinding, with arbitration. Mammograms were interpreted by 10 radiologists in the PDPCM. A total of 33.7% of the interval cancers could not be classified; of the interval cancers that could be classified, 40.67% were labeled true interval cancers, 31.4% were labeled false negatives on screening, 23.7% had minimal signs, and 4.23% were considered occult. A total of 70% of the interval cancers were diagnosed in the year of the period between screening examinations and 71.7% were diagnosed after subsequent screening. A total of 76.9% were invasive ductal carcinomas, 61.1% were stage II when detected, and 78.7% were larger than 10mm when detected. The rate of interval cancers and the rate of false negatives in the PDPCM are higher than those recommended in the European guidelines. Interval cancers are diagnosed later than the tumors detected at screening. Studying interval cancers provides significant training for the radiologists in the PDPCM. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.

  6. Human adenylate kinases – classification, structure, physiological and pathological importance

    Directory of Open Access Journals (Sweden)

    Magdalena Wujak

    2015-01-01

    Full Text Available Adenylate kinase (AK, EC 2.7.4.3 is a ubiquitous phosphotransferase which catalyzes the reversible transfer of high-energy β – and γ-phosphate groups between nucleotides. All classified AKs show a similar structure: they contain a large central CORE region, nucleoside monophosphate and triphosphate binding domains (NMPbd and NTPbd and the LID domain. Analysis of amino acid sequence similarity revealed the presence of as many as nine human AK isoenzymes, which demonstrate different organ-tissue and intercellular localization. Among these kinases, only two, AK1 and AK2, fulfill the structural and functional criterion by the highest affinity for adenine nucleotides and the utilization of only AMP or dAMP as phosphate acceptors. Human AK isoenzymes are involved in nucleotide homeostasis and monitor disturbances of cell energy charge. Participating in large regulatory protein complexes, AK supplies high energy substrates for controlling the functions of channels and transporters as well as ligands for extracellular P2 nucleotide receptors. In pathological conditions AK can take over the function of other kinases, such as creatine kinase in oxygen-depleted myocardium. Directed mutagenesis and genetic studies of diseases (such as aleukocytosis, hemolytic anemia, primary ciliary dyskinesia (PCD link the presence and activity of AK with etiology of these disturbances. Moreover, AK participates in regulation of differentiation and maturation of cells as well as in apoptosis and oncogenesis. Involvement of AK in a wide range of processes and the correlation between AK and etiology of diseases support the medical potential for the use of adenylate kinases in the diagnosis and treatment of certain diseases. This paper summarizes the current knowledge on the structure, properties and functions of human adenylate kinase.

  7. Human Papillomavirus and Vaccination in Cervical Cancer

    Directory of Open Access Journals (Sweden)

    Kung-Liahng Wang

    2007-12-01

    Full Text Available Cervical cancer is not only the most frequently reported cancer among women, but also the most common female genital tract neoplasm in Taiwan. Early detection is effective, because the development, maintenance and progression of precursor lesions (cervical intraepithelial neoplasia [CIN] evolve slowly into invasive cancer, typically over a period of more than 10 years. It is now recognized that human papillomavirus (HPV infection is a necessary cause for over 99% of cervical cancer cases. Advances in the understanding of the causative role of HPV in the etiology of high-grade cervical lesions (CIN 2/3 and cervical cancer have led to the development, evaluation and recommendation of HPV-based technologies for cervical cancer prevention and control. The prevention of HPV infection before the onset of CIN is now possible with recently available prophylactic HPV vaccines, e.g. the quadrivalent Gardasil (Merck & Co., NJ, USA and bivalent Cervarix (GlaxoSmithKline, London, UK. This review article provides an up-to-date summary of recent studies and available information concerning HPV and vaccination in cervical cancer.

  8. CrossLink: a novel method for cross-condition classification of cancer subtypes.

    Science.gov (United States)

    Ma, Chifeng; Sastry, Konduru S; Flore, Mario; Gehani, Salah; Al-Bozom, Issam; Feng, Yusheng; Serpedin, Erchin; Chouchane, Lotfi; Chen, Yidong; Huang, Yufei

    2016-08-22

    We considered the prediction of cancer classes (e.g. subtypes) using patient gene expression profiles that contain both systematic and condition-specific biases when compared with the training reference dataset. The conventional normalization-based approaches cannot guarantee that the gene signatures in the reference and prediction datasets always have the same distribution for all different conditions as the class-specific gene signatures change with the condition. Therefore, the trained classifier would work well under one condition but not under another. To address the problem of current normalization approaches, we propose a novel algorithm called CrossLink (CL). CL recognizes that there is no universal, condition-independent normalization mapping of signatures. In contrast, it exploits the fact that the signature is unique to its associated class under any condition and thus employs an unsupervised clustering algorithm to discover this unique signature. We assessed the performance of CL for cross-condition predictions of PAM50 subtypes of breast cancer by using a simulated dataset modeled after TCGA BRCA tumor samples with a cross-validation scheme, and datasets with known and unknown PAM50 classification. CL achieved prediction accuracy >73 %, highest among other methods we evaluated. We also applied the algorithm to a set of breast cancer tumors derived from Arabic population to assign a PAM50 classification to each tumor based on their gene expression profiles. A novel algorithm CrossLink for cross-condition prediction of cancer classes was proposed. In all test datasets, CL showed robust and consistent improvement in prediction performance over other state-of-the-art normalization and classification algorithms.

  9. In vivo subsite classification and diagnosis of oral cancers using Raman spectroscopy

    Directory of Open Access Journals (Sweden)

    Aditi Sahu

    2016-09-01

    Full Text Available Oral cancers suffer from poor disease-free survival rates due to delayed diagnosis. Noninvasive, rapid, objective approaches as adjuncts to visual inspection can help in better management of oral cancers. Raman spectroscopy (RS has shown potential in identification of oral premalignant and malignant conditions and also in the detection of early cancer changes like cancer-field-effects (CFE at buccal mucosa subsite. Anatomic differences between different oral subsites have also been reported using RS. In this study, anatomical differences between subsites and their possible influence on healthy vs pathological classification were evaluated on 85 oral cancer and 72 healthy subjects. Spectra were acquired from buccal mucosa, lip and tongue in healthy, contralateral (internal healthy control, premalignant and cancer conditions using fiber-optic Raman spectrometer. Mean spectra indicate predominance of lipids in healthy buccal mucosa, contribution of both lipids and proteins in lip while major dominance of protein in tongue spectra. From healthy to tumor, changes in protein secondary-structure, DNA and heme-related features were observed. Principal component linear discriminant analysis (PC-LDA followed by leave-one-out-cross-validation (LOOCV was used for data analysis. Findings indicate buccal mucosa and tongue are distinct entities, while lip misclassifies with both these subsites. Additionally, the diagnostic algorithm for individual subsites gave improved classification efficiencies with respect to the pooled subsites model. However, as the pooled subsites model yielded 98% specificity and 100% sensitivity, this model may be more useful for preliminary screening applications. Large-scale validation studies are a pre-requisite before envisaging future clinical applications.

  10. Prediction of Depression in Cancer Patients With Different Classification Criteria, Linear Discriminant Analysis versus Logistic Regression.

    Science.gov (United States)

    Shayan, Zahra; Mohammad Gholi Mezerji, Naser; Shayan, Leila; Naseri, Parisa

    2015-11-03

    Logistic regression (LR) and linear discriminant analysis (LDA) are two popular statistical models for prediction of group membership. Although they are very similar, the LDA makes more assumptions about the data. When categorical and continuous variables used simultaneously, the optimal choice between the two models is questionable. In most studies, classification error (CE) is used to discriminate between subjects in several groups, but this index is not suitable to predict the accuracy of the outcome. The present study compared LR and LDA models using classification indices. This cross-sectional study selected 243 cancer patients. Sample sets of different sizes (n = 50, 100, 150, 200, 220) were randomly selected and the CE, B, and Q classification indices were calculated by the LR and LDA models. CE revealed the a lack of superiority for one model over the other, but the results showed that LR performed better than LDA for the B and Q indices in all situations. No significant effect for sample size on CE was noted for selection of an optimal model. Assessment of the accuracy of prediction of real data indicated that the B and Q indices are appropriate for selection of an optimal model. The results of this study showed that LR performs better in some cases and LDA in others when based on CE. The CE index is not appropriate for classification, although the B and Q indices performed better and offered more efficient criteria for comparison and discrimination between groups.

  11. Classification of prostate cancer grade using temporal ultrasound: in vivo feasibility study

    Science.gov (United States)

    Ghavidel, Sahar; Imani, Farhad; Khallaghi, Siavash; Gibson, Eli; Khojaste, Amir; Gaed, Mena; Moussa, Madeleine; Gomez, Jose A.; Siemens, D. Robert; Leveridge, Michael; Chang, Silvia; Fenster, Aaron; Ward, Aaron D.; Abolmaesumi, Purang; Mousavi, Parvin

    2016-03-01

    Temporal ultrasound has been shown to have high classification accuracy in differentiating cancer from benign tissue. In this paper, we extend the temporal ultrasound method to classify lower grade Prostate Cancer (PCa) from all other grades. We use a group of nine patients with mostly lower grade PCa, where cancerous regions are also limited. A critical challenge is to train a classifier with limited aggressive cancerous tissue compared to low grade cancerous tissue. To resolve the problem of imbalanced data, we use Synthetic Minority Oversampling Technique (SMOTE) to generate synthetic samples for the minority class. We calculate spectral features of temporal ultrasound data and perform feature selection using Random Forests. In leave-one-patient-out cross-validation strategy, an area under receiver operating characteristic curve (AUC) of 0.74 is achieved with overall sensitivity and specificity of 70%. Using an unsupervised learning approach prior to proposed method improves sensitivity and AUC to 80% and 0.79. This work represents promising results to classify lower and higher grade PCa with limited cancerous training samples, using temporal ultrasound.

  12. Classification tree analysis of second neoplasms in survivors of childhood cancer

    International Nuclear Information System (INIS)

    Jazbec, Janez; Todorovski, Ljupčo; Jereb, Berta

    2007-01-01

    Reports on childhood cancer survivors estimated cumulative probability of developing secondary neoplasms vary from 3,3% to 25% at 25 years from diagnosis, and the risk of developing another cancer to several times greater than in the general population. In our retrospective study, we have used the classification tree multivariate method on a group of 849 first cancer survivors, to identify childhood cancer patients with the greatest risk for development of secondary neoplasms. In observed group of patients, 34 develop secondary neoplasm after treatment of primary cancer. Analysis of parameters present at the treatment of first cancer, exposed two groups of patients at the special risk for secondary neoplasm. First are female patients treated for Hodgkin's disease at the age between 10 and 15 years, whose treatment included radiotherapy. Second group at special risk were male patients with acute lymphoblastic leukemia who were treated at the age between 4,6 and 6,6 years of age. The risk groups identified in our study are similar to the results of studies that used more conventional approaches. Usefulness of our approach in study of occurrence of second neoplasms should be confirmed in larger sample study, but user friendly presentation of results makes it attractive for further studies

  13. Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles

    Directory of Open Access Journals (Sweden)

    Wong G William

    2008-06-01

    Full Text Available Abstract Background Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detection of this cancer type is urgently needed. In recent years, proteomics profiling techniques combined with various data analysis methods have been successfully used to gain critical insights into processes and mechanisms underlying pathologic conditions, particularly as they relate to cancer. However, the high dimensionality of proteomics data combined with their relatively small sample sizes poses a significant challenge to current data mining methodology where many of the standard methods cannot be applied directly. Here, we propose a novel methodological framework using machine learning method, in which decision tree based classifier ensembles coupled with feature selection methods, is applied to proteomics data generated from premalignant pancreatic cancer. Results This study explores the utility of three different feature selection schemas (Student t test, Wilcoxon rank sum test and genetic algorithm to reduce the high dimensionality of a pancreatic cancer proteomic dataset. Using the top features selected from each method, we compared the prediction performances of a single decision tree algorithm C4.5 with six different decision-tree based classifier ensembles (Random forest, Stacked generalization, Bagging, Adaboost, Logitboost and Multiboost. We show that ensemble classifiers always outperform single decision tree classifier in having greater accuracies and smaller prediction errors when applied to a pancreatic cancer proteomics dataset. Conclusion In our cross validation framework, classifier ensembles generally have better classification accuracies compared to that of a single decision tree when applied to a pancreatic cancer proteomic dataset, thus suggesting its utility in future proteomics data analysis. Additionally, the use of feature selection

  14. Human papillomavirus-associated cancers: A growing global problem

    OpenAIRE

    Bansal, Anshuma; Singh, Mini P; Rai, Bhavana

    2016-01-01

    Human papillomavirus (HPV) infection is linked with several cancers such as cancer cervix, vagina, vulva, head and neck, anal, and penile carcinomas. Although there is a proven association of HPV with these cancers, questions regarding HPV testing, vaccination, and treatment of HPV-related cancers continue to remain unanswered. The present article provides an overview of the HPV-associated cancers.

  15. [Clinical Study of 2014 ISUP New Grade Group Classification for Prostate Cancer Patients Treated by Androgen Deprivation Therapy].

    Science.gov (United States)

    Uno, Masahiro; Kawase, Makoto; Kato, Daiki; Ishida, Takashi; Kato, Seiichi; Fujimoto, Yoshinori

    2018-01-01

    The 2014 International Society of Urological Pathology (ISUP) has proposed a new grade group (GG) classification for Gleason scores (GS). The usefulness of the new GG classification was investigated with 518 prostate cancer patients who underwent androgen deprivation therapy. According to the new GG classification, Stages B‒D and the new GG classification relapse-free rate for each stage were calculated using the Kaplan‒Meier method. The new GG classification revealed a significant difference for the relapse-free rate only between some groups. Analysis using the Cox proportional hazards model indicated that the risk of relapse was higher in GGs 4 and 5 than in GG 1. The usefulness about the relapse-free rate in androgen deprivation therapy of the 2014 ISUP new grade group classification a waits future examination.

  16. Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team

    DEFF Research Database (Denmark)

    Bjørn, Signe Frahm; Schnack, Tine Henrichsen; Lajer, Henrik

    2017-01-01

    multidisciplinary team (MDT) decisions. Materials and Methods Four hundred eighteen women diagnosed with ovarian cancers (n = 351) or borderline tumors (n = 66) were selected for primary debulking surgery from January 2008 to July 2013. At an MDT meeting, women were allocated into 3 groups named "pre-COVA" 1 to 3...... classifying the expected extent of the primary surgery and need for postoperative care. On the basis of the operative procedures performed, women were allocated into 1 of the 3 corresponding COVA 1 to 3 groups. The outcome measure was the predictive value of the pre-COVA score compared with the actual COVA......-COVA classification predicted the actual COVA group in 79 (49%) FIGO stages I to IIIB and in 85 (45%) FIGO stages IIIC to IV. Conclusions The COVA classification system is a simple and useful tool in the MDT setting where specialists make treatment decisions based on advanced technology. The use of pre...

  17. The classification of benign and malignant human prostate tissue by multivariate analysis of {sup 1}H magnetic resonance spectra

    Energy Technology Data Exchange (ETDEWEB)

    Hahn, P.; Smith, I.; Leboldus, L.; Littman, C.; Somorjai, L.; Bezabeh, T. [Institute for Biodiagnostic, National Research Council, Manitoba (Canada)

    1998-04-01

    {sup 1}H magnetic resonance spectroscopy studies (360 MHz) were performed on specimens of benign (n = 66) and malignant (n = 21) human prostate tissue from 50 patients and the spectral data were subjected to multivariate analysis, specifically linear-discriminant analysis. On the basis of histopathological assessments, an overall classification accuracy of 96.6 % was achieved, with a sensitivity of 100 % and a specificity of 95.5 % in classifying benign prostatic hyperplasia from prostatic cancer. Resonances due to citrate, glutamate, and taurine were among the six spectral subregions identified by our algorithm as having diagnostic potential. Significantly higher levels of citrate were observed in glandular than in stromal benign prostatic hyperplasia (P < 0.05). This method shows excellent promise for the possibility of in vivo assessment of prostate tissue by magnetic resonance. (author)

  18. A transcriptome anatomy of human colorectal cancers

    International Nuclear Information System (INIS)

    Lü, Bingjian; Xu, Jing; Lai, Maode; Zhang, Hao; Chen, Jian

    2006-01-01

    Accumulating databases in human genome research have enabled integrated genome-wide study on complicated diseases such as cancers. A practical approach is to mine a global transcriptome profile of disease from public database. New concepts of these diseases might emerge by landscaping this profile. In this study, we clustered human colorectal normal mucosa (N), inflammatory bowel disease (IBD), adenoma (A) and cancer (T) related expression sequence tags (EST) into UniGenes via an in-house GetUni software package and analyzed the transcriptome overview of these libraries by GOTree Machine (GOTM). Additionally, we downloaded UniGene based cDNA libraries of colon and analyzed them by Xprofiler to cross validate the efficiency of GetUni. Semi-quantitative RT-PCR was used to validate the expression of β-catenin and. 7 novel genes in colorectal cancers. The efficiency of GetUni was successfully validated by Xprofiler and RT-PCR. Genes in library N, IBD and A were all found in library T. A total of 14,879 genes were identified with 2,355 of them having at least 2 transcripts. Differences in gene enrichment among these libraries were statistically significant in 50 signal transduction pathways and Pfam protein domains by GOTM analysis P < 0.01 Hypergeometric Test). Genes in two metabolic pathways, ribosome and glycolysis, were more enriched in the expression profiles of A and IBD than in N and T. Seven transmembrane receptor superfamily genes were typically abundant in cancers. Colorectal cancers are genetically heterogeneous. Transcription variants are common in them. Aberrations of ribosome and glycolysis pathway might be early indicators of precursor lesions in colon cancers. The electronic gene expression profile could be used to highlight the integral molecular events in colorectal cancers

  19. Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

    Science.gov (United States)

    Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

    2015-06-01

    Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Regulatory T Cells in Human Ovarian Cancer

    Directory of Open Access Journals (Sweden)

    Dong-Jun Peng

    2012-01-01

    Full Text Available Multiple layers of suppressive components including regulatory T (TReg cells, suppressive antigen-presenting cells, and inhibitory cytokines form suppressive networks in the ovarian cancer microenvironment. It has been demonstrated that as a major suppressive element, TReg cells infiltrate tumor, interact with several types of immune cells, and mediate immune suppression through different molecular and cellular mechanisms. In this paper, we focus on human ovarian cancer and will discuss the nature of TReg cells including their subsets, trafficking, expansion, and function. We will briefly review the development of manipulation of TReg cells in preclinical and clinical settings.

  1. Global classification of human facial healthy skin using PLS discriminant analysis and clustering analysis.

    Science.gov (United States)

    Guinot, C; Latreille, J; Tenenhaus, M; Malvy, D J

    2001-04-01

    Today's classifications of healthy skin are predominantly based on a very limited number of skin characteristics, such as skin oiliness or susceptibility to sun exposure. The aim of the present analysis was to set up a global classification of healthy facial skin, using mathematical models. This classification is based on clinical, biophysical skin characteristics and self-reported information related to the skin, as well as the results of a theoretical skin classification assessed separately for the frontal and the malar zones of the face. In order to maximize the predictive power of the models with a minimum of variables, the Partial Least Square (PLS) discriminant analysis method was used. The resulting PLS components were subjected to clustering analyses to identify the plausible number of clusters and to group the individuals according to their proximities. Using this approach, four PLS components could be constructed and six clusters were found relevant. So, from the 36 hypothetical combinations of the theoretical skin types classification, we tended to a strengthened six classes proposal. Our data suggest that the association of the PLS discriminant analysis and the clustering methods leads to a valid and simple way to classify healthy human skin and represents a potentially useful tool for cosmetic and dermatological research.

  2. Controlling a human-computer interface system with a novel classification method that uses electrooculography signals.

    Science.gov (United States)

    Wu, Shang-Lin; Liao, Lun-De; Lu, Shao-Wei; Jiang, Wei-Ling; Chen, Shi-An; Lin, Chin-Teng

    2013-08-01

    Electrooculography (EOG) signals can be used to control human-computer interface (HCI) systems, if properly classified. The ability to measure and process these signals may help HCI users to overcome many of the physical limitations and inconveniences in daily life. However, there are currently no effective multidirectional classification methods for monitoring eye movements. Here, we describe a classification method used in a wireless EOG-based HCI device for detecting eye movements in eight directions. This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-left, up-right, and down-right) and blinking. The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future.

  3. Acromioclavicular joint dislocations: radiological correlation between Rockwood classification system and injury patterns in human cadaver species.

    Science.gov (United States)

    Eschler, Anica; Rösler, Klaus; Rotter, Robert; Gradl, Georg; Mittlmeier, Thomas; Gierer, Philip

    2014-09-01

    The classification system of Rockwood and Young is a commonly used classification for acromioclavicular joint separations subdividing types I-VI. This classification hypothesizes specific lesions to anatomical structures (acromioclavicular and coracoclavicular ligaments, capsule, attached muscles) leading to the injury. In recent literature, our understanding for anatomical correlates leading to the radiological-based Rockwood classification is questioned. The goal of this experimental-based investigation was to approve the correlation between the anatomical injury pattern and the Rockwood classification. In four human cadavers (seven shoulders), the acromioclavicular and coracoclavicular ligaments were transected stepwise. Radiological correlates were recorded (Zanca view) with 15-kg longitudinal tension applied at the wrist. The resulting acromio- and coracoclavicular distances were measured. Radiographs after acromioclavicular ligament transection showed joint space enlargement (8.6 ± 0.3 vs. 3.1 ± 0.5 mm, p acromioclavicular joint space width increased to 16.7 ± 2.7 vs. 8.6 ± 0.3 mm, p acromioclavicular joint lesions higher than Rockwood type I and II. The clinical consequence for reconstruction of low-grade injuries might be a solely surgical approach for the acromioclavicular ligaments or conservative treatment. High-grade injuries were always based on additional structural damage to the coracoclavicular ligaments. Rockwood type V lesions occurred while muscle attachments were intact.

  4. Human retroviruses: their role in cancer.

    Science.gov (United States)

    Blattner, W A

    1999-01-01

    Viruses are etiologically linked to approximately 20% of all malignancies worldwide. Retroviruses account for approximately 8%-10% of the total. For human T-cell leukemia virus 1 (HTLV-I), the viral regulatory tax gene product is responsible for enhanced transcription of viral and cellular genes that promote cell growth by stimulating various growth factors and through dysregulation of cellular regulatory suppressor genes, such as p53. After a long latent period, adult T-cell leukemia/lymphoma (ATL) occurs in 1 per 1000 carriers per year, resulting in 2500-3000 cases per year worldwide and over half of the adult lymphoid malignancies in endemic areas. Human immunodeficiency virus 1 (HIV-1) accounts for a significant cancer burden, and its transactivating regulatory protein Tat enhances direct and indirect cytokine and immunological dysregulation to cause diverse cancers. Kaposi's sarcoma (KS) is a very rare tumor except after HIV-1 infection, when its incidence is greatly amplified reaching seventy thousand-fold in HIV-infected homosexual men. Human herpesvirus 8 (HHV-8), which is also known as Kaposi's sarcoma-associated virus (KSHV), is a necessary but not sufficient etiological factor in KS. The dramatic decline of KS since the introduction of highly active antiretroviral therapy (HAART) could be due to suppression of HIV-1 tat. B-cell non-Hodgkin's lymphoma occurs as their first acquired immunodeficiency syndrome-defining diagnosis in 3%-4% of HIV-infected patients. Hodgkin's lymphoma is also associated with HIV infection but at a lower risk. Human papillomaviruses are linked to invasive cervical cancer and anogenital cancers among HIV-infected patients. Human retroviruses cause malignancy via direct effects as well as through interactions with other oncogenic herpesviruses and other viruses.

  5. Real-time classification of humans versus animals using profiling sensors and hidden Markov tree model

    Science.gov (United States)

    Hossen, Jakir; Jacobs, Eddie L.; Chari, Srikant

    2015-07-01

    Linear pyroelectric array sensors have enabled useful classifications of objects such as humans and animals to be performed with relatively low-cost hardware in border and perimeter security applications. Ongoing research has sought to improve the performance of these sensors through signal processing algorithms. In the research presented here, we introduce the use of hidden Markov tree (HMT) models for object recognition in images generated by linear pyroelectric sensors. HMTs are trained to statistically model the wavelet features of individual objects through an expectation-maximization learning process. Human versus animal classification for a test object is made by evaluating its wavelet features against the trained HMTs using the maximum-likelihood criterion. The classification performance of this approach is compared to two other techniques; a texture, shape, and spectral component features (TSSF) based classifier and a speeded-up robust feature (SURF) classifier. The evaluation indicates that among the three techniques, the wavelet-based HMT model works well, is robust, and has improved classification performance compared to a SURF-based algorithm in equivalent computation time. When compared to the TSSF-based classifier, the HMT model has a slightly degraded performance but almost an order of magnitude improvement in computation time enabling real-time implementation.

  6. Human Classification Based on Gestural Motions by Using Components of PCA

    International Nuclear Information System (INIS)

    Aziz, Azri A; Wan, Khairunizam; Za'aba, S K; Shahriman A B; Asyekin H; Zuradzman M R; Adnan, Nazrul H

    2013-01-01

    Lately, a study of human capabilities with the aim to be integrated into machine is the famous topic to be discussed. Moreover, human are bless with special abilities that they can hear, see, sense, speak, think and understand each other. Giving such abilities to machine for improvement of human life is researcher's aim for better quality of life in the future. This research was concentrating on human gesture, specifically arm motions for differencing the individuality which lead to the development of the hand gesture database. We try to differentiate the human physical characteristic based on hand gesture represented by arm trajectories. Subjects are selected from different type of the body sizes, and then acquired data undergo resampling process. The results discuss the classification of human based on arm trajectories by using Principle Component Analysis (PCA)

  7. ParSel: Parallel Selection of Micro-RNAs for Survival Classification in Cancers.

    Science.gov (United States)

    Sinha, Debajyoti; Sengupta, Debarka; Bandyopadhyay, Sanghamitra

    2017-07-01

    It is known that tumor micro-RNAs (miRNA) can define patient survival and treatment response. We present a framework to identify miRNAs which are predictive of cancer survival. The framework attempts to rank the miRNAs by exploring their collaborative role in gene regulation. Our approach tests a significantly large number of combinatorial cases leveraging parallel computation. We carefully avoided parametric assumptions involved in evaluations of miRNA expressions but used rigorous statistical computation to assign an importance score to a miRNA. Experimental results on three cancer types namely, KIRC, OV and GBM verify that the top ranked miRNAs obtained using the proposed framework produce better classification accuracy as compared to some best practice variable selection methods. Some of these top ranked miRNA are also known to be associated with related diseases. © 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. On the classification and evolution of endogenous retrovirus: human endogenous retroviruses may not be 'human' after all.

    Science.gov (United States)

    Escalera-Zamudio, Marina; Greenwood, Alex D

    2016-01-01

    Retroviruses, as part of their replication cycle, become integrated into the genome of their host. When this occurs in the germline the integrated proviruses can become an endogenous retrovirus (ERV) which may eventually become fixed in the population. ERVs are present in the genomes of all vertebrates including humans, where more than 50 groups of human endogenous retrovirus (HERVs) have been described within the last 30 years. Despite state-of-the-art genomic tools available for retroviral discovery and the large number of retroviral sequences described to date, there are still gaps in understanding retroviral macroevolutionary patterns and host-retrovirus interactions and a lack of a coherent systematic classification particularly for HERVs. Here, we discuss the current knowledge on ERV (and HERV) classification, distribution and origins focusing on the role of cross-species transmission in retroviral diversity. © 2016 APMIS. Published by John Wiley & Sons Ltd.

  9. Improving breast cancer classification with mammography, supported on an appropriate variable selection analysis

    Science.gov (United States)

    Pérez, Noel; Guevara, Miguel A.; Silva, Augusto

    2013-02-01

    This work addresses the issue of variable selection within the context of breast cancer classification with mammography. A comprehensive repository of feature vectors was used including a hybrid subset gathering image-based and clinical features. It aimed to gather experimental evidence of variable selection in terms of cardinality, type and find a classification scheme that provides the best performance over the Area Under Receiver Operating Characteristics Curve (AUC) scores using the ranked features subset. We evaluated and classified a total of 300 subsets of features formed by the application of Chi-Square Discretization, Information-Gain, One-Rule and RELIEF methods in association with Feed-Forward Backpropagation Neural Network (FFBP), Support Vector Machine (SVM) and Decision Tree J48 (DTJ48) Machine Learning Algorithms (MLA) for a comparative performance evaluation based on AUC scores. A variable selection analysis was performed for Single-View Ranking and Multi-View Ranking groups of features. Features subsets representing Microcalcifications (MCs), Masses and both MCs and Masses lesions achieved AUC scores of 0.91, 0.954 and 0.934 respectively. Experimental evidence demonstrated that classification performance was improved by combining image-based and clinical features. The most important clinical and image-based features were StromaDistortion and Circularity respectively. Other less important but worth to use due to its consistency were Contrast, Perimeter, Microcalcification, Correlation and Elongation.

  10. Enigmatic human tails: A review of their history, embryology, classification, and clinical manifestations.

    Science.gov (United States)

    Tubbs, R Shane; Malefant, Jason; Loukas, Marios; Jerry Oakes, W; Oskouian, Rod J; Fries, Fabian N

    2016-05-01

    The presence of a human tail is a rare and intriguing phenomenon. While cases have been reported in the literature, confusion remains with respect to the proper classification, definition, and treatment methods. We review the literature concerning this anatomical derailment. We also consider the importance of excluding underlying congenital anomalies in these patients to prevent neurological deficits and other abnormal manifestations. © 2016 Wiley Periodicals, Inc.

  11. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Maolong Xi

    2016-01-01

    Full Text Available This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO for cancer feature gene selection, coupling support vector machine (SVM for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV. Finally, the BQPSO coupling SVM (BQPSO/SVM, binary PSO coupling SVM (BPSO/SVM, and genetic algorithm coupling SVM (GA/SVM are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms.

  12. Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

    Science.gov (United States)

    Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

    2016-01-01

    This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV). Finally, the BQPSO coupling SVM (BQPSO/SVM), binary PSO coupling SVM (BPSO/SVM), and genetic algorithm coupling SVM (GA/SVM) are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms. PMID:27642363

  13. Ultrasonographic characteristics and BI-RADS-US classification of BRCA1 mutation-associated breast cancer in Guangxi, China.

    Science.gov (United States)

    Li, Cheng; Liu, Junjie; Wang, Sida; Chen, Yuanyuan; Yuan, Zhigang; Zeng, Jian; Li, Zhixian

    2015-01-01

    To retrospectively analyze and compare the ultrasonographic characteristics and BI-RADS-US classification between patients with BRCA1 mutation-associated breast cancer and those without BRCA1 gene mutation in Guangxi, China. The study was performed in 36 lesions from 34 BRCA1 mutation-associated breast cancer patients. A total of 422 lesions from 422 breast cancer patients without BRCA1 mutations served as control group. The comparison of the ultrasonographic features and BI-RADS-US classification between two the groups were reviewed. More complex inner echo was disclosed in BRCA1 mutation-associated breast cancer patients (x(2) = 4.741, P = 0.029). The BI-RADS classification of BRCA1 mutation-associated breast cancer was lower (U = 6094.0, P = 0.022). BRCA1 mutation-associated breast cancer frequently displays as microlobulated margin and complex echo. It also shows more benign characteristics in morphology, and the BI-RADS classification is prone to be underestimated.

  14. Actionable gene-based classification toward precision medicine in gastric cancer

    Directory of Open Access Journals (Sweden)

    Hiroshi Ichikawa

    2017-10-01

    Full Text Available Abstract Background Intertumoral heterogeneity represents a significant hurdle to identifying optimized targeted therapies in gastric cancer (GC. To realize precision medicine for GC patients, an actionable gene alteration-based molecular classification that directly associates GCs with targeted therapies is needed. Methods A total of 207 Japanese patients with GC were included in this study. Formalin-fixed, paraffin-embedded (FFPE tumor tissues were obtained from surgical or biopsy specimens and were subjected to DNA extraction. We generated comprehensive genomic profiling data using a 435-gene panel including 69 actionable genes paired with US Food and Drug Administration-approved targeted therapies, and the evaluation of Epstein-Barr virus (EBV infection and microsatellite instability (MSI status. Results Comprehensive genomic sequencing detected at least one alteration of 435 cancer-related genes in 194 GCs (93.7% and of 69 actionable genes in 141 GCs (68.1%. We classified the 207 GCs into four The Cancer Genome Atlas (TCGA subtypes using the genomic profiling data; EBV (N = 9, MSI (N = 17, chromosomal instability (N = 119, and genomically stable subtype (N = 62. Actionable gene alterations were not specific and were widely observed throughout all TCGA subtypes. To discover a novel classification which more precisely selects candidates for targeted therapies, 207 GCs were classified using hypermutated phenotype and the mutation profile of 69 actionable genes. We identified a hypermutated group (N = 32, while the others (N = 175 were sub-divided into six clusters including five with actionable gene alterations: ERBB2 (N = 25, CDKN2A, and CDKN2B (N = 10, KRAS (N = 10, BRCA2 (N = 9, and ATM cluster (N = 12. The clinical utility of this classification was demonstrated by a case of unresectable GC with a remarkable response to anti-HER2 therapy in the ERBB2 cluster. Conclusions This actionable gene

  15. Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value.

    Directory of Open Access Journals (Sweden)

    Laetitia Marisa

    Full Text Available Colon cancer (CC pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses.Fresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype-like, normal-like, serrated CC phenotype-like, and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II-III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse-free survival, even after

  16. [Molecular classification of breast cancer patients obtained through the technique of chromogenic in situ hybridization (CISH)].

    Science.gov (United States)

    Fernández, Angel; Reigosa, Aldo

    2013-12-01

    Breast cancer is a heterogeneous disease composed of a growing number of biological subtypes, with substantial variability of the disease progression within each category. The aim of this research was to classify the samples object of study according to the molecular classes of breast cancer: luminal A, luminal B, HER2 and triple negative, as a result of the state of HER2 amplification obtained by the technique of chromogenic in situ hybridization (CISH). The sample consisted of 200 biopsies fixed in 10% formalin, processed by standard techniques up to paraffin embedding, corresponding to patients diagnosed with invasive ductal carcinoma of the breast. These biopsies were obtained from patients from private practice and the Institute of Oncology "Dr. Miguel Pérez Carreño", for immunohistochemistry (IHC) of hormone receptors and HER2 made in the Hospital Metropolitano del Norte, Valencia, Venezuela. The molecular classification of the patient's tumors considering the expression of estrogen and progesterone receptors by IHC and HER2 amplification by CISH, allowed those cases originally classified as unknown, since they had an indeterminate (2+) outcome for HER2 expression by IHC, to be grouped into the different molecular classes. Also, this classification permitted that some cases, initially considered as belonging to a molecular class, were assigned to another class, after the revaluation of the HER2 status by CISH.

  17. Does the use of the 2009 FIGO classification of endometrial cancer impact on indications of the sentinel node biopsy?

    Directory of Open Access Journals (Sweden)

    Ballester Marcos

    2010-08-01

    Full Text Available Abstract Background Lymphadenectomy is debated in early stages endometrial cancer. Moreover, a new FIGO classification of endometrial cancer, merging stages IA and IB has been recently published. Therefore, the aims of the present study was to evaluate the relevance of the sentinel node (SN procedure in women with endometrial cancer and to discuss whether the use of the 2009 FIGO classification could modify the indications for SN procedure. Methods Eighty-five patients with endometrial cancer underwent the SN procedure followed by pelvic lymphadenectomy. SNs were detected with a dual or single labelling method in 74 and 11 cases, respectively. All SNs were analysed by both H&E staining and immunohistochemistry. Presumed stage before surgery was assessed for all patients based on MR imaging features using the 1988 FIGO classification and the 2009 FIGO classification. Results An SN was detected in 88.2% of cases (75/85 women. Among the fourteen patients with lymph node metastases one-half were detected by serial sectioning and immunohistochemical analysis. There were no false negative case. Using the 1988 FIGO classification and the 2009 FIGO classification, the correlation between preoperative MRI staging and final histology was moderate with Kappa = 0.24 and Kappa = 0.45, respectively. None of the patients with grade 1 endometrioid carcinoma on biopsy and IA 2009 FIGO stage on MR imaging exhibited positive SN. In patients with grade 2-3 endometrioid carcinoma and stage IA on MR imaging, the rate of positive SN reached 16.6% with an incidence of micrometastases of 50%. Conclusions The present study suggests that sentinel node biopsy is an adequate technique to evaluate lymph node status. The use of the 2009 FIGO classification increases the accuracy of MR imaging to stage patients with early stages of endometrial cancer and contributes to clarify the indication of SN biopsy according to tumour grade and histological type.

  18. Does the use of the 2009 FIGO classification of endometrial cancer impact on indications of the sentinel node biopsy?

    International Nuclear Information System (INIS)

    Ballester, Marcos; Koskas, Martin; Coutant, Charles; Chéreau, Elisabeth; Seror, Jeremy; Rouzier, Roman; Daraï, Emile

    2010-01-01

    Lymphadenectomy is debated in early stages endometrial cancer. Moreover, a new FIGO classification of endometrial cancer, merging stages IA and IB has been recently published. Therefore, the aims of the present study was to evaluate the relevance of the sentinel node (SN) procedure in women with endometrial cancer and to discuss whether the use of the 2009 FIGO classification could modify the indications for SN procedure. Eighty-five patients with endometrial cancer underwent the SN procedure followed by pelvic lymphadenectomy. SNs were detected with a dual or single labelling method in 74 and 11 cases, respectively. All SNs were analysed by both H&E staining and immunohistochemistry. Presumed stage before surgery was assessed for all patients based on MR imaging features using the 1988 FIGO classification and the 2009 FIGO classification. An SN was detected in 88.2% of cases (75/85 women). Among the fourteen patients with lymph node metastases one-half were detected by serial sectioning and immunohistochemical analysis. There were no false negative case. Using the 1988 FIGO classification and the 2009 FIGO classification, the correlation between preoperative MRI staging and final histology was moderate with Kappa = 0.24 and Kappa = 0.45, respectively. None of the patients with grade 1 endometrioid carcinoma on biopsy and IA 2009 FIGO stage on MR imaging exhibited positive SN. In patients with grade 2-3 endometrioid carcinoma and stage IA on MR imaging, the rate of positive SN reached 16.6% with an incidence of micrometastases of 50%. The present study suggests that sentinel node biopsy is an adequate technique to evaluate lymph node status. The use of the 2009 FIGO classification increases the accuracy of MR imaging to stage patients with early stages of endometrial cancer and contributes to clarify the indication of SN biopsy according to tumour grade and histological type

  19. Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering.

    Science.gov (United States)

    Nahid, Abdullah-Al; Mehrabi, Mohamad Ali; Kong, Yinan

    2018-01-01

    Breast Cancer is a serious threat and one of the largest causes of death of women throughout the world. The identification of cancer largely depends on digital biomedical photography analysis such as histopathological images by doctors and physicians. Analyzing histopathological images is a nontrivial task, and decisions from investigation of these kinds of images always require specialised knowledge. However, Computer Aided Diagnosis (CAD) techniques can help the doctor make more reliable decisions. The state-of-the-art Deep Neural Network (DNN) has been recently introduced for biomedical image analysis. Normally each image contains structural and statistical information. This paper classifies a set of biomedical breast cancer images (BreakHis dataset) using novel DNN techniques guided by structural and statistical information derived from the images. Specifically a Convolutional Neural Network (CNN), a Long-Short-Term-Memory (LSTM), and a combination of CNN and LSTM are proposed for breast cancer image classification. Softmax and Support Vector Machine (SVM) layers have been used for the decision-making stage after extracting features utilising the proposed novel DNN models. In this experiment the best Accuracy value of 91.00% is achieved on the 200x dataset, the best Precision value 96.00% is achieved on the 40x dataset, and the best F -Measure value is achieved on both the 40x and 100x datasets.

  20. Are preoperative histology and MRI useful for classification of endometrial cancer risk?

    International Nuclear Information System (INIS)

    Body, Noemie; Lavoué, Vincent; De Kerdaniel, Olivier; Foucher, Fabrice; Henno, Sébastien; Cauchois, Aurélie; Laviolle, Bruno; Leblanc, Marc; Levêque, Jean

    2016-01-01

    The 2010 guidelines of the French National Cancer Institute (INCa) classify patients with endometrial cancer into three risk groups for lymph node invasion and recurrence on the basis of MRI and histological analysis of an endometrial specimen obtained preoperatively. The classification guides therapeutic choices, which may include pelvic and/or para-aortic lymphadenectomy. The purpose of this study was to evaluate the diagnostic performance of preoperative assessment to help identify intermediate- or high-risk patients requiring lymphadenectomy. The study included all patients who underwent surgery for endometrial cancer between January 2010 and December 2013 at either Rennes University Hospital or Vannes Regional Hospital. The criteria for eligibility included a preoperative assessment with MRI and histological examination of an endometrial sample. A histological comparison was made between the preoperative and surgical specimens. Among the 91 patients who underwent a full preoperative assessment, the diagnosis of intermediate- or high-risk endometrial cancer was established by MRI and histology with a sensitivity of 70 %, specificity of 82 %, positive predictive value (PPV) of 87 %, negative predictive value (NPV) of 61 %, positive likelihood ratio (LR+) of 3.8 and negative likelihood ratio (LR-) of 0.3. The risk group was underestimated in 32 % of patients and overestimated in 7 % of patients. MRI underestimated endometrial cancer stage in 20 % of cases, while endometrial sampling underestimated the histological type in 4 % of cases and the grade in 9 % of cases. The preoperative assessment overestimated or underestimated the risk of recurrence in nearly 40 % of cases, with errors in lesion type, grade or stage. Erroneous preoperative risk assessment leads to suboptimal initial surgical management of patients with endometrial cancer

  1. BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.

    Science.gov (United States)

    Guo, Yang; Liu, Shuhui; Li, Zhanhuai; Shang, Xuequn

    2018-04-11

    The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed as an alternative of deep neural networks to learn hyper-representations by using cascade ensemble decision trees. It has been proved that the deep forest model has competitive or even better performance than deep neural networks in some extent. However, the standard deep forest model may face overfitting and ensemble diversity challenges when dealing with small sample size and high-dimensional biology data. In this paper, we propose a deep learning model, so-called BCDForest, to address cancer subtype classification on small-scale biology datasets, which can be viewed as a modification of the standard deep forest model. The BCDForest distinguishes from the standard deep forest model with the following two main contributions: First, a named multi-class-grained scanning method is proposed to train multiple binary classifiers to encourage diversity of ensemble. Meanwhile, the fitting quality of each classifier is considered in representation learning. Second, we propose a boosting strategy to emphasize more important features in cascade forests, thus to propagate the benefits of discriminative features among cascade layers to improve the classification performance. Systematic comparison experiments on both microarray and RNA-Seq gene expression datasets demonstrate that our method consistently outperforms the state-of-the-art methods in application of cancer subtype classification. The multi-class-grained scanning and boosting strategy in our model provide an effective solution to ease the overfitting challenge and improve the robustness of deep forest model working on small-scale data. Our model provides a useful approach to the classification of cancer subtypes

  2. Molecular concept in human oral cancer.

    Science.gov (United States)

    Krishna, Akhilesh; Singh, Shraddha; Kumar, Vijay; Pal, U S

    2015-01-01

    The incidence of oral cancer remains high in both Asian and Western countries. Several risk factors associated with development of oral cancer are now well-known, including tobacco chewing, smoking, and alcohol consumption. Cancerous risk factors may cause many genetic events through chromosomal alteration or mutations in genetic material and lead to progression and development of oral cancer through histological progress, carcinogenesis. Oral squamous carcinogenesis is a multistep process in which multiple genetic events occur that alter the normal functions of proto-oncogenes/oncogenes and tumor suppressor genes. Furthermore, these gene alterations can deregulate the normal activity such as increase in the production of growth factors (transforming growth factor-α [TGF-α], TGF-β, platelet-derived growth factor, etc.) or numbers of cell surface receptors (epidermal growth factor receptor, G-protein-coupled receptor, etc.), enhanced intracellular messenger signaling and mutated production of transcription factors (ras gene family, c-myc gene) which results disturb to tightly regulated signaling pathways of normal cell. Several oncogenes and tumor suppressor genes have been implicated in oral cancer especially cyclin family, ras, PRAD-1, cyclin-dependent kinase inhibitors, p53 and RB1. Viral infections, particularly with oncogenic human papilloma virus subtype (16 and 18) and Epstein-Barr virus have tumorigenic effect on oral epithelia. Worldwide, this is an urgent need to initiate oral cancer research programs at molecular and genetic level which investigates the causes of genetic and molecular defect, responsible for malignancy. This approach may lead to development of target dependent tumor-specific drugs and appropriate gene therapy.

  3. Evaluating human cancer cell metastasis in zebrafish

    International Nuclear Information System (INIS)

    Teng, Yong; Xie, Xiayang; Walker, Steven; White, David T; Mumm, Jeff S; Cowell, John K

    2013-01-01

    In vivo metastasis assays have traditionally been performed in mice, but the process is inefficient and costly. However, since zebrafish do not develop an adaptive immune system until 14 days post-fertilization, human cancer cells can survive and metastasize when transplanted into zebrafish larvae. Despite isolated reports, there has been no systematic evaluation of the robustness of this system to date. Individual cell lines were stained with CM-Dil and injected into the perivitelline space of 2-day old zebrafish larvae. After 2-4 days fish were imaged using confocal microscopy and the number of metastatic cells was determined using Fiji software. To determine whether zebrafish can faithfully report metastatic potential in human cancer cells, we injected a series of cells with different metastatic potential into the perivitelline space of 2 day old embryos. Using cells from breast, prostate, colon and pancreas we demonstrated that the degree of cell metastasis in fish is proportional to their invasion potential in vitro. Highly metastatic cells such as MDA231, DU145, SW620 and ASPC-1 are seen in the vasculature and throughout the body of the fish after only 24–48 hours. Importantly, cells that are not invasive in vitro such as T47D, LNCaP and HT29 do not metastasize in fish. Inactivation of JAK1/2 in fibrosarcoma cells leads to loss of invasion in vitro and metastasis in vivo, and in zebrafish these cells show limited spread throughout the zebrafish body compared with the highly metastatic parental cells. Further, knockdown of WASF3 in DU145 cells which leads to loss of invasion in vitro and metastasis in vivo also results in suppression of metastasis in zebrafish. In a cancer progression model involving normal MCF10A breast epithelial cells, the degree of invasion/metastasis in vitro and in mice is mirrored in zebrafish. Using a modified version of Fiji software, it is possible to quantify individual metastatic cells in the transparent larvae to correlate with

  4. Towards precise classification of cancers based on robust gene functional expression profiles

    Directory of Open Access Journals (Sweden)

    Zhu Jing

    2005-03-01

    Full Text Available Abstract Background Development of robust and efficient methods for analyzing and interpreting high dimension gene expression profiles continues to be a focus in computational biology. The accumulated experiment evidence supports the assumption that genes express and perform their functions in modular fashions in cells. Therefore, there is an open space for development of the timely and relevant computational algorithms that use robust functional expression profiles towards precise classification of complex human diseases at the modular level. Results Inspired by the insight that genes act as a module to carry out a highly integrated cellular function, we thus define a low dimension functional expression profile for data reduction. After annotating each individual gene to functional categories defined in a proper gene function classification system such as Gene Ontology applied in this study, we identify those functional categories enriched with differentially expressed genes. For each functional category or functional module, we compute a summary measure (s for the raw expression values of the annotated genes to capture the overall activity level of the module. In this way, we can treat the gene expressions within a functional module as an integrative data point to replace the multiple values of individual genes. We compare the classification performance of decision trees based on functional expression profiles with the conventional gene expression profiles using four publicly available datasets, which indicates that precise classification of tumour types and improved interpretation can be achieved with the reduced functional expression profiles. Conclusion This modular approach is demonstrated to be a powerful alternative approach to analyzing high dimension microarray data and is robust to high measurement noise and intrinsic biological variance inherent in microarray data. Furthermore, efficient integration with current biological knowledge

  5. A taxonomy of epithelial human cancer and their metastases

    Directory of Open Access Journals (Sweden)

    De Moor Bart

    2009-12-01

    . Moreover, a signature was developed based on our unsupervised clustering of breast tumors and this was predictive for disease-specific survival in three independent studies. Next, the metastases from ovarian, breast, lung and vulva cluster with their tissue of origin while metastases from colon showed a bimodal distribution. A significant part clusters with tissue of origin while the remaining tumors cluster with the tissue of destination. Conclusion Our molecular taxonomy of epithelial human cancer indicates surprising correlations over tissues. This may have a significant impact on the classification of many cancer sites and may guide pathologists, both in research and daily practice. Moreover, these results based on unsupervised analysis yielded a signature predictive of clinical outcome in breast cancer. Additionally, we hypothesize that metastases from gastrointestinal origin either remember their tissue of origin or adapt to the tissue of destination. More specifically, colon metastases in the liver show strong evidence for such a bimodal tissue specific profile.

  6. Human Papilloma Virus Vaccination for Control of Cervical Cancer ...

    African Journals Online (AJOL)

    Human Papilloma Virus Vaccination for Control of Cervical Cancer: A ... Primary HPV prevention may be the key to reducing incidence and burden of cervical cancer ... Other resources included locally-published articles and additional internet ...

  7. Effect of Training on Knowledge about Cervical Cancer and Human ...

    African Journals Online (AJOL)

    UNIBEN

    Effect of Training on Knowledge about Cervical Cancer and Human. Papiloma Virus Vaccine ... debut, multiple sexual partners, smoking, history of sexually ... prevent cervical cancer. These include ..... needed to understand and explain the.

  8. Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Jinhee Park

    2016-11-01

    Full Text Available Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on water using radar has not been extensively studied, unlike the case on dry ground, due to its unique challenge. Namely, not only is the radar cross section of a human on water small, but the micro-Doppler signatures are much noisier due to water drops and waves. In this paper, we first investigate whether discriminative signatures could be obtained for activities on water through a simulation study. Then, we show how we can effectively achieve high classification accuracy by applying deep convolutional neural networks (DCNN directly to the spectrogram of real measurement data. From the five-fold cross-validation on our dataset, which consists of five aquatic activities, we report that the conventional feature-based scheme only achieves an accuracy of 45.1%. In contrast, the DCNN trained using only the collected data attains 66.7%, and the transfer learned DCNN, which takes a DCNN pre-trained on a RGB image dataset and fine-tunes the parameters using the collected data, achieves a much higher 80.3%, which is a significant performance boost.

  9. Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

    Science.gov (United States)

    Vidić, Igor; Egnell, Liv; Jerome, Neil P; Teruel, Jose R; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F; Goa, Pål Erik

    2018-05-01

    Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our

  10. MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

    Energy Technology Data Exchange (ETDEWEB)

    Young, M; Craft, D [Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States)

    2016-06-15

    Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchical clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve

  11. Exploring human error in military aviation flight safety events using post-incident classification systems.

    Science.gov (United States)

    Hooper, Brionny J; O'Hare, David P A

    2013-08-01

    Human error classification systems theoretically allow researchers to analyze postaccident data in an objective and consistent manner. The Human Factors Analysis and Classification System (HFACS) framework is one such practical analysis tool that has been widely used to classify human error in aviation. The Cognitive Error Taxonomy (CET) is another. It has been postulated that the focus on interrelationships within HFACS can facilitate the identification of the underlying causes of pilot error. The CET provides increased granularity at the level of unsafe acts. The aim was to analyze the influence of factors at higher organizational levels on the unsafe acts of front-line operators and to compare the errors of fixed-wing and rotary-wing operations. This study analyzed 288 aircraft incidents involving human error from an Australasian military organization occurring between 2001 and 2008. Action errors accounted for almost twice (44%) the proportion of rotary wing compared to fixed wing (23%) incidents. Both classificatory systems showed significant relationships between precursor factors such as the physical environment, mental and physiological states, crew resource management, training and personal readiness, and skill-based, but not decision-based, acts. The CET analysis showed different predisposing factors for different aspects of skill-based behaviors. Skill-based errors in military operations are more prevalent in rotary wing incidents and are related to higher level supervisory processes in the organization. The Cognitive Error Taxonomy provides increased granularity to HFACS analyses of unsafe acts.

  12. Alterations of 5-Hydroxymethylcytosine in Human Cancers

    Directory of Open Access Journals (Sweden)

    Ali Yesilkanal

    2013-06-01

    Full Text Available Prior to 2009, 5-methylcytosine (5-mC was thought to be the only biologically significant cytosine modification in mammalian DNA. With the discovery of the TET enzymes, which convert 5-methylcytosine (5-mC to 5-hydroxymethylcytosine (5-hmC, however, intense interest has emerged in determining the biological function of 5-hmC. Here, we review the techniques used to study 5-hmC and evidence that alterations to 5-hmC physiology play a functional role in the molecular pathogenesis of human cancers.

  13. Tumor-Associated Neutrophils in Human Lung Cancer

    Science.gov (United States)

    2017-10-01

    markers in humans. The logistical, ethical , and regulatory difficulties in obtaining human tumor tissue for research also act to discourage such...Mouse models of cancer. Annu. Rev. Pathol 6, 95–119 52. Merlo, L.M. et al. (2006) Cancer as an evolutionary and ecological process. Nat. Rev. Cancer...some effect on the phenotype and function of TANs. The logistical, ethical , and regulatory difficulties in obtaining human tumor tissue for research

  14. Finding Combination of Features from Promoter Regions for Ovarian Cancer-related Gene Group Classification

    KAUST Repository

    Olayan, Rawan S.

    2012-12-01

    In classification problems, it is always important to use the suitable combination of features that will be employed by classifiers. Generating the right combination of features usually results in good classifiers. In the situation when the problem is not well understood, data items are usually described by many features in the hope that some of these may be the relevant or most relevant ones. In this study, we focus on one such problem related to genes implicated in ovarian cancer (OC). We try to recognize two important OC-related gene groups: oncogenes, which support the development and progression of OC, and oncosuppressors, which oppose such tendencies. For this, we use the properties of promoters of these genes. We identified potential “regulatory features” that characterize OC-related oncogenes and oncosuppressors promoters. In our study, we used 211 oncogenes and 39 oncosuppressors. For these, we identified 538 characteristic sequence motifs from their promoters. Promoters are annotated by these motifs and derived feature vectors used to develop classification models. We made a comparison of a number of classification models in their ability to distinguish oncogenes from oncosuppressors. Based on 10-fold cross-validation, the resultant model was able to separate the two classes with sensitivity of 96% and specificity of 100% with the complete set of features. Moreover, we developed another recognition model where we attempted to distinguish oncogenes and oncosuppressors as one group from other OC-related genes. That model achieved accuracy of 82%. We believe that the results of this study will help in discovering other OC-related oncogenes and oncosuppressors not identified as yet.

  15. Finding Combination of Features from Promoter Regions for Ovarian Cancer-related Gene Group Classification

    KAUST Repository

    Olayan, Rawan S.

    2012-01-01

    In classification problems, it is always important to use the suitable combination of features that will be employed by classifiers. Generating the right combination of features usually results in good classifiers. In the situation when the problem is not well understood, data items are usually described by many features in the hope that some of these may be the relevant or most relevant ones. In this study, we focus on one such problem related to genes implicated in ovarian cancer (OC). We try to recognize two important OC-related gene groups: oncogenes, which support the development and progression of OC, and oncosuppressors, which oppose such tendencies. For this, we use the properties of promoters of these genes. We identified potential “regulatory features” that characterize OC-related oncogenes and oncosuppressors promoters. In our study, we used 211 oncogenes and 39 oncosuppressors. For these, we identified 538 characteristic sequence motifs from their promoters. Promoters are annotated by these motifs and derived feature vectors used to develop classification models. We made a comparison of a number of classification models in their ability to distinguish oncogenes from oncosuppressors. Based on 10-fold cross-validation, the resultant model was able to separate the two classes with sensitivity of 96% and specificity of 100% with the complete set of features. Moreover, we developed another recognition model where we attempted to distinguish oncogenes and oncosuppressors as one group from other OC-related genes. That model achieved accuracy of 82%. We believe that the results of this study will help in discovering other OC-related oncogenes and oncosuppressors not identified as yet.

  16. Cancer cell detection and classification using transformation invariant template learning methods

    International Nuclear Information System (INIS)

    Talware, Rajendra; Abhyankar, Aditya

    2011-01-01

    In traditional cancer cell detection, pathologists examine biopsies to make diagnostic assessments, largely based on cell morphology and tissue distribution. The process of image acquisition is very much subjective and the pattern undergoes unknown or random transformations during data acquisition (e.g. variation in illumination, orientation, translation and perspective) results in high degree of variability. Transformed Component Analysis (TCA) incorporates a discrete, hidden variable that accounts for transformations and uses the Expectation Maximization (EM) algorithm to jointly extract components and normalize for transformations. Further the TEMPLAR framework developed takes advantage of hierarchical pattern models and adds probabilistic modeling for local transformations. Pattern classification is based on Expectation Maximization algorithm and General Likelihood Ratio Tests (GLRT). Performance of TEMPLAR is certainly improved by defining area of interest on slide a priori. Performance can be further enhanced by making the kernel function adaptive during learning. (author)

  17. Gene Expression Profiles for Predicting Metastasis in Breast Cancer: A Cross-Study Comparison of Classification Methods

    Directory of Open Access Journals (Sweden)

    Mark Burton

    2012-01-01

    Full Text Available Machine learning has increasingly been used with microarray gene expression data and for the development of classifiers using a variety of methods. However, method comparisons in cross-study datasets are very scarce. This study compares the performance of seven classification methods and the effect of voting for predicting metastasis outcome in breast cancer patients, in three situations: within the same dataset or across datasets on similar or dissimilar microarray platforms. Combining classification results from seven classifiers into one voting decision performed significantly better during internal validation as well as external validation in similar microarray platforms than the underlying classification methods. When validating between different microarray platforms, random forest, another voting-based method, proved to be the best performing method. We conclude that voting based classifiers provided an advantage with respect to classifying metastasis outcome in breast cancer patients.

  18. Support vector machine classification and validation of cancer tissue samples using microarray expression data.

    Science.gov (United States)

    Furey, T S; Cristianini, N; Duffy, N; Bednarski, D W; Schummer, M; Haussler, D

    2000-10-01

    DNA microarray experiments generating thousands of gene expression measurements, are being used to gather information from tissue and cell samples regarding gene expression differences that will be useful in diagnosing disease. We have developed a new method to analyse this kind of data using support vector machines (SVMs). This analysis consists of both classification of the tissue samples, and an exploration of the data for mis-labeled or questionable tissue results. We demonstrate the method in detail on samples consisting of ovarian cancer tissues, normal ovarian tissues, and other normal tissues. The dataset consists of expression experiment results for 97,802 cDNAs for each tissue. As a result of computational analysis, a tissue sample is discovered and confirmed to be wrongly labeled. Upon correction of this mistake and the removal of an outlier, perfect classification of tissues is achieved, but not with high confidence. We identify and analyse a subset of genes from the ovarian dataset whose expression is highly differentiated between the types of tissues. To show robustness of the SVM method, two previously published datasets from other types of tissues or cells are analysed. The results are comparable to those previously obtained. We show that other machine learning methods also perform comparably to the SVM on many of those datasets. The SVM software is available at http://www.cs. columbia.edu/ approximately bgrundy/svm.

  19. A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification

    Directory of Open Access Journals (Sweden)

    Wang Lily

    2008-07-01

    Full Text Available Abstract Background Cancer diagnosis and clinical outcome prediction are among the most important emerging applications of gene expression microarray technology with several molecular signatures on their way toward clinical deployment. Use of the most accurate classification algorithms available for microarray gene expression data is a critical ingredient in order to develop the best possible molecular signatures for patient care. As suggested by a large body of literature to date, support vector machines can be considered "best of class" algorithms for classification of such data. Recent work, however, suggests that random forest classifiers may outperform support vector machines in this domain. Results In the present paper we identify methodological biases of prior work comparing random forests and support vector machines and conduct a new rigorous evaluation of the two algorithms that corrects these limitations. Our experiments use 22 diagnostic and prognostic datasets and show that support vector machines outperform random forests, often by a large margin. Our data also underlines the importance of sound research design in benchmarking and comparison of bioinformatics algorithms. Conclusion We found that both on average and in the majority of microarray datasets, random forests are outperformed by support vector machines both in the settings when no gene selection is performed and when several popular gene selection methods are used.

  20. An Entropy-based gene selection method for cancer classification using microarray data

    Directory of Open Access Journals (Sweden)

    Krishnan Arun

    2005-03-01

    Full Text Available Abstract Background Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. Results The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets Conclusion This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.

  1. Endogenous retroviral promoter exaptation in human cancer

    Directory of Open Access Journals (Sweden)

    Artem Babaian

    2016-12-01

    Full Text Available Abstract Cancer arises from a series of genetic and epigenetic changes, which result in abnormal expression or mutational activation of oncogenes, as well as suppression/inactivation of tumor suppressor genes. Aberrant expression of coding genes or long non-coding RNAs (lncRNAs with oncogenic properties can be caused by translocations, gene amplifications, point mutations or other less characterized mechanisms. One such mechanism is the inappropriate usage of normally dormant, tissue-restricted or cryptic enhancers or promoters that serve to drive oncogenic gene expression. Dispersed across the human genome, endogenous retroviruses (ERVs provide an enormous reservoir of autonomous gene regulatory modules, some of which have been co-opted by the host during evolution to play important roles in normal regulation of genes and gene networks. This review focuses on the “dark side” of such ERV regulatory capacity. Specifically, we discuss a growing number of examples of normally dormant or epigenetically repressed ERVs that have been harnessed to drive oncogenes in human cancer, a process we term onco-exaptation, and we propose potential mechanisms that may underlie this phenomenon.

  2. Human bladder cancer diagnosis using multiphoton microscopy

    Science.gov (United States)

    Mukherjee, Sushmita; Wysock, James S.; Ng, Casey K.; Akhtar, Mohammed; Perner, Sven; Lee, Ming-Ming; Rubin, Mark A.; Maxfield, Frederick R.; Webb, Watt W.; Scherr, Douglas S.

    2009-02-01

    At the time of diagnosis, approximately 75% of bladder cancers are non-muscle invasive. Appropriate diagnosis and surgical resection at this stage improves prognosis dramatically. However, these lesions, being small and/or flat, are often missed by conventional white-light cystoscopes. Furthermore, it is difficult to assess the surgical margin for negativity using conventional cystoscopes. Resultantly, the recurrence rates in patients with early bladder cancer are very high. This is currently addressed by repeat cystoscopies and biopsies, which can last throughout the life of a patient, increasing cost and patient morbidity. Multiphoton endoscopes offer a potential solution, allowing real time, noninvasive biopsies of the human bladder, as well as an up-close assessment of the resection margin. While miniaturization of the Multiphoton microscope into an endoscopic format is currently in progress, we present results here indicating that Multiphoton imaging (using a bench-top Multiphoton microscope) can indeed identify cancers in fresh, unfixed human bladder biopsies. Multiphoton images are acquired in two channels: (1) broadband autofluorescence from cells, and (2) second harmonic generation (SHG), mostly by tissue collagen. These images are then compared with gold standard hematoxylin/eosin (H&E) stained histopathology slides from the same specimen. Based on a "training set" and a very small "blinded set" of samples, we have found excellent correlation between the Multiphoton and histopathological diagnoses. A larger blinded analysis by two independent uropathologists is currently in progress. We expect that the conclusion of this phase will provide us with diagnostic accuracy estimates, as well as the degree of inter-observer heterogeneity.

  3. Predicting decisions in human social interactions using real-time fMRI and pattern classification.

    Science.gov (United States)

    Hollmann, Maurice; Rieger, Jochem W; Baecke, Sebastian; Lützkendorf, Ralf; Müller, Charles; Adolf, Daniela; Bernarding, Johannes

    2011-01-01

    Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.

  4. Predicting decisions in human social interactions using real-time fMRI and pattern classification.

    Directory of Open Access Journals (Sweden)

    Maurice Hollmann

    Full Text Available Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.

  5. Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

    Science.gov (United States)

    Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio

    2018-01-01

    )-based classification including feature ranking was performed. The accuracy attained exceeded the 92% in overall recognition of the 7 different cancer-related skin states. The proposed integration scheme is expected to allow the co-integration with other state-of-the-art technologies such as RNA-seq.

  6. Classification of weakly carcinogenic human papillomavirus types: addressing the limits of epidemiology at the borderline

    Directory of Open Access Journals (Sweden)

    Buonaguro Franco M

    2009-06-01

    Full Text Available Abstract Virtually all cases of cervical cancer are caused by persistent infections with a restricted set of human papillomaviruses (HPV. Some HPV types, like HPV16 and HPV18, are clear and powerful carcinogens. However, the categorization of the most weakly carcinogenic HPV types is extremely challenging. The decisions are important for screening test and vaccine development. This article describes for open discussion an approach recently taken by a World Health Organization International Agency for Research on Cancer (IARC Monographs Working Group to re-assess the carcinogenicity of different HPV types.

  7. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features

    Directory of Open Access Journals (Sweden)

    Eman Magdy

    2015-01-01

    Full Text Available Computer-aided diagnostic (CAD systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients’ lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately. Amplitude-Modulation Frequency-Modulation (AM-FM method thirdly, has been used to extract features for ROIs. Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR for classification step. Finally, K-nearest neighbour (KNN, support vector machine (SVM, naïve Bayes, and linear classifiers have been used with the selected AM-FM features. The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated. The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier.

  8. Classification of samples into two or more ordered populations with application to a cancer trial.

    Science.gov (United States)

    Conde, D; Fernández, M A; Rueda, C; Salvador, B

    2012-12-10

    In many applications, especially in cancer treatment and diagnosis, investigators are interested in classifying patients into various diagnosis groups on the basis of molecular data such as gene expression or proteomic data. Often, some of the diagnosis groups are known to be related to higher or lower values of some of the predictors. The standard methods of classifying patients into various groups do not take into account the underlying order. This could potentially result in high misclassification rates, especially when the number of groups is larger than two. In this article, we develop classification procedures that exploit the underlying order among the mean values of the predictor variables and the diagnostic groups by using ideas from order-restricted inference. We generalize the existing methodology on discrimination under restrictions and provide empirical evidence to demonstrate that the proposed methodology improves over the existing unrestricted methodology. The proposed methodology is applied to a bladder cancer data set where the researchers are interested in classifying patients into various groups. Copyright © 2012 John Wiley & Sons, Ltd.

  9. Computed aided system for separation and classification of the abnormal erythrocytes in human blood

    Science.gov (United States)

    Wąsowicz, Michał; Grochowski, Michał; Kulka, Marek; Mikołajczyk, Agnieszka; Ficek, Mateusz; Karpieńko, Katarzyna; Cićkiewicz, Maciej

    2017-12-01

    The human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified diamonds and oxidation modified. The blood was put under an impact of two diamond concentrations: 20μl and 100μl. The amount of abnormal cells increased with time. The percentage of echinocytes as a result of interaction with nanodiamonds in various time intervals for individual specimens was scarce. The impact of the two diamond types had no clinical importance on red blood cells. It is supposed that as a result of longlasting exposure a dehydratation of red cells takes place, because of the function of the cells. The analysis of an influence of nanodiamond particles on blood elements was supported by computer system designed for automatic counting and classification of the Red Blood Cells (RBC). The system utilizes advanced image processing methods for RBCs separation and counting and Eigenfaces method coupled with the neural networks for RBCs classification into normal and abnormal cells purposes.

  10. Real-time classification of auditory sentences using evoked cortical activity in humans

    Science.gov (United States)

    Moses, David A.; Leonard, Matthew K.; Chang, Edward F.

    2018-06-01

    Objective. Recent research has characterized the anatomical and functional basis of speech perception in the human auditory cortex. These advances have made it possible to decode speech information from activity in brain regions like the superior temporal gyrus, but no published work has demonstrated this ability in real-time, which is necessary for neuroprosthetic brain-computer interfaces. Approach. Here, we introduce a real-time neural speech recognition (rtNSR) software package, which was used to classify spoken input from high-resolution electrocorticography signals in real-time. We tested the system with two human subjects implanted with electrode arrays over the lateral brain surface. Subjects listened to multiple repetitions of ten sentences, and rtNSR classified what was heard in real-time from neural activity patterns using direct sentence-level and HMM-based phoneme-level classification schemes. Main results. We observed single-trial sentence classification accuracies of 90% or higher for each subject with less than 7 minutes of training data, demonstrating the ability of rtNSR to use cortical recordings to perform accurate real-time speech decoding in a limited vocabulary setting. Significance. Further development and testing of the package with different speech paradigms could influence the design of future speech neuroprosthetic applications.

  11. Clinical Relevance of KRAS in Human Cancers

    Directory of Open Access Journals (Sweden)

    Sylwia Jančík

    2010-01-01

    Full Text Available The KRAS gene (Ki-ras2 Kirsten rat sarcoma viral oncogene homolog is an oncogene that encodes a small GTPase transductor protein called KRAS. KRAS is involved in the regulation of cell division as a result of its ability to relay external signals to the cell nucleus. Activating mutations in the KRAS gene impair the ability of the KRAS protein to switch between active and inactive states, leading to cell transformation and increased resistance to chemotherapy and biological therapies targeting epidermal growth factor receptors. This review highlights some of the features of the KRAS gene and the KRAS protein and summarizes current knowledge of the mechanism of KRAS gene regulation. It also underlines the importance of activating mutations in the KRAS gene in relation to carcinogenesis and their importance as diagnostic biomarkers, providing clues regarding human cancer patients' prognosis and indicating potential therapeutic approaches.

  12. Laser Raman detection for oral cancer based on a Gaussian process classification method

    International Nuclear Information System (INIS)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Zhang, Chijun; Chen, He; Luo, Yusheng; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Shen, Aiguo; Hu, Jiming; Jia, Jun

    2013-01-01

    Oral squamous cell carcinoma is the most common neoplasm of the oral cavity. The incidence rate accounts for 80% of total oral cancer and shows an upward trend in recent years. It has a high degree of malignancy and is difficult to detect in terms of differential diagnosis, as a consequence of which the timing of treatment is always delayed. In this work, Raman spectroscopy was adopted to differentially diagnose oral squamous cell carcinoma and oral gland carcinoma. In total, 852 entries of raw spectral data which consisted of 631 items from 36 oral squamous cell carcinoma patients, 87 items from four oral gland carcinoma patients and 134 items from five normal people were collected by utilizing an optical method on oral tissues. The probability distribution of the datasets corresponding to the spectral peaks of the oral squamous cell carcinoma tissue was analyzed and the experimental result showed that the data obeyed a normal distribution. Moreover, the distribution characteristic of the noise was also in compliance with a Gaussian distribution. A Gaussian process (GP) classification method was utilized to distinguish the normal people and the oral gland carcinoma patients from the oral squamous cell carcinoma patients. The experimental results showed that all the normal people could be recognized. 83.33% of the oral squamous cell carcinoma patients could be correctly diagnosed and the remaining ones would be diagnosed as having oral gland carcinoma. For the classification process of oral gland carcinoma and oral squamous cell carcinoma, the correct ratio was 66.67% and the erroneously diagnosed percentage was 33.33%. The total sensitivity was 80% and the specificity was 100% with the Matthews correlation coefficient (MCC) set to 0.447 213 595. Considering the numerical results above, the application prospects and clinical value of this technique are significantly impressive. (letter)

  13. Laser Raman detection for oral cancer based on a Gaussian process classification method

    Science.gov (United States)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Zhang, Chijun; Chen, He; Luo, Yusheng; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

    2013-06-01

    Oral squamous cell carcinoma is the most common neoplasm of the oral cavity. The incidence rate accounts for 80% of total oral cancer and shows an upward trend in recent years. It has a high degree of malignancy and is difficult to detect in terms of differential diagnosis, as a consequence of which the timing of treatment is always delayed. In this work, Raman spectroscopy was adopted to differentially diagnose oral squamous cell carcinoma and oral gland carcinoma. In total, 852 entries of raw spectral data which consisted of 631 items from 36 oral squamous cell carcinoma patients, 87 items from four oral gland carcinoma patients and 134 items from five normal people were collected by utilizing an optical method on oral tissues. The probability distribution of the datasets corresponding to the spectral peaks of the oral squamous cell carcinoma tissue was analyzed and the experimental result showed that the data obeyed a normal distribution. Moreover, the distribution characteristic of the noise was also in compliance with a Gaussian distribution. A Gaussian process (GP) classification method was utilized to distinguish the normal people and the oral gland carcinoma patients from the oral squamous cell carcinoma patients. The experimental results showed that all the normal people could be recognized. 83.33% of the oral squamous cell carcinoma patients could be correctly diagnosed and the remaining ones would be diagnosed as having oral gland carcinoma. For the classification process of oral gland carcinoma and oral squamous cell carcinoma, the correct ratio was 66.67% and the erroneously diagnosed percentage was 33.33%. The total sensitivity was 80% and the specificity was 100% with the Matthews correlation coefficient (MCC) set to 0.447 213 595. Considering the numerical results above, the application prospects and clinical value of this technique are significantly impressive.

  14. Stratification and Prognostic Relevance of Jass’s Molecular Classification of Colorectal Cancer

    International Nuclear Information System (INIS)

    Zlobec, Inti; Bihl, Michel P.; Foerster, Anja; Rufle, Alex; Terracciano, Luigi; Lugli, Alessandro

    2012-01-01

    Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into five subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: Three hundred two patients were included in this study. Molecular analysis was performed for five CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1), MGMT, MSI, KRAS, and BRAF. Methylation in at least 4 promoters or in one to three promoters was considered CIMP-high and CIMP-low (CIMP-H/L), respectively. Results: CIMP-H, CIMP-L, and CIMP-negative were found in 7.1, 43, and 49.9% cases, respectively. One hundred twenty-three tumors (41%) could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-L, 14 CIMP-H, and two CIMP-negative cases. The 10 year survival rate for CIMP-high patients [22.6% (95%CI: 7–43)] was significantly lower than for CIMP-L or CIMP-negative (p = 0.0295). Only the combined analysis of BRAF and CIMP (negative versus L/H) led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  15. Stratification and Prognostic Relevance of Jass’s Molecular Classification of Colorectal Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Zlobec, Inti [Institute of Pathology, University of Bern, Bern (Switzerland); Institute for Pathology, University Hospital Basel, Basel (Switzerland); Bihl, Michel P.; Foerster, Anja; Rufle, Alex; Terracciano, Luigi [Institute for Pathology, University Hospital Basel, Basel (Switzerland); Lugli, Alessandro, E-mail: inti.zlobec@pathology.unibe.ch [Institute of Pathology, University of Bern, Bern (Switzerland); Institute for Pathology, University Hospital Basel, Basel (Switzerland)

    2012-02-27

    Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into five subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: Three hundred two patients were included in this study. Molecular analysis was performed for five CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1), MGMT, MSI, KRAS, and BRAF. Methylation in at least 4 promoters or in one to three promoters was considered CIMP-high and CIMP-low (CIMP-H/L), respectively. Results: CIMP-H, CIMP-L, and CIMP-negative were found in 7.1, 43, and 49.9% cases, respectively. One hundred twenty-three tumors (41%) could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-L, 14 CIMP-H, and two CIMP-negative cases. The 10 year survival rate for CIMP-high patients [22.6% (95%CI: 7–43)] was significantly lower than for CIMP-L or CIMP-negative (p = 0.0295). Only the combined analysis of BRAF and CIMP (negative versus L/H) led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  16. Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

    Directory of Open Access Journals (Sweden)

    Inti eZlobec

    2012-02-01

    Full Text Available Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP, microsatellite instability (MSI, KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1, MGMT, MSI, KRAS and BRAF. Tumors were CIMP-high or CIMP-low if ≥4 and 1-3 promoters were methylated, respectively. Results: CIMP-high, CIMP-low and CIMP–negative were found in 7.1%, 43% and 49.9% cases, respectively. 123 tumors (41% could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-low, 14 CIMP-high and 2 CIMP-negative cases. The 10-year survival rate for CIMP-high patients (22.6% (95%CI: 7-43 was significantly lower than for CIMP-low or CIMP-negative (p=0.0295. Only the combined analysis of BRAF and CIMP (negative versus low/high led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

  17. CD147 expression in human gastric cancer is associated with tumor recurrence and prognosis.

    Directory of Open Access Journals (Sweden)

    Dake Chu

    Full Text Available CD147 is correlated with tumor aggressiveness in various human malignancies. Here, we investigated CD147 protein expression in 223 patients with gastric cancer by immunohistochemistry and analyzed its association with disease-free and overall survival. CD147 was increased in gastric cancer compared to normal tissues. Additionally, CD147 expression was associated with gastric cancer invasion, metastasis and TNM stage, whereas it was not related to age, sex, differentiation status, tumor site or Lauren classification. Kaplan-Meier analysis confirmed that CD147 was associated with disease-free and overall survival in patients with gastric cancer; i.e., patients with positive CD147 staining tend to have worse disease-free and overall survival. Moreover, Cox's proportional hazards analysis demonstrated that CD147 was an independent marker of disease-free and overall survival for patients with gastric cancer. These results confirm the association of CD147 with gastric cancer invasion and metastasis and prove that CD147 might be an indicator of tumor recurrence and prognosis in gastric cancer.

  18. CASAnova: a multiclass support vector machine model for the classification of human sperm motility patterns.

    Science.gov (United States)

    Goodson, Summer G; White, Sarah; Stevans, Alicia M; Bhat, Sanjana; Kao, Chia-Yu; Jaworski, Scott; Marlowe, Tamara R; Kohlmeier, Martin; McMillan, Leonard; Zeisel, Steven H; O'Brien, Deborah A

    2017-11-01

    The ability to accurately monitor alterations in sperm motility is paramount to understanding multiple genetic and biochemical perturbations impacting normal fertilization. Computer-aided sperm analysis (CASA) of human sperm typically reports motile percentage and kinematic parameters at the population level, and uses kinematic gating methods to identify subpopulations such as progressive or hyperactivated sperm. The goal of this study was to develop an automated method that classifies all patterns of human sperm motility during in vitro capacitation following the removal of seminal plasma. We visually classified CASA tracks of 2817 sperm from 18 individuals and used a support vector machine-based decision tree to compute four hyperplanes that separate five classes based on their kinematic parameters. We then developed a web-based program, CASAnova, which applies these equations sequentially to assign a single classification to each motile sperm. Vigorous sperm are classified as progressive, intermediate, or hyperactivated, and nonvigorous sperm as slow or weakly motile. This program correctly classifies sperm motility into one of five classes with an overall accuracy of 89.9%. Application of CASAnova to capacitating sperm populations showed a shift from predominantly linear patterns of motility at initial time points to more vigorous patterns, including hyperactivated motility, as capacitation proceeds. Both intermediate and hyperactivated motility patterns were largely eliminated when sperm were incubated in noncapacitating medium, demonstrating the sensitivity of this method. The five CASAnova classifications are distinctive and reflect kinetic parameters of washed human sperm, providing an accurate, quantitative, and high-throughput method for monitoring alterations in motility. © The Authors 2017. Published by Oxford University Press on behalf of Society for the Study of Reproduction. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  19. Prediction of lung cancer patient survival via supervised machine learning classification techniques.

    Science.gov (United States)

    Lynch, Chip M; Abdollahi, Behnaz; Fuqua, Joshua D; de Carlo, Alexandra R; Bartholomai, James A; Balgemann, Rayeanne N; van Berkel, Victor H; Frieboes, Hermann B

    2017-12-01

    Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not well understood which types of techniques would yield more predictive information, and which data attributes should be used in order to determine this information. In this study, a number of supervised learning techniques is applied to the SEER database to classify lung cancer patients in terms of survival, including linear regression, Decision Trees, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), and a custom ensemble. Key data attributes in applying these methods include tumor grade, tumor size, gender, age, stage, and number of primaries, with the goal to enable comparison of predictive power between the various methods The prediction is treated like a continuous target, rather than a classification into categories, as a first step towards improving survival prediction. The results show that the predicted values agree with actual values for low to moderate survival times, which constitute the majority of the data. The best performing technique was the custom ensemble with a Root Mean Square Error (RMSE) value of 15.05. The most influential model within the custom ensemble was GBM, while Decision Trees may be inapplicable as it had too few discrete outputs. The results further show that among the five individual models generated, the most accurate was GBM with an RMSE value of 15.32. Although SVM underperformed with an RMSE value of 15.82, statistical analysis singles the SVM as the only model that generated a distinctive output. The results of the models are consistent with a classical Cox proportional hazards model used as a reference technique. We conclude that application of these supervised learning techniques to lung cancer data in the SEER database may be of use to estimate patient survival time

  20. Transduction motif analysis of gastric cancer based on a human signaling network

    Energy Technology Data Exchange (ETDEWEB)

    Liu, G.; Li, D.Z.; Jiang, C.S.; Wang, W. [Fuzhou General Hospital of Nanjing Command, Department of Gastroenterology, Fuzhou, China, Department of Gastroenterology, Fuzhou General Hospital of Nanjing Command, Fuzhou (China)

    2014-04-04

    To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the mining of gastric cancer-related motifs in a network with three vertices. The significant motif difference method was adopted to identify significantly different motifs in the normal and cancer states. Finally, we conducted a series of analyses of the significantly different motifs, including gene ontology, function annotation of genes, and model classification. A human signaling network was constructed, with 1643 nodes and 5089 regulating interactions. The network was configured to have the characteristics of other biological networks. There were 57,942 motifs marked with gastric cancer-related genes out of a total of 69,492 motifs, and 264 motifs were selected as significantly different motifs by calculating the significant motif difference (SMD) scores. Genes in significantly different motifs were mainly enriched in functions associated with cancer genesis, such as regulation of cell death, amino acid phosphorylation of proteins, and intracellular signaling cascades. The top five significantly different motifs were mainly cascade and positive feedback types. Almost all genes in the five motifs were cancer related, including EPOR, MAPK14, BCL2L1, KRT18, PTPN6, CASP3, TGFBR2, AR, and CASP7. The development of cancer might be curbed by inhibiting signal transductions upstream and downstream of the selected motifs.

  1. Cell nuclei attributed relational graphs for efficient representation and classification of gastric cancer in digital histopathology

    Science.gov (United States)

    Sharma, Harshita; Zerbe, Norman; Heim, Daniel; Wienert, Stephan; Lohmann, Sebastian; Hellwich, Olaf; Hufnagl, Peter

    2016-03-01

    This paper describes a novel graph-based method for efficient representation and subsequent classification in histological whole slide images of gastric cancer. Her2/neu immunohistochemically stained and haematoxylin and eosin stained histological sections of gastric carcinoma are digitized. Immunohistochemical staining is used in practice by pathologists to determine extent of malignancy, however, it is laborious to visually discriminate the corresponding malignancy levels in the more commonly used haematoxylin and eosin stain, and this study attempts to solve this problem using a computer-based method. Cell nuclei are first isolated at high magnification using an automatic cell nuclei segmentation strategy, followed by construction of cell nuclei attributed relational graphs of the tissue regions. These graphs represent tissue architecture comprehensively, as they contain information about cell nuclei morphology as vertex attributes, along with knowledge of neighborhood in the form of edge linking and edge attributes. Global graph characteristics are derived and ensemble learning is used to discriminate between three types of malignancy levels, namely, non-tumor, Her2/neu positive tumor and Her2/neu negative tumor. Performance is compared with state of the art methods including four texture feature groups (Haralick, Gabor, Local Binary Patterns and Varma Zisserman features), color and intensity features, and Voronoi diagram and Delaunay triangulation. Texture, color and intensity information is also combined with graph-based knowledge, followed by correlation analysis. Quantitative assessment is performed using two cross validation strategies. On investigating the experimental results, it can be concluded that the proposed method provides a promising way for computer-based analysis of histopathological images of gastric cancer.

  2. Automated classification of immunostaining patterns in breast tissue from the human protein atlas.

    Science.gov (United States)

    Swamidoss, Issac Niwas; Kårsnäs, Andreas; Uhlmann, Virginie; Ponnusamy, Palanisamy; Kampf, Caroline; Simonsson, Martin; Wählby, Carolina; Strand, Robin

    2013-01-01

    The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/). It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA) are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM)-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM) and linear discriminant analysis (LDA) classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many

  3. Automated classification of immunostaining patterns in breast tissue from the human protein Atlas

    Directory of Open Access Journals (Sweden)

    Issac Niwas Swamidoss

    2013-01-01

    Full Text Available Background: The Human Protein Atlas (HPA is an effort to map the location of all human proteins (http://www.proteinatlas.org/. It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples. Materials and Methods: The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM features, complex wavelet co-occurrence matrix (CWCM features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM and linear discriminant analysis (LDA classifier. Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue. Results: We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert. Conclusions: Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for

  4. Body mass index: different nutritional status according to WHO, OPAS and Lipschitz classifications in gastrointestinal cancer patients.

    Science.gov (United States)

    Barao, Katia; Forones, Nora Manoukian

    2012-01-01

    The body mass index (BMI) is the most common marker used on diagnoses of the nutritional status. The great advantage of this index is the easy way to measure, the low cost, the good correlation with the fat mass and the association to morbidity and mortality. To compare the BMI differences according to the WHO, OPAS and Lipschitz classification. A prospective study on 352 patients with esophageal, gastric or colorectal cancer was done. The BMI was calculated and analyzed by the classification of WHO, Lipschitz and OPAS. The mean age was 62.1 ± 12.4 years and 59% of them had more than 59 years. The BMI had not difference between the genders in patients cancer had more than 65 years. A different cut off must be used for this patients, because undernourished patients may be wrongly considered well nourished.

  5. Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections.

    Science.gov (United States)

    Kuepper, Claus; Kallenbach-Thieltges, Angela; Juette, Hendrik; Tannapfel, Andrea; Großerueschkamp, Frederik; Gerwert, Klaus

    2018-05-16

    A feasibility study using a quantum cascade laser-based infrared microscope for the rapid and label-free classification of colorectal cancer tissues is presented. Infrared imaging is a reliable, robust, automated, and operator-independent tissue classification method that has been used for differential classification of tissue thin sections identifying tumorous regions. However, long acquisition time by the so far used FT-IR-based microscopes hampered the clinical translation of this technique. Here, the used quantum cascade laser-based microscope provides now infrared images for precise tissue classification within few minutes. We analyzed 110 patients with UICC-Stage II and III colorectal cancer, showing 96% sensitivity and 100% specificity of this label-free method as compared to histopathology, the gold standard in routine clinical diagnostics. The main hurdle for the clinical translation of IR-Imaging is overcome now by the short acquisition time for high quality diagnostic images, which is in the same time range as frozen sections by pathologists.

  6. Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis

    Directory of Open Access Journals (Sweden)

    Amal Saki Malehi

    2016-01-01

    Full Text Available Aims: The aim of this study was to determine the prognostic index for separating homogenous subgroups in colorectal cancer (CRC patients based on clinicopathological characteristics using survival tree analysis. Methods: The current study was conducted at the Research Center of Gastroenterology and Liver Disease, Shahid Beheshti Medical University in Tehran, between January 2004 and January 2009. A total of 739 patients who already have been diagnosed with CRC based on pathologic report were enrolled. The data included demographic and clinical-pathological characteristic of patients. Tree-structured survival analysis based on a recursive partitioning algorithm was implemented to evaluate prognostic factors. The probability curves were calculated according to the Kaplan-Meier method, and the hazard ratio was estimated as an interest effect size. Result: There were 526 males (71.2% of these patients. The mean survival time (from diagnosis time was 42.46± (3.4. Survival tree identified three variables as main prognostic factors and based on their four prognostic subgroups was constructed. The log-rank test showed good separation of survival curves. Patients with Stage I-IIIA and treated with surgery as the first treatment showed low risk (median = 34 months whereas patients with stage IIIB, IV, and more than 68 years have the worse survival outcome (median = 9.5 months. Conclusion: Constructing the prognostic classification index via survival tree can aid the researchers to assess interaction between clinical variables and determining the cumulative effect of these variables on survival outcome.

  7. A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection.

    Science.gov (United States)

    Ceccarelli, Michele; d'Acierno, Antonio; Facchiano, Angelo

    2009-10-15

    Mass spectrometry spectra, widely used in proteomics studies as a screening tool for protein profiling and to detect discriminatory signals, are high dimensional data. A large number of local maxima (a.k.a. peaks) have to be analyzed as part of computational pipelines aimed at the realization of efficient predictive and screening protocols. With this kind of data dimensions and samples size the risk of over-fitting and selection bias is pervasive. Therefore the development of bio-informatics methods based on unsupervised feature extraction can lead to general tools which can be applied to several fields of predictive proteomics. We propose a method for feature selection and extraction grounded on the theory of multi-scale spaces for high resolution spectra derived from analysis of serum. Then we use support vector machines for classification. In particular we use a database containing 216 samples spectra divided in 115 cancer and 91 control samples. The overall accuracy averaged over a large cross validation study is 98.18. The area under the ROC curve of the best selected model is 0.9962. We improved previous known results on the problem on the same data, with the advantage that the proposed method has an unsupervised feature selection phase. All the developed code, as MATLAB scripts, can be downloaded from http://medeaserver.isa.cnr.it/dacierno/spectracode.htm.

  8. Statistical control chart and neural network classification for improving human fall detection

    KAUST Repository

    Harrou, Fouzi; Zerrouki, Nabil; Sun, Ying; Houacine, Amrane

    2017-01-01

    This paper proposes a statistical approach to detect and classify human falls based on both visual data from camera and accelerometric data captured by accelerometer. Specifically, we first use a Shewhart control chart to detect the presence of potential falls by using accelerometric data. Unfortunately, this chart cannot distinguish real falls from fall-like actions, such as lying down. To bypass this difficulty, a neural network classifier is then applied only on the detected cases through visual data. To assess the performance of the proposed method, experiments are conducted on the publicly available fall detection databases: the University of Rzeszow's fall detection (URFD) dataset. Results demonstrate that the detection phase play a key role in reducing the number of sequences used as input into the neural network classifier for classification, significantly reducing computational burden and achieving better accuracy.

  9. Statistical control chart and neural network classification for improving human fall detection

    KAUST Repository

    Harrou, Fouzi

    2017-01-05

    This paper proposes a statistical approach to detect and classify human falls based on both visual data from camera and accelerometric data captured by accelerometer. Specifically, we first use a Shewhart control chart to detect the presence of potential falls by using accelerometric data. Unfortunately, this chart cannot distinguish real falls from fall-like actions, such as lying down. To bypass this difficulty, a neural network classifier is then applied only on the detected cases through visual data. To assess the performance of the proposed method, experiments are conducted on the publicly available fall detection databases: the University of Rzeszow\\'s fall detection (URFD) dataset. Results demonstrate that the detection phase play a key role in reducing the number of sequences used as input into the neural network classifier for classification, significantly reducing computational burden and achieving better accuracy.

  10. An early history of human breast cancer: West meets East.

    Science.gov (United States)

    Yan, Shou-He

    2013-09-01

    Cancer has been increasingly recognized as a global issue. This is especially true in countries like China, where cancer incidence has increased likely because of changes in environment and lifestyle. However, cancer is not a modern disease; early cases have been recorded in ancient medical books in the West and in China. Here, we provide a brief history of cancer, focusing on cancer of the breast, and review the etymology of ai, the Chinese character for cancer. Notable findings from both Western and Chinese traditional medicine are presented to give an overview of the most important, early contributors to our evolving understanding of human breast cancer. We also discuss the earliest historical documents to record patients with breast cancer.

  11. Transposable Elements in Human Cancer: Causes and Consequences of Deregulation

    Science.gov (United States)

    Anwar, Sumadi Lukman; Wulaningsih, Wahyu; Lehmann, Ulrich

    2017-01-01

    Transposable elements (TEs) comprise nearly half of the human genome and play an essential role in the maintenance of genomic stability, chromosomal architecture, and transcriptional regulation. TEs are repetitive sequences consisting of RNA transposons, DNA transposons, and endogenous retroviruses that can invade the human genome with a substantial contribution in human evolution and genomic diversity. TEs are therefore firmly regulated from early embryonic development and during the entire course of human life by epigenetic mechanisms, in particular DNA methylation and histone modifications. The deregulation of TEs has been reported in some developmental diseases, as well as for different types of human cancers. To date, the role of TEs, the mechanisms underlying TE reactivation, and the interplay with DNA methylation in human cancers remain largely unexplained. We reviewed the loss of epigenetic regulation and subsequent genomic instability, chromosomal aberrations, transcriptional deregulation, oncogenic activation, and aberrations of non-coding RNAs as the potential mechanisms underlying TE deregulation in human cancers. PMID:28471386

  12. Transposable Elements in Human Cancer: Causes and Consequences of Deregulation

    Directory of Open Access Journals (Sweden)

    Sumadi Lukman Anwar

    2017-05-01

    Full Text Available Transposable elements (TEs comprise nearly half of the human genome and play an essential role in the maintenance of genomic stability, chromosomal architecture, and transcriptional regulation. TEs are repetitive sequences consisting of RNA transposons, DNA transposons, and endogenous retroviruses that can invade the human genome with a substantial contribution in human evolution and genomic diversity. TEs are therefore firmly regulated from early embryonic development and during the entire course of human life by epigenetic mechanisms, in particular DNA methylation and histone modifications. The deregulation of TEs has been reported in some developmental diseases, as well as for different types of human cancers. To date, the role of TEs, the mechanisms underlying TE reactivation, and the interplay with DNA methylation in human cancers remain largely unexplained. We reviewed the loss of epigenetic regulation and subsequent genomic instability, chromosomal aberrations, transcriptional deregulation, oncogenic activation, and aberrations of non-coding RNAs as the potential mechanisms underlying TE deregulation in human cancers.

  13. Molecular concept in human oral cancer

    OpenAIRE

    Krishna, Akhilesh; Singh, Shraddha; Kumar, Vijay; Pal, U. S.

    2015-01-01

    The incidence of oral cancer remains high in both Asian and Western countries. Several risk factors associated with development of oral cancer are now well-known, including tobacco chewing, smoking, and alcohol consumption. Cancerous risk factors may cause many genetic events through chromosomal alteration or mutations in genetic material and lead to progression and development of oral cancer through histological progress, carcinogenesis. Oral squamous carcinogenesis is a multistep process in...

  14. Human errors identification using the human factors analysis and classification system technique (HFACS

    Directory of Open Access Journals (Sweden)

    G. A. Shirali

    2013-12-01

    .Result: In this study, 158 reports of accident in Ahvaz steel industry were analyzed by HFACS technique. This analysis showed that most of the human errors were: in the first level was related to the skill-based errors, in the second to the physical environment, in the third level to the inadequate supervision and in the fourth level to the management of resources. .Conclusion: Studying and analyzing of past events using the HFACS technique can identify the major and root causes of accidents and can be effective on prevent repetitions of such mishaps. Also, it can be used as a basis for developing strategies to prevent future events in steel industries.

  15. Classifying Human Activity Patterns from Smartphone Collected GPS data: a Fuzzy Classification and Aggregation Approach.

    Science.gov (United States)

    Wan, Neng; Lin, Ge

    2016-12-01

    Smartphones have emerged as a promising type of equipment for monitoring human activities in environmental health studies. However, degraded location accuracy and inconsistency of smartphone-measured GPS data have limited its effectiveness for classifying human activity patterns. This study proposes a fuzzy classification scheme for differentiating human activity patterns from smartphone-collected GPS data. Specifically, a fuzzy logic reasoning was adopted to overcome the influence of location uncertainty by estimating the probability of different activity types for single GPS points. Based on that approach, a segment aggregation method was developed to infer activity patterns, while adjusting for uncertainties of point attributes. Validations of the proposed methods were carried out based on a convenient sample of three subjects with different types of smartphones. The results indicate desirable accuracy (e.g., up to 96% in activity identification) with use of this method. Two examples were provided in the appendix to illustrate how the proposed methods could be applied in environmental health studies. Researchers could tailor this scheme to fit a variety of research topics.

  16. Genetic Fuzzy System (GFS based wavelet co-occurrence feature selection in mammogram classification for breast cancer diagnosis

    Directory of Open Access Journals (Sweden)

    Meenakshi M. Pawar

    2016-09-01

    Full Text Available Breast cancer is significant health problem diagnosed mostly in women worldwide. Therefore, early detection of breast cancer is performed with the help of digital mammography, which can reduce mortality rate. This paper presents wrapper based feature selection approach for wavelet co-occurrence feature (WCF using Genetic Fuzzy System (GFS in mammogram classification problem. The performance of GFS algorithm is explained using mini-MIAS database. WCF features are obtained from detail wavelet coefficients at each level of decomposition of mammogram image. At first level of decomposition, 18 features are applied to GFS algorithm, which selects 5 features with an average classification success rate of 39.64%. Subsequently, at second level it selects 9 features from 36 features and the classification success rate is improved to 56.75%. For third level, 16 features are selected from 54 features and average success rate is improved to 64.98%. Lastly, at fourth level 72 features are applied to GFS, which selects 16 features and thereby increasing average success rate to 89.47%. Hence, GFS algorithm is the effective way of obtaining optimal set of feature in breast cancer diagnosis.

  17. miR-134: A Human Cancer Suppressor?

    Directory of Open Access Journals (Sweden)

    Jing-Yu Pan

    2017-03-01

    Full Text Available MicroRNAs (miRNAs are small noncoding RNAs approximately 20–25 nt in length, which play crucial roles through directly binding to corresponding 3′ UTR of targeted mRNAs. It has been reported that miRNAs are involved in numerous of diseases, including cancers. Recently, miR-134 has been identified to dysregulate in handles of human cancers, such as lung cancer, glioma, breast cancer, colorectal cancer, and so on. Increasing evidence indicates that miR-134 is essential for human carcinoma and participates in tumor cell proliferation, apoptosis, invasion and metastasis, drug resistance, as well as cancer diagnosis, treatment, and prognosis. Nevertheless, its roles in human cancer are still ambiguous, and its mechanisms are sophisticated as well, referring to a variety of targets and signal pathways, such as STAT5B, KRAS, MAPK/ERK signal pathway, Notch pathway, etc. Herein, we review the crucial roles of miR-134 in scores of human cancers via analyzing latest investigations, which might provide evidence for cancer diagnose, treatment, prognosis, or further investigations.

  18. REGγ is associated with multiple oncogenic pathways in human cancers

    International Nuclear Information System (INIS)

    He, Jing; Wang, Zhuo; Shi, Tieliu; Zhang, Pei; Chen, Rui; Li, Xiaotao; Cui, Long; Zeng, Yu; Wang, Guangqiang; Zhou, Ping; Yang, Yuanyuan; Ji, Lei; Zhao, Yanyan; Chen, Jiwu

    2012-01-01

    Recent studies suggest a role of the proteasome activator, REGγ, in cancer progression. Since there are limited numbers of known REGγ targets, it is not known which cancers and pathways are associated with REGγ. REGγ protein expressions in four different cancers were investigated by immunohistochemistry (IHC) analysis. Following NCBI Gene Expression Omnibus (GEO) database search, microarray platform validation, differential expressions of REGγ in corresponding cancers were statistically analyzed. Genes highly correlated with REGγ were defined based on Pearson's correlation coefficient. Functional links were estimated by Ingenuity Core analysis. Finally, validation was performed by RT-PCR analysis in established cancer cell lines and IHC in human colon cancer tissues Here, we demonstrate overexpression of REGγ in four different cancer types by micro-tissue array analysis. Using meta-analysis of publicly available microarray databases and biological studies, we verified elevated REGγ gene expression in the four types of cancers and identified genes significantly correlated with REGγ expression, including genes in p53, Myc pathways, and multiple other cancer-related pathways. The predicted correlations were largely consistent with quantitative RT-PCR analysis. This study provides us novel insights in REGγ gene expression profiles and its link to multiple cancer-related pathways in cancers. Our results indicate potentially important pathogenic roles of REGγ in multiple cancer types and implicate REGγ as a putative cancer marker

  19. Survival differences of CIMP subtypes integrated with CNA information in human breast cancer.

    Science.gov (United States)

    Wang, Huihan; Yan, Weili; Zhang, Shumei; Gu, Yue; Wang, Yihan; Wei, Yanjun; Liu, Hongbo; Wang, Fang; Wu, Qiong; Zhang, Yan

    2017-07-25

    CpG island methylator phenotype of breast cancer is associated with widespread aberrant methylation at specified CpG islands and distinct patient outcomes. However, the influence of copy number contributing to the prognosis of tumors with different CpG island methylator phenotypes is still unclear. We analyzed both genetic (copy number) and epigenetic alterations in 765 breast cancers from The Cancer Genome Atlas data portal and got a panel of 15 biomarkers for copy number and methylation status evaluation. The gene panel identified two groups corresponding to distinct copy number profiles. In status of mere-loss copy number, patients were faced with a greater risk if they presented a higher CpG islands methylation pattern in biomarker panels. But for samples presenting merely-gained copy number, higher methylation level of CpG islands was associated with improved viability. In all, the integration of copy number alteration and methylation information enhanced the classification power on prognosis. Moreover, we found the molecular subtypes of breast cancer presented different distributions in two CpG island methylation phenotypes. Generated by the same set of human methylation 450K data, additional copy number information could provide insights into survival prediction of cancers with less heterogeneity and might help to determine the biomarkers for diagnosis and treatment for breast cancer patients in a more personalized approach.

  20. Human HRAD9B and testicular cancer

    International Nuclear Information System (INIS)

    Hopkins, K.M.; Wang, X.; Berlin, A.; Thaker, H.M.; Lieberman, H.B.

    2003-01-01

    Full text: The HRAD9 gene mediates radioresistance and regulates the G2/M cell cycle checkpoint induced by ionizing radiation. In this report, we describe the isolation of the human paralog of HRAD9, called HRAD9B. Furthermore, we demonstrate that, like HRAD9 protein, the HRAD9B gene product can coimmunoprecipitate with HRAD1, HRAD9, HHUS1 and HHUS1B proteins. However, HRAD9B is expressed predominantly in testis, whereas its paralog is expressed more universally in different tissues. And most notably, we demonstrate that HRAD9B exhibits markedly and consistently reduced expression in testicular seminomas, high levels of expression in normal adult testis, yet also shows expression in fetal testis cells where meiosis is not performed. These results suggest that HRAD9B could at the least serve as a marker for testicular cancer, and its expression may be causally related to the disease. Further studies are under way to determine the cause of the reduced expression of HRAD9B in germ cell tumors

  1. Towards the human colorectal cancer microbiome.

    Directory of Open Access Journals (Sweden)

    Julian R Marchesi

    Full Text Available Multiple factors drive the progression from healthy mucosa towards sporadic colorectal carcinomas and accumulating evidence associates intestinal bacteria with disease initiation and progression. Therefore, the aim of this study was to provide a first high-resolution map of colonic dysbiosis that is associated with human colorectal cancer (CRC. To this purpose, the microbiomes colonizing colon tumor tissue and adjacent non-malignant mucosa were compared by deep rRNA sequencing. The results revealed striking differences in microbial colonization patterns between these two sites. Although inter-individual colonization in CRC patients was variable, tumors consistently formed a niche for Coriobacteria and other proposed probiotic bacterial species, while potentially pathogenic Enterobacteria were underrepresented in tumor tissue. As the intestinal microbiota is generally stable during adult life, these findings suggest that CRC-associated physiological and metabolic changes recruit tumor-foraging commensal-like bacteria. These microbes thus have an apparent competitive advantage in the tumor microenvironment and thereby seem to replace pathogenic bacteria that may be implicated in CRC etiology. This first glimpse of the CRC microbiome provides an important step towards full understanding of the dynamic interplay between intestinal microbial ecology and sporadic CRC, which may provide important leads towards novel microbiome-related diagnostic tools and therapeutic interventions.

  2. Restaging and Survival Analysis of 4036 Ovarian Cancer Patients According to the 2013 FIGO Classification for Ovarian, Fallopian Tube, and Primary Peritoneal Cancer

    DEFF Research Database (Denmark)

    Rosendahl, Mikkel; Høgdall, Claus Kim; Mosgaard, Berit Jul

    2016-01-01

    OBJECTIVE: With the 2013 International Federation of Gynecology and Obstetrics (FIGO) staging for ovarian, fallopian tube, and primary peritoneal cancer, the number of substages changed from 10 to 14. Any classification of a malignancy should easily assign patients to prognostic groups, refer....... MATERIALS AND METHODS: Demographic, surgical, histological, and survival data from 4036 ovarian cancer patients were used in the analysis. Five-year survival rates (5YSR) and hazard ratios for the old and revised FIGO staging were calculated using Kaplan-Meier curves and Cox regression. RESULTS: A total...

  3. Comparison of Computational Algorithms for the Classification of Liver Cancer using SELDI Mass Spectrometry: A Case Study

    Directory of Open Access Journals (Sweden)

    Robert J Hickey

    2007-01-01

    Full Text Available Introduction: As an alternative to DNA microarrays, mass spectrometry based analysis of proteomic patterns has shown great potential in cancer diagnosis. The ultimate application of this technique in clinical settings relies on the advancement of the technology itself and the maturity of the computational tools used to analyze the data. A number of computational algorithms constructed on different principles are available for the classification of disease status based on proteomic patterns. Nevertheless, few studies have addressed the difference in the performance of these approaches. In this report, we describe a comparative case study on the classification accuracy of hepatocellular carcinoma based on the serum proteomic pattern generated from a Surface Enhanced Laser Desorption/Ionization (SELDI mass spectrometer.Methods: Nine supervised classifi cation algorithms are implemented in R software and compared for the classification accuracy.Results: We found that the support vector machine with radial function is preferable as a tool for classification of hepatocellular carcinoma using features in SELDI mass spectra. Among the rest of the methods, random forest and prediction analysis of microarrays have better performance. A permutation-based technique reveals that the support vector machine with a radial function seems intrinsically superior in learning from the training data since it has a lower prediction error than others when there is essentially no differential signal. On the other hand, the performance of the random forest and prediction analysis of microarrays rely on their capability of capturing the signals with substantial differentiation between groups.Conclusions: Our finding is similar to a previous study, where classification methods based on the Matrix Assisted Laser Desorption/Ionization (MALDI mass spectrometry are compared for the prediction accuracy of ovarian cancer. The support vector machine, random forest and prediction

  4. Apoptosis induction of epifriedelinol on human cervical cancer cell line

    African Journals Online (AJOL)

    Background: Present investigation evaluates the antitumor activity of epifriedelinol for the management of cervical cancer by inducing process of apoptosis. Methods: Human Cervical Cancer Cell Line, C33A and HeLa were selected for study and treated with epifriedelinol at a concentration of (50-1000 μg/ml). Cytotoxicity of ...

  5. Identification of hormonal receptors in human breast cancer

    International Nuclear Information System (INIS)

    Rosa Pascual, M.; Lage, A.; Diaz, J.W.; Moreno, L.; Marta Diaz, T.

    1981-01-01

    The experience in the implementation of a technique for determining hormono-dependence of human breast cancer is presented. The results found with the use of the technique in 50 patients with malignant breast cancer treated at IOR are examined and discussed. (author)

  6. Acceptability of human papilloma virus vaccine and cervical cancer ...

    African Journals Online (AJOL)

    2012-07-14

    Jul 14, 2012 ... names in a prepared sampling frame of each group of workers, and thereafter ... Following individual counseling of eligible participants, .... Stanley M. Human Papilloma Virus Vaccines versus cervical cancer screening.

  7. Cloning of Novel Oncogenes Involved in Human Breast Cancer

    National Research Council Canada - National Science Library

    Clark, Geoffrey

    1998-01-01

    .... In order to identify genes which may play a role in breast cancer we have begun a process of manufacturing cDNA expression libraries derived from human breast tumor cell lines in retroviral vectors...

  8. Raman spectroscopy and imaging: applications in human breast cancer diagnosis.

    Science.gov (United States)

    Brozek-Pluska, Beata; Musial, Jacek; Kordek, Radzislaw; Bailo, Elena; Dieing, Thomas; Abramczyk, Halina

    2012-08-21

    The applications of spectroscopic methods in cancer detection open new possibilities in early stage diagnostics. Raman spectroscopy and Raman imaging represent novel and rapidly developing tools in cancer diagnosis. In the study described in this paper Raman spectroscopy has been employed to examine noncancerous and cancerous human breast tissues of the same patient. The most significant differences between noncancerous and cancerous tissues were found in regions characteristic for the vibrations of carotenoids, lipids and proteins. Particular attention was paid to the role played by unsaturated fatty acids in the differentiation between the noncancerous and the cancerous tissues. Comparison of Raman spectra of the noncancerous and the cancerous tissues with the spectra of oleic, linoleic, α-linolenic, γ-linolenic, docosahexaenoic and eicosapentaenoic acids has been presented. The role of sample preparation in the determination of cancer markers is also discussed in this study.

  9. Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism.

    Science.gov (United States)

    Mohammed, Akram; Guda, Chittibabu

    2015-01-01

    Enzymes are known as the molecular machines that drive the metabolism of an organism; hence identification of the full enzyme complement of an organism is essential to build the metabolic blueprint of that species as well as to understand the interplay of multiple species in an ecosystem. Experimental characterization of the enzymatic reactions of all enzymes in a genome is a tedious and expensive task. The problem is more pronounced in the metagenomic samples where even the species are not adequately cultured or characterized. Enzymes encoded by the gut microbiota play an essential role in the host metabolism; thus, warranting the need to accurately identify and annotate the full enzyme complements of species in the genomic and metagenomic projects. To fulfill this need, we develop and apply a method called ECemble, an ensemble approach to identify enzymes and enzyme classes and study the human gut metabolic pathways. ECemble method uses an ensemble of machine-learning methods to accurately model and predict enzymes from protein sequences and also identifies the enzyme classes and subclasses at the finest resolution. A tenfold cross-validation result shows accuracy between 97 and 99% at different levels in the hierarchy of enzyme classification, which is superior to comparable methods. We applied ECemble to predict the entire complements of enzymes from ten sequenced proteomes including the human proteome. We also applied this method to predict enzymes encoded by the human gut microbiome from gut metagenomic samples, and to study the role played by the microbe-derived enzymes in the human metabolism. After mapping the known and predicted enzymes to canonical human pathways, we identified 48 pathways that have at least one bacteria-encoded enzyme, which demonstrates the complementary role of gut microbiome in human gut metabolism. These pathways are primarily involved in metabolizing dietary nutrients such as carbohydrates, amino acids, lipids, cofactors and

  10. Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism

    Science.gov (United States)

    2015-01-01

    Background Enzymes are known as the molecular machines that drive the metabolism of an organism; hence identification of the full enzyme complement of an organism is essential to build the metabolic blueprint of that species as well as to understand the interplay of multiple species in an ecosystem. Experimental characterization of the enzymatic reactions of all enzymes in a genome is a tedious and expensive task. The problem is more pronounced in the metagenomic samples where even the species are not adequately cultured or characterized. Enzymes encoded by the gut microbiota play an essential role in the host metabolism; thus, warranting the need to accurately identify and annotate the full enzyme complements of species in the genomic and metagenomic projects. To fulfill this need, we develop and apply a method called ECemble, an ensemble approach to identify enzymes and enzyme classes and study the human gut metabolic pathways. Results ECemble method uses an ensemble of machine-learning methods to accurately model and predict enzymes from protein sequences and also identifies the enzyme classes and subclasses at the finest resolution. A tenfold cross-validation result shows accuracy between 97 and 99% at different levels in the hierarchy of enzyme classification, which is superior to comparable methods. We applied ECemble to predict the entire complements of enzymes from ten sequenced proteomes including the human proteome. We also applied this method to predict enzymes encoded by the human gut microbiome from gut metagenomic samples, and to study the role played by the microbe-derived enzymes in the human metabolism. After mapping the known and predicted enzymes to canonical human pathways, we identified 48 pathways that have at least one bacteria-encoded enzyme, which demonstrates the complementary role of gut microbiome in human gut metabolism. These pathways are primarily involved in metabolizing dietary nutrients such as carbohydrates, amino acids, lipids

  11. North American Magazine Coverage of Skin Cancer and Recreational Tanning Before and After the WHO/IARC 2009 Classification of Indoor Tanning Devices as Carcinogenic.

    Science.gov (United States)

    McWhirter, Jennifer E; Hoffman-Goetz, Laurie

    2015-09-01

    The mass media is an influential source of skin cancer information for the public. In 2009, the World Health Organization's International Agency for Research on Cancer classified UV radiation from tanning devices as carcinogenic. Our objective was to determine if media coverage of skin cancer and recreational tanning increased in volume or changed in nature after this classification. We conducted a directed content analysis on 29 North American popular magazines (2007-2012) to investigate the overall volume of articles on skin cancer and recreational tanning and, more specifically, the presence of skin cancer risk factors, UV behaviors, and early detection information in article text (n = 410) and images (n = 714). The volume of coverage on skin cancer and recreational tanning did not increase significantly after the 2009 classification of tanning beds as carcinogenic. Key-related messages, including that UV exposure is a risk factor for skin cancer and that indoor tanning should be avoided, were not reported more frequently after the classification, but the promotion of the tanned look as attractive was conveyed more often in images afterwards (p skin cancer risk factors, other UV behaviors, or early detection information over time. The classification of indoor tanning beds as carcinogenic had no significant impact on the volume or nature of skin cancer and recreational tanning coverage in magazines.

  12. Polarimetry based partial least square classification of ex vivo healthy and basal cell carcinoma human skin tissues.

    Science.gov (United States)

    Ahmad, Iftikhar; Ahmad, Manzoor; Khan, Karim; Ikram, Masroor

    2016-06-01

    Optical polarimetry was employed for assessment of ex vivo healthy and basal cell carcinoma (BCC) tissue samples from human skin. Polarimetric analyses revealed that depolarization and retardance for healthy tissue group were significantly higher (ppolarimetry together with PLS statistics hold promise for automated pathology classification. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Detection and Classification of Human Body Odor Using an Electronic Nose

    Directory of Open Access Journals (Sweden)

    Teerakiat Kerdcharoen

    2009-09-01

    Full Text Available An electronic nose (E-nose has been designed and equipped with software that can detect and classify human armpit body odor. An array of metal oxide sensors was used for detecting volatile organic compounds. The measurement circuit employs a voltage divider resistor to measure the sensitivity of each sensor. This E-nose was controlled by in-house developed software through a portable USB data acquisition card with a principle component analysis (PCA algorithm implemented for pattern recognition and classification. Because gas sensor sensitivity in the detection of armpit odor samples is affected by humidity, we propose a new method and algorithms combining hardware/software for the correction of the humidity noise. After the humidity correction, the E-nose showed the capability of detecting human body odor and distinguishing the body odors from two persons in a relative manner. The E-nose is still able to recognize people, even after application of deodorant. In conclusion, this is the first report of the application of an E-nose for armpit odor recognition.

  14. Detection and classification of human body odor using an electronic nose.

    Science.gov (United States)

    Wongchoosuk, Chatchawal; Lutz, Mario; Kerdcharoen, Teerakiat

    2009-01-01

    An electronic nose (E-nose) has been designed and equipped with software that can detect and classify human armpit body odor. An array of metal oxide sensors was used for detecting volatile organic compounds. The measurement circuit employs a voltage divider resistor to measure the sensitivity of each sensor. This E-nose was controlled by in-house developed software through a portable USB data acquisition card with a principle component analysis (PCA) algorithm implemented for pattern recognition and classification. Because gas sensor sensitivity in the detection of armpit odor samples is affected by humidity, we propose a new method and algorithms combining hardware/software for the correction of the humidity noise. After the humidity correction, the E-nose showed the capability of detecting human body odor and distinguishing the body odors from two persons in a relative manner. The E-nose is still able to recognize people, even after application of deodorant. In conclusion, this is the first report of the application of an E-nose for armpit odor recognition.

  15. Calorimetric signatures of human cancer cells and their nuclei

    Energy Technology Data Exchange (ETDEWEB)

    Todinova, S. [Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 21, Sofia 1113 (Bulgaria); Stoyanova, E. [Department of Molecular Immunology, Institute of Biology and Immunology of Reproduction, Bulgarian Academy of Sciences, Tzarigradsko shose Blvd. 73, Sofia 1113 (Bulgaria); Krumova, S., E-mail: sakrumo@gmail.com [Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 21, Sofia 1113 (Bulgaria); Iliev, I. [Institute of Experimental Morphology, Pathology and Anthropology with Museum, Acad. G. Bonchev Str., Bl. 25, Sofia 1113 (Bulgaria); Taneva, S.G. [Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 21, Sofia 1113 (Bulgaria)

    2016-01-10

    Graphical abstract: - Highlights: • Two temperature ranges are distinguished in the thermograms of cells/nuclei. • Different thermodynamic properties of cancer and normal human cells/nuclei. • Dramatic reduction of the enthalpy of the low-temperature range in cancer cells. • Oxaliplatin and 5-FU affect the nuclear matrix proteins and the DNA stability. - Abstract: The human cancer cell lines HeLa, JEG-3, Hep G2, SSC-9, PC-3, HT-29, MCF7 and their isolated nuclei were characterized by differential scanning calorimetry. The calorimetric profiles differed from normal human fibroblast (BJ) cells in the two well distinguished temperature ranges—the high-temperature range (H{sub T}, due to DNA-containing structures) and the low-temperature range (L{sub T}, assigned to the nuclear matrix and cellular proteins). The enthalpy of the L{sub T} range, and, respectively the ratio of the enthalpies of the L{sub T}- vs. H{sub T}-range, ΔH{sub L}/ΔH{sub H}, is strongly reduced for all cancer cells compared to normal fibroblasts. On the contrary, for most of the cancer nuclei this ratio is higher compared to normal nuclei. The HT-29 human colorectal cancer cells/nuclei differed most drastically from normal human fibroblast cells/nuclei. Our data also reveal that the treatment of HT-29 cancer cells with cytostatic drugs affects not only the DNA replication but also the cellular proteome.

  16. Oropharyngeal cancer and human papilloma virus: evolving diagnostic and management paradigms.

    Science.gov (United States)

    Buckley, Lisa; Gupta, Ruta; Ashford, Bruce; Jabbour, Joe; Clark, Jonathan R

    2016-06-01

    The significant increase in human papilloma virus (HPV)-associated oropharyngeal carcinoma (OPC) over recent years has lead to a surge in research and an improved understanding of the disease. Most patients with HPV-associated OPC present with cystic nodal metastases with a small primary tumour, and respond well to all treatment modalities including primary surgery and primary chemoradiotherapy. Current research is evaluating treatment de-escalation to reduce long-term treatment-associated morbidities. Transoral robotic surgery (TORS) is particularly relevant as the transoral approach allows small primary tumours to be removed with lower morbidity than traditional surgical approaches. The current American Joint Committee on Cancer staging system for oropharyngeal cancer does not appropriately stratify HPV-associated OPC; hence, alternative risk stratification and staging classifications are being proposed. © 2015 Royal Australasian College of Surgeons.

  17. Mastectomy or breast conserving surgery? Factors affecting type of surgical treatment for breast cancer – a classification tree approach

    International Nuclear Information System (INIS)

    Martin, Michael A; Meyricke, Ramona; O'Neill, Terry; Roberts, Steven

    2006-01-01

    A critical choice facing breast cancer patients is which surgical treatment – mastectomy or breast conserving surgery (BCS) – is most appropriate. Several studies have investigated factors that impact the type of surgery chosen, identifying features such as place of residence, age at diagnosis, tumor size, socio-economic and racial/ethnic elements as relevant. Such assessment of 'propensity' is important in understanding issues such as a reported under-utilisation of BCS among women for whom such treatment was not contraindicated. Using Western Australian (WA) data, we further examine the factors associated with the type of surgical treatment for breast cancer using a classification tree approach. This approach deals naturally with complicated interactions between factors, and so allows flexible and interpretable models for treatment choice to be built that add to the current understanding of this complex decision process. Data was extracted from the WA Cancer Registry on women diagnosed with breast cancer in WA from 1990 to 2000. Subjects' treatment preferences were predicted from covariates using both classification trees and logistic regression. Tumor size was the primary determinant of patient choice, subjects with tumors smaller than 20 mm in diameter preferring BCS. For subjects with tumors greater than 20 mm in diameter factors such as patient age, nodal status, and tumor histology become relevant as predictors of patient choice. Classification trees perform as well as logistic regression for predicting patient choice, but are much easier to interpret for clinical use. The selected tree can inform clinicians' advice to patients

  18. Lung cancer gene expression database analysis incorporating prior knowledge with support vector machine-based classification method

    Directory of Open Access Journals (Sweden)

    Huang Desheng

    2009-07-01

    Full Text Available Abstract Background A reliable and precise classification is essential for successful diagnosis and treatment of cancer. Gene expression microarrays have provided the high-throughput platform to discover genomic biomarkers for cancer diagnosis and prognosis. Rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, only some studies have been aware of the importance of prior information in cancer classification. Methods Together with the application of support vector machine as the discriminant approach, we proposed one modified method that incorporated prior knowledge into cancer classification based on gene expression data to improve accuracy. A public well-known dataset, Malignant pleural mesothelioma and lung adenocarcinoma gene expression database, was used in this study. Prior knowledge is viewed here as a means of directing the classifier using known lung adenocarcinoma related genes. The procedures were performed by software R 2.80. Results The modified method performed better after incorporating prior knowledge. Accuracy of the modified method improved from 98.86% to 100% in training set and from 98.51% to 99.06% in test set. The standard deviations of the modified method decreased from 0.26% to 0 in training set and from 3.04% to 2.10% in test set. Conclusion The method that incorporates prior knowledge into discriminant analysis could effectively improve the capacity and reduce the impact of noise. This idea may have good future not only in practice but also in methodology.

  19. Plasma membrane proteomics of human breast cancer cell lines identifies potential targets for breast cancer diagnosis and treatment.

    Directory of Open Access Journals (Sweden)

    Yvonne S Ziegler

    Full Text Available The use of broad spectrum chemotherapeutic agents to treat breast cancer results in substantial and debilitating side effects, necessitating the development of targeted therapies to limit tumor proliferation and prevent metastasis. In recent years, the list of approved targeted therapies has expanded, and it includes both monoclonal antibodies and small molecule inhibitors that interfere with key proteins involved in the uncontrolled growth and migration of cancer cells. The targeting of plasma membrane proteins has been most successful to date, and this is reflected in the large representation of these proteins as targets of newer therapies. In view of these facts, experiments were designed to investigate the plasma membrane proteome of a variety of human breast cancer cell lines representing hormone-responsive, ErbB2 over-expressing and triple negative cell types, as well as a benign control. Plasma membranes were isolated by using an aqueous two-phase system, and the resulting proteins were subjected to mass spectrometry analysis. Overall, each of the cell lines expressed some unique proteins, and a number of proteins were expressed in multiple cell lines, but in patterns that did not always follow traditional clinical definitions of breast cancer type. From our data, it can be deduced that most cancer cells possess multiple strategies to promote uncontrolled growth, reflected in aberrant expression of tyrosine kinases, cellular adhesion molecules, and structural proteins. Our data set provides a very rich and complex picture of plasma membrane proteins present on breast cancer cells, and the sorting and categorizing of this data provides interesting insights into the biology, classification, and potential treatment of this prevalent and debilitating disease.

  20. The correlation study of radiological findings with pathological classification of superficial depressed (IIc type) early gastric cancer

    International Nuclear Information System (INIS)

    Liu Linxiang; Deng Bingxing; Liu Yujin; Iinuma, G.; Moriyama, N.

    2007-01-01

    Objective: To investigate the relations between radiological findings and pathological classification of superficial depressed (II c type) early gastric cancer. Methods: Radiological features in subtonic double contrast barium examination and the endoscopic pictures of early gastric cancer compared with the global pathological specimens and micro-pathological features were prospectively studied. Combined with the gastric endoscopic pictures, the sharpness of margin of the lesions, the changes of converging mucosal folds and the changes of the depressed surface on the film of double contrast barium examination were analyzed. The correlation between the radiological features and histological classification of gastric cancer including well differentiated tubular adenocarcinoma (tub1), moderately differentiated tubular adenocarcinoma (tub2), poorly differentiated adenocarcinoma (por) and signet-ring cell carcinoma (sig) were studied. Results: In 102 cases of II c type early gastric cancer, there were tub1 27 cases, tub2 11, por 26 and sig 38 cases histologically. The margin of the depressed lesions of tubl (24 cases) and tub2 (9 cases) cancers were mostly unsharply demarcated or with fine spicular border, while the margin of lesions of por(15 cases) and sig(31 cases) were mostly clearly and sharply demarcated, with statistical significance (P<0.01). The depressed surface of tub1 and tub2 lesions (17 cases) revealed little unevenness, sometimes with evenly granulations, single nodule and scar-like depression, while that of por and sig lesions (41 cases) manifested as nodules of varying sizes, with statistical significance (P<0.01). Conclusion: The radiological findings of superficial depressed early gastric cancer in different histological types were different, the possible histological type could be speculated according to the radiological findings of the lesions. (authors)

  1. Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

    International Nuclear Information System (INIS)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Shen, Aiguo; Hu, Jiming; Jia, Jun

    2013-01-01

    The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory. (paper)

  2. Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

    Science.gov (United States)

    Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

    2013-03-01

    The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.

  3. Signatures of mutational processes in human cancer

    NARCIS (Netherlands)

    Alexandrov, L.B.; Nik-Zainal, S.; Wedge, D.C.; Aparicio, S.A.; Behjati, S.; Biankin, A.V.; Bignell, G.R.; Bolli, N.; Borg, A.; Borresen-Dale, A.L.; Boyault, S.; Burkhardt, B.; Butler, A.P.; Caldas, C.; Davies, H.R.; Desmedt, C.; Eils, R.; Eyfjord, J.E.; Foekens, J.A.; Greaves, M.; Hosoda, F.; Hutter, B.; Ilicic, T.; Imbeaud, S.; Imielinsk, M.; Jager, N.; Jones, D.T.; Knappskog, S.; Kool, M.; Lakhani, S.R.; Lopez-Otin, C.; Martin, S.; Munshi, N.C.; Nakamura, H.; Northcott, P.A.; Pajic, M.; Papaemmanuil, E.; Paradiso, A.; Pearson, J.V.; Puente, X.S.; Raine, K.; Ramakrishna, M.; Richardson, A.L.; Richter, J.; Rosenstiel, P.; Schlesner, M.; Schumacher, T.N.; Span, P.N.; Teague, J.W.; Totoki, Y.; Tutt, A.N.; Valdes-Mas, R.; Buuren, M.M. van; Veer, L. van 't; Vincent-Salomon, A.; Waddell, N.; Yates, L.R.; Zucman-Rossi, J.; Futreal, P.A.; McDermott, U.; Lichter, P.; Meyerson, M.; Grimmond, S.M.; Siebert, R.; Campo, E.; Shibata, T.; Pfister, S.M.; Campbell, P.J.; Stratton, M.R.; Schlooz-Vries, M.S.; Tol, J.J. van; Laarhoven, H.W. van; Sweep, F.C.; Bult, P.; et al.,

    2013-01-01

    All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362

  4. The detection, diagnosis and therapy of human lung cancer

    International Nuclear Information System (INIS)

    1978-01-01

    The Cancergram covers clinical aspects of cancers of the lung and tracheo-bronchial tree, i.e., the lower respiratory tract. This includes primary lung cancer in both early and advanced disease status. The topic includes clinically relevant aspects of the prevention, detection, diagnosis, evaluation, and therapy of lung cancer. Certain aspects of metastatic lung disease treatment or therapy which involve aspects of interest to primary lung cancer are included. With certain exceptions, general pre-clinical or animal studies not directly related to the primary human disease are excluded

  5. Human Papilloma Viruses and Breast Cancer – Assessment of Causality

    Science.gov (United States)

    Lawson, James Sutherland; Glenn, Wendy K.; Whitaker, Noel James

    2016-01-01

    High risk human papilloma viruses (HPVs) may have a causal role in some breast cancers. Case–control studies, conducted in many different countries, consistently indicate that HPVs are more frequently present in breast cancers as compared to benign breast and normal breast controls (odds ratio 4.02). The assessment of causality of HPVs in breast cancer is difficult because (i) the HPV viral load is extremely low, (ii) HPV infections are common but HPV associated breast cancers are uncommon, and (iii) HPV infections may precede the development of breast and other cancers by years or even decades. Further, HPV oncogenesis can be indirect. Despite these difficulties, the emergence of new evidence has made the assessment of HPV causality, in breast cancer, a practical proposition. With one exception, the evidence meets all the conventional criteria for a causal role of HPVs in breast cancer. The exception is “specificity.” HPVs are ubiquitous, which is the exact opposite of specificity. An additional reservation is that the prevalence of breast cancer is not increased in immunocompromised patients as is the case with respect to HPV-associated cervical cancer. This indicates that HPVs may have an indirect causal influence in breast cancer. Based on the overall evidence, high-risk HPVs may have a causal role in some breast cancers. PMID:27747193

  6. Human Papilloma Viruses and Breast Cancer - Assessment of Causality.

    Science.gov (United States)

    Lawson, James Sutherland; Glenn, Wendy K; Whitaker, Noel James

    2016-01-01

    High risk human papilloma viruses (HPVs) may have a causal role in some breast cancers. Case-control studies, conducted in many different countries, consistently indicate that HPVs are more frequently present in breast cancers as compared to benign breast and normal breast controls (odds ratio 4.02). The assessment of causality of HPVs in breast cancer is difficult because (i) the HPV viral load is extremely low, (ii) HPV infections are common but HPV associated breast cancers are uncommon, and (iii) HPV infections may precede the development of breast and other cancers by years or even decades. Further, HPV oncogenesis can be indirect. Despite these difficulties, the emergence of new evidence has made the assessment of HPV causality, in breast cancer, a practical proposition. With one exception, the evidence meets all the conventional criteria for a causal role of HPVs in breast cancer. The exception is "specificity." HPVs are ubiquitous, which is the exact opposite of specificity. An additional reservation is that the prevalence of breast cancer is not increased in immunocompromised patients as is the case with respect to HPV-associated cervical cancer. This indicates that HPVs may have an indirect causal influence in breast cancer. Based on the overall evidence, high-risk HPVs may have a causal role in some breast cancers.

  7. hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine.

    Science.gov (United States)

    Falgreen, Steffen; Ellern Bilgrau, Anders; Brøndum, Rasmus Froberg; Hjort Jakobsen, Lasse; Have, Jonas; Lindblad Nielsen, Kasper; El-Galaly, Tarec Christoffer; Bødker, Julie Støve; Schmitz, Alexander; H Young, Ken; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

    2016-01-01

    Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically. The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays.

  8. Current understanding of mdig/MINA in human cancers.

    Science.gov (United States)

    Thakur, Chitra; Chen, Fei

    2015-07-01

    Mineral dust-induced gene, mdig has recently been identified and is known to be overexpressed in a majority of human cancers and holds predictive power in the poor prognosis of the disease. Mdig is an environmentally expressed gene that is involved in cell proliferation, neoplastic transformation and immune regulation. With the advancement in deciphering the prognostic role of mdig in human cancers, our understanding on how mdig renders a normal cell to undergo malignant transformation is still very limited. This article reviews the current knowledge of the mdig gene in context to human neoplasias and its relation to the clinico-pathologic factors predicting the outcome of the disease in patients. It also emphasizes on the promising role of mdig that can serve as a potential candidate for biomarker discovery and as a therapeutic target in inflammation and cancers. Considering the recent advances in understanding the underlying mechanisms of tumor formation, more preclinical and clinical research is required to validate the potential of using mdig as a novel biological target of therapeutic and diagnostic value. Expression level of mdig influences the prognosis of several human cancers especially cancers of the breast and lung. Evaluation of mdig in cancers can offer novel biomarker with potential therapeutic interventions for the early assessment of cancer development in patients.

  9. BMI-1, a promising therapeutic target for human cancer

    Science.gov (United States)

    WANG, MIN-CONG; LI, CHUN-LI; CUI, JIE; JIAO, MIN; WU, TAO; JING, LI; NAN, KE-JUN

    2015-01-01

    BMI-1 oncogene is a member of the polycomb-group gene family and a transcriptional repressor. Overexpression of BMI-1 has been identified in various human cancer tissues and is known to be involved in cancer cell proliferation, cell invasion, distant metastasis, chemosensitivity and patient survival. Accumulating evidence has revealed that BMI-1 is also involved in the regulation of self-renewal, differentiation and tumor initiation of cancer stem cells (CSCs). However, the molecular mechanisms underlying these biological processes remain unclear. The present review summarized the function of BMI-1 in different human cancer types and CSCs, and discussed the signaling pathways in which BMI-1 is potentially involved. In conclusion, BMI-1 may represent a promising target for the prevention and therapy of various cancer types. PMID:26622537

  10. Maintenance of prolactin receptors in human breast cancer

    International Nuclear Information System (INIS)

    Ben-David, M.; Dror, Y.; Biran, S.

    1981-01-01

    Breast tissue specimens of 110 women with various stages of breast cancer were tested in vitro to determine their specific binding sites for human prolactin. In contrast to the case of steroid receptors, binding sites for prolactin were found in the vast majority of breast cancer tissue. Distribution profiles giving amount of prolactin receptor and their affinity coefficients were found to be similar in the tissues of women whose ages, hormonal status, or stage of breast cancer varied. These findings show that in contrast to steroid receptors, human breast cancer tissue maintains binding sites for prolactin. The findings also indicate that there may be a higher dependency of breast cancer on prolactin than on steroids. Clinical trials must be carried out to determine the role of ''positive'' prolactin receptors in prognosis and prediction of response to future hormone therapy. (author)

  11. Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.

    Science.gov (United States)

    Saini, Harsh; Lal, Sunil Pranit; Naidu, Vimal Vikash; Pickering, Vincel Wince; Singh, Gurmeet; Tsunoda, Tatsuhiko; Sharma, Alok

    2016-12-05

    High dimensional feature space generally degrades classification in several applications. In this paper, we propose a strategy called gene masking, in which non-contributing dimensions are heuristically removed from the data to improve classification accuracy. Gene masking is implemented via a binary encoded genetic algorithm that can be integrated seamlessly with classifiers during the training phase of classification to perform feature selection. It can also be used to discriminate between features that contribute most to the classification, thereby, allowing researchers to isolate features that may have special significance. This technique was applied on publicly available datasets whereby it substantially reduced the number of features used for classification while maintaining high accuracies. The proposed technique can be extremely useful in feature selection as it heuristically removes non-contributing features to improve the performance of classifiers.

  12. A SEMI-AUTOMATIC RULE SET BUILDING METHOD FOR URBAN LAND COVER CLASSIFICATION BASED ON MACHINE LEARNING AND HUMAN KNOWLEDGE

    Directory of Open Access Journals (Sweden)

    H. Y. Gu

    2017-09-01

    Full Text Available Classification rule set is important for Land Cover classification, which refers to features and decision rules. The selection of features and decision are based on an iterative trial-and-error approach that is often utilized in GEOBIA, however, it is time-consuming and has a poor versatility. This study has put forward a rule set building method for Land cover classification based on human knowledge and machine learning. The use of machine learning is to build rule sets effectively which will overcome the iterative trial-and-error approach. The use of human knowledge is to solve the shortcomings of existing machine learning method on insufficient usage of prior knowledge, and improve the versatility of rule sets. A two-step workflow has been introduced, firstly, an initial rule is built based on Random Forest and CART decision tree. Secondly, the initial rule is analyzed and validated based on human knowledge, where we use statistical confidence interval to determine its threshold. The test site is located in Potsdam City. We utilised the TOP, DSM and ground truth data. The results show that the method could determine rule set for Land Cover classification semi-automatically, and there are static features for different land cover classes.

  13. CRISPR/Cas9-mediated noncoding RNA editing in human cancers.

    Science.gov (United States)

    Yang, Jie; Meng, Xiaodan; Pan, Jinchang; Jiang, Nan; Zhou, Chengwei; Wu, Zhenhua; Gong, Zhaohui

    2018-01-02

    Cancer is characterized by multiple genetic and epigenetic alterations, including a higher prevalence of mutations of oncogenes and/or tumor suppressors. Mounting evidences have shown that noncoding RNAs (ncRNAs) are involved in the epigenetic regulation of cancer genes and their associated pathways. The clustered regularly interspaced short palindromic repeats (CRISPR)-associated nuclease 9 (CRISPR/Cas9) system, a revolutionary genome-editing technology, has shed light on ncRNA-based cancer therapy. Here, we briefly introduce the classifications and mechanisms of CRISPR/Cas9 system. Importantly, we mainly focused on the applications of CRISPR/Cas9 system as a molecular tool for ncRNA (microRNA, long noncoding RNA and circular RNA, etc.) editing in human cancers, and the novel techniques that are based on CRISPR/Cas9 system. Additionally, the off-target effects and the corresponding solutions as well as the challenges toward CRISPR/Cas9 were also evaluated and discussed. Long- and short-ncRNAs have been employed as targets in precision oncology, and CRISPR/Cas9-mediated ncRNA editing may provide an excellent way to cure cancer.

  14. Rhein Induces Apoptosis in Human Breast Cancer Cells

    Directory of Open Access Journals (Sweden)

    Ching-Yao Chang

    2012-01-01

    Full Text Available Human breast cancers cells overexpressing HER2/neu are more aggressive tumors with poor prognosis, and resistance to chemotherapy. This study investigates antiproliferation effects of anthraquinone derivatives of rhubarb root on human breast cancer cells. Of 7 anthraquinone derivatives, only rhein showed antiproliferative and apoptotic effects on both HER2-overexpressing MCF-7 (MCF-7/HER2 and control vector MCF-7 (MCF-7/VEC cells. Rhein induced dose- and time-dependent manners increase in caspase-9-mediated apoptosis correlating with activation of ROS-mediated activation of NF-κB- and p53-signaling pathways in both cell types. Therefore, this study highlighted rhein as processing anti-proliferative activity against HER2 overexpression or HER2-basal expression in breast cancer cells and playing important roles in apoptotic induction of human breast cancer cells.

  15. Defining the cellular precursors to human breast cancer

    Science.gov (United States)

    Keller, Patricia J.; Arendt, Lisa M.; Skibinski, Adam; Logvinenko, Tanya; Klebba, Ina; Dong, Shumin; Smith, Avi E.; Prat, Aleix; Perou, Charles M.; Gilmore, Hannah; Schnitt, Stuart; Naber, Stephen P.; Garlick, Jonathan A.; Kuperwasser, Charlotte

    2012-01-01

    Human breast cancers are broadly classified based on their gene-expression profiles into luminal- and basal-type tumors. These two major tumor subtypes express markers corresponding to the major differentiation states of epithelial cells in the breast: luminal (EpCAM+) and basal/myoepithelial (CD10+). However, there are also rare types of breast cancers, such as metaplastic carcinomas, where tumor cells exhibit features of alternate cell types that no longer resemble breast epithelium. Until now, it has been difficult to identify the cell type(s) in the human breast that gives rise to these various forms of breast cancer. Here we report that transformation of EpCAM+ epithelial cells results in the formation of common forms of human breast cancer, including estrogen receptor-positive and estrogen receptor-negative tumors with luminal and basal-like characteristics, respectively, whereas transformation of CD10+ cells results in the development of rare metaplastic tumors reminiscent of the claudin-low subtype. We also demonstrate the existence of CD10+ breast cells with metaplastic traits that can give rise to skin and epidermal tissues. Furthermore, we show that the development of metaplastic breast cancer is attributable, in part, to the transformation of these metaplastic breast epithelial cells. These findings identify normal cellular precursors to human breast cancers and reveal the existence of a population of cells with epidermal progenitor activity within adult human breast tissues. PMID:21940501

  16. Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification

    Directory of Open Access Journals (Sweden)

    D. Ramyachitra

    2015-09-01

    Full Text Available Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high compared to the number of data samples. Thus the difficulty that lies with data are of high dimensionality and the sample size is small. This research work addresses the problem by classifying resultant dataset using the existing algorithms such as Support Vector Machine (SVM, K-nearest neighbor (KNN, Interval Valued Classification (IVC and the improvised Interval Value based Particle Swarm Optimization (IVPSO algorithm. Thus the results show that the IVPSO algorithm outperformed compared with other algorithms under several performance evaluation functions.

  17. Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification.

    Science.gov (United States)

    Ramyachitra, D; Sofia, M; Manikandan, P

    2015-09-01

    Microarray technology allows simultaneous measurement of the expression levels of thousands of genes within a biological tissue sample. The fundamental power of microarrays lies within the ability to conduct parallel surveys of gene expression using microarray data. The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases such as cancer. In gene expression data, the number of genes is usually very high compared to the number of data samples. Thus the difficulty that lies with data are of high dimensionality and the sample size is small. This research work addresses the problem by classifying resultant dataset using the existing algorithms such as Support Vector Machine (SVM), K-nearest neighbor (KNN), Interval Valued Classification (IVC) and the improvised Interval Value based Particle Swarm Optimization (IVPSO) algorithm. Thus the results show that the IVPSO algorithm outperformed compared with other algorithms under several performance evaluation functions.

  18. Vaccines against human papilloma virus and cervical cancer: An overview

    Directory of Open Access Journals (Sweden)

    Sharma Savita

    2008-01-01

    Full Text Available The paradigm of preventing human papilloma virus (HPV infection through currently approved vaccines, namely, Gardasil, manufactured by Merck and Co., Inc. (Whitehouse Station, NJ and Cervarix, manufactured by GlaxoSmithKline (GSK, Philadelphia holds tremendous promise for the developing countries in decreasing the burden of HPV infection and its sequelae, such as cervical cancer, genital warts and anogenital cancers. Effective screening programs that have reduced the burden of this killer disease in the developed countries are still lacking in India, despite the high incidence of cervical cancer and the implementation of the National Cancer Control Programme since 1975. The recent breakthrough in the global war against cervical cancer will provide new insight for meeting the future challenge of the prevention of cervical cancer in India.

  19. Endocrine therapy of human breast cancer grown in nude mice

    DEFF Research Database (Denmark)

    Brünner, N; Osborne, C K; Spang-Thomsen, M

    1987-01-01

    mice bearing transplanted human breast tumors have been proposed as such a model. This review therefore discusses the use of the athymic nude mouse model of the study of human breast cancer biology, and focuses on four subjects: 1. biological characteristics of heterotransplanted breast tumors; 2...

  20. Multi-step EMG Classification Algorithm for Human-Computer Interaction

    Science.gov (United States)

    Ren, Peng; Barreto, Armando; Adjouadi, Malek

    A three-electrode human-computer interaction system, based on digital processing of the Electromyogram (EMG) signal, is presented. This system can effectively help disabled individuals paralyzed from the neck down to interact with computers or communicate with people through computers using point-and-click graphic interfaces. The three electrodes are placed on the right frontalis, the left temporalis and the right temporalis muscles in the head, respectively. The signal processing algorithm used translates the EMG signals during five kinds of facial movements (left jaw clenching, right jaw clenching, eyebrows up, eyebrows down, simultaneous left & right jaw clenching) into five corresponding types of cursor movements (left, right, up, down and left-click), to provide basic mouse control. The classification strategy is based on three principles: the EMG energy of one channel is typically larger than the others during one specific muscle contraction; the spectral characteristics of the EMG signals produced by the frontalis and temporalis muscles during different movements are different; the EMG signals from adjacent channels typically have correlated energy profiles. The algorithm is evaluated on 20 pre-recorded EMG signal sets, using Matlab simulations. The results show that this method provides improvements and is more robust than other previous approaches.

  1. Environmental factors in causing human cancers: emphasis on tumorigenesis.

    Science.gov (United States)

    Sankpal, Umesh T; Pius, Hima; Khan, Moeez; Shukoor, Mohammed I; Maliakal, Pius; Lee, Chris M; Abdelrahim, Maen; Connelly, Sarah F; Basha, Riyaz

    2012-10-01

    The environment and dietary factors play an essential role in the etiology of cancer. Environmental component is implicated in ~80 % of all cancers; however, the causes for certain cancers are still unknown. The potential players associated with various cancers include chemicals, heavy metals, diet, radiation, and smoking. Lifestyle habits such as smoking and alcohol consumption, exposure to certain chemicals (e.g., polycyclic aromatic hydrocarbons, organochlorines), metals and pesticides also pose risk in causing human cancers. Several studies indicated a strong association of lung cancer with the exposure to tobacco products and asbestos. The contribution of excessive sunlight, radiation, occupational exposure (e.g., painting, coal, and certain metals) is also well established in cancer. Smoking, excessive alcohol intake, consumption of an unhealthy diet, and lack of physical activity can act as risk factors for cancer and also impact the prognosis. Even though the environmental disposition is linked to cancer, the level and duration of carcinogen-exposure and associated cellular and biochemical aspects determine the actual risk. Modulations in metabolism and DNA adduct formation are considered central mechanisms in environmental carcinogenesis. This review describes the major environmental contributors in causing cancer with an emphasis on molecular aspects associated with environmental disposition in carcinogenesis.

  2. Human cancer protein-protein interaction network: a structural perspective.

    Directory of Open Access Journals (Sweden)

    Gozde Kar

    2009-12-01

    Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

  3. Neurons from the adult human dentate nucleus: neural networks in the neuron classification.

    Science.gov (United States)

    Grbatinić, Ivan; Marić, Dušica L; Milošević, Nebojša T

    2015-04-07

    Topological (central vs. border neuron type) and morphological classification of adult human dentate nucleus neurons according to their quantified histomorphological properties using neural networks on real and virtual neuron samples. In the real sample 53.1% and 14.1% of central and border neurons, respectively, are classified correctly with total of 32.8% of misclassified neurons. The most important result present 62.2% of misclassified neurons in border neurons group which is even greater than number of correctly classified neurons (37.8%) in that group, showing obvious failure of network to classify neurons correctly based on computational parameters used in our study. On the virtual sample 97.3% of misclassified neurons in border neurons group which is much greater than number of correctly classified neurons (2.7%) in that group, again confirms obvious failure of network to classify neurons correctly. Statistical analysis shows that there is no statistically significant difference in between central and border neurons for each measured parameter (p>0.05). Total of 96.74% neurons are morphologically classified correctly by neural networks and each one belongs to one of the four histomorphological types: (a) neurons with small soma and short dendrites, (b) neurons with small soma and long dendrites, (c) neuron with large soma and short dendrites, (d) neurons with large soma and long dendrites. Statistical analysis supports these results (pneurons can be classified in four neuron types according to their quantitative histomorphological properties. These neuron types consist of two neuron sets, small and large ones with respect to their perykarions with subtypes differing in dendrite length i.e. neurons with short vs. long dendrites. Besides confirmation of neuron classification on small and large ones, already shown in literature, we found two new subtypes i.e. neurons with small soma and long dendrites and with large soma and short dendrites. These neurons are

  4. Breast cancer surgery and diagnosis-related groups (DRGs): patient classification and hospital reimbursement in 11 European countries.

    Science.gov (United States)

    Scheller-Kreinsen, David; Quentin, Wilm; Geissler, Alexander; Busse, Reinhard

    2013-10-01

    Researchers from eleven countries (i.e. Austria, England, Estonia, Finland, France, Germany, Ireland, Netherlands, Poland, Spain, and Sweden) compared how their DRG systems deal with breast cancer surgery patients. DRG algorithms and indicators of resource consumption were assessed for those DRGs that individually contain at least 1% of all breast cancer surgery patients. Six standardised case vignettes were defined and quasi prices according to national DRG-based hospital payment systems were ascertained. European DRG systems classify breast cancer surgery patients according to different sets of classification variables into three to seven DRGs. Quasi prices for an index case treated with partial mastectomy range from €577 in Poland to €5780 in the Netherlands. Countries award their highest payments for very different kinds of patients. Breast cancer specialists and national DRG authorities should consider how other countries' DRG systems classify breast cancer patients in order to identify potential scope for improvement and to ensure fair and appropriate reimbursement. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. Endocrine Disruption and Human Prostate Cancer

    National Research Council Canada - National Science Library

    Risbridger, Gail

    2008-01-01

    .... In order to test the concept that Vinclozolin alters human prostate development and induces disease, we used our model system to study human prostate development and maturation over 8-12 weeks...

  6. Human Papillomavirus (HPV) and Oropharyngeal Cancer

    Science.gov (United States)

    ... Español (Spanish) Recommend on Facebook Tweet Share Compartir Human papillomavirus (HPV) can cause serious health problems, including ... 6348 Email CDC-INFO U.S. Department of Health & Human Services HHS/Open USA.gov TOP

  7. Comparison of breast cancer mucin (BCM) and CA 15-3 in human breast cancer

    NARCIS (Netherlands)

    Garcia, M.B.; Blankenstein, M.A.; Wall, E. van der; Nortier, J.W.R.; Schornagel, J.H.; Thijssen, J.H.H.

    1990-01-01

    The Breast Cancer Mucin (BCM) enzyme immunoassay utilizes two monoclonal antibodies (Mab), M85/34 and F36/22, for the identification of a mucin-like glycoprotein in serum of breast cancer patients. We have compared BCM with CA 15-3, another member of the human mammary epithelial antigen

  8. Human tissue models in cancer research: looking beyond the mouse

    Directory of Open Access Journals (Sweden)

    Samuel J. Jackson

    2017-08-01

    Full Text Available Mouse models, including patient-derived xenograft mice, are widely used to address questions in cancer research. However, there are documented flaws in these models that can result in the misrepresentation of human tumour biology and limit the suitability of the model for translational research. A coordinated effort to promote the more widespread development and use of ‘non-animal human tissue’ models could provide a clinically relevant platform for many cancer studies, maximising the opportunities presented by human tissue resources such as biobanks. A number of key factors limit the wide adoption of non-animal human tissue models in cancer research, including deficiencies in the infrastructure and the technical tools required to collect, transport, store and maintain human tissue for lab use. Another obstacle is the long-standing cultural reliance on animal models, which can make researchers resistant to change, often because of concerns about historical data compatibility and losing ground in a competitive environment while new approaches are embedded in lab practice. There are a wide range of initiatives that aim to address these issues by facilitating data sharing and promoting collaborations between organisations and researchers who work with human tissue. The importance of coordinating biobanks and introducing quality standards is gaining momentum. There is an exciting opportunity to transform cancer drug discovery by optimising the use of human tissue and reducing the reliance on potentially less predictive animal models.

  9. Human tissue models in cancer research: looking beyond the mouse.

    Science.gov (United States)

    Jackson, Samuel J; Thomas, Gareth J

    2017-08-01

    Mouse models, including patient-derived xenograft mice, are widely used to address questions in cancer research. However, there are documented flaws in these models that can result in the misrepresentation of human tumour biology and limit the suitability of the model for translational research. A coordinated effort to promote the more widespread development and use of 'non-animal human tissue' models could provide a clinically relevant platform for many cancer studies, maximising the opportunities presented by human tissue resources such as biobanks. A number of key factors limit the wide adoption of non-animal human tissue models in cancer research, including deficiencies in the infrastructure and the technical tools required to collect, transport, store and maintain human tissue for lab use. Another obstacle is the long-standing cultural reliance on animal models, which can make researchers resistant to change, often because of concerns about historical data compatibility and losing ground in a competitive environment while new approaches are embedded in lab practice. There are a wide range of initiatives that aim to address these issues by facilitating data sharing and promoting collaborations between organisations and researchers who work with human tissue. The importance of coordinating biobanks and introducing quality standards is gaining momentum. There is an exciting opportunity to transform cancer drug discovery by optimising the use of human tissue and reducing the reliance on potentially less predictive animal models. © 2017. Published by The Company of Biologists Ltd.

  10. Urinary acylcarnitines are altered in human kidney cancer.

    Science.gov (United States)

    Ganti, Sheila; Taylor, Sandra L; Kim, Kyoungmi; Hoppel, Charles L; Guo, Lining; Yang, Joy; Evans, Christopher; Weiss, Robert H

    2012-06-15

    Kidney cancer often diagnosed at late stages when treatment options are severely limited. Thus, greater understanding of tumor metabolism leading ultimately to novel approaches to diagnosis is needed. Our laboratory has been utilizing metabolomics to evaluate compounds appearing in kidney cancer patients' biofluids at concentrations different from control patients. Here, we collected urine samples from kidney cancer patients and analyzed them by chromatography coupled to mass spectrometry. Once normalized to control for urinary concentration, samples were analyzed by two independent laboratories. After technical validation, we now show differential urinary concentrations of several acylcarnitines as a function of both cancer status and kidney cancer grade, with most acylcarnitines being increased in the urine of cancer patients and in those patients with high cancer grades. This finding was validated in a mouse xenograft model of human kidney cancer. Biological validation shows carbon chain length-dependent effects of the acylcarnitines on cytotoxicity in vitro, and higher chain length acylcarnitines demonstrated inhibitory effects on NF-κB activation, suggesting an immune modulatory effect of these compounds. Thus, acylcarnitines in the kidney cancer urine may reflect alterations in metabolism, cell component synthesis and/or immune surveillance, and may help explain the profound chemotherapy resistance seen with this cancer. This study shows for the first time the value of a novel class of metabolites which may lead to new therapeutic approaches for cancer and may prove useful in cancer biomarker studies. Furthermore, these findings open up a new area of investigation into the metabolic basis of kidney cancer. Copyright © 2011 UICC.

  11. Human papillomavirus in cervical cancer and oropharyngeal cancer: One cause, two diseases.

    Science.gov (United States)

    Berman, Tara A; Schiller, John T

    2017-06-15

    Human papillomavirus (HPV) causes greater than 5% of cancers worldwide, including all cervical cancers and an alarmingly increasing proportion of oropharyngeal cancers (OPCs). Despite markedly reduced cervical cancer incidence in industrialized nations with organized screening programs, cervical cancer remains the second most common cause of death from cancer in women worldwide, as developing countries lack resources for universal, high-quality screening. In the United States, HPV-related OPC is only 1 of 5 cancers with a rising incidence since 1975 and now has taken over the cervix as the most common site of HPV-related cancer. Similar trends follow throughout North America and Europe. The need for early detection and prevention is paramount. Despite the common etiologic role of HPV in the development of cervical cancer and HPV-associated OPC, great disparity exists between incidence, screening modalities (or lack thereof), treatment, and prevention in these 2 very distinct cohorts. These differences in cervical cancer and HPV-associated OPC and their impact are discussed here. Cancer 2017;123:2219-2229. © 2017 American Cancer Society. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

  12. Decorin in Human Colon Cancer: Localization In Vivo and Effect on Cancer Cell Behavior In Vitro.

    Science.gov (United States)

    Nyman, Marie C; Sainio, Annele O; Pennanen, Mirka M; Lund, Riikka J; Vuorikoski, Sanna; Sundström, Jari T T; Järveläinen, Hannu T

    2015-09-01

    Decorin is generally recognized as a tumor suppressing molecule. Nevertheless, although decorin has been shown to be differentially expressed in malignant tissues, it has often remained unclear whether, in addition to non-malignant stromal cells, cancer cells also express it. Here, we first used two publicly available databases to analyze the current information about decorin expression and immunoreactivity in normal and malignant human colorectal tissue samples. The analyses demonstrated that decorin expression and immunoreactivity may vary in cancer cells of human colorectal tissues. Therefore, we next examined decorin expression in normal, premalignant and malignant human colorectal tissues in more detail using both in situ hybridization and immunohistochemistry for decorin. Our results invariably demonstrate that malignant cells within human colorectal cancer tissues are devoid of both decorin mRNA and immunoreactivity. Identical results were obtained for cells of neuroendocrine tumors of human colon. Using RT-qPCR, we showed that human colon cancer cell lines are also decorin negative, in accordance with the above in vivo results. Finally, we demonstrate that decorin transduction of human colon cancer cell lines causes a significant reduction in their colony forming capability. Thus, strategies to develop decorin-based adjuvant therapies for human colorectal malignancies are highly rational. © The Author(s) 2015.

  13. Statistical Considerations for Immunohistochemistry Panel Development after Gene Expression Profiling of Human Cancers

    Science.gov (United States)

    Betensky, Rebecca A.; Nutt, Catherine L.; Batchelor, Tracy T.; Louis, David N.

    2005-01-01

    In recent years there have been a number of microarray expression studies in which different types of tumors were classified by identifying a panel of differentially expressed genes. Immunohistochemistry is a practical and robust method for extending gene expression data to common pathological specimens with the advantage of being applicable to paraffin-embedded tissues. However, the number of assays required for successful immunohistochemical classification remains unclear. We propose a simulation-based method for assessing sample size for an immunohistochemistry investigation after a promising gene expression study of human tumors. The goals of such an immunohistochemistry study would be to develop and validate a marker panel that yields improved prognostic classification of cancer patients. We demonstrate how the preliminary gene expression data, coupled with certain realistic assumptions, can be used to estimate the number of immunohistochemical assays required for development. These assumptions are more tenable than alternative assumptions that would be required for crude analytic sample size calculations and that may yield underpowered and inefficient studies. We applied our methods to the design of an immunohistochemistry study for glioma classification and estimated the number of assays required to ensure satisfactory technical and prognostic validation. Simulation approaches for computing power and sample size that are based on existing gene expression data provide a powerful tool for efficient design of follow-up genomic studies. PMID:15858152

  14. Deep learning based classification for head and neck cancer detection with hyperspectral imaging in an animal model

    Science.gov (United States)

    Ma, Ling; Lu, Guolan; Wang, Dongsheng; Wang, Xu; Chen, Zhuo Georgia; Muller, Susan; Chen, Amy; Fei, Baowei

    2017-03-01

    Hyperspectral imaging (HSI) is an emerging imaging modality that can provide a noninvasive tool for cancer detection and image-guided surgery. HSI acquires high-resolution images at hundreds of spectral bands, providing big data to differentiating different types of tissue. We proposed a deep learning based method for the detection of head and neck cancer with hyperspectral images. Since the deep learning algorithm can learn the feature hierarchically, the learned features are more discriminative and concise than the handcrafted features. In this study, we adopt convolutional neural networks (CNN) to learn the deep feature of pixels for classifying each pixel into tumor or normal tissue. We evaluated our proposed classification method on the dataset containing hyperspectral images from 12 tumor-bearing mice. Experimental results show that our method achieved an average accuracy of 91.36%. The preliminary study demonstrated that our deep learning method can be applied to hyperspectral images for detecting head and neck tumors in animal models.

  15. Frequency of human papillomavirus infection in patients with gastrointestinal cancer.

    Science.gov (United States)

    Roesch-Dietlen, F; Cano-Contreras, A D; Sánchez-Maza, Y J; Espinosa-González, J M; Vázquez-Prieto, M Á; Valdés-de la O, E J; Díaz-Roesch, F; Carrasco-Arroniz, M Á; Cruz-Palacios, A; Grube-Pagola, P; Sumoza-Toledo, A; Vivanco-Cid, H; Mellado-Sánchez, G; Meixueiro-Daza, A; Silva-Cañetas, C S; Carrillo-Toledo, M G; Lagunes-Torres, R; Amieva-Balmori, M; Gómez-Castaño, P C; Reyes-Huerta, J U; Remes-Troche, J M

    2018-02-15

    Cancer is the result of the interaction of genetic and environmental factors. It has recently been related to viral infections, one of which is human papillomavirus. The aim of the present study was to describe the frequency of human papillomavirus infection in patients with digestive system cancers. A prospective, multicenter, observational study was conducted on patients with gastrointestinal cancer at 2public healthcare institutes in Veracruz. Two tumor samples were taken, one for histologic study and the other for DNA determination of human papillomavirus and its genotypes. Anthropometric variables, risk factors, sexual habits, tumor location, and histologic type of the cancer were analyzed. Absolute and relative frequencies were determined using the SPSS version 24.0 program. Fifty-three patients were studied. They had gastrointestinal cancer located in: the colon (62.26%), stomach (18.87%), esophagus (7.55%), rectum (7.55%), and small bowel (3.77%). Human papillomavirus was identified in 11.32% of the patients, 66.7% of which corresponded to squamous cell carcinoma and 33.3% to adenocarcinoma. Only genotype 18 was identified. Mean patient age was 61.8±15.2 years, 56.60% of the patients were men, and 43.40% were women. A total of 15.8% of the patients had a family history of cancer and 31.6% had a personal history of the disease, 38.6% were tobacco smokers, and 61.4% consumed alcohol. Regarding sex, 5.3% of the patients said they were homosexual, 3.5% were bisexual, 29.8% engaged in oral sex, and 24.6% in anal sex. Our study showed that human papillomavirus infection was a risk factor for the development of gastrointestinal cancer, especially of squamous cell origin. Copyright © 2018 Asociación Mexicana de Gastroenterología. Publicado por Masson Doyma México S.A. All rights reserved.

  16. Human papillomavirus 33 worldwide genetic variation and associated risk of cervical cancer

    Science.gov (United States)

    Chen, Alyce A.; Heideman, Daniëlle A.M.; Boon, Debby; Chen, Zigui; Burk, Robert D.; De Vuyst, Hugo; Gheit, Tarik; Snijders, Peter J.F.; Tommasino, Massimo; Franceschi, Silvia; Clifford, Gary M.

    2014-01-01

    Human papillomavirus (HPV) 33, a member of the HPV16-related alpha-9 species group, is found in approximately 5% of cervical cancers worldwide. The current study aimed to characterize the genetic diversity of HPV33 and to explore the association of HPV33 variants with the risk for cervical cancer. Taking advantage of the International Agency for Research on Cancer biobank, we sequenced the entire E6 and E7 open reading frames of 213 HPV33-positive cervical samples from 30 countries. We identified 28 HPV33 variants that formed 5 phylogenetic groups: the previously identified A1, A2, and B (sub) lineages and the novel A3 and C (sub)lineages. The A1 sublineage was strongly over-represented in cervical cases compared to controls in both Africa and Europe. In conclusion, we provide a classification system for HPV33 variants based on the sequence of E6 and E7 and suggest that the association of HPV33 with cervical cancer may differ by variant (sub)lineage. PMID:24314666

  17. Thermographic image analysis for classification of ACL rupture disease, bone cancer, and feline hyperthyroid, with Gabor filters

    Science.gov (United States)

    Alvandipour, Mehrdad; Umbaugh, Scott E.; Mishra, Deependra K.; Dahal, Rohini; Lama, Norsang; Marino, Dominic J.; Sackman, Joseph

    2017-05-01

    Thermography and pattern classification techniques are used to classify three different pathologies in veterinary images. Thermographic images of both normal and diseased animals were provided by the Long Island Veterinary Specialists (LIVS). The three pathologies are ACL rupture disease, bone cancer, and feline hyperthyroid. The diagnosis of these diseases usually involves radiology and laboratory tests while the method that we propose uses thermographic images and image analysis techniques and is intended for use as a prescreening tool. Images in each category of pathologies are first filtered by Gabor filters and then various features are extracted and used for classification into normal and abnormal classes. Gabor filters are linear filters that can be characterized by the two parameters wavelength λ and orientation θ. With two different wavelength and five different orientations, a total of ten different filters were studied. Different combinations of camera views, filters, feature vectors, normalization methods, and classification methods, produce different tests that were examined and the sensitivity, specificity and success rate for each test were produced. Using the Gabor features alone, sensitivity, specificity, and overall success rates of 85% for each of the pathologies was achieved.

  18. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

    Directory of Open Access Journals (Sweden)

    Hala Alshamlan

    2015-01-01

    Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  19. mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

    Science.gov (United States)

    Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

    2015-01-01

    An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

  20. Foxp3 expression in human cancer cells

    Directory of Open Access Journals (Sweden)

    Gourgoulianis Konstantinos I

    2008-04-01

    Full Text Available Abstract Objective Transcription factor forkhead box protein 3 (Foxp3 specifically characterizes the thymically derived naturally occurring regulatory T cells (Tregs. Limited evidence indicates that it is also expressed, albeit to a lesser extent, in tissues other than thymus and spleen, while, very recently, it was shown that Foxp3 is expressed by pancreatic carcinoma. This study was scheduled to investigate whether expression of Foxp3 transcripts and mature protein occurs constitutively in various tumor types. Materials and methods Twenty five tumor cell lines of different tissue origins (lung cancer, colon cancer, breast cancer, melanoma, erythroid leukemia, acute T-cell leukemia were studied. Detection of Foxp3 mRNA was performed using both conventional RT-PCR and quantitative real-time PCR while protein expression was assessed by immunocytochemistry and flow cytometry, using different antibody clones. Results Foxp3 mRNA as well as Foxp3 protein was detected in all tumor cell lines, albeit in variable levels, not related to the tissue of origin. This expression correlated with the expression levels of IL-10 and TGFb1. Conclusion We offer evidence that Foxp3 expression, characterizes tumor cells of various tissue origins. The biological significance of these findings warrants further investigation in the context of tumor immune escape, and especially under the light of current anti-cancer efforts interfering with Foxp3 expression.

  1. Fraction against Human Cancer Cell Lines

    African Journals Online (AJOL)

    fraction of A. sieberi against seven cancer cell lines (Colo20, HCT116, DLD, MCF7, Jurkat, HepG2 and ... The morphology of the HepG2 cell nucleus was investigated by Hoechst 33342, ..... Gong F, Liang Y, Xie P, Chau F. Information theory.

  2. (Asteraceae) Fraction against Human Cancer Cell Lines

    African Journals Online (AJOL)

    Purpose: To investigate the anti-proliferative and apoptotic activity of crude and dichloromethane fraction of A. sieberi against seven cancer cell lines (Colo20, HCT116, DLD, MCF7, Jurkat, HepG2 and L929). Methods: A. sieberi was extracted with methanol and further purification was carried out using liquidliquid extraction ...

  3. Immune and Inflammatory Cell Composition of Human Lung Cancer Stroma.

    Directory of Open Access Journals (Sweden)

    G-Andre Banat

    Full Text Available Recent studies indicate that the abnormal microenvironment of tumors may play a critical role in carcinogenesis, including lung cancer. We comprehensively assessed the number of stromal cells, especially immune/inflammatory cells, in lung cancer and evaluated their infiltration in cancers of different stages, types and metastatic characteristics potential. Immunohistochemical analysis of lung cancer tissue arrays containing normal and lung cancer sections was performed. This analysis was combined with cyto-/histomorphological assessment and quantification of cells to classify/subclassify tumors accurately and to perform a high throughput analysis of stromal cell composition in different types of lung cancer. In human lung cancer sections we observed a significant elevation/infiltration of total-T lymphocytes (CD3+, cytotoxic-T cells (CD8+, T-helper cells (CD4+, B cells (CD20+, macrophages (CD68+, mast cells (CD117+, mononuclear cells (CD11c+, plasma cells, activated-T cells (MUM1+, B cells, myeloid cells (PD1+ and neutrophilic granulocytes (myeloperoxidase+ compared with healthy donor specimens. We observed all of these immune cell markers in different types of lung cancers including squamous cell carcinoma, adenocarcinoma, adenosquamous cell carcinoma, small cell carcinoma, papillary adenocarcinoma, metastatic adenocarcinoma, and bronchioloalveolar carcinoma. The numbers of all tumor-associated immune cells (except MUM1+ cells in stage III cancer specimens was significantly greater than those in stage I samples. We observed substantial stage-dependent immune cell infiltration in human lung tumors suggesting that the tumor microenvironment plays a critical role during lung carcinogenesis. Strategies for therapeutic interference with lung cancer microenvironment should consider the complexity of its immune cell composition.

  4. Autophagy Therapeutic Potential of Garlic in Human Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Yung-Lin Chu

    2013-07-01

    Full Text Available Cancer is one of the deadliest diseases against humans. To tackle this menace, humans have developed several high-technology therapies, such as chemotherapy, tomotherapy, targeted therapy, and antibody therapy. However, all these therapies have their own adverse side effects. Therefore, recent years have seen increased attention being given to the natural food for complementary therapy, which have less side effects. Garlic 大 蒜 Dà Suàn; Allium sativum, is one of most powerful food used in many of the civilizations for both culinary and medicinal purpose. In general, these foods induce cancer cell death by apoptosis, autophagy, or necrosis. Studies have discussed how natural food factors regulate cell survival or death by autophagy in cancer cells. From many literature reviews, garlic could not only induce apoptosis but also autophagy in cancer cells. Autophagy, which is called type-II programmed cell death, provides new strategy in cancer therapy. In conclusion, we wish that garlic could be the pioneer food of complementary therapy in clinical cancer treatment and increase the life quality of cancer patients.

  5. Immunological responses against human papilloma virus and human papilloma virus induced laryngeal cancer.

    Science.gov (United States)

    Chitose, Shun-ichi; Sakazaki, T; Ono, T; Kurita, T; Mihashi, H; Nakashima, T

    2010-06-01

    This study aimed to clarify the local immune status in the larynx in the presence of infection or carcinogenesis associated with human papilloma virus. Cytological samples (for human papilloma virus detection) and laryngeal secretions (for immunoglobulin assessment) were obtained from 31 patients with laryngeal disease, during microscopic laryngeal surgery. On histological examination, 12 patients had squamous cell carcinoma, four had laryngeal papilloma and 15 had other benign laryngeal disease. Cytological samples were tested for human papilloma virus DNA using the Hybrid Capture 2 assay. High risk human papilloma virus DNA was detected in 25 per cent of patients (three of 12) with laryngeal cancer. Low risk human papilloma virus DNA was detected only in three laryngeal papilloma patients. The mean laryngeal secretion concentrations of immunoglobulins M, G and A and secretory immunoglobulin A in human papilloma virus DNA positive patients were more than twice those in human papilloma virus DNA negative patients. A statistically significant difference was observed between the secretory immunoglobulin A concentrations in the two groups. Patients with laryngeal cancer had higher laryngeal secretion concentrations of each immunoglobulin type, compared with patients with benign laryngeal disease. The study assessed the mean laryngeal secretion concentrations of each immunoglobulin type in the 12 laryngeal cancer patients, comparing human papilloma virus DNA positive patients (n = 3) and human papilloma virus DNA negative patients (n = 9); the mean concentrations of immunoglobulins M, G and A and secretory immunoglobulin A tended to be greater in human papilloma virus DNA positive cancer patients, compared with human papilloma virus DNA negative cancer patients. These results suggest that the local laryngeal immune response is activated by infection or carcinogenesis due to human papilloma virus. The findings strongly suggest that secretory IgA has inhibitory activity

  6. Computerized three-class classification of MRI-based prognostic markers for breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Bhooshan, Neha; Giger, Maryellen; Edwards, Darrin; Yuan Yading; Jansen, Sanaz; Li Hui; Lan Li; Newstead, Gillian [Department of Radiology, University of Chicago, Chicago, IL 60637 (United States); Sattar, Husain, E-mail: bhooshan@uchicago.edu [Department of Pathology, University of Chicago, Chicago, IL 60637 (United States)

    2011-09-21

    The purpose of this study is to investigate whether computerized analysis using three-class Bayesian artificial neural network (BANN) feature selection and classification can characterize tumor grades (grade 1, grade 2 and grade 3) of breast lesions for prognostic classification on DCE-MRI. A database of 26 IDC grade 1 lesions, 86 IDC grade 2 lesions and 58 IDC grade 3 lesions was collected. The computer automatically segmented the lesions, and kinetic and morphological lesion features were automatically extracted. The discrimination tasks-grade 1 versus grade 3, grade 2 versus grade 3, and grade 1 versus grade 2 lesions-were investigated. Step-wise feature selection was conducted by three-class BANNs. Classification was performed with three-class BANNs using leave-one-lesion-out cross-validation to yield computer-estimated probabilities of being grade 3 lesion, grade 2 lesion and grade 1 lesion. Two-class ROC analysis was used to evaluate the performances. We achieved AUC values of 0.80 {+-} 0.05, 0.78 {+-} 0.05 and 0.62 {+-} 0.05 for grade 1 versus grade 3, grade 1 versus grade 2, and grade 2 versus grade 3, respectively. This study shows the potential for (1) applying three-class BANN feature selection and classification to CADx and (2) expanding the role of DCE-MRI CADx from diagnostic to prognostic classification in distinguishing tumor grades.

  7. CDX2 prognostic value in stage II/III resected colon cancer is related to CMS classification.

    Science.gov (United States)

    Pilati, C; Taieb, J; Balogoun, R; Marisa, L; de Reyniès, A; Laurent-Puig, P

    2017-05-01

    Caudal-type homeobox transcription factor 2 (CDX2) is involved in colon cancer (CC) oncogenesis and has been proposed as a prognostic biomarker in patients with stage II or III CC. We analyzed CDX2 expression in a series of 469 CC typed for the new international consensus molecular subtype (CMS) classification, and we confirmed results in a series of 90 CC. Here, we show that lack of CDX2 expression is only present in the mesenchymal subgroup (CMS4) and in MSI-immune tumors (CMS1) and not in CMS2 and CMS3 colon cancer. Although CDX2 expression was a globally independent prognostic factor, loss of CDX2 expression is not associated with a worse prognosis in the CMS1 group, but is highly prognostic in CMS4 patients for both relapse free and overall survival. Similarly, lack of CDX2 expression was a bad prognostic factor in MSS patients, but not in MSI. Our work suggests that combination of the consensual CMS classification and lack of CDX2 expression could be a useful marker to identify CMS4/CDX2-negative patients with a very poor prognosis. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  8. [Magnetic resonance semiotics of prostate cancer according to the PI-RADS classification. The clinical diagnostic algorithm of a study].

    Science.gov (United States)

    Korobkin, A S; Shariya, M A; Chaban, A S; Voskanvan, G A; Vinarov, A Z

    2015-01-01

    to elaborate the magnetic resonance imaging (MRI) signs of prostate cancer (PC) in accordance with the PI-RADS classification during multiparametric MRI (mpMRI). A total of 89 men aged 20 to 82 years were examined. A control group consisted of 8 (9%) healthy volunteers younger than 30 years of age with no urological history to obtain control images and MRI plots and 20 (22.5%) men aged 26-76 years, whose morphological changes were inflammatory and hyperplastic. The second age-matched group included 61 (68.5%) patients diagnosed with prostate cancer at morphological examination. A set of studies included digital rectal examination, serum prostate-specific antigen, and transrectal ultrasound-guided prostate biopsy. All the patients underwent prostate mpMRI applying a 3.0 T Achieva MRI scanner (Philips, the Netherlands). The patients have been found to have mpMRI signs that were typical of PC; its MRI semiotics according to the PI-RADS classification is presented. Each mpMRI procedure has been determined to be of importance and informative value in detecting PC. The comprehensive mpMRI approach to diagnosing PC improves the quality and diagnostic value of prostate MRI.

  9. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Directory of Open Access Journals (Sweden)

    Enrico Glaab

    Full Text Available Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  10. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Science.gov (United States)

    Glaab, Enrico; Bacardit, Jaume; Garibaldi, Jonathan M; Krasnogor, Natalio

    2012-01-01

    Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  11. Genetic and environmental factors in experimental and human cancer

    Energy Technology Data Exchange (ETDEWEB)

    Takayama, S.; Takebe, H.; Gelboin, H.V.; MaChahon, B.; Matsushima, T.; Sugimura, T.

    1980-01-01

    Recently technological advances in assaying mutagenic principles have revealed that there are many mutagens in the environment, some of which might be carcinogenic to human beings. Other advances in genetics have shown that genetic factors might play an important role in the induction of cancer in human beings, e.g., the high incidence of skin cancers in patients with xeroderma pigmentosum. These proceedings deal with the relationships between genetic and environmental factors in carcinogenesis. The contributors cover mixed-function oxidases, pharmacogenetics, twin studies, DNA repair, immunology, and epidemiology.

  12. AR Signaling in Human Malignancies: Prostate Cancer and Beyond.

    Science.gov (United States)

    Antonarakis, Emmanuel S

    2018-01-18

    The notion that androgens and androgen receptor (AR) signaling are the hallmarks of prostate cancer oncogenesis and disease progression is generally well accepted. What is more poorly understood is the role of AR signaling in other human malignancies. This special issue of Cancers initially reviews the role of AR in advanced prostate cancer, and then explores the potential importance of AR signaling in other epithelial malignancies. The first few articles focus on the use of novel AR-targeting therapies in castration-resistant prostate cancer and the mechanisms of resistance to novel antiandrogens, and they also outline the interaction between AR and other cellular pathways, including PI3 kinase signaling, transcriptional regulation, angiogenesis, stromal factors, Wnt signaling, and epigenetic regulation in prostate cancer. The next several articles review the possible role of androgens and AR signaling in breast cancer, bladder cancer, salivary gland cancer, and hepatocellular carcinoma, as well as the potential treatment implications of using antiandrogen therapies in these non-prostatic malignancies.

  13. Mechanism-based classification and physical therapy management of persons with cancer pain: A prospective case series

    Directory of Open Access Journals (Sweden)

    Senthil P Kumar

    2013-01-01

    Full Text Available Context: Mechanism-based classification (MBC was established with current evidence and physical therapy (PT management methods for both cancer and for noncancer pain. Aims: This study aims to describe the efficacy of MBC-based PT in persons with primary complaints of cancer pain. Settings and Design: A prospective case series of patients who attended the physiotherapy department of a multispecialty university-affiliated teaching hospital. Material and Methods: A total of 24 adults (18 female, 6 male aged 47.5 ± 10.6 years, with primary diagnosis of heterogeneous group of cancer, chief complaints of chronic disabling pain were included in the study on their consent for participation The patients were evaluated and classified on the basis of five predominant mechanisms for pain. Physical therapy interventions were recommended based on mechanisms identified and home program was prescribed with a patient log to ensure compliance. Treatments were given in five consecutive weekly sessions for five weeks each of 30 min duration. Statistical Analysis Used: Pre-post comparisons for pain severity (PS and pain interference (PI subscales of Brief pain inventory-Cancer pain (BPI-CP and, European organization for research and treatment in cancer-quality of life questionnaire (EORTC-QLQ-C30 were done using Wilcoxon signed-rank test at 95% confidence interval using SPSS for Windows version 16.0 (SPSS Inc, Chicago, IL. Results: There were statistically significant ( P < 0.05 reduction in pain severity, pain interference and total BPI-CP scores, and the EORTC-QLQ-C30. Conclusion: MBC-PT was effective for improving BPI-CP and EORTC-QLQ-C30 scores in people with cancer pain.

  14. Breast Cancer Survival Defined by the ER/PR/HER2 Subtypes and a Surrogate Classification according to Tumor Grade and Immunohistochemical Bio markers

    International Nuclear Information System (INIS)

    Parise, C. A.; Caggiano, V.

    2014-01-01

    ER, PR, and HER2 are routinely available in breast cancer specimens. The purpose of this study is to contrast breast cancer-specific survival for the eight ER/PR/HER2 subtypes with survival of an immunohistochemical surrogate for the molecular subtype based on the ER/PR/HER2 subtypes and tumor grade. Methods. We identified 123,780 cases of stages 1-3 primary female invasive breast cancer from California Cancer Registry. The surrogate classification was derived using ER/PR/HER2 and tumor grade. Kaplan-Meier survival analysis and Cox proportional hazards modeling were used to assess differences in survival and risk of mortality for the ER/PR/HER2 subtypes and surrogate classification within each stage. Results. The luminal B/HER2− surrogate classification had a higher risk of mortality than the luminal B/HER2+ for all stages of disease. There was no difference in risk of mortality between the ER+/PR+/HER2− and ER+/PR+/HER2+ in stage 3. With one exception in stage 3, the ER-negative subtypes all had an increased risk of mortality when compared with the ER-positive subtypes. Conclusions. Assessment of survival using ER/PR/HER2 illustrates the heterogeneity of HER2+ subtypes. The surrogate classification provides clear separation in survival and adjusted mortality but underestimates the wide variability within the subtypes that make up the classification.

  15. Breast Cancer Survival Defined by the ER/PR/HER2 Subtypes and a Surrogate Classification according to Tumor Grade and Immunohistochemical Biomarkers

    Directory of Open Access Journals (Sweden)

    Carol A. Parise

    2014-01-01

    Full Text Available Introduction. ER, PR, and HER2 are routinely available in breast cancer specimens. The purpose of this study is to contrast breast cancer-specific survival for the eight ER/PR/HER2 subtypes with survival of an immunohistochemical surrogate for the molecular subtype based on the ER/PR/HER2 subtypes and tumor grade. Methods. We identified 123,780 cases of stages 1–3 primary female invasive breast cancer from California Cancer Registry. The surrogate classification was derived using ER/PR/HER2 and tumor grade. Kaplan-Meier survival analysis and Cox proportional hazards modeling were used to assess differences in survival and risk of mortality for the ER/PR/HER2 subtypes and surrogate classification within each stage. Results. The luminal B/HER2− surrogate classification had a higher risk of mortality than the luminal B/HER2+ for all stages of disease. There was no difference in risk of mortality between the ER+/PR+/HER2− and ER+/PR+/HER2+ in stage 3. With one exception in stage 3, the ER-negative subtypes all had an increased risk of mortality when compared with the ER-positive subtypes. Conclusions. Assessment of survival using ER/PR/HER2 illustrates the heterogeneity of HER2+ subtypes. The surrogate classification provides clear separation in survival and adjusted mortality but underestimates the wide variability within the subtypes that make up the classification.

  16. Classification of Breast Cancer Subtypes by combining Gene Expression and DNA Methylation Data

    DEFF Research Database (Denmark)

    List, Markus; Hauschild, Anne-Christin; Tan, Qihua

    2014-01-01

    expression data for hundreds of patients, the challenge is to extract a minimal optimal set of genes with good prognostic properties from a large bulk of genes making a moderate contribution to classification. Several studies have successfully applied machine learning algorithms to solve this so-called gene...... on the transcriptomic, but also on an epigenetic level. We compared so-called random forest derived classification models based on gene expression and methylation data alone, to a model based on the combined features and to a model based on the gold standard PAM50. We obtained bootstrap errors of 10...

  17. Anticancer Properties of Capsaicin Against Human Cancer.

    Science.gov (United States)

    Clark, Ruth; Lee, Seong-Ho

    2016-03-01

    There is persuasive epidemiological and experimental evidence that dietary phytochemicals have anticancer activity. Capsaicin is a bioactive phytochemical abundant in red and chili peppers. While the preponderance of the data strongly indicates significant anticancer benefits of capsaicin, more information to highlight molecular mechanisms of its action is required to improve our knowledge to be able to propose a potential therapeutic strategy for use of capsaicin against cancer. Capsaicin has been shown to alter the expression of several genes involved in cancer cell survival, growth arrest, angiogenesis and metastasis. Recently, many research groups, including ours, found that capsaicin targets multiple signaling pathways, oncogenes and tumor-suppressor genes in various types of cancer models. In this review article, we highlight multiple molecular targets responsible for the anticancer mechanism of capsaicin. In addition, we deal with the benefits of combinational use of capsaicin with other dietary or chemotherapeutic compounds, focusing on synergistic anticancer activities. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  18. Assessing Unmet Information Needs of Breast Cancer Survivors: Exploratory Study of Online Health Forums Using Text Classification and Retrieval.

    Science.gov (United States)

    McRoy, Susan; Rastegar-Mojarad, Majid; Wang, Yanshan; Ruddy, Kathryn J; Haddad, Tufia C; Liu, Hongfang

    2018-05-15

    Patient education materials given to breast cancer survivors may not be a good fit for their information needs. Needs may change over time, be forgotten, or be misreported, for a variety of reasons. An automated content analysis of survivors' postings to online health forums can identify expressed information needs over a span of time and be repeated regularly at low cost. Identifying these unmet needs can guide improvements to existing education materials and the creation of new resources. The primary goals of this project are to assess the unmet information needs of breast cancer survivors from their own perspectives and to identify gaps between information needs and current education materials. This approach employs computational methods for content modeling and supervised text classification to data from online health forums to identify explicit and implicit requests for health-related information. Potential gaps between needs and education materials are identified using techniques from information retrieval. We provide a new taxonomy for the classification of sentences in online health forum data. 260 postings from two online health forums were selected, yielding 4179 sentences for coding. After annotation of data and training alternative one-versus-others classifiers, a random forest-based approach achieved F1 scores from 66% (Other, dataset2) to 90% (Medical, dataset1) on the primary information types. 136 expressions of need were used to generate queries to indexed education materials. Upon examination of the best two pages retrieved for each query, 12% (17/136) of queries were found to have relevant content by all coders, and 33% (45/136) were judged to have relevant content by at least one. Text from online health forums can be analyzed effectively using automated methods. Our analysis confirms that breast cancer survivors have many information needs that are not covered by the written documents they typically receive, as our results suggest that at most

  19. Clinical significance of combined detection of CYFRA21-1, NSE and CEA in classification and staging of patients with lung cancer

    International Nuclear Information System (INIS)

    Hu He; Li Yanhua; Liang Weida; Zhang Qin

    2011-01-01

    To explore clinical value of combined detection of CYFRA21-1, NSE and CEA in classification and staging of patients with lung cancer, the CYFRA21-1, NSE and CEA levels in pleural effusion in 330 patients with lung cancer and in 43 patients with benign were detected by the electrochemiluminescence. The results showed that CYFRA21-1, NSE and CEA levels in pleural effusion in patients with lung cancer group were significantly higher than that of in benign group (P<0.01). The positive rate of tumor markers in different pathological type lung cancer were different,which CYFRA21-1 positive rate in squamous cell cancer group was highest with 65.5%; CEA positive rate in glands cancer group was supreme with 65.0%; the NSE positive rate in differentiation cancer group was highest with 79.5%. The positive rate in three markers combined detection was higher than that in one item detection. The tumor marker levels in lung cancer were positively related with clinical staging. The higher of tumor marker levels and the more late of clinical staging, and the clinical III∼IV period was obviously higher than that I∼II period (P<0.05). The combined detection of CYFRA21-1, NSE and CEA may enhance the positive rate in lung cancer detection, and may have significant clinical value in the classification and staging of patients with lung cancer. (authors)

  20. Deoxyribonucleic-binding homeobox proteins are augmented in human cancer

    DEFF Research Database (Denmark)

    Wewer, U M; Mercurio, A M; Chung, S Y

    1990-01-01

    Homeobox genes encode sequence-specific DNA-binding proteins that are involved in the regulation of gene expression during embryonic development. In this study, we examined the expression of homeobox proteins in human cancer. Antiserum was obtained against a synthetic peptide derived from...... was then isolated and used to elicit a rabbit antiserum. In immunostaining, both antisera reacted with the nuclei of cultured tumor cells. In tissue sections of human carcinoma, nuclear immunoreactivity was observed in the tumor cells in 40 of 42 cases examined. Adjacent normal epithelial tissue obtained from......, the presence of the homeobox transcript in human carcinoma was documented by in situ hybridization and RNase protection mapping. These results demonstrate that human cancer is associated with the expression of homeobox proteins. Such homeobox proteins, as well as other regulatory proteins, could be involved...

  1. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks | Center for Cancer Research

    Science.gov (United States)

    The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs). We trained the ANNs using the small, round blue-cell tumors (SRBCTs) as a model. These cancers belong to four distinct diagnostic categories and often present diagnostic dilemmas in

  2. Concepts in causality: chemically induced human urinary bladder cancer

    International Nuclear Information System (INIS)

    Lower, G.M. Jr.

    1982-01-01

    A significant portion of the incidence of human urinary bladder cancer can be attributed to occupational and cultural (tobacco smoking) situations associated with exposures to various arylamines, many of which represent established human carcinogens. A brief historical overview of research in bladder cancer causality indicates that the identification of causal agents and causal mechanism has been approached and rests upon information gathered at the organismal (geographical/historical), cellular, and molecular levels of biologic organization. This viewpoint speaks of a natural evolution within the biomedical sciences; a natural evolution from descriptive approaches to mechanistic approaches; and a natural evolution from more or less independent discipline-oriented approaches to hierarchically organized multidisciplinary approaches. Available information relevant to bladder cancer causality can be readily integrated into general conceptual frameworks to yield a hierarchial view of the natural history of urinary bladder cancer, a view consistent with contemporary natural systems and information theory and perhaps relevant also to other chemically induced epithelial cancers. Such frameworks are useful in appreciating the spatial and temporal boundaries and interrelationships in causality and the conceptual interrelationships within the biomedical sciences. Recent approaches in molecular epidemiology and the assessment of relative individual susceptibility to bladder cancer indicate that such frameworks are useful in forming hypotheses

  3. Characterization of human breast cancer by scanning acoustic microscopy

    Science.gov (United States)

    Chen, Di; Malyarenko, Eugene; Seviaryn, Fedar; Yuan, Ye; Sherman, Mark; Bandyopadhyay, Sudeshna; Gierach, Gretchen; Greenway, Christopher W.; Maeva, Elena; Strumban, Emil; Duric, Neb; Maev, Roman

    2013-03-01

    Objectives: The purpose of this study was to characterize human breast cancer tissues by the measurement of microacoustic properties. Methods: We investigated eight breast cancer patients using acoustic microscopy. For each patient, seven blocks of tumor tissue were collected from seven different positions around a tumor mass. Frozen sections (10 micrometer, μm) of human breast cancer tissues without staining and fixation were examined in a scanning acoustic microscope with focused transducers at 80 and 200 MHz. Hematoxylin and Eosin (H and E) stained sections from the same frozen breast cancer tissues were imaged by optical microscopy for comparison. Results: The results of acoustic imaging showed that acoustic attenuation and sound speed in cancer cell-rich tissue regions were significantly decreased compared with the surrounding tissue regions, where most components are normal cells/tissues, such as fibroblasts, connective tissue and lymphocytes. Our observation also showed that the ultrasonic properties were influenced by arrangements of cells and tissue patterns. Conclusions: Our data demonstrate that attenuation and sound speed imaging can provide biomechanical information of the tumor and normal tissues. The results also demonstrate the potential of acoustic microscopy as an auxiliary method for operative detection and localization of cancer affected regions.

  4. Gene selection and classification for cancer microarray data based on machine learning and similarity measures

    Directory of Open Access Journals (Sweden)

    Liu Qingzhong

    2011-12-01

    Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

  5. The 2016 revision of the World Health Organization classification of lymphoid neoplasms | Center for Cancer Research

    Science.gov (United States)

    A revision of the nearly 8-year-old World Health Organization classification of the lymphoid neoplasms and the accompanying monograph is being published. It reflects a consensus among hematopathologists, geneticists, and clinicians regarding both updates to current entities as well as the addition of a limited number of new provisional entities.

  6. Ionizing radiation decreases human cancer mortality rates

    International Nuclear Information System (INIS)

    Luckey, T.D.

    1997-01-01

    Information from nine studies with exposed nuclear workers and military observers of atmospheric bomb explosions confirms the results from animal studies which showed that low doses of ionizing radiation are beneficial. The usual ''healthy worker effect'' was eliminated by using carefully selected control populations. The results from 13 million person-years show the cancer mortality rate of exposed persons is only 65.6% that of carefully selected unexposed controls. This overwhelming evidence makes it politically untenable and morally wrong to withhold public health benefits of low dose irradiation. Safe supplementation of ionizing radiation should become a public health service. (author)

  7. Artificial sweeteners and human bladder cancer.

    Science.gov (United States)

    Howe, G R; Burch, J D; Miller, A B; Morrison, B; Gordon, P; Weldon, L; Chambers, L W; Fodor, G; Winsor, G M

    1977-09-17

    A positive association between the use of artificial sweetners, particularly saccharin, and risk of bladder cancer in males has been observed in a case-control study of 480 men and 152 women in three Provinces in Canada. The risk ratio for ever versus never used is 1-6 for males (P=0-009, one-tailed test), and a significant dose-response relationship was obtained for both duration and frequency of use. The population attributable risk for males is estimated at 7%, though for diabetics, who have a similar risk ratio for artificial sweetner use as non-diabetics, the attributable risk is 33%.

  8. Resveratrol: A review of preclinical studies for human cancer prevention

    International Nuclear Information System (INIS)

    Athar, Mohammad; Back, Jung Ho; Tang Xiuwei; Kim, Kwang Ho; Kopelovich, Levy; Bickers, David R.; Kim, Arianna L.

    2007-01-01

    The search for novel and effective cancer chemopreventive agents has led to the identification of various naturally occurring compounds one of which is resveratrol (trans-3,4',5-trihydroxystilbene), a phytoalexin derived from the skin of grapes and other fruits. Resveratrol is known to have potent anti-inflammatory and antioxidant effects and to inhibit platelet aggregation and the growth of a variety of cancer cells. Its potential chemopreventive and chemotherapeutic activities have been demonstrated in all three stages of carcinogenesis (initiation, promotion, and progression), in both chemically and UVB-induced skin carcinogenesis in mice, as well as in various murine models of human cancers. Evidence from numerous in vitro and in vivo studies has confirmed its ability to modulate various targets and signaling pathways. This review discusses the current preclinical and mechanistic data available and assesses resveratrol's anticancer effects to support its potential as an anticancer agent in human populations

  9. Sulphur XANES Analysis of Cultured Human Prostate Cancer Cells

    International Nuclear Information System (INIS)

    Kwiatek, W.M.; Podgorczyk, M.; Paluszkiewicz, Cz.; Balerna, A.; Kisiel, A.

    2008-01-01

    Prostate cancer is one of the most commonly diagnosed cancers in men throughout the world. It is believed that changes to the structure of protein binding sites, altering its metabolism, may play an important role in carcinogenesis. Sulphur, often present in binding sites, can influence such changes through its chemical speciation. Hence there is a need for precise investigation of coordination environment of sulphur. X-ray absorption near edge structure spectroscopy offers such possibility. Cell culture samples offer histologically well defined areas of good homogeneity, suitable for successful and reliable X-ray absorption near edge structure analysis. This paper presents sulphur speciation data collected from three different human prostate cancer cell lines (PC-3, LNCaP and DU-145). Sulphur X-ray absorption near edge structure analysis was performed on K-edge structure. The spectra of cells were compared with those of cancerous tissue and with organic substances as well as inorganic compounds. (authors)

  10. Endothelium specific matrilysin (MMP-7) expression in human cancers

    NARCIS (Netherlands)

    Sier, C.F.M.; Hawinkels, L.J.A.C.; Zijlmans, H.J.M.A.A.; Zuidwijk, K.; Jonge de; Muller, E.S.M.; Ferreira, V.; Hanemaaijer, R.; Mulder-Stapel, A.A.; Kenter, G.G.; Verspaget, H.W.; Gorter, A.

    2008-01-01

    Over-expression of matrilysin (MMP-7) is predominantly associated with epithelial (pre)malignant cells. In the present study MMP-7 expression is also found in endothelial cells in various human cancer types. Endothelial MMP-7 was associated with CD34 and/or CD105 expression. These

  11. Knowledge and attitudes towards cervical cancer and human ...

    African Journals Online (AJOL)

    on respondents' biodata, knowledge of STIs, human papilloma virus and cervical cancer, health and communication resources in their communities. This was supplemented by focus group discussions among religious and tribal groups within the urban and rural communities. We found a low level of awareness about HPV ...

  12. Comparison of the prevalence of malnutrition diagnosis in head and neck, gastrointestinal and lung cancer patients by three classification methods

    Science.gov (United States)

    Platek, Mary E.; Popp KPf, Johann V.; Possinger, Candi S.; DeNysschen, Carol A.; Horvath, Peter; Brown, Jean K.

    2011-01-01

    Background Malnutrition is prevalent among patients within certain cancer types. There is lack of universal standard of care for nutrition screening, lack of agreement on an operational definition and on validity of malnutrition indicators. Objective In a secondary data analysis, we investigated prevalence of malnutrition diagnosis by three classification methods using data from medical records of a National Cancer Institute (NCI)-designated comprehensive cancer center. Interventions/Methods Records of 227 patients hospitalized during 1998 with head and neck, gastrointestinal or lung cancer were reviewed for malnutrition based on three methods: 1) physician diagnosed malnutrition related ICD-9 codes; 2) in-hospital nutritional assessment summary conducted by Registered Dietitians; and 3) body mass index (BMI). For patients with multiple admissions, only data from the first hospitalization was included. Results Prevalence of malnutrition diagnosis ranged from 8.8% based on BMI to approximately 26% of all cases based on dietitian assessment. Kappa coefficients between any methods indicated a weak (kappa=0.23, BMI and Dietitians and kappa=0.28, Dietitians and Physicians) to fair strength of agreement (kappa=0.38, BMI and Physicians). Conclusions Available methods to identify patients with malnutrition in an NCI designated comprehensive cancer center resulted in varied prevalence of malnutrition diagnosis. Universal standard of care for nutrition screening that utilizes validated tools is needed. Implications for Practice The Joint Commission on the Accreditation of Healthcare Organizations requires nutritional screening of patients within 24 hours of admission. For this purpose, implementation of a validated tool that can be used by various healthcare practitioners, including nurses, needs to be considered. PMID:21242767

  13. Viruses and human cancers: challenges for preventive strategies.

    Science.gov (United States)

    de The, G

    1995-01-01

    Virus-associated human cancers provide unique opportunities for preventive strategies. The role of human papilloma viruses (HPV 16 and 18), hepatitis B virus (HBV), Epstein-Barr herpes virus (EBV), and retroviruses (human immunodeficiency virus [HIV] and human T-cell leukemia/lymphoma virus [HTLV]) in the development of common carcinomas and lymphomas represents a major cancer threat, particularly among individuals residing in developing countries, which account for 80% of the world's population. Even though these viruses are not the sole etiological agents of these cancers (as would be the case for infectious diseases), different approaches can be implemented to significantly decrease the incidence of virus-associated malignancies. The first approach is vaccination, which is available for HBV and possibly soon for EBV. The long delay between primary viral infection and development of associated tumors as well as the cost involved with administering vaccinations detracts from the feasibility of such an approach within developing countries. The second approach is to increase efforts to detect pre-cancerous lesions or early tumors using immunovirological means. This would allow early diagnosis and better treatment. The third strategy is linked to the existence of disease susceptibility genes, and suggests that counseling be provided for individuals carrying these genes to encourage them to modify their lifestyles and other conditions associated with increased cancer risks (predictive oncology). Specific recommendations include: a) increase international studies that explore the causes of the large variations in prevalence of common cancers throughout the world; b) conduct interdisciplinary studies involving laboratory investigation and social sciences, which may suggest hypotheses that may then be tested experimentally; and c) promote more preventive and health enhancement strategies in addition to curative and replacement therapies. PMID:8741797

  14. Identification of DNA methylation changes associated with human gastric cancer

    Directory of Open Access Journals (Sweden)

    Park Jung-Hoon

    2011-12-01

    Full Text Available Abstract Background Epigenetic alteration of gene expression is a common event in human cancer. DNA methylation is a well-known epigenetic process, but verifying the exact nature of epigenetic changes associated with cancer remains difficult. Methods We profiled the methylome of human gastric cancer tissue at 50-bp resolution using a methylated DNA enrichment technique (methylated CpG island recovery assay in combination with a genome analyzer and a new normalization algorithm. Results We were able to gain a comprehensive view of promoters with various CpG densities, including CpG Islands (CGIs, transcript bodies, and various repeat classes. We found that gastric cancer was associated with hypermethylation of 5' CGIs and the 5'-end of coding exons as well as hypomethylation of repeat elements, such as short interspersed nuclear elements and the composite element SVA. Hypermethylation of 5' CGIs was significantly correlated with downregulation of associated genes, such as those in the HOX and histone gene families. We also discovered long-range epigenetic silencing (LRES regions in gastric cancer tissue and identified several hypermethylated genes (MDM2, DYRK2, and LYZ within these regions. The methylation status of CGIs and gene annotation elements in metastatic lymph nodes was intermediate between normal and cancerous tissue, indicating that methylation of specific genes is gradually increased in cancerous tissue. Conclusions Our findings will provide valuable data for future analysis of CpG methylation patterns, useful markers for the diagnosis of stomach cancer, as well as a new analysis method for clinical epigenomics investigations.

  15. An Inter-Rater Comparison of DoD Human Factors Analysis and Classification System (HFACS) and Human Factors Analysis and Classification System-Maritime (HFACS-M)

    Science.gov (United States)

    2013-09-01

    LEFT BLANK vii TABLE OF CONTENTS I.  INTRODUCTION ............................................................................................. 1...Adams, Brent DeVore, John Zuzich, and Cory Blaser. xviii THIS PAGE INTENTIONALLY LEFT BLANK 1 I. INTRODUCTION A. OVERVIEW Human error has...Behavioral Factors Perceptual Factors Condition of Individuals Crew Resource Mangement Self Imposed Stress Personnel Factors PRECONDITIONS Figure 7

  16. The mammographic correlations of a new immunohistochemical classification of invasive breast cancer

    Energy Technology Data Exchange (ETDEWEB)

    Taneja, S. [Nottingham Breast Institute, City Hospital, Hucknall Road, Nottingham NG5 1PB (United Kingdom)], E-mail: sheeba_taneja@yahoo.co.uk; Evans, A.J. [Nottingham Breast Institute, City Hospital, Hucknall Road, Nottingham NG5 1PB (United Kingdom); Rakha, E.A.; Green, A.R. [Division of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham (United Kingdom); Ball, G. [Nottingham Trent University, School of Biomedical and Natural Sciences, Nottingham (United Kingdom); Ellis, I.O. [Division of Pathology, School of Molecular Medical Sciences, Nottingham University Hospitals NHS Trust and University of Nottingham, Nottingham (United Kingdom)

    2008-11-15

    Aim: Recent protein expression profiling of breast cancer has identified specific subtypes with clinical, biological, and therapeutic implications. The aim of this study was to identify the mammographic correlates of these novel molecular classes of invasive breast cancer. Materials and methods: The mammographic findings of 415 patients with operable breast cancer were correlated with the previously described protein expression classes identified by our group using immunohistochemical (IHC) assessment of a large series of breast cancer cases prepared as tissue microarrays (TMAs). Twenty-five proteins of known relevance in breast cancer were assessed, including hormone receptors, HER-2 status, basal and luminal markers, p53 expression, and E-cadherin. Results: The mammographic background pattern and proportion of lesions that were mammographically occult were similar in all groups. Groups characterized by luminal and hormone receptor positivity had significantly more spiculate lesions at mammography. Groups characterized by HER-2 overexpression, basal characteristics, and E-cadherin positivity had a significantly higher proportion of ill-defined masses. These findings were independent of histological grade. Conclusion: The mammographic features of breast cancer show significant correlation with molecular classes of invasive breast cancer identified by protein expression IHC analysis. The biological reasons for the findings and implications of these regarding imaging protocols require further study and may provide mechanisms for improvement of detection of these lesions.

  17. Toxicity of diuron in human cancer cells.

    Science.gov (United States)

    Huovinen, Marjo; Loikkanen, Jarkko; Naarala, Jonne; Vähäkangas, Kirsi

    2015-10-01

    Diuron is a substituted phenylurea used as a herbicide to control broadleaf and grass weeds and as a biocidal antifouling agent. Diuron is carcinogenic in rat urinary bladder and toxic to the reproductive system of oysters, sea urchins and lizards. The few studies carried out in human cells do not include the genotoxicity of diuron. We have investigated the toxicity of diuron in human breast adenocarcinoma (MCF-7) and human placental choriocarcinoma (BeWo) cells. The production of reactive oxygen species (ROS) was statistically significantly increased in both cell lines but only at the highest 200 μM concentration. Diuron clearly reduced the viability of BeWo, but not MCF-7 cells. The relative cell number was decreased in both cell lines indicative of inhibition of cell proliferation. In the Comet assay, diuron increased DNA fragmentation in MCF-7 but not in BeWo cells. The expressions of p53 protein, a marker for cell stress, and p21 protein, a transcriptional target of p53, were increased, but only in MCF-7 cells. In conclusion, our results suggest that diuron is cytotoxic and potentially genotoxic in a tissue-specific manner and that ROS play a role in its toxicity. Thus, exposure to diuron may exert harmful effects on fetal development and damage human health. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Classification of follicular cell-derived thyroid cancer by global RNA profiling

    DEFF Research Database (Denmark)

    Rossing, Maria

    2013-01-01

    The incidence of thyroid cancer is increasing worldwide and thyroid nodules are a frequent clinical finding. Diagnosing follicular cell-derived cancers is, however, challenging both histopathologically and especially cytopathologically. The advent of high-throughput molecular technologies has...... profiling of follicular cell-derived thyroid cancers....... prompted many researchers to explore the transcriptome and, in recent years, also the miRNome in order to generate new molecular classifiers capable of classifying thyroid tumours more accurately than by conventional cytopathological and histopathological methods. This has led to a number of molecular...

  19. Clinicopathological significance of PTPN12 expression in human breast cancer

    International Nuclear Information System (INIS)

    Yuan, Xunyi; Yuan, Zhentao; Jiang, Dandan; Li, Funian

    2012-01-01

    Protein tyrosine phosphatase non-receptor type 12 (PTPN12) is a recently identified tumor suppressor gene (TSG) that is frequently compromised in human triple-negative breast cancer. In the present study, we investigated the expression of PTPN12 protein by patients with breast cancer in a Chinese population and the relationship between PTPN12 expression levels and patient clinicopathological features and prognosis. Additionally, we explored the underlying down-regulation mechanism from the perspective of an epigenetic alteration. We examined PTPN12 mRNA expression in five breast cancer cell lines using semi-quantitative reverse-transcription PCR, and detected PTPN12 protein expression using immunohistochemistry in 150 primary invasive breast cancer cases and paired adjacent non-tumor tissues. Methylation-specific PCR was performed to analyze the promoter CpG island methylation status of PTPN12. PTPN12 was significantly down-regulated in breast cancer cases (48/150) compared to adjacent noncancerous tissues (17/150; P < 0.05). Furthermore, low expression of PTPN12 showed a significant positive correlation with tumor size (P = 0.047), lymph node metastasis (P = 0.001), distant metastasis (P = 0.009), histological grade (P = 0.012), and survival time (P = 0.019). Additionally, promoter CpG island hypermethylation occurs more frequently in breast cancer cases and breast cancer cell lines with low PTPN12 expression. Our findings suggest that PTPN12 is potentially a methylation-silenced TSG for breast cancer that may play an important role in breast carcinogenesis and could potentially serve as an independent prognostic factor for invasive breast cancer patients

  20. Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

    OpenAIRE

    Inti eZlobec; Inti eZlobec; Michel P Bihl; Anja eFoerster; Alex eRufle; Luigi eTerracciano; Alessandro eLugli; Alessandro eLugli

    2012-01-01

    Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related pro...

  1. Human cancers converge at the HIF-2alpha oncogenic axis.

    Science.gov (United States)

    Franovic, Aleksandra; Holterman, Chet E; Payette, Josianne; Lee, Stephen

    2009-12-15

    Cancer development is a multistep process, driven by a series of genetic and environmental alterations, that endows cells with a set of hallmark traits required for tumorigenesis. It is broadly accepted that growth signal autonomy, the first hallmark of malignancies, can be acquired through multiple genetic mutations that activate an array of complex, cancer-specific growth circuits [Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100:57-70; Vogelstein B, Kinzler KW (2004) Cancer genes and the pathways they control. Nat Med 10:789-799]. The superfluous nature of these pathways is thought to severely limit therapeutic approaches targeting tumor proliferation, and it has been suggested that this strategy be abandoned in favor of inhibiting more systemic hallmarks, including angiogenesis (Ellis LM, Hicklin DJ (2008) VEGF-targeted therapy: Mechanisms of anti-tumor activity. Nat Rev Cancer 8:579-591; Stommel JM, et al. (2007) Coactivation of receptor tyrosine kinases affects the response of tumor cells to targeted therapies. Science 318:287-290; Kerbel R, Folkman J (2002) Clinical translation of angiogenesis inhibitors. Nat Rev Cancer 2:727-739; Kaiser J (2008) Cancer genetics: A detailed genetic portrait of the deadliest human cancers. Science 321:1280-1281]. Here, we report the unexpected observation that genetically diverse cancers converge at a common and obligatory growth axis instigated by HIF-2alpha, an element of the oxygen-sensing machinery. Inhibition of HIF-2alpha prevents the in vivo growth and tumorigenesis of highly aggressive glioblastoma, colorectal, and non-small-cell lung carcinomas and the in vitro autonomous proliferation of several others, regardless of their mutational status and tissue of origin. The concomitant deactivation of select receptor tyrosine kinases, including the EGFR and IGF1R, as well as downstream ERK/Akt signaling, suggests that HIF-2alpha exerts its proliferative effects by endorsing these major pathways. Consistently

  2. Controversies surrounding human papilloma virus infection, head & neck vs oral cancer, implications for prophylaxis and treatment.

    Science.gov (United States)

    Campisi, Giuseppina; Giovannelli, Lucia

    2009-03-30

    Head & Neck Cancer (HNC) represents the sixth most common malignancy worldwide and it is historically linked to well-known behavioural risk factors, i.e., tobacco smoking and/or the alcohol consumption. Recently, substantial evidence has been mounting that Human Papillomavirus (HPV) infection is playing an increasing important role in oral cancer. Because of the attention and clamor surrounding oral HPV infection and related cancers, as well as the use of HPV prophylactic vaccines, in this invited perspective the authors raise some questions and review some controversial issues on HPV infection and its role in HNC, with a particular focus on oral squamous cell carcinoma. The problematic definition and classification of HNC will be discussed, together with the characteristics of oral infection with oncogenic HPV types, the frequency of HPV DNA detection in HNC, the location of HPV-related tumours, the severity and prognosis of HPV-positive HNC, the diagnosis of oral HPV infection, common routes of oral infection and the likelihood of oro-genital HPV transmission, the prevention of HPV infection and novel therapeutic approaches.

  3. Classification of a palliative care population in a comprehensive cancer centre

    DEFF Research Database (Denmark)

    Benthien, K.S; Nordly, M.; Videbæk, K.

    2016-01-01

    PURPOSE: The purposes of the present study were to classify the palliative care population (PCP) in a comprehensive cancer centre by using information on antineoplastic treatment options and to analyse associations between socio-demographic factors, cancer diagnoses, treatment characteristics...... and receiving specialist palliative care (SPC). METHODS: This is a cross-sectional screening study of patients with cancer in the Department of Oncology, Rigshospitalet, Copenhagen University Hospital for 6 months. Patients were assessed to be included in the DOMUS study: a randomised controlled trial...... of accelerated transition to SPC at home (NCT01885637). The PCP was classified as patients with incurable cancer and limited or no antineoplastic treatment options. Patients with performance status 2-4 were further classified as the essential palliative care population (EPCP). RESULTS: During the study period...

  4. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, H.M.J.; Moerland, P.D.; Van den Ham, R.; Reinders, M.J.T.; Verhaegh, W.F.J.

    2009-01-01

    Background: Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for

  5. A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

    NARCIS (Netherlands)

    Sontrop, Herman M. J.; Moerland, Perry D.; van den Ham, René; Reinders, Marcel J. T.; Verhaegh, Wim F. J.

    2009-01-01

    Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the

  6. Decision Tree of Occupational Lung Cancer Using Classification and Regression Analysis

    Directory of Open Access Journals (Sweden)

    Tae-Woo Kim

    2010-12-01

    Conclusion: We found that exposure to lung carcinogens, latency and smoking history were predictive factors of approval for occupational lung cancer. Further studies for work-relatedness of occupational disease are needed.

  7. [Soy isoflavones and human health: breast cancer and puberty timing].

    Science.gov (United States)

    Valladares, Luis; Garrido, Argelia; Sierralta, Walter

    2012-04-01

    Accumulated exposure to high levels of estrogen is associated with an increased incidence of breast cancer. Thus, factors such as early puberty, late menopause and hormone replacement therapy are considered to be risk factors, whereas early childbirth, breastfeeding and puberty at a later age are known to consistently decrease the lifetime breast cancer risk. Epidemiological studies suggest that consumption of isoflavones correlates with a lower incidence of breast cancer. Data from human intervention studies show that the effects of isoflavones on early breast cancer markers differ between pre- and post-menopausal women. The reports from experimental animals (rats and mice) on mammary tumors are variable. These results taken together with heterogeneous outcomes of human interventions, have led to a controversy surrounding the intake of isoflavones to reduce breast cancer risk. This review summarizes recent studies and analyzes factors that could explain the variability of results. In mammary tissue, from the cellular endocrine viewpoint, we analyze the effect of isoflavones on the estrogen receptor and their capacity to act as agonists or antagonists. On the issue of puberty timing, we analyze the mechanisms by which girls, but not boys, with higher prepuberal isoflavone intakes appear to enter puberty at a later age.

  8. Development of a computer aided diagnosis model for prostate cancer classification on multi-parametric MRI

    Science.gov (United States)

    Alfano, R.; Soetemans, D.; Bauman, G. S.; Gibson, E.; Gaed, M.; Moussa, M.; Gomez, J. A.; Chin, J. L.; Pautler, S.; Ward, A. D.

    2018-02-01

    Multi-parametric MRI (mp-MRI) is becoming a standard in contemporary prostate cancer screening and diagnosis, and has shown to aid physicians in cancer detection. It offers many advantages over traditional systematic biopsy, which has shown to have very high clinical false-negative rates of up to 23% at all stages of the disease. However beneficial, mp-MRI is relatively complex to interpret and suffers from inter-observer variability in lesion localization and grading. Computer-aided diagnosis (CAD) systems have been developed as a solution as they have the power to perform deterministic quantitative image analysis. We measured the accuracy of such a system validated using accurately co-registered whole-mount digitized histology. We trained a logistic linear classifier (LOGLC), support vector machine (SVC), k-nearest neighbour (KNN) and random forest classifier (RFC) in a four part ROI based experiment against: 1) cancer vs. non-cancer, 2) high-grade (Gleason score ≥4+3) vs. low-grade cancer (Gleason score work will form the basis for a tool that enhances the radiologist's ability to detect malignancies, potentially improving biopsy guidance, treatment selection, and focal therapy for prostate cancer patients, maximizing the potential for cure and increasing quality of life.

  9. Human cancer stem cells are a target for cancer prevention using (-)-epigallocatechin gallate.

    Science.gov (United States)

    Fujiki, Hirota; Sueoka, Eisaburo; Rawangkan, Anchalee; Suganuma, Masami

    2017-12-01

    Our previous experiments show that the main constituent of green-tea catechins, (-)-epigallocatechin gallate (EGCG), completely prevents tumor promotion on mouse skin initiated with 7,12-dimethylbenz(a)anthracene followed by okadaic acid and that EGCG and green tea extract prevent cancer development in a wide range of target organs in rodents. Therefore, we focused our attention on human cancer stem cells (CSCs) as targets of cancer prevention and treatment with EGCG. The numerous reports concerning anticancer activity of EGCG against human CSCs enriched from cancer cell lines were gathered from a search of PubMed, and we hope our review of the literatures will provide a broad selection for the effects of EGCG on various human CSCs. Based on our theoretical study, we discuss the findings as follows: (1) Compared with the parental cells, human CSCs express increased levels of the stemness markers Nanog, Oct4, Sox2, CD44, CD133, as well as the EMT markers, Twist, Snail, vimentin, and also aldehyde dehydrogenase. They showed decreased levels of E-cadherin and cyclin D1. (2) EGCG inhibits the transcription and translation of genes encoding stemness markers, indicating that EGCG generally inhibits the self-renewal of CSCs. (3) EGCG inhibits the expression of the epithelial-mesenchymal transition phenotypes of human CSCs. (4) The inhibition of EGCG of the stemness of CSCs was weaker compared with parental cells. (5) The weak inhibitory activity of EGCG increased synergistically in combination with anticancer drugs. Green tea prevents human cancer, and the combination of EGCG and anticancer drugs confers cancer treatment with tissue-agnostic efficacy.

  10. Classification of bladder cancer cell lines using Raman spectroscopy: a comparison of excitation wavelength, sample substrate and statistical algorithms

    Science.gov (United States)

    Kerr, Laura T.; Adams, Aine; O'Dea, Shirley; Domijan, Katarina; Cullen, Ivor; Hennelly, Bryan M.

    2014-05-01

    Raman microspectroscopy can be applied to the urinary bladder for highly accurate classification and diagnosis of bladder cancer. This technique can be applied in vitro to bladder epithelial cells obtained from urine cytology or in vivo as an optical biopsy" to provide results in real-time with higher sensitivity and specificity than current clinical methods. However, there exists a high degree of variability across experimental parameters which need to be standardised before this technique can be utilized in an everyday clinical environment. In this study, we investigate different laser wavelengths (473 nm and 532 nm), sample substrates (glass, fused silica and calcium fluoride) and multivariate statistical methods in order to gain insight into how these various experimental parameters impact on the sensitivity and specificity of Raman cytology.

  11. Clinical Usefulness of the VS Classification System Using Magnifying Endoscopy with Blue Laser Imaging for Early Gastric Cancer

    Directory of Open Access Journals (Sweden)

    Yoshikazu Yoshifuku

    2017-01-01

    Full Text Available Background. Blue laser imaging (BLI enables the acquisition of more information from tumors’ surfaces compared with white light imaging. Few reports confirm the validity of magnifying endoscopy (ME with BLI (ME-BLI for early gastric cancer (EGC. We aimed to assess the detailed endoscopic findings from EGCs using ME-BLI. Methods. We enrolled 386 consecutive patients with 417 EGCs that were diagnosed using ME-BLI and resected by endoscopic submucosal dissection. Using the VS classification system, three highly experienced endoscopists (HEEs and three less experienced endoscopists (LEEs evaluated the demarcation line (DL, microsurface pattern (MSP, and microvascular pattern (MVP within the endoscopic images of EGCs obtained using ME-BLI, assigning high-confidence (HC or low-confidence (LC levels. We investigated the clinicopathological features associated with each confidence level. Results. The HEEs’ evaluations determined the presence of DL in 99%, irregular MSP in 96%, and irregular MVP in 96%, and the LEEs’ evaluations determined the presence of DL in 98%, irregular MSP in 95%, and irregular MVP in 95% of the EGCs. When DL was present, HC levels in the Helicobacter pylori- (H. pylori- eradicated group and noneradicated group were evident in 65% and 89%, a difference that was significant (p<0.001. Conclusions. In the diagnosis of EGC with ME-BLI, the VS classification system with ME-NBI can be applied, but identifying the DL after H. pylori was difficult.

  12. An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

    Science.gov (United States)

    Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua

    2014-01-01

    The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.

  13. [HPV (Human Papilloma Virus) implication in other cancers than gynaecological].

    Science.gov (United States)

    Badoual, C; Tartour, E; Roussel, H; Bats, A S; Pavie, J; Pernot, S; Weiss, L; Mohamed, A Si; Thariat, J; Hoffmann, C; Péré, H

    2015-08-01

    Worldwide, approximately 5 to 10% of the population is infected by a Human Papilloma Virus (HPV). Some of these viruses, with a high oncogenic risk (HPV HR), are responsible for about 5% of cancer. It is now accepted that almost all carcinomas of the cervix and the vulva are due to an HPV HR (HPV16 and 18) infection. However, these viruses are known to be involved in the carcinogenesis of many other cancers (head and neck [SCCHN], penis, anus). For head and neck cancer, HPV infection is considered as a good prognostic factor. The role of HPV HR in anal cancer is also extensively studied in high-risk patient's population. The role of HPV infection in the carcinogenesis of esophageal, bladder, lung, breast or skin cancers is still debated. Given the multiple possible locations of HPV HR infection, the question of optimizing the management of patients with a HPV+ cancer arises in the implementation of a comprehensive clinical and biological monitoring. It is the same in therapeutics with the existence of a preventive vaccination, for example. Copyright © 2015 Société nationale française de médecine interne (SNFMI). Published by Elsevier SAS. All rights reserved.

  14. ANALYSES ON DIFFERENTIALLY EXPRESSED GENES ASSOCIATED WITH HUMAN BREAST CANCER

    Institute of Scientific and Technical Information of China (English)

    MENG Xu-li; DING Xiao-wen; XU Xiao-hong

    2006-01-01

    Objective: To investigate the molecular etiology of breast cancer by way of studying the differential expression and initial function of the related genes in the occurrence and development of breast cancer. Methods: Two hundred and eighty-eight human tumor related genes were chosen for preparation of the oligochips probe. mRNA was extracted from 16 breast cancer tissues and the corresponding normal breast tissues, and cDNA probe was prepared through reverse-transcription and hybridized with the gene chip. A laser focused fluorescent scanner was used to scan the chip. The different gene expressions were thereafter automatically compared and analyzed between the two sample groups. Cy3/Cy5>3.5 meant significant up-regulation. Cy3/Cy5<0.25 meant significant down-regulation. Results: The comparison between the breast cancer tissues and their corresponding normal tissues showed that 84 genes had differential expression in the Chip. Among the differently expressed genes, there were 4 genes with significant down-regulation and 6 with significant up-regulation. Compared with normal breast tissues, differentially expressed genes did partially exist in the breast cancer tissues. Conclusion: Changes in multi-gene expression regulations take place during the occurrence and development of breast cancer; and the research on related genes can help understanding the mechanism of tumor occurrence.

  15. Are 20 human papillomavirus types causing cervical cancer?

    OpenAIRE

    Arbyn, Marc; Tommasino, Massimo; Depuydt, Christophe; Dillner, Joakim

    2014-01-01

    Abstract: In 2012, the International Agency for Research on Cancer concluded that there was consistent and sufficient epidemiological, experimental and mechanistic evidence of carcinogenicity to humans for 12 HPV types (HPV16, HPV18, HPV31, HPV33, HPV35, HPV39, HPV45, HPV51, HPV52, HPV56, HPV58 and HPV59) for cervical cancer. Therefore, these types were considered as 1A carcinogens. They all belong to the family of the -Papillomaviridae, in particular to the species 5 (HPV51), 6 (HPV56), 7 (H...

  16. Human endogenous retroviruses and cancer prevention: evidence and prospects

    Directory of Open Access Journals (Sweden)

    Cegolon Luca

    2013-01-01

    Full Text Available Abstract Background Cancer is a significant and growing problem worldwide. While this increase may, in part, be attributed to increasing longevity, improved case notifications and risk-enhancing lifestyle (such as smoking, diet and obesity, hygiene-related factors resulting in immuno-regulatory failure may also play a major role and call for a revision of vaccination strategies to protect against a range of cancers in addition to infections. Discussion Human endogenous retroviruses (HERVs are a significant component of a wider family of retroelements that constitutes part of the human genome. They were originated by the integration of exogenous retroviruses into the human genome millions of years ago. HERVs are estimated to comprise about 8% of human DNA and are ubiquitous in somatic and germinal tissues. Physiologic and pathologic processes are influenced by some biologically active HERV families. HERV antigens are only expressed at low levels by the host, but in circumstances of inappropriate control their genes may initiate or maintain pathological processes. Although the precise mechanism leading to abnormal HERVs gene expression has yet to be clearly elucidated, environmental factors seem to be involved by influencing the human immune system. HERV-K expression has been detected in different types of tumors. Among the various human endogenous retroviral families, the K series was the latest acquired by the human species. Probably because of its relatively recent origin, the HERV-K is the most complete and biologically active family. The abnormal expression of HERV-K seemingly triggers pathological processes leading to melanoma onset, but also contributes to the morphological and functional cellular modifications implicated in melanoma maintenance and progression. The HERV-K-MEL antigen is encoded by a pseudo-gene incorporated in the HERV-K env-gene. HERV-K-MEL is significantly expressed in the majority of dysplastic and normal naevi, as well

  17. Human endogenous retroviruses and cancer prevention: evidence and prospects.

    Science.gov (United States)

    Cegolon, Luca; Salata, Cristiano; Weiderpass, Elisabete; Vineis, Paolo; Palù, Giorgio; Mastrangelo, Giuseppe

    2013-01-03

    Cancer is a significant and growing problem worldwide. While this increase may, in part, be attributed to increasing longevity, improved case notifications and risk-enhancing lifestyle (such as smoking, diet and obesity), hygiene-related factors resulting in immuno-regulatory failure may also play a major role and call for a revision of vaccination strategies to protect against a range of cancers in addition to infections. Human endogenous retroviruses (HERVs) are a significant component of a wider family of retroelements that constitutes part of the human genome. They were originated by the integration of exogenous retroviruses into the human genome millions of years ago. HERVs are estimated to comprise about 8% of human DNA and are ubiquitous in somatic and germinal tissues.Physiologic and pathologic processes are influenced by some biologically active HERV families. HERV antigens are only expressed at low levels by the host, but in circumstances of inappropriate control their genes may initiate or maintain pathological processes. Although the precise mechanism leading to abnormal HERVs gene expression has yet to be clearly elucidated, environmental factors seem to be involved by influencing the human immune system.HERV-K expression has been detected in different types of tumors.Among the various human endogenous retroviral families, the K series was the latest acquired by the human species. Probably because of its relatively recent origin, the HERV-K is the most complete and biologically active family.The abnormal expression of HERV-K seemingly triggers pathological processes leading to melanoma onset, but also contributes to the morphological and functional cellular modifications implicated in melanoma maintenance and progression.The HERV-K-MEL antigen is encoded by a pseudo-gene incorporated in the HERV-K env-gene. HERV-K-MEL is significantly expressed in the majority of dysplastic and normal naevi, as well as other tumors like sarcoma, lymphoma, bladder and

  18. Human endogenous retroviruses and cancer prevention: evidence and prospects

    International Nuclear Information System (INIS)

    Cegolon, Luca; Salata, Cristiano; Weiderpass, Elisabete; Vineis, Paolo; Palù, Giorgio; Mastrangelo, Giuseppe

    2013-01-01

    Cancer is a significant and growing problem worldwide. While this increase may, in part, be attributed to increasing longevity, improved case notifications and risk-enhancing lifestyle (such as smoking, diet and obesity), hygiene-related factors resulting in immuno-regulatory failure may also play a major role and call for a revision of vaccination strategies to protect against a range of cancers in addition to infections. Human endogenous retroviruses (HERVs) are a significant component of a wider family of retroelements that constitutes part of the human genome. They were originated by the integration of exogenous retroviruses into the human genome millions of years ago. HERVs are estimated to comprise about 8% of human DNA and are ubiquitous in somatic and germinal tissues. Physiologic and pathologic processes are influenced by some biologically active HERV families. HERV antigens are only expressed at low levels by the host, but in circumstances of inappropriate control their genes may initiate or maintain pathological processes. Although the precise mechanism leading to abnormal HERVs gene expression has yet to be clearly elucidated, environmental factors seem to be involved by influencing the human immune system. HERV-K expression has been detected in different types of tumors. Among the various human endogenous retroviral families, the K series was the latest acquired by the human species. Probably because of its relatively recent origin, the HERV-K is the most complete and biologically active family. The abnormal expression of HERV-K seemingly triggers pathological processes leading to melanoma onset, but also contributes to the morphological and functional cellular modifications implicated in melanoma maintenance and progression. The HERV-K-MEL antigen is encoded by a pseudo-gene incorporated in the HERV-K env-gene. HERV-K-MEL is significantly expressed in the majority of dysplastic and normal naevi, as well as other tumors like sarcoma, lymphoma, bladder

  19. Feature selection and classification of MAQC-II breast cancer and multiple myeloma microarray gene expression data.

    Directory of Open Access Journals (Sweden)

    Qingzhong Liu

    Full Text Available Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. In this paper, we propose a gene selection method called Recursive Feature Addition (RFA, which combines supervised learning and statistical similarity measures. We compare our method with the following gene selection methods: Support Vector Machine Recursive Feature Elimination (SVMRFE, Leave-One-Out Calculation Sequential Forward Selection (LOOCSFS, Gradient based Leave-one-out Gene Selection (GLGS. To evaluate the performance of these gene selection methods, we employ several popular learning classifiers on the MicroArray Quality Control phase II on predictive modeling (MAQC-II breast cancer dataset and the MAQC-II multiple myeloma dataset. Experimental results show that gene selection is strictly paired with learning classifier. Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and

  20. Computer-aided diagnosis of lung cancer: the effect of training data sets on classification accuracy of lung nodules

    Science.gov (United States)

    Gong, Jing; Liu, Ji-Yu; Sun, Xi-Wen; Zheng, Bin; Nie, Sheng-Dong

    2018-02-01

    This study aims to develop a computer-aided diagnosis (CADx) scheme for classification between malignant and benign lung nodules, and also assess whether CADx performance changes in detecting nodules associated with early and advanced stage lung cancer. The study involves 243 biopsy-confirmed pulmonary nodules. Among them, 76 are benign, 81 are stage I and 86 are stage III malignant nodules. The cases are separated into three data sets involving: (1) all nodules, (2) benign and stage I malignant nodules, and (3) benign and stage III malignant nodules. A CADx scheme is applied to segment lung nodules depicted on computed tomography images and we initially computed 66 3D image features. Then, three machine learning models namely, a support vector machine, naïve Bayes classifier and linear discriminant analysis, are separately trained and tested by using three data sets and a leave-one-case-out cross-validation method embedded with a Relief-F feature selection algorithm. When separately using three data sets to train and test three classifiers, the average areas under receiver operating characteristic curves (AUC) are 0.94, 0.90 and 0.99, respectively. When using the classifiers trained using data sets with all nodules, average AUC values are 0.88 and 0.99 for detecting early and advanced stage nodules, respectively. AUC values computed from three classifiers trained using the same data set are consistent without statistically significant difference (p  >  0.05). This study demonstrates (1) the feasibility of applying a CADx scheme to accurately distinguish between benign and malignant lung nodules, and (2) a positive trend between CADx performance and cancer progression stage. Thus, in order to increase CADx performance in detecting subtle and early cancer, training data sets should include more diverse early stage cancer cases.

  1. Identification of immune cell infiltration in hematoxylin-eosin stained breast cancer samples: texture-based classification of tissue morphologies

    Science.gov (United States)

    Turkki, Riku; Linder, Nina; Kovanen, Panu E.; Pellinen, Teijo; Lundin, Johan

    2016-03-01

    The characteristics of immune cells in the tumor microenvironment of breast cancer capture clinically important information. Despite the heterogeneity of tumor-infiltrating immune cells, it has been shown that the degree of infiltration assessed by visual evaluation of hematoxylin-eosin (H and E) stained samples has prognostic and possibly predictive value. However, quantification of the infiltration in H and E-stained tissue samples is currently dependent on visual scoring by an expert. Computer vision enables automated characterization of the components of the tumor microenvironment, and texture-based methods have successfully been used to discriminate between different tissue morphologies and cell phenotypes. In this study, we evaluate whether local binary pattern texture features with superpixel segmentation and classification with support vector machine can be utilized to identify immune cell infiltration in H and E-stained breast cancer samples. Guided with the pan-leukocyte CD45 marker, we annotated training and test sets from 20 primary breast cancer samples. In the training set of arbitrary sized image regions (n=1,116) a 3-fold cross-validation resulted in 98% accuracy and an area under the receiver-operating characteristic curve (AUC) of 0.98 to discriminate between immune cell -rich and - poor areas. In the test set (n=204), we achieved an accuracy of 96% and AUC of 0.99 to label cropped tissue regions correctly into immune cell -rich and -poor categories. The obtained results demonstrate strong discrimination between immune cell -rich and -poor tissue morphologies. The proposed method can provide a quantitative measurement of the degree of immune cell infiltration and applied to digitally scanned H and E-stained breast cancer samples for diagnostic purposes.

  2. A novel gene signature for molecular diagnosis of human prostate cancer by RT-qPCR.

    Directory of Open Access Journals (Sweden)

    Federica Rizzi

    Full Text Available Prostate cancer (CaP is one of the most relevant causes of cancer death in Western Countries. Although detection of CaP at early curable stage is highly desirable, actual screening methods present limitations and new molecular approaches are needed. Gene expression analysis increases our knowledge about the biology of CaP and may render novel molecular tools, but the identification of accurate biomarkers for reliable molecular diagnosis is a real challenge. We describe here the diagnostic power of a novel 8-genes signature: ornithine decarboxylase (ODC, ornithine decarboxylase antizyme (OAZ, adenosylmethionine decarboxylase (AdoMetDC, spermidine/spermine N(1-acetyltransferase (SSAT, histone H3 (H3, growth arrest specific gene (GAS1, glyceraldehyde 3-phosphate dehydrogenase (GAPDH and Clusterin (CLU in tumour detection/classification of human CaP.The 8-gene signature was detected by retrotranscription real-time quantitative PCR (RT-qPCR in frozen prostate surgical specimens obtained from 41 patients diagnosed with CaP and recommended to undergo radical prostatectomy (RP. No therapy was given to patients at any time before RP. The bio-bank used for the study consisted of 66 specimens: 44 were benign-CaP paired from the same patient. Thirty-five were classified as benign and 31 as CaP after final pathological examination. Only molecular data were used for classification of specimens. The Nearest Neighbour (NN classifier was used in order to discriminate CaP from benign tissue. Validation of final results was obtained with 10-fold cross-validation procedure. CaP versus benign specimens were discriminated with (80+/-5% accuracy, (81+/-6% sensitivity and (78+/-7% specificity. The method also correctly classified 71% of patients with Gleason score or =7, an important predictor of final outcome.The method showed high sensitivity in a collection of specimens in which a significant portion of the total (13/31, equal to 42% was considered CaP on the basis

  3. Study on Biopharmaceutics Classification and Oral Bioavailability of a Novel Multikinase Inhibitor NCE for Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Yang Yang

    2014-04-01

    Full Text Available Specific biopharmaceutics classification investigation and study on phamacokinetic profile of a novel drug candidate (2-methylcarbamoyl-4-{4-[3- (trifluoromethyl benzamido] phenoxy} pyridinium 4-methylbenzenesulfonate monohydrate, NCE were carried out. Equilibrium solubility and intrinsic dissolution rate (IDR of NCE were estimated in different phosphate buffers. Effective intestinal permeability (Peff of NCE was determined using single-pass intestinal perfusion technique in rat duodenum, jejunum and ileum at three concentrations. Theophylline (high permeability and ranitidine (low permeability were also applied to access the permeability of NCE as reference compounds. The bioavailability after intragastrical and intravenous administration was measured in beagle dogs. The solubility of NCE in tested phosphate buffers was quite low with the maximum solubility of 81.73 μg/mL at pH 1.0. The intrinsic dissolution ratio of NCE was 1 × 10−4 mg·min−1·cm−2. The Peff value of NCE in all intestinal segments was more proximate to the high-permeability reference theophylline. Therefore, NCE was classified as class II drug according to Biopharmaceutics Classification System due to its low solubility and high intestinal permeability. In addition, concentration-dependent permeability was not observed in all the segments, indicating that there might be passive transportation for NCE. The absolute oral bioavailability of NCE in beagle dogs was 26.75%. Therefore, dissolution promotion will be crucial for oral formulation development and intravenous administration route will also be suggested for further NCE formulation development. All the data would provide a reference for biopharmaceutics classification research of other novel drug candidates.

  4. Study on biopharmaceutics classification and oral bioavailability of a novel multikinase inhibitor NCE for cancer therapy.

    Science.gov (United States)

    Yang, Yang; Fan, Chun-Mei; He, Xuan; Ren, Ke; Zhang, Jin-Kun; He, Ying-Ju; Yu, Luo-Ting; Zhao, Ying-Lan; Gong, Chang-Yang; Zheng, Yu; Song, Xiang-Rong; Zeng, Jun

    2014-04-25

    Specific biopharmaceutics classification investigation and study on phamacokinetic profile of a novel drug candidate (2-methylcarbamoyl-4-{4-[3- (trifluoromethyl) benzamido] phenoxy} pyridinium 4-methylbenzenesulfonate monohydrate, NCE) were carried out. Equilibrium solubility and intrinsic dissolution rate (IDR) of NCE were estimated in different phosphate buffers. Effective intestinal permeability (P(eff)) of NCE was determined using single-pass intestinal perfusion technique in rat duodenum, jejunum and ileum at three concentrations. Theophylline (high permeability) and ranitidine (low permeability) were also applied to access the permeability of NCE as reference compounds. The bioavailability after intragastrical and intravenous administration was measured in beagle dogs. The solubility of NCE in tested phosphate buffers was quite low with the maximum solubility of 81.73 μg/mL at pH 1.0. The intrinsic dissolution ratio of NCE was 1 × 10⁻⁴ mg·min⁻¹·cm⁻². The P(eff) value of NCE in all intestinal segments was more proximate to the high-permeability reference theophylline. Therefore, NCE was classified as class II drug according to Biopharmaceutics Classification System due to its low solubility and high intestinal permeability. In addition, concentration-dependent permeability was not observed in all the segments, indicating that there might be passive transportation for NCE. The absolute oral bioavailability of NCE in beagle dogs was 26.75%. Therefore, dissolution promotion will be crucial for oral formulation development and intravenous administration route will also be suggested for further NCE formulation development. All the data would provide a reference for biopharmaceutics classification research of other novel drug candidates.

  5. A novel method for human age group classification based on Correlation Fractal Dimension of facial edges

    OpenAIRE

    Yarlagadda, Anuradha; Murthy, J.V.R.; Krishna Prasad, M.H.M.

    2015-01-01

    In the computer vision community, easy categorization of a person’s facial image into various age groups is often quite precise and is not pursued effectively. To address this problem, which is an important area of research, the present paper proposes an innovative method of age group classification system based on the Correlation Fractal Dimension of complex facial image. Wrinkles appear on the face with aging thereby changing the facial edges of the image. The proposed method is rotation an...

  6. Hand posture classification using electrocorticography signals in the gamma band over human sensorimotor brain areas

    Science.gov (United States)

    Chestek, Cynthia A.; Gilja, Vikash; Blabe, Christine H.; Foster, Brett L.; Shenoy, Krishna V.; Parvizi, Josef; Henderson, Jaimie M.

    2013-04-01

    Objective. Brain-machine interface systems translate recorded neural signals into command signals for assistive technology. In individuals with upper limb amputation or cervical spinal cord injury, the restoration of a useful hand grasp could significantly improve daily function. We sought to determine if electrocorticographic (ECoG) signals contain sufficient information to select among multiple hand postures for a prosthetic hand, orthotic, or functional electrical stimulation system.Approach. We recorded ECoG signals from subdural macro- and microelectrodes implanted in motor areas of three participants who were undergoing inpatient monitoring for diagnosis and treatment of intractable epilepsy. Participants performed five distinct isometric hand postures, as well as four distinct finger movements. Several control experiments were attempted in order to remove sensory information from the classification results. Online experiments were performed with two participants. Main results. Classification rates were 68%, 84% and 81% for correct identification of 5 isometric hand postures offline. Using 3 potential controls for removing sensory signals, error rates were approximately doubled on average (2.1×). A similar increase in errors (2.6×) was noted when the participant was asked to make simultaneous wrist movements along with the hand postures. In online experiments, fist versus rest was successfully classified on 97% of trials; the classification output drove a prosthetic hand. Online classification performance for a larger number of hand postures remained above chance, but substantially below offline performance. In addition, the long integration windows used would preclude the use of decoded signals for control of a BCI system. Significance. These results suggest that ECoG is a plausible source of command signals for prosthetic grasp selection. Overall, avenues remain for improvement through better electrode designs and placement, better participant training

  7. Abridged republication of FIGO's staging classification for cancer of the ovary, fallopian tube, and peritoneum.

    Science.gov (United States)

    Prat, Jaime

    2015-10-01

    Ovarian, fallopian tube, and peritoneal cancers have a similar clinical presentation and are treated similarly, and current evidence supports staging all 3 cancers in a single system. The primary site (i.e. ovary, fallopian tube, or peritoneum) should be designated where possible. The histologic type should be recorded. Intraoperative rupture ("surgical spill") is IC1; capsule ruptured before surgery or tumor on ovarian or fallopian tube surface is IC2; and positive peritoneal cytology with or without rupture is IC3. The new staging includes a revision of stage III patients; assignment to stage IIIA1 is based on spread to the retroperitoneal lymph nodes without intraperitoneal dissemination. Extension of tumor from omentum to spleen or liver (stage IIIC) should be differentiated from isolated parenchymal metastases (stage IVB). © 2015 American Cancer Society.

  8. Radiation sensitivity of human lung cancer cell lines

    International Nuclear Information System (INIS)

    Carmichael, J.; Degraff, W.G.; Gamson, J.; Russo, G.; Mitchell, J.B.; Gazdar, A.F.; Minna, J.D.; Levitt, M.L.

    1989-01-01

    X-Ray survival curves were determined using a panel of 17 human lung cancer cell lines, with emphasis on non-small cell lung cancer (NSCLC). In contrast to classic small cell lung cancer (SCLC) cell lines, NSCLC cell lines were generally less sensitive to radiation as evidenced by higher radiation survival curve extrapolation numbers, surviving fraction values following a 2Gy dose (SF2) and the mean inactivation dose values (D) values. The spectrum of in vitro radiation responses observed was similar to that expected in clinical practice, although mesothelioma was unexpectedly sensitive in vitro. Differences in radiosensitivity were best distinguished by comparison of SF2 values. Some NSCLC lines were relatively sensitive, and in view of this demonstrable variability in radiation sensitivity, the SF2 value may be useful for in vitro predictive assay testing of clinical specimens. (author)

  9. Epidermal growth factor receptor in primary human lung cancer

    International Nuclear Information System (INIS)

    Yu Xueyan; Hu Guoqiang; Tian Keli; Wang Mingyun

    1996-01-01

    Cell membranes were prepared from 12 human lung cancers for the study of the expression of epidermal growth factor receptors (EGFR). EGFR concentration was estimated by ligand binding studies using 125 I-radiolabeled EGF. The dissociation constants of the high affinity sites were identical, 1.48 nmol and 1.1 nmol in cancer and normal lung tissues, the EGFR contents were higher in lung cancer tissues (range: 2.25 to 19.39 pmol·g -1 membrane protein) than that in normal tissues from the same patients (range: 0.72 to 7.43 pmol·g -1 membrane protein). These results suggest that EGF and its receptor may play a role in the regulatory mechanisms in the control of lung cellular growth and tumor promotion

  10. Distribution of Human papilloma virus genotypes in cervical cancer tissues

    Directory of Open Access Journals (Sweden)

    Stamenković M.

    2014-01-01

    Full Text Available Cervical cancer incidence and mortality rates in Serbia are among the highest in Europe and data on Human papilloma virus (HPV type distribution are scarce. The aim of this study was to determine the prevalence of HPV types in archival specimens of cervical cancer tissues of women in the Serbian population. A total of 45 paraffin-embedded tissue samples of cervical carcinoma were used in this study. The procedure included deparaffinization of tissue samples, DNA extraction, PCR, gel electrophoresis and HPV genotyping by direct sequencing. HPV was detected in 32 samples (71%. Genotyping revealed the presence of 6 high-risk HPV types 16, 18, 33, 45, 53 and 58, where HPV type 16 was the most prevalent type (73.7%. The results of this study and further studies will provide more detailed information about HPV genotype distribution and may contribute to the formulation of national guidelines for the prevention of cervical cancer. [175073

  11. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  12. Application of SVM classifier in thermographic image classification for early detection of breast cancer

    Science.gov (United States)

    Oleszkiewicz, Witold; Cichosz, Paweł; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał

    2016-09-01

    This article presents the application of machine learning algorithms for early detection of breast cancer on the basis of thermographic images. Supervised learning model: Support vector machine (SVM) and Sequential Minimal Optimization algorithm (SMO) for the training of SVM classifier were implemented. The SVM classifier was included in a client-server application which enables to create a training set of examinations and to apply classifiers (including SVM) for the diagnosis and early detection of the breast cancer. The sensitivity and specificity of SVM classifier were calculated based on the thermographic images from studies. Furthermore, the heuristic method for SVM's parameters tuning was proposed.

  13. Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations

    Science.gov (United States)

    2014-01-01

    Introduction Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. Methods An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). Results The original training cohort reached a statistically significant difference (p risk groups. Conclusions Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments. PMID:24996446

  14. Refining Time-Activity Classification of Human Subjects Using the Global Positioning System.

    Science.gov (United States)

    Hu, Maogui; Li, Wei; Li, Lianfa; Houston, Douglas; Wu, Jun

    2016-01-01

    Detailed spatial location information is important in accurately estimating personal exposure to air pollution. Global Position System (GPS) has been widely used in tracking personal paths and activities. Previous researchers have developed time-activity classification models based on GPS data, most of them were developed for specific regions. An adaptive model for time-location classification can be widely applied to air pollution studies that use GPS to track individual level time-activity patterns. Time-activity data were collected for seven days using GPS loggers and accelerometers from thirteen adult participants from Southern California under free living conditions. We developed an automated model based on random forests to classify major time-activity patterns (i.e. indoor, outdoor-static, outdoor-walking, and in-vehicle travel). Sensitivity analysis was conducted to examine the contribution of the accelerometer data and the supplemental spatial data (i.e. roadway and tax parcel data) to the accuracy of time-activity classification. Our model was evaluated using both leave-one-fold-out and leave-one-subject-out methods. Maximum speeds in averaging time intervals of 7 and 5 minutes, and distance to primary highways with limited access were found to be the three most important variables in the classification model. Leave-one-fold-out cross-validation showed an overall accuracy of 99.71%. Sensitivities varied from 84.62% (outdoor walking) to 99.90% (indoor). Specificities varied from 96.33% (indoor) to 99.98% (outdoor static). The exclusion of accelerometer and ambient light sensor variables caused a slight loss in sensitivity for outdoor walking, but little loss in overall accuracy. However, leave-one-subject-out cross-validation showed considerable loss in sensitivity for outdoor static and outdoor walking conditions. The random forests classification model can achieve high accuracy for the four major time-activity categories. The model also performed well

  15. Fenton reaction induced cancer in wild type rats recapitulates genomic alterations observed in human cancer.

    Directory of Open Access Journals (Sweden)

    Shinya Akatsuka

    Full Text Available Iron overload has been associated with carcinogenesis in humans. Intraperitoneal administration of ferric nitrilotriacetate initiates a Fenton reaction in renal proximal tubules of rodents that ultimately leads to a high incidence of renal cell carcinoma (RCC after repeated treatments. We performed high-resolution microarray comparative genomic hybridization to identify characteristics in the genomic profiles of this oxidative stress-induced rat RCCs. The results revealed extensive large-scale genomic alterations with a preference for deletions. Deletions and amplifications were numerous and sometimes fragmented, demonstrating that a Fenton reaction is a cause of such genomic alterations in vivo. Frequency plotting indicated that two of the most commonly altered loci corresponded to a Cdkn2a/2b deletion and a Met amplification. Tumor sizes were proportionally associated with Met expression and/or amplification, and clustering analysis confirmed our results. Furthermore, we developed a procedure to compare whole genomic patterns of the copy number alterations among different species based on chromosomal syntenic relationship. Patterns of the rat RCCs showed the strongest similarity to the human RCCs among five types of human cancers, followed by human malignant mesothelioma, an iron overload-associated cancer. Therefore, an iron-dependent Fenton chemical reaction causes large-scale genomic alterations during carcinogenesis, which may result in distinct genomic profiles. Based on the characteristics of extensive genome alterations in human cancer, our results suggest that this chemical reaction may play a major role during human carcinogenesis.

  16. The Epidemiology of Human Papillomavirus Infection and Cervical Cancer

    Directory of Open Access Journals (Sweden)

    F. Xavier Bosch

    2007-01-01

    Full Text Available Cervical cancer has been recognized as a rare outcome of a common Sexually Transmitted Infection (STI. The etiologic association is restricted to a limited number of viral types of the family of the Human Papillomaviruses (HPVs. The association is causal in nature and under optimal testing systems, HPV DNA can be identified in all specimens of invasive cervical cancer. As a consequence, it has been claimed that HPV infection is a necessary cause of cervical cancer. The evidence is consistent worldwide and implies both the Squamous Cell Carcinomas (SCC, the adenocarcinomas and the vast majority (i.e. > 95% of the immediate precursors, namely High Grade Squamous Intraepithelial Lesions (HSIL/Cervical Intraepithelial Neoplasia 3 (CIN3/Carcinoma in situ. Co-factors that modify the risk among HPV DNA positive women include the use of oral contraceptives (OC for five or more years, smoking, high parity (five or more full term pregnancies and previous exposure to other sexually transmitted diseases such as Chlamydia Trachomatis (CT and Herpes Simplex Virus type 2 (HSV-2. Women exposed to the Human Immunodeficiency Virus (HIV are at high risk for HPV infection, HPV DNA persistency and progression of HPV lesions to cervical cancer.

  17. Prevention of human cancer by modulation of chronic inflammatory processes

    Energy Technology Data Exchange (ETDEWEB)

    Ohshima, Hiroshi [International Agency for Research on Cancer, 150 Cours Albert Thomas, 69372 Lyon Cedex 08 (France)]. E-mail: ohshima@iarc.fr; Tazawa, Hiroshi [International Agency for Research on Cancer, 150 Cours Albert Thomas, 69372 Lyon Cedex 08 (France); Sylla, Bakary S. [International Agency for Research on Cancer, 150 Cours Albert Thomas, 69372 Lyon Cedex 08 (France); Sawa, Tomohiro [International Agency for Research on Cancer, 150 Cours Albert Thomas, 69372 Lyon Cedex 08 (France)

    2005-12-11

    Chronic inflammation induced by biological, chemical and physical factors has been associated with increased risk of human cancer at various sites. Inflammation facilitates the initiation of normal cells and their growth and progression to malignancy through production of pro-inflammatory cytokines and diverse reactive oxygen and nitrogen species. These also activate signaling molecules involved in inflammation and carcinogenesis such as nuclear transcription factor (NF-{kappa}B), inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). Several chemopreventive agents act through inhibition of signaling pathways (e.g. NF-{kappa}B), inhibition of oxidant-generating enzymes (e.g. iNOS) and mediators of inflammation (e.g. COX-2), scavenging reactive oxygen and nitrogen species, and modulation of xenobiotic-metabolizing enzymes (especially phase II enzyme induction). Some anti-inflammatory drugs have been tested in clinical trials to prevent human cancer at several sites. Better understanding of the molecular mechanisms by which chronic inflammation increases cancer risk will lead to further development of new strategies for cancer prevention at many sites.

  18. Frizzled Receptors as Potential Therapeutic Targets in Human Cancers

    Directory of Open Access Journals (Sweden)

    Chui-Mian Zeng

    2018-05-01

    Full Text Available Frizzled receptors (FZDs are a family of seven-span transmembrane receptors with hallmarks of G protein-coupled receptors (GPCRs that serve as receptors for secreted Wingless-type (WNT ligands in the WNT signaling pathway. Functionally, FZDs play crucial roles in regulating cell polarity, embryonic development, cell proliferation, formation of neural synapses, and many other processes in developing and adult organisms. In this review, we will introduce the basic structural features and review the biological function and mechanism of FZDs in the progression of human cancers, followed by an analysis of clinical relevance and therapeutic potential of FZDs. We will focus on the development of antibody-based and small molecule inhibitor-based therapeutic strategies by targeting FZDs for human cancers.

  19. Classification and Diagnostic Output Prediction of Cancer Using Gene Expression Profiling and Supervised Machine Learning Algorithms

    DEFF Research Database (Denmark)

    Yoo, C.; Gernaey, Krist

    2008-01-01

    importance in the projection (VIP) information of the DPLS method. The power of the gene selection method and the proposed supervised hierarchical clustering method is illustrated on a three microarray data sets of leukemia, breast, and colon cancer. Supervised machine learning algorithms thus enable...

  20. Prognostic classification with laboratory parameters or imaging techniques in small-cell lung cancer

    NARCIS (Netherlands)

    de Jong, Wouter K.; Fidler, Vaclav; Groen, Harry J. M.

    PURPOSE: Our aim in this study was to compare prognostic models based on laboratory tests with a model including imaging information in small-cell lung cancer. PATIENTS AND METHODS: A retrospective analysis was performed on 156 consecutive patients. Three existing models based on laboratory tests

  1. Towards a molecular classification of colorectal cancer: The role of BRAF

    Directory of Open Access Journals (Sweden)

    Alexandra eThiel

    2013-11-01

    Full Text Available Different genetic aberrations of BRAF have been reported in various malignancies. BRAF is member of the RAS/RAF/MEK/ERK pathway and constitutive activity of this pathway can lead to increased cellular growth, invasion, and metastasis. The most common activating BRAF mutation in colorectal cancer is the V600E mutation, which is present in 5-15% of all tumors, and up to 80% of tumors with high microsatellite instability harbor this mutation. BRAF mutation is associated with proximal location, higher age, female gender, MSI-H, high grade, and mucinous histology, and is a marker of poor prognosis in colorectal cancer. The role of BRAF mutation as a predictive marker in respect of EGFR targeted treatments is controversial. BRAF V600 selective inhibitors have been approved for the treatment of V600 mutation positive metastatic melanoma, but the response rates in colorectal cancer are poor. This might be due to innate resistance mechanisms of colorectal cancers against the treatment solely targeting BRAF. To overcome resistance the combination of treatments, simultaneous inhibition of BRAF and MEK or PI3K/mTOR, might emerge as a successful therapeutic concept.

  2. Studies of rhodamine-123: effect on rat prostate cancer and human prostate cancer cells in vitro.

    Science.gov (United States)

    Arcadi, J A; Narayan, K S; Techy, G; Ng, C P; Saroufeem, R M; Jones, L W

    1995-06-01

    The effect of the lipophilic, cationic dye, Rhodamine-123 (Rh-123), on prostate cancer in rats, and on three tumor cell lines in vitro is reported here. The general toxicity of Rh-123 in mice has been found to be minimal. Lobund-Wistar (L-W) rats with the autochthonous prostate cancer of Pollard were treated for six doses with Rh-123 at a dose of 15 mg/kg subcutaneously every other day. Microscopic examination of the tumors revealed cellular and acinar destruction. The effectiveness of Rh-123 as a cytotoxic agent was tested by clonogenic and viability assays in vitro with three human prostate cancer cell lines. Severe (60-95%) growth inhibition was observed following Rh-123 exposure for 2-5 days at doses as low as 1.6 micrograms/ml in all three prostate cancer cell lines.

  3. Lnc2Cancer: a manually curated database of experimentally supported lncRNAs associated with various human cancers.

    Science.gov (United States)

    Ning, Shangwei; Zhang, Jizhou; Wang, Peng; Zhi, Hui; Wang, Jianjian; Liu, Yue; Gao, Yue; Guo, Maoni; Yue, Ming; Wang, Lihua; Li, Xia

    2016-01-04

    Lnc2Cancer (http://www.bio-bigdata.net/lnc2cancer) is a manually curated database of cancer-associated long non-coding RNAs (lncRNAs) with experimental support that aims to provide a high-quality and integrated resource for exploring lncRNA deregulation in various human cancers. LncRNAs represent a large category of functional RNA molecules that play a significant role in human cancers. A curated collection and summary of deregulated lncRNAs in cancer is essential to thoroughly understand the mechanisms and functions of lncRNAs. Here, we developed the Lnc2Cancer database, which contains 1057 manually curated associations between 531 lncRNAs and 86 human cancers. Each association includes lncRNA and cancer name, the lncRNA expression pattern, experimental techniques, a brief functional description, the original reference and additional annotation information. Lnc2Cancer provides a user-friendly interface to conveniently browse, retrieve and download data. Lnc2Cancer also offers a submission page for researchers to submit newly validated lncRNA-cancer associations. With the rapidly increasing interest in lncRNAs, Lnc2Cancer will significantly improve our understanding of lncRNA deregulation in cancer and has the potential to be a timely and valuable resource. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  4. Drug-selected human lung cancer stem cells: cytokine network, tumorigenic and metastatic properties.

    Directory of Open Access Journals (Sweden)

    Vera Levina

    2008-08-01

    Full Text Available Cancer stem cells (CSCs are thought to be responsible for tumor regeneration after chemotherapy, although direct confirmation of this remains forthcoming. We therefore investigated whether drug treatment could enrich and maintain CSCs and whether the high tumorogenic and metastatic abilities of CSCs were based on their marked ability to produce growth and angiogenic factors and express their cognate receptors to stimulate tumor cell proliferation and stroma formation.Treatment of lung tumor cells with doxorubicin, cisplatin, or etoposide resulted in the selection of drug surviving cells (DSCs. These cells expressed CD133, CD117, SSEA-3, TRA1-81, Oct-4, and nuclear beta-catenin and lost expression of the differentiation markers cytokeratins 8/18 (CK 8/18. DSCs were able to grow as tumor spheres, maintain self-renewal capacity, and differentiate. Differentiated progenitors lost expression of CD133, gained CK 8/18 and acquired drug sensitivity. In the presence of drugs, differentiation of DSCs was abrogated allowing propagation of cells with CSC-like characteristics. Lung DSCs demonstrated high tumorogenic and metastatic potential following inoculation into SCID mice, which supported their classification as CSCs. Luminex analysis of human and murine cytokines in sonicated lysates of parental- and CSC-derived tumors revealed that CSC-derived tumors contained two- to three-fold higher levels of human angiogenic and growth factors (VEGF, bFGF, IL-6, IL-8, HGF, PDGF-BB, G-CSF, and SCGF-beta. CSCs also showed elevated levels of expression of human VEGFR2, FGFR2, CXCR1, 2 and 4 receptors. Moreover, human CSCs growing in SCID mice stimulated murine stroma to produce elevated levels of angiogenic and growth factors.These findings suggest that chemotherapy can lead to propagation of CSCs and prevention of their differentiation. The high tumorigenic and metastatic potentials of CSCs are associated with efficient cytokine network production that may represent

  5. Resources for Precision Analysis of Human Breast Cancer

    Science.gov (United States)

    2000-08-01

    correlation chemistry are necessary to confirm this observation, the, is different between the in vitro and in vivo situations, pattern of expression is...Feunteun 44. Mandinova A, Atar D, Schafer BW, Spiess M, Aebi U, Heizmann C1 J, Schnitt S, Livingston DM: Location of BRCA1 in human breast and Distinct...with progression-free survival, in prostate cancer [20]. expression but strong staining by immunohisto-S • chemistry were positive by western blot

  6. Human Papillomavirus Genome Integration and Head and Neck Cancer.

    Science.gov (United States)

    Pinatti, L M; Walline, H M; Carey, T E

    2018-06-01

    We conducted a critical review of human papillomavirus (HPV) integration into the host genome in oral/oropharyngeal cancer, reviewed the literature for HPV-induced cancers, and obtained current data for HPV-related oral and oropharyngeal cancers. In addition, we performed studies to identify HPV integration sites and the relationship of integration to viral-host fusion transcripts and whether integration is required for HPV-associated oncogenesis. Viral integration of HPV into the host genome is not required for the viral life cycle and might not be necessary for cellular transformation, yet HPV integration is frequently reported in cervical and head and neck cancer specimens. Studies of large numbers of early cervical lesions revealed frequent viral integration into gene-poor regions of the host genome with comparatively rare integration into cellular genes, suggesting that integration is a stochastic event and that site of integration may be largely a function of chance. However, more recent studies of head and neck squamous cell carcinomas (HNSCCs) suggest that integration may represent an additional oncogenic mechanism through direct effects on cancer-related gene expression and generation of hybrid viral-host fusion transcripts. In HNSCC cell lines as well as primary tumors, integration into cancer-related genes leading to gene disruption has been reported. The studies have shown that integration-induced altered gene expression may be associated with tumor recurrence. Evidence from several studies indicates that viral integration into genic regions is accompanied by local amplification, increased expression in some cases, interruption of gene expression, and likely additional oncogenic effects. Similarly, reported examples of viral integration near microRNAs suggest that altered expression of these regulatory molecules may also contribute to oncogenesis. Future work is indicated to identify the mechanisms of these events on cancer cell behavior.

  7. Induction of apoptosis by eugenol in human breast cancer cells

    International Nuclear Information System (INIS)

    Vidhya, N.; Niranjali Devaraj, S.

    2011-01-01

    In the present study, potential anticancer effect of eugenol on inhibition of cell proliferation and induction of apoptosis in human MCF-7 breast cancer cells was investigated. Induction of cell death by eugenol was evaluated following MTT assay and monitoring lactate dehydrogenase released into the culture medium for cell viability and cytotoxicity, giemsa staining for morphological alterations, fluorescence microscopy analysis of cells using ethidium bromide and acridine orange and quantitation of DNA fragments for induction of apoptosis. Effect of eugenol on intracellular redox status of the human breast cancer cells was assessed by determining the level of glutathione and lipid peroxidation products (TBARS). Eugenol treatment inhibited the growth and proliferation of human MCF-7 breast cancer cells through induction of cell death, which was dose and time dependent. Microscopic examination of eugenol treated cells showed cell shrinkage, membrane blebbing and apoptotic body formation. Further, eugenol treatment also depleted the level of intracellular glutathione and increased the level of lipid peroxidation. The dose dependent increase in the percentage of apoptotic cells and DNA fragments suggested that apoptosis was involved in eugenol induced cell death and apoptosis might have played a role in the chemopreventive action of eugenol. (author)

  8. Imaging Proteolysis by Living Human Breast Cancer Cells

    Directory of Open Access Journals (Sweden)

    Mansoureh Sameni

    2000-01-01

    Full Text Available Malignant progression is accompanied by degradation of extracellular matrix proteins. Here we describe a novel confocal assay in which we can observe proteolysis by living human breast cancer cells (BT20 and BT549 through the use of quenchedfluorescent protein substrates. Degradation thus was imaged, by confocal optical sectioning, as an accumulation of fluorescent products. With the BT20 cells, fluorescence was localized to pericellular focal areas that coincide with pits in the underlying matrix. In contrast, fluorescence was localized to intracellular vesicles in the BT549 cells, vesicles that also label for lysosomal markers. Neither intracellular nor pericellular fluorescence was observed in the BT549 cells in the presence of cytochalasin B, suggesting that degradation occurred intracellularly and was dependent on endocytic uptake of substrate. In the presence of a cathepsin 13-selective cysteine protease inhibitor, intracellular fluorescence was decreased ~90% and pericellular fluorescence decreased 67% to 96%, depending on the protein substrate. Matrix metallo protease inhibitors reduced pericellular fluorescence ~50%, i.e., comparably to a serine and a broad spectrum cysteine protease inhibitor. Our results suggest that: 1 a proteolytic cascade participates in pericellular digestion of matrix proteins by living human breast cancer cells, and 2 the cysteine protease cathepsin B participates in both pericellular and intracellular digestion of matrix proteins by living human breast cancer cells.

  9. New classification of operators' human errors at overseas nuclear power plants and preparation of easy-to-use case sheets

    International Nuclear Information System (INIS)

    Takagawa, Kenichi

    2004-01-01

    At nuclear power plants, plant operators examine other human error cases, including those that occurred at other plants, so that they can learn from such experiences and avoid making similar errors again. Although there is little data available on errors made at domestic plants, nuclear operators in foreign countries are reporting even minor irregularities and signs of faults, and a large amount of data on human errors at overseas plants could be collected and examined. However, these overseas data have not been used effectively because most of them are poorly organized or not properly classified and are often hard to understand. Accordingly, we carried out a study on the cases of human errors at overseas power plants in order to help plant personnel clearly understand overseas experiences and avoid repeating similar errors, The study produced the following results, which were put to use at nuclear power plants and other facilities. (1) ''One-Point-Advice'' refers to a practice where a leader gives pieces of advice to his team of operators in order to prevent human errors before starting work. Based on this practice and those used in the aviation industry, we have developed a new method of classifying human errors that consists of four basic actions and three applied actions. (2) We used this new classification method to classify human errors made by operators at overseas nuclear power plants. The results show that the most frequent errors caused not by operators themselves but due to insufficient team monitoring, for which superiors and/or their colleagues were responsible. We therefore analyzed and classified possible factors contributing to insufficient team monitoring, and demonstrated that the frequent errors have also occurred at domestic power plants. (3) Using the new classification formula, we prepared a human error case sheets that is easy for plant personnel to understand. The sheets are designed to make data more understandable and easier to remember

  10. University Students' Knowledge and Attitudes Regarding Cervical Cancer, Human Papillomavirus, and Human Papillomavirus Vaccines in Turkey

    Science.gov (United States)

    Koç, Zeliha

    2015-01-01

    Objectives: The current descriptive study aimed to determine university students' knowledge and attitudes regarding cervical cancer, human papillomavirus (HPV), and HPV vaccines in Turkey. Participants: A total of 800 students participated. Methods: This study was carried out between September 1, 2012, and October 30, 2012, in 8 female…

  11. A multigene mutation classification of 468 colorectal cancers reveals a prognostic role for APC

    Science.gov (United States)

    Schell, Michael J.; Yang, Mingli; Teer, Jamie K.; Lo, Fang Yin; Madan, Anup; Coppola, Domenico; Monteiro, Alvaro N. A.; Nebozhyn, Michael V.; Yue, Binglin; Loboda, Andrey; Bien-Willner, Gabriel A.; Greenawalt, Danielle M.; Yeatman, Timothy J.

    2016-01-01

    Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinicopathologic staging for decades. There is a need to stratify subpopulations of CRC on a molecular basis to better predict outcome and assign therapies. Here we report targeted exome-sequencing of 1,321 cancer-related genes on 468 tumour specimens, which identified a subset of 17 genes that best classify CRC, with APC playing a central role in predicting overall survival. APC may assume 0, 1 or 2 truncating mutations, each with a striking differential impact on survival. Tumours lacking any APC mutation carry a worse prognosis than single APC mutation tumours; however, two APC mutation tumours with mutant KRAS and TP53 confer the poorest survival among all the subgroups examined. Our study demonstrates a prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC. PMID:27302369

  12. Regulations of enzymes in animals: effects of developmental processes, cancer, and radiation. Final report. [Analysis of enzymes in human cancer tissue

    Energy Technology Data Exchange (ETDEWEB)

    Knox, W.E.

    1978-09-01

    Low grade tumors of various origins are chemically very different. High grade tumors, whatever their origin, are chemically very similar to one another and to embryonic tissues. Analyses of human tumor tissues and sera from cancer patients were conducted for two new groups of enzymes expected to be informative about the physiological state of the tissue. The enzymes measured in tumors and sera were chosen because they were characteristic of fetal tissues and high grade neoplasms in rats, and could, therefore, be expected to exist in human cancers (and fetuses) and to predominate more in those of higher grade malignancies. Results indicated that the classification of enzymes (or isozymes) as fetal or adult types in the rat could be extended to man. Human cancers do contain most of the enzymes expected, and lack others, as expected. Analyses of the same enzymes in sera gave less clear results. It was recognized at the outset that no simple proportionality existed between tissue and serum levels. The tendency existed in cancer patients to have in serum elevated amounts of those enzymes characteristic of undifferentiated tissues. The abnormalities in a specific patient are conditioned by his physiological state, by the grade of his tumor, and by the mass of tumor present. The tumor mass had a very significant effect, so that monitoring this tumor burden by chemical means should be quite possible. The latest work focused on particular enzymes that have not previously been measured in cancer patients. These studies concentrated on pyrroline-5-carboxylate (P-5-C) reductase and its inhibition and on lysosomal glucosidases and phosphatases. Both groups are relatively high in fetal and neoplastic tissues.

  13. Treatment deintensification in human papillomavirus-positive oropharynx cancer: Outcomes from the National Cancer Data Base.

    Science.gov (United States)

    Cheraghlou, Shayan; Yu, Phoebe K; Otremba, Michael D; Park, Henry S; Bhatia, Aarti; Zogg, Cheryl K; Mehra, Saral; Yarbrough, Wendell G; Judson, Benjamin L

    2018-02-15

    The growing epidemic of human papillomavirus-positive (HPV+) oropharyngeal cancer and the favorable prognosis of this disease etiology have led to a call for deintensified treatment for some patients with HPV+ cancers. One of the proposed methods of treatment deintensification is the avoidance of chemotherapy concurrent with definitive/adjuvant radiotherapy. To the authors' knowledge, the safety of this form of treatment de-escalation is unknown and the current literature in this area is sparse. The authors investigated outcomes after various treatment combinations stratified by American Joint Committee on Cancer (AJCC) eighth edition disease stage using patients from the National Cancer Data Base. A retrospective study of 4443 patients with HPV+ oropharyngeal cancer in the National Cancer Data Base was conducted. Patients were stratified into AJCC eighth edition disease stage groups. Multivariate Cox regressions as well as univariate Kaplan-Meier analyses were conducted. For patients with stage I disease, treatment with definitive radiotherapy was associated with diminished survival compared with chemoradiotherapy (hazard ratio [HR], 1.798; P = .029), surgery with adjuvant radiotherapy (HR, 2.563; P = .002), or surgery with adjuvant chemoradiotherapy (HR, 2.427; P = .001). For patients with stage II disease, compared with treatment with chemoradiotherapy, patients treated with a single-modality (either surgery [HR, 2.539; P = .009] or radiotherapy [HR, 2.200; P = .030]) were found to have poorer survival. Among patients with stage III disease, triple-modality therapy was associated with improved survival (HR, 0.518; P = .024) compared with treatment with chemoradiotherapy. Deintensification of treatment from chemoradiotherapy to radiotherapy or surgery alone in cases of HPV+ AJCC eighth edition stage I or stage II disease may compromise patient safety. Treatment intensification to triple-modality therapy for patients with stage III disease may improve survival in

  14. Towards automated human gait disease classification using phase space representation of intrinsic mode functions

    Science.gov (United States)

    Pratiher, Sawon; Patra, Sayantani; Pratiher, Souvik

    2017-06-01

    A novel analytical methodology for segregating healthy and neurological disorders from gait patterns is proposed by employing a set of oscillating components called intrinsic mode functions (IMF's). These IMF's are generated by the Empirical Mode Decomposition of the gait time series and the Hilbert transformed analytic signal representation forms the complex plane trace of the elliptical shaped analytic IMFs. The area measure and the relative change in the centroid position of the polygon formed by the Convex Hull of these analytic IMF's are taken as the discriminative features. Classification accuracy of 79.31% with Ensemble learning based Adaboost classifier validates the adequacy of the proposed methodology for a computer aided diagnostic (CAD) system for gait pattern identification. Also, the efficacy of several potential biomarkers like Bandwidth of Amplitude Modulation and Frequency Modulation IMF's and it's Mean Frequency from the Fourier-Bessel expansion from each of these analytic IMF's has been discussed for its potency in diagnosis of gait pattern identification and classification.

  15. Carcinoma de mama: novos conceitos na classificação Breast cancer: new concepts in classification

    Directory of Open Access Journals (Sweden)

    Daniella Serafin Couto Vieira

    2008-01-01

    and the basis for and improved breast cancer molecular taxonomy. Another important implication is that genetic profiling may lead to the identification of new target for therapy and better predictive markers are needed to guide difficult treatment decisions. Additionally, the current pathology classification system is suboptimal, since patients with identical tumor types and stage of disease present different responses to therapy and different overall outcomes. Basal breast tumor represents one of the most intriguing subtypes and is frequently associated with poor prognosis and absence of putative therapeutic targets. Then, the purpose of this review was to resume the most recent knowledge about the breast carcinoma classification and characterization.

  16. Validation of the RTOG recursive partitioning analysis (RPA) classification for small-cell lung cancer-only brain metastases

    International Nuclear Information System (INIS)

    Videtic, Gregory M.M.; Adelstein, David J.; Mekhail, Tarek M.; Rice, Thomas W.; Stevens, Glen H.J.; Lee, S.-Y.; Suh, John H.

    2007-01-01

    Purpose: Radiation Therapy Oncology Group (RTOG) developed a prognostic classification based on a recursive partitioning analysis (RPA) of patient pretreatment characteristics from three completed brain metastases randomized trials. Clinical trials for patients with brain metastases generally exclude small-cell lung cancer (SCLC) cases. We hypothesize that the RPA classes are valid in the setting of SCLC brain metastases. Methods and Materials: A retrospective review of 154 SCLC patients with brain metastases treated between April 1983 and May 2005 was performed. RPA criteria used for class assignment were Karnofsky performance status (KPS), primary tumor status (PT), presence of extracranial metastases (ED), and age. Results: Median survival was 4.9 months, with 4 patients (2.6%) alive at analysis. Median follow-up was 4.7 months (range, 0.3-40.3 months). Median age was 65 (range, 42-85 years). Median KPS was 70 (range, 40-100). Number of patients with controlled PT and no ED was 20 (13%) and with ED, 27 (18%); without controlled PT and ED, 34 (22%) and with ED, 73 (47%). RPA class distribution was: Class I: 8 (5%); Class II: 96 (62%); Class III: 51 (33%). Median survivals (in months) by RPA class were: Class I: 8.6; Class II: 4.2; Class III: 2.3 (p = 0.0023). Conclusions: Survivals for SCLC-only brain metastases replicate the results from the RTOG RPA classification. These classes are therefore valid for brain metastases from SCLC, support the inclusion of SCLC patients in future brain metastases trials, and may also serve as a basis for historical comparisons

  17. Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations.

    Science.gov (United States)

    Wang, Dong-Yu; Done, Susan J; Mc Cready, David R; Leong, Wey L

    2014-07-04

    Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). The original training cohort reached a statistically significant difference (p value of the triad classification was reproduced in the second independent internal cohort and the new external validation cohort. CMTC achieved even higher prognostic significance when all available patients were analyzed (n = 4,851). Oncogenic pathways Myc, E2F1, Ras and β-catenin were again implicated in the high-risk groups. Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments.

  18. A joint model of persistent human papillomavirus infection and cervical cancer risk: Implications for cervical cancer screening

    OpenAIRE

    Katki, Hormuzd A.; Cheung, Li C.; Fetterman, Barbara; Castle, Philip E.; Sundaram, Rajeshwari

    2015-01-01

    New cervical cancer screening guidelines in the US and many European countries recommend that women get tested for human papillomavirus (HPV). To inform decisions about screening intervals, we calculate the increase in precancer/cancer risk per year of continued HPV infection. However, both time to onset of precancer/cancer and time to HPV clearance are interval-censored, and onset of precancer/cancer strongly informatively censors HPV clearance. We analyze this bivariate informatively interv...

  19. Cancer classification through filtering progressive transductive support vector machine based on gene expression data

    Science.gov (United States)

    Lu, Xinguo; Chen, Dan

    2017-08-01

    Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

  20. c-Myc-Dependent Cell Competition in Human Cancer Cells.

    Science.gov (United States)

    Patel, Manish S; Shah, Heta S; Shrivastava, Neeta

    2017-07-01

    Cell Competition is an interaction between cells for existence in heterogeneous cell populations of multicellular organisms. This phenomenon is involved in initiation and progression of cancer where heterogeneous cell populations compete directly or indirectly for the survival of the fittest based on differential gene expression. In Drosophila, cells having lower dMyc expression are eliminated by cell competition through apoptosis when present in the milieu of cells having higher dMyc expression. Thus, we designed a study to develop c-Myc (human homolog) dependent in vitro cell competition model of human cancer cells. Cells with higher c-Myc were transfected with c-myc shRNA to prepare cells with lower c-Myc and then co-cultured with the same type of cells having a higher c-Myc in equal ratio. Cells with lower c-Myc showed a significant decrease in numbers when compared with higher c-Myc cells, suggesting "loser" and "winner" status of cells, respectively. During microscopy, engulfment of loser cells by winner cells was observed with higher expression of JNK in loser cells. Furthermore, elimination of loser cells was prevented significantly, when co-cultured cells were treated with the JNK (apoptosis) inhibitor. Above results indicate elimination of loser cells in the presence of winner cells by c-Myc-dependent mechanisms of cell competition in human cancer cells. This could be an important mechanism in human tumors where normal cells are eliminated by c-Myc-overexpressed tumor cells. J. Cell. Biochem. 118: 1782-1791, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  1. Human papillomavirus detection in paraffin-embedded colorectal cancer tissues.

    Science.gov (United States)

    Tanzi, Elisabetta; Bianchi, Silvia; Frati, Elena R; Amicizia, Daniela; Martinelli, Marianna; Bragazzi, Nicola L; Brisigotti, Maria Pia; Colzani, Daniela; Fasoli, Ester; Zehender, Gianguglielmo; Panatto, Donatella; Gasparini, Roberto

    2015-01-01

    Human papillomavirus (HPV) has a well-recognized aetiological role in the development of cervical cancer and other anogenital tumours. Recently, an association between colorectal cancer and HPV infection has been suggested, although this is still controversial. This study aimed at detecting and characterizing HPV infection in 57 paired biopsies from colorectal cancers and adjacent intact tissues using a degenerate PCR approach. All amplified fragments were genotyped by means of sequencing. Overall, HPV prevalence was 12.3 %. In particular, 15.8 % of tumour tissues and 8.8 % of non-cancerous tissue samples were HPV DNA-positive. Of these samples, 85.7 % were genotyped successfully, with 41.7 % of sequences identifying four genotypes of the HR (high oncogenic risk) clade Group 1; the remaining 58.3 % of HPV-genotyped specimens had an unclassified β-HPV. Examining additional cases and analysing whole genomes will help to outline the significance of these findings.

  2. PIXE analysis of cancer-afflicted human bladder

    Energy Technology Data Exchange (ETDEWEB)

    Raju, G.J. Naga; Sarita, P.; Kumar, M. Ravi [Department of Physics, Institute of Technology, GITAM University, Visakhapatnam (India); Reddy, S. Bhuloka [Swami Jnanananda Laboratories for Nuclear Research, Andhra University, Visakhapatnam (India)

    2013-07-01

    Full text: The proton induced x-ray emission (PIXE) technique was used for analysis of trace elements in small quantities of biological samples. Both the biological samples of normal and cancer-afflicted human bladder tissues were studied. The present experiment was performed using a 3 MV pelletron accelerator at the Institute of Physics in Bhubaneswar, India. A proton beam of 3 MeV energy was used to excite the samples. NIST SRM 1577b Bovine Liver Tissue was used as external standards for the determination of trace element concentration in the biological tissue samples. The elements CI, K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, and Se were identified and their concentrations were estimated. The concentrations of Ti and Zn are lower (p < 0.005) and that of Cr, Mn, Fe, Ni, and Cu are significantly higher (p < 0.001) in cancerous tissues than that in normal tissues. The deficiency or excess of different trace elements observed in the cancer tissues relative to the normal tissues of bladder are correlated to the pathology of cancer. (author)

  3. Breast Cancer Mortality In Brazil: Correlation With Human Development Index

    Directory of Open Access Journals (Sweden)

    Mara Rejane Barroso Barcelos

    2017-01-01

    Full Text Available Background: Mortality from breast cancer decreased in high-income countries, while countries with middle and low incomes as Brazil still has upward trend. However, large geographical variations among the federal units are observed in the country. The aim of the study was to evaluate the trend of specific mortality from breast cancer in women over 20 years old years among different states of Brazil from 1996 to 2012.  Methods and Findings: Ecological study, using linear regression model for temporal analysis of specific mortality coefficient from malignant neoplasm of breast. We also checked the degree of its correlation with the HDI for the states of Brazil during the stated period. There was an increase in the specific mortality rate for malignant neoplasm of the breast in order of 33%, with range from 23.2 to 30.8 / 100,000 inhabitants. The states with the highest human development HDI in 2010, showed the largest specific mortality rates of breast cancer. Conclusion: Taking the trends of mortality from cancer an important role, this study confirms the need for improvements in mammography coverage, following radiological lesions suspected and access to appropriate therapy.

  4. Zinc in human prostate gland. Normal, hyperplastic and cancerous

    International Nuclear Information System (INIS)

    Zaichick, V.Ye.; Sviridova, T.V.; Zaichick, S.V.

    1997-01-01

    Zinc concentration in a prostate gland is much higher than that in other human tissues. Data about zinc changes for different prostate diseases are limited and greatly contradictory. Zinc content was determined for biopsy and resected materials of transrectal puncture tissues from benign prostate hyperplasia (BPH) and prostate cancer. There were 109 patients (50 BPH and 59 cancer) available for the present study. Control group consisted of 37 intact glands of men died an unexpected death (accident, murder, acute cardiac insufficiency, etc.). All materials studied were divided into two parts. One of them was morphologically examined, while another one was subjected to zinc analysis by INAA. Zinc contents (M ± SE) of normal, benign hyperplastic and cancerous prostate glands were found to be 1018 ± 124, 1142 ± 77, and 146 ± 10 μg/g dry tissue, respectively. It was shown that zinc assessments in the materials of transrectal puncture biopsy of indurated prostate sites can be used as an additional test for differential diagnostics of BPH and cancer. Accuracy, sensitivity and specificity of the test are 98 ± 2%. (author)

  5. Collection and classification of human error and human reliability data from Indian nuclear power plants for use in PSA

    International Nuclear Information System (INIS)

    Subramaniam, K.; Saraf, R.K.; Sanyasi Rao, V.V.S.; Venkat Raj, V.; Venkatraman, R.

    2000-01-01

    Complex systems such as NPPs involve a large number of Human Interactions (HIs) in every phase of plant operations. Human Reliability Analysis (HRA) in the context of a PSA, attempts to model the HIs and evaluate/predict their impact on safety and reliability using human error/human reliability data. A large number of HRA techniques have been developed for modelling and integrating HIs into PSA but there is a significant lack of HAR data. In the face of insufficient data, human reliability analysts have had to resort to expert judgement methods in order to extend the insufficient data sets. In this situation, the generation of data from plant operating experience assumes importance. The development of a HRA data bank for Indian nuclear power plants was therefore initiated as part of the programme of work on HRA. Later, with the establishment of the coordinated research programme (CRP) on collection of human reliability data and use in PSA by IAEA in 1994-95, the development was carried out under the aegis of the IAEA research contract No. 8239/RB. The work described in this report covers the activities of development of a data taxonomy and a human error reporting form (HERF) based on it, data structuring, review and analysis of plant event reports, collection of data on human errors, analysis of the data and calculation of human error probabilities (HEPs). Analysis of plant operating experience does yield a good amount of qualitative data but obtaining quantitative data on human reliability in the form of HEPs is seen to be more difficult. The difficulties have been highlighted and some ways to bring about improvements in the data situation have been discussed. The implementation of a data system for HRA is described and useful features that can be incorporated in future systems are also discussed. (author)

  6. Inflammation, Adenoma and Cancer: Objective Classification of Colon Biopsy Specimens with Gene Expression Signature

    Directory of Open Access Journals (Sweden)

    Orsolya Galamb

    2008-01-01

    Full Text Available Gene expression analysis of colon biopsies using high-density oligonucleotide microarrays can contribute to the understanding of local pathophysiological alterations and to functional classification of adenoma (15 samples, colorectal carcinomas (CRC (15 and inflammatory bowel diseases (IBD (14. Total RNA was extracted, amplified and biotinylated from frozen colonic biopsies. Genome-wide gene expression profile was evaluated by HGU133plus2 microarrays and verified by RT-PCR. We applied two independent methods for data normalization and used PAM for feature selection. Leave one-out stepwise discriminant analysis was performed. Top validated genes included collagenIVα1, lipocalin-2, calumenin, aquaporin-8 genes in CRC; CD44, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; and lipocalin-2, ubiquitin D and IFITM2 genes in IBD. Best differentiating markers between Ulcerative colitis and Crohn's disease were cyclin-G2; tripartite motif-containing-31; TNFR shedding aminopeptidase regulator-1 and AMICA. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes (indoleamine-pyrrole-2,3-dioxygenase, ectodermal-neural cortex, TIMP3, fucosyltransferase-8, collectin sub-family member 12, carboxypeptidase D, and transglutaminase-2. Using routine biopsy samples we successfully performed whole genomic microarray analysis to identify discriminative signatures. Our results provide further insight into the pathophysiological background of colonic diseases. The results set up data warehouse which can be mined further.

  7. Pattern Recognition Approaches for Breast Cancer DCE-MRI Classification: A Systematic Review.

    Science.gov (United States)

    Fusco, Roberta; Sansone, Mario; Filice, Salvatore; Carone, Guglielmo; Amato, Daniela Maria; Sansone, Carlo; Petrillo, Antonella

    2016-01-01

    We performed a systematic review of several pattern analysis approaches for classifying breast lesions using dynamic, morphological, and textural features in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Several machine learning approaches, namely artificial neural networks (ANN), support vector machines (SVM), linear discriminant analysis (LDA), tree-based classifiers (TC), and Bayesian classifiers (BC), and features used for classification are described. The findings of a systematic review of 26 studies are presented. The sensitivity and specificity are respectively 91 and 83 % for ANN, 85 and 82 % for SVM, 96 and 85 % for LDA, 92 and 87 % for TC, and 82 and 85 % for BC. The sensitivity and specificity are respectively 82 and 74 % for dynamic features, 93 and 60 % for morphological features, 88 and 81 % for textural features, 95 and 86 % for a combination of dynamic and morphological features, and 88 and 84 % for a combination of dynamic, morphological, and other features. LDA and TC have the best performance. A combination of dynamic and morphological features gives the best performance.

  8. Effect of primarily cultured human lung cancer-associated fibroblasts on radiosensitivity of lung cancer cells

    International Nuclear Information System (INIS)

    Ji Xiaoqin; Ji Jiang; Chen Yongbing; Shan Fang; Lu Xueguan

    2014-01-01

    Objective: To investigate the effect of human lung cancer-associated fibroblasts (CAF) on the radiosensitivity of lung cancer cells when CAF is placed in direct contact co-culture with lung cancer cells. Methods: Human lung CAF was obtained from fresh human lung adenocarcinoma tissue specimens by primary culture and subculture and was then identified by immunofluorescence staining. The CAF was placed in direct contact co-culture with lung cancer A 549 and H 1299 cells, and the effects of CAF on the radiosensitivity of A 549 and H 1299 cells were evaluated by colony-forming assay. Results: The human lung CAF obtained by adherent culture could stably grow and proliferate, and it had specific expression of α-smooth muscle actin, vimentin, and fibroblast activation protein,but without expression of cytokeratin-18. The plating efficiency (PE, %) of A 549 cells at 0 Gy irradiation was (20.0 ± 3.9)% when cultured alone versus (32.3 ± 5.5)% when co-cultured with CAF (t=3.16, P<0.05), and the PE of H 1299 cells at 0 Gy irradiation was (20.6 ± 3.1)% when cultured alone versus (35.2 ± 2.3)% when co-cultured with CAF (t=6.55, P<0.05). The cell survival rate at 2 Gy irradiation (SF 2 ) of A 549 cells was 0.727 ±0.061 when cultured alone versus 0.782 ± 0.089 when co-cultured with CAF (t=0.88, P>0.05), and the SF 2 of H 1299 cells was 0.692 ±0.065 when cultured alone versus 0.782 ± 0.037 when co-cultured with CAF (t=2.08, P>0.05). The protection enhancement ratios of human lung CAF for A 549 cells and H 1299 cells were 1.29 and 1.25, respectively. Conclusions: Human lung CAF reduces the radiosensitivity of lung cancer cells when placed in direct contact co-culture with them, and the radioprotective effect may be attributed to CAF promoting the proliferation of lung cancer cells. (authors)

  9. Differential expression of carbohydrate antigen 19-9 in human colorectal cancer: A comparison with colon and rectal cancers

    Science.gov (United States)

    ZHANG, SHUAI; CHEN, YIJUN; ZHU, ZHANMENG; DING, YUNLONG; REN, SHUANGYI; ZUO, YUNFEI

    2013-01-01

    Colorectal cancer is one of the leading causes of cancer-related mortality, being the third most commonly diagnosed cancer among men and the second among women. Accumulating evidence regarding carbohydrate antigen (CA) demonstrated that tumor-associated antigens are clinically useful for the diagnosis, staging and monitoring of human gastrointestinal cancers, particularly colorectal cancer. There has been an extensive investigation for sensitive and specific markers of this disease. Currently, the gastrointestinal cancer-associated carbohydrate antigen 19-9 (CA19-9) is the most widely applied tumor marker in cancer diagnosis. Despite a similar etiology and cancer incidence rates, there are anatomical and clinical differences between colon and rectal cancer, as well as differences regarding tumor progression and adjuvant treatments. To investigate whether CA19-9 is differentially expressed between colon and rectal cancer, we conducted a differential analysis of serum CA19-9 levels among 227 cases of colorectal cancer, analyzing gender, age, Dukes’ stage and distant metastasis for human colon and rectal cancer as a single entity, separately and as matched pairs. We demonstrated that the serum CA19-9 levels in colorectal cancer were upregulated in advanced stages with distant metastasis. By contrast, the serum CA19-9 levels in colon cancer displayed a differential and upregulated behavior in advanced stages with distant metastasis. By analyzing as matched pairs, the upregulated serum CA19-9 levels in rectal cancer during the early stages without distant metastasis further supported our hypothesis that the expression of CA19-9 displays a site-specific differential behavior. The integrative analysis suggested a significant difference between human colon and rectal cancer, justifying individualized therapy for these two types of cancer. PMID:24649295

  10. Classification of Breast Cancer Resistant Protein (BCRP) Inhibitors and Non-Inhibitors Using Machine Learning Approaches.

    Science.gov (United States)

    Belekar, Vilas; Lingineni, Karthik; Garg, Prabha

    2015-01-01

    The breast cancer resistant protein (BCRP) is an important transporter and its inhibitors play an important role in cancer treatment by improving the oral bioavailability as well as blood brain barrier (BBB) permeability of anticancer drugs. In this work, a computational model was developed to predict the compounds as BCRP inhibitors or non-inhibitors. Various machine learning approaches like, support vector machine (SVM), k-nearest neighbor (k-NN) and artificial neural network (ANN) were used to develop the models. The Matthews correlation coefficients (MCC) of developed models using ANN, k-NN and SVM are 0.67, 0.71 and 0.77, and prediction accuracies are 85.2%, 88.3% and 90.8% respectively. The developed models were tested with a test set of 99 compounds and further validated with external set of 98 compounds. Distribution plot analysis and various machine learning models were also developed based on druglikeness descriptors. Applicability domain is used to check the prediction reliability of the new molecules.

  11. Classification of hospital pathways in the management of cancer: application to lung cancer in the region of burgundy.

    Science.gov (United States)

    Nuemi, G; Afonso, F; Roussot, A; Billard, L; Cottenet, J; Combier, E; Diday, E; Quantin, C

    2013-10-01

    The evaluation of national cancer plans is an important aspect of their implementation. For this evaluation, the principal actors in the field (doctors, nurses, etc.) as well as decision-makers must have access to information that is reliable, synthetic and easy to interpret, and which reflects the implementation process in the field. We propose here a methodology to make this type of information available in the context of reducing inequalities with regard to access to healthcare for patients with lung cancer in the region of Burgundy. We used the national medico-administrative DRG-type database, which gathers together all hospital stays. By using this database, it was possible to identify and reconstruct the care management history of these patients. That is, by linking together all attended hospitals, sorted chronologically. Eligible patients were at least 18 years old, whatever the gender and had undergone surgery for their lung cancer. They had to be residents of Burgundy at the time of the first operation between 2006 and 2008. Patient's pathway was defined as the sequence of all attended hospitals (hospital stays) during the year of follow up linked together using an anonymised patient identifier. We then constructed a pathway typology of pathway using an unsupervised clustering method, and conducted a spatial analysis of this typology. Between 2006 and 2008, we selected 495 patients in the 4 administrative departments of the Burgundy region. They accounted for a total of 3821 stays during the year of follow-up. There were 393 men (79%) and the mean age was 64 (95% confidence interval: 63-65) years. We reconstructed 94 pathways (about five per patient). Here, neighbourhood's cares accounted for 41% of them, while 44% included a surgical intervention outside the region of Burgundy. We constructed a pathway typology with five classes. Spatial analysis showed that the vast majority of initial surgeries took place in the major regional centres. The construction

  12. Clinical and Pathological Staging Validation in the Eighth Edition of the TNM Classification for Lung Cancer: Correlation between Solid Size on Thin-Section Computed Tomography and Invasive Size in Pathological Findings in the New T Classification.

    Science.gov (United States)

    Aokage, Keiju; Miyoshi, Tomohiro; Ishii, Genichiro; Kusumoto, Masahiro; Nomura, Shogo; Katsumata, Shinya; Sekihara, Keigo; Hishida, Tomoyuki; Tsuboi, Masahiro

    2017-09-01

    The aim of this study was to validate the new eighth edition of the TNM classification and to elucidate whether radiological solid size corresponds to pathological invasive size incorporated in this T factor. We analyzed the data on 1792 patients who underwent complete resection from 2003 to 2011 at the National Cancer Center Hospital East, Japan. We reevaluated preoperative thin-section computed tomography (TSCT) to determine solid size and pathological invasive size using the fourth edition of the WHO classification and reclassified them according to the new TNM classification. The discriminative power of survival curves by the seventh edition was compared with that by the eighth edition by using concordance probability estimates and Akaike's information criteria calculated using a univariable Cox regression model. Pearson's correlation coefficient was calculated to elucidate the correlation between radiological solid size using TSCT and pathological invasive size. The overall survival curves in the eighth edition were well distinct at each clinical and pathological stage. The 5-year survival rates of patients with clinical and pathological stage 0 newly defined were both 100%. The concordance probability estimate and Akaike's information criterion values of the eighth edition were higher than those of the seventh edition in discriminatory power for overall survival. Solid size on TSCT scan and pathological invasive size showed a positive linear relationship, and Pearson's correlation coefficient was calculated as 0.83, which indicated strong correlation. This TNM classification will be feasible regarding patient survival, and radiological solid size correlates significantly with pathological invasive size as a new T factor. Copyright © 2017 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

  13. Classification of M1/M2-polarized human macrophages by label-free hyperspectral reflectance confocal microscopy and multivariate analysis.

    Science.gov (United States)

    Bertani, Francesca R; Mozetic, Pamela; Fioramonti, Marco; Iuliani, Michele; Ribelli, Giulia; Pantano, Francesco; Santini, Daniele; Tonini, Giuseppe; Trombetta, Marcella; Businaro, Luca; Selci, Stefano; Rainer, Alberto

    2017-08-21

    The possibility of detecting and classifying living cells in a label-free and non-invasive manner holds significant theranostic potential. In this work, Hyperspectral Imaging (HSI) has been successfully applied to the analysis of macrophagic polarization, given its central role in several pathological settings, including the regulation of tumour microenvironment. Human monocyte derived macrophages have been investigated using hyperspectral reflectance confocal microscopy, and hyperspectral datasets have been analysed in terms of M1 vs. M2 polarization by Principal Components Analysis (PCA). Following PCA, Linear Discriminant Analysis has been implemented for semi-automatic classification of macrophagic polarization from HSI data. Our results confirm the possibility to perform single-cell-level in vitro classification of M1 vs. M2 macrophages in a non-invasive and label-free manner with a high accuracy (above 98% for cells deriving from the same donor), supporting the idea of applying the technique to the study of complex interacting cellular systems, such in the case of tumour-immunity in vitro models.

  14. Prognostic Performance and Reproducibility of the 1973 and 2004/2016 World Health Organization Grading Classification Systems in Non-muscle-invasive Bladder Cancer: A European Association of Urology Non-muscle Invasive Bladder Cancer Guidelines Panel Systematic Review.

    Science.gov (United States)

    Soukup, Viktor; Čapoun, Otakar; Cohen, Daniel; Hernández, Virginia; Babjuk, Marek; Burger, Max; Compérat, Eva; Gontero, Paolo; Lam, Thomas; MacLennan, Steven; Mostafid, A Hugh; Palou, Joan; van Rhijn, Bas W G; Rouprêt, Morgan; Shariat, Shahrokh F; Sylvester, Richard; Yuan, Yuhong; Zigeuner, Richard

    2017-11-01

    Tumour grade is an important prognostic indicator in non-muscle-invasive bladder cancer (NMIBC). Histopathological classifications are limited by interobserver variability (reproducibility), which may have prognostic implications. European Association of Urology NMIBC guidelines suggest concurrent use of both 1973 and 2004/2016 World Health Organization (WHO) classifications. To compare the prognostic performance and reproducibility of the 1973 and 2004/2016 WHO grading systems for NMIBC. A systematic literature search was undertaken incorporating Medline, Embase, and the Cochrane Library. Studies were critically appraised for risk of bias (QUIPS). For prognosis, the primary outcome was progression to muscle-invasive or metastatic disease. Secondary outcomes were disease recurrence, and overall and cancer-specific survival. For reproducibility, the primary outcome was interobserver variability between pathologists. Secondary outcome was intraobserver variability (repeatability) by the same pathologist. Of 3593 articles identified, 20 were included in the prognostic review; three were eligible for the reproducibility review. Increasing tumour grade in both classifications was associated with higher disease progression and recurrence rates. Progression rates in grade 1 patients were similar to those in low-grade patients; progression rates in grade 3 patients were higher than those in high-grade patients. Survival data were limited. Reproducibility of the 2004/2016 system was marginally better than that of the 1973 system. Two studies on repeatability showed conflicting results. Most studies had a moderate to high risk of bias. Current grading classifications in NMIBC are suboptimal. The 1973 system identifies more aggressive tumours. Intra- and interobserver variability was slightly less in the 2004/2016 classification. We could not confirm that the 2004/2016 classification outperforms the 1973 classification in prediction of recurrence and progression. This article

  15. Apoptosis induced by GanoPoly in human gastric cancer cell line ...

    African Journals Online (AJOL)

    use

    2011-12-12

    Dec 12, 2011 ... ... cancer's active therapy. Key words: Apoptosis, polysaccharide, human gastric cancer cells. ... The active components of polysaccharides are all glucans, which have a ... for the treatment of alleviated fatigue, night sweating,.

  16. Ipilimumab in Treating Patients With Metastatic or Recurrent Human Papilloma Virus-Related Cervical Cancer

    Science.gov (United States)

    2018-05-23

    Cervical Adenocarcinoma; Cervical Squamous Cell Carcinoma, Not Otherwise Specified; Human Papillomavirus Infection; Recurrent Cervical Carcinoma; Stage IVA Cervical Cancer AJCC v6 and v7; Stage IVB Cervical Cancer AJCC v6 and v7

  17. Review of colorectal cancer and its metastases in rodent models: comparative aspects with those in humans

    DEFF Research Database (Denmark)

    Kobaek-Larsen, M; Thorup, I; Diederichsen, Axel Cosmus Pyndt

    2000-01-01

    BACKGROUND AND PURPOSE: Colorectal cancer (CRC) remains one of the most common cancer forms developing in industrialized countries, and its incidence appears to be rising. Studies of human population groups provide insufficient information about carcinogenesis, pathogenesis, and treatment of CRC...

  18. Prevalence of human papillomavirus in epithelial ovarian cancer tissue. A meta-analysis of observational studies

    DEFF Research Database (Denmark)

    Svahn, Malene F; Faber, Mette Tuxen; Christensen, Jane

    2014-01-01

    The role of human papillomavirus (HPV) in the pathogenesis of ovarian cancer is controversial, and conflicting results have been published. We conducted a systematic review and meta-analysis to estimate the prevalence of HPV in epithelial ovarian cancer tissue....

  19. Prognostic significance of visceral pleural invasion in the forthcoming (seventh) edition of TNM classification for lung cancer.

    Science.gov (United States)

    Shim, Hyo Sup; Park, In Kyu; Lee, Chang Young; Chung, Kyung Young

    2009-08-01

    The next revision to the TNM classification for lung cancer (the seventh edition) is scheduled to be released in 2009. However, the definition of visceral pleural invasion (VPI), which is a non-size-based T2 descriptor, still lacks in detail, and its validation is not included. We analyzed 1046 cases of non-small cell lung cancer (NSCLC) with T1, T2, or T3 diseases from 1990 to 2005, and subclassified into p0-p3 according to the degrees of pleural invasion. Survival analyses were performed using Kaplan-Meier method. Then, all patients were subdivided into nine groups according to tumor size and pleural invasion, and we compared survival differences, primarily focusing on T2a and T2b diseases according to the seventh edition. There was no survival difference between patients with p1 and p2, thus we regarded p1 or p2 as VPI. There was survival difference between two groups, which are expected to be classified as T2b. The behavior of tumors larger than 5cm but 7cm or less with VPI was similar to T3 tumors. VPI is a poor prognostic factor of NSCLC, and the penetration through the elastic layer of the visceral pleura regardless of its exposure on the pleural surface (pl and p2) should be defined as VPI. This study also indicates that VPI influences T stage dependent on tumor size, and it can be suggested that tumors of larger than 5cm but 7cm or less with VPI should be upgraded to T3 stage.

  20. Improving supervised classification accuracy using non-rigid multimodal image registration: detecting prostate cancer

    Science.gov (United States)

    Chappelow, Jonathan; Viswanath, Satish; Monaco, James; Rosen, Mark; Tomaszewski, John; Feldman, Michael; Madabhushi, Anant

    2008-03-01

    Computer-aided diagnosis (CAD) systems for the detection of cancer in medical images require precise labeling of training data. For magnetic resonance (MR) imaging (MRI) of the prostate, training labels define the spatial extent of prostate cancer (CaP); the most common source for these labels is expert segmentations. When ancillary data such as whole mount histology (WMH) sections, which provide the gold standard for cancer ground truth, are available, the manual labeling of CaP can be improved by referencing WMH. However, manual segmentation is error prone, time consuming and not reproducible. Therefore, we present the use of multimodal image registration to automatically and accurately transcribe CaP from histology onto MRI following alignment of the two modalities, in order to improve the quality of training data and hence classifier performance. We quantitatively demonstrate the superiority of this registration-based methodology by comparing its results to the manual CaP annotation of expert radiologists. Five supervised CAD classifiers were trained using the labels for CaP extent on MRI obtained by the expert and 4 different registration techniques. Two of the registration methods were affi;ne schemes; one based on maximization of mutual information (MI) and the other method that we previously developed, Combined Feature Ensemble Mutual Information (COFEMI), which incorporates high-order statistical features for robust multimodal registration. Two non-rigid schemes were obtained by succeeding the two affine registration methods with an elastic deformation step using thin-plate splines (TPS). In the absence of definitive ground truth for CaP extent on MRI, classifier accuracy was evaluated against 7 ground truth surrogates obtained by different combinations of the expert and registration segmentations. For 26 multimodal MRI-WMH image pairs, all four registration methods produced a higher area under the receiver operating characteristic curve compared to that

  1. Can-CSC-GBE: Developing Cost-sensitive Classifier with Gentleboost Ensemble for breast cancer classification using protein amino acids and imbalanced data.

    Science.gov (United States)

    Ali, Safdar; Majid, Abdul; Javed, Syed Gibran; Sattar, Mohsin

    2016-06-01

    Early prediction of breast cancer is important for effective treatment and survival. We developed an effective Cost-Sensitive Classifier with GentleBoost Ensemble (Can-CSC-GBE) for the classification of breast cancer using protein amino acid features. In this work, first, discriminant information of the protein sequences related to breast tissue is extracted. Then, the physicochemical properties hydrophobicity and hydrophilicity of amino acids are employed to generate molecule descriptors in different feature spaces. For comparison, we obtained results by combining Cost-Sensitive learning with conventional ensemble of AdaBoostM1 and Bagging. The proposed Can-CSC-GBE system has effectively reduced the misclassification costs and thereby improved the overall classification performance. Our novel approach has highlighted promising results as compared to the state-of-the-art ensemble approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Regularization strategies for hyperplane classifiers: application to cancer classification with gene expression data.

    Science.gov (United States)

    Andries, Erik; Hagstrom, Thomas; Atlas, Susan R; Willman, Cheryl

    2007-02-01

    Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require regularization. Here, we examine the ill-posedness involved in the linear discrimination of cancer gene expression data with respect to outcome and tumor subclasses. We show that a filter factor representation, based upon Singular Value Decomposition, yields insight into the numerical ill-posedness of the hyperplane-based separation when applied to gene expression data. We also show that this representation yields useful diagnostic tools for guiding the selection of classifier parameters, thus leading to improved performance.

  3. Detection of Gastric Cancer with Fourier Transform Infrared Spectroscopy and Support Vector Machine Classification

    Directory of Open Access Journals (Sweden)

    Qingbo Li

    2013-01-01

    Full Text Available Early diagnosis and early medical treatments are the keys to save the patients' lives and improve the living quality. Fourier transform infrared (FT-IR spectroscopy can distinguish malignant from normal tissues at the molecular level. In this paper, programs were made with pattern recognition method to classify unknown samples. Spectral data were pretreated by using smoothing and standard normal variate (SNV methods. Leave-one-out cross validation was used to evaluate the discrimination result of support vector machine (SVM method. A total of 54 gastric tissue samples were employed in this study, including 24 cases of normal tissue samples and 30 cases of cancerous tissue samples. The discrimination results of SVM method showed the sensitivity with 100%, specificity with 83.3%, and total discrimination accuracy with 92.2%.

  4. Constructing Support Vector Machine Ensembles for Cancer Classification Based on Proteomic Profiling

    Institute of Scientific and Technical Information of China (English)

    Yong Mao; Xiao-Bo Zhou; Dao-Ying Pi; You-Xian Sun

    2005-01-01

    In this study, we present a constructive algorithm for training cooperative support vector machine ensembles (CSVMEs). CSVME combines ensemble architecture design with cooperative training for individual SVMs in ensembles. Unlike most previous studies on training ensembles, CSVME puts emphasis on both accuracy and collaboration among individual SVMs in an ensemble. A group of SVMs selected on the basis of recursive classifier elimination is used in CSVME, and the number of the individual SVMs selected to construct CSVME is determined by 10-fold cross-validation. This kind of SVME has been tested on two ovarian cancer datasets previously obtained by proteomic mass spectrometry. By combining several individual SVMs, the proposed method achieves better performance than the SVME of all base SVMs.

  5. Incorporating Hofstede’ National Culture in Human Factor Analysis and Classification System (HFACS: Cases of Indonesian Aviation Safety

    Directory of Open Access Journals (Sweden)

    Pratama Gradiyan Budi

    2018-01-01

    Full Text Available National culture plays an important role in the application of ergonomics and safety. This research examined role of national culture in accident analysis of Indonesian aviation using framework of Human Factors Analysis and Classification System (HFACS. 53 Indonesian aviation accidents during year of 2001-2012 were analyzed using the HFACS framework by authors and were validated to 14 air-transport experts in Indonesia. National culture is viewed with Hofstede’ lens of national culture. Result shows that high collectivistic, low uncertainty avoidance, high power distance, and masculinity dimension which are characteristics of Indonesian culture, play an important role in Indonesian aviation accident and should be incorporated within HFACS. Result is discussed in relation with HFACS and Indonesian aviation accident analysis.

  6. Human Papillomavirus and Tonsillar and Base of Tongue Cancer

    Directory of Open Access Journals (Sweden)

    Torbjörn Ramqvist

    2015-03-01

    Full Text Available In 2007, human papillomavirus (HPV type 16 was recognized as a risk factor by the International Agency for Research on Cancer, for oropharyngeal squamous cell carcinoma (OSCC, where tonsillar and base of tongue cancer (TSCC and BOTSCC dominate. Furthermore, patients with HPV-positive TSCC and BOTSCC, had a much better clinical outcome than those with corresponding HPV-negative cancer and other head and neck cancer. More specifically, survival was around 80% for HPV-positive TSCC and BOTSCC vs. 40% five-year disease free survival, for the corresponding HPV-negative tumors with conventional radiotherapy and surgery, while this could not be observed for HPV-positive OSCC at other sites. In addition, the past 20–40 years in many Western Countries, the incidence of HPV-positive TSCC and BOTSCC has risen, and >70% are men. This has resulted in a relative increase of patients with HPV-positive TSCC and BOTSCC that may not need the intensified chemo-radiotherapy (with many more severe debilitating side effects often given today to patients with head and neck cancer. However, before tapering therapy, one needs to enable selection of patients for such treatment, by identifying clinical and molecular markers that together with HPV-positive status will better predict patient prognosis and response to therapy. To conclude, there is a new increasing group of patients with HPV-positive TSCC and BOTSCC with good clinical outcome, where options for better-tailored therapy are needed. For prevention, it would be of benefit to vaccinate both girls and boys against HPV16 infection. For potential future screening the ways to do so need optimizing.

  7. Phase I study of anticolon cancer humanized antibody A33.

    Science.gov (United States)

    Welt, Sydney; Ritter, Gerd; Williams, Clarence; Cohen, Leonard S; John, Mary; Jungbluth, Achim; Richards, Elizabeth A; Old, Lloyd J; Kemeny, Nancy E

    2003-04-01

    Humanized A33 (huA33; IgG1) monoclonal antibody detects a determinant expressed by 95% of colorectal cancers and can activate immune cytolytic mechanisms. The present study was designed to (a) define the toxicities and maximum tolerated dose of huA33 and (b) determine huA33 immunogenicity. Patients (n = 11) with advanced chemotherapy-resistant colorectal cancer received 4-week cycles of huA33 at 10, 25, or 50 mg/m(2)/week. Serum samples were analyzed using biosensor technology for evidence of human antihuman antibody (HAHA) response. Eight of 11 patients developed a HAHA response. Significant toxicity was limited to four patients who developed high HAHA titers. In two of these cases, infusion-related reactions such as fevers, rigors, facial flushing, and changes in blood pressure were observed, whereas in the other two cases, toxicity consisted of skin rash, fever, or myalgia. Of three patients who remained HAHA negative, one achieved a radiographic partial response, with reduction of serum carcinoembryonic antigen from 80 to 3 ng/ml. Four patients had radiographic evidence of stable disease (2, 4, 6, and 12 months), with significant reductions (>25%) in serum carcinoembryonic antigen levels in two cases. The complementarity-determining region-grafted huA33 antibody is immunogenic in the majority of colon cancer patients (73%). HAHA activity can be measured reproducibly and quantitatively by BIACORE analysis. Whereas the huA33 construct tested here may be too immunogenic for further clinical development, the antitumor effects observed in the absence of antibody-mediated toxicity and in this heavily pretreated patient population warrant clinical testing of other IgG1 humanized versions of A33 antibody.

  8. Clinical application of a microfluidic chip for immunocapture and quantification of circulating exosomes to assist breast cancer diagnosis and molecular classification.

    Science.gov (United States)

    Fang, Shimeng; Tian, Hongzhu; Li, Xiancheng; Jin, Dong; Li, Xiaojie; Kong, Jing; Yang, Chun; Yang, Xuesong; Lu, Yao; Luo, Yong; Lin, Bingcheng; Niu, Weidong; Liu, Tingjiao

    2017-01-01

    Increasing attention has been attracted by exosomes in blood-based diagnosis because cancer cells release more exosomes in serum than normal cells and these exosomes overexpress a certain number of cancer-related biomarkers. However, capture and biomarker analysis of exosomes for clinical application are technically challenging. In this study, we developed a microfluidic chip for immunocapture and quantification of circulating exosomes from small sample volume and applied this device in clinical study. Circulating EpCAM-positive exosomes were measured in 6 cases breast cancer patients and 3 healthy controls to assist diagnosis. A significant increase in the EpCAM-positive exosome level in these patients was detected, compared to healthy controls. Furthermore, we quantified circulating HER2-positive exosomes in 19 cases of breast cancer patients for molecular classification. We demonstrated that the exosomal HER2 expression levels were almost consistent with that in tumor tissues assessed by immunohistochemical staining. The microfluidic chip might provide a new platform to assist breast cancer diagnosis and molecular classification.

  9. Cancer in human immunodeficiency virus-infected children : A case series from the Children's Cancer Group and the National Cancer Institute

    NARCIS (Netherlands)

    Granovsky, MO; Mueller, BU; Nicholson, HS; Rosenberg, PS; Rabkin, CS

    Purpose: To describe the spectrum of malignancies in human immunodeficiency virus (HIV)-infected children and the clinical outcome of patients with these tumors. Methods: We retrospectively surveyed the Children's Cancer Group (CCG) and the National Cancer institute (NCI) for cases of cancer that

  10. Large-Scale Analysis of Network Bistability for Human Cancers

    Science.gov (United States)

    Shiraishi, Tetsuya; Matsuyama, Shinako; Kitano, Hiroaki

    2010-01-01

    Protein–protein interaction and gene regulatory networks are likely to be locked in a state corresponding to a disease by the behavior of one or more bistable circuits exhibiting switch-like behavior. Sets of genes could be over-expressed or repressed when anomalies due to disease appear, and the circuits responsible for this over- or under-expression might persist for as long as the disease state continues. This paper shows how a large-scale analysis of network bistability for various human cancers can identify genes that can potentially serve as drug targets or diagnosis biomarkers. PMID:20628618

  11. Biological relevance of human papillomaviruses in vulvar cancer.

    Science.gov (United States)

    Halec, Gordana; Alemany, Laia; Quiros, Beatriz; Clavero, Omar; Höfler, Daniela; Alejo, Maria; Quint, Wim; Pawlita, Michael; Bosch, Francesc X; de Sanjose, Silvia

    2017-04-01

    The carcinogenic role of high-risk human papillomavirus (HR-HPV) types in the increasing subset of vulvar intraepithelial neoplasia and vulvar cancer in young women has been established. However, the actual number of vulvar cancer cases attributed to HPV is still imprecisely defined. In an attempt to provide a more precise definition of HPV-driven vulvar cancer, we performed HPV-type-specific E6*I mRNA analyses available for 20 HR-/possible HR (pHR)-HPV types, on tissue samples from 447 cases of vulvar cancer. HPV DNA genotyping was performed using SPF10-LiPA 25 assay due to its high sensitivity in formalin-fixed paraffin-embedded tissues. Data on p16 INK4a expression was available for comparative analysis via kappa statistics. The use of highly sensitive assays covering the detection of HPV mRNA in a broad spectrum of mucosal HPV types resulted in the detection of viral transcripts in 87% of HPV DNA+ vulvar cancers. Overall concordance between HPV mRNA+ and p16 INK4a upregulation (strong, diffuse immunostaining in >25% of tumor cells) was 92% (K=0.625, 95% confidence interval (CI)=0.531-0.719). Among these cases, 83% were concordant pairs of HPV mRNA+ and p16 INK4a + and 9% were concordant pairs of HPV mRNA- and p16 INK4a -. Our data confirm the biological role of HR-/pHR-HPV types in the great majority of HPV DNA+ vulvar cancers, resulting in an HPV-attributable fraction of at least 21% worldwide. Most HPV DNA+ vulvar cancers were associated with HPV16 (85%), but a causative role for other, less frequently occurring mucosal HPV types (HPV26, 66, 67, 68, 70 and 73) was also confirmed at the mRNA level for the first time. These findings should be taken into consideration for future screening options as HPV-associated vulvar preneoplastic lesions have increased in incidence in younger women and require different treatment than vulvar lesions that develop from rare autoimmune-related mechanisms in older women.

  12. A classification scheme of erroneous behaviors for human error probability estimations based on simulator data

    International Nuclear Information System (INIS)

    Kim, Yochan; Park, Jinkyun; Jung, Wondea

    2017-01-01

    Because it has been indicated that empirical data supporting the estimates used in human reliability analysis (HRA) is insufficient, several databases have been constructed recently. To generate quantitative estimates from human reliability data, it is important to appropriately sort the erroneous behaviors found in the reliability data. Therefore, this paper proposes a scheme to classify the erroneous behaviors identified by the HuREX (Human Reliability data Extraction) framework through a review of the relevant literature. A case study of the human error probability (HEP) calculations is conducted to verify that the proposed scheme can be successfully implemented for the categorization of the erroneous behaviors and to assess whether the scheme is useful for the HEP quantification purposes. Although continuously accumulating and analyzing simulator data is desirable to secure more reliable HEPs, the resulting HEPs were insightful in several important ways with regard to human reliability in off-normal conditions. From the findings of the literature review and the case study, the potential and limitations of the proposed method are discussed. - Highlights: • A taxonomy of erroneous behaviors is proposed to estimate HEPs from a database. • The cognitive models, procedures, HRA methods, and HRA databases were reviewed. • HEPs for several types of erroneous behaviors are calculated as a case study.

  13. Clinical Effect of Human Papillomavirus Genotypes in Patients With Cervical Cancer Undergoing Primary Radiotherapy

    International Nuclear Information System (INIS)

    Wang, Chun-Chieh; Lai, Chyong-Huey; Huang, Huei-Jean; Chao, Angel; Chang, Chee-Jen; Chang, Ting-Chang; Chou, Hung-Hsueh; Hong, Ji-Hong

    2010-01-01

    Purpose: To study the prognostic value of the human papillomavirus (HPV) genotypes in cervical cancer patients undergoing radiotherapy. Patients and Methods: A total of 1,010 patients with cervical cancer after radiotherapy between 1993 and 2000 were eligible for this study. The HPV genotypes were determined by a genechip, which detects 38 types of HPV. The patient characteristics and treatment outcomes were analyzed using the Cox regression hazard model and classification and regression tree decision tree method. Results: A total of 25 genotypes of HPV were detected in 992 specimens (98.2%). The leading 8 types were HPV16, 58, 18, 33, 52, 39, 31, and 45. These types belong to two high-risk HPV species: alpha-7 (HPV18, 39, 45) and alpha-9 (HPV16, 31, 33, 52, 58). Three HPV-based risk groups, which were independent of established prognostic factors, such as International Federation of Gynecology and Obstetrics stage, age, pathologic features, squamous cell carcinoma antigen, and lymph node metastasis, were associated with the survival outcomes. The high-risk group consisted of the patients without HPV infection or the ones infected with the alpha-7 species only. Patients co-infected with the alpha-7 and alpha-9 species belonged to the medium-risk group, and the others were included in the low-risk group. Conclusion: The results of the present study have confirmed the prognostic value of HPV genotypes in cervical cancer treated with radiotherapy. The different effect of the alpha-7 and alpha-9 species on the radiation response deserves additional exploration.

  14. Classification of 27 Tumor-Associated Antigens by Histochemical Analysis of 36 Freshly Resected Lung Cancer Tissues

    Directory of Open Access Journals (Sweden)

    Gene Kurosawa

    2016-11-01

    Full Text Available In previous studies, we identified 29 tumor-associated antigens (TAAs and isolated 488 human monoclonal antibodies (mAbs that specifically bind to one of the 29 TAAs. In the present study, we performed histochemical analysis of 36 freshly resected lung cancer tissues by using 60 mAbs against 27 TAAs. Comparison of the staining patterns of tumor cells, bronchial epithelial cells, and normal pulmonary alveolus cells and interalveolar septum allowed us to determine the type and location of cells that express target molecules, as well as the degree of expression. The patterns were classified into 7 categories. While multiple Abs were used against certain TAAs, the differences observed among them should be derived from differences in the binding activity and/or the epitope. Thus, such data indicate the versatility of respective clones as anti-cancer drugs. Although the information obtained was limited to the lung and bronchial tube, bronchial epithelial cells represent normal growing cells, and therefore, the data are informative. The results indicate that 9 of the 27 TAAs are suitable targets for therapeutic Abs. These 9 Ags include EGFR, HER2, TfR, and integrin α6β4. Based on our findings, a pharmaceutical company has started to develop anti-cancer drugs by using Abs to TfR and integrin α6β4. HGFR, PTP-LAR, CD147, CDCP1, and integrin αvβ3 are also appropriate targets for therapeutic purposes.

  15. Identification and classification of conserved RNA secondary structures in the human genome

    DEFF Research Database (Denmark)

    Pedersen, Jakob Skou; Bejerano, Gill; Siepel, Adam

    2006-01-01

    The discoveries of microRNAs and riboswitches, among others, have shown functional RNAs to be biologically more important and genomically more prevalent than previously anticipated. We have developed a general comparative genomics method based on phylogenetic stochastic context-free grammars...... for identifying functional RNAs encoded in the human genome and used it to survey an eight-way genome-wide alignment of the human, chimpanzee, mouse, rat, dog, chicken, zebra-fish, and puffer-fish genomes for deeply conserved functional RNAs. At a loose threshold for acceptance, this search resulted in a set......, the results nevertheless provide evidence for many new human functional RNAs and present specific predictions to facilitate their further characterization....

  16. Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data

    OpenAIRE

    REN, ZHONGLU; WANG, WENHUI; LI, JINMING

    2015-01-01

    Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristi...

  17. Saudi anti-human cancer plants database (SACPD): A collection of plants with anti-human cancer activities.

    Science.gov (United States)

    Al-Zahrani, Ateeq Ahmed

    2018-01-30

    Several anticancer drugs have been developed from natural products such as plants. Successful experiments in inhibiting the growth of human cancer cell lines using Saudi plants were published over the last three decades. Up to date, there is no Saudi anticancer plants database as a comprehensive source for the interesting data generated from these experiments. Therefore, there was a need for creating a database to collect, organize, search and retrieve such data. As a result, the current paper describes the generation of the Saudi anti-human cancer plants database (SACPD). The database contains most of the reported information about the naturally growing Saudi anticancer plants. SACPD comprises the scientific and local names of 91 plant species that grow naturally in Saudi Arabia. These species belong to 38 different taxonomic families. In Addition, 18 species that represent16 family of medicinal plants and are intensively sold in the local markets in Saudi Arabia were added to the database. The website provides interesting details, including plant part containing the anticancer bioactive compounds, plants locations and cancer/cell type against which they exhibit their anticancer activity. Our survey revealed that breast, liver and leukemia were the most studied cancer cell lines in Saudi Arabia with percentages of 27%, 19% and 15%, respectively. The current SACPD represents a nucleus around which more development efforts can expand to accommodate all future submissions about new Saudi plant species with anticancer activities. SACPD will provide an excellent starting point for researchers and pharmaceutical companies who are interested in developing new anticancer drugs. SACPD is available online at https://teeqrani1.wixsite.com/sapd.

  18. Human movement activity classification approaches that use wearable sensors and mobile devices

    Science.gov (United States)

    Kaghyan, Sahak; Sarukhanyan, Hakob; Akopian, David

    2013-03-01

    Cell phones and other mobile devices become part of human culture and change activity and lifestyle patterns. Mobile phone technology continuously evolves and incorporates more and more sensors for enabling advanced applications. Latest generations of smart phones incorporate GPS and WLAN location finding modules, vision cameras, microphones, accelerometers, temperature sensors etc. The availability of these sensors in mass-market communication devices creates exciting new opportunities for data mining applications. Particularly healthcare applications exploiting build-in sensors are very promising. This paper reviews different approaches of human activity recognition.

  19. [Evaluation and classification of drug therapy for breast cancer with bone-only metastasis].

    Science.gov (United States)

    Meng, X Y; Song, S T

    2017-03-23

    Skeleton is one of the most common metastatic organs for breast cancer, which has a better prognosis than visceral metastases. Bone-only metastasis was defined"non-measurable" in the RECIST (Response Evaluation Criteria in Solid Tumors) criteria, and was excluded by clinical trials. However, patients with bone-only metastasis are also in need of effective treatment to prolong survival. Endocrine therapy is the most important treatment for bone metastatic patients. Tumor response of bone metastases can be determined objectively by bone-window CT. Effective treatment should be continued if the symptoms are relieved or osteogenesis is observed. Osteoblastic change in bone-window CT is a sign of improvement after treatment. Endocrine therapy is proper for ER-positive patients. The patients with initial osteoblastic metastasis should not be treated with salvage chemotherapy or anti-HER2 treatment, only if osteolytic metastasis or visceral metastasis is observed. Bishosphonates are just auxiliary drugs in bone metastasis, which should not be abused.

  20. Differential Cytotoxic Potential of Silver Nanoparticles in Human Ovarian Cancer Cells and Ovarian Cancer Stem Cells

    Directory of Open Access Journals (Sweden)

    Yun-Jung Choi

    2016-12-01

    Full Text Available The cancer stem cell (CSC hypothesis postulates that cancer cells are composed of hierarchically-organized subpopulations of cells with distinct phenotypes and tumorigenic capacities. As a result, CSCs have been suggested as a source of disease recurrence. Recently, silver nanoparticles (AgNPs have been used as antimicrobial, disinfectant, and antitumor agents. However, there is no study reporting the effects of AgNPs on ovarian cancer stem cells (OvCSCs. In this study, we investigated the cytotoxic effects of AgNPs and their mechanism of causing cell death in A2780 (human ovarian cancer cells and OvCSCs derived from A2780. In order to examine these effects, OvCSCs were isolated and characterized using positive CSC markers including aldehyde dehydrogenase (ALDH and CD133 by fluorescence-activated cell sorting (FACS. The anticancer properties of the AgNPs were evaluated by assessing cell viability, leakage of lactate dehydrogenase (LDH, reactive oxygen species (ROS, and mitochondrial membrane potential (mt-MP. The inhibitory effect of AgNPs on the growth of ovarian cancer cells and OvCSCs was evaluated using a clonogenic assay. Following 1–2 weeks of incubation with the AgNPs, the numbers of A2780 (bulk cells and ALDH+/CD133+ colonies were significantly reduced. The expression of apoptotic and anti-apoptotic genes was measured by real-time quantitative reverse transcriptase polymerase chain reaction (qRT-PCR. Our observations showed that treatment with AgNPs resulted in severe cytotoxicity in both ovarian cancer cells and OvCSCs. In particular, AgNPs showed significant cytotoxic potential in ALDH+/CD133+ subpopulations of cells compared with other subpopulation of cells and also human ovarian cancer cells (bulk cells. These findings suggest that AgNPs can be utilized in the development of novel nanotherapeutic molecules for the treatment of ovarian cancers by specific targeting of the ALDH+/CD133+ subpopulation of cells.

  1. Organoid Models of Human and Mouse Ductal Pancreatic Cancer

    Science.gov (United States)

    Boj, Sylvia F.; Hwang, Chang-Il; Baker, Lindsey A.; Chio, Iok In Christine; Engle, Dannielle D.; Corbo, Vincenzo; Jager, Myrthe; Ponz-Sarvise, Mariano; Tiriac, Hervé; Spector, Mona S.; Gracanin, Ana; Oni, Tobiloba; Yu, Kenneth H.; van Boxtel, Ruben; Huch, Meritxell; Rivera, Keith D.; Wilson, John P.; Feigin, Michael E.; Öhlund, Daniel; Handly-Santana, Abram; Ardito-Abraham, Christine M.; Ludwig, Michael; Elyada, Ela; Alagesan, Brinda; Biffi, Giulia; Yordanov, Georgi N.; Delcuze, Bethany; Creighton, Brianna; Wright, Kevin; Park, Youngkyu; Morsink, Folkert H.M.; Molenaar, I. Quintus; Borel Rinkes, Inne H.; Cuppen, Edwin; Hao, Yuan; Jin, Ying; Nijman, Isaac J.; Iacobuzio-Donahue, Christine; Leach, Steven D.; Pappin, Darryl J.; Hammell, Molly; Klimstra, David S.; Basturk, Olca; Hruban, Ralph H.; Offerhaus, George Johan; Vries, Robert G.J.; Clevers, Hans; Tuveson, David A.

    2015-01-01

    SUMMARY Pancreatic cancer is one of the most lethal malignancies due to its late diagnosis and limited response to treatment. Tractable methods to identify and interrogate pathways involved in pancreatic tumorigenesis are urgently needed. We established organoid models from normal and neoplastic murine and human pancreas tissues. Pancreatic organoids can be rapidly generated from resected tumors and biopsies, survive cryopreservation and exhibit ductal- and disease stage-specific characteristics. Orthotopically transplanted neoplastic organoids recapitulate the full spectrum of tumor development by forming early-grade neoplasms that progress to locally invasive and metastatic carcinomas. Due to their ability to be genetically manipulated, organoids are a platform to probe genetic cooperation. Comprehensive transcriptional and proteomic analyses of murine pancreatic organoids revealed genes and pathways altered during disease progression. The confirmation of many of these protein changes in human tissues demonstrates that organoids are a facile model system to discover characteristics of this deadly malignancy. PMID:25557080

  2. Making Meaning out of Human/Animal: Scientific Competition of Classifications in the Spanish Legislature

    Science.gov (United States)

    Mitchell, Ross

    2010-01-01

    In the summer of 2008, the Spanish legislature resolved to grant great apes (though not all simians) basic human rights. While the decision to grant such rights came about largely through the lobbying efforts of the Great Ape Project (GAP), the decision has potential reverberations throughout the scientific world and beyond in its implications for…

  3. Classification of human- and automated resource allocation approaches in multi-project management

    NARCIS (Netherlands)

    Ponsteen, A.; Kusters, R.J.; Pasian, B.; Storm, P.

    2015-01-01

    Managing a multi-project environment requires a different method than managing a single project. The main challenge of managing a multi-project environment is the allocation of scarce human resources over the projects in execution. As part of a broader research on this topic, the aim of this paper

  4. Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans

    DEFF Research Database (Denmark)

    Timmons, James A; Knudsen, Steen; Rankinen, Tuomo

    2010-01-01

    A low maximal oxygen consumption (VO2max) is a strong risk factor for premature mortality. Supervised endurance exercise training increases VO2max with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial s...

  5. Human Papilloma Virus in Head and Neck Squamous Cell Cancer

    Science.gov (United States)

    Asvadi Kermani, I; Seifi, SH; Dolatkhah, R; Sakhinia, E; Dastgiri, S; Ebrahimi, A; Lotfy, A; Esmaeili, HA; G, Mohammadi; M, Naderpour; SH, Hajalipour; Haggi A, Asghari; M, Nadri

    2012-01-01

    Background Epidemiologic and molecular evidences have established a strong link between high risk types of Human Papilloma Virus and a subgroup of Head and Neck Squamous Cell Carcinomas (HNSCC). We evaluated the frequency of HPV positivity in HNSCC and its relationship to demographic and some risk factor variables in an open case- control study. Methods Fourteen recently diagnosed patients with squamous cell cancer of oropharynx, hypopharynx and larynx aged 18-50 years were examined from 2008-2010 in Tabriz, Iran. HPV DNA was extracted from paraffin-embedded blocks of each patient's sample for PCR evaluation. Saliva samples of 94 control cancer-free subjects were collected for DNA analysis. Multivariable logistic regression method was used to calculate odds ratio for case-control comparisons. Results High risk HPV was detected in 6(42.8%) patients, and 6(5.3%) control subjects which was statistically significant (p<0.0001). HPV-18 was the most frequent type both in the cases and controls. HPV-16 DNA was detected in two patients of the case group, but it was not detected in any of the controls. The relation between demographic and risk factor variables was not statistically significant. Conclusion HPV infection has a significant impact on HNSCC. Despite HPV-16 stronger impact, HPV-18 is more likely to cause malignant degeneration in such cancers amongst some communities. It is vital to introduce and conduct immunization schedules in health care systems to protect communities to some extent. PMID:25780535

  6. Defining Driver DNA Methylation Changes in Human Cancer

    Directory of Open Access Journals (Sweden)

    Gerd P. Pfeifer

    2018-04-01

    Full Text Available Human malignant tumors are characterized by pervasive changes in the patterns of DNA methylation. These changes include a globally hypomethylated tumor cell genome and the focal hypermethylation of numerous 5′-cytosine-phosphate-guanine-3′ (CpG islands, many of them associated with gene promoters. It has been challenging to link specific DNA methylation changes with tumorigenesis in a cause-and-effect relationship. Some evidence suggests that cancer-associated DNA hypomethylation may increase genomic instability. Promoter hypermethylation events can lead to silencing of genes functioning in pathways reflecting hallmarks of cancer, including DNA repair, cell cycle regulation, promotion of apoptosis or control of key tumor-relevant signaling networks. A convincing argument for a tumor-driving role of DNA methylation can be made when the same genes are also frequently mutated in cancer. Many of the most commonly hypermethylated genes encode developmental transcription factors, the methylation of which may lead to permanent gene silencing. Inactivation of such genes will deprive the cells in which the tumor may initiate from the option of undergoing or maintaining lineage differentiation and will lock them into a perpetuated stem cell-like state thus providing an additional window for cell transformation.

  7. Current status of immunologic studies in human lung cancer

    Energy Technology Data Exchange (ETDEWEB)

    Gross, R.L.

    1978-06-01

    Several aspects of the immunology of human malignancy are reviewed, with particular emphasis on relevant findings in lung cancer. The existence of tumor-specific cell-mediated immune responses in patients with cancer has been demonstrated in numerous tumor types. Of more relevance in clinical situations is the association of generalized immunologic depression with malignancy. In the vast majority of cases, progressive declines in both tumor-specific and nonspecific immunologic parameters are observed with advancing disease. The approach to the immunologic evaluation of cancer patients and the potential usefulness of this approach to the diagnosis, prognosis, management, and assessment of therapeutic response are discussed. Evidence aimed at elucidating the mechanism of immunosuppression in malignancy, such as serum-blocking factors, immunoregulatory alpha globulins, and suppressor cells, is presented. Finally, emphasis is placed on the various forms of immunotherapy, including both specific active methods such as tumor cell or tumor antigen vaccines and nonspecific active immunotherapy involving agents like Bacillus Calmette-Guerin and levamisole. Early results from clinical immunotherapeutic trials are discussed.

  8. Targeting telomerase and DNA repair in human cancers

    International Nuclear Information System (INIS)

    Prakash Hande, M.

    2014-01-01

    Telomerase reactivation is essential for telomere maintenance in human cancer cells ensuring indefinite proliferation. Targeting telomere homeostasis has become one of the promising strategies in the therapeutic management of tumours. One major potential drawback, however, is the time lag between telomerase inhibition and critically shortened telomeres triggering cell death, allowing cancer cells to acquire drug resistance. Numerous studies over the last decade have highlighted the role of DNA repair proteins such as Poly (ADP-Ribose) Polymerase-1 (PARP-1), and DNA-dependent protein kinase (DNA-PKcs) in the maintenance of telomere homoeostasis. Dysfunctional telomeres, resulting from the loss of telomeric DNA repeats or the loss of function of telomere-associated proteins trigger DNA damage responses similar to that observed for double strand breaks. We have been working on unravelling such synthetic lethality in cancer cells and this talk would be on one such recently concluded study that demonstrates that inhibition of DNA repair pathways, i.e., NHEJ pathway and that of telomerase could be an alternative strategy to enhance anti-tumour effects and circumvent the possibility of drug resistance. (author)

  9. Prolactin-inducible proteins in human breast cancer cells

    International Nuclear Information System (INIS)

    Shiu, R.P.; Iwasiow, B.M.

    1985-01-01

    The mechanism of action of prolactin in target cells and the role of prolactin in human breast cancer are poorly understood phenomena. The present study examines the effect of human prolactin (hPRL) on the synthesis of unique proteins by a human breast cancer cell line, T-47D, in serum-free medium containing bovine serum albumin. [ 35 S]Methionine-labeled proteins were analysed by sodium dodecyl sulfate-polyacrylamide slab gel electrophoresis and fluorography. Treatment of cells with hPRL (1-1000 ng/ml) and hydrocortisone (1 microgram/ml) for 36 h or longer resulted in the synthesis and secretion of three proteins having molecular weights of 11,000, 14,000, and 16,000. Neither hPRL nor hydrocortisone alone induced these proteins. Of several other peptide hormones tested, only human growth hormone, a hormone structurally and functionally similar to hPRL, could replace hPRL in causing protein induction. These three proteins were, therefore, referred to as prolactin-inducible proteins (PIP). Each of the three PIPs was purified to homogeneity by preparative sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and specific antibodies were generated to them in rabbits. By immunoprecipitation and immunoblotting (Western blot) of proteins secreted by T-47D cells, it was demonstrated that the three PIPs were immunologically identical to one another. In addition, the 16-kDa and 14-kDa proteins (PIP-16 and PIP-14), and not the 11-kDa protein (PIP-11), incorporated [ 3 H]glycosamine. Furthermore, 2-deoxyglucose (2 mM) and tunicamycin (0.5 micrograms/ml), two compounds known to inhibit glycosylation, blocked the production of PIP-16 and PIP-14, with a concomitant increase in the accumulation of PIP-11

  10. Roles of the Y chromosome genes in human cancers

    Directory of Open Access Journals (Sweden)

    Tatsuo Kido

    2015-06-01

    Full Text Available Male and female differ genetically by their respective sex chromosome composition, that is, XY as male and XX as female. Although both X and Y chromosomes evolved from the same ancestor pair of autosomes, the Y chromosome harbors male-specific genes, which play pivotal roles in male sex determination, germ cell differentiation, and masculinization of various tissues. Deletions or translocation of the sex-determining gene, SRY, from the Y chromosome causes disorders of sex development (previously termed as an intersex condition with dysgenic gonads. Failure of gonadal development results not only in infertility, but also in increased risks of germ cell tumor (GCT, such as gonadoblastoma and various types of testicular GCT. Recent studies demonstrate that either loss of Y chromosome or ectopic expression of Y chromosome genes is closely associated with various male-biased diseases, including selected somatic cancers. These observations suggest that the Y-linked genes are involved in male health and diseases in more frequently than expected. Although only a small number of protein-coding genes are present in the male-specific region of Y chromosome, the impacts of Y chromosome genes on human diseases are still largely unknown, due to lack of in vivo models and differences between the Y chromosomes of human and rodents. In this review, we highlight the involvement of selected Y chromosome genes in cancer development in men.

  11. [High oncogenic risk human papillomavirus and urinary bladder cancer].

    Science.gov (United States)

    Loran, O B; Sinyakova, L A; Gundorova, L V; Kosov, V A; Kosova, I V; Pogodina, I E; Kolbasov, D N

    2017-07-01

    To determine the role of human papillomavirus (HPV) of high oncogenic risk in the development of urinary bladder cancer. 100 patients (72 men and 28 women) aged 38 to 90 years (mean age 65+/-10 years) diagnosed with bladder cancer were examined and underwent treatment. Clinical assessment was complemented by enzyme-linked immunosorbent assays for the presence of antiviral antibodies to herpes simplex virus (HSV) type 1 and type 2, cytomegalovirus (CMV), Epstein-Barr virus (EBV), urethra scraping for detecting high oncogenic risk HPV. Tumor tissue was sampled for PCR virus detection. Semi-quantitative analysis was used to evaluate the components of lymphocyte-plasmocyte and leukocyte infiltrates and cytopathic changes in tumor tissue. There were positive correlations between cytopathic cell changes (koylocytosis and intranuclear inclusions, as manifestations of HPV) and the level of antiviral antibodies, the presence of viruses in the tumor, as well as with the components of the lymphoid-plasmocyte infiltrate. Negative correlations were found between the presence of papillomatosis and the above changes. Human papillomavirus is believed to be a trigger for the initiation of a tumor in young patients with a latent infection (CMV and EBV, HSV, HPV). Cytopathic changes (kylocytosis and intranuclear inclusions) were associated with the activity and morphological features of herpes-viral infections. Their degree varied depending on the stage of the process, but not on the anaplasia degree. Papillomatosis is associated with a more favorable course of the tumor process.

  12. Glyphosate induces human breast cancer cells growth via estrogen receptors.

    Science.gov (United States)

    Thongprakaisang, Siriporn; Thiantanawat, Apinya; Rangkadilok, Nuchanart; Suriyo, Tawit; Satayavivad, Jutamaad

    2013-09-01

    Glyphosate is an active ingredient of the most widely used herbicide and it is believed to be less toxic than other pesticides. However, several recent studies showed its potential adverse health effects to humans as it may be an endocrine disruptor. This study focuses on the effects of pure glyphosate on estrogen receptors (ERs) mediated transcriptional activity and their expressions. Glyphosate exerted proliferative effects only in human hormone-dependent breast cancer, T47D cells, but not in hormone-independent breast cancer, MDA-MB231 cells, at 10⁻¹² to 10⁻⁶M in estrogen withdrawal condition. The proliferative concentrations of glyphosate that induced the activation of estrogen response element (ERE) transcription activity were 5-13 fold of control in T47D-KBluc cells and this activation was inhibited by an estrogen antagonist, ICI 182780, indicating that the estrogenic activity of glyphosate was mediated via ERs. Furthermore, glyphosate also altered both ERα and β expression. These results indicated that low and environmentally relevant concentrations of glyphosate possessed estrogenic activity. Glyphosate-based herbicides are widely used for soybean cultivation, and our results also found that there was an additive estrogenic effect between glyphosate and genistein, a phytoestrogen in soybeans. However, these additive effects of glyphosate contamination in soybeans need further animal study. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Potential Therapeutic Roles of Tanshinone IIA in Human Bladder Cancer Cells

    Directory of Open Access Journals (Sweden)

    Sheng-Chun Chiu

    2014-09-01

    Full Text Available Tanshinone IIA (Tan-IIA, one of the major lipophilic components isolated from the root of Salviae Miltiorrhizae, has been found to exhibit anticancer activity in various cancer cells. We have demonstrated that Tan-IIA induces apoptosis in several human cancer cells through caspase- and mitochondria-dependent pathways. Here we explored the anticancer effect of Tan-IIA in human bladder cancer cell lines. Our results showed that Tan-IIA caused bladder cancer cell death in a time- and dose-dependent manner. Tan-IIA induced apoptosis through the mitochondria-dependent pathway in these bladder cancer cells. Tan-IIA also suppressed the migration of bladder cancer cells as revealed by the wound healing and transwell assays. Finally, combination therapy of Tan-IIA with a lower dose of cisplatin successfully killed bladder cancer cells, suggesting that Tan-IIA can serve as a potential anti-cancer agent in bladder cancer