Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found. PMID:28168295
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.
Zhang Michael Q
Full Text Available Abstract Background Although microarray-based studies have revealed global view of gene expression in cancer cells, we still have little knowledge about regulatory mechanisms underlying the transcriptome. Several computational methods applied to yeast data have recently succeeded in identifying expression modules, which is defined as co-expressed gene sets under common regulatory mechanisms. However, such module discovery methods are not applied cancer transcriptome data. Results In order to decode oncogenic regulatory programs in cancer cells, we developed a novel module discovery method termed EEM by extending a previously reported module discovery method, and applied it to breast cancer expression data. Starting from seed gene sets prepared based on cis-regulatory elements, ChIP-chip data, and gene locus information, EEM identified 10 principal expression modules in breast cancer based on their expression coherence. Moreover, EEM depicted their activity profiles, which predict regulatory programs in each subtypes of breast tumors. For example, our analysis revealed that the expression module regulated by the Polycomb repressive complex 2 (PRC2 is downregulated in triple negative breast cancers, suggesting similarity of transcriptional programs between stem cells and aggressive breast cancer cells. We also found that the activity of the PRC2 expression module is negatively correlated to the expression of EZH2, a component of PRC2 which belongs to the E2F expression module. E2F-driven EZH2 overexpression may be responsible for the repression of the PRC2 expression modules in triple negative tumors. Furthermore, our network analysis predicts regulatory circuits in breast cancer cells. Conclusion These results demonstrate that the gene set-based module discovery approach is a powerful tool to decode regulatory programs in cancer cells.
Hackett James R
Full Text Available Abstract Background Reverse transcription PCR (RT-PCR is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan® RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco typeDX™ assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis and the likelihood of tumor response to standard chemotherapy regimens (prediction. We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application. Results RNA was extracted from formalin fixed paraffin embedded (FPE tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan® reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery. Conclusion We have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of
and MPNSTs by determining whether these same genes are mutated in human tumors. 15. SUBJECT TERMS Nothing listed 16. SECURITY CLASSIFICATION OF: 17...sheath tumour (MPNST). In: Louis DNO, H.;Wiestler,O.D.;Cavenee,W.K., editor. WHO Classification of Tumours of the Central Nervous System. Lyon: IARC...Location Sex Major or Micro WHO Grade H6 DRG Male Major IV H9 Trigeminal ganglion Female Major III H17 Trigeminal ganglion Male Major II H19 Sciatic
Perry, Antoinette S
Aberrant activation of Wnts is common in human cancers, including prostate. Hypermethylation associated transcriptional silencing of Wnt antagonist genes SFRPs (Secreted Frizzled-Related Proteins) is a frequent oncogenic event. The significance of this is not known in prostate cancer. The objectives of our study were to (i) profile Wnt signaling related gene expression and (ii) investigate methylation of Wnt antagonist genes in prostate cancer. Using TaqMan Low Density Arrays, we identified 15 Wnt signaling related genes with significantly altered expression in prostate cancer; the majority of which were upregulated in tumors. Notably, histologically benign tissue from men with prostate cancer appeared more similar to tumor (r = 0.76) than to benign prostatic hyperplasia (BPH; r = 0.57, p < 0.001). Overall, the expression profile was highly similar between tumors of high (≥ 7) and low (≤ 6) Gleason scores. Pharmacological demethylation of PC-3 cells with 5-Aza-CdR reactivated 39 genes (≥ 2-fold); 40% of which inhibit Wnt signaling. Methylation frequencies in prostate cancer were 10% (2\\/20) (SFRP1), 64.86% (48\\/74) (SFRP2), 0% (0\\/20) (SFRP4) and 60% (12\\/20) (SFRP5). SFRP2 methylation was detected at significantly lower frequencies in high-grade prostatic intraepithelial neoplasia (HGPIN; 30%, (6\\/20), p = 0.0096), tumor adjacent benign areas (8.82%, (7\\/69), p < 0.0001) and BPH (11.43% (4\\/35), p < 0.0001). The quantitative level of SFRP2 methylation (normalized index of methylation) was also significantly higher in tumors (116) than in the other samples (HGPIN = 7.45, HB = 0.47, and BPH = 0.12). We show that SFRP2 hypermethylation is a common event in prostate cancer. SFRP2 methylation in combination with other epigenetic markers may be a useful biomarker of prostate cancer.
Fu, Junjie; Khaybullin, Ravil; Zhang, Yanping; Xia, Amy; Qi, Xin
In order to identify biomarkers involved in breast cancer, gene expression profiling was conducted using human breast cancer tissues. Total RNAs were extracted from 150 clinical patient tissues covering three breast cancer subtypes (Luminal A, Luminal B, and Triple negative) as well as normal tissues. The expression profiles of a total of 50,739 genes were established from a training set of 32 samples using the Agilent Sure Print G3 Human Gene Expression Microarray technology. Data were analyzed using Agilent Gene Spring GX 12.6 software. The expression of several genes was validated using real-time RT-qPCR. Data analysis with Agilent GeneSpring GX 12.6 software showed distinct expression patterns between cancer and normal tissue samples. A group of 28 promising genes were identified with ≥ 10-fold changes of expression level and p-values < 0.05. In particular, MMP11 and HPSE2 were closely examined due to the important roles they play in cancer cell growth and migration. Real-time RT-qPCR analyses of both training and testing sets validated the gene expression profiles of MMP11 and HPSE2. Our findings identified these 2 genes as a novel breast cancer biomarker gene set, which may facilitate the diagnosis and treatment in breast cancer clinical therapies
Tan, Aik Choon; Fan, Jian-Bing; Karikari, Collins; Bibikova, Marina; Garcia, Eliza Wickham; Zhou, Lixin; Barker, David; Serre, David; Feldmann, Georg; Hruban, Ralph H.; Klein, Alison P.; Goggins, Michael; Couch, Fergus J.; Hudson, Thomas J.; Winslow, Raimond L.
Physiologic allele-specific expression (ASE) in germline tissues occurs during random X-chromosome inactivation1 and in genomic imprinting,2 wherein the two alleles of a gene in a heterozygous individual are not expressed equally. Recent studies have confirmed the existence of ASE in apparently non-imprinted autosomal genes;3–14 however, the extent of ASE in the human genome is unknown. We explored ASE in lymphoblastoid cell lines of 145 individuals using an oligonucleotide array based assay....
Full Text Available Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches.
Palsule, Vrushalee; Coric, Dijana; Delancy, Russell; Dunham, Heather; Melancon, Caleb; Thompson, Dennis; Toms, Jamie; White, Ashley; Shultz, Jeffry
A clear understanding of basic gene structure is critical when teaching molecular genetics, the central dogma and the biological sciences. We sought to create a gene-based teaching project to improve students' understanding of gene structure and to integrate this into a research project that can be implemented by instructors at the secondary level…
Goonesekere, Nalin C W; Andersen, Wyatt; Smith, Alex; Wang, Xiaosheng
The lack of specific symptoms at early tumor stages, together with a high biological aggressiveness of the tumor contribute to the high mortality rate for pancreatic cancer (PC), which has a 5-year survival rate of about 7%. Recent failures of targeted therapies inhibiting kinase activity in clinical trials have highlighted the need for new approaches towards combating this deadly disease. In this study, we have identified genes that are significantly downregulated in PC, through a meta-analysis of large number of microarray datasets. We have used qRT-PCR to confirm the downregulation of selected genes in a panel of PC cell lines. This study has yielded several novel candidate tumor-suppressor genes (TSGs) including GNMT, CEL, PLA2G1B and SERPINI2. We highlight the role of GNMT, a methyl transferase associated with the methylation potential of the cell, and CEL, a lipase, as potential therapeutic targets. We have uncovered genetic links to risk factors associated with PC such as smoking and obesity. Genes important for patient survival and prognosis are also discussed, and we confirm the dysregulation of metabolic pathways previously observed in PC. While many of the genes downregulated in our dataset are associated with protein products normally produced by the pancreas for excretion, we have uncovered some genes whose downregulation appear to play a more causal role in PC. These genes will assist in providing a better understanding of the disease etiology of PC, and in the search for new therapeutic targets and biomarkers.
Chiche, L; Metairie, S
The prognosis of gallbladder cancer is basically dependent on the histological stage at diagnosis. In practice, the discovery of a small cancer of the bladder, generally during cholecystectomy give the patient a better care for curative treatment. The advent of laparoscopy has increased the number of cholecstectomies and could increase the frequency of this situation but also raises the difficult problem of metastatic dissemination. In the literature the figures on parietal metastasis after laparoscopy have ranged from 125% to 19%. The median delay to diagnosis of recurrence is 6 months. The cause of this phenomenon (role of the pneumoperitoneum) remains poorly elucidated. Risk factors for the development of a metastasis on the trocar orifice are: rupture of the gallbladder perioperatively and extraction of the gallbladder without protection. It is important to keep in mind this exceptional but serious risk and apply rigorous operative technique. In case of suspected gallbladder we do not advocate laparoscopy. Surgery (hepatectomy, lymphodenectomy, possibly resection of the biliary tract) would be indicted for all stages except pTis and T1a, taking into consideration the localization of the tumor and the patient's general status. It is also classical to recommend resection of the trocar orifices after laparoscopic cholecystectomy. There is a dual challenge today for small-sized gallbladder cancer: improving treatment and avoiding poorer prognosis due to the specific problems raised by laparoscopy.
I.. Zbar. B.. androle for the VHL gene in the development of hyperplasia in a number Lerman. I. I. Identification of the son Hippel-Lindau disease...of heterozy- gosity of chromosome 3p markers in small-cell lung cancer. Nature (Lond.). 329: eleguns produced hyperplasia in all tissues (26...central fibrovascular core lined by cuboidal tumor cells. Tumor weights were determined (Fig. 2d). At the end of 47 days after cells were
Prior to the 1950s, treatment for the majority of cancers was limited to either surgery or the use of radiation. The discovery of the use of methotrexate in curing a rare cancer marked the first time a cancer had been cured. This led to the development of many of today’s common cancer treatments.
de Burgos Nelia
Full Text Available Abstract Background Triatoma infestans is the most relevant vector of Chagas disease in the southern cone of South America. Since its genome has not yet been studied, sequencing of Expressed Sequence Tags (ESTs is one of the most powerful tools for efficiently identifying large numbers of expressed genes in this insect vector. Results In this work, we generated 826 ESTs, resulting in an increase of 47% in the number of ESTs available for T. infestans. These ESTs were assembled in 471 unique sequences, 151 of which represent 136 new genes for the Reduviidae family. Conclusions Among the putative new genes for the Reduviidae family, we identified and described an interesting subset of genes involved in development and reproduction, which constitute potential targets for insecticide development.
Full Text Available Immune response-related genes play a major role in colorectal carcinogenesis by mediating inflammation or immune-surveillance evasion. Although remarkable progress has been made to investigate the underlying mechanism, the understanding of the complicated carcinogenesis process was enormously hindered by large-scale tumor heterogeneity. Development and carcinogenesis share striking similarities in their cellular behavior and underlying molecular mechanisms. The association between embryonic development and carcinogenesis makes embryonic development a viable reference model for studying cancer thereby circumventing the potentially misleading complexity of tumor heterogeneity. Here we proposed that the immune genes, responsible for intra-immune cooperativity disorientation (defined in this study as disruption of developmental expression correlation patterns during carcinogenesis, probably contain untapped prognostic resource of colorectal cancer. In this study, we determined the mRNA expression profile of 137 human biopsy samples, including samples from different stages of human colonic development, colorectal precancerous progression and colorectal cancer samples, among which 60 were also used to generate miRNA expression profile. We originally established Spearman correlation transition model to quantify the cooperativity disorientation associated with the transition from normal to precancerous to cancer tissue, in conjunction with miRNA-mRNA regulatory network and machine learning algorithm to identify genes with prognostic value. Finally, a 12-gene signature was extracted, whose prognostic value was evaluated using Kaplan-Meier survival analysis in five independent datasets. Using the log-rank test, the 12-gene signature was closely related to overall survival in four datasets (GSE17536, n = 177, p = 0.0054; GSE17537, n = 55, p = 0.0039; GSE39582, n = 562, p = 0.13; GSE39084, n = 70, p = 0.11, and significantly associated with disease
Huber, Margit A; Kraut, Norbert
Discovery and translational research has led to the identification of a series of ?cancer drivers??genes that, when mutated or otherwise misregulated, can drive malignancy. An increasing number of drugs that directly target such drivers have demonstrated activity in clinical trials and are shaping a new landscape for molecularly targeted cancer therapies. Such therapies rely on molecular and genetic diagnostic tests to detect the presence of a biomarker that predicts response. Here, we highli...
Full Text Available Abstract Background The use of gene signatures can potentially be of considerable value in the field of clinical diagnosis. However, gene signatures defined with different methods can be quite various even when applied the same disease and the same endpoint. Previous studies have shown that the correct selection of subsets of genes from microarray data is key for the accurate classification of disease phenotypes, and a number of methods have been proposed for the purpose. However, these methods refine the subsets by only considering each single feature, and they do not confirm the association between the genes identified in each gene signature and the phenotype of the disease. We proposed an innovative new method termed Minimize Feature's Size (MFS based on multiple level similarity analyses and association between the genes and disease for breast cancer endpoints by comparing classifier models generated from the second phase of MicroArray Quality Control (MAQC-II, trying to develop effective meta-analysis strategies to transform the MAQC-II signatures into a robust and reliable set of biomarker for clinical applications. Results We analyzed the similarity of the multiple gene signatures in an endpoint and between the two endpoints of breast cancer at probe and gene levels, the results indicate that disease-related genes can be preferably selected as the components of gene signature, and that the gene signatures for the two endpoints could be interchangeable. The minimized signatures were built at probe level by using MFS for each endpoint. By applying the approach, we generated a much smaller set of gene signature with the similar predictive power compared with those gene signatures from MAQC-II. Conclusions Our results indicate that gene signatures of both large and small sizes could perform equally well in clinical applications. Besides, consistency and biological significances can be detected among different gene signatures, reflecting the
An international group of scientists has identified three genes that predispose Asian women who have never smoked to lung cancer. The discovery of specific genetic variations, which have not previously been associated with lung cancer risk in other popul
Kamanu, Timothy K.
MicroRNA (miRNA) are a class of small endogenous non-coding RNA that are mainly negative transcriptional and post-transcriptional regulators in both plants and animals. Recent studies have shown that miRNA are involved in different types of cancer and other incurable diseases such as autism and Alzheimer’s. Functional miRNAs are excised from hairpin-like sequences that are known as miRNA genes. There are about 21,000 known miRNA genes, most of which have been determined using experimental methods. miRNA genes are classified into different groups (miRNA families). This study reports about 19,000 unknown miRNA genes in nine species whereby approximately 15,300 predictions were computationally validated to contain at least one experimentally verified functional miRNA product. The predictions are based on a novel computational strategy which relies on miRNA family groupings and exploits the physics and geometry of miRNA genes to unveil the hidden palindromic signals and symmetries in miRNA gene sequences. Unlike conventional computational miRNA gene discovery methods, the algorithm developed here is species-independent: it allows prediction at higher accuracy and resolution from arbitrary RNA/DNA sequences in any species and thus enables examination of repeat-prone genomic regions which are thought to be non-informative or ’junk’ sequences. The information non-redundancy of uni-directional RNA sequences compared to information redundancy of bi-directional DNA is demonstrated, a fact that is overlooked by most pattern discovery algorithms. A novel method for computing upstream and downstream miRNA gene boundaries based on mathematical/statistical functions is suggested, as well as cutoffs for annotation of miRNA genes in different miRNA families. Another tool is proposed to allow hypotheses generation and visualization of data matrices, intra- and inter-species chromosomal distribution of miRNA genes or miRNA families. Our results indicate that: miRNA and mi
Full Text Available RNA editing is vital to provide the RNA and protein complexity to regulate the gene expression. Correct RNA editing maintains the cell function and organism development. Imbalance of the RNA editing machinery may lead to diseases and cancers. Recently, RNA editing has been recognized as a target for drug discovery although few studies targeting RNA editing for disease and cancer therapy were reported in the field of natural products. Therefore, RNA editing may be a potential target for therapeutic natural products. In this review, we provide a literature overview of the biological functions of RNA editing on gene expression, diseases, cancers, and drugs. The bioinformatics resources of RNA editing were also summarized.
Näätsaari, Laura; Krainer, Florian W; Schubert, Michael; Glieder, Anton; Thallinger, Gerhard G
Horseradish peroxidases (HRPs) from Armoracia rusticana have long been utilized as reporters in various diagnostic assays and histochemical stainings. Regardless of their increasing importance in the field of life sciences and suggested uses in medical applications, chemical synthesis and other industrial applications, the HRP isoenzymes, their substrate specificities and enzymatic properties are poorly characterized. Due to lacking sequence information of natural isoenzymes and the low levels of HRP expression in heterologous hosts, commercially available HRP is still extracted as a mixture of isoenzymes from the roots of A. rusticana. In this study, a normalized, size-selected A. rusticana transcriptome library was sequenced using 454 Titanium technology. The resulting reads were assembled into 14871 isotigs with an average length of 1133 bp. Sequence databases, ORF finding and ORF characterization were utilized to identify peroxidase genes from the 14871 isotigs generated by de novo assembly. The sequences were manually reviewed and verified with Sanger sequencing of PCR amplified genomic fragments, resulting in the discovery of 28 secretory peroxidases, 23 of them previously unknown. A total of 22 isoenzymes including allelic variants were successfully expressed in Pichia pastoris and showed peroxidase activity with at least one of the substrates tested, thus enabling their development into commercial pure isoenzymes. This study demonstrates that transcriptome sequencing combined with sequence motif search is a powerful concept for the discovery and quick supply of new enzymes and isoenzymes from any plant or other eukaryotic organisms. Identification and manual verification of the sequences of 28 HRP isoenzymes do not only contribute a set of peroxidases for industrial, biological and biomedical applications, but also provide valuable information on the reliability of the approach in identifying and characterizing a large group of isoenzymes.
Berretta, Regina; Moscato, Pablo
It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles
Yun Min Chang
Full Text Available Aptamers are single-stranded synthetic DNA- or RNA-based oligonucleotides that fold into various shapes to bind to a specific target, which includes proteins, metals, and molecules. Aptamers have high affinity and high specificity that are comparable to that of antibodies. They are obtained using iterative method, called (Systematic Evolution of Ligands by Exponential Enrichment SELEX and cell-based SELEX (cell-SELEX. Aptamers can be paired with recent advances in nanotechnology, microarray, microfluidics, and other technologies for applications in clinical medicine. One particular area that aptamers can shed a light on is biomarker discovery. Biomarkers are important in diagnosis and treatment of cancer. In this paper, we will describe ways in which aptamers can be used to discover biomarkers for cancer diagnosis and therapeutics.
Full Text Available Biomarker discovery can identify molecular markers in various cancers that can be used for detection, screening, diagnosis, and monitoring of disease progression. Lectin-affinity is a technique that can be used for the enrichment of glycoproteins from a complex sample, facilitating the discovery of novel cancer biomarkers associated with a disease state.
Barua, Sutapa; Ramos, James; Potta, Thrimoorthy; Taylor, David; Huang, Huang-Chiao; Montanez, Gabriela; Rege, Kaushal
Gene therapy is an attractive treatment option for diseases of genetic origin, including several cancers and cardiovascular diseases. While viruses are effective vectors for delivering exogenous genes to cells, concerns related to insertional mutagenesis, immunogenicity, lack of tropism, decay and high production costs necessitate the discovery of non-viral methods. Significant efforts have been focused on cationic polymers as non-viral alternatives for gene delivery. Recent studies have employed combinatorial syntheses and parallel screening methods for enhancing the efficacy of gene delivery, biocompatibility of the delivery vehicle, and overcoming cellular level barriers as they relate to polymer-mediated transgene uptake, transport, transcription, and expression. This review summarizes and discusses recent advances in combinatorial syntheses and parallel screening of cationic polymer libraries for the discovery of efficient and safe gene delivery systems. PMID:21843141
Li, Yupeng; Jackson, Scott A
Lu, Meixia; Zhang, Jinxiang; Zhang, Lanjing
Cancer biomarker discovery is a critical part of cancer prevention and treatment. Despite the decades of effort, only a small number of cancer biomarkers have been identified for and validated in clinical settings. Conceptual and methodological breakthroughs may help accelerate the discovery of additional cancer biomarkers, particularly their use for diagnostics. In this review, we have attempted to review the emerging concepts in cancer biomarker discovery, including real-world evidence, open access data, and data paucity in rare or uncommon cancers. We have also summarized the recent methodological progress in cancer biomarker discovery, such as high-throughput sequencing, liquid biopsy, big data, artificial intelligence (AI), and deep learning and neural networks. Much attention has been given to the methodological details and comparison of the methodologies. Notably, these concepts and methodologies interact with each other and will likely lead to synergistic effects when carefully combined. Newer, more innovative concepts and methodologies are emerging as the current emerging ones became mainstream and widely applied to the field. Some future challenges are also discussed. This review contributes to the development of future theoretical frameworks and technologies in cancer biomarker discovery and will contribute to the discovery of more useful cancer biomarkers.
Albuquerque, Marco A; Grande, Bruno M; Ritch, Elie J; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K; Shah, Sohrab P; Boutros, Paul C; Morin, Ryan D
The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. © The Author 2017. Published by Oxford University Press.
Álvarez-Chaver, Paula; Otero-Estévez, Olalla; Páez de la Cadena, María; Rodríguez-Berrocal, Francisco J; Martínez-Zorzano, Vicenta S
Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers. PMID:24744574
Olsen, Lars Rønn; Campos, Benito; Barnkob, Mike Stein
therapy target discovery in a bioinformatics analysis pipeline. We describe specialized bioinformatics tools and databases for three main bottlenecks in immunotherapy target discovery: the cataloging of potentially antigenic proteins, the identification of potential HLA binders, and the selection epitopes...
Background As genome-wide sequence analyses for complex human disease determinants are expanding, it is increasingly necessary to develop strategies to promote discovery and validation of potential disease-gene associations. Findings Here we present a dynamic web-based platform – GWATCH – that automates and facilitates four steps in genetic epidemiological discovery: 1) Rapid gene association search and discovery analysis of large genome-wide datasets; 2) Expanded visual display of gene associations for genome-wide variants (SNPs, indels, CNVs), including Manhattan plots, 2D and 3D snapshots of any gene region, and a dynamic genome browser illustrating gene association chromosomal regions; 3) Real-time validation/replication of candidate or putative genes suggested from other sources, limiting Bonferroni genome-wide association study (GWAS) penalties; 4) Open data release and sharing by eliminating privacy constraints (The National Human Genome Research Institute (NHGRI) Institutional Review Board (IRB), informed consent, The Health Insurance Portability and Accountability Act (HIPAA) of 1996 etc.) on unabridged results, which allows for open access comparative and meta-analysis. Conclusions GWATCH is suitable for both GWAS and whole genome sequence association datasets. We illustrate the utility of GWATCH with three large genome-wide association studies for HIV-AIDS resistance genes screened in large multicenter cohorts; however, association datasets from any study can be uploaded and analyzed by GWATCH. PMID:25374661
Gasser Robin B
Full Text Available Abstract Background Cholangiocarcinoma (CCA – cancer of the bile ducts – is associated with chronic infection with the liver fluke, Opisthorchis viverrini. Despite being the only eukaryote that is designated as a 'class I carcinogen' by the International Agency for Research on Cancer, little is known about its genome. Results Approximately 5,000 randomly selected cDNAs from the adult stage of O. viverrini were characterized and accounted for 1,932 contigs, representing ~14% of the entire transcriptome, and, presently, the largest sequence dataset for any species of liver fluke. Twenty percent of contigs were assigned GO classifications. Abundantly represented protein families included those involved in physiological functions that are essential to parasitism, such as anaerobic respiration, reproduction, detoxification, surface maintenance and feeding. GO assignments were well conserved in relation to other parasitic flukes, however, some categories were over-represented in O. viverrini, such as structural and motor proteins. An assessment of evolutionary relationships showed that O. viverrini was more similar to other parasitic (Clonorchis sinensis and Schistosoma japonicum than to free-living (Schmidtea mediterranea flatworms, and 105 sequences had close homologues in both parasitic species but not in S. mediterranea. A total of 164 O. viverrini contigs contained ORFs with signal sequences, many of which were platyhelminth-specific. Examples of convergent evolution between host and parasite secreted/membrane proteins were identified as were homologues of vaccine antigens from other helminths. Finally, ORFs representing secreted proteins with known roles in tumorigenesis were identified, and these might play roles in the pathogenesis of O. viverrini-induced CCA. Conclusion This gene discovery effort for O. viverrini should expedite molecular studies of cholangiocarcinogenesis and accelerate research focused on developing new interventions
Moggs, Jonathan G.; Goodman, Jay I.; Trosko, James E.; Roberts, Ruth A.
It is necessary to determine whether chemicals or drugs have the potential to pose a threat to human health. Research conducted over the last two decades has led to the paradigm that chemicals can cause cancer either by damaging DNA or by altering cellular growth, probably via receptor-mediated changes in gene expression. However, recent evidence suggests that gene expression can be altered markedly via several diverse epigenetic mechanisms that can lead to permanent or reversible changes in cellular behavior. Key molecular events underlying these mechanisms include the alteration of DNA methylation and chromatin, and changes in the function of cell surface molecules. Thus, for example, DNA methyltransferase enzymes together with chromatin-associated proteins such as histone modifying enzymes and remodelling factors can modify the genetic code and contribute to the establishment and maintenance of altered epigenetic states. This is relevant to many types of toxicity including but not limited to cancer. In this paper, we describe the potential for interplay between genetic alteration and epigenetic changes in cell growth regulation and discuss the implications for drug discovery and safety assessment
Zhang, Ping; Brusic, Vladimir
Mathematical modeling enables: the in silico classification of cancers, the prediction of disease outcomes, optimization of therapy, identification of promising drug targets and prediction of resistance to anticancer drugs. In silico pre-screened drug targets can be validated by a small number of carefully selected experiments. This review discusses the basics of mathematical modeling in cancer drug discovery and development. The topics include in silico discovery of novel molecular drug targets, optimization of immunotherapies, personalized medicine and guiding preclinical and clinical trials. Breast cancer has been used to demonstrate the applications of mathematical modeling in cancer diagnostics, the identification of high-risk population, cancer screening strategies, prediction of tumor growth and guiding cancer treatment. Mathematical models are the key components of the toolkit used in the fight against cancer. The combinatorial complexity of new drugs discovery is enormous, making systematic drug discovery, by experimentation, alone difficult if not impossible. The biggest challenges include seamless integration of growing data, information and knowledge, and making them available for a multiplicity of analyses. Mathematical models are essential for bringing cancer drug discovery into the era of Omics, Big Data and personalized medicine.
Tanzi, Rudolph E
The rich and colorful history of gene discovery in Alzheimer's disease (AD) over the past three decades is as complex and heterogeneous as the disease, itself. Twin and family studies indicate that genetic factors are estimated to play a role in at least 80% of AD cases. The inheritance of AD exhibits a dichotomous pattern. On one hand, rare mutations inAPP, PSEN1, and PSEN2 are fully penetrant for early-onset (95%) late-onset AD. These four genes account for 30-50% of the inheritability of AD. Genome-wide association studies have recently led to the identification of additional highly confirmed AD candidate genes. Here, I review the past, present, and future of attempts to elucidate the complex and heterogeneous genetic underpinnings of AD along with some of the unique events that made these discoveries possible.
Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander
While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.
Ashkani, Jahanshah; Naidoo, Kevin J.
Aberrant glycosylation in tumours stem from altered glycosyltransferase (GT) gene expression but can the expression profiles of these signature genes be used to classify cancer types and lead to cancer subtype discovery? The differential structural changes to cellular glycan structures are predominantly regulated by the expression patterns of GT genes and are a hallmark of neoplastic cell metamorphoses. We found that the expression of 210 GT genes taken from 1893 cancer patient samples in The Cancer Genome Atlas (TCGA) microarray data are able to classify six cancers; breast, ovarian, glioblastoma, kidney, colon and lung. The GT gene expression profiles are used to develop cancer classifiers and propose subtypes. The subclassification of breast cancer solid tumour samples illustrates the discovery of subgroups from GT genes that match well against basal-like and HER2-enriched subtypes and correlates to clinical, mutation and survival data. This cancer type glycosyltransferase gene signature finding provides foundational evidence for the centrality of glycosylation in cancer.
Hassani-Pak, Keywan; Castellote, Martin; Esch, Maria; Hindle, Matthew; Lysenko, Artem; Taubert, Jan; Rawlings, Christopher
The chances of raising crop productivity to enhance global food security would be greatly improved if we had a complete understanding of all the biological mechanisms that underpinned traits such as crop yield, disease resistance or nutrient and water use efficiency. With more crop genomes emerging all the time, we are nearer having the basic information, at the gene-level, to begin assembling crop gene catalogues and using data from other plant species to understand how the genes function and how their interactions govern crop development and physiology. Unfortunately, the task of creating such a complete knowledge base of gene functions, interaction networks and trait biology is technically challenging because the relevant data are dispersed in myriad databases in a variety of data formats with variable quality and coverage. In this paper we present a general approach for building genome-scale knowledge networks that provide a unified representation of heterogeneous but interconnected datasets to enable effective knowledge mining and gene discovery. We describe the datasets and outline the methods, workflows and tools that we have developed for creating and visualising these networks for the major crop species, wheat and barley. We present the global characteristics of such knowledge networks and with an example linking a seed size phenotype to a barley WRKY transcription factor orthologous to TTG2 from Arabidopsis, we illustrate the value of integrated data in biological knowledge discovery. The software we have developed (www.ondex.org) and the knowledge resources (http://knetminer.rothamsted.ac.uk) we have created are all open-source and provide a first step towards systematic and evidence-based gene discovery in order to facilitate crop improvement.
Today’s high-powered microscopes are allowing researchers to study the fine details of individual cells and to peer into cells, opening up new avenues of discovery about the inner workings of cells, including the events that can cause healthy cells to tra
Georg K Gerber
Full Text Available An important research problem in computational biology is the identification of expression programs, sets of co-expressed genes orchestrating normal or pathological processes, and the characterization of the functional breadth of these programs. The use of human expression data compendia for discovery of such programs presents several challenges including cellular inhomogeneity within samples, genetic and environmental variation across samples, uncertainty in the numbers of programs and sample populations, and temporal behavior. We developed GeneProgram, a new unsupervised computational framework based on Hierarchical Dirichlet Processes that addresses each of the above challenges. GeneProgram uses expression data to simultaneously organize tissues into groups and genes into overlapping programs with consistent temporal behavior, to produce maps of expression programs, which are sorted by generality scores that exploit the automatically learned groupings. Using synthetic and real gene expression data, we showed that GeneProgram outperformed several popular expression analysis methods. We applied GeneProgram to a compendium of 62 short time-series gene expression datasets exploring the responses of human cells to infectious agents and immune-modulating molecules. GeneProgram produced a map of 104 expression programs, a substantial number of which were significantly enriched for genes involved in key signaling pathways and/or bound by NF-kappaB transcription factors in genome-wide experiments. Further, GeneProgram discovered expression programs that appear to implicate surprising signaling pathways or receptor types in the response to infection, including Wnt signaling and neurotransmitter receptors. We believe the discovered map of expression programs involved in the response to infection will be useful for guiding future biological experiments; genes from programs with low generality scores might serve as new drug targets that exhibit minimal
Kocevar, Nina; Komel, Radovan
Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies. PMID:24550697
Armitage, Emily G; Barbas, Coral
Cancer is one of the most devastating human diseases that causes a vast number of mortalities worldwide each year. Cancer research is one of the largest fields in the life sciences and despite many astounding breakthroughs and contributions over the past few decades, there is still a considerable amount to unveil on the function of cancer. It is well known that cancer metabolism differs from that of normal tissue and an important hypothesis published in the 1950s by Otto Warburg proposed that cancer cells rely on anaerobic metabolism as the source for energy, even under physiological oxygen levels. Following this, cancer central carbon metabolism has been researched extensively and beyond respiration, cancer has been found to involve a wide range of metabolic processes, and many more are still to be unveiled. Studying cancer through metabolomics could reveal new biomarkers for cancer that could be useful for its future prognosis, diagnosis and therapy. Metabolomics is becoming an increasingly popular tool in the life sciences since it is a relatively fast and accurate technique that can be applied with either a particular focus or in a global manner to reveal new knowledge about biological systems. There have been many examples of its application to reveal potential biomarkers in different cancers that have employed a range of different analytical platforms. In this review, approaches in metabolomics that have been employed in cancer biomarker discovery are discussed and some of the most noteworthy research in the field is highlighted. Copyright © 2013 Elsevier B.V. All rights reserved.
Filichkin, Sergei; Etherington, Elizabeth; Ma, Caiping; Strauss, Steve
The goals of the S.H. Strauss laboratory portion of 'Genome-enabled discovery of carbon sequestration genes in poplar' are (1) to explore the functions of candidate genes using Populus transformation by inserting genes provided by Oakridge National Laboratory (ORNL) and the University of Florida (UF) into poplar; (2) to expand the poplar transformation toolkit by developing transformation methods for important genotypes; and (3) to allow induced expression, and efficient gene suppression, in roots and other tissues. As part of the transformation improvement effort, OSU developed transformation protocols for Populus trichocarpa 'Nisqually-1' clone and an early flowering P. alba clone, 6K10. Complete descriptions of the transformation systems were published (Ma et. al. 2004, Meilan et. al 2004). Twenty-one 'Nisqually-1' and 622 6K10 transgenic plants were generated. To identify root predominant promoters, a set of three promoters were tested for their tissue-specific expression patterns in poplar and in Arabidopsis as a model system. A novel gene, ET304, was identified by analyzing a collection of poplar enhancer trap lines generated at OSU (Filichkin et. al 2006a, 2006b). Other promoters include the pGgMT1 root-predominant promoter from Casuarina glauca and the pAtPIN2 promoter from Arabidopsis root specific PIN2 gene. OSU tested two induction systems, alcohol- and estrogen-inducible, in multiple poplar transgenics. Ethanol proved to be the more efficient when tested in tissue culture and greenhouse conditions. Two estrogen-inducible systems were evaluated in transgenic Populus, neither of which functioned reliably in tissue culture conditions. GATEWAY-compatible plant binary vectors were designed to compare the silencing efficiency of homologous (direct) RNAi vs. heterologous (transitive) RNAi inverted repeats. A set of genes was targeted for post transcriptional silencing in the model Arabidopsis system; these include the floral
Lu, Xinguo; Lu, Jibo
Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.
Constructing, evaluating, and interpreting gene networks generally sits within the broader field of systems biology, which continues to emerge rapidly, particular with respect to its application to understanding the complexity of signaling in the context of cancer biology. For the purposes of this volume, we take a broad definition of systems biology. Considering an organism or disease within an organism as a system, systems biology is the study of the integrated and coordinated interactions of the network(s) of genes, their variants both natural and mutated (e.g., polymorphisms, rearrangements, alternate splicing, mutations), their proteins and isoforms, and the organic and inorganic molecules with which they interact, to execute the biochemical reactions (e.g., as enzymes, substrates, products) that reflect the function of that system. Central to systems biology, and perhaps the only approach that can effectively manage the complexity of such systems, is the building of quantitative multiscale predictive models. The predictions of the models can vary substantially depending on the nature of the model and its inputoutput relationships. For example, a model may predict the outcome of a specific molecular reaction(s), a cellular phenotype (e.g., alive, dead, growth arrest, proliferation, and motility), a change in the respective prevalence of cell or subpopulations, a patient or patient subgroup outcome(s). Such models necessarily require computers. Computational modeling can be thought of as using machine learning and related tools to integrate the very high dimensional data generated from modern, high throughput omics technologies including genomics (next generation sequencing), transcriptomics (gene expression microarrays; RNAseq), metabolomics and proteomics (ultra high performance liquid chromatography, mass spectrometry), and "subomic" technologies to study the kinome, methylome, and others. Mathematical modeling can be thought of as the use of ordinary
Philippakis, Anthony A; Azzariti, Danielle R; Beltran, Sergi; Brookes, Anthony J; Brownstein, Catherine A; Brudno, Michael; Brunner, Han G; Buske, Orion J; Carey, Knox; Doll, Cassie; Dumitriu, Sergiu; Dyke, Stephanie O M; den Dunnen, Johan T; Firth, Helen V; Gibbs, Richard A; Girdea, Marta; Gonzalez, Michael; Haendel, Melissa A; Hamosh, Ada; Holm, Ingrid A; Huang, Lijia; Hurles, Matthew E; Hutton, Ben; Krier, Joel B; Misyura, Andriy; Mungall, Christopher J; Paschall, Justin; Paten, Benedict; Robinson, Peter N; Schiettecatte, François; Sobreira, Nara L; Swaminathan, Ganesh J; Taschner, Peter E; Terry, Sharon F; Washington, Nicole L; Züchner, Stephan; Boycott, Kym M; Rehm, Heidi L
There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow. © 2015 WILEY PERIODICALS, INC.
David E. Kang
Full Text Available Xenotropic murine leukemia virus-related virus (XMRV was first reported in 2006 in a study of human prostate cancer patients with genetic variants of the antiviral enzyme, RNase L. Subsequent investigations in North America, Europe, Asia, and Africa have either observed or failed to detect XMRV in patients (prostate cancer, chronic fatigue syndrome-myalgic encephalomyelitis (CFS-ME, and immunosuppressed with respiratory tract infections or normal, healthy, control individuals. The principal confounding factors are the near ubiquitous presence of mouse-derived reagents, antibodies and cells, and often XMRV itself, in laboratories. XMRV infects and replicates well in many human cell lines, but especially in certain prostate cancer cell lines. XMRV also traffics to prostate in a nonhuman primate model of infection. Here, we will review the discovery of XMRV and then focus on prostate cancer-related research involving this intriguing virus.
of a patient’s response to a particular treatment, thus helping to avoid unnecessary treatment and unwanted side effects in non-responding individuals.Currently biomarker discovery is facilitated by recent advances in high-throughput technologies when association between a given biological phenotype...... and the state or level of a large number of molecular entities is investigated. Such associative analysis could be confounded by several factors, leading to false discoveries. For example, it is assumed that with the exception of the true biomarkers most molecular entities such as gene expression levels show...... random distribution in a given cohort. However, gene expression levels may also be affected by technical bias when the actual measurement technology or sample handling may introduce a systematic error. If the distribution of systematic errors correlates with the biological phenotype then the risk...
Jose A Seoane
Full Text Available Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy and for testing multiple variants for association with a single phenotype (gene-based association tests. Such approaches can increase statistical power by combining evidence for association over multiple phenotypes or genetic variants respectively. Canonical Correlation Analysis (CCA measures the correlation between two sets of multidimensional variables, and thus offers the potential to combine these two approaches. To apply CCA, we must restrict the number of attributes relative to the number of samples. Hence we consider modules of genetic variation that can comprise a gene, a pathway or another biologically relevant grouping, and/or a set of phenotypes. In order to do this, we use an attribute selection strategy based on a binary genetic algorithm. Applied to a UK-based prospective cohort study of 4286 women (the British Women's Heart and Health Study, we find improved statistical power in the detection of previously reported genetic associations, and identify a number of novel pleiotropic associations between genetic variants and phenotypes. New discoveries include gene-based association of NSF with triglyceride levels and several genes (ACSM3, ERI2, IL18RAP, IL23RAP and NRG1 with left ventricular hypertrophy phenotypes. In multiple-phenotype analyses we find association of NRG1 with left ventricular hypertrophy phenotypes, fibrinogen and urea and pleiotropic relationships of F7 and F10 with Factor VII, Factor IX and cholesterol levels.
Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun
When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.
Peitzsch, Claudia; Kurth, Ina; Kunz-Schughart, Leoni; Baumann, Michael; Dubrovska, Anna
Tumors are known to be heterogeneous containing a dynamic mixture of phenotypically and functionally different tumor cells. The two concepts attempting to explain the origin of intratumor heterogeneity are the cancer stem cell hypothesis and the clonal evolution model. The stochastic model argues that tumors are biologically homogenous and all cancer cells within the tumor have equal ability to propagate the tumor growth depending on continuing mutations and selective pressure. By contrast, the stem cells model suggests that cancer heterogeneity is due to the hierarchy that originates from a small population of cancer stem cells (CSCs) which are biologically distinct from the bulk tumor and possesses self-renewal, tumorigenic and multilineage potential. Although these two hypotheses have been discussed for a long time as mutually exclusive explanations of tumor heterogeneity, they are easily reconciled serving as a driving force of cancer evolution and diversity. Recent discovery of the cancer cell plasticity and heterogeneity makes the CSC population a moving target that could be hard to track and eradicate. Understanding the signaling mechanisms regulating CSCs during the course of cancer treatment can be indispensable for the optimization of current treatment strategies
Cancer remains a leading cause of morbidity and mortality. Despite advances in understanding, detection, and treatment, it accounts for almost one-fourth of all deaths per year in Western countries. Prostate cancer is currently the most commonly diagnosed noncutaneous cancer in men in Europe and the United States, accounting for 15% of all cancers in men. As life expectancy of individuals increases, it is expected that there will also be an increase in the incidence and mortality of prostate cancer. Prostate cancer may be inoperable at initial presentation, unresponsive to chemotherapy and radiotherapy, or recur following appropriate treatment. At the time of presentation, patients may already have metastases in their tissues. Preventing tumor recurrence requires systemic therapy; however, current modalities are limited by toxicity or lack of efficacy. For patients with such metastatic cancers, the development of alternative therapies is essential. Gene therapy is a realistic prospect for the treatment of prostate and other cancers, and involves the delivery of genetic information to the patient to facilitate the production of therapeutic proteins. Therapeutics can act directly (eg, by inducing tumor cells to produce cytotoxic agents) or indirectly by upregulating the immune system to efficiently target tumor cells or by destroying the tumor\\'s vasculature. However, technological difficulties must be addressed before an efficient and safe gene medicine is achieved (primarily by developing a means of delivering genes to the target cells or tissue safely and efficiently). A wealth of research has been carried out over the past 20 years, involving various strategies for the treatment of prostate cancer at preclinical and clinical trial levels. The therapeutic efficacy observed with many of these approaches in patients indicates that these treatment modalities will serve as an important component of urological malignancy treatment in the clinic, either in isolation or
Birkenkamp-Demtroder, Karin; Christensen, Lise Lotte; Olesen, Sanne Harder
Understanding molecular alterations in colorectal cancer (CRC) is needed to define new biomarkers and treatment targets. We used oligonucleotide microarrays to monitor gene expression of about 6,800 known genes and 35,000 expressed sequence tags (ESTs) on five pools (four to six samples in each...... pool) of total RNA from left-sided sporadic colorectal carcinomas. We compared normal tissue to carcinoma tissue from Dukes' stages A-D (noninvasive to distant metastasis) and identified 908 known genes and 4,155 ESTs that changed remarkably from normal to tumor tissue. Based on intensive filtering 226...
We hypothesized that genes that are differentially expressed as a result of the decreased IGF-I receptor gene expression seen in metastatic prostate cancer contribute to prostate cancer progression...
Roberts, Charles T., Jr
We hypothesized that genes that are differentially expressed as a result of the decreased IGF-I receptor gene expression seen in metastatic prostate cancer contribute to prostate cancer progression...
Full Text Available Pediatric cancers differ from adult tumors, especially by their very low mutational rate. Therefore, their etiology could be explained in part by other oncogenic mechanisms such as chromosomal rearrangements, supporting the possible implication of fusion genes in the development of pediatric cancers. Fusion genes result from chromosomal rearrangements leading to the juxtaposition of two genes. Consequently, an abnormal activation of one or both genes is observed. The detection of fusion genes has generated great interest in basic cancer research and in the clinical setting, since these genes can lead to better comprehension of the biological mechanisms of tumorigenesis and they can also be used as therapeutic targets and diagnostic or prognostic biomarkers. In this review, we discuss the molecular mechanisms of fusion genes and their particularities in pediatric cancers, as well as their relevance in murine models and in the clinical setting. We also point out the difficulties encountered in the discovery of fusion genes. Finally, we discuss future perspectives and priorities for finding new innovative therapies in childhood cancer.
Toloza, Eric M; Morse, Michael A; Lyerly, H Kim
Lung cancer patients suffer a 15% overall survival despite advances in chemotherapy, radiation therapy, and surgery. This unacceptably low survival rate is due to the usual finding of advanced disease at diagnosis. However, multimodality strategies using conventional therapies only minimally improve survival rates even in early stages of lung cancer. Attempts to improve survival in advanced disease using various combinations of platinum-based chemotherapy have demonstrated that no regimen is superior, suggesting a therapeutic plateau and the need for novel, more specific, and less toxic therapeutic strategies. Over the past three decades, the genetic etiology of cancer has been gradually delineated, albeit not yet completely. Understanding the molecular events that occur during the multistep process of bronchogenic carcinogenesis may make these tasks more surmountable. During these same three decades, techniques have been developed which allow transfer of functional genes into mammalian cells. For example, blockade of activated tumor-promoting oncogenes or replacement of inactivated tumor-suppressing or apoptosis-promoting genes can be achieved by gene therapy. This article will discuss the therapeutic implications of these molecular changes associated with bronchogenic carcinomas and will then review the status of gene therapies for treatment of lung cancer. (c) 2006 Wiley-Liss, Inc.
Marcelo Bento Soares
In previous years, with support from the U.S. Department of Energy, we developed methods for construction of normalized and subtracted cDNA libraries, and constructed hundreds of high-quality libraries for production of Expressed Sequence Tags (ESTs). Our clones were made widely available to the scientific community through the IMAGE Consortium, and millions of ESTs were produced from our libraries either by collaborators or by our own sequencing laboratory at the University of Iowa. During this grant period, we focused on (1) the development of a method for preferential cloning of tissue-specific and/or rare transcripts, (2) its utilization to expedite EST-based gene discovery for the NIH Mouse Brain Molecular Anatomy Project, (3) further development and optimization of a method for construction of full-length-enriched cDNA libraries, and (4) modification of a plasmid vector to maximize efficiency of full-length cDNA sequencing by the transposon-mediated approach. It is noteworthy that the technology developed for preferential cloning of rare mRNAs enabled identification of over 2,000 mouse transcripts differentially expressed in the hippocampus. In addition, the method that we optimized for construction of full-length-enriched cDNA libraries was successfully utilized for the production of approximately fifty libraries from the developing mouse nervous system, from which over 2,500 full-ORF-containing cDNAs have been identified and accurately sequenced in their entirety either by our group or by the NIH-Mammalian Gene Collection Program Sequencing Team.
Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying
The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.
Full Text Available Drug repositioning is a popular approach in the pharmaceutical industry for identifying potential new uses for existing drugs and accelerating the development time. Non-small-cell lung cancer (NSCLC is one of the leading causes of death worldwide. To reduce the biological heterogeneity effects among different individuals, both normal and cancer tissues were taken from the same patient, hence allowing pairwise testing. By comparing early- and late-stage cancer patients, we can identify stage-specific NSCLC genes. Differentially expressed genes are clustered separately to form up- and downregulated communities that are used as queries to perform enrichment analysis. The results suggest that pathways for early- and late-stage cancers are different. Sets of up- and downregulated genes were submitted to the cMap web resource to identify potential drugs. To achieve high confidence drug prediction, multiple microarray experimental results were merged by performing meta-analysis. The results of a few drug findings are supported by MTT assay or clonogenic assay data. In conclusion, we have been able to assess the potential existing drugs to identify novel anticancer drugs, which may be helpful in drug repositioning discovery for NSCLC.
Qiu, Yushan; Shimada, Kazuaki; Hiraoka, Nobuyoshi; Maeshiro, Kensei; Ching, Wai-Ki; Aoki-Kinoshita, Kiyoko F; Furuta, Koh
Pancreatic cancer is a devastating disease and predicting the status of the patients becomes an important and urgent issue. The authors explore the applicability of inductive logic programming (ILP) method in the disease and show that the accumulated clinical laboratory data can be used to predict disease characteristics, and this will contribute to the selection of therapeutic modalities of pancreatic cancer. The availability of a large amount of clinical laboratory data provides clues to aid in the knowledge discovery of diseases. In predicting the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer, using the ILP model, three rules are developed that are consistent with descriptions in the literature. The rules that are identified are useful to detect the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer and therefore contributed significantly to the decision of therapeutic strategies. In addition, the proposed method is compared with the other typical classification techniques and the results further confirm the superiority and merit of the proposed method.
Prior to the discovery of cisplatin in 1965, men with testicular cancer had few medical options. Now, thanks to NCI research, cisplatin and similar chemotherapy drugs are known for curing testicular and other forms of cancer.
The objective of this CDA is to evaluate the gene-gene and gene-environment interactions in the etiology of breast cancer in two ongoing case-control studies, the Shanghai Breast Cancer Study (SBCS...
Joyce, Brian T; Zheng, Yinan; Zhang, Zhou; Liu, Lei; Kocherginsky, Masha; Murphy, Robert; Achenbach, Chad J; Musa, Jonah; Wehbe, Firas; Just, Allan; Shen, Jincheng; Vokonas, Pantel; Schwartz, Joel; Baccarelli, Andrea A; Hou, Lifang
Background: Dysregulation of miRNA and methylation levels are epigenetic hallmarks of cancer, potentially linked via miRNA-processing genes. Studies have found genetic alterations to miRNA-processing genes in cancer cells and human population studies. Our objective was to prospectively examine changes in DNA methylation of miRNA-processing genes and their associations with cancer risk. Methods: We examined cohort data from the Department of Veterans' Affairs Normative Aging Study. Participants were assessed every 3 to 5 years starting in 1999 through 2013 including questionnaires, medical record review, and blood collection. Blood from 686 consenting participants was analyzed using the Illumina 450K BeadChip array to measure methylation at CpG sites throughout the genome. We selected 19 genes based on a literature review, with 519 corresponding CpG sites. We then used Cox proportional hazards models to examine associations with cancer incidence, and generalized estimating equations to examine associations with cancer prevalence. Associations at false discovery rate time to cancer development (positively for cg06751583, inversely for cg23230564 and cg21034183), whereas methylation of one CpG site ( DROSHA : cg16131300) was positively associated with cancer prevalence. Conclusions: DNA methylation of DROSHA , a key miRNA-processing gene, and TNRC6B may play a role in early carcinogenesis. Impact: Changes in miRNA processing may exert multiple effects on cancer development, including protecting against it via altered global miRNAs, and may be a useful early detection biomarker of cancer. Cancer Epidemiol Biomarkers Prev; 27(5); 550-7. ©2018 AACR . ©2018 American Association for Cancer Research.
Full Text Available Novel drugs, drug sequences and combinations have improved the outcome of prostate cancer in recent years. The latest approvals include abiraterone acetate, enzalutamide and apalutamide which target androgen receptor (AR signaling, radium-223 dichloride for reduction of bone metastases, sipuleucel-T immunotherapy and taxane-based chemotherapy. Adding abiraterone acetate to androgen deprivation therapy (ADT in order to achieve complete androgen blockade has proven highly beneficial for treatment of locally advanced prostate cancer and metastatic hormone-sensitive prostate cancer (mHSPC. Also, ADT together with docetaxel treatment showed significant benefit in mHSPC. Ongoing clinical trials for different subgroups of prostate cancer patients include the evaluation of the second-generation AR antagonists enzalutamide, apalutamide and darolutamide, of inhibitors of the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K pathway, of inhibitors of DNA damage response, of targeted alpha therapy and of prostate-specific membrane antigen (PSMA targeting approaches. Advanced clinical studies with immune checkpoint inhibitors have shown limited benefits in prostate cancer and more trials are needed to demonstrate efficacy. The identification of improved, personalized treatments will be much supported by the major progress recently made in the molecular characterization of early- and late-stage prostate cancer using “omics” technologies. This has already led to novel classifications of prostate tumors based on gene expression profiles and mutation status, and should greatly help in the choice of novel targeted therapies best tailored to the needs of patients.
McGuire, Mary F.; Enderling, Heiko; Wallace, Dorothy I.; Batra, Jaspreet; Jordan, Marie; Kumar, Sushil; Panetta, John C.; Pasquier, Eddy
Although many clinicians and researchers work to understand cancer, there has been limited success to effectively combine forces and collaborate over time, distance, data and budget constraints. Here we present a workflow template for multidisciplinary cancer therapy that was developed during the 2nd Annual Workshop on Cancer Systems Biology sponsored by Tufts University, Boston, MA in July 2012. The template was applied to the development of a metronomic therapy backbone for neuroblastoma. Three primary groups were identified: clinicians, biologists, and scientists (mathematicians, computer scientists, physicists and engineers). The workflow described their integrative interactions; parallel or sequential processes; data sources and computational tools at different stages as well as the iterative nature of therapeutic development from clinical observations to in vitro, in vivo, and clinical trials. We found that theoreticians in dialog with experimentalists could develop calibrated and parameterized predictive models that inform and formalize sets of testable hypotheses, thus speeding up discovery and validation while reducing laboratory resources and costs. The developed template outlines an interdisciplinary collaboration workflow designed to systematically investigate the mechanistic underpinnings of a new therapy and validate that therapy to advance development and clinical acceptance. PMID:23955390
Full Text Available Controlled clinical trials are widely considered to be the vehicle to treatment discovery in cancer that leads to significant improvements in health outcomes including an increase in life expectancy. We have previously shown that the pattern of therapeutic discovery in randomized controlled trials (RCTs can be described by a power law distribution. However, the mechanism generating this pattern is unknown. Here, we propose an explanation in terms of the social relations between researchers in RCTs. We use social network analysis to study the impact of interactions between RCTs on treatment success. Our dataset consists of 280 phase III RCTs conducted by the NCI from 1955 to 2006. The RCT networks are formed through trial interactions formed i at random, ii based on common characteristics, or iii based on treatment success. We analyze treatment success in terms of survival hazard ratio as a function of the network structures. Our results show that the discovery process displays power law if there are preferential interactions between trials that may stem from researchers' tendency to interact selectively with established and successful peers. Furthermore, the RCT networks are "small worlds": trials are connected through a small number of ties, yet there is much clustering among subsets of trials. We also find that treatment success (improved survival is proportional to the network centrality measures of closeness and betweenness. Negative correlation exists between survival and the extent to which trials operate within a limited scope of information. Finally, the trials testing curative treatments in solid tumors showed the highest centrality and the most influential group was the ECOG. We conclude that the chances of discovering life-saving treatments are directly related to the richness of social interactions between researchers inherent in a preferential interaction model.
Full Text Available For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures—weighted rank-based Jaccard and Cosine measures—and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm—RANWAR—was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.
Mallik, Saurav; Zhao, Zhongming
For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.
Background The demand for novel molecularly targeted drugs will continue to rise as we move forward toward the goal of personalizing cancer treatment to the molecular signature of individual tumors. However, the identification of targets and combinations of targets that can be safely and effectively modulated is one of the greatest challenges facing the drug discovery process. A promising approach is to use biological networks to prioritize targets based on their relative positions to one another, a property that affects their ability to maintain network integrity and propagate information-flow. Here, we introduce influence networks and demonstrate how they can be used to generate influence scores as a network-based metric to rank genes as potential drug targets. Results We use this approach to prioritize genes as drug target candidates in a set of ER + breast tumor samples collected during the course of neoadjuvant treatment with the aromatase inhibitor letrozole. We show that influential genes, those with high influence scores, tend to be essential and include a higher proportion of essential genes than those prioritized based on their position (i.e. hubs or bottlenecks) within the same network. Additionally, we show that influential genes represent novel biologically relevant drug targets for the treatment of ER + breast cancers. Moreover, we demonstrate that gene influence differs between untreated tumors and residual tumors that have adapted to drug treatment. In this way, influence scores capture the context-dependent functions of genes and present the opportunity to design combination treatment strategies that take advantage of the tumor adaptation process. Conclusions Influence networks efficiently find essential genes as promising drug targets and combinations of targets to inform the development of molecularly targeted drugs and their use. PMID:24495353
behavioral teaching strategies and best practice for teaching students with autism spectrum disorders 4.52 Learn strategies for incorporating IEP goals...AFRL-SA-WP-TR-2013-0013 Comprehensive Clinical Phenotyping and Genetic Mapping for the Discovery of Autism Susceptibility Genes...Genetic Mapping for the Discovery of Autism Susceptibility Genes 5a. CONTRACT NUMBER N/A 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER N/A 6
San Lucas, F Anthony; Fowler, Jerry; Chang, Kyle; Kopetz, Scott; Vilar, Eduardo; Scheet, Paul
Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA. ©2014 American Association for Cancer Research.
Hall, Michael J; Forman, Andrea D; Pilarski, Robert; Wiesner, Georgia; Giri, Veda N
Next-generation sequencing technologies have ushered in the capability to assess multiple genes in parallel for genetic alterations that may contribute to inherited risk for cancers in families. Thus, gene panel testing is now an option in the setting of genetic counseling and testing for cancer risk. This article describes the many gene panel testing options clinically available to assess inherited cancer susceptibility, the potential advantages and challenges associated with various types of panels, clinical scenarios in which gene panels may be particularly useful in cancer risk assessment, and testing and counseling considerations. Given the potential issues for patients and their families, gene panel testing for inherited cancer risk is recommended to be offered in conjunction or consultation with an experienced cancer genetic specialist, such as a certified genetic counselor or geneticist, as an integral part of the testing process. Copyright © 2014 by the National Comprehensive Cancer Network.
Philippakis, A.A.; Azzariti, D.R.; Beltran, S.; Brookes, A.J.; Brownstein, C.A.; Brudno, M.; Brunner, H.G.; Buske, O.J.; Carey, K.; Doll, C.; Dumitriu, S.; Dyke, S.O.M.; Dunnen, J.T. den; Firth, H.V.; Gibbs, R.A.; Girdea, M.; Gonzalez, M.; Haendel, M.A.; Hamosh, A.; Holm, I.A.; Huang, L.; Hurles, M.E.; Hutton, B.; Krier, J.B.; Misyura, A.; Mungall, C.J.; Paschall, J.; Paten, B.; Robinson, P.N.; Schiettecatte, F.; Sobreira, N.L.; Swaminathan, G.J.; Taschner, P.E.M.; Terry, S.F.; Washington, N.L.; Zuchner, S.; Boycott, K.M.; Rehm, H.L.
There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of
Lee, Yuandan; Quackenbush, John
The TIGR Gene Index web pages provide access to analyses of ESTs and gene sequences for nearly 60 species, as well as a number of resources derived from these. Each species-specific database is presented using a common format with a homepage. A variety of methods exist that allow users to search each species-specific database. Methods implemented currently include nucleotide or protein sequence queries using WU-BLAST, text-based searches using various sequence identifiers, searches by gene, tissue and library name, and searches using functional classes through Gene Ontology assignments. This protocol provides guidance for using the Gene Index Databases to extract information.
Ahmed, Kamran A.; Davis, Brian J. [Department of Radiation Oncology, Mayo Clinic, Rochester, MN (United States); Wilson, Torrence M. [Department of Urology, Mayo Clinic, Rochester, MN (United States); Wiseman, Gregory A. [Division of Nuclear Medicine, Mayo Clinic, Rochester, MN (United States); Federspiel, Mark J. [Department of Molecular Medicine, Mayo Clinic, Rochester, MN (United States); Morris, John C., E-mail: firstname.lastname@example.org [Division of Endocrinology, Mayo Clinic, Rochester, MN (United States)
Gene therapy has held promise to correct various disease processes. Prostate cancer represents the second leading cause of cancer death in American men. A number of clinical trials involving gene therapy for the treatment of prostate cancer have been reported. The ability to efficiently transduce tumors with effective levels of therapeutic genes has been identified as a fundamental barrier to effective cancer gene therapy. The approach utilizing gene therapy in prostate cancer patients at our institution attempts to address this deficiency. The sodium-iodide symporter (NIS) is responsible for the ability of the thyroid gland to transport and concentrate iodide. The characteristics of the NIS gene suggest that it could represent an ideal therapeutic gene for cancer therapy. Published results from Mayo Clinic researchers have indicated several important successes with the use of the NIS gene and prostate gene therapy. Studies have demonstrated that transfer of the human NIS gene into prostate cancer using adenovirus vectors in vitro and in vivo results in efficient uptake of radioactive iodine and significant tumor growth delay with prolongation of survival. Preclinical successes have culminated in the opening of a phase I trial for patients with advanced prostate disease which is currently accruing patients. Further study will reveal the clinical promise of NIS gene therapy in the treatment of prostate as well as other malignancies.
Ahmed, Kamran A.; Davis, Brian J.; Wilson, Torrence M.; Wiseman, Gregory A.; Federspiel, Mark J.; Morris, John C.
Gene therapy has held promise to correct various disease processes. Prostate cancer represents the second leading cause of cancer death in American men. A number of clinical trials involving gene therapy for the treatment of prostate cancer have been reported. The ability to efficiently transduce tumors with effective levels of therapeutic genes has been identified as a fundamental barrier to effective cancer gene therapy. The approach utilizing gene therapy in prostate cancer patients at our institution attempts to address this deficiency. The sodium-iodide symporter (NIS) is responsible for the ability of the thyroid gland to transport and concentrate iodide. The characteristics of the NIS gene suggest that it could represent an ideal therapeutic gene for cancer therapy. Published results from Mayo Clinic researchers have indicated several important successes with the use of the NIS gene and prostate gene therapy. Studies have demonstrated that transfer of the human NIS gene into prostate cancer using adenovirus vectors in vitro and in vivo results in efficient uptake of radioactive iodine and significant tumor growth delay with prolongation of survival. Preclinical successes have culminated in the opening of a phase I trial for patients with advanced prostate disease which is currently accruing patients. Further study will reveal the clinical promise of NIS gene therapy in the treatment of prostate as well as other malignancies.
Gorlov, Ivan P; Logothetis, Christopher J; Sircar, Kanishka; Zhao, Hongya; Maity, Sankar N; Navone, Nora M; Gorlova, Olga Y; Troncoso, Patricia; Pettaway, Curtis A; Byun, Jin Young
The genetic control of prostate cancer development is poorly understood. Large numbers of gene-expression datasets on different aspects of prostate tumorigenesis are available. We used these data to identify and prioritize candidate genes associated with the development of prostate cancer and bone metastases. Our working hypothesis was that combining meta-analyses on different but overlapping steps of prostate tumorigenesis will improve identification of genes associated with prostate cancer development. A Z score-based meta-analysis of gene-expression data was used to identify candidate genes associated with prostate cancer development. To put together different datasets, we conducted a meta-analysis on 3 levels that follow the natural history of prostate cancer development. For experimental verification of candidates, we used in silico validation as well as in-house gene-expression data. Genes with experimental evidence of an association with prostate cancer development were overrepresented among our top candidates. The meta-analysis also identified a considerable number of novel candidate genes with no published evidence of a role in prostate cancer development. Functional annotation identified cytoskeleton, cell adhesion, extracellular matrix, and cell motility as the top functions associated with prostate cancer development. We identified 10 genes--CDC2, CCNA2, IGF1, EGR1, SRF, CTGF, CCL2, CAV1, SMAD4, and AURKA--that form hubs of the interaction network and therefore are likely to be primary drivers of prostate cancer development. By using this large 3-level meta-analysis of the gene-expression data to identify candidate genes associated with prostate cancer development, we have generated a list of candidate genes that may be a useful resource for researchers studying the molecular mechanisms underlying prostate cancer development
Tang, Suisheng; Tan, Sin Lam; Ramadoss, Suresh Kumar
Estrogen has a profound impact on human physiology and affects numerous genes. The classical estrogen reaction is mediated by its receptors (ERs), which bind to the estrogen response elements (EREs) in target gene's promoter region. Due to tedious and expensive experiments, a limited number of hu...
Kamanu, Timothy K.
and other incurable diseases such as autism and Alzheimer’s. Functional miRNAs are excised from hairpin-like sequences that are known as miRNA genes. There are about 21,000 known miRNA genes, most of which have been determined using experimental methods. mi
Navarro, Saúl Abenhamar; Carrillo, Esmeralda; Griñán-Lisón, Carmen; Martín, Ana; Perán, Macarena; Marchal, Juan Antonio; Boulaiz, Houria
Cancer is considered the second leading cause of death worldwide despite the progress made in early detection and advances in classical therapies. Advancing in the fight against cancer requires the development of novel strategies, and the suicide gene transfer to tumor cells is providing new possibilities for cancer therapy. In this manuscript, authors present an overview of suicide gene systems and the latest innovations done to enhance cancer suicide gene therapy strategies by i) improving vectors for targeted gene delivery using tissue specific promoter and receptors; ii) modification of the tropism; and iii) combining suicide genes and/or classical therapies for cancer. Finally, the authors highlight the main challenges to be addressed in the future. Even if many efforts are needed for suicide gene therapy to be a real alternative for cancer treatment, we believe that the significant progress made in the knowledge of cancer biology and characterization of cancer stem cells accompanied by the development of novel targeted vectors will enhance the effectiveness of this type of therapeutic strategy. Moreover, combined with current treatments, suicide gene therapy will improve the clinical outcome of patients with cancer in the future.
Porteous David J
Full Text Available Abstract Background Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning. Results We examined a variety of sequence-based features and found that for many of them there are significant differences between the sets of genes known to be involved in human hereditary disease and those not known to be involved in disease. We have created an automatic classifier called PROSPECTR based on those features using the alternating decision tree algorithm which ranks genes in the order of likelihood of involvement in disease. On average, PROSPECTR enriches lists for disease genes two-fold 77% of the time, five-fold 37% of the time and twenty-fold 11% of the time. Conclusion PROSPECTR is a simple and effective way to identify genes involved in Mendelian and oligogenic disorders. It performs markedly better than the single existing sequence-based classifier on novel data. PROSPECTR could save investigators looking at large regions of interest time and effort by prioritizing positional candidate genes for mutation detection and case-control association studies.
Full Text Available Abstract Background We have identified a set of genes whose relative mRNA expression levels in various solid tumors can be used to robustly distinguish cancer from matching normal tissue. Our current feature set consists of 113 gene probes for 104 unique genes, originally identified as differentially expressed in solid primary tumors in microarray data on Affymetrix HG-U133A platform in five tissue types: breast, colon, lung, prostate and ovary. For each dataset, we first identified a set of genes significantly differentially expressed in tumor vs. normal tissue at p-value = 0.05 using an experimentally derived error model. Our common cancer gene panel is the intersection of these sets of significantly dysregulated genes and can distinguish tumors from normal tissue on all these five tissue types. Methods Frozen tumor specimens were obtained from two commercial vendors Clinomics (Pittsfield, MA and Asterand (Detroit, MI. Biotinylated targets were prepared using published methods (Affymetrix, CA and hybridized to Affymetrix U133A GeneChips (Affymetrix, CA. Expression values for each gene were calculated using Affymetrix GeneChip analysis software MAS 5.0. We then used a software package called Genes@Work for differential expression discovery, and SVM light linear kernel for building classification models. Results We validate the predictability of this gene list on several publicly available data sets generated on the same platform. Of note, when analysing the lung cancer data set of Spira et al, using an SVM linear kernel classifier, our gene panel had 94.7% leave-one-out accuracy compared to 87.8% using the gene panel in the original paper. In addition, we performed high-throughput validation on the Dana Farber Cancer Institute GCOD database and several GEO datasets. Conclusions Our result showed the potential for this panel as a robust classification tool for multiple tumor types on the Affymetrix platform, as well as other whole genome arrays
Rigali, Sébastien; Anderssen, Sinaeda; Naômé, Aymeric; van Wezel, Gilles P
The World Health Organization (WHO) describes antibiotic resistance as "one of the biggest threats to global health, food security, and development today", as the number of multi- and pan-resistant bacteria is rising dangerously. Acquired resistance phenomena also impair antifungals, antivirals, anti-cancer drug therapy, while herbicide resistance in weeds threatens the crop industry. On the positive side, it is likely that the chemical space of natural products goes far beyond what has currently been discovered. This idea is fueled by genome sequencing of microorganisms which unveiled numerous so-called cryptic biosynthetic gene clusters (BGCs), many of which are transcriptionally silent under laboratory culture conditions, and by the fact that most bacteria cannot yet be cultivated in the laboratory. However, brute force antibiotic discovery does not yield the same results as it did in the past, and researchers have had to develop creative strategies in order to unravel the hidden potential of microorganisms such as Streptomyces and other antibiotic-producing microorganisms. Identifying the cis elements and their corresponding transcription factors(s) involved in the control of BGCs through bioinformatic approaches is a promising strategy. Theoretically, we are a few 'clicks' away from unveiling the culturing conditions or genetic changes needed to activate the production of cryptic metabolites or increase the production yield of known compounds to make them economically viable. In this opinion article, we describe and illustrate the idea beyond 'cracking' the regulatory code for natural product discovery, by presenting a series of proofs of concept, and discuss what still should be achieved to increase the rate of success of this strategy. Copyright © 2018 Elsevier Inc. All rights reserved.
Barzon, Luisa; Boscaro, Marco; Palù, Giorgio
The field of cancer gene therapy is in continuous expansion, and technology is quickly moving ahead as far as gene targeting and regulation of gene expression are concerned. This review focuses on the endocrine aspects of gene therapy, including the possibility to exploit hormone and hormone receptor functions for regulating therapeutic gene expression, the use of endocrine-specific genes as new therapeutic tools, the effects of viral vector delivery and transgene expression on the endocrine system, and the endocrine response to viral vector delivery. Present ethical concerns of gene therapy and the risk of germ cell transduction are also discussed, along with potential lines of innovation to improve cell and gene targeting.
Full Text Available Abstract Background The Signal-to-Noise-Ratio (SNR is often used for identification of biomarkers for two-class problems and no formal and useful generalization of SNR is available for multiclass problems. We propose innovative generalizations of SNR for multiclass cancer discrimination through introduction of two indices, Gene Dominant Index and Gene Dormant Index (GDIs. These two indices lead to the concepts of dominant and dormant genes with biological significance. We use these indices to develop methodologies for discovery of dominant and dormant biomarkers with interesting biological significance. The dominancy and dormancy of the identified biomarkers and their excellent discriminating power are also demonstrated pictorially using the scatterplot of individual gene and 2-D Sammon's projection of the selected set of genes. Using information from the literature we have shown that the GDI based method can identify dominant and dormant genes that play significant roles in cancer biology. These biomarkers are also used to design diagnostic prediction systems. Results and discussion To evaluate the effectiveness of the GDIs, we have used four multiclass cancer data sets (Small Round Blue Cell Tumors, Leukemia, Central Nervous System Tumors, and Lung Cancer. For each data set we demonstrate that the new indices can find biologically meaningful genes that can act as biomarkers. We then use six machine learning tools, Nearest Neighbor Classifier (NNC, Nearest Mean Classifier (NMC, Support Vector Machine (SVM classifier with linear kernel, and SVM classifier with Gaussian kernel, where both SVMs are used in conjunction with one-vs-all (OVA and one-vs-one (OVO strategies. We found GDIs to be very effective in identifying biomarkers with strong class specific signatures. With all six tools and for all data sets we could achieve better or comparable prediction accuracies usually with fewer marker genes than results reported in the literature using the
Sánchez, Daniel O.; Zandomeni, Ruben O.; Cravero, Silvio; Verdún, Ramiro E.; Pierrou, Ester; Faccio, Paula; Diaz, Gabriela; Lanzavecchia, Silvia; Agüero, Fernán; Frasch, Alberto C. C.; Andersson, Siv G. E.; Rossetti, Osvaldo L.; Grau, Oscar; Ugalde, Rodolfo A.
Brucella abortus is the etiological agent of brucellosis, a disease that affects bovines and human. We generated DNA random sequences from the genome of B. abortus strain 2308 in order to characterize molecular targets that might be useful for developing immunological or chemotherapeutic strategies against this pathogen. The partial sequencing of 1,899 clones allowed the identification of 1,199 genomic sequence surveys (GSSs) with high homology (BLAST expect value < 10−5) to sequences deposited in the GenBank databases. Among them, 925 represent putative novel genes for the Brucella genus. Out of 925 nonredundant GSSs, 470 were classified in 15 categories based on cellular function. Seven hundred GSSs showed no significant database matches and remain available for further studies in order to identify their function. A high number of GSSs with homology to Agrobacterium tumefaciens and Rhizobium meliloti proteins were observed, thus confirming their close phylogenetic relationship. Among them, several GSSs showed high similarity with genes related to nodule nitrogen fixation, synthesis of nod factors, nodulation protein symbiotic plasmid, and nodule bacteroid differentiation. We have also identified several B. abortus homologs of virulence and pathogenesis genes from other pathogens, including a homolog to both the Shda gene from Salmonella enterica serovar Typhimurium and the AidA-1 gene from Escherichia coli. Other GSSs displayed significant homologies to genes encoding components of the type III and type IV secretion machineries, suggesting that Brucella might also have an active type III secretion machinery. PMID:11159979
DAVIS J M
Plants utilize carbon by partitioning the reduced carbon obtained through photosynthesis into different compartments and into different chemistries within a cell and subsequently allocating such carbon to sink tissues throughout the plant. Since the phytohormones auxin and cytokinin are known to influence sink strength in tissues such as roots (Skoog & Miller 1957, Nordstrom et al. 2004), we hypothesized that altering the expression of genes that regulate auxin-mediated (e.g., AUX/IAA or ARF transcription factors) or cytokinin-mediated (e.g., RR transcription factors) control of root growth and development would impact carbon allocation and partitioning belowground (Fig. 1 - Renewal Proposal). Specifically, the ARF, AUX/IAA and RR transcription factor gene families mediate the effects of the growth regulators auxin and cytokinin on cell expansion, cell division and differentiation into root primordia. Invertases (IVR), whose transcript abundance is enhanced by both auxin and cytokinin, are critical components of carbon movement and therefore of carbon allocation. Thus, we initiated comparative genomic studies to identify the AUX/IAA, ARF, RR and IVR gene families in the Populus genome that could impact carbon allocation and partitioning. Bioinformatics searches using Arabidopsis gene sequences as queries identified regions with high degrees of sequence similarities in the Populus genome. These Populus sequences formed the basis of our transgenic experiments. Transgenic modification of gene expression involving members of these gene families was hypothesized to have profound effects on carbon allocation and partitioning.
Full Text Available Beside the well known nutritional and health benefits, strawberry (Fragaria X ananassa crop draws increasing attention as plant model system for the Rosaceae family, due to the short generation time, the rapid in vitro regeneration, and to the availability of the genome sequence of F. X ananassa and of the closely related F. vesca species. In the last years, the use of high-throughput sequence technologies provided large amounts of molecular information on the genes possibly related to several biological processes of this crop. Nevertheless, the function of most genes or gene products is still poorly understood and needs investigation. Transient transformation technology provides a powerful tool to study gene function in vivo, avoiding difficult drawbacks that typically affect the stable transformation protocols, such as transformation efficiency, transformants selection and regeneration. In this review we provide an overview of the use of transient expression in the investigation of the function of genes important for strawberry fruit development, defence and nutritional properties. The technical aspects related to an efficient use of this technique are described, and the possible impact and application in strawberry crop improvement are discussed.
Labaj, Wojciech; Papiez, Anna; Polanski, Andrzej; Polanska, Joanna
Large collections of data in studies on cancer such as leukaemia provoke the necessity of applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation of the voluminous MILE gene expression data set. Three analyses are accomplished, each for gaining a deeper understanding of the processes underlying leukaemia types and subtypes. First, the main disease groups are tested for differential expression against the healthy control as in a standard case-control study. Here, the basic knowledge on molecular mechanisms is confirmed quantitatively and by literature references. Second, pairwise comparison testing is performed for juxtaposing the main leukaemia types among each other. In this case by means of the Dice coefficient similarity measure the general relations are pointed out. Moreover, lists of candidate main leukaemia group biomarkers are proposed. Finally, with this approach being successful, the third analysis provides insight into all of the studied subtypes, followed by the emergence of four leukaemia subtype biomarkers. In addition, the class enhanced DEG signature obtained on the basis of novel pipeline processing leads to significantly better classification power of multi-class data classifiers. The developed methodology consisting of batch effect adjustment, adaptive noise and feature filtration coupled with adequate statistical testing and biomarker definition proves to be an effective approach towards knowledge discovery in high-throughput molecular biology experiments.
Protein-protein interactions (PPIs) mediate the transmission and regulation of oncogenic signals that are essential to cellular proliferation and survival, and thus represent potential targets for anti-cancer therapeutic discovery. Despite their significance, there is no method to experimentally disrupt and interrogate the essentiality of individual endogenous PPIs. The ability to computationally predict or infer PPI essentiality would help prioritize PPIs for drug discovery and help advance understanding of cancer biology.
Feng, Cai-ping; Mundy, J.
The present mini-review describes newer methods and strategies, including transposon and T-DNA insertions, TILLING, Deleteagene, and RNA interference, to functionally analyze genes of interest in the model plant Arabidopsis. The relative advantages and disadvantages of the systems are also discus...
Duffy, M J
Aberrant hypermethylation of promoter regions in specific genes is a key event in the formation and progression of cancer. In at least some situations, these aberrant alterations occur early in the formation of malignancy and appear to be tumour specific. Multiple reports have suggested that measurement of the methylation status of the promoter regions of specific genes can aid early detection of cancer, determine prognosis and predict therapy responses. Promising DNA methylation biomarkers include the use of methylated GSTP1 for aiding the early diagnosis of prostate cancer, methylated PITX2 for predicting outcome in lymph node-negative breast cancer patients and methylated MGMT in predicting benefit from alkylating agents in patients with glioblastomas. However, prior to clinical utilisation, these findings require validation in prospective clinical studies. Furthermore, assays for measuring gene methylation need to be standardised, simplified and evaluated in external quality assurance programmes. It is concluded that methylated genes have the potential to provide a new generation of cancer biomarkers.
Hassani-Pak, Keywan; Rawlings, Christopher
Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.
Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub-networks (modules). These discovered modules help to unravel the underlying mechanisms of the observed biological processes. While most of the existing module discovery methods use only the interaction data, in this work we propose, CLARM, which discovers biological modules by incorporating gene profiles data with protein-protein interaction networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional module discovery methods.
Kumar, Dhirendra; Mondal, Anupam Kumar; Yadav, Amit Kumar; Dash, Debasis
Proteogenomics involves the use of MS to refine annotation of protein-coding genes and discover genes in a genome. We carried out comprehensive proteogenomic analysis of Methylobacterium extorquens AM1 (ME-AM1) from publicly available proteomics data with a motive to improve annotation for methylotrophs; organisms capable of surviving in reduced carbon compounds such as methanol. Besides identifying 2482(50%) proteins, 29 new genes were discovered and 66 annotated gene models were revised in ME-AM1 genome. One such novel gene is identified with 75 peptides, lacks homolog in other methylobacteria but has glycosyl transferase and lipopolysaccharide biosynthesis protein domains, indicating its potential role in outer membrane synthesis. Many novel genes are present only in ME-AM1 among methylobacteria. Distant homologs of these genes in unrelated taxonomic classes and low GC-content of few genes suggest lateral gene transfer as a potential mode of their origin. Annotations of methylotrophy related genes were also improved by the discovery of a short gene in methylotrophy gene island and redefining a gene important for pyrroquinoline quinone synthesis, essential for methylotrophy. The combined use of proteogenomics and rigorous bioinformatics analysis greatly enhanced the annotation of protein-coding genes in model methylotroph ME-AM1 genome. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
.... Enhanced by the bystander effect, the specific expression of the DTA gene causes significant cell death in prostate cancer cell cultures, with very low background cell eradication in control cell lines...
Eaton, Keith D; Romine, Perrin E; Goodman, Gary E; Thornquist, Mark D; Barnett, Matt J; Petersdorf, Effie W
Chronic inflammation has been implicated in carcinogenesis, with increasing evidence of its role in lung cancer. We aimed to evaluate the role of genetic polymorphisms in inflammation-related genes in the risk for development of lung cancer. A nested case-control study design was used, and 625 cases and 625 well-matched controls were selected from participants in the β-Carotene and Retinol Efficacy Trial, which is a large, prospective lung cancer chemoprevention trial. The association between lung cancer incidence and survival and 23 polymorphisms descriptive of 11 inflammation-related genes (interferon gamma gene [IFNG], interleukin 10 gene [IL10], interleukin 1 alpha gene [IL1A], interleukin 1 beta gene [IL1B], interleukin 2 gene [IL2], interleukin 4 receptor gene [IL4R], interleukin 4 gene [IL4], interleukin 6 gene [IL6], prostaglandin-endoperoxide synthase 2 gene [PTGS2] (also known as COX2), transforming growth factor beta 1 gene [TGFB1], and tumor necrosis factor alpha gene [TNFA]) was evaluated. Of the 23 polymorphisms, two were associated with risk for lung cancer. Compared with individuals with the wild-type (CC) variant, individuals carrying the minor allele variants of the IL-1β-511C>T promoter polymorphism (rs16944) (CT and TT) had decreased odds of lung cancer (OR = 0.74, [95% confidence interval (CI): 0.58-0.94] and OR = 0.71 [95% CI: 0.50-1.01], respectively, p = 0.03). Similar results were observed for the IL-1β-1464 C>G promoter polymorphism (rs1143623), with presence of the minor variants CG and CC having decreased odds of lung cancer (OR = 0.75 [95% CI: 0.59-0.95] and OR = 0.69 [95% CI: 0.46-1.03], respectively, p = 0.03). Survival was not influenced by genotype. This study provides further evidence that IL1B promoter polymorphisms may modulate the risk for development of lung cancer. Copyright © 2018 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.
Carpenter, Richard L.; Lo, Hui-Wen
Since its discovery, the STAT3 transcription factor has been extensively studied for its function as a transcriptional regulator and its role as a mediator of development, normal physiology, and pathology of many diseases, including cancers. These efforts have uncovered an array of genes that can be positively and negatively regulated by STAT3, alone and in cooperation with other transcription factors. Through regulating gene expression, STAT3 has been demonstrated to play a pivotal role in many cellular processes including oncogenesis, tumor growth and progression, and stemness. Interestingly, recent studies suggest that STAT3 may behave as a tumor suppressor by activating expression of genes known to inhibit tumorigenesis. Additional evidence suggested that STAT3 may elicit opposing effects depending on cellular context and tumor types. These mixed results signify the need for a deeper understanding of STAT3, including its upstream regulators, parallel transcription co-regulators, and downstream target genes. To help facilitate fulfilling this unmet need, this review will be primarily focused on STAT3 downstream target genes that have been validated to associate with tumorigenesis and/or malignant biology of human cancers
Win, Aung Ko; Jenkins, Mark A.; Dowty, James G.; Antoniou, Antonis C.; Lee, Andrew; Giles, Graham G.; Buchanan, Daniel D.; Clendenning, Mark; Rosty, Christophe; Ahnen, Dennis J.; Thibodeau, Stephen N.; Casey, Graham; Gallinger, Steven; Le Marchand, Loïc; Haile, Robert W.; Potter, John D.; Zheng, Yingye; Lindor, Noralane M.; Newcomb, Polly A.; Hopper, John L.; MacInnis, Robert J.
Background While high-risk mutations in identified major susceptibility genes (DNA mismatch repair genes and MUTYH) account for some familial aggregation of colorectal cancer, their population prevalence and the causes of the remaining familial aggregation are not known. Methods We studied the families of 5,744 colorectal cancer cases (probands) recruited from population cancer registries in the USA, Canada and Australia and screened probands for mutations in mismatch repair genes and MUTYH. We conducted modified segregation analyses using the cancer history of first-degree relatives, conditional on the proband’s age at diagnosis. We estimated the prevalence of mutations in the identified genes, the prevalence of and hazard ratio for unidentified major gene mutations, and the variance of the residual polygenic component. Results We estimated that 1 in 279 of the population carry mutations in mismatch repair genes (MLH1= 1 in 1946, MSH2= 1 in 2841, MSH6= 1 in 758, PMS2= 1 in 714), 1 in 45 carry mutations in MUTYH, and 1 in 504 carry mutations associated with an average 31-fold increased risk of colorectal cancer in unidentified major genes. The estimated polygenic variance was reduced by 30–50% after allowing for unidentified major genes and decreased from 3.3 for age colorectal cancer. Impact Our findings could aid gene discovery and development of better colorectal cancer risk prediction models. PMID:27799157
Whetten, R. W.; Sederoff, R. R.; Kinlaw, C.; Retzel, E.
Integration of pines into the large scope of plant biology research depends on study of pines in parallel with study of annual plants, and on availability of research materials from pine to plant biologists interested in comparing pine with annual plant systems. The objectives of the Pine Gene Discovery Project were to obtain 10,000 partial DNA sequences of genes expressed in loblolly pine, to determine which of those pine genes were similar to known genes from other organisms, and to make the DNA sequences and isolated pine genes available to plant researchers to stimulate integration of pines into the wider scope of plant biology research. Those objectives have been completed, and the results are available to the public. Requests for pine genes have been received from a number of laboratories that would otherwise not have included pine in their research, indicating that progress is being made toward the goal of integrating pine research into the larger molecular biology research community
Full Text Available Abstract Background Technological leaps in genome sequencing have resulted in a surge in discovery of human disease genes. These discoveries have led to increased clarity on the molecular pathology of disease and have also demonstrated considerable overlap in the genetic roots of human diseases. In light of this large genetic overlap, we tested whether cross-disease research approaches lead to faster, more impactful discoveries. Methods We leveraged several gene-disease association databases to calculate a Mutual Citation Score (MCS for 10,853 pairs of genetically related diseases to measure the frequency of cross-citation between research fields. To assess the importance of cooperative research, we computed an Individual Disease Cooperation Score (ICS and the average publication rate for each disease. Results For all disease pairs with one gene in common, we found that the degree of genetic overlap was a poor predictor of cooperation (r2=0.3198 and that the vast majority of disease pairs (89.56% never cited previous discoveries of the same gene in a different disease, irrespective of the level of genetic similarity between the diseases. A fraction (0.25% of the pairs demonstrated cross-citation in greater than 5% of their published genetic discoveries and 0.037% cross-referenced discoveries more than 10% of the time. We found strong positive correlations between ICS and publication rate (r2=0.7931, and an even stronger correlation between the publication rate and the number of cross-referenced diseases (r2=0.8585. These results suggested that cross-disease research may have the potential to yield novel discoveries at a faster pace than singular disease research. Conclusions Our findings suggest that the frequency of cross-disease study is low despite the high level of genetic similarity among many human diseases, and that collaborative methods may accelerate and increase the impact of new genetic discoveries. Until we have a better
Verstraeten, Aline; Alaerts, Maaike; Van Laer, Lut; Loeys, Bart
Marfan syndrome (MFS) is a rare, autosomal-dominant, multisystem disorder, presenting with skeletal, ocular, skin, and cardiovascular symptoms. Significant clinical overlap with other systemic connective tissue diseases, including Loeys-Dietz syndrome (LDS), Shprintzen-Goldberg syndrome (SGS), and the MASS phenotype, has been documented. In MFS and LDS, the cardiovascular manifestations account for the major cause of patient morbidity and mortality, rendering them the main target for therapeutic intervention. Over the past decades, gene identification studies confidently linked the aforementioned syndromes, as well as nonsyndromic aneurysmal disease, to genetic defects in proteins related to the transforming growth factor (TGF)-β pathway, greatly expanding our knowledge on the disease mechanisms and providing us with novel therapeutic targets. As a result, the focus of the developing pharmacological treatment strategies is shifting from hemodynamic stress management to TGF-β antagonism. In this review, we discuss the insights that have been gained in the molecular biology of MFS and related disorders over the past 25 years. © 2016 WILEY PERIODICALS, INC.
Lumniczky, K.; Safrany, G.
Cancer gene therapy is a new, promising therapeutic agent. In the clinic, it should be used in combination with existing modalities, such as tumour irradiation. First, we summarise the most important fields of cancer gene therapy: gene directed enzyme pro-drug therapy; the activation of an anti-tumour immune attack; restoration of the wild type p53 status; the application of new, replication competent and oncolytic viral vectors; tumour specific, as well as radiation- and hypoxia-induced gene expression. Special emphasizes are put on the combined effect of these modalities with local tumour irradiation. Using the available vector systems, only a small portion of the cancer cells will contain the therapeutic genes under therapeutic situations. Bystander cell killing might contribute to the success of various gene therapy protocols. We summarise the evidences that lethal bystander effects may occur during cancer gene therapy. Bystander effects are especially important in the gene directed enzyme pro-drug therapy. There, bystander cell killing might have different routes: cell communication through gap junction intercellular contacts; release of toxic metabolites into the neighbourhood or to larger distances; phagocytosis of apoptotic bodies; and the activation of the immune system. Bystander cell killing can be enhanced by the introduction of gap junction proteins into the cells, by further activating the immune system with immune-stimulatory molecules, or by introducing genes into the cells that help the transfer of cytotoxic genes and / or metabolites into the bystander cells. In conclusion, there should be additional improvements in cancer gene therapy for the more efficient clinical application. (orig.)
In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.
Sekar, Thillai V; Paulmurugan, Ramasamy
Gene-directed enzyme prodrug therapy (GDEPT) is a promising therapeutic approach for treating cancers of various phenotypes. This strategy is independent of various other chemotherapeutic drugs used for treating cancers where the drugs are mainly designed to target endogenous cellular mechanisms, which are different in various cancer subtypes. In GDEPT an external enzyme, which is different from the cellular proteins, is expressed to convert the injected prodrug in to a toxic metabolite, that normally kill cancer cells express this protein. Theranostic imaging is an approach used to directly monitor the expression of these gene therapy enzymes while evaluating therapeutic effect. We recently developed a dual-GDEPT system where we combined mutant human herpes simplex thymidine kinase (HSV1sr39TK) and E. coli nitroreductase (NTR) enzyme, to improve therapeutic efficiency of cancer gene therapy by simultaneously injecting two prodrugs at a lower dose. In this approach we use two different prodrugs such as ganciclovir (GCV) and CB1954 to target two different cellular mechanisms to kill cancer cells. The developed dual GDEPT system was highly efficacious than that of either of the system used independently. In this chapter, we describe the complete protocol involved for in vitro and in vivo imaging of therapeutic cancer gene therapy evaluation.
Newhauser, Wayne D; Scheurer, Michael E; Faupel-Badger, Jessica M; Clague, Jessica; Weitzel, Jeffrey; Woods, Kendra V
As part of a 2-day conference on October 15 and 16, 2009, a nine-member task force composed of scientists, clinicians, educators, administrators, and students from across the USA was formed to discuss research, discovery, and technology obstacles to progress in cancer prevention and control, specifically those related to the cancer prevention workforce. This article summarizes the task force's findings on the current state of the cancer prevention workforce in this area and its needs for the future. The task force identified two types of barriers impeding the current cancer prevention workforce in research, discovery, and technology from reaching its fullest potential: (1) limited cross-disciplinary research opportunities with underutilization of some disciplines is hampering discovery and research in cancer prevention, and (2) new research avenues are not being investigated because technology development and implementation are lagging. Examples of impediments and desired outcomes are provided in each of these areas. Recommended solutions to these problems are based on the goals of enhancing the current cancer prevention workforce and accelerating the pace of discovery and clinical translation.
teaching students with autism spectrum disorders 4.52 Learn strategies for incorporating IEP goals and district standard into daily teaching...W403 Columbus, OH 43205 Final Report Comprehensive Clinical Phenotyping & Genetic Mapping for the Discovery of Autism Susceptibility Genes...QFOXGHDUHDFRGH 1.0 Summary In 2006, the Central Ohio Registry for Autism (CORA) was initiated as a collaboration between Wright-Patterson Air
Celis, Julio E; Moreira, José M A; Gromova, Irina
, promise to have a major impact on the way breast cancer will be diagnosed, treated and monitored in the future. Here we present a brief report on long-term ongoing strategies at the Danish Centre for Translational Breast Cancer Research to search for markers for early detection and targets for therapeutic...
Full Text Available Approximately one-third of individuals diagnosed with colorectal cancer have a family history of cancer, suggesting that CRCs may result from a heritable component. Despite the availability of current gene-identification techniques, only 5% of all CRCs emerge from well-identifiable inherited causes for predisposition, including polyposis and nonpolyposis syndromes. Hereditary nonpolyposis colorectal cancer represents a large proportion of cases, and robustly affected patients are at increased risk for early onset, synchronous, and metachronous colorectal malignancies and extracolonic malignancies. HNPCC encompasses several cancer syndromes, such as Lynch syndrome, Lynch-like syndrome, and familial colorectal cancer type X, which have remarkable clinical presentations and overlapping genetic profiles that make clinical diagnosis a challenging task. Therefore, distinguishing between the HNPCC disorders is crucial for physicians as an approach to tailor different recommendations for patients and their at-risk family members according to the risks for colonic and extracolonic cancer associated with each syndrome. Identification of these potential patients through epidemiological characteristics and new genetic testing can estimate the individual risk, which informs appropriate cancer screening, surveillance, and/or treatment strategies. In the past three years, many appealing and important advances have been made in our understanding of the relationship between HNPCC and CRC-associated syndromes. The knowledge from the genetic profile of cancer syndromes and unique genotype-phenotype profiles in the different syndromes has changed our cognition. Therefore, this review presents and discusses HNPCC and several common nonpolyposis syndromes with respect to molecular phenotype, histopathologic features, and clinical presentation.
Potter, Jared W; Jones, Kevin B; Barrott, Jared J
Sarcoma is a rare tumor type that occurs most frequently in connective tissue. Despite its uncommon occurrence, sarcoma research has provided the means for groundbreaking research that has advanced our understanding of general cancer mechanisms. It is through sarcoma research that the pioneering efforts of cancer immunotherapy were explored, that we understand the inherent genetic nature of cancer mutations, and that we appreciate the subclassification of general cancer types to make more accurate prognoses. This review explores the brief history of sarcoma research and what sarcomas can still teach us about the future of cancer research, especially in regard to novel immunotherapy targets, the role of epigenetics in disease progression and chemoresistance, and the benefits of more focused clinical trials. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
Fehrmann, Rudolf S. N.; Karjalainen, Juha M.; Krajewska, Malgorzata
Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gen...
Full Text Available Abstract Background The Dachshund homolog 2 (DACH2 gene has been implicated in development of the female genital tract in mouse models and premature ovarian failure syndrome, but to date, its expression in human normal and cancerous tissue remains unexplored. Using the Human Protein Atlas as a tool for cancer biomarker discovery, DACH2 protein was found to be differentially expressed in epithelial ovarian cancer (EOC. Here, the expression and prognostic significance of DACH2 was further evaluated in ovarian cancer cell lines and human EOC samples. Methods Immunohistochemical expression of DACH2 was examined in tissue microarrays with 143 incident EOC cases from two prospective, population-based cohorts, including a subset of benign-appearing fallopian tubes (n = 32. A nuclear score (NS, i.e. multiplier of staining fraction and intensity, was calculated. For survival analyses, cases were dichotomized into low (NS 3 using classification and regression tree analysis. Kaplan Meier analysis and Cox proportional hazards modelling were used to assess the impact of DACH2 expression on survival. DACH2 expression was analysed in the cisplatin sensitive ovarian cancer cell line A2780 and its cisplatin resistant derivative A2780-Cp70. The specificity of the DACH2 antibody was tested using siRNA-mediated silencing of DACH2 in A2780-Cp70 cells. Results DACH2 expression was considerably higher in the cisplatin resistant A2780-Cp70 cells compared to the cisplatin-sensitive A2780 cells. While present in all sampled fallopian tubes, DACH2 expression ranged from negative to strong in EOC. In EOC, DACH2 expression correlated with several proteins involved in DNA integrity and repair, and proliferation. DACH2 expression was significantly higher in carcinoma of the serous subtype compared to non-serous carcinoma. In the full cohort, high DACH2 expression was significantly associated with poor prognosis in univariable analysis, and in carcinoma of the serous subtype
Full Text Available To explore the patterns of gene expression in gastric cancer, a total of 26 paired gastric cancer and noncancerous tissues from patients were enrolled for gene expression microarray analyses. Limma methods were applied to analyze the data, and genes were considered to be significantly differentially expressed if the False Discovery Rate (FDR value was 2. Subsequently, Gene Ontology (GO categories were used to analyze the main functions of the differentially expressed genes. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG database, we found pathways significantly associated with the differential genes. Gene-Act network and co-expression network were built respectively based on the relationships among the genes, proteins and compounds in the database. 2371 mRNAs and 350 lncRNAs considered as significantly differentially expressed genes were selected for the further analysis. The GO categories, pathway analyses and the Gene-Act network showed a consistent result that up-regulated genes were responsible for tumorigenesis, migration, angiogenesis and microenvironment formation, while down-regulated genes were involved in metabolism. These results of this study provide some novel findings on coding RNAs, lncRNAs, pathways and the co-expression network in gastric cancer which will be useful to guide further investigation and target therapy for this disease.
Janos L. Tanyi; Nathalie Scholler
The development of comprehensive strategies for biomarker discovery of gynecological cancers is needed. The unique physiology of the female genital track revolves around ovulatory cycles ending by the proteolysis of the endometrium triggered by progesterone decline during the last part of the luteal phase. Building on the known link between incessant ovulation and ovarian cancer, we hypothesize that life-long menstruations could damage neighboring organs such as fallopian tubes, ovaries and p...
Kar, Siddhartha P; Adler, Emily; Tyrer, Jonathan
BACKGROUND: Genome-wide association studies (GWAS) have identified 18 loci associated with serous ovarian cancer (SOC) susceptibility but the biological mechanisms driving these findings remain poorly characterised. Germline cancer risk loci may be enriched for target genes of transcription factors...... (TFs) critical to somatic tumorigenesis. METHODS: All 615 TF-target sets from the Molecular Signatures Database were evaluated using gene set enrichment analysis (GSEA) and three GWAS for SOC risk: discovery (2196 cases/4396 controls), replication (7035 cases/21 693 controls; independent from discovery...... to interact with PAX8 in the literature to the PAX8-target set and applying an alternative to GSEA, interval enrichment, further confirmed this association (P=0.006). Fifteen of the 157 genes from this expanded PAX8 pathway were near eight loci associated with SOC risk at P
Full Text Available Analysis of fusion transcripts has become increasingly important due to their link with cancer development. Since high-throughput sequencing approaches survey fusion events exhaustively, several computational methods for the detection of gene fusions from RNA-seq data have been developed. This kind of analysis, however, is complicated by native trans-splicing events, the splicing-induced complexity of the transcriptome and biases and artefacts introduced in experiments and data analysis. There are a number of tools available for the detection of fusions from RNA-seq data; however, certain differences in specificity and sensitivity between commonly used approaches have been found. The ability to detect gene fusions of different types, including isoform fusions and fusions involving non-coding regions, has not been thoroughly studied yet. Here, we propose a novel computational toolkit called InFusion for fusion gene detection from RNA-seq data. InFusion introduces several unique features, such as discovery of fusions involving intergenic regions, and detection of anti-sense transcription in chimeric RNAs based on strand-specificity. Our approach demonstrates superior detection accuracy on simulated data and several public RNA-seq datasets. This improved performance was also evident when evaluating data from RNA deep-sequencing of two well-established prostate cancer cell lines. InFusion identified 26 novel fusion events that were validated in vitro, including alternatively spliced gene fusion isoforms and chimeric transcripts that include intergenic regions. The toolkit is freely available to download from http:/bitbucket.org/kokonech/infusion.
Yang, Haixuan; Seoighe, Cathal
Nonnegative Matrix Factorization (NMF) has proved to be an effective method for unsupervised clustering analysis of gene expression data. By the nonnegativity constraint, NMF provides a decomposition of the data matrix into two matrices that have been used for clustering analysis. However, the decomposition is not unique. This allows different clustering results to be obtained, resulting in different interpretations of the decomposition. To alleviate this problem, some existing methods directly enforce uniqueness to some extent by adding regularization terms in the NMF objective function. Alternatively, various normalization methods have been applied to the factor matrices; however, the effects of the choice of normalization have not been carefully investigated. Here we investigate the performance of NMF for the task of cancer class discovery, under a wide range of normalization choices. After extensive evaluations, we observe that the maximum norm showed the best performance, although the maximum norm has not previously been used for NMF. Matlab codes are freely available from: http://maths.nuigalway.ie/~haixuanyang/pNMF/pNMF.htm.
Brunner, Nils; Duffy, M.J; Napieralski, R.
Aberrant hypermethylation of promoter regions in specific genes is a key event in the formation and progression of cancer. In at least some situations, these aberrant alterations occur early in the formation of malignancy and appear to be tumour specific. Multiple reports have suggested that meas......Aberrant hypermethylation of promoter regions in specific genes is a key event in the formation and progression of cancer. In at least some situations, these aberrant alterations occur early in the formation of malignancy and appear to be tumour specific. Multiple reports have suggested...... that measurement of the methylation status of the promoter regions of specific genes can aid early detection of cancer, determine prognosis and predict therapy responses. Promising DNA methylation biomarkers include the use of methylated GSTP1 for aiding the early diagnosis of prostate cancer, methylated PITX2...... for predicting outcome in lymph node-negative breast cancer patients and methylated MGMT in predicting benefit from alkylating agents in patients with glioblastomas. However, prior to clinical utilisation, these findings require validation in prospective clinical studies. Furthermore, assays for measuring gene...
Wang, Hui; Shi, Tujin; Qian, Wei-Jun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D.; Rodland, Karin D.; Camp, David G.
Mass spectrometry-based proteomics has become an indispensable tool in biomedical research with broad applications ranging from fundamental biology, systems biology, and biomarker discovery. Recent advances in LC-MS have made it become a major technology in clinical applications, especially in cancer biomarker discovery and verification. To overcome the challenges associated with the analysis of clinical samples, such as extremely wide dynamic range of protein concentrations in biofluids and the need to perform high throughput and accurate quantification, significant efforts have been devoted to improve the overall performance of LC-MS bases clinical proteomics. In this review, we summarize the recent advances in LC-MS in the aspect of cancer biomarker discovery and quantification, and discuss its potentials, limitations, and future perspectives.
Ross-Adams, H.; Lamb, A.D.; Dunning, M.J.; Halim, S.; Lindberg, J.; Massie, C.M.; Egevad, L.A.; Russell, R.; Ramos-Montoya, A.; Vowler, S.L.; Sharma, N.L.; Kay, J.; Whitaker, H.; Clark, J.; Hurst, R.; Gnanapragasam, V.J.; Shah, N.C.; Warren, A.Y.; Cooper, C.S.; Lynch, A.G.; Stark, R.; Mills, I.G.; Grönberg, H.; Neal, D.E.
Background Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome. Methods In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone. Findings We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene
Celis, Julio E; Gromov, Pavel; Gromova, Irina
The application of state-of-the-art proteomics and functional genomics technologies to the study of cancer is rapidly shifting toward the analysis of clinically relevant samples derived from patients, as the ultimate aim of translational research is to bring basic discoveries closer to the bedside...
Filges, Isabel; Friedman, Jan M
Massively parallel sequencing has revolutionized our understanding of Mendelian disorders, and many novel genes have been discovered to cause disease phenotypes when mutant. At the same time, next-generation sequencing approaches have enabled non-invasive prenatal testing of free fetal DNA in maternal blood. However, little attention has been paid to using whole exome and genome sequencing strategies for gene identification in fetal disorders that are lethal in utero, because they can appear to be sporadic and Mendelian inheritance may be missed. We present challenges and advantages of applying next-generation sequencing approaches to gene discovery in fetal malformation phenotypes and review recent successful discovery approaches. We discuss the implication and significance of recessive inheritance and cross-species phenotyping in fetal lethal conditions. Whole exome sequencing can be used in individual families with undiagnosed lethal congenital anomaly syndromes to discover causal mutations, provided that prior to data analysis, the fetal phenotype can be correlated to a particular developmental pathway in embryogenesis. Cross-species phenotyping allows providing further evidence for causality of discovered variants in genes involved in those extremely rare phenotypes and will increase our knowledge about normal and abnormal human developmental processes. Ultimately, families will benefit from the option of early prenatal diagnosis. © 2014 John Wiley & Sons, Ltd.
Kirk, Jon; Shah, Nirav; Noll, Braxton; Stevens, Craig B; Lawler, Marshall; Mougeot, Farah B; Mougeot, Jean-Luc C
Oral mucositis (OM) is a major dose-limiting side effect of chemotherapy and radiation used in cancer treatment. Due to the complex nature of OM, currently available drug-based treatments are of limited efficacy. Our objectives were (i) to determine genes and molecular pathways associated with OM and wound healing using computational tools and publicly available data and (ii) to identify drugs formulated for topical use targeting the relevant OM molecular pathways. OM and wound healing-associated genes were determined by text mining, and the intersection of the two gene sets was selected for gene ontology analysis using the GeneCodis program. Protein interaction network analysis was performed using STRING-db. Enriched gene sets belonging to the identified pathways were queried against the Drug-Gene Interaction database to find drug candidates for topical use in OM. Our analysis identified 447 genes common to both the "OM" and "wound healing" text mining concepts. Gene enrichment analysis yielded 20 genes representing six pathways and targetable by a total of 32 drugs which could possibly be formulated for topical application. A manual search on ClinicalTrials.gov confirmed no relevant pathway/drug candidate had been overlooked. Twenty-five of the 32 drugs can directly affect the PTGS2 (COX-2) pathway, the pathway that has been targeted in previous clinical trials with limited success. Drug discovery using in silico text mining and pathway analysis tools can facilitate the identification of existing drugs that have the potential of topical administration to improve OM treatment.
Agarwal, D; Pineda, S; Michailidou, K
Background:Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying...... genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium.Methods:Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry......, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression.Results:Little evidence of association with breast cancer risk...
OhEigeartaigh, Sean S
Abstract Background In standard BLAST searches, no information other than the sequences of the query and the database entries is considered. However, in situations where two genes from different species have only borderline similarity in a BLAST search, the discovery that the genes are located within a region of conserved gene order (synteny) can provide additional evidence that they are orthologs. Thus, for interpreting borderline search results, it would be useful to know whether the syntenic context of a database hit is similar to that of the query. This principle has often been used in investigations of particular genes or genomic regions, but to our knowledge it has never been implemented systematically. Results We made use of the synteny information contained in the Yeast Gene Order Browser database for 11 yeast species to carry out a systematic search for protein-coding genes that were overlooked in the original annotations of one or more yeast genomes but which are syntenic with their orthologs. Such genes tend to have been overlooked because they are short, highly divergent, or contain introns. The key features of our software - called SearchDOGS - are that the database entries are classified into sets of genomic segments that are already known to be orthologous, and that very weak BLAST hits are retained for further analysis if their genomic location is similar to that of the query. Using SearchDOGS we identified 595 additional protein-coding genes among the 11 yeast species, including two new genes in Saccharomyces cerevisiae. We found additional genes for the mating pheromone a-factor in six species including Kluyveromyces lactis. Conclusions SearchDOGS has proven highly successful for identifying overlooked genes in the yeast genomes. We anticipate that our approach can be adapted for study of further groups of species, such as bacterial genomes. More generally, the concept of doing sequence similarity searches against databases to which external
Full Text Available Alternative pre-mRNA splicing is a crucial process that allows the generation of diversified RNA and protein products from a multi-exon gene. In tumor cells, this mechanism can facilitate cancer development and progression through both creating oncogenic isoforms and reducing the expression of normal or controllable protein species. We recently demonstrated that an alternative cyclin D-binding myb-like transcription factor 1 (DMTF1 pre-mRNA splicing isoform, DMTF1β, is increasingly expressed in breast cancer and promotes mammary tumorigenesis in a transgenic mouse model. Aberrant pre-mRNA splicing is a typical event occurring for many cancer-related functional proteins. In this review, we introduce general aberrant pre-mRNA splicing in cancers and discuss its therapeutic application using our recent discovery of the oncogenic DMTF1 isoform as an example. We also summarize new insights in designing novel targeting strategies of cancer therapies based on the understanding of deregulated pre-mRNA splicing mechanisms.
Full Text Available One of the most powerful ways to develop hypotheses regarding the biological functions of conserved genes in a given species, such as humans, is to first look at what is known about their function in another species. Model organism databases and other resources are rich with functional information but difficult to mine. Gene2Function addresses a broad need by integrating information about conserved genes in a single online resource.
Full Text Available Oral cancer is the sixth most common cancer in the world. Oral cancer is the cancer of the oral cavity and pharynx, including cancer of the lip, tongue, salivary glands, gum, floor and other areas of the mouth. The aim of the study is to identify SNPs using dbSNP and predict the effect of mutation using Predict SNP. The association of genes is done by STRING. The disease and drugs associated with the genes are obtained from Webgestalt. The prediction of binding site is done by CASTp. The interaction of ligand and protein is done by using Autodock and Visualised through Discovery studio, pymol, Ligplot. From this report we found that oral cancer differs from person to person based on their genes and genetic interactions and expressions which recommend the clinicians to go for personalized medicine rather that generalized medicine for the patients with oral cancer. Seeking the importance of genetic background of oral cancer patients further studies can be done by mining of non-synonymous SNPs associated with genes for causing oral cancer.
Schenk, E.; Essand, M.; Bangma, Ch. H.; Barber, Ch.; Behr, J.-P.; Briggs, S.; Carlisle, R.; Cheng, W.-S.; Danielsson, A.; Dautzenberg, I. J. C.; Dzojic, H.; Erbacher, P.; Fisher, K.; Frazier, A.; Georgopoulos, L. J.; Hoeben, R.; Kochanek, S.; Koppers-Lalic, D.; Kraaij, R.; Kreppel, F.; Lindholm, L.; Magnusson, M.; Maitland, N.; Neuberg, P.; Nilsson, B.; Ogris, M.; Remy, J.-S.; Scaife, M.; Schooten, E.; Seymour, L.; Totterman, T.; Uil, T. G.; Ulbrich, Karel; Veldhoven-Zweistra, J. L. M.; de Vrij, J.; van Weerden, W.; Wagner, E.; Willemsen, R.
Roč. 21, č. 7 (2010), s. 807-813 ISSN 1043-0342 EU Projects: European Commission(XE) 512087 - GIANT Keywords : adenovirus * gene delivery * prostate cancer Subject RIV: CD - Macromolecular Chemistry Impact factor: 4.829, year: 2010
Biewenga, Petra; Buist, Marrije R.; Moerland, Perry D.; van Thernaat, Emiel Ver Loren; van Kampen, Antoine H. C.; ten Kate, Fiebo J. W.; Baas, Frank
Objective. Pelvic lymph node metastases are the main prognostic factor for survival in early stage cervical cancer, yet accurate detection methods before surgery are lacking. In this study, we examined whether gene expression profiling can predict the presence of lymph node metastasis in early stage
Full Text Available Abstract Background There is growing evidence that gene-gene interactions are ubiquitous in determining the susceptibility to common human diseases. The investigation of such gene-gene interactions presents new statistical challenges for studies with relatively small sample sizes as the number of potential interactions in the genome can be large. Breast cancer provides a useful paradigm to study genetically complex diseases because commonly occurring single nucleotide polymorphisms (SNPs may additively or synergistically disturb the system-wide communication of the cellular processes leading to cancer development. Methods In this study, we systematically studied SNP-SNP interactions among 19 SNPs from 18 key genes involved in major cancer pathways in a sample of 398 breast cancer cases and 372 controls from Ontario. We discuss the methodological issues associated with the detection of SNP-SNP interactions in this dataset by applying and comparing three commonly used methods: the logistic regression model, classification and regression trees (CART, and the multifactor dimensionality reduction (MDR method. Results Our analyses show evidence for several simple (two-way and complex (multi-way SNP-SNP interactions associated with breast cancer. For example, all three methods identified XPD-[Lys751Gln]*IL10-[G(-1082A] as the most significant two-way interaction. CART and MDR identified the same critical SNPs participating in complex interactions. Our results suggest that the use of multiple statistical approaches (or an integrated approach rather than a single methodology could be the best strategy to elucidate complex gene interactions that have generally very different patterns. Conclusion The strategy used here has the potential to identify complex biological relationships among breast cancer genes and processes. This will lead to the discovery of novel biological information, which will improve breast cancer risk management.
Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella
Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.
Full Text Available Identification and elucidation of functions of plant genes is valuable for both basic and applied research. In addition to natural variation in model plants, numerous loss-of-function resources have been produced by mutagenesis with chemicals, irradiation, or insertions of transposable elements or T-DNA. However, we may be unable to observe loss-of-function phenotypes for genes with functionally redundant homologs, and for those essential for growth and development. To offset such disadvantages, gain-of-function transgenic resources have been exploited. Activation-tagged lines have been generated using obligatory overexpression of endogenous genes by random insertion of an enhancer. Recent progress in DNA sequencing technology and bioinformatics has enabled the preparation of genomewide collections of full-length cDNAs (fl-cDNAs in some model species. Using the fl-cDNA clones, a novel gain-of-function strategy, Fl-cDNA OvereXpressor gene (FOX-hunting system, has been developed. A mutant phenotype in a FOX line can be directly attributed to the overexpressed fl-cDNA. Investigating a large population of FOX lines could reveal important genes conferring favorable phenotypes for crop breeding. Alternatively, a unique loss-of-function approach Chimeric REpressor gene Silencing Technology (CRES-T has been developed. In CRES-T, overexpression of a chimeric repressor, composed of the coding sequence of a transcription factor (TF and short peptide designated as the repression domain, could interfere with the action of endogenous TF in plants. Although plant TFs usually consist of gene families, CRES-T is effective, in principle, even for the TFs with functional redundancy. In this review, we focus on the current status of the gene-overexpression strategies and resources for identifying and elucidating novel functions of cereal genes. We discuss the potential of these research tools for identifying useful genes and phenotypes for application in crop
Full Text Available The Chinese giant salamander, Andrias davidianus, is an important species in the course of evolution; however, there is insufficient genomic data in public databases for understanding its immunologic mechanisms. High-throughput transcriptome sequencing is necessary to generate an enormous number of transcript sequences from A. davidianus for gene discovery. In this study, we generated more than 40 million reads from samples of spleen and skin tissue using the Illumina paired-end sequencing technology. De novo assembly yielded 87,297 transcripts with a mean length of 734 base pairs (bp. Based on the sequence similarities, searching with known proteins, 38,916 genes were identified. Gene enrichment analysis determined that 981 transcripts were assigned to the immune system. Tissue-specific expression analysis indicated that 443 of transcripts were specifically expressed in the spleen and skin. Among these transcripts, 147 transcripts were found to be involved in immune responses and inflammatory reactions, such as fucolectin, β-defensins and lymphotoxin beta. Eight tissue-specific genes were selected for validation using real time reverse transcription quantitative PCR (qRT-PCR. The results showed that these genes were significantly more expressed in spleen and skin than in other tissues, suggesting that these genes have vital roles in the immune response. This work provides a comprehensive genomic sequence resource for A. davidianus and lays the foundation for future research on the immunologic and disease resistance mechanisms of A. davidianus and other amphibians.
Halanych, Kenneth M; Kocot, Kevin M
The growing volume of genomic data from across life represents opportunities for deriving valuable biological information from data that were initially collected for another purpose. Here, we use transcriptomes collected for phylogenomic studies to search for toll-like receptor (TLR) genes in poorly sampled lophotrochozoan clades (Annelida, Mollusca, Brachiopoda, Phoronida, and Entoprocta) and one ecdysozoan clade (Priapulida). TLR genes are involved in innate immunity across animals by recognizing potential microbial infection. They have an extracellular leucine-rich repeat (LRR) domain connected to a transmembrane domain and an intracellular toll/interleukin-1 receptor (TIR) domain. Consequently, these genes are important in initiating a signaling pathway to trigger defense. We found at least one TLR ortholog in all but two taxa examined, suggesting that a broad array of lophotrochozoans may have innate immune systems similar to those observed in vertebrates and arthropods. Comparison to the SMART database confirmed the presence of both the LRR and the TIR protein motifs characteristic of TLR genes. Because we looked at only one transcriptome per species, discovery of TLR genes was limited for most taxa. However, several TRL-like genes that vary in the number and placement of LRR domains were found in phoronids. Additionally, several contigs contained LRR domains but lacked TIR domains, suggesting they were not TLRs. Many of these LRR-containing contigs had other domains (e.g., immunoglobin) and are likely involved in innate immunity. © 2014 Marine Biological Laboratory.
Yip, Shun H; Sham, Pak Chung; Wang, Junwen
Traditional RNA sequencing (RNA-seq) allows the detection of gene expression variations between two or more cell populations through differentially expressed gene (DEG) analysis. However, genes that contribute to cell-to-cell differences are not discoverable with RNA-seq because RNA-seq samples are obtained from a mixture of cells. Single-cell RNA-seq (scRNA-seq) allows the detection of gene expression in each cell. With scRNA-seq, highly variable gene (HVG) discovery allows the detection of genes that contribute strongly to cell-to-cell variation within a homogeneous cell population, such as a population of embryonic stem cells. This analysis is implemented in many software packages. In this study, we compare seven HVG methods from six software packages, including BASiCS, Brennecke, scLVM, scran, scVEGs and Seurat. Our results demonstrate that reproducibility in HVG analysis requires a larger sample size than DEG analysis. Discrepancies between methods and potential issues in these tools are discussed and recommendations are made.
Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.
Lee H. Pratt
Full Text Available The rapidly increasing rate at which biological data is being produced requires a corresponding growth in relational databases and associated tools that can help laboratories contend with that data. With this need in mind, we describe here a Modular Approach to a Genomic, Integrated and Comprehensive (MAGIC Database. This Oracle 9i database derives from an initial focus in our laboratory on gene discovery via production and analysis of expressed sequence tags (ESTs, and subsequently on gene expression as assessed by both EST clustering and microarrays. The MAGIC Gene Discovery portion of the database focuses on information derived from DNA sequences and on its biological relevance. In addition to MAGIC SEQ-LIMS, which is designed to support activities in the laboratory, it contains several additional subschemas. The latter include MAGIC Admin for database administration, MAGIC Sequence for sequence processing as well as sequence and clone attributes, MAGIC Cluster for the results of EST clustering, MAGIC Polymorphism in support of microsatellite and single-nucleotide-polymorphism discovery, and MAGIC Annotation for electronic annotation by BLAST and BLAT. The MAGIC Microarray portion is a MIAME-compliant database with two components at present. These are MAGIC Array-LIMS, which makes possible remote entry of all information into the database, and MAGIC Array Analysis, which provides data mining and visualization. Because all aspects of interaction with the MAGIC Database are via a web browser, it is ideally suited not only for individual research laboratories but also for core facilities that serve clients at any distance.
Full Text Available BACKGROUND: Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. METHODS AND RESULTS: In this study, we compared eight gene association methods - Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. CONCLUSIONS: We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction.
Full Text Available Abstract Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network to address the underlying regulations of genes that can span any unit(s of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex
Vieira Campos, Diana Alexandra; Freitas, Daniela; Gomes, Joana
biomarker assays. However, the current knowledge of secreted and circulating O-glycoproteins is limited. Here, we used the COSMC KO "SimpleCell" (SC) strategy to characterize the O-glycoproteome of two gastric cancer SC lines (AGS, MKN45) as well as a gastric cell line (KATO III) which naturally expresses...... at least partially truncated O-glycans. Overall we identified 499 O-glycoproteins and 1,236 O-glycosites in gastric cancer SCs, and a total 47 O-glycoproteins and 73 O-glycosites in the KATO III cell line. We next modified the glycoproteomic strategy to apply it to pools of sera from gastric cancer...... with the STn glycoform were further validated as being expressed in gastric cancer tissue. A proximity ligation assay was used to demonstrate that CD44 was expressed with the STn glycoform in gastric cancer tissues. The study provides a discovery strategy for aberrantly glycosylated O-glycoproteins and a set...
Shim, Gayong; Kim, Dongyoon; Le, Quoc-Viet; Park, Gyu Thae; Kwon, Taekhyun; Oh, Yu-Kyoung
Gene therapy has been receiving widespread attention due to its unique advantage in regulating the expression of specific target genes. In the field of cancer gene therapy, modulation of gene expression has been shown to decrease oncogenic factors in cancer cells or increase immune responses against cancer. Due to the macromolecular size and highly negative physicochemical features of plasmid DNA, efficient delivery systems are an essential ingredient for successful gene therapy. To date, a variety of nanostructures and materials have been studied as nonviral gene delivery systems. In this review, we will cover nonviral delivery strategies for cancer gene therapy, with a focus on target cancer genes and delivery materials. Moreover, we will address current challenges and perspectives for nonviral delivery-based cancer gene therapeutics. Copyright© Bentham Science Publishers; For any queries, please email at email@example.com.
Zeng, Xuemei; Hood, Brian L.; Zhao, Ting; Conrads, Thomas P.; Sun, Mai; Gopalakrishnan, Vanathi; Grover, Himanshu; Day, Roger S.; Weissfeld, Joel L.; Wilson, David O.; Siegfried, Jill M.; Bigbee, William L.
Introduction Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. Given the clinical burden from lung cancer, and the relatively favorable survival associated with early stage lung cancer, biomarkers for early detection of lung cancer are of important potential clinical benefit. Methods We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a set of pooled non-small cell lung cancer (NSCLC) case sera and matched controls. Immunoaffinity subtraction was used to deplete the top most abundant serum proteins; the remaining serum proteins were subjected to trypsin digestion and analyzed in triplicate by LC-MS/MS. The tandem mass spectrum data were searched against the human proteome database and the resultant spectral counting data were used to estimate the relative abundance of proteins across the case/control serum pools. The spectral counting derived abundances of some candidate biomarker proteins were confirmed with multiple reaction monitoring MS assays. Results A list of 49 differentially abundant candidate proteins was compiled by applying a negative binomial regression model to the spectral counting data (pbiomarkers with statistically significant differential abundance across the lung cancer case/control pools which, when validated, could improve lung cancer early detection. PMID:21304412
Full Text Available Molecular-targeted therapy has been developed for cancer chemoprevention and treatment. Cancer cells have different metabolic properties from normal cells. Normal cells mostly rely upon the process of mitochondrial oxidative phosphorylation to produce energy whereas cancer cells have developed an altered metabolism that allows them to sustain higher proliferation rates. Cancer cells could predominantly produce energy by glycolysis even in the presence of oxygen. This alternative metabolic characteristic is known as the “Warburg Effect.” Although the exact mechanisms underlying the Warburg effect are unclear, recent progress indicates that glycolytic pathway of cancer cells could be a critical target for drug discovery. With a long history in cancer treatment, traditional Chinese medicine (TCM is recognized as a valuable source for seeking bioactive anticancer compounds. A great progress has been made to identify active compounds from herbal medicine targeting on glycolysis for cancer treatment. Herein, we provide an overall picture of the current understanding of the molecular targets in the cancer glycolytic pathway and reviewed active compounds from Chinese herbal medicine with the potentials to inhibit the metabolic targets for cancer treatment. Combination of TCM with conventional therapies will provide an attractive strategy for improving clinical outcome in cancer treatment.
Full Text Available Secondary metabolites (SMs produced by Aspergillus have been extensively studied for their crucial roles in human health, medicine and industrial production. However, the resulting information is almost exclusively derived from a few model organisms, including A. nidulans and A. fumigatus, but little is known about rare pathogens. In this study, we performed a genomics based discovery of SM biosynthetic gene clusters in Aspergillus ustus, a rare human pathogen. A total of 52 gene clusters were identified in the draft genome of A. ustus 3.3904, such as the sterigmatocystin biosynthesis pathway that was commonly found in Aspergillus species. In addition, several SM biosynthetic gene clusters were firstly identified in Aspergillus that were possibly acquired by horizontal gene transfer, including the vrt cluster that is responsible for viridicatumtoxin production. Comparative genomics revealed that A. ustus shared the largest number of SM biosynthetic gene clusters with A. nidulans, but much fewer with other Aspergilli like A. niger and A. oryzae. These findings would help to understand the diversity and evolution of SM biosynthesis pathways in genus Aspergillus, and we hope they will also promote the development of fungal identification methodology in clinic.
Pi, Borui; Yu, Dongliang; Dai, Fangwei; Song, Xiaoming; Zhu, Congyi; Li, Hongye; Yu, Yunsong
Secondary metabolites (SMs) produced by Aspergillus have been extensively studied for their crucial roles in human health, medicine and industrial production. However, the resulting information is almost exclusively derived from a few model organisms, including A. nidulans and A. fumigatus, but little is known about rare pathogens. In this study, we performed a genomics based discovery of SM biosynthetic gene clusters in Aspergillus ustus, a rare human pathogen. A total of 52 gene clusters were identified in the draft genome of A. ustus 3.3904, such as the sterigmatocystin biosynthesis pathway that was commonly found in Aspergillus species. In addition, several SM biosynthetic gene clusters were firstly identified in Aspergillus that were possibly acquired by horizontal gene transfer, including the vrt cluster that is responsible for viridicatumtoxin production. Comparative genomics revealed that A. ustus shared the largest number of SM biosynthetic gene clusters with A. nidulans, but much fewer with other Aspergilli like A. niger and A. oryzae. These findings would help to understand the diversity and evolution of SM biosynthesis pathways in genus Aspergillus, and we hope they will also promote the development of fungal identification methodology in clinic. PMID:25706180
Mir A. Iquebal
Full Text Available Background: Chickpea (Cicer arietinum L. contributes 75% of total pulse production. Being cheaper than animal protein, makes it important in dietary requirement of developing countries. Weed not only competes with chickpea resulting into drastic yield reduction but also creates problem of harboring fungi, bacterial diseases and insect pests. Chemical approach having new herbicide discovery has constraint of limited lead molecule options, statutory regulations and environmental clearance. Through genetic approach, transgenic herbicide tolerant crop has given successful result but led to serious concern over ecological safety thus non-transgenic approach like marker assisted selection is desirable. Since large variability in tolerance limit of herbicide already exists in chickpea varieties, thus the genes offering herbicide tolerance can be introgressed in variety improvement programme. Transcriptome studies can discover such associated key genes with herbicide tolerance in chickpea.Results: This is first transcriptomic studies of chickpea or even any legume crop using two herbicide susceptible and tolerant genotypes exposed to imidazoline (Imazethapyr. Approximately 90 million paired-end reads generated from four samples were processed and assembled into 30,803 contigs using reference based assembly. We report 6,310 differentially expressed genes (DEGs, of which 3,037 were regulated by 980 miRNAs, 1,528 transcription factors associated with 897 DEGs, 47 Hub proteins, 3,540 putative Simple Sequence Repeat-Functional Domain Marker (SSR-FDM, 13,778 genic Single Nucleotide Polymorphism (SNP putative markers and 1,174 Indels. Randomly selected 20 DEGs were validated using qPCR. Pathway analysis suggested that xenobiotic degradation related gene, glutathione S-transferase (GST were only up-regulated in presence of herbicide. Down-regulation of DNA replication genes and up-regulation of abscisic acid pathway genes were observed. Study further reveals
Full Text Available Prioritising candidate genes for further experimental characterisation is a non-trivial challenge in drug discovery and biomedical research in general. An integrated approach that combines results from multiple data types is best suited for optimal target selection. We developed TargetMine, a data warehouse for efficient target prioritisation. TargetMine utilises the InterMine framework, with new data models such as protein-DNA interactions integrated in a novel way. It enables complicated searches that are difficult to perform with existing tools and it also offers integration of custom annotations and in-house experimental data. We proposed an objective protocol for target prioritisation using TargetMine and set up a benchmarking procedure to evaluate its performance. The results show that the protocol can identify known disease-associated genes with high precision and coverage. A demonstration version of TargetMine is available at http://targetmine.nibio.go.jp/.
Bønnelykke, Klaus; Ober, Carole
, such as childhood asthma with severe exacerbations, and on relevant exposures that are involved in gene-environment interactions (GEIs), such as rhinovirus infections, will improve detection of asthma genes and our understanding of the underlying mechanisms. We will discuss the challenges of considering GEIs......Asthma is a heterogeneous clinical syndrome that includes subtypes of disease with different underlying causes and disease mechanisms. Asthma is caused by a complex interaction between genes and environmental exposures; early-life exposures in particular play an important role. Asthma is also...... heritable, and a number of susceptibility variants have been discovered in genome-wide association studies, although the known risk alleles explain only a small proportion of the heritability. In this review, we present evidence supporting the hypothesis that focusing on more specific asthma phenotypes...
Moreno, Lucas; Pearson, Andrew D J
Attrition is a major issue in anticancer drug development with up to 95% of drugs tested in Phase I trials not reaching a marketing authorisation making the drug development process enormously costly and inefficient. It is essential that this problem is addressed throughout the whole drug development process to improve efficiency which will ultimately result in increased patient benefit with more profitable drugs. The approach to reduce cancer drug attrition rates must be based on three pillars. The first of these is that there is a need for new pre-clinical models which can act as better predictors of success in clinical trials. Furthermore, clinical trials driven by tumour biology with the incorporation of predictive and pharmacodynamic biomarkers would be beneficial in drug development. Finally, there is a need for increased collaboration to combine the unique strengths between industry, academia and regulators to ensure that the needs of all stakeholders are met.
Li, Li; Brunk, Brian P.; Kissinger, Jessica C.; Pape, Deana; Tang, Keliang; Cole, Robert H.; Martin, John; Wylie, Todd; Dante, Mike; Fogarty, Steven J.; Howe, Daniel K.; Liberator, Paul; Diaz, Carmen; Anderson, Jennifer; White, Michael; Jerome, Maria E.; Johnson, Emily A.; Radke, Jay A.; Stoeckert, Christian J.; Waterston, Robert H.; Clifton, Sandra W.; Roos, David S.; Sibley, L. David
Large-scale EST sequencing projects for several important parasites within the phylum Apicomplexa were undertaken for the purpose of gene discovery. Included were several parasites of medical importance (Plasmodium falciparum, Toxoplasma gondii) and others of veterinary importance (Eimeria tenella, Sarcocystis neurona, and Neospora caninum). A total of 55,192 ESTs, deposited into dbEST/GenBank, were included in the analyses. The resulting sequences have been clustered into nonredundant gene assemblies and deposited into a relational database that supports a variety of sequence and text searches. This database has been used to compare the gene assemblies using BLAST similarity comparisons to the public protein databases to identify putative genes. Of these new entries, ∼15%–20% represent putative homologs with a conservative cutoff of p neurona: , , , , , , , , , , , , , –, –, –, –, –. Eimeria tenella: –, –, –, –, –, –, –, –, – , –, –, –, –, –, –, –, –, –, –, –. Neospora caninum: –, –, , – , –, –.] PMID:12618375
Guo, Kaimin; Liang, Zuowen; Li, Fubiao; Wang, Hongliang
The present study aimed to identify the regulatory mechanisms associated with the metastasis of prostate cancer (PC). The microRNA (miRNA/miR) microarray dataset GSE21036 and gene transcript dataset GSE21034 were downloaded from the Gene Expression Omnibus database. Following pre-processing, differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) between samples from patients with primary prostate cancer (PPC) and metastatic prostate cancer (MPC) with |log 2 fold change (FC)| >1 and a false discovery rate terms (36 terms), followed by miR-494 (24 terms), miR-30d (18 terms), miR-181a (15 terms), hsa-miR-196a (8 terms), miR-708 (7 terms) and miR-486-5p (2 terms). Therefore, these miRNAs may serve roles in the metastasis of PC cells via downregulation of their corresponding target DEGs.
Vivianne G A A Vleeshouwers
Full Text Available Potato is the world's fourth largest food crop yet it continues to endure late blight, a devastating disease caused by the Irish famine pathogen Phytophthora infestans. Breeding broad-spectrum disease resistance (R genes into potato (Solanum tuberosum is the best strategy for genetically managing late blight but current approaches are slow and inefficient. We used a repertoire of effector genes predicted computationally from the P. infestans genome to accelerate the identification, functional characterization, and cloning of potentially broad-spectrum R genes. An initial set of 54 effectors containing a signal peptide and a RXLR motif was profiled for activation of innate immunity (avirulence or Avr activity on wild Solanum species and tentative Avr candidates were identified. The RXLR effector family IpiO induced hypersensitive responses (HR in S. stoloniferum, S. papita and the more distantly related S. bulbocastanum, the source of the R gene Rpi-blb1. Genetic studies with S. stoloniferum showed cosegregation of resistance to P. infestans and response to IpiO. Transient co-expression of IpiO with Rpi-blb1 in a heterologous Nicotiana benthamiana system identified IpiO as Avr-blb1. A candidate gene approach led to the rapid cloning of S. stoloniferum Rpi-sto1 and S. papita Rpi-pta1, which are functionally equivalent to Rpi-blb1. Our findings indicate that effector genomics enables discovery and functional profiling of late blight R genes and Avr genes at an unprecedented rate and promises to accelerate the engineering of late blight resistant potato varieties.
Walton, Thomas J; Li, Geng; McCulloch, Thomas A; Seth, Rashmi; Powe, Desmond G; Bishop, Michael C; Rees, Robert C
Real-time quantitative RT-PCR analysis of laser microdissected tissue is considered the most accurate technique for determining tissue gene expression. The discovery of estrogen receptor beta (ERbeta) has focussed renewed interest on the role of estrogen receptors in prostate cancer, yet few studies have utilized the technique to analyze estrogen receptor gene expression in prostate cancer. Fresh tissue was obtained from 11 radical prostatectomy specimens and from 6 patients with benign prostate hyperplasia. Pure populations of benign and malignant prostate epithelium were laser microdissected, followed by RNA isolation and electrophoresis. Quantitative RT-PCR was performed using primers for androgen receptor (AR), estrogen receptor beta (ERbeta), estrogen receptor alpha (ERalpha), progesterone receptor (PGR) and prostate specific antigen (PSA), with normalization to two housekeeping genes. Differences in gene expression were analyzed using the Mann-Whitney U-test. Correlation coefficients were analyzed using Spearman's test. Significant positive correlations were seen when AR and AR-dependent PSA, and ERalpha and ERalpha-dependent PGR were compared, indicating a representative population of RNA transcripts. ERbeta gene expression was significantly over-expressed in the cancer group compared with benign controls (P cancer group (P prostate cancer specimens. In concert with recent studies the findings suggest differential production of ERbeta splice variants, which may play important roles in the genesis of prostate cancer. (c) 2009 Wiley-Liss, Inc.
Petricoin, Emanuel F; Ornstein, David K; Liotta, Lance A
The science of proteomics comprises much more than simply generating lists of proteins that change in expression as a cause of or consequence of pathophysiology. The goal of proteomics should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. Serum proteomic pattern diagnostics is a new type of proteomic concept in which patterns of ion signatures generated from high dimensional mass spectrometry data are used as diagnostic classifiers. This recent approach has exciting potential for clinical utility of diagnostic patterns because low molecular weight metabolites, peptides, and protein fragments may have higher accuracy than traditional biomarkers of cancer detection. Intriguingly, we now have discovered that this diagnostic information exists in a bound state, complexed with circulating highly abundant carrier proteins. These diagnostic fragments may one day be harvested by circulating nanoparticles, designed to absorb, enrich, and amplify the repertoire of diagnostic biomarkers generated-even at the critical, initial stages of carcinogenesis. Copyright 2004 Elsevier Inc.
Li, Cheng-Lin Frank; Santhanam, Balaji; Webb, Amanda Nicole; Zupan, Blaž; Shaulsky, Gad
Whole-genome sequencing is a useful approach for identification of chemical-induced lesions, but previous applications involved tedious genetic mapping to pinpoint the causative mutations. We propose that saturation mutagenesis under low mutagenic loads, followed by whole-genome sequencing, should allow direct implication of genes by identifying multiple independent alleles of each relevant gene. We tested the hypothesis by performing three genetic screens with chemical mutagenesis in the social soil amoeba Dictyostelium discoideum Through genome sequencing, we successfully identified mutant genes with multiple alleles in near-saturation screens, including resistance to intense illumination and strong suppressors of defects in an allorecognition pathway. We tested the causality of the mutations by comparison to published data and by direct complementation tests, finding both dominant and recessive causative mutations. Therefore, our strategy provides a cost- and time-efficient approach to gene discovery by integrating chemical mutagenesis and whole-genome sequencing. The method should be applicable to many microbial systems, and it is expected to revolutionize the field of functional genomics in Dictyostelium by greatly expanding the mutation spectrum relative to other common mutagenesis methods. © 2016 Li et al.; Published by Cold Spring Harbor Laboratory Press.
Farrar, Jason E.; Quarello, Paola; Fisher, Ross; O’Brien, Kelly A.; Aspesi, Anna; Parrella, Sara; Henson, Adrianna L.; Seidel, Nancy E.; Atsidaftos, Eva; Prakash, Supraja; Bari, Shahla; Garelli, Emanuela; Arceci, Robert J.; Dianzani, Irma; Ramenghi, Ugo; Vlachos, Adrianna; Lipton, Jeffrey M.; Bodine, David M.; Ellis, Steven R.
Diamond Blackfan anemia (DBA), a syndrome primarily characterized by anemia and physical abnormalities, is one among a group of related inherited bone marrow failure syndromes (IBMFS) which share overlapping clinical features. Heterozygous mutations or single-copy deletions have been identified in 12 ribosomal protein genes in approximately 60% of DBA cases, with the genetic etiology unexplained in most remaining patients. Unlike many IBMFS, for which functional screening assays complement clinical and genetic findings, suspected DBA in the absence of typical alterations of the known genes must frequently be diagnosed after exclusion of other IBMFS. We report here a novel deletion in a child that presented such a diagnostic challenge and prompted development of a novel functional assay that can assist in the diagnosis of a significant fraction of patients with DBA. The ribosomal proteins affected in DBA are required for pre-rRNA processing, a process which can be interrogated to monitor steps in the maturation of 40S and 60S ribosomal subunits. In contrast to prior methods used to assess pre-rRNA processing, the assay reported here, based on capillary electrophoresis measurement of the maturation of rRNA in pre-60S ribosomal subunits, would be readily amenable to use in diagnostic laboratories. In addition to utility as a diagnostic tool, we applied this technique to gene discovery in DBA, resulting in the identification of RPL31 as a novel DBA gene. PMID:25042156
Roffler, Gretchen H.; Amish, Stephen J.; Smith, Seth; Cosart, Ted F.; Kardos, Marty; Schwartz, Michael K.; Luikart, Gordon
Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein-coding and nearby 5′ and 3′ untranslated regions of chosen candidate genes. Targeted sequences were taken from bighorn sheep (Ovis canadensis) exon capture data and directly from the domestic sheep genome (Ovis aries v. 3; oviAri3). The bighorn sheep sequences used in the Dall's sheep (Ovis dalli dalli) exon capture aligned to 2350 genes on the oviAri3 genome with an average of 2 exons each. We developed a microfluidic qPCR-based SNP chip to genotype 476 Dall's sheep from locations across their range and test for patterns of selection. Using multiple corroborating approaches (lositan and bayescan), we detected 28 SNP loci potentially under selection. We additionally identified candidate loci significantly associated with latitude, longitude, precipitation and temperature, suggesting local environmental adaptation. The three methods demonstrated consistent support for natural selection on nine genes with immune and disease-regulating functions (e.g. Ovar-DRA, APC, BATF2, MAGEB18), cell regulation signalling pathways (e.g. KRIT1, PI3K, ORRC3), and respiratory health (CYSLTR1). Characterizing adaptive allele distributions from novel genetic techniques will facilitate investigation of the influence of environmental variation on local adaptation of a northern alpine ungulate throughout its range. This research demonstrated the utility of exon capture for gene-targeted SNP discovery and subsequent SNP chip genotyping using low-quality samples in a nonmodel species.
Dylan T Jones
Full Text Available Angiogenesis is essential for solid tumour growth, whilst the molecular profiles of tumour blood vessels have been reported to be different between cancer types. Although presently available anti-angiogenic strategies are providing some promise for the treatment of some cancers it is perhaps not surprisingly that, none of the anti-angiogenic agents available work on all tumours. Thus, the discovery of novel anti-angiogenic targets, relevant to individual cancer types, is required. Using Affymetrix microarray analysis of laser-captured, CD31-positive blood vessels we have identified 63 genes that are upregulated significantly (5-72 fold in angiogenic blood vessels associated with human invasive ductal carcinoma (IDC of the breast as compared with blood vessels in normal human breast. We tested the angiogenic capacity of a subset of these genes. Genes were selected based on either their known cellular functions, their enriched expression in endothelial cells and/or their sensitivity to anti-VEGF treatment; all features implicating their involvement in angiogenesis. For example, RRM2, a ribonucleotide reductase involved in DNA synthesis, was upregulated 32-fold in IDC-associated blood vessels; ATF1, a nuclear activating transcription factor involved in cellular growth and survival was upregulated 23-fold in IDC-associated blood vessels and HEX-B, a hexosaminidase involved in the breakdown of GM2 gangliosides, was upregulated 8-fold in IDC-associated blood vessels. Furthermore, in silico analysis confirmed that AFT1 and HEX-B also were enriched in endothelial cells when compared with non-endothelial cells. None of these genes have been reported previously to be involved in neovascularisation. However, our data establish that siRNA depletion of Rrm2, Atf1 or Hex-B had significant anti-angiogenic effects in VEGF-stimulated ex vivo mouse aortic ring assays. Overall, our results provide proof-of-principle that our approach can identify a cohort of
Conclusion: The expression of KLK2 gene in people with prostate cancer is the higher than the healthy person; finally, according to the results, it could be mentioned that the KLK2 gene considered as a useful factor in prostate cancer, whose expression is associated with progression and development of the prostate cancer.
Celedon, J M; Bohlmann, J
Terpenoid fragrances are powerful mediators of ecological interactions in nature and have a long history of traditional and modern industrial applications. Plants produce a great diversity of fragrant terpenoid metabolites, which make them a superb source of biosynthetic genes and enzymes. Advances in fragrance gene discovery have enabled new approaches in synthetic biology of high-value speciality molecules toward applications in the fragrance and flavor, food and beverage, cosmetics, and other industries. Rapid developments in transcriptome and genome sequencing of nonmodel plant species have accelerated the discovery of fragrance biosynthetic pathways. In parallel, advances in metabolic engineering of microbial and plant systems have established platforms for synthetic biology applications of some of the thousands of plant genes that underlie fragrance diversity. While many fragrance molecules (eg, simple monoterpenes) are abundant in readily renewable plant materials, some highly valuable fragrant terpenoids (eg, santalols, ambroxides) are rare in nature and interesting targets for synthetic biology. As a representative example for genomics/transcriptomics enabled gene and enzyme discovery, we describe a strategy used successfully for elucidation of a complete fragrance biosynthetic pathway in sandalwood (Santalum album) and its reconstruction in yeast (Saccharomyces cerevisiae). We address questions related to the discovery of specific genes within large gene families and recovery of rare gene transcripts that are selectively expressed in recalcitrant tissues. To substantiate the validity of the approaches, we describe the combination of methods used in the gene and enzyme discovery of a cytochrome P450 in the fragrant heartwood of tropical sandalwood, responsible for the fragrance defining, final step in the biosynthesis of (Z)-santalols. © 2016 Elsevier Inc. All rights reserved.
Full Text Available Abstract Background In the analysis of microarray data one generally produces a vector of p-values that for each gene give the likelihood of obtaining equally strong evidence of change by pure chance. The distribution of these p-values is a mixture of two components corresponding to the changed genes and the unchanged ones. The focus of this article is how to estimate the proportion unchanged and the false discovery rate (FDR and how to make inferences based on these concepts. Six published methods for estimating the proportion unchanged genes are reviewed, two alternatives are presented, and all are tested on both simulated and real data. All estimates but one make do without any parametric assumptions concerning the distributions of the p-values. Furthermore, the estimation and use of the FDR and the closely related q-value is illustrated with examples. Five published estimates of the FDR and one new are presented and tested. Implementations in R code are available. Results A simulation model based on the distribution of real microarray data plus two real data sets were used to assess the methods. The proposed alternative methods for estimating the proportion unchanged fared very well, and gave evidence of low bias and very low variance. Different methods perform well depending upon whether there are few or many regulated genes. Furthermore, the methods for estimating FDR showed a varying performance, and were sometimes misleading. The new method had a very low error. Conclusion The concept of the q-value or false discovery rate is useful in practical research, despite some theoretical and practical shortcomings. However, it seems possible to challenge the performance of the published methods, and there is likely scope for further developing the estimates of the FDR. The new methods provide the scientist with more options to choose a suitable method for any particular experiment. The article advocates the use of the conjoint information
Full Text Available Application of high-throughput transcriptome sequencing has spurred highly sensitive detection and discovery of gene fusions in cancer, but distinguishing potentially oncogenic fusions from random, “passenger” aberrations has proven challenging. Here we examine a distinctive group of gene fusions that involve genes present in the loci of chromosomal amplifications—a class of oncogenic aberrations that are widely prevalent in breast cancers. Integrative analysis of a panel of 14 breast cancer cell lines comparing gene fusions discovered by high-throughput transcriptome sequencing and genome-wide copy number aberrations assessed by array comparative genomic hybridization, led to the identification of 77 gene fusions, of which more than 60% were localized to amplicons including 17q12, 17q23, 20q13, chr8q, and others. Many of these fusions appeared to be recurrent or involved highly expressed oncogenic drivers, frequently fused with multiple different partners, but sometimes displaying loss of functional domains. As illustrative examples of the “amplicon-associated” gene fusions, we examined here a recurrent gene fusion involving the mediator of mammalian target of rapamycin signaling, RPS6KB1 kinase in BT-474, and the therapeutically important receptor tyrosine kinase EGFR in MDA-MB-468 breast cancer cell line. These gene fusions comprise a minor allelic fraction relative to the highly expressed full-length transcripts and encode chimera lacking the kinase domains, which do not impart dependence on the respective cells. Our study suggests that amplicon-associated gene fusions in breast cancer primarily represent a by-product of chromosomal amplifications, which constitutes a subset of passenger aberrations and should be factored accordingly during prioritization of gene fusion candidates.
Full Text Available Poor prognosis of hepatocellular carcinoma (HCC associated with late diagnosis necessitates the development of early diagnostic biomarkers. We have previously delineated the landscape of DNA methylation in HCC patients unraveling the importance of promoter hypomethylation in activation of cancer- and metastasis-driving genes. The purpose of the present study was to test the feasibility that genes that are hypomethylated in HCC could serve as candidate diagnostic markers. We use high resolution melting analysis (HRM as a simple translatable PCR-based method to define methylation states in clinical samples. We tested seven regions selected from the shortlist of genes hypomethylated in HCC and showed that HRM analysis of several of them distinguishes methylation states in liver cancer specimens from normal adjacent liver and chronic hepatitis in the Shanghai area. Such regions were identified within promoters of neuronal membrane glycoprotein M6-B (GPM6B and melanoma antigen family A12 (MAGEA12 genes. Differences in HRM in the immunoglobulin superfamily Fc receptor (FCRL1 separated invasive tumors from less invasive HCC. The identified biomarkers differentiated HCC from chronic hepatitis in another set of samples from Dhaka. Although the main thrust in DNA methylation diagnostics in cancer is on hypermethylated genes, our study for the first time illustrates the potential use of hypomethylated genes as markers for solid tumors. After further validation in a larger cohort, the identified DNA hypomethylated regions can become important candidate biomarkers for liver cancer diagnosis and prognosis, especially in populations with high risk for HCC development.
Paul, Debasish; Kumar, Avinash; Gajbhiye, Akshada; Santra, Manas K.; Srikanth, Rapole
Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA) were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches. PMID:23586059
Full Text Available Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.
Full Text Available Abstract Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered, missing value imputation (2, standardization of data (2, gene selection (19 or clustering method (11. The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that
Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is
Liu Bing; Chinese Academy of Sciences, Beijing; Zhang Hong
Radiotherapy has some disadvantages due to the severe side-effect on the normal tissues at a curative dose of ionizing radiation (IR). Similarly, as a new developing approach, gene therapy also has some disadvantages, such as lack of specificity for tumors, limited expression of therapeutic gene, potential biological risk. To certain extent, above problems would be solved by the suicide genes or p53 gene and its target genes therapies targeted by ionizing radiation. This strategy not only makes up the disadvantage from radiotherapy or gene therapy alone, but also promotes success rate on the base of lower dose. By present, there have been several vectors measuring up to be reaching clinical trials. This review focused on the development of the cancer gene therapy through suicide genes or p53 and its target genes mediated by IR. (authors)
Dunford, Andrew; Weinstock, David M.; Savova, Virginia; Schumacher, Steven E.; Cleary, John P.; Yoda, Akinori; Sullivan, Timothy J.; Hess, Julian M.; Gimelbrant, Alexander A.; Beroukhim, Rameen; Lawrence, Michael S.; Getz, Gad; Lane, Andrew A.
There is a striking and unexplained male predominance across many cancer types. A subset of X chromosome (chrX) genes can escape X-inactivation, which would protect females from complete functional loss by a single mutation. To identify putative “Escape from X-Inactivation Tumor Suppressor” (EXITS) genes, we compared somatic alterations from >4100 cancers across 21 tumor types for sex bias. Six of 783 non-pseudoautosomal region (PAR) chrX genes (ATRX, CNKSR2, DDX3X, KDM5C, KDM6A, and MAGEC3) more frequently harbored loss-of-function mutations in males (based on false discovery rate <0.1), compared to zero of 18,055 autosomal and PAR genes (P<0.0001). Male-biased mutations in genes that escape X-inactivation were observed in combined analysis across many cancers and in several individual tumor types, suggesting a generalized phenomenon. We conclude that biallelic expression of EXITS genes in females explains a portion of the reduced cancer incidence compared to males across a variety of tumor types. PMID:27869828
Dunford, Andrew; Weinstock, David M; Savova, Virginia; Schumacher, Steven E; Cleary, John P; Yoda, Akinori; Sullivan, Timothy J; Hess, Julian M; Gimelbrant, Alexander A; Beroukhim, Rameen; Lawrence, Michael S; Getz, Gad; Lane, Andrew A
There is a striking and unexplained male predominance across many cancer types. A subset of X-chromosome genes can escape X-inactivation, which would protect females from complete functional loss by a single mutation. To identify putative 'escape from X-inactivation tumor-suppressor' (EXITS) genes, we examined somatic alterations from >4,100 cancers across 21 tumor types for sex bias. Six of 783 non-pseudoautosomal region (PAR) X-chromosome genes (ATRX, CNKSR2, DDX3X, KDM5C, KDM6A, and MAGEC3) harbored loss-of-function mutations more frequently in males (based on a false discovery rate < 0.1), in comparison to zero of 18,055 autosomal and PAR genes (Fisher's exact P < 0.0001). Male-biased mutations in genes that escape X-inactivation were observed in combined analysis across many cancers and in several individual tumor types, suggesting a generalized phenomenon. We conclude that biallelic expression of EXITS genes in females explains a portion of the reduced cancer incidence in females as compared to males across a variety of tumor types.
Alan W. Shindel
Full Text Available Genomics is the science of how genes influence human health and disease states. It differs from traditional genetic screening in that the transcriptional activity (or other markers in full panels of related genes are studied. Compared to simple genetic testing, assessment of expression levels in a panel of genes provides a more nuanced and holistic understanding of genetic modulation of human disease. Genomic testing may be used to great effect in resolving controversial questions on detection and treatment of prostate cancer. Genomic tests are currently in use for numerous facets of prostate cancer care, including screening, biopsy, and treatment planning. The clinical validity (predictive capacity of these assays has been well established; studies on clinical utility (i.e. usefulness of these tests in guiding patient/provider decisions have shown promising results. Men’s health specialists should be familiar with the role genomic testing will play in contemporary management of prostate cancer.
Chu, Xin-Yi; Jiang, Ling-Han; Zhou, Xiong-Hui; Cui, Ze-Jia; Zhang, Hong-Yu
The cancer atavistic theory suggests that carcinogenesis is a reverse evolution process. It is thus of great interest to explore the evolutionary origins of cancer driver genes and the relevant mechanisms underlying the carcinogenesis. Moreover, the evolutionary features of cancer driver genes could be helpful in selecting cancer biomarkers from high-throughput data. In this study, through analyzing the cancer endogenous molecular networks, we revealed that the subnetwork originating from eukaryota could control the unlimited proliferation of cancer cells, and the subnetwork originating from eumetazoa could recapitulate the other hallmarks of cancer. In addition, investigations based on multiple datasets revealed that cancer driver genes were enriched in genes originating from eukaryota, opisthokonta, and eumetazoa. These results have important implications for enhancing the robustness of cancer prognosis models through selecting the gene signatures by the gene age information.
The Cancer Target Discovery and Development (CTD2) Network aims to use functional genomics to accelerate the translation of high-throughput and high-content genomic and small-molecule data towards use in precision oncology.
Suh, K Stephen; Remache, Yvonne K; Patel, Jalpa S; Chen, Steve H; Haystrand, Russell; Ford, Peggy; Shaikh, Anadil M; Wang, Jian; Goy, Andre H
Modern cancer research for biomarker discovery program requires solving several tasks that are directly involved with patient sample procurement. One requirement is to construct a highly efficient workflow on the clinical side for the procurement to generate a consistent supply of high quality samples for research. This undertaking needs a network of interdepartmental collaborations and participations at various levels, including physical human interactions, information technology implementations and a bioinformatics tool that is highly effective and user-friendly to busy clinicians and researchers associated with the sample procurement. Collegial participation that is sequential but continual from one department to another demands dedicated bioinformatics software coordinating between the institutional clinic and the tissue repository facility. Participants in the process include admissions, consenting process, phlebotomy, surgery center and pathology. During this multiple step procedures, clinical data are collected for detailed analytical endpoints to supplement logistics of defining and validating the discovery of biomarkers.
Lewis, Z; Price, T A R; Wedell, N
Sperm competition is widespread and has played an important role in shaping male reproductive characters such as testis size and numbers of sperm produced, and this is reflected in the rapid evolution of many reproductive genes. Additionally, sperm competition has been implicated in the rapid evolution of seminal fluids. However, our understanding of the molecular basis of many traits thought to be important in sperm competition is rudimentary. Furthermore, links between sperm competition and a range of issues not directly related to reproduction are only just beginning to be explored. These include associations between sperm competition and selfish genes, immunity and diseases such as cancer.We briefly review these topics and suggest areas we consider worthy of additional research.
Bachtarzi, Houria; Stevenson, Mark; Fisher, Kerry
Clinical experience with adenovirus vectors has highlighted the need for improved delivery and targeting. This manuscript aims to provide an overview of the techniques currently under development for improving adenovirus delivery to malignant cells in vivo. Primary research articles reporting improvements in adenoviral gene delivery are described. Strategies include genetic modification of viral coat proteins, non-genetic modifications including polymer encapsulation approaches and pharmacological interventions. Reprogramming adenovirus tropism in vitro has been convincingly demonstrated using a range of genetic and physical strategies. These studies have provided new insights into our understanding of virology and the field is progressing. However, there are still some limitations that need special consideration before adenovirus-targeted cancer gene therapy emerges as a routine treatment in the clinical setting.
Gu, De-Leung; Chen, Yen-Hsieh; Shih, Jou-Ho; Lin, Chi-Hung; Jou, Yuh-Shan; Chen, Chian-Feng
High-throughput short-read sequencing of exomes and whole cancer genomes in multiple human hepatocellular carcinoma (HCC) cohorts confirmed previously identified frequently mutated somatic genes, such as TP53, CTNNB1 and AXIN1, and identified several novel genes with moderate mutation frequencies, including ARID1A, ARID2, MLL, MLL2, MLL3, MLL4, IRF2, ATM, CDKN2A, FGF19, PIK3CA, RPS6KA3, JAK1, KEAP1, NFE2L2, C16orf62, LEPR, RAC2, and IL6ST. Functional classification of these mutated genes suggested that alterations in pathways participating in chromatin remodeling, Wnt/β-catenin signaling, JAK/STAT signaling, and oxidative stress play critical roles in HCC tumorigenesis. Nevertheless, because there are few druggable genes used in HCC therapy, the identification of new therapeutic targets through integrated genomic approaches remains an important task. Because a large amount of HCC genomic data genotyped by high density single nucleotide polymorphism arrays is deposited in the public domain, copy number alteration (CNA) analyses of these arrays is a cost-effective way to reveal target genes through profiling of recurrent and overlapping amplicons, homozygous deletions and potentially unbalanced chromosomal translocations accumulated during HCC progression. Moreover, integration of CNAs with other high-throughput genomic data, such as aberrantly coding transcriptomes and non-coding gene expression in human HCC tissues and rodent HCC models, provides lines of evidence that can be used to facilitate the identification of novel HCC target genes with the potential of improving the survival of HCC patients.
King, Mary-Claire; Welcsh, Piri L
Genetic instability is a hallmark of tumor development. Mechanisms for maintenance of genomic stability are heterogeneous and identification of the genes responsible a critical goal of cancer biologists...
Singh, Prithvi Kumar; Kumar, Vijay; Ahmad, Mohammad Kaleem; Gupta, Rajni; Mahdi, Abbas Ali; Jain, Amita; Bogra, Jaishri; Chandra, Girish
Cytokines play an important role in the development of cancer. Several single-nucleotide polymorphisms (SNPs) of cytokine genes have been reported to be associated with the development and severity of inflammatory diseases and cancer predisposition. This study was undertaken to evaluate a possible association of interleukin 2 (IL-2) (- 330A>C) gene polymorphisms with the susceptibility to oral cancer. The SNP in IL-2 (-330A>C) gene was genotyped in 300 oral cancer patients and in similar number of healthy volunteers by polymerase chain reaction (PCR)-restriction fragment length polymorphism and the association of the gene with the disease was evaluated. IL-2 (-330A>C) gene polymorphism was significantly associated with oral cancer whereas it was neither associated with clinicopathological status nor with cancer pain. The AC heterozygous genotype was significantly associated with oral cancer patients as compared to controls [odds ratio (OR): 3.0; confidence interval (CI): 2.14-4.20; Poral cancer (OR: 1.80; CI: 1.39-2.33; PC) gene polymorphism was also associated with oral cancer in tobacco smokers and chewers. Our results showed that oral cancer patients had significantly higher frequency of AA genotype but significantly lower frequency of AC genotype and C allele compared to controls. The IL-2 AC genotype and C allele of IL-2 (-330A>C) gene polymorphisms could be potential protective factors and might reduce the risk of oral cancer in Indian population.
Wilson, Raphael A.; Teng, Ling; Bachmeyer, Karen M.; Bissonnette, Mei Lin Z.; Husain, Aliya N.; Parham, David M.; Triche, Timothy J.; Wing, Michele R.; Gastier-Foster, Julie M.; Barr, Frederic G.; Hawkins, Douglas S.; Anderson, James R.; Skapek, Stephen X.; Volchenboum, Samuel L.
The clinical application of complex molecular classifiers as diagnostic or prognostic tools has been limited by the time and cost needed to apply them to patients. Using an existing fifty-gene expression signature known to separate two molecular subtypes of the pediatric cancer rhabdomyosarcoma, we show that an exhaustive iterative search algorithm can distill this complex classifier down to two or three features with equal discrimination. We validated the two-gene signatures using three separate and distinct data sets, including one that uses degraded RNA extracted from formalin-fixed, paraffin-embedded material. Finally, to demonstrate the generalizability of our algorithm, we applied it to a lung cancer data set to find minimal gene signatures that can distinguish survival. Our approach can easily be generalized and coupled to existing technical platforms to facilitate the discovery of simplified signatures that are ready for routine clinical use. PMID:23913937
Zhang, Fan; Yang, Kai; Deng, Kui; Zhang, Yuanyuan; Zhao, Weiwei; Xu, Huan; Rong, Zhiwei; Li, Kang
We sought to identify stable single-gene prognostic signatures based on a large collection of advanced stage serous ovarian cancer (AS-OvCa) gene expression data and explore their functions. The empirical Bayes (EB) method was used to remove the batch effect and integrate 8 ovarian cancer datasets. Univariate Cox regression was used to evaluate the association between gene and overall survival (OS). The Database for Annotation, Visualization and Integrated Discovery (DAVID) tool was used for the functional annotation of genes for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The batch effect was removed by the EB method, and 1257 patient samples were used for further analysis. We selected 341 single-gene prognostic signatures with FDR matrix organization, focal adhesion and DNA replication which are closely associated with cancer. We used the EB method to remove the batch effect of 8 datasets, integrated these datasets and identified stable prognosis signatures for AS-OvCa.
Wang, Kui; Kievit, Forrest M; Zhang, Miqin
Compared to conventional treatments, gene therapy offers a variety of advantages for cancer treatment including high potency and specificity, low off-target toxicity, and delivery of multiple genes that concurrently target cancer tumorigenesis, recurrence, and drug resistance. In the past decades, gene therapy has undergone remarkable progress, and is now poised to become a first line therapy for cancer. Among various gene delivery systems, nanoparticles have attracted much attention because of their desirable characteristics including low toxicity profiles, well-controlled and high gene delivery efficiency, and multi-functionalities. This review provides an overview on gene therapeutics and gene delivery technologies, and highlight recent advances, challenges and insights into the design and the utility of nanoparticles in gene therapy for cancer treatment. Copyright © 2016. Published by Elsevier Ltd.
Li Hongyan; Chen Zhihua; He Guifang
It has a good application prospect to predict effects of radiotherapy by examining radiosensitivity of patients with cervical cancers before their radiotherapy. Prediction of tumor cell radiosensitivity according to their level of gene expression and gene therapy to reverse radio-resistance prior to radiation on cervical cancers are heated researches on tumor therapy. The expression of some proliferation-related genes, apoptosis-related genes and hypoxia-related genes can inerease the radiosensitivity of cervical cancer. Microarray technology may have more direct applications to the study of biological pathway contributing to radiation resistance and may lead to development of alternative treatment modalities. (authors)
Busov, Victor [Michigan Technological Univ., Houghton, MI (United States)
Adoption of biofuels as economically and environmentally viable alternative to fossil fuels would require development of specialized bioenergy varieties. A major goal in the breeding of such varieties is the improvement of lignocellulosic biomass yield and quality. These are complex traits and understanding the underpinning molecular mechanism can assist and accelerate their improvement. This is particularly important for tree bioenergy crops like poplars (species and hybrids from the genus Populus), for which breeding progress is extremely slow due to long generation cycles. A variety of approaches have been already undertaken to better understand the molecular bases of biomass yield and quality in poplar. An obvious void in these undertakings has been the application of mutagenesis. Mutagenesis has been instrumental in the discovery and characterization of many plant traits including such that affect biomass yield and quality. In this proposal we use activation tagging to discover genes that can significantly affect biomass associated traits directly in poplar, a premier bioenergy crop. We screened a population of 5,000 independent poplar activation tagging lines under greenhouse conditions for a battery of biomass yield traits. These same plants were then analyzed for changes in wood chemistry using pyMBMS. As a result of these screens we have identified nearly 800 mutants, which are significantly (P<0.05) different when compared to wild type. Of these majority (~700) are affected in one of ten different biomass yield traits and 100 in biomass quality traits (e.g., lignin, S/G ration and C6/C5 sugars). We successfully recovered the position of the tag in approximately 130 lines, showed activation in nearly half of them and performed recapitulation experiments with 20 genes prioritized by the significance of the phenotype. Recapitulation experiments are still ongoing for many of the genes but the results are encouraging. For example, we have shown successful
Vogiatzi, P; Cassone, M; Claudio, P P
Gene therapy was proposed many decades ago as a more straightforward and definitive way of curing human diseases, but only recently technical advancements and improved knowledge have allowed its active development as a broad and promising research field. After the first successes in the cure of genetic and infectious diseases, it has been actively investigated as a means to decrease the burden and suffering generated by cancer. The field of gastric cancer is witnessing an impressive flourishing of studies testing the possibilities and actual efficacy of the many different strategies employed in gene therapy, and overall results seem to be two-sided: while original ideas and innovative protocols are providing extremely interesting contributions with great potential, more advanced-phase studies concluded so far have fallen short of expectations regarding efficacy, although invariably demonstrating little or no toxicity. An overview of the major efforts in this field is provided here, and a critical discussion is presented on the single strategies undertaken and on the overall balance between potentiality and pitfalls. Copyright 2006 Prous Science. All rights reserved.
It has been recognized that malignancies in blood cells often bear specific chromosome translocations or gene fusions. In recent years, the presence of fusion genes became to be known also among solid cancers as driver mutations. However, representative solid cancers bearing specific gene fusions are limited to cancers of thyroid, prostate, and sarcomas among which only thyroid cancer risk is known to be related to radiation exposures. On the other hand, it is extremely rare to find recurrent reciprocal translocations among common cancers such as in the lung, stomach, breast, and colon, which form a major component of radiation risks. It is therefore unlikely that radiation increases the risk of cancer by inducing specific translocations (gene fusions) but more likely through induction of mutations (including deletions). Although gene fusions could play a role in radiation carcinogenesis, it does not seem good enough to serve for a radiation fingerprint. (author)
Martin, Cara M
Cervical cancer, a potentially preventable disease, remains the second most common malignancy in women worldwide. Human papillomavirus is the single most important etiological agent in cervical cancer. HPV contributes to neoplastic progression through the action of two viral oncoproteins E6 and E7, which interfere with critical cell cycle pathways, p53, and retinoblastoma. However, evidence suggests that HPV infection alone is insufficient to induce malignant changes and other host genetic variations are important in the development of cervical cancer. Advances in molecular biology and high throughput gene expression profiling technologies have heralded a new era in biomarker discovery and identification of molecular targets related to carcinogenesis. These advancements have improved our understanding of carcinogenesis and will facilitate screening, early detection, management, and personalised targeted therapy. In this chapter, we have described the use of high density microarrays to assess gene expression profiles in cervical cancer. Using this approach we have identified a number of novel genes which are differentially expressed in cervical cancer, including several genes involved in cell cycle regulation. These include p16ink4a, MCM 3 and 5, CDC6, Geminin, Cyclins A-D, TOPO2A, CDCA1, and BIRC5. We have validated expression of mRNA using real-time PCR and protein by immunohistochemistry.
Moon, Myungjin; Nakai, Kenta
Currently, cancer biomarker discovery is one of the important research topics worldwide. In particular, detecting significant genes related to cancer is an important task for early diagnosis and treatment of cancer. Conventional studies mostly focus on genes that are differentially expressed in different states of cancer; however, noise in gene expression datasets and insufficient information in limited datasets impede precise analysis of novel candidate biomarkers. In this study, we propose an integrative analysis of gene expression and DNA methylation using normalization and unsupervised feature extractions to identify candidate biomarkers of cancer using renal cell carcinoma RNA-seq datasets. Gene expression and DNA methylation datasets are normalized by Box-Cox transformation and integrated into a one-dimensional dataset that retains the major characteristics of the original datasets by unsupervised feature extraction methods, and differentially expressed genes are selected from the integrated dataset. Use of the integrated dataset demonstrated improved performance as compared with conventional approaches that utilize gene expression or DNA methylation datasets alone. Validation based on the literature showed that a considerable number of top-ranked genes from the integrated dataset have known relationships with cancer, implying that novel candidate biomarkers can also be acquired from the proposed analysis method. Furthermore, we expect that the proposed method can be expanded for applications involving various types of multi-omics datasets.
V Uma Bai
Full Text Available The identification of a blood-based diagnostic marker is a goal in many areas of medicine, including the early diagnosis of prostate cancer. We describe the use of averaged differential display as an efficient mechanism for biomarker discovery in whole blood RNA. The process of averaging reduces the problem of clinical heterogeneity while simultaneously minimizing sample handling.RNA was isolated from the blood of prostate cancer patients and healthy controls. Samples were pooled and subjected to the averaged differential display process. Transcripts present at different levels between patients and controls were purified and sequenced for identification. Transcript levels in the blood of prostate cancer patients and controls were verified by quantitative RT-PCR. Means were compared using a t-test and a receiver-operating curve was generated. The Ring finger protein 19A (RNF19A transcript was identified as having higher levels in prostate cancer patients compared to healthy men through the averaged differential display process. Quantitative RT-PCR analysis confirmed a more than 2-fold higher level of RNF19A mRNA levels in the blood of patients with prostate cancer than in healthy controls (p = 0.0066. The accuracy of distinguishing cancer patients from healthy men using RNF19A mRNA levels in blood as determined by the area under the receiving operator curve was 0.727.Averaged differential display offers a simplified approach for the comprehensive screening of body fluids, such as blood, to identify biomarkers in patients with prostate cancer. Furthermore, this proof-of-concept study warrants further analysis of RNF19A as a clinically relevant biomarker for prostate cancer detection.
Janos L. Tanyi
Full Text Available The development of comprehensive strategies for biomarker discovery of gynecological cancers is needed. The unique physiology of the female genital track revolves around ovulatory cycles ending by the proteolysis of the endometrium triggered by progesterone decline during the last part of the luteal phase. Building on the known link between incessant ovulation and ovarian cancer, we hypothesize that life-long menstruations could damage neighboring organs such as fallopian tubes, ovaries and peritoneum via endometrial secretions, and thus endometrium neighboring structures may have developed highly efficient protective strategies that could, in turn, be hijacked by cancer cells for survival and invasion. After literature review, we could classify the molecules involved in ovulation and menstruation pathways in three main categories: proteases, proteases inhibitors and cell-surface protectors. Strikingly, all validated biomarkers for ovarian cancers belong to at least one of these categories. We thus propose the development of comprehensive methods for identification of early diagnostic markers for gynecological cancers using systematical mapping and characterization of surface or soluble molecules belonging to physiological pathways linked to menstruation and differently expressed during luteal cycles.
Full Text Available Shanchun Guo,1 Jin Zou,2 Guangdi Wang3 1Department of Microbiology, Biochemistry, and Immunology, Morehouse School of Medicine, 2Center for Cancer Research and Therapeutic Development, Clark Atlanta University, Atlanta, GA, USA; 3Research Centers in Minority Institutions Cancer Research Program, Xavier University of Louisiana, New Orleans, LA, USA Abstract: Proteomic approaches are continuing to make headways in cancer research by helping to elucidate complex signaling networks that underlie tumorigenesis and disease progression. This review describes recent advances made in the proteomic discovery of drug targets for therapeutic development. A variety of technical and methodological advances are overviewed with a critical assessment of challenges and potentials. A number of potential drug targets, such as baculoviral inhibitor of apoptosis protein repeat-containing protein 6, macrophage inhibitory cytokine 1, phosphoglycerate mutase 1, prohibitin 1, fascin, and pyruvate kinase isozyme 2 were identified in the proteomic analysis of drug-resistant cancer cells, drug action, and differential disease state tissues. Future directions for proteomics-based target identification and validation to be more translation efficient are also discussed. Keywords: proteomics, cancer, therapeutic target, signaling network, tumorigenesis
Victor M. Bii
Full Text Available Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types.
Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun
The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867
Wang, Chong-Zhi; Qi, Lian-Wen; Yuan, Chun-Su
Ginger is a commonly used spice and herbal medicine worldwide. Besides its extensive use as a condiment, ginger has been used in traditional Chinese medicine for the management of various medical conditions. In recent years, ginger has received wide attention due to its observed antiemetic and anticancer activities. This paper reviews the potential role of ginger and its active constituents in cancer chemoprevention. The phytochemistry, bioactivity, and molecular targets of ginger constituents, especially 6-shogaol, are discussed. The content of 6-shogaol is very low in fresh ginger, but significantly higher after steaming. With reported anti-cancer activities, 6-shogaol can be served as a lead compound for new drug discovery. The lead compound derivative synthesis, bioactivity evaluation, and computational docking provide a promising opportunity to identify novel anticancer compounds originating from ginger.
Full Text Available Poor prognosis for late-stage, high-grade, and recurrent cancers has been motivating cancer researchers to search for more efficient biomarkers to identify the onset of cancer. Recent advances in constructing and dynamically analyzing biomolecular networks for different types of cancer have provided a promising novel strategy to detect tumorigenesis and metastasis. The observation of different biomolecular networks associated with normal and cancerous states led us to hypothesize that correlations for gene expressions could serve as valid indicators of early cancer development. In this pilot study, we tested our hypothesis by examining whether the mRNA expressions of three randomly selected cancer-related genes PIK3C3, PIM3, and PTEN were correlated during cancer progression and the correlation coefficients could be used for cancer diagnosis. Strong correlations (0.68≤r≤1.0 were observed between PIK3C3 and PIM3 in breast cancer, between PIK3C3 and PTEN in breast and ovary cancers, and between PIM3 and PTEN in breast, kidney, liver, and thyroid cancers during disease progression, implicating that the correlations for cancer network gene expressions could serve as a supplement to current clinical biomarkers, such as cancer antigens, for early cancer diagnosis.
Rots, MG; Curiel, DT; Gerritsen, WR; Haisma, HJ
Recombinant adenoviral vectors are promising reagents for therapeutic interventions in humans, including gene therapy for biologically complex diseases like cancer and cardiovascular diseases. In this regard, the major advantage of adenoviral vectors is their superior in vivo gene transfer
Samantha B. Foley
Full Text Available Despite the potential of whole-genome sequencing (WGS to improve patient diagnosis and care, the empirical value of WGS in the cancer genetics clinic is unknown. We performed WGS on members of two cohorts of cancer genetics patients: those with BRCA1/2 mutations (n = 176 and those without (n = 82. Initial analysis of potentially pathogenic variants (PPVs, defined as nonsynonymous variants with allele frequency < 1% in ESP6500 in 163 clinically-relevant genes suggested that WGS will provide useful clinical results. This is despite the fact that a majority of PPVs were novel missense variants likely to be classified as variants of unknown significance (VUS. Furthermore, previously reported pathogenic missense variants did not always associate with their predicted diseases in our patients. This suggests that the clinical use of WGS will require large-scale efforts to consolidate WGS and patient data to improve accuracy of interpretation of rare variants. While loss-of-function (LoF variants represented only a small fraction of PPVs, WGS identified additional cancer risk LoF PPVs in patients with known BRCA1/2 mutations and led to cancer risk diagnoses in 21% of non-BRCA cancer genetics patients after expanding our analysis to 3209 ClinVar genes. These data illustrate how WGS can be used to improve our ability to discover patients' cancer genetic risks.
McGrath Michael S
Full Text Available Abstract The AIDS Cancer and Specimen Resource (ACSR supports scientific discovery in the area of HIV/AIDS-associated malignancies. The ACSR was established as a cooperative agreement between the NCI (Office of the Director, Division of Cancer Treatment and Diagnosis and regional consortia, University of California, San Francisco (West Coast, George Washington University (East Coast and Ohio State University (Mid-Region to collect, preserve and disperse HIV-related tissues and biologic fluids and controls along with clinical data to qualified investigators. The available biological samples with clinical data and the application process are described on the ACSR web site. The ACSR tissue bank has more than 100,000 human HIV positive specimens that represent different processing (43, specimen (15, and anatomical site (50 types. The ACSR provides special biospecimen collections and prepares speciality items, e.g., tissue microarrays (TMA, DNA libraries. Requests have been greatest for Kaposi's sarcoma (32% and non-Hodgkin's lymphoma (26%. Dispersed requests include 83% tissue (frozen and paraffin embedded, 18% plasma/serum and 9% other. ACSR also provides tissue microarrays of, e.g., Kaposi's sarcoma and non-Hodgkin's lymphoma, for biomarker assays and has developed collaborations with other groups that provide access to additional AIDS-related malignancy specimens. ACSR members and associates have completed 63 podium and poster presentations. Investigators have submitted 125 letters of intent requests. Discoveries using ACSR have been reported in 61 scientific publications in notable journals with an average impact factor of 7. The ACSR promotes the scientific exploration of the relationship between HIV/AIDS and malignancy by participation at national and international scientific meetings, contact with investigators who have productive research in this area and identifying, collecting, preserving, enhancing, and dispersing HIV
MENG Xu-li; DING Xiao-wen; XU Xiao-hong
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.
Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.
Roy, Janine; Winter, Christof; Schroeder, Michael
The simultaneous measurement of thousands of genes gives the opportunity to personalize and improve cancer therapy. In addition, the integration of meta-data such as protein-protein interaction (PPI) information into the analyses helps in the identification and prioritization of genes from these screens. Here, we describe a computational approach that identifies genes prognostic for outcome by combining gene profiling data from any source with a network of known relationships between genes.
Fujii, Kiyonaga; Nakamura, Haruhiko; Nishimura, Toshihide
Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.
Monitoring the photosynthetic performance of plants is a major key to understanding how plants adapt to their growth conditions. Stress tolerance traits have a high genetic complexity as plants are constantly, and unavoidably, exposed to numerous stress factors, which limits their growth rates in the natural environment. Arabidopsis thaliana, with its broad genetic diversity and wide climatic range, has been shown to successfully adapt to stressful conditions to ensure the completion of its life cycle. As a result, A. thaliana has become a robust and renowned plant model system for studying natural variation and conducting gene discovery studies. Genome wide association studies (GWAS) in restructured populations combining natural and recombinant lines is a particularly effective way to identify the genetic basis of complex traits. As most abiotic stresses affect photosynthetic activity, chlorophyll fluorescence measurements are a potential phenotyping technique for monitoring plant performance under stress conditions. This review focuses on the use of chlorophyll fluorescence as a tool to study genetic variation underlying the stress tolerance responses to abiotic stress in A. thaliana.
Peña-Diaz, Javier; Rasmussen, Lene Juel
development was first observed in colorectal cancer patients that carried inactivating germline mutations in MMR genes and the disease was named as hereditary non-polyposis colorectal cancer (HNPCC). Currently, a growing list of cancers is found to be MMR defective and HNPCC has been renamed Lynch syndrome...
Ebot, Ericka M; Gerke, Travis; Labbé, David P; Sinnott, Jennifer A; Zadra, Giorgia; Rider, Jennifer R; Tyekucheva, Svitlana; Wilson, Kathryn M; Kelly, Rachel S; Shui, Irene M; Loda, Massimo; Kantoff, Philip W; Finn, Stephen; Vander Heiden, Matthew G; Brown, Myles; Giovannucci, Edward L; Mucci, Lorelei A
Obese men are at higher risk of advanced prostate cancer and cancer-specific mortality; however, the biology underlying this association remains unclear. This study examined gene expression profiles of prostate tissue to identify biological processes differentially expressed by obesity status and lethal prostate cancer. Gene expression profiling was performed on tumor (n = 402) and adjacent normal (n = 200) prostate tissue from participants in 2 prospective cohorts who had been diagnosed with prostate cancer from 1982 to 2005. Body mass index (BMI) was calculated from the questionnaire immediately preceding cancer diagnosis. Men were followed for metastases or prostate cancer-specific death (lethal disease) through 2011. Gene Ontology biological processes differentially expressed by BMI were identified using gene set enrichment analysis. Pathway scores were computed by averaging the signal intensities of member genes. Odds ratios (ORs) for lethal prostate cancer were estimated with logistic regression. Among 402 men, 48% were healthy weight, 31% were overweight, and 21% were very overweight/obese. Fifteen gene sets were enriched in tumor tissue, but not normal tissue, of very overweight/obese men versus healthy-weight men; 5 of these were related to chromatin modification and remodeling (false-discovery rate 7, 41% vs 17%; P = 2 × 10 -4 ) and an increased risk of lethal disease that was independent of grade and stage (OR, 5.26; 95% confidence interval, 2.37-12.25). This study improves our understanding of the biology of aggressive prostate cancer and identifies a potential mechanistic link between obesity and prostate cancer death that warrants further study. Cancer 2017;123:4130-4138. © 2017 American Cancer Society. © 2017 American Cancer Society.
Johnson, Ian R D
Prostate cancer continues to be a major cause of morbidity and mortality in men, but a method for accurate prognosis in these patients is yet to be developed. The recent discovery of altered endosomal biogenesis in prostate cancer has identified a fundamental change in the cell biology of this cancer, which holds great promise for the identification of novel biomarkers that can predict disease outcomes. Here we have identified significantly altered expression of endosomal genes in prostate cancer compared to non-malignant tissue in mRNA microarrays and confirmed these findings by qRT-PCR on fresh-frozen tissue. Importantly, we identified endosomal gene expression patterns that were predictive of patient outcomes. Two endosomal tri-gene signatures were identified from a previously published microarray cohort and had a significant capacity to stratify patient outcomes. The expression of APPL1, RAB5A, EEA1, PDCD6IP, NOX4 and SORT1 were altered in malignant patient tissue, when compared to indolent and normal prostate tissue. These findings support the initiation of a case-control study using larger cohorts of prostate tissue, with documented patient outcomes, to determine if different combinations of these new biomarkers can accurately predict disease status and clinical progression in prostate cancer patients.
Sharon E Johnatty
Full Text Available We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs in 173 genes involved in stromal epithelial interactions in the Ovarian Cancer Association Consortium (OCAC. In the discovery stage, cases with epithelial ovarian cancer (n=675 and controls (n=1,162 were genotyped at 1,536 SNPs using an Illumina GoldenGate assay. Based on Positive Predictive Value estimates, three SNPs-PODXL rs1013368, ITGA6 rs13027811, and MMP3 rs522616-were selected for replication using TaqMan genotyping in up to 3,059 serous invasive cases and 8,905 controls from 16 OCAC case-control studies. An additional 18 SNPs with Pper-alleleor=0.5. However genotypes at TERT rs7726159 were associated with ovarian cancer risk in the smaller, five-study replication study (Pper-allele=0.03. Combined analysis of the discovery and replication sets for this TERT SNP showed an increased risk of serous ovarian cancer among non-Hispanic whites [adj. ORper-allele 1.14 (1.04-1.24 p=0.003]. Our study adds to the growing evidence that, like the 8q24 locus, the telomerase reverse transcriptase locus at 5p15.33, is a general cancer susceptibility locus.
Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander
Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894
Full Text Available Abstract Background Mammalian target of rapamycin (mTOR is a serine/threonine kinase involved in multiple intracellular signaling pathways promoting tumor growth. mTOR is aberrantly activated in a significant portion of breast cancers and is a promising target for treatment. Rapamycin and its analogues are in clinical trials for breast cancer treatment. Patterns of gene expression (metagenes may also be used to simulate a biologic process or effects of a drug treatment. In this study, we tested the hypothesis that the gene-expression signature regulated by rapamycin could predict disease outcome for patients with breast cancer. Results Colony formation and sulforhodamine B (IC50 in vitro and in vivo gene expression data identified a signature, termed rapamycin metagene index (RMI, of 31 genes upregulated by rapamycin treatment in vitro as well as in vivo (false discovery rate of 10%. In the Miller dataset, RMI did not correlate with tumor size or lymph node status. High (>75th percentile RMI was significantly associated with longer survival (P = 0.015. On multivariate analysis, RMI (P = 0.029, tumor size (P = 0.015 and lymph node status (P = 0.001 were prognostic. In van 't Veer study, RMI was not associated with the time to develop distant metastasis (P = 0.41. In the Wang dataset, RMI predicted time to disease relapse (P = 0.009. Conclusion Rapamycin-regulated gene expression signature predicts clinical outcome in breast cancer. This supports the central role of mTOR signaling in breast cancer biology and provides further impetus to pursue mTOR-targeted therapies for breast cancer treatment.
Hadjithomas, Michalis; Chen, I-Min A; Chu, Ken; Huang, Jinghua; Ratner, Anna; Palaniappan, Krishna; Andersen, Evan; Markowitz, Victor; Kyrpides, Nikos C; Ivanova, Natalia N
Secondary metabolites produced by microbes have diverse biological functions, which makes them a great potential source of biotechnologically relevant compounds with antimicrobial, anti-cancer and other activities. The proteins needed to synthesize these natural products are often encoded by clusters of co-located genes called biosynthetic gene clusters (BCs). In order to advance the exploration of microbial secondary metabolism, we developed the largest publically available database of experimentally verified and predicted BCs, the Integrated Microbial Genomes Atlas of Biosynthetic gene Clusters (IMG-ABC) (https://img.jgi.doe.gov/abc/). Here, we describe an update of IMG-ABC, which includes ClusterScout, a tool for targeted identification of custom biosynthetic gene clusters across 40 000 isolate microbial genomes, and a new search capability to query more than 700 000 BCs from isolate genomes for clusters with similar Pfam composition. Additional features enable fast exploration and analysis of BCs through two new interactive visualization features, a BC function heatmap and a BC similarity network graph. These new tools and features add to the value of IMG-ABC's vast body of BC data, facilitating their in-depth analysis and accelerating secondary metabolite discovery. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Abbott, Kenneth L; Nyre, Erik T; Abrahante, Juan; Ho, Yen-Yi; Isaksson Vogel, Rachel; Starr, Timothy K
Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Background: Our study focuses on identifying potential biomarkers for diagnosis and early detection of ovarian cancer (OC) through the study of transcription regulation of genes affected by estrogen hormone.Results: The results are based on a set of 323 experimentally validated OC-associated genes compiled from several databases, and their subset controlled by estrogen. For these two gene sets we computationally determined transcription factors (TFs) that putatively regulate transcription initiation. We ranked these TFs based on the number of genes they are likely to control. In this way, we selected 17 top-ranked TFs as potential key regulators and thus possible biomarkers for a set of 323 OC-associated genes. For 77 estrogen controlled genes from this set we identified three unique TFs as potential biomarkers.Conclusions: We introduced a new methodology to identify potential diagnostic biomarkers for OC. This report is the first bioinformatics study that explores multiple transcriptional regulators of OC-associated genes as potential diagnostic biomarkers in connection with estrogen responsiveness. We show that 64% of TF biomarkers identified in our study are validated based on real-time data from microarray expression studies. As an illustration, our method could identify CP2 that in combination with CA125 has been reported to be sensitive in diagnosing ovarian tumors. 2011 Kaur et al; licensee BioMed Central Ltd.
Kaur, Mandeep; MacPherson, Cameron R; Schmeier, Sebastian; Narasimhan, Kothandaraman; Choolani, Mahesh; Bajic, Vladimir B.
Background: Our study focuses on identifying potential biomarkers for diagnosis and early detection of ovarian cancer (OC) through the study of transcription regulation of genes affected by estrogen hormone.Results: The results are based on a set of 323 experimentally validated OC-associated genes compiled from several databases, and their subset controlled by estrogen. For these two gene sets we computationally determined transcription factors (TFs) that putatively regulate transcription initiation. We ranked these TFs based on the number of genes they are likely to control. In this way, we selected 17 top-ranked TFs as potential key regulators and thus possible biomarkers for a set of 323 OC-associated genes. For 77 estrogen controlled genes from this set we identified three unique TFs as potential biomarkers.Conclusions: We introduced a new methodology to identify potential diagnostic biomarkers for OC. This report is the first bioinformatics study that explores multiple transcriptional regulators of OC-associated genes as potential diagnostic biomarkers in connection with estrogen responsiveness. We show that 64% of TF biomarkers identified in our study are validated based on real-time data from microarray expression studies. As an illustration, our method could identify CP2 that in combination with CA125 has been reported to be sensitive in diagnosing ovarian tumors. 2011 Kaur et al; licensee BioMed Central Ltd.
Lockwood William W
Full Text Available Abstract Background Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer. Results Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations. Conclusions Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.
Wang, Minkun; Tsai, Tsung-Heng; Di Poto, Cristina; Ferrarini, Alessia; Yu, Guoqiang; Ressom, Habtom W
A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. We investigated topic model-based inference methods to computationally address the heterogeneity issue in samples analyzed by LC/GC-MS. We observed
Ana Rita Lima
Full Text Available Prostate cancer (PCa is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.
Lackey, N R; Gates, M F; Brown, G
To describe the experiences of African American women living with breast cancer following the primary diagnosis and while undergoing initial treatment. Phenomenologic. 13 African American women (ages 30-66) purposefully selected from two oncology clinics in the mid-South. Phenomenologic interviews (transcribed verbatim) and field notes were analyzed using Colaizzi's method of phenomenologic description and analysis. Experience Trajectory, Femininity, and Spirituality were the three major themes. The Experience Trajectory subthemes were finding the lump, getting the diagnosis, undergoing surgery and adjuvant treatment. The Femininity subthemes were loss of all or part of the breast, loss of hair, and sexual attractiveness to a man. Spirituality was reflected as a reliance on God. Telling the story of their experience trajectory during their breast cancer experience is valuable in assessing African American women's feelings, emotions, and fears of body changes that occur during surgery and treatment. Their spirituality helps them through this experience. Research involving both African American women and their partners would provide greater insight into specific relationship patterns and communication related to sexuality during this experience. Nurses need to listen to the stories of African American women about the initial experience of discovery, diagnosis, and treatment of breast cancer so they can be more informed advocates for these women. African American women need more information from healthcare providers regarding the whole experience trajectory.
Full Text Available Colorectal cancer (CRC is the third most common cancer in the world. The early detection of CRC, during the promotion/progression stages, is an enormous challenge for a successful outcome and remains a fundamental problem in clinical approach. Despite the continuous advancement in diagnostic and therapeutic methods, there is a need for discovery of sensitive and specific, noninvasive biomarkers. Tumor endothelial markers (TEMs are associated with tumor-specific angiogenesis and are potentially useful to discriminate between tumor and normal endothelium. The most promising TEMs for oncogenic signaling in CRC appeared to be the TEM1, TEM5, TEM7, and TEM8. Overexpression of TEMs especially TEM1, TEM7, and TEM8 in colorectal tumor tissue compared to healthy tissue suggests their role in tumor blood vessels formation. Thus TEMs appear to be perspective candidates for early detection, monitoring, and treatment of CRC patients. This review provides an update on recent data on tumor endothelial markers and their possible use as biomarkers for screening, diagnosis, and therapy of colorectal cancer patients.
Colorectal cancer (CRC) is the third most common cancer in the world. The early detection of CRC, during the promotion/progression stages, is an enormous challenge for a successful outcome and remains a fundamental problem in clinical approach. Despite the continuous advancement in diagnostic and therapeutic methods, there is a need for discovery of sensitive and specific, noninvasive biomarkers. Tumor endothelial markers (TEMs) are associated with tumor-specific angiogenesis and are potentially useful to discriminate between tumor and normal endothelium. The most promising TEMs for oncogenic signaling in CRC appeared to be the TEM1, TEM5, TEM7, and TEM8. Overexpression of TEMs especially TEM1, TEM7, and TEM8 in colorectal tumor tissue compared to healthy tissue suggests their role in tumor blood vessels formation. Thus TEMs appear to be perspective candidates for early detection, monitoring, and treatment of CRC patients. This review provides an update on recent data on tumor endothelial markers and their possible use as biomarkers for screening, diagnosis, and therapy of colorectal cancer patients.
Akkiprik, Mustafa; Peker, İrem; Özmen, Tolga; Amuran, Gökçe Güllü; Güllüoğlu, Bahadır M; Kaya, Handan; Özer, Ayşe
IGFBP5 is an important regulatory protein in breast cancer progression. We tried to identify differentially expressed genes (DEGs) between breast tumor tissues with IGFBP5 overexpression and their adjacent normal tissues. In this study, thirty-eight breast cancer and adjacent normal breast tissue samples were used to determine IGFBP5 expression by qPCR. cDNA microarrays were applied to the highest IGFBP5 overexpressed tumor samples compared to their adjacent normal breast tissue. Microarray analysis revealed that a total of 186 genes were differentially expressed in breast cancer compared with normal breast tissues. Of the 186 genes, 169 genes were downregulated and 17 genes were upregulated in the tumor samples. KEGG pathway analyses showed that protein digestion and absorption, focal adhesion, salivary secretion, drug metabolism-cytochrome P450, and phenylalanine metabolism pathways are involved. Among these DEGs, the prominent top two genes (MMP11 and COL1A1) which potentially correlated with IGFBP5 were selected for validation using real time RT-qPCR. Only COL1A1 expression showed a consistent upregulation with IGFBP5 expression and COL1A1 and MMP11 were significantly positively correlated. We concluded that the discovery of coordinately expressed genes related with IGFBP5 might contribute to understanding of the molecular mechanism of the function of IGFBP5 in breast cancer. Further functional studies on DEGs and association with IGFBP5 may identify novel biomarkers for clinical applications in breast cancer.
Agarwal, Subhash M; Raghav, Dhwani; Singh, Harinder; Raghava, G P S
The Cervical Cancer gene DataBase (CCDB, http://crdd.osdd.net/raghava/ccdb) is a manually curated catalog of experimentally validated genes that are thought, or are known to be involved in the different stages of cervical carcinogenesis. In spite of the large women population that is presently affected from this malignancy still at present, no database exists that catalogs information on genes associated with cervical cancer. Therefore, we have compiled 537 genes in CCDB that are linked with cervical cancer causation processes such as methylation, gene amplification, mutation, polymorphism and change in expression level, as evident from published literature. Each record contains details related to gene like architecture (exon-intron structure), location, function, sequences (mRNA/CDS/protein), ontology, interacting partners, homology to other eukaryotic genomes, structure and links to other public databases, thus augmenting CCDB with external data. Also, manually curated literature references have been provided to support the inclusion of the gene in the database and establish its association with cervix cancer. In addition, CCDB provides information on microRNA altered in cervical cancer as well as search facility for querying, several browse options and an online tool for sequence similarity search, thereby providing researchers with easy access to the latest information on genes involved in cervix cancer.
Kanth, Priyanka; Bronner, Mary P.; Boucher, Kenneth M.; Burt, Randall W.; Neklason, Deborah W.; Hagedorn, Curt H.; Delker, Don A.
Sessile serrated colon adenoma/polyps (SSA/Ps) are found during routine screening colonoscopy and may account for 20–30% of colon cancers. However, differentiating SSA/Ps from hyperplastic polyps (HP) with little risk of cancer is challenging and complementary molecular markers are needed. Additionally, the molecular mechanisms of colon cancer development from SSA/Ps are poorly understood. RNA sequencing was performed on 21 SSA/Ps, 10 HPs, 10 adenomas, 21 uninvolved colon and 20 control colon specimens. Differential expression and leave-one-out cross validation methods were used to define a unique gene signature of SSA/Ps. Our SSA/P gene signature was evaluated in colon cancer RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify a subtype of colon cancers that may develop from SSA/Ps. A total of 1422 differentially expressed genes were found in SSA/Ps relative to controls. Serrated polyposis syndrome (n=12) and sporadic SSA/Ps (n=9) exhibited almost complete (96%) gene overlap. A 51-gene panel in SSA/P showed similar expression in a subset of TCGA colon cancers with high microsatellite instability (MSI-H). A smaller seven-gene panel showed high sensitivity and specificity in identifying BRAF mutant, CpG island methylator phenotype high (CIMP-H) and MLH1 silenced colon cancers. We describe a unique gene signature in SSA/Ps that identifies a subset of colon cancers likely to develop through the serrated pathway. These gene panels may be utilized for improved differentiation of SSA/Ps from HPs and provide insights into novel molecular pathways altered in colon cancer arising from the serrated pathway. PMID:27026680
Hartmaier, Ryan J; Ditsch, Nina; Bugert, Peter; Weber, Bernhard HF; Niederacher, Dieter; Arnold, Norbert; Varon-Mateeva, Raymonda; Wappenschmidt, Barbara; Schmutzler, Rita K; Meindl, Alfons; Bartram, Claus R; Tchatchou, Sandrine; Burwinkel, Barbara; Oesterreich, Steffi; Richter, Alexandra S; Wang, Jay; McGuire, Sean E; Skaar, Todd C; Rae, Jimmy M; Hemminki, Kari; Sutter, Christian
Coregulator proteins are 'master regulators', directing transcriptional and posttranscriptional regulation of many target genes, and are critical in many normal physiological processes, but also in hormone driven diseases, such as breast cancer. Little is known on how genetic changes in these genes impact disease development and progression. Thus, we set out to identify novel single nucleotide polymorphisms (SNPs) within SRC-1 (NCoA1), SRC-3 (NCoA3, AIB1), NCoR (NCoR1), and SMRT (NCoR2), and test the most promising SNPs for associations with breast cancer risk. The identification of novel SNPs was accomplished by sequencing the coding regions of these genes in 96 apparently normal individuals (48 Caucasian Americans, 48 African Americans). To assess their association with breast cancer risk, five SNPs were genotyped in 1218 familial BRCA1/2-mutation negative breast cancer cases and 1509 controls (rs1804645, rs6094752, rs2230782, rs2076546, rs2229840). Through our resequencing effort, we identified 74 novel SNPs (30 in NCoR, 32 in SMRT, 10 in SRC-3, and 2 in SRC-1). Of these, 8 were found with minor allele frequency (MAF) >5% illustrating the large amount of genetic diversity yet to be discovered. The previously shown protective effect of rs2230782 in SRC-3 was strengthened (OR = 0.45 [0.21-0.98], p = 0.04). No significant associations were found with the other SNPs genotyped. This data illustrates the importance of coregulators, especially SRC-3, in breast cancer development and suggests that more focused studies, including functional analyses, should be conducted
Desprez, Pierre-Yves; Campisi, Judith
A method for treatment of breast cancer and other types of cancer. The method comprises targeting and modulating Id-1 gene expression, if any, for the Id-1 gene, or gene products in breast or other epithelial cancers in a patient by delivering products that modulate Id-1 gene expression. When expressed, Id-1 gene is a prognostic indicator that cancer cells are invasive and metastatic.
Luo, Yanxin; Tsuchiya, Karen D.; Park, Dong Il; Fausel, Rebecca; Kanngurn, Samornmas; Welcsh, Piri; Dzieciatkowski, Slavomir; Wang, Jianping; Grady, William M.
Cancer arises as the consequence of mutations and epigenetic alterations that activate oncogenes and inactivate tumor suppressor genes. Through a genome-wide screen for methylated genes in colon neoplasms, we identified aberrantly methylated RET in colorectal cancer. RET, a transmembrane receptor tyrosine kinase and a receptor for the GDNF-family ligands, was one of the first oncogenes to be identified and has been shown to be an oncogene in thyroid cancer and pheochromocytoma. However, unexpectedly, we found RET is methylated in 27% of colon adenomas and in 63% of colorectal cancers, and now provide evidence that RET has tumor suppressor activity in colon cancer. The aberrant methylation of RET correlates with decreased RET expression, whereas the restoration of RET in colorectal cancer cell lines results in apoptosis. Furthermore, in support of a tumor suppressor function of RET, mutant RET has also been found in primary colorectal cancer. We now show that these mutations inactivate RET, which is consistent with RET being a tumor suppressor gene in the colon. These findings suggest that the aberrant methylation of RET and the mutational inactivation of RET promote colorectal cancer formation and that RET can serve as a tumor suppressor gene in the colon. Moreover, the increased frequency of methylated RET in colon cancers compared to adenomas suggests RET inactivation is involved in the progression of colon adenomas to cancer. PMID:22751117
Shchetynsky, Klementy; Diaz-Gallo, Lina-Marcella; Folkersen, Lasse; Hensvold, Aase Haj; Catrina, Anca Irinel; Berg, Louise; Klareskog, Lars; Padyukov, Leonid
Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of "connector" genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA.
Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter
Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes.
Ahmed, Farid E
Sample preparation and fractionation technologies are one of the most crucial processes in proteomic analysis and biomarker discovery in solubilized samples. Chromatographic or electrophoretic proteomic technologies are also available for separation of cellular protein components. There are, however, considerable limitations in currently available proteomic technologies as none of them allows for the analysis of the entire proteome in a simple step because of the large number of peptides, and because of the wide concentration dynamic range of the proteome in clinical blood samples. The results of any undertaken experiment depend on the condition of the starting material. Therefore, proper experimental design and pertinent sample preparation is essential to obtain meaningful results, particularly in comparative clinical proteomics in which one is looking for minor differences between experimental (diseased) and control (nondiseased) samples. This review discusses problems associated with general and specialized strategies of sample preparation and fractionation, dealing with samples that are solution or suspension, in a frozen tissue state, or formalin-preserved tissue archival samples, and illustrates how sample processing might influence detection with mass spectrometric techniques. Strategies that dramatically improve the potential for cancer biomarker discovery in minimally invasive, blood-collected human samples are also presented.
Full Text Available Prostate cancer is the most common cancer in men in western countries, and its incidence is increasing steadily worldwide. Molecular changes including both genetic and epigenetic events underlying the development and progression of this disease are still not well understood. Epigenetic events are involved in gene regulation and occur through different mechanisms such as DNA methylation and histone modifi cations. Both DNA methylation and histone modifi cations affect gene regulation and play important roles either independently or by interaction in tumor initiation and progression. This review will discuss the genes associated with epigenetic alterations in prostate cancer progression: their regulation and importance as possible markers for the disease.
Rasmussen, L D; Zawadsky, C; Binnerup, S J
different 16S rRNA gene sequences were observed, including Alpha-, Beta-, and Gammaproteobacteria; Actinobacteria; Firmicutes; and Bacteroidetes. The diversity of isolates obtained by direct plating included eight different 16S rRNA gene sequences (Alpha- and Betaproteobacteria and Actinobacteria). Partial...... sequencing of merA of selected isolates led to the discovery of new merA sequences. With phylum-specific merA primers, PCR products were obtained for Alpha- and Betaproteobacteria and Actinobacteria but not for Bacteroidetes and Firmicutes. The similarity to known sequences ranged between 89 and 95%. One...
Thorsteinsson, Morten; Kirkeby, Lene T; Hansen, Raino
PURPOSE: A 128-gene signature has been proposed to predict outcome in patients with stages II and III colorectal cancers. In the present study, we aimed to reproduce and validate the 128-gene signature in external and independent material. METHODS: Gene expression data from the original material...... were retrieved from the Gene Expression Omnibus (GEO) (n¿=¿111) in addition to a Danish data set (n¿=¿37). All patients had stages II and III colon cancers. A Prediction Analysis of Microarray classifier, based on the 128-gene signature and the original training set of stage I (n¿=¿65) and stage IV (n...... correctly predicted as stage IV-like, and the remaining patients were predicted as stage I-like and unclassifiable, respectively. Stage II patients could not be stratified. CONCLUSIONS: The 128-gene signature showed reproducibility in stage III colon cancer, but could not predict recurrence in stage II...
Liu, Ching-Chiu; Shen, Zan; Kung, Hsiang-Fu; Lin, Marie CM
Since the relationship between angiogenesis and tumor growth was established by Folkman in 1971, scientists have made efforts exploring the possibilities in treating cancer by targeting angiogenesis. Inhibition of angiogenesis growth factors and administration of angiogenesis inhibitors are the basics of anti-angiogenesis therapy. Transfer of anti-angiogenesis genes has received attention recently not only because of the advancement of recombinant vectors, but also because of the localized and sustained expression of therapeutic gene product inside the tumor after gene transfer. This review provides the up-to-date information about the strategies and the vectors studied in the field of anti-angiogenesis cancer gene therapy. PMID:17109514
Full Text Available Genome-wide association studies (GWAS have successfully identified a number of single-nucleotide polymorphisms (SNPs associated with colorectal cancer (CRC risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI. With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10(-4. For the known locus rs10795668 (10p14, we found an interacting SNP rs367615 (5q21 with replication p = 0.01 and combined p = 4.19×10(-8. Among the top marginal SNPs after LD pruning (n = 163, we identified an interaction between rs1571218 (20p12.3 and rs10879357 (12q21.1 (nominal combined p = 2.51×10(-6; Bonferroni adjusted p = 0.03. Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.
Erin M Siegel
Full Text Available Aberrant DNA methylation has been observed in cervical cancer; however, most studies have used non-quantitative approaches to measure DNA methylation. The objective of this study was to quantify methylation within a select panel of genes previously identified as targets for epigenetic silencing in cervical cancer and to identify genes with elevated methylation that can distinguish cancer from normal cervical tissues. We identified 49 women with invasive squamous cell cancer of the cervix and 22 women with normal cytology specimens. Bisulfite-modified genomic DNA was amplified and quantitative pyrosequencing completed for 10 genes (APC, CCNA, CDH1, CDH13, WIF1, TIMP3, DAPK1, RARB, FHIT, and SLIT2. A Methylation Index was calculated as the mean percent methylation across all CpG sites analyzed per gene (~4-9 CpG site per sequence. A binary cut-point was defined at >15% methylation. Sensitivity, specificity and area under ROC curve (AUC of methylation in individual genes or a panel was examined. The median methylation index was significantly higher in cases compared to controls in 8 genes, whereas there was no difference in median methylation for 2 genes. Compared to HPV and age, the combination of DNA methylation level of DAPK1, SLIT2, WIF1 and RARB with HPV and age significantly improved the AUC from 0.79 to 0.99 (95% CI: 0.97-1.00, p-value = 0.003. Pyrosequencing analysis confirmed that several genes are common targets for aberrant methylation in cervical cancer and DNA methylation level of four genes appears to increase specificity to identify cancer compared to HPV detection alone. Alterations in DNA methylation of specific genes in cervical cancers, such as DAPK1, RARB, WIF1, and SLIT2, may also occur early in cervical carcinogenesis and should be evaluated.
Kim, Chang Min; Kwon, Hee Chung
We applied HSV-tk/GCV strategy to orthotopic rat hepatoma model and showed anticancer effects of hepatoma. The increased expression of Lac Z gene after adenovirus-mediated gene delivery throughout hepatic artery was thought that is increased the possibility of gene therapy for curing hepatoma. With the construction of kGLP-laboratory, it is possible to produce a good quantity and quality of adenovirus in lage-scale production and purification of adenovirus vector. Also, the analysis of hepatoma related genes by PCR-LOH could be used for the diagnosis of patients and the development of therapeutic gene.
Kim, Chang Min; Kwon, Hee Chung
We applied HSV-tk/GCV strategy to orthotopic rat hepatoma model and showed anticancer effects of hepatoma. The increased expression of Lac Z gene after adenovirus-mediated gene delivery throughout hepatic artery was thought that is increased the possibility of gene therapy for curing hepatoma. With the construction of kGLP-laboratory, it is possible to produce a good quantity and quality of adenovirus in lage-scale production and purification of adenovirus vector. Also, the analysis of hepatoma related genes by PCR-LOH could be used for the diagnosis of patients and the development of therapeutic gene
Maqungo, Monique; Kaur, Mandeep; Kwofie, Samuel K.; Radovanovic, Aleksandar; Schaefer, Ulf; Schmeier, Sebastian; Oppon, Ekow; Christoffels, Alan; Bajic, Vladimir B.
associated with Prostate Cancer (DDPC) as an integrated knowledgebase of genes experimentally verified as implicated in PC. DDPC is distinctive from other databases in that (i) it provides pre-compiled biomedical text-mining information on PC, which otherwise
Delahanty, Ryan J.; Xiang, Yong-Bing; Spurdle, Amanda; Beeghly-Fadiel, Alicia; Long, Jirong; Thompson, Deborah; Tomlinson, Ian; Yu, Herbert; Lambrechts, Diether; Dörk, Thilo; Goodman, Marc T.; Zheng, Ying; Salvesen, Helga B.; Bao, Ping-Ping; Amant, Frederic; Beckmann, Matthias W.; Coenegrachts, Lieve; Coosemans, An; Dubrowinskaja, Natalia; Dunning, Alison; Runnebaum, Ingo B.; Easton, Douglas; Ekici, Arif B.; Fasching, Peter A.; Halle, Mari K.; Hein, Alexander; Howarth, Kimberly; Gorman, Maggie; Kaydarova, Dylyara; Krakstad, Camilla; Lose, Felicity; Lu, Lingeng; Lurie, Galina; O’Mara, Tracy; Matsuno, Rayna K.; Pharoah, Paul; Risch, Harvey; Corssen, Madeleine; Trovik, Jone; Turmanov, Nurzhan; Wen, Wanqing; Lu, Wei; Cai, Qiuyin; Zheng, Wei; Shu, Xiao-Ou
Background Experimental and epidemiological evidence have suggested that chronic inflammation may play a critical role in endometrial carcinogenesis. Methods To investigate this hypothesis, a two-stage study was carried out to evaluate single nucleotide polymorphisms (SNPs) in inflammatory pathway genes in association with endometrial cancer risk. In stage 1, 64 candidate pathway genes were identified and 4,542 directly genotyped or imputed SNPs were analyzed among 832 endometrial cancer cases and 2,049 controls, using data from the Shanghai Endometrial Cancer Genetics Study. Linkage disequilibrium of stage 1 SNPs significantly associated with endometrial cancer (PAsian- and European-ancestry samples. Conclusions These findings lend support to the hypothesis that genetic polymorphisms in genes involved in the inflammatory pathway may contribute to genetic susceptibility to endometrial cancer. Impact Statement This study adds to the growing evidence that inflammation plays an important role in endometrial carcinogenesis. PMID:23221126
Bakhtiar, Athirah; Sayyad, Mustak; Rosli, Rozita; Maruyama, Atsushi; Chowdhury, Ezharul H
Conventional therapies for malignant cancer such as chemotherapy and radiotherapy are associated with poor survival rates owing to the development of cellular resistance to cancer drugs and the lack of targetability, resulting in unwanted adverse effects on healthy cells and necessitating the lowering of therapeutic dose with consequential lower efficacy of the treatment. Gene therapy employing different types of viral and non-viral carriers to transport gene(s) of interest and facilitating production of the desirable therapeutic protein(s) has tremendous prospects in cancer treatments due to the high-level of specificity in therapeutic action of the expressed protein(s) with diminished off-target effects, although cancer cell-specific delivery of transgene(s) still poses some challenges to be addressed. Depending on the potential therapeutic target genes, cancer gene therapy could be categorized into tumor suppressor gene replacement therapy, immune gene therapy and enzyme- or prodrug-based therapy. This review would shed light on the current progress of delivery of potentially therapeutic genes into various cancer cells in vitro and animal models utilizing a variety of viral and non-viral vectors.
Full Text Available Review of: MEME and Melina II, which are two free and easy-to-use online motif discovery tools that can be employed to actively engage students in learning about gene regulatory elements.
Diaw, Lena; Woodson, Karen; Gillespie, John W.
Prostate cancer is the most common cancer in men in western countries, and its incidence is increasing steadily worldwide. Molecular changes including both genetic and epigenetic events underlying the development and progression of this disease are still not well understood. Epigenetic events are involved in gene regulation and occur through different mechanisms such as DNA methylation and histone modifi cations. Both DNA methylation and histone modifi cations affect gene regulation and play ...
S. Parvovirus vectors for cancer gene therapy. Expert. Opin. Bid. Ther., 2004, 4: 53-64. Ponnazhagan, S., and Hoover, F. Delivery of DNA to tumor... vaccine with plasmid adjuvants 95h Annual Meeting of the American Society for Cancer Research, Orlando, FL, April 2004. Chaudhuri, T.R., Cao, Z...with recombinant AAV vectors results in sustained expression in a dog model of hemophilia. Gene Ther., 5: 40-49, 1998. 2ś 35. Bohl, D., Bosch, A
Soek Sin Teh
Full Text Available An investigation on biologically active secondary metabolites from the stem bark of Mesua beccariana was carried out. A new cyclodione, mesuadione (1, along with several known constituents which are beccamarin (2, 2,5-dihydroxy-1,3,4-trimethoxy anthraquinone (3, 4-methoxy-1,3,5-trihydroxyanthraquinone (4, betulinic acid (5 and stigmasterol (6 were obtained from this ongoing research. Structures of these compounds were elucidated by extensive spectroscopic methods, including 1D and 2D-NMR, GC-MS, IR and UV techniques. Preliminary tests of the in vitro cytotoxic activities of all the isolated metabolites against a panel of human cancer cell lines Raji (lymphoma, SNU-1 (gastric carcinoma, K562 (erythroleukemia cells, LS-174T (colorectal adenocarcinoma, HeLa (cervical cells, SK-MEL-28 (malignant melanoma cells, NCI-H23 (lung adenocarcinoma, IMR-32 (neuroblastoma and Hep-G2 (hepatocellular liver carcinoma were carried out using an MTT assay. Mesuadione (1, beccamarin (2, betulinic acid (5 and stigmasterol (6 displayed strong inhibition of Raji cell proliferation, while the proliferation rate of SK-MEL-28 and HeLa were strongly inhibited by stigmasterol (6 and beccamarin (2, indicating these secondary metabolites could be anti-cancer lead compounds in drug discovery.
Baban, Chwanrow K
Anti-cancer therapy faces major challenges, particularly in terms of specificity of treatment. The ideal therapy would eradicate tumor cells selectively with minimum side effects on normal tissue. Gene or cell therapies have emerged as realistic prospects for the treatment of cancer, and involve the delivery of genetic information to a tumor to facilitate the production of therapeutic proteins. However, there is still much to be done before an efficient and safe gene medicine is achieved, primarily developing the means of targeting genes to tumors safely and efficiently. An emerging family of vectors involves bacteria of various genera. It has been shown that bacteria are naturally capable of homing to tumors when systemically administered resulting in high levels of replication locally. Furthermore, invasive species can deliver heterologous genes intra-cellularly for tumor cell expression. Here, we review the use of bacteria as vehicles for gene therapy of cancer, detailing the mechanisms of action and successes at preclinical and clinical levels.
Ribarska, Teodora; Goering, Wolfgang; Droop, Johanna; Bastian, Klaus-Marius; Ingenwerth, Marc; Schulz, Wolfgang A
Multiple epigenetic alterations contribute to prostate cancer progression by deregulating gene expression. Epigenetic mechanisms, especially differential DNA methylation at imprinting control regions (termed DMRs), normally ensure the exclusive expression of imprinted genes from one specific parental allele. We therefore wondered to which extent imprinted genes become deregulated in prostate cancer and, if so, whether deregulation is due to altered DNA methylation at DMRs. Therefore, we selected presumptive deregulated imprinted genes from a previously conducted in silico analysis and from the literature and analyzed their expression in prostate cancer tissues by qRT-PCR. We found significantly diminished expression of PLAGL1/ZAC1, MEG3, NDN, CDKN1C, IGF2, and H19, while LIT1 was significantly overexpressed. The PPP1R9A gene, which is imprinted in selected tissues only, was strongly overexpressed, but was expressed biallelically in benign and cancerous prostatic tissues. Expression of many of these genes was strongly correlated, suggesting co-regulation, as in an imprinted gene network (IGN) reported in mice. Deregulation of the network genes also correlated with EZH2 and HOXC6 overexpression. Pyrosequencing analysis of all relevant DMRs revealed generally stable DNA methylation between benign and cancerous prostatic tissues, but frequent hypo- and hyper-methylation was observed at the H19 DMR in both benign and cancerous tissues. Re-expression of the ZAC1 transcription factor induced H19, CDKN1C and IGF2, supporting its function as a nodal regulator of the IGN. Our results indicate that a group of imprinted genes are coordinately deregulated in prostate cancers, independently of DNA methylation changes.
Full Text Available Shinkan Tokudome,1 Ryosuke Ando,2 Yoshiro Koda,3 1Department of Nutritional Epidemiology, National Institute of Health and Nutrition, Shinjuku-ku, Tokyo, 2Department of Nephro-urology, Nagoya City University Graduate School of Medical Sciences, Mizuho-ku, Nagoya, 3Department of Forensic Medicine and Human Genetics, Kurume University School of Medicine, Kurume, Japan Abstract: The discoveries and application of prostate-specific antigen (PSA have been much appreciated because PSA-based screening has saved millions of lives of prostate cancer (PCa patients. Historically speaking, Flocks et al first identified antigenic properties in prostate tissue in 1960. Then, Barnes et al detected immunologic characteristics in prostatic fluid in 1963. Hara et al characterized γ-semino-protein in semen in 1966, and it has been proven to be identical to PSA. Subsequently, Ablin et al independently reported the presence of precipitation antigens in the prostate in 1970. Wang et al purified the PSA in 1979, and Kuriyama et al first applied an enzyme-linked immunosorbent assay for PSA in 1980. However, the positive predictive value with a cutoff figure of 4.0 ng/mL appeared substantially low (~30%. There are overdiagnoses and overtreatments for latent/low-risk PCa. Controversies exist in the PCa mortality-reducing effects of PSA screening between the European Randomized Study of Screening for Prostate Cancer (ERSPC and the US Prostate, Lung, Colorectal, and Ovarian (PLCO Cancer Screening Trial. For optimizing PCa screening, PSA-related items may require the following: 1 adjustment of the cutoff values according to age, as well as setting limits to age and screening intervals; 2 improving test performance using doubling time, density, and ratio of free: total PSA; and 3 fostering active surveillance for low-risk PCa with monitoring by PSA value. Other items needing consideration may include the following: 1 examinations of cell proliferation and cell cycle markers
Kaczkowski, Bogumil; Tanaka, Yuji; Kawaji, Hideya
Genes that are commonly deregulated in cancer are clinically attractive as candidate pan-diagnostic markers and therapeutic targets. To globally identify such targets, we compared Cap Analysis of Gene Expression (CAGE) profiles from 225 different cancer cell lines and 339 corresponding primary cell...
2008). The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320, 1344–1349. Palanisamy, N., Ateeq, B., Kalyana-Sundaram...census of human cancer genes. Nat Rev Cancer 4, 177–183.  Santarius T, Shipley J, Brewer D, Stratton MR, and Cooper CS (2010). A census of amplified
Full Text Available More than one-fifth of ovarian tumors have hereditary susceptibility and, in about 65–85% of these cases, the genetic abnormality is a germline mutation in BRCA genes. Nevertheless, several other suppressor genes and oncogenes have been associated with hereditary ovarian cancers, including the mismatch repair (MMR genes in Lynch syndrome, the tumor suppressor gene, TP53, in the Li-Fraumeni syndrome, and several other genes involved in the double-strand breaks repair system, such as CHEK2, RAD51, BRIP1, and PALB2. The study of genetic discriminators and deregulated pathways involved in hereditary ovarian syndromes is relevant for the future development of molecular diagnostic strategies and targeted therapeutic approaches. The recent development and implementation of next-generation sequencing technologies have provided the opportunity to simultaneously analyze multiple cancer susceptibility genes, reduce the delay and costs, and optimize the molecular diagnosis of hereditary tumors. Particularly, the identification of mutations in ovarian cancer susceptibility genes in healthy women may result in a more personalized cancer risk management with tailored clinical and radiological surveillance, chemopreventive approaches, and/or prophylactic surgeries. On the other hand, for ovarian cancer patients, the identification of mutations may provide potential targets for biologic agents and guide treatment decision-making.
Full Text Available Tissue hypoxia induces reprogramming of cell metabolism and may result in normal cell transformation and cancer progression. Hypoxia-inducible factor 1-alpha (HIF-1α, the key transcription factor, plays an important role in gastric cancer development and progression. This study aimed to investigate the underlying regulatory signaling pathway in gastric cancer using gastric cancer tissue specimens. The integration of gene expression profile and transcriptional regulatory element database (TRED was pursued to identify HIF-1α ↔ NFκB1 → BRCA1 → STAT3 ← STAT1 gene pathways and their regulated genes. The data showed that there were 82 differentially expressed genes that could be regulated by these five transcription factors in gastric cancer tissues and these genes formed 95 regulation modes, among which seven genes (MMP1, TIMP1, TLR2, FCGR3A, IRF1, FAS, and TFF3 were hub molecules that are regulated at least by two of these five transcription factors simultaneously and were associated with hypoxia, inflammation, and immune disorder. Real-Time PCR and western blot showed increasing of HIF-1α in mRNA and protein levels as well as TIMP1, TFF3 in mRNA levels in gastric cancer tissues. The data are the first study to demonstrate HIF-1α-regulated transcription factors and their corresponding network genes in gastric cancer. Further study with a larger sample size and more functional experiments is needed to confirm these data and then translate into clinical biomarker discovery and treatment strategy for gastric cancer.
Brown, M.; Brown, J.A.; Game, J.C.
A large proportion of cancer susceptibility syndromes are the result of mutations in genes in DNA repair or in cell-cycle checkpoints in response to DNA damage, such as ataxia telangiectasia (AT), Fanconi's anemia (FA), Bloom's syndrome (BS), Nijmegen breakage syndrome (NBS), and xeroderma pigmentosum (XP). Mutations in these genes often cause gross chromosomal instability leading to an increased mutation rate of all genes including those directly responsible for cancer. We have proposed that because the orthologs of these genes in budding yeast, S. cerevisiae, confer protection against killing by DNA damaging agents it should be possible to identify new cancer susceptibility genes by identifying yeast genes whose deletion causes sensitivity to DNA damage. We therefore screened the recently completed collection of individual gene deletion mutants to identify genes that affect sensitivity to DNA-damaging agents. Screening for sensitivity in this obtained up to now with the F98 glioma model othe fact that each deleted gene is replaced by a cassette containing two molecular 'barcodes', or 20-mers, that uniquely identify the strain when DNA from a pool of strains is hybridized to an oligonucleotide array containing the complementary sequences of the barcodes. We performed the screen with UV, IR, H 2 0 2 and other DNA damaging agents. In addition to identifying genes already known to confer resistance to DNA damaging agents we have identified, and individually confirmed, several genes not previously associated with resistance. Several of these are of unknown function. We have also examined the chromosomal stability of selected strains and found that IR sensitive strains often but not always exhibit genomic instability. We are presently constructing a yeast artificial chromosome to globally interrogate all the genes in the deletion pool for their involvement in genomic stability. This work shows that budding yeast is a valuable eukaryotic model organism to identify
Chen, I-Min; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Huang, Jinghua; Reddy, T. B.K.; Cimermancic, Peter; Fischbach, Michael; Ivanova, Natalia; Markowitz, Victor; Kyrpides, Nikos; Pati, Amrita
In the discovery of secondary metabolites (SMs), large-scale analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of relevant computational resources. We present IMG-ABC (https://img.jgi.doe.gov/abc/) -- An Atlas of Biosynthetic gene Clusters within the Integrated Microbial Genomes (IMG) system1. IMG-ABC is a rich repository of both validated and predicted biosynthetic clusters (BCs) in cultured isolates, single-cells and metagenomes linked with the SM chemicals they produce and enhanced with focused analysis tools within IMG. The underlying scalable framework enables traversal of phylogenetic dark matter and chemical structure space -- serving as a doorway to a new era in the discovery of novel molecules.
Dresang, Lindsay R.; Teuton, Jeremy R.; Feng, Huichen; Jacobs, Jon M.; Camp, David G.; Purvine, Samuel O.; Gritsenko, Marina A.; Li, Zhihua; Smith, Richard D.; Sugden, Bill; Moore, Patrick S.; Chang, Yuan
Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) are related human tumor viruses that cause primary effusion lymphomas (PEL) and Burkitt's lymphomas (BL), respectively. Viral genes expressed in naturally-infected cancer cells contribute to disease pathogenesis; knowing which viral genes are expressed is critical in understanding how these viruses cause cancer. To evaluate the expression of viral genes, we used high-resolution separation and mass spectrometry coupled with custom tiling arrays to align the viral proteomes and transcriptomes of three PEL and two BL cell lines under latent and lytic culture conditions. Results The majority of viral genes were efficiently detected at the transcript and/or protein level on manipulating the viral life cycle. Overall the correlation of expressed viral proteins and transcripts was highly complementary in both validating and providing orthogonal data with latent/lytic viral gene expression. Our approach also identified novel viral genes in both KSHV and EBV, and extends viral genome annotation. Several previously uncharacterized genes were validated at both transcript and protein levels. Conclusions This systems biology approach coupling proteome and transcriptome measurements provides a comprehensive view of viral gene expression that could not have been attained using each methodology independently. Detection of viral proteins in combination with viral transcripts is a potentially powerful method for establishing virus-disease relationships.
Background: Esophageal cancer ranks eighth in order of cancer occurrence. Its lethality primarily stems from inability to detect the disease during the early organ-confined stage and the lack of effective therapies for advanced-stage disease. Moreover, the understanding of molecular processes involved in esophageal cancer is not complete, hampering the development of efficient diagnostics and therapy. Efforts made by the scientific community to improve the survival rate of esophageal cancer have resulted in a wealth of scattered information that is difficult to find and not easily amendable to data-mining. To reduce this gap and to complement available cancer related bioinformatic resources, we have developed a comprehensive database (Dragon Database of Genes Implicated in Esophageal Cancer) with esophageal cancer related information, as an integrated knowledge database aimed at representing a gateway to esophageal cancer related data. Description: Manually curated 529 genes differentially expressed in EC are contained in the database. We extracted and analyzed the promoter regions of these genes and complemented gene-related information with transcription factors that potentially control them. We further, precompiled text-mined and data-mined reports about each of these genes to allow for easy exploration of information about associations of EC-implicated genes with other human genes and proteins, metabolites and enzymes, toxins, chemicals with pharmacological effects, disease concepts and human anatomy. The resulting database, DDEC, has a useful feature to display potential associations that are rarely reported and thus difficult to identify. Moreover, DDEC enables inspection of potentially new \\'association hypotheses\\' generated based on the precompiled reports. Conclusion: We hope that this resource will serve as a useful complement to the existing public resources and as a good starting point for researchers and physicians interested in EC genetics. DDEC is
Essack, Magbubah; Radovanovic, Aleksandar; Schaefer, Ulf; Schmeier, Sebastian; Seshadri, Sundararajan V; Christoffels, Alan; Kaur, Mandeep; Bajic, Vladimir B
Esophageal cancer ranks eighth in order of cancer occurrence. Its lethality primarily stems from inability to detect the disease during the early organ-confined stage and the lack of effective therapies for advanced-stage disease. Moreover, the understanding of molecular processes involved in esophageal cancer is not complete, hampering the development of efficient diagnostics and therapy. Efforts made by the scientific community to improve the survival rate of esophageal cancer have resulted in a wealth of scattered information that is difficult to find and not easily amendable to data-mining. To reduce this gap and to complement available cancer related bioinformatic resources, we have developed a comprehensive database (Dragon Database of Genes Implicated in Esophageal Cancer) with esophageal cancer related information, as an integrated knowledge database aimed at representing a gateway to esophageal cancer related data. Manually curated 529 genes differentially expressed in EC are contained in the database. We extracted and analyzed the promoter regions of these genes and complemented gene-related information with transcription factors that potentially control them. We further, precompiled text-mined and data-mined reports about each of these genes to allow for easy exploration of information about associations of EC-implicated genes with other human genes and proteins, metabolites and enzymes, toxins, chemicals with pharmacological effects, disease concepts and human anatomy. The resulting database, DDEC, has a useful feature to display potential associations that are rarely reported and thus difficult to identify. Moreover, DDEC enables inspection of potentially new 'association hypotheses' generated based on the precompiled reports. We hope that this resource will serve as a useful complement to the existing public resources and as a good starting point for researchers and physicians interested in EC genetics. DDEC is freely accessible to academic
Full Text Available Introduction. Breast cancer is the most common type of cancer among women. In Kazakhstan, breast cancer holds first place among causes of women death caused by cancer in the 45-55 year age group . Many studies have shown that the risk of acquiring breast cancer may be related to the level of calcium in the blood serum. One of the important regulators of calcium metabolism in the body is the parathyroid hormone. Single nucleotide polymorphisms in the gene encoding the parathyroid hormone (PTH are associated with breast cancer development risk, and may modify the associative interaction between the levels of calcium intake and breast cancer. Experimental studies have shown that PTH gene has a carcinogenic effect. At least three studies showed a weak positive correlation between the risk of acquiring breast cancer and primary hyperparathyroidism, a state with high levels of PTH and often high levels of calcium. The aim of this investigation was to evaluate potential association between PTH gene polymorphism and breast cancer risk among Kazakhstani women.Methods. Female breast cancer patients (n = 429 and matched control women (n = 373 were recruited into a case – control study,. Genomic DNA was extracted from peripheral venous blood of study participants using Wizard® Genomic DNA Purification Kit (Promega, USA. Detection of PTH gene polymorphism (rs1459015 was done by means of the TaqMan® SNP Genotyping Assay of real-time PCR. Statistical analysis was conducted using SPSS 19.0.Results. PTH gene alleles were in Hardy–Weinberg equilibrium (p > 0.05. Distribution was 59% CC, 35% CT, 6% TT in the group with breast cancer and 50% CC, 43% CT, 6% TT in the control group. Total difference (between the group with breast cancer and the control group in allele frequencies for PTH polymorphism was not significant (p > 0.05. No association was found between rs1459015 TT and breast cancer risk (OR = 1.039; 95%, CI 0.740 - 1.297; p = 0.893.Conclusion. We
Full Text Available Evidence on the association between vitamin D status and pancreatic cancer risk is inconsistent. This inconsistency may be partially attributable to variation in vitamin D regulating genes. We selected 11 vitamin D-related genes (GC, DHCR7, CYP2R1, VDR, CYP27B1, CYP24A1, CYP27A1, RXRA, CRP2, CASR and CUBN totaling 213 single nucleotide polymorphisms (SNPs, and examined associations with pancreatic adenocarcinoma. Our study included 3,583 pancreatic cancer cases and 7,053 controls from the genome-wide association studies of pancreatic cancer PanScans-I-III. We used the Adaptive Joint Test and the Adaptive Rank Truncated Product statistic for pathway and gene analyses, and unconditional logistic regression for SNP analyses, adjusting for age, sex, study and population stratification. We examined effect modification by circulating vitamin D concentration (≤50, >50 nmol/L for the most significant SNPs using a subset of cohort cases (n = 713 and controls (n = 878. The vitamin D metabolic pathway was not associated with pancreatic cancer risk (p = 0.830. Of the individual genes, none were associated with pancreatic cancer risk at a significance level of p<0.05. SNPs near the VDR (rs2239186, LRP2 (rs4668123, CYP24A1 (rs2762932, GC (rs2282679, and CUBN (rs1810205 genes were the top SNPs associated with pancreatic cancer (p-values 0.008-0.037, but none were statistically significant after adjusting for multiple comparisons. Associations between these SNPs and pancreatic cancer were not modified by circulating concentrations of vitamin D. These findings do not support an association between vitamin D-related genes and pancreatic cancer risk. Future research should explore other pathways through which vitamin D status might be associated with pancreatic cancer risk.
Full Text Available Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo, allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1 rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2 identification of co-expressed genes for creation of potential metagenes, 3 association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.
Microarrays offer biologists an exciting tool that allows the simultaneous assessment of gene expression levels for thousands of genes at once. At the time of their inception, microarrays were hailed as the new dawn in cancer biology and oncology practice with the hope that within a decade diseases
Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong
With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.
Kruhøffer, M; Jensen, J L; Laiho, P
The majority of microsatellite instable (MSI) colorectal cancers are sporadic, but a subset belongs to the syndrome hereditary non-polyposis colorectal cancer (HNPCC). Microsatellite instability is caused by dysfunction of the mismatch repair (MMR) system that leads to a mutator phenotype, and MSI...... of 101 stage II and III colorectal cancers (34 MSI, 67 microsatellite stable (MSS)) using high-density oligonucleotide microarrays. From these data, we constructed a nine-gene signature capable of separating the mismatch repair proficient and deficient tumours. Subsequently, we demonstrated...... is correlated to prognosis and response to chemotherapy. Gene expression signatures as predictive markers are being developed for many cancers, and the identification of a signature for MMR deficiency would be of interest both clinically and biologically. To address this issue, we profiled the gene expression...
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.
Davis, Elizabeth; Sloan, Tyler; Aurelius, Krista; Barbour, Angela; Bodey, Elijah; Clark, Brigette; Dennis, Celeste; Drown, Rachel; Fleming, Megan; Humbert, Allison; Glasgo, Elizabeth; Kerns, Trent; Lingro, Kelly; McMillin, MacKenzie; Meyer, Aaron; Pope, Breanna; Stalevicz, April; Steffen, Brittney; Steindl, Austin; Williams, Carolyn; Wimberley, Carmen; Zenas, Robert; Butela, Kristen; Wildschutte, Hans
The emergence of bacterial pathogens resistant to all known antibiotics is a global health crisis. Adding to this problem is that major pharmaceutical companies have shifted away from antibiotic discovery due to low profitability. As a result, the pipeline of new antibiotics is essentially dry and many bacteria now resist the effects of most commonly used drugs. To address this global health concern, citizen science through the Small World Initiative (SWI) was formed in 2012. As part of SWI, students isolate bacteria from their local environments, characterize the strains, and assay for antibiotic production. During the 2015 fall semester at Bowling Green State University, students isolated 77 soil-derived bacteria and genetically characterized strains using the 16S rRNA gene, identified strains exhibiting antagonistic activity, and performed an expanded SWI workflow using transposon mutagenesis to identify a biosynthetic gene cluster involved in toxigenic compound production. We identified one mutant with loss of antagonistic activity and through subsequent whole-genome sequencing and linker-mediated PCR identified a 24.9 kb biosynthetic gene locus likely involved in inhibitory activity in that mutant. Further assessment against human pathogens demonstrated the inhibition of Bacillus cereus, Listeria monocytogenes, and methicillin-resistant Staphylococcus aureus in the presence of this compound, thus supporting our molecular strategy as an effective research pipeline for SWI antibiotic discovery and genetic characterization. © 2017 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.
Pahle, Jessica; Walther, Wolfgang
For suicide gene therapy, initially prodrug-converting enzymes (gene-directed enzyme-producing therapy, GDEPT) were employed to intracellularly metabolize non-toxic prodrugs into toxic compounds, leading to the effective suicidal killing of the transfected tumor cells. In this regard, the suicide gene therapy has demonstrated its potential for efficient tumor eradication. Numerous suicide genes of viral or bacterial origin were isolated, characterized, and extensively tested in vitro and in vivo, demonstrating their therapeutic potential even in clinical trials to treat cancers of different entities. Apart from this, growing efforts are made to generate more targeted and more effective suicide gene systems for cancer gene therapy. In this regard, bacterial toxins are an alternative to the classical GDEPT strategy, which add to the broad spectrum of different suicide approaches. In this context, lytic bacterial toxins, such as streptolysin O (SLO) or the claudin-targeted Clostridium perfringens enterotoxin (CPE) represent attractive new types of suicide oncoleaking genes. They permit as pore-forming proteins rapid and also selective toxicity toward a broad range of cancers. In this chapter, we describe the generation and use of SLO as well as of CPE-based gene therapies for the effective tumor cell eradication as promising, novel suicide gene approach particularly for treatment of therapy refractory tumors.
Kiljunen, Saija; Pajunen, Maria I; Dilks, Kieran; Storf, Stefanie; Pohlschroder, Mechthild; Savilahti, Harri
Archaea share fundamental properties with bacteria and eukaryotes. Yet, they also possess unique attributes, which largely remain poorly characterized. Haloferax volcanii is an aerobic, moderately halophilic archaeon that can be grown in defined media. It serves as an excellent archaeal model organism to study the molecular mechanisms of biological processes and cellular responses to changes in the environment. Studies on haloarchaea have been impeded by the lack of efficient genetic screens that would facilitate the identification of protein functions and respective metabolic pathways. Here, we devised an insertion mutagenesis strategy that combined Mu in vitro DNA transposition and homologous-recombination-based gene targeting in H. volcanii. We generated an insertion mutant library, in which the clones contained a single genomic insertion. From the library, we isolated pigmentation-defective and auxotrophic mutants, and the respective insertions pinpointed a number of genes previously known to be involved in carotenoid and amino acid biosynthesis pathways, thus validating the performance of the methodologies used. We also identified mutants that had a transposon insertion in a gene encoding a protein of unknown or putative function, demonstrating that novel roles for non-annotated genes could be assigned. We have generated, for the first time, a random genomic insertion mutant library for a halophilic archaeon and used it for efficient gene discovery. The library will facilitate the identification of non-essential genes behind any specific biochemical pathway. It represents a significant step towards achieving a more complete understanding of the unique characteristics of halophilic archaea.
Kakrana, Atul; Yang, Andrian; Anand, Deepti; Djordjevic, Djordje; Ramachandruni, Deepti; Singh, Abhyudai; Huang, Hongzhan
Abstract Although successful in identifying new cataract-linked genes, the previous version of the database iSyTE (integrated Systems Tool for Eye gene discovery) was based on expression information on just three mouse lens stages and was functionally limited to visualization by only UCSC-Genome Browser tracks. To increase its efficacy, here we provide an enhanced iSyTE version 2.0 (URL: http://research.bioinformatics.udel.edu/iSyTE) based on well-curated, comprehensive genome-level lens expression data as a one-stop portal for the effective visualization and analysis of candidate genes in lens development and disease. iSyTE 2.0 includes all publicly available lens Affymetrix and Illumina microarray datasets representing a broad range of embryonic and postnatal stages from wild-type and specific gene-perturbation mouse mutants with eye defects. Further, we developed a new user-friendly web interface for direct access and cogent visualization of the curated expression data, which supports convenient searches and a range of downstream analyses. The utility of these new iSyTE 2.0 features is illustrated through examples of established genes associated with lens development and pathobiology, which serve as tutorials for its application by the end-user. iSyTE 2.0 will facilitate the prioritization of eye development and disease-linked candidate genes in studies involving transcriptomics or next-generation sequencing data, linkage analysis and GWAS approaches. PMID:29036527
Juliette J Kahle
Full Text Available Hematopoietic stem cells (HSCs are rare quiescent cells that continuously replenish the cellular components of the peripheral blood. Observing that the ataxia-associated gene Ataxin-1-like (Atxn1L was highly expressed in HSCs, we examined its role in HSC function through in vitro and in vivo assays. Mice lacking Atxn1L had greater numbers of HSCs that regenerated the blood more quickly than their wild-type counterparts. Molecular analyses indicated Atxn1L null HSCs had gene expression changes that regulate a program consistent with their higher level of proliferation, suggesting that Atxn1L is a novel regulator of HSC quiescence. To determine if additional brain-associated genes were candidates for hematologic regulation, we examined genes encoding proteins from autism- and ataxia-associated protein-protein interaction networks for their representation in hematopoietic cell populations. The interactomes were found to be highly enriched for proteins encoded by genes specifically expressed in HSCs relative to their differentiated progeny. Our data suggest a heretofore unappreciated similarity between regulatory modules in the brain and HSCs, offering a new strategy for novel gene discovery in both systems.
Full Text Available Abstract Background Suppression subtractive hybridization is a popular technique for gene discovery from non-model organisms without an annotated genome sequence, such as cowpea (Vigna unguiculata (L. Walp. We aimed to use this method to enrich for genes expressed during drought stress in a drought tolerant cowpea line. However, current methods were inefficient in screening libraries and management of the sequence data, and thus there was a need to develop software tools to facilitate the process. Results Forward and reverse cDNA libraries enriched for cowpea drought response genes were screened on microarrays, and the R software package SSHscreen 2.0.1 was developed (i to normalize the data effectively using spike-in control spot normalization, and (ii to select clones for sequencing based on the calculation of enrichment ratios with associated statistics. Enrichment ratio 3 values for each clone showed that 62% of the forward library and 34% of the reverse library clones were significantly differentially expressed by drought stress (adjusted p value 88% of the clones in both libraries were derived from rare transcripts in the original tester samples, thus supporting the notion that suppression subtractive hybridization enriches for rare transcripts. A set of 118 clones were chosen for sequencing, and drought-induced cowpea genes were identified, the most interesting encoding a late embryogenesis abundant Lea5 protein, a glutathione S-transferase, a thaumatin, a universal stress protein, and a wound induced protein. A lipid transfer protein and several components of photosynthesis were down-regulated by the drought stress. Reverse transcriptase quantitative PCR confirmed the enrichment ratio values for the selected cowpea genes. SSHdb, a web-accessible database, was developed to manage the clone sequences and combine the SSHscreen data with sequence annotations derived from BLAST and Blast2GO. The self-BLAST function within SSHdb grouped
Roč. 53, č. 3 (2007), s. 71-73 ISSN 0015-5500 Grant - others:EU-FP6 NoE Clinigene(XE) 018933; Liga proti rakovině, Praha(CZ) XX Institutional research plan: CEZ:AV0Z50520514 Keywords : gene therapy * immunostimulatory genes * vaccine Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 0.596, year: 2007
Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian
Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast
Full Text Available BACKGROUND: Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123 and test set (n = 81, respectively. Gene sets from eleven previously published gene signatures are included in the study. PRINCIPAL FINDINGS: To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014. Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001. The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. CONCLUSION: Combining the predictive strength of multiple gene signatures improves
Chavez-Alvarez, Rocio; Chavoya, Arturo; Mendez-Vazquez, Andres
DNA microarrays and cell cycle synchronization experiments have made possible the study of the mechanisms of cell cycle regulation of Saccharomyces cerevisiae by simultaneously monitoring the expression levels of thousands of genes at specific time points. On the other hand, pattern recognition techniques can contribute to the analysis of such massive measurements, providing a model of gene expression level evolution through the cell cycle process. In this paper, we propose the use of one of such techniques--an unsupervised artificial neural network called a Self-Organizing Map (SOM)-which has been successfully applied to processes involving very noisy signals, classifying and organizing them, and assisting in the discovery of behavior patterns without requiring prior knowledge about the process under analysis. As a test bed for the use of SOMs in finding possible relationships among genes and their possible contribution in some biological processes, we selected 282 S. cerevisiae genes that have been shown through biological experiments to have an activity during the cell cycle. The expression level of these genes was analyzed in five of the most cited time series DNA microarray databases used in the study of the cell cycle of this organism. With the use of SOM, it was possible to find clusters of genes with similar behavior in the five databases along two cell cycles. This result suggested that some of these genes might be biologically related or might have a regulatory relationship, as was corroborated by comparing some of the clusters obtained with SOMs against a previously reported regulatory network that was generated using biological knowledge, such as protein-protein interactions, gene expression levels, metabolism dynamics, promoter binding, and modification, regulation and transport of proteins. The methodology described in this paper could be applied to the study of gene relationships of other biological processes in different organisms.
Michiels, Stefan; Laplanche, Agnès; Boulet, Thomas; Dessen, Philippe; Guillonneau, Bertrand; Méjean, Arnaud; Desgrandchamps, François; Lathrop, Mark; Sarasin, Alain; Benhamou, Simone
Several defense mechanisms have been developed and maintained during the evolution to protect human cells against damage produced from exogenous or endogenous sources. We examined the associations between bladder cancer and a panel of 652 polymorphisms from 85 genes involved in maintenance of genetic stability [base excision repair, nucleotide excision repair, double-strand break repair (DSBR) and mismatch repair, as well as DNA synthesis and cell cycle regulation pathways] in 201 incident bladder cancer cases and 326 hospital controls. Score statistics were used to test differences in haplotype frequencies between cases and controls in an unconditional logistic regression model. To account for multiple testing, we associated to each P-value the expected proportion of false discoveries (q-value). Haplotype analysis revealed significant associations (P genes (POLB and FANCA) with an associated q-value of 24%. A permutation test was also used to determine whether, in each pathway analyzed, there are more variants whose allelic frequencies are different between cases and controls as compared with what would be expected by chance. Differences were found for cell cycle regulation (P = 0.02) and to a lesser extent for DSBR (P = 0.05) pathways. These results hint to a few potential candidate genes; however, our study was limited by the small sample size and therefore low statistical power to detect associations. It is anticipated that genome-wide association studies will open new perspectives for interpretation of the results of extensive candidate gene studies such as ours.
Rachel M Ostroff
Full Text Available BACKGROUND: Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥ 10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90α, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC. CONCLUSIONS/SIGNIFICANCE: This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels
Fridley, Brooke L; Batzler, Anthony; Li, Liang; Li, Fang; Matimba, Alice; Jenkins, Gregory D; Ji, Yuan; Wang, Liewei; Weinshilboum, Richard M
Responses to therapies, either with regard to toxicities or efficacy, are expected to involve complex relationships of gene products within the same molecular pathway or functional gene set. Therefore, pathways or gene sets, as opposed to single genes, may better reflect the true underlying biology and may be more appropriate units for analysis of pharmacogenomic studies. Application of such methods to pharmacogenomic studies may enable the detection of more subtle effects of multiple genes in the same pathway that may be missed by assessing each gene individually. A gene set analysis of 3821 gene sets is presented assessing the association between basal messenger RNA expression and drug cytotoxicity using ethnically defined human lymphoblastoid cell lines for two classes of drugs: pyrimidines [gemcitabine (dFdC) and arabinoside] and purines [6-thioguanine and 6-mercaptopurine]. The gene set nucleoside-diphosphatase activity was found to be significantly associated with both dFdC and arabinoside, whereas gene set γ-aminobutyric acid catabolic process was associated with dFdC and 6-thioguanine. These gene sets were significantly associated with the phenotype even after adjusting for multiple testing. In addition, five associated gene sets were found in common between the pyrimidines and two gene sets for the purines (3',5'-cyclic-AMP phosphodiesterase activity and γ-aminobutyric acid catabolic process) with a P value of less than 0.0001. Functional validation was attempted with four genes each in gene sets for thiopurine and pyrimidine antimetabolites. All four genes selected from the pyrimidine gene sets (PSME3, CANT1, ENTPD6, ADRM1) were validated, but only one (PDE4D) was validated for the thiopurine gene sets. In summary, results from the gene set analysis of pyrimidine and purine therapies, used often in the treatment of various cancers, provide novel insight into the relationship between genomic variation and drug response.
Amankwah, Ernest K; Lin, Hui-Yi; Tyrer, Jonathan P; Lawrenson, Kate; Dennis, Joe; Chornokur, Ganna; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Bruinsma, Fiona; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A; Brooks-Wilson, Angela; Bunker, Clareann H; Butzow, Ralf; Campbell, Ian G; Carty, Karen; Chen, Zhihua; Chen, Y Ann; Chang-Claude, Jenny; Cook, Linda S; Cramer, Daniel W; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; du Bois, Andreas; Despierre, Evelyn; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; Dürst, Matthias; Easton, Douglas F; Eccles, Diana M; Edwards, Robert P; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goodman, Marc T; Gronwald, Jacek; Harrington, Patricia; Harter, Philipp; Hasmad, Hanis N; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Claus K; Hogdall, Estrid; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Jim, Heather; Kellar, Melissa; Kiemeney, Lambertus A; Krakstad, Camilla; Kjaer, Susanne K; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lim, Boon Kiong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F A G; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Ian; Menon, Usha; Milne, Roger L; Modugno, Francesmary; Moysich, Kirsten B; Ness, Roberta B; Nevanlinna, Heli; Eilber, Ursula; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Paul, James; Pearce, Celeste L; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Pike, Malcolm C; Poole, Elizabeth M; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schernhammer, Eva; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Spiewankiewicz, Beata; Sucheston-Campbell, Lara; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Thomsen, Lotte; Tangen, Ingvild L; Tworoger, Shelley S; van Altena, Anne M; Vierkant, Robert A; Vergote, Ignace; Walsh, Christine S; Wang-Gohrke, Shan; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Wu, Anna H; Wu, Xifeng; Woo, Yin-Ling; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Kelemen, Linda E; Berchuck, Andrew; Schildkraut, Joellen M; Ramus, Susan J; Goode, Ellen L; Monteiro, Alvaro N A; Gayther, Simon A; Narod, Steven A; Pharoah, Paul D P; Sellers, Thomas A; Phelan, Catherine M
Epithelial-mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single-nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome-wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT-related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive-cancer patients and 23,447 controls. A P-value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07-1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27-2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69-0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC. © 2015 WILEY PERIODICALS, INC.
Scientists may have discovered why a protein called MYC can provoke a variety of cancers. Like many proteins associated with cancer, MYC helps regulate cell growth. A new study carried out by researchers at the National Institutes of Health and colleagues
E. L. Yumov
Full Text Available We studied the expression of multidrug resistance genes (MDR and monoresistance genes in normal bronchial tissue and tumor tissue of the non-small cell lung cancer (NSCLC after neoadjuvant chemotherapy (NACT (vinorelbine-carboplatine. The study included 30 patients with NSCLC (Т2–4N0–3M0. Normal bronchial tissue, normal lung tissue and tumor tissue collected during surgery following neoadjuvant chemotherapy (NACT served as a material of the study. The expression levels of MDR genes (ABCB1, ABCB2, ABCC1, ABCC2, ABCС5, ABCG1, ABCG2, GSTP and MVP, and monoresistance genes (BRCA1, ERCC1, RRM1, TOP1, TOP2A, TUBB3 and TYMS were estimated by quantitative reverse transcriptase PCR (RT-qPCR. The expression levels of some MDR genes and monoresistance genes (АВСВ1, АВСВ2, ABCG1, ERCC1, GSTP1 and MVP were significantly higher in the bronchi than in tumor tissue. The expression of ABCG1, ABCG2 and ERCC1 genes was higher in patients with T1-2 cancer than in patients with T3-4 cancer. Patients with adenocarcinoma had higher expression of BRCA1, MVP and ABCB1 genes than patients with squamous cell lung cancer. A tendency towards reduction in the expression level of MDR-genes and monoresistance genes was observed in patients with partial tumor regression compared to that observed in patients with stable disease. These findings were consistent with the previous data on reduction in the MDR-gene expression after chemotherapy with a good response in breast cancer patients.
Full Text Available Research in biomedical text mining is starting to produce technology which can make information in biomedical literature more accessible for bio-scientists. One of the current challenges is to integrate and refine this technology to support real-life scientific tasks in biomedicine, and to evaluate its usefulness in the context of such tasks. We describe CRAB - a fully integrated text mining tool designed to support chemical health risk assessment. This task is complex and time-consuming, requiring a thorough review of existing scientific data on a particular chemical. Covering human, animal, cellular and other mechanistic data from various fields of biomedicine, this is highly varied and therefore difficult to harvest from literature databases via manual means. Our tool automates the process by extracting relevant scientific data in published literature and classifying it according to multiple qualitative dimensions. Developed in close collaboration with risk assessors, the tool allows navigating the classified dataset in various ways and sharing the data with other users. We present a direct and user-based evaluation which shows that the technology integrated in the tool is highly accurate, and report a number of case studies which demonstrate how the tool can be used to support scientific discovery in cancer risk assessment and research. Our work demonstrates the usefulness of a text mining pipeline in facilitating complex research tasks in biomedicine. We discuss further development and application of our technology to other types of chemical risk assessment in the future.
Kim, Jung Seok; Kang, Seong Jae; Jeong, Hwa Yeon; Kim, Min Woo; Park, Sang Il; Lee, Yeon Kyung; Kim, Hong Sung; Kim, Keun Sik; Park, Yong Serk
Tumor-directed gene delivery is of major interest in the field of cancer gene therapy. Varied functionalizations of non-viral vectors have been suggested to enhance tumor targetability. In the present study, we prepared two different types of anti-EGF receptor (EGFR) immunonanoparticles containing pDNA, neutrally charged liposomes and cationic lipoplexes, for tumor-directed transfection of cancer therapeutic genes. Even though both anti-EGFR immunonanoparticles had a high binding affinity to the EGFR-positive cancer cells, the anti-EGFR immunolipoplex formulation exhibited approximately 100-fold higher transfection to the target cells than anti-EGFR immunoliposomes. The lipoplex formulation also showed a higher transfection to SK-OV-3 tumor xenografts in mice. Thus, IL12 and/or salmosin genes were loaded in the anti-EGFR immunolipoplexes and intravenously administered to mice carrying SK-OV-3 tumors. Co-transfection of IL12 and salmosin genes using anti-EGFR immunolipoplexes significantly reduced tumor growth and pulmonary metastasis. Furthermore, combinatorial treatment with doxorubicin synergistically inhibited tumor growth. These results suggest that anti-EGFR immunolipoplexes containing pDNA encoding therapeutic genes could be utilized as a gene-transfer modality for cancer gene therapy.
Tess V Clendenen
Full Text Available Genetic polymorphisms in vitamin D metabolism and signaling genes have been inconsistently associated with risk of breast cancer, though few studies have examined SNPs in vitamin D-related genes other than the vitamin D receptor (VDR gene and particularly have not examined the association with the retinoid X receptor alpha (RXRA gene which may be a key vitamin D pathway gene. We conducted a nested case-control study of 734 cases and 1435 individually matched controls from a population-based prospective cohort study, the Northern Sweden Mammary Screening Cohort. Tag and functional SNPs were genotyped for the VDR, cytochrome p450 24A1 (CYP24A1, and RXRA genes. We also genotyped specific SNPs in four other genes related to vitamin D metabolism and signaling (GC/VDBP, CYP2R1, DHCR7, and CYP27B1. SNPs in the CYP2R1, DHCR7, and VDBP gene regions that were associated with circulating 25(OHD concentration in GWAS were also associated with plasma 25(OHD in our study (p-trend <0.005. After taking into account the false discovery rate, these SNPs were not significantly associated with breast cancer risk, nor were any of the other SNPs or haplotypes in VDR, RXRA, and CYP24A1. We observed no statistically significant associations between polymorphisms or haplotypes in key vitamin D-related genes and risk of breast cancer. These results, combined with the observation in this cohort and most other prospective studies of no association of circulating 25(OHD with breast cancer risk, do not support an association between vitamin D and breast cancer risk.
Suzuki, H; Toyota, M; Caraway, H; Gabrielson, E; Ohmura, T; Fujikane, T; Nishikawa, N; Sogabe, Y; Nojima, M; Sonoda, T; Mori, M; Hirata, K; Imai, K; Shinomura, Y; Baylin, S B; Tokino, T
Although mutation of APC or CTNNB1 (β-catenin) is rare in breast cancer, activation of Wnt signalling is nonetheless thought to play an important role in breast tumorigenesis, and epigenetic silencing of Wnt antagonist genes, including the secreted frizzled-related protein (SFRP) and Dickkopf (DKK) families, has been observed in various tumours. In breast cancer, frequent methylation and silencing of SFRP1 was recently documented; however, altered expression of other Wnt antagonist genes is largely unknown. In the present study, we found frequent methylation of SFRP family genes in breast cancer cell lines (SFRP1, 7 out of 11, 64%; SFRP2, 11 out of 11, 100%; SFRP5, 10 out of 11, 91%) and primary breast tumours (SFRP1, 31 out of 78, 40%; SFRP2, 60 out of 78, 77%; SFRP5, 55 out of 78, 71%). We also observed methylation of DKK1, although less frequently, in cell lines (3 out of 11, 27%) and primary tumours (15 out of 78, 19%). Breast cancer cell lines express various Wnt ligands, and overexpression of SFRPs inhibited cancer cell growth. In addition, overexpression of a β-catenin mutant and depletion of SFRP1 using small interfering RNA synergistically upregulated transcriptional activity of T-cell factor/lymphocyte enhancer factor. Our results confirm the frequent methylation and silencing of Wnt antagonist genes in breast cancer, and suggest that their loss of function contributes to activation of Wnt signalling in breast carcinogenesis. PMID:18283316
Yang, Liejian; Bao, Guanhui; Zhu, Yan; Dong, Hongjun; Zhang, Yanping; Li, Yin
Cell autolysis plays important physiological roles in the life cycle of clostridial cells. Understanding the genetic basis of the autolysis phenomenon of pathogenic Clostridium or solvent producing Clostridium cells might provide new insights into this important species. Genes that might be involved in autolysis of Clostridium acetobutylicum, a model clostridial species, were investigated in this study. Twelve putative autolysin genes were predicted in C. acetobutylicum DSM 1731 genome through bioinformatics analysis. Of these 12 genes, gene SMB_G3117 was selected for testing the in tracellular autolysin activity, growth profile, viable cell numbers, and cellular morphology. We found that overexpression of SMB_G3117 gene led to earlier ceased growth, significantly increased number of dead cells, and clear electrolucent cavities, while disruption of SMB_G3117 gene exhibited remarkably reduced intracellular autolysin activity. These results indicate that SMB_G3117 is a novel gene involved in cellular autolysis of C. acetobutylicum.
Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Guohua; Huang, Tao; Cai, Yu-Dong
Uncovering the molecular mechanisms underlying reproduction is of great importance to infertility treatment and to the generation of healthy offspring. In this study, we discovered novel reproduction-related genes with a hybrid computational method, integrating three different types of method, which offered new clues for further reproduction research. This method was first executed on a weighted graph, constructed based on known protein-protein interactions, to search the shortest paths connecting any two known reproduction-related genes. Genes occurring in these paths were deemed to have a special relationship with reproduction. These newly discovered genes were filtered with a randomization test. Then, the remaining genes were further selected according to their associations with known reproduction-related genes measured by protein-protein interaction score and alignment score obtained by BLAST. The in-depth analysis of the high confidence novel reproduction genes revealed hidden mechanisms of reproduction and provided guidelines for further experimental validations.
Burks, Heather E.; Abrams, Tinya; Kirby, Christina A.; Baird, Jason; Fekete, Alexander; Hamann, Lawrence G.; Kim, Sunkyu; Lombardo, Franco; Loo, Alice; Lubicka, Danuta; Macchi, Kaitlin; McDonnell, Donald P.; Mishina, Yuji; Norris, John D.; Nunez, Jill; Saran, Chitra; Sun, Yingchuan; Thomsen, Noel M.; Wang, Chunrong; Wang, Jianling; Peukert, Stefan (Novartis); (Duke-MED)
Tetrahydroisoquinoline 40 has been identified as a potent ERα antagonist and selective estrogen receptor degrader (SERD), exhibiting good oral bioavailability, antitumor efficacy, and SERD activity in vivo. We outline the discovery and chemical optimization of the THIQ scaffold leading to THIQ 40 and showcase the racemization of the scaffold, pharmacokinetic studies in preclinical species, and the in vivo efficacy of THIQ 40 in a MCF-7 human breast cancer xenograft model.
Doungpan, Narumol; Engchuan, Worrawat; Chan, Jonathan H; Meechai, Asawin
Gene expression has been used to identify disease gene biomarkers, but there are ongoing challenges. Single gene or gene-set biomarkers are inadequate to provide sufficient understanding of complex disease mechanisms and the relationship among those genes. Network-based methods have thus been considered for inferring the interaction within a group of genes to further study the disease mechanism. Recently, the Gene-Network-based Feature Set (GNFS), which is capable of handling case-control and multiclass expression for gene biomarker identification, has been proposed, partly taking into account of network topology. However, its performance relies on a greedy search for building subnetworks and thus requires further improvement. In this work, we establish a new approach named Gene Sub-Network-based Feature Selection (GSNFS) by implementing the GNFS framework with two proposed searching and scoring algorithms, namely gene-set-based (GS) search and parent-node-based (PN) search, to identify subnetworks. An additional dataset is used to validate the results. The two proposed searching algorithms of the GSNFS method for subnetwork expansion are concerned with the degree of connectivity and the scoring scheme for building subnetworks and their topology. For each iteration of expansion, the neighbour genes of a current subnetwork, whose expression data improved the overall subnetwork score, is recruited. While the GS search calculated the subnetwork score using an activity score of a current subnetwork and the gene expression values of its neighbours, the PN search uses the expression value of the corresponding parent of each neighbour gene. Four lung cancer expression datasets were used for subnetwork identification. In addition, using pathway data and protein-protein interaction as network data in order to consider the interaction among significant genes were discussed. Classification was performed to compare the performance of the identified gene subnetworks with three
Full Text Available Current screening methods for ovarian cancer can only detect advanced disease. Earlier detection has proved difficult because the molecular precursors involved in the natural history of the disease are unknown. To identify early driver mutations in ovarian cancer cells, we used dense whole genome sequencing of micrometastases and microscopic residual disease collected at three time points over three years from a single patient during treatment for high-grade serous ovarian cancer (HGSOC. The functional and clinical significance of the identified mutations was examined using a combination of population-based whole genome sequencing, targeted deep sequencing, multi-center analysis of protein expression, loss of function experiments in an in-vivo reporter assay and mammalian models, and gain of function experiments in primary cultured fallopian tube epithelial (FTE cells. We identified frequent mutations involving a 40 kb distal repressor region for the key stem cell differentiation gene SOX2. In the apparently normal FTE, the region was also mutated. This was associated with a profound increase in SOX2 expression (p < 2−16, which was not found in patients without cancer (n = 108. Importantly, we show that SOX2 overexpression in FTE is nearly ubiquitous in patients with HGSOCs (n = 100, and common in BRCA1-BRCA2 mutation carriers (n = 71 who underwent prophylactic salpingo-oophorectomy. We propose that the finding of SOX2 overexpression in FTE could be exploited to develop biomarkers for detecting disease at a premalignant stage, which would reduce mortality from this devastating disease.
Systematic Search for Gene-Gene Interaction 5a. CONTRACT NUMBER Effect on Prostate Cancer Risk 5b. GRANT NUMBER W81XWH-09-1-0488 5c. PROGRAM...Supported by this grant ) 1. Tao S, Wang Z, Feng J, Hsu FC, Jin G, Kin ST, Zhang Z, Gronberg H, Zheng, SL, Isaacs WB, XU J, Sun J. A Genome-Wide Search for...order interactions among estrogen- metabolism genes in sporadic breast cancer. Am J Hum Genet, 69, 138-47. 48. Marchini, J., Donnelly, P. and Cardon
Cho, William C S
The Annual Meeting of the American Association for Cancer Research (AACR) is the world's largest and most comprehensive gathering of cancer researchers. At the 2008 AACR Annual Meeting, innovative research approaches, novel technologies, potentially life-saving therapies in the pipeline, late-breaking clinical trial findings, and new approaches to cancer prevention were presented by top scientists. Reflecting the global state of cancer research with an eye toward future trends, several areas of great science and discovery in the cancer field were shared in this report, which include cancer biomarkers, the role of microRNAs in cancer research, cancer stem cells, tumor microenvironment, targeted therapy, and cancer prevention. This article presents an overview of hot topics discussed at the 2008 AACR Annual Meeting and recapitulates some scientific sessions geared toward new technologies, recent progress, and current challenges reported by cancer researchers. For those who did not attend the meeting, this report may serve as a highlight of this important international cancer research meeting.
Lovering, Ruth C; Roncaglia, Paola; Howe, Douglas G; Laulederkind, Stanley J F; Khodiyar, Varsha K; Berardini, Tanya Z; Tweedie, Susan; Foulger, Rebecca E; Osumi-Sutherland, David; Campbell, Nancy H; Huntley, Rachael P; Talmud, Philippa J; Blake, Judith A; Breckenridge, Ross; Riley, Paul R; Lambiase, Pier D; Elliott, Perry M; Clapp, Lucie; Tinker, Andrew; Hill, David P
A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. © 2018 The Authors.
Full Text Available Abstract Background In candidate-gene association studies of single nucleotide polymorphisms (SNPs, multilocus analyses are frequently of high dimensionality when considering haplotypes or haplotype pairs (diplotypes and differing modes of expression. Often, while candidate genes are selected based on their biological involvement in a given pathway, little is known about the functionality of SNPs to guide association studies. Investigators face the challenge of exploring multiple SNP models to elucidate which variants, independently or in combination, might be associated with a disease of interest. A data mining module, hapConstructor (freely-available in Genie software performs systematic construction and association testing of multilocus genotype data in a Monte Carlo framework. Our objective was to assess its utility to guide statistical analyses of haplotypes within a candidate region (or combined genotypes across candidate genes beyond that offered by a standard logistic regression approach. Methods We applied the hapConstructor method to a multilocus investigation of candidate genes involved in pro-inflammatory cytokine IL6 production, IKBKB, IL6, and NFKB1 (16 SNPs total hypothesized to operate together to alter colorectal cancer risk. Data come from two U.S. multicenter studies, one of colon cancer (1,556 cases and 1,956 matched controls and one of rectal cancer (754 cases and 959 matched controls. Results HapConstrcutor enabled us to identify important associations that were further analyzed in logistic regression models to simultaneously adjust for confounders. The most significant finding (nominal P = 0.0004; false discovery rate q = 0.037 was a combined genotype association across IKBKB SNP rs5029748 (1 or 2 variant alleles, IL6 rs1800797 (1 or 2 variant alleles, and NFKB1 rs4648110 (2 variant alleles which conferred an ~80% decreased risk of colon cancer. Conclusions Strengths of hapConstructor were: systematic identification of
Litlekalsoy, Jorunn; Rostad, Kari; Kalland, Karl-Henning; Hostmark, Jens G.; Laerum, Ole Didrik
The purpose of this study was to evaluate invasive and metastatic potential of urothelial cancer by investigating differential expression of various clock genes/proteins participating in the 24 h circadian rhythms and to compare these gene expressions with transcription of other cancer-associated genes. Twenty seven paired samples of tumour and benign tissue collected from patients who underwent cystectomy were analysed and compared to 15 samples of normal bladder tissue taken from patients who underwent cystoscopy for benign prostate hyperplasia (unrelated donors). Immunohistochemical analyses were made for clock and clock-related proteins. In addition, the gene-expression levels of 22 genes (clock genes, casein kinases, oncogenes, tumour suppressor genes and cytokeratins) were analysed by real-time quantitative PCR (qPCR). Considerable up- or down-regulation and altered cellular distribution of different clock proteins, a reduction of casein kinase1A1 (CSNK1A1) and increase of casein kinase alpha 1 E (CSNK1E) were found. The pattern was significantly correlated with simultaneous up-regulation of stimulatory tumour markers, and a down-regulation of several suppressor genes. The pattern was mainly seen in aneuploid high-grade cancers. Considerable alterations were also found in the neighbouring bladder mucosa. The close correlation between altered expression of various clock genes and common tumour markers in urothelial cancer indicates that disturbed function in the cellular clock work may be an important additional mechanism contributing to cancer progression and malignant behaviour. The online version of this article (doi:10.1186/s12885-016-2580-y) contains supplementary material, which is available to authorized users
Atoum, Manar F.; Al-Kayed, Sameer A.
To screen mutations of the tumor suppressor breast cancer susceptibility gene 1 (BRCA1) within 3 exons among Jordanian breast cancer females. A total of 135 Jordanian breast cancer females were genetically analyzed by denaturing gradient electrophoresis (DGGE) for mutation detection in 3 BRCA1 exons (2, 11 and 20) between 2000-2002 in Al-Basheer Hospital, Amman, Jordan. Of the studied patients 50 had a family history of breast cancer, 28 had a family history of cancer other than breast cancer, and 57 had no family history of any cancer. Five germline mutations were detected among breast cancer females with a family history of breast cancers (one in exon 2 and 4 mutations in exon 11). Another germline mutation (within exon 11) was detected among breast cancer females with family history of cancer other than breast cancer, and no mutation was detected among breast cancer females with no family history of any cancer or among normal control females. Screening mutations within exon 2, exon 11 and exon 20 showed that most screened mutations were within BRCA1 exon 11 among breast cancer Jordanian families with a family history of breast cancer. (author)
Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P
With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.
Rodenhizer, Darren; Dean, Teresa; D'Arcangelo, Elisa; McGuigan, Alison P
Cancer prognosis remains a lottery dependent on cancer type, disease stage at diagnosis, and personal genetics. While investment in research is at an all-time high, new drugs are more likely to fail in clinical trials today than in the 1970s. In this review, a summary of current survival statistics in North America is provided, followed by an overview of the modern drug discovery process, classes of models used throughout different stages, and challenges associated with drug development efficiency are highlighted. Then, an overview of the cancer hallmarks that drive clinical progression is provided, and the range of available clinical therapies within the context of these hallmarks is categorized. Specifically, it is found that historically, the development of therapies is limited to a subset of possible targets. This provides evidence for the opportunities offered by novel disease-relevant in vitro models that enable identification of novel targets that facilitate interactions between the tumor cells and their surrounding microenvironment. Next, an overview of the models currently reported in literature is provided, and the cancer biology they have been used to explore is highlighted. Finally, four priority areas are suggested for the field to accelerate adoption of in vitro tumour models for cancer drug discovery. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Full Text Available Common genetic variation could alter the risk for developing bladder cancer. We conducted a large-scale evaluation of single nucleotide polymorphisms (SNPs in candidate genes for cancer to identify common variants that influence bladder cancer risk. An Illumina GoldenGate assay was used to genotype 1,433 SNPs within or near 386 genes in 1,086 cases and 1,033 controls in Spain. The most significant finding was in the 5' UTR of VEGF (rs25648, p for likelihood ratio test, 2 degrees of freedom = 1 x 10(-5. To further investigate the region, we analyzed 29 additional SNPs in VEGF, selected to saturate the promoter and 5' UTR and to tag common genetic variation in this gene. Three additional SNPs in the promoter region (rs833052, rs1109324, and rs1547651 were associated with increased risk for bladder cancer: odds ratio (95% confidence interval: 2.52 (1.06-5.97, 2.74 (1.26-5.98, and 3.02 (1.36-6.63, respectively; and a polymorphism in intron 2 (rs3024994 was associated with reduced risk: 0.65 (0.46-0.91. Two of the promoter SNPs and the intron 2 SNP showed linkage disequilibrium with rs25648. Haplotype analyses revealed three blocks of linkage disequilibrium with significant associations for two blocks including the promoter and 5' UTR (global p = 0.02 and 0.009, respectively. These findings are biologically plausible since VEGF is critical in angiogenesis, which is important for tumor growth, its elevated expression in bladder tumors correlates with tumor progression, and specific 5' UTR haplotypes have been shown to influence promoter activity. Associations between bladder cancer risk and other genes in this report were not robust based on false discovery rate calculations. In conclusion, this large-scale evaluation of candidate cancer genes has identified common genetic variants in the regulatory regions of VEGF that could be associated with bladder cancer risk.
Walden, Paul D
.... During this study we showed that BTG2 protein expression is lost as an early event in prostate carcinogenesis and that prostate cancer cells degrade BTG2 at a greater rate than noncancerous prostate cells...
Sommer, Steve S
.... The central hypothesis of this proposal is that variability in the patterns of p53 mutagensis in breast cancer reflects differences in exposures to different amounts and/or types of diverse environmental mutagens...
Sørensen, Kristina Pilekær
Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group...... clinical courses, and they may be useful as novel prognostic biomarkers in breast cancer. The aim of the present project was to predict the development of metastasis in lymph node negative breast cancer patients by RNA profiling. We collected and analyzed 82 primary breast tumors from patients who...... and the time of event. Previous findings have shown that high expression of the lncRNA HOTAIR is correlated with poor survival in breast cancer. We validated this finding by demonstrating that high HOTAIR expression in our primary tumors was significantly associated with worse prognosis independent...
Wang, Shuyang; Beeghly-Fadiel, Alicia; Cai, Qiuyin; Cai, Hui; Guo, Xingyi; Shi, Liang; Wu, Jie; Ye, Fei; Qiu, Qingchao; Zheng, Ying; Zheng, Wei; Bao, Ping-Ping; Shu, Xiao-Ou
The identification of biomarkers related to the prognosis of triple-negative breast cancer (TNBC) is critically important for improved understanding of the biology that drives TNBC progression. We evaluated gene expression in total RNA isolated from formalin-fixed paraffin-embedded tumor samples using the NanoString nCounter assay for 469 TNBC cases from the Shanghai Breast Cancer Survival Study. We used Cox regression to quantify Hazard Ratios (HR) and corresponding confidence intervals (CI) for overall survival (OS) and disease-free survival (DFS) in models that included adjustment for breast cancer intrinsic subtype. Of 302 genes in our discovery analysis, 22 were further evaluated in relation to OS among 134 TNBC cases from the Nashville Breast Health Study and the Southern Community Cohort Study; 16 genes were further evaluated in relation to DFS in 335 TNBC cases from four gene expression omnibus datasets. Fixed-effect meta-analysis was used to combine results across data sources. Twofold higher expression of EOMES (HR 0.90, 95% CI 0.83-0.97), RASGRP1 (HR 0.89, 95% CI 0.82-0.97), and SOD2 (HR 0.80, 95% CI 0.66-0.96) was associated with better OS. Twofold higher expression of EOMES (HR 0.89, 95% CI 0.81-0.97) and RASGRP1 (HR 0.87, 95% CI 0.81-0.95) was also associated with better DFS. On the contrary, a doubling of FA2H (HR 1.14, 95% CI 1.06-1.22) and GSPT1 (HR 1.33, 95% CI 1.14-1.55) expression was associated with shorter DFS. We identified five genes (EOMES, FA2H, GSPT1, RASGRP1, and SOD2) that may serve as potential prognostic biomarkers and/or therapeutic targets for TNBC.
Win, Aung Ko; Parry, Susan; Parry, Bryan; Kalady, Matthew F; Macrae, Finlay A; Ahnen, Dennis J; Young, Graeme P; Lipton, Lara; Winship, Ingrid; Boussioutas, Alex; Young, Joanne P; Buchanan, Daniel D; Arnold, Julie; Le Marchand, Loïc; Newcomb, Polly A; Haile, Robert W; Lindor, Noralane M; Gallinger, Steven; Hopper, John L; Jenkins, Mark A
Despite regular surveillance colonoscopy, the metachronous colorectal cancer risk for mismatch repair (MMR) gene mutation carriers after segmental resection for colon cancer is high and total or subtotal colectomy is the preferred option. However, if the index cancer is in the rectum, management decisions are complicated by considerations of impaired bowel function. We aimed to estimate the risk of metachronous colon cancer for MMR gene mutation carriers who underwent a proctectomy for index rectal cancer. This retrospective cohort study comprised 79 carriers of germline mutation in a MMR gene (18 MLH1, 55 MSH2, 4 MSH6, and 2 PMS2) from the Colon Cancer Family Registry who had had a proctectomy for index rectal cancer. Cumulative risks of metachronous colon cancer were calculated using the Kaplan-Meier method. During median 9 years (range 1-32 years) of observation since the first diagnosis of rectal cancer, 21 carriers (27 %) were diagnosed with metachronous colon cancer (incidence 24.25, 95 % confidence interval [CI] 15.81-37.19 per 1,000 person-years). Cumulative risk of metachronous colon cancer was 19 % (95 % CI 9-31 %) at 10 years, 47 (95 % CI 31-68 %) at 20 years, and 69 % (95 % CI 45-89 %) at 30 years after surgical resection. The frequency of surveillance colonoscopy was 1 colonoscopy per 1.16 years (95 % CI 1.01-1.31 years). The AJCC stages of the metachronous cancers, where available, were 72 % stage I, 22 % stage II, and 6 % stage III. Given the high metachronous colon cancer risk for MMR gene mutation carriers diagnosed with an index rectal cancer, proctocolectomy may need to be considered.
Full Text Available We implemented LASSO (least absolute shrinkage and selection operator regression to evaluate gene effects in genome-wide association studies (GWAS of brain images, using an MRI-derived temporal lobe volume measure from 729 subjects scanned as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI. Sparse groups of SNPs in individual genes were selected by LASSO, which identifies efficient sets of variants influencing the data. These SNPs were considered jointly when assessing their association with neuroimaging measures. We discovered 22 genes that passed genome-wide significance for influencing temporal lobe volume. This was a substantially greater number of significant genes compared to those found with standard, univariate GWAS. These top genes are all expressed in the brain and include genes previously related to brain function or neuropsychiatric disorders such as MACROD2, SORCS2, GRIN2B, MAGI2, NPAS3, CLSTN2, GABRG3, NRXN3, PRKAG2, GAS7, RBFOX1, ADARB2, CHD4 and CDH13. The top genes we identified with this method also displayed significant and widespread post-hoc effects on voxelwise, tensor-based morphometry (TBM maps of the temporal lobes. The most significantly associated gene was an autism susceptibility gene known as MACROD2. We were able to successfully replicate the effect of the MACROD2 gene in an independent cohort of 564 young, Australian healthy adult twins and siblings scanned with MRI (mean age: 23.8±2.2 SD years. In exploratory analyses, three selected SNPs in the MACROD2 gene were also significantly associated with performance intelligence quotient (PIQ. Our approach powerfully complements univariate techniques in detecting influences of genes on the living brain.
Rouanet, Marie; Lebrin, Marine; Gross, Fabian; Bournet, Barbara; Cordelier, Pierre; Buscail, Louis
A recent death projection has placed pancreatic ductal adenocarcinoma as the second cause of death by cancer in 2030. The prognosis for pancreatic cancer is very poor and there is a great need for new treatments that can change this poor outcome. Developments of therapeutic innovations in combination with conventional chemotherapy are needed urgently. Among innovative treatments the gene therapy offers a promising avenue. The present review gives an overview of the general strategy of gene therapy as well as the limitations and stakes of the different experimental in vivo models, expression vectors (synthetic and viral), molecular tools (interference RNA, genome editing) and therapeutic genes (tumor suppressor genes, antiangiogenic and pro-apoptotic genes, suicide genes). The latest developments in pancreatic carcinoma gene therapy are described including gene-based tumor cell sensitization to chemotherapy, vaccination and adoptive immunotherapy (chimeric antigen receptor T-cells strategy). Nowadays, there is a specific development of oncolytic virus therapies including oncolytic adenoviruses, herpes virus, parvovirus or reovirus. A summary of all published and on-going phase-1 trials is given. Most of them associate gene therapy and chemotherapy or radiochemotherapy. The first results are encouraging for most of the trials but remain to be confirmed in phase 2 trials.
Soemedi, Rachel; Maguire, Samantha; Murray, Michael F.; Monaghan, Sean F.
Substitutions that disrupt pre-mRNA splicing are a common cause of genetic disease. On average, 13.4% of all hereditary disease alleles are classified as splicing mutations mapping to the canonical 5′ and 3′ splice sites. However, splicing mutations present in exons and deeper intronic positions are vastly underreported. A recent re-analysis of coding mutations in exon 10 of the Lynch Syndrome gene, MLH1, revealed an extremely high rate (77%) of mutations that lead to defective splicing. This finding is confirmed by extending the sampling to five other exons in the MLH1 gene. Further analysis suggests a more general phenomenon of defective splicing driving Lynch Syndrome. Of the 36 mutations tested, 11 disrupted splicing. Furthermore, analyzing past reports suggest that MLH1 mutations in canonical splice sites also occupy a much higher fraction (36%) of total mutations than expected. When performing a comprehensive analysis of splicing mutations in human disease genes, we found that three main causal genes of Lynch Syndrome, MLH1, MSH2, and PMS2, belonged to a class of 86 disease genes which are enriched for splicing mutations. Other cancer genes were also enriched in the 86 susceptible genes. The enrichment of splicing mutations in hereditary cancers strongly argues for additional priority in interpreting clinical sequencing data in relation to cancer and splicing. PMID:29505604
Christy L Rhine
Full Text Available Substitutions that disrupt pre-mRNA splicing are a common cause of genetic disease. On average, 13.4% of all hereditary disease alleles are classified as splicing mutations mapping to the canonical 5' and 3' splice sites. However, splicing mutations present in exons and deeper intronic positions are vastly underreported. A recent re-analysis of coding mutations in exon 10 of the Lynch Syndrome gene, MLH1, revealed an extremely high rate (77% of mutations that lead to defective splicing. This finding is confirmed by extending the sampling to five other exons in the MLH1 gene. Further analysis suggests a more general phenomenon of defective splicing driving Lynch Syndrome. Of the 36 mutations tested, 11 disrupted splicing. Furthermore, analyzing past reports suggest that MLH1 mutations in canonical splice sites also occupy a much higher fraction (36% of total mutations than expected. When performing a comprehensive analysis of splicing mutations in human disease genes, we found that three main causal genes of Lynch Syndrome, MLH1, MSH2, and PMS2, belonged to a class of 86 disease genes which are enriched for splicing mutations. Other cancer genes were also enriched in the 86 susceptible genes. The enrichment of splicing mutations in hereditary cancers strongly argues for additional priority in interpreting clinical sequencing data in relation to cancer and splicing.
Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.
Full Text Available Using a modified version of the mRNA differential display technique, five human bladder cancer cell lines from low grade to metastatic were analyzed to identify differences in gene expression. A 316-bp cDNA (C11300 was isolated that was not expressed in the metastatic cell line TccSuP. Sequence analysis revealed that this gene was identical to KIAA 0429, has a 5.3-kb transcript that mapped to 8824.1. The protein is predicted to be 356 amino acids in size and has an actin-binding WH2 domain. Northern blot revealed expression in multiple normal tissues, but none in a metastatic breast cancer cell line (SKBR3 or in metastatic prostatic cancer cell lines (LNCaP, PC3. We have named this gene Missing in Metastasis (MIM and our data suggest that it may be involved in cytoskeletal organization.
Gov, Esra; Kori, Medi; Arga, Kazim Yalcin
Ovarian cancer remains the leading cause of death from a gynecologic malignancy, and treatment of this disease is harder than any other type of female reproductive cancer. Improvements in the diagnosis and development of novel and effective treatment strategies for complex pathophysiologies, such as ovarian cancer, require a better understanding of disease emergence and mechanisms of progression through systems medicine approaches. RNA-level analyses generate new information that can help in understanding the mechanisms behind disease pathogenesis, to identify new biomarkers and therapeutic targets and in new drug discovery. Whole RNA sequencing and coding and non-coding RNA expression array datasets have shed light on the mechanisms underlying disease progression and have identified mRNAs, miRNAs, and lncRNAs involved in ovarian cancer progression. In addition, the results from these analyses indicate that various signalling pathways and biological processes are associated with ovarian cancer. Here, we present a comprehensive literature review on RNA-based ovarian cancer research and highlight the benefits of integrative approaches within the systems biomedicine concept for future ovarian cancer research. We invite the ovarian cancer and systems biomedicine research fields to join forces to achieve the interdisciplinary caliber and rigor required to find real-life solutions to common, devastating, and complex diseases such as ovarian cancer. CAF: cancer-associated fibroblasts; COG: Cluster of Orthologous Groups; DEA: disease enrichment analysis; EOC: epithelial ovarian carcinoma; ESCC: oesophageal squamous cell carcinoma; GSI: gamma secretase inhibitor; GO: Gene Ontology; GSEA: gene set enrichment analyzes; HAS: Hungarian Academy of Sciences; lncRNAs: long non-coding RNAs; MAPK/ERK: mitogen-activated protein kinase/extracellular signal-regulated kinases; NGS: next-generation sequencing; ncRNAs: non-coding RNAs; OvC: ovarian cancer; PI3K
Dobbins, Sara E; Broderick, Peter; Chubb, Daniel; Kinnersley, Ben; Sherborne, Amy L; Houlston, Richard S
Although family history is a major risk factor for colorectal cancer (CRC) a genetic diagnosis cannot be obtained in over 50 % of familial cases when screened for known CRC cancer susceptibility genes. The genetics of undefined-familial CRC is complex and recent studies have implied additional clinically actionable mutations for CRC in susceptibility genes for other cancers. To clarify the contribution of non-CRC susceptibility genes to undefined-familial CRC we conducted a mutational screen of 114 cancer susceptibility genes in 847 patients with early-onset undefined-familial CRC and 1609 controls by analysing high-coverage exome sequencing data. We implemented American College of Medical Genetics and Genomics standards and guidelines for assigning pathogenicity to variants. Globally across all 114 cancer susceptibility genes no statistically significant enrichment of likely pathogenic variants was shown (6.7 % cases 57/847, 5.3 % controls 85/1609; P = 0.15). Moreover there was no significant enrichment of mutations in genes such as TP53 or BRCA2 which have been proposed for clinical testing in CRC. In conclusion, while we identified genes that may be considered interesting candidates as determinants of CRC risk warranting further research, there is currently scant evidence to support a role for genes other than those responsible for established CRC syndromes in the clinical management of familial CRC.
Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Szeto, Ernest; Huang, Jinghua; Reddy, T B K; Cimermančič, Peter; Fischbach, Michael A; Ivanova, Natalia N; Markowitz, Victor M; Kyrpides, Nikos C; Pati, Amrita
In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of "big" genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to
Gretchen H. Roffler; Stephen J. Amish; Seth Smith; Ted Cosart; Marty Kardos; Michael K. Schwartz; Gordon Luikart
Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identify SNP markers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein-coding...
Cai, Peng; Xiong, Xujie; Xu, Yong; Yong, Qiang; Zhu, Junjun; Shiyuan, Yu
At transcriptional level, the inhibitory effects of formic acid was investigated on Candida shehatae, a model yeast strain capable of fermenting xylose to ethanol. Thereby, the target genes were regulated by formic acid and the transcript profiles were discovered. On the basis of the transcriptome data of C. shehatae metabolizing glucose and xylose, the genes responsible for ethanol fermentation were chosen as candidates by the combined method of yeast metabolic pathway analysis and manual gene BLAST search. These candidates were then quantitatively detected by RQ-PCR technique to find the regulating genes under gradient doses of formic acid. By quantitative analysis of 42 candidate genes, we finally identified 10 and 5 genes as markedly down-regulated and up-regulated targets by formic acid, respectively. With regard to gene transcripts regulated by formic acid in C. shehatae, the markedly down-regulated genes ranking declines as follows: xylitol dehydrogenase (XYL2), acetyl-CoA synthetase (ACS), ribose-5-phosphate isomerase (RKI), transaldolase (TAL), phosphogluconate dehydrogenase (GND1), transketolase (TKL), glucose-6-phosphate dehydrogenase (ZWF1), xylose reductase (XYL1), pyruvate dehydrogenase (PDH) and pyruvate decarboxylase (PDC); and a declining rank for up-regulated gens as follows: fructose-bisphosphate aldolase (ALD), glucokinase (GLK), malate dehydrogenase (MDH), 6-phosphofructokinase (PFK) and alcohol dehydrogenase (ADH).
Single nucleotide polymorphisms (SNPs) in immune response genes have been reported as markers of susceptibility to infectious diseases in human and livestock. A disease caused by cyprinid herpes virus 3 (CyHV-3) is highly contagious and virulent in common carp. With the aim to investigate the gene...
Makondi, Precious Takondwa; Lee, Chia-Hwa; Huang, Chien-Yu; Chu, Chi-Ming; Chang, Yu-Jia
Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC) therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO) database (dataset, GSE86525) was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID). Protein–protein interaction (PPI) networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING) and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs); the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1A(CDKN1A), toll-like receptor 4 (TLR4), CD19 molecule (CD19), breast cancer 1, early onset (BRCA1), platelet-derived growth factor subunit A (PDGFA), and matrix metallopeptidase 1 (MMP1) were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4) revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS). The identified genes and pathways
Precious Takondwa Makondi
Full Text Available Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO database (dataset, GSE86525 was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs. Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID. Protein-protein interaction (PPI networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs; the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1A(CDKN1A, toll-like receptor 4 (TLR4, CD19 molecule (CD19, breast cancer 1, early onset (BRCA1, platelet-derived growth factor subunit A (PDGFA, and matrix metallopeptidase 1 (MMP1 were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4 revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS. The identified genes and pathways
Maiyo, Fiona; Singh, Moganavelli
In recent decades, colloidal selenium nanoparticles have emerged as exceptional selenium species with reported chemopreventative and therapeutic properties. This has sparked widespread interest in their use as a carrier of therapeutic agents with results displaying synergistic effects of selenium with its therapeutic cargo and improved anticancer activity. Functionalization remains a critical step in selenium nanoparticles' development for application in gene or drug delivery. In this review, we highlight recent developments in the synthesis and functionalization strategies of selenium nanoparticles used in cancer drug and gene delivery systems. We also provide an update of recent preclinical studies utilizing selenium nanoparticles in cancer therapeutics.
Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen; Nautiyal, Shivani; Flaucher, Diane; Carlton, Victoria EH; Moorhead, Martin; Lu, Yontao; Gray, Joe W; Faham, Malek; Spellman, Paul; Parvin, Bahram
Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fxed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically signifcant negative correlation between methylation profles and gene expression in the
Fillat, Cristina, E-mail: firstname.lastname@example.org; Jose, Anabel; Ros, Xavier Bofill-De; Mato-Berciano, Ana; Maliandi, Maria Victoria; Sobrevals, Luciano [Programa Gens i Malaltia, Centre de Regulació Genòmica-CRG, UPF, Parc de Recerca Biomedica de Barcelona-PRBB and Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona (Spain)
The continuous identification of molecular changes deregulating critical pathways in pancreatic tumor cells provides us with a large number of novel candidates to engineer gene-targeted approaches for pancreatic cancer treatment. Targets—both protein coding and non-coding—are being exploited in gene therapy to influence the deregulated pathways to facilitate cytotoxicity, enhance the immune response or sensitize to current treatments. Delivery vehicles based on viral or non-viral systems as well as cellular vectors with tumor homing characteristics are a critical part of the design of gene therapy strategies. The different behavior of tumoral versus non-tumoral cells inspires vector engineering with the generation of tumor selective products that can prevent potential toxic-associated effects. In the current review, a detailed analysis of the different targets, the delivery vectors, the preclinical approaches and a descriptive update on the conducted clinical trials are presented. Moreover, future possibilities in pancreatic cancer treatment by gene therapy strategies are discussed.
Wendy Anne Gold
Full Text Available Rett syndrome (RTT is a rare, severe disorder of neuronal plasticity that predominantly affects girls. Girls with RTT usually appear asymptomatic in the first 6-18 months of life, but gradually develop severe motor, cognitive and behavioural abnormalities that persist for life. A predominance of neuronal and synaptic dysfunction, with altered excitatory-inhibitory neuronal synaptic transmission and synaptic plasticity are overarching features of RTT in children and in mouse models. Approximately 95% of patients with classical RTT have mutations in the X-linked methyl-CpG-binding (MECP2 gene, whilst other genes, including cyclin-dependent kinase-like 5 (CDKL5, Forkhead box protein G1 (FOXG1, Myocyte-specific enhancer factor 2C (MEF2C and Transcription factor 4 (TCF4, have been associated with phenotypes overlapping with RTT. However, there remain a proportion of patients who carry a clinical diagnosis of RTT, but who are mutation negative. In recent years, next-generation sequencing (NGS technologies have revolutionized approaches to genetic studies, making whole-exome and even whole-genome sequencing possible strategies for the detection of rare and de novo mutations, aiding the discovery of novel disease genes. Here, we review the recent progress that is emerging in identifying pathogenic variations, specifically from exome sequencing in RTT patients, and emphasize the need for the use of this technology to identify known and new disease genes in RTT patients.
Xing, Xiaofang; Du, Hong; Zhou, Chunlian; Zhang, Qingyun; Hao, Chunyi; Wen, Xianzi; Ji, Jiafu
Background Lysosome-associated transmembrane-4 beta (LAPTM4B) is an oncogene that participates tumorgenesis in a variety of human solid tumors, and it has two alleles named as LAPTM4B*1 and *2. The present study aimed to identify the association of LAPTM4B genotype with clinicopathological features and prognosis in colorectal and esophageal cancer patients. Method Genotypes of LAPTM4B were determined by PCR in 167 colon cancer cases (72 patients in a discovery cohort and 95 patients in a testing cohort), 160 rectal cancer cases and 164 esophageal cancer cases. Association between the LAPTM4B gene polymorphism and clinicopathological variables was calculated by Chi-square test or Fisher’s exact test. Patient survival differences were calculated by the Kaplan-Meier method. Prognostic factors were determined with Log-rank test and Cox regression model. Results LAPTM4B *1/1 was more frequently detected in colon cancer patients with lymph node metastasis and TNM III+IV stages in total colon cancer (discovery + testing cohorts). LAPTM4B *2/2 decreased in recurrent patients in total colon cancer patients (P = 0.045). Kaplan-Meier survival curves and Log-rank test showed that LAPTM4B*1 was correlated with shorter overall survival (OS) in discovery and testing cohorts of colon cancer (P = 0.0254 and 0.0292, respectively), but not in rectal and esophageal cancer cases (P = 0.7669 and 0.9356, respectively). Multivariate analysis showed that LAPTM4B genotype was an independent prognostic factor for OS in total colon cancer [P = 0.004, hazard ratio (HR) = 0.432; 95% confidence interval (CI) = 0.243–0.768], but not in rectal and esophageal cancers (P = 0.791, HR = 1.073, 95% CI = 0.638–1.804 and 0.998, HR = 1.000, 95% CI = 0.663–1.530, respectively). Conclusion These findings suggested that LAPTM4B allele *1 was a risk factor associated with poor prognosis in patients with colon cancer, but not in patients with rectal or esophageal cancers. LAPTM4B genotype status might
Full Text Available Lysosome-associated transmembrane-4 beta (LAPTM4B is an oncogene that participates tumorgenesis in a variety of human solid tumors, and it has two alleles named as LAPTM4B*1 and *2. The present study aimed to identify the association of LAPTM4B genotype with clinicopathological features and prognosis in colorectal and esophageal cancer patients.Genotypes of LAPTM4B were determined by PCR in 167 colon cancer cases (72 patients in a discovery cohort and 95 patients in a testing cohort, 160 rectal cancer cases and 164 esophageal cancer cases. Association between the LAPTM4B gene polymorphism and clinicopathological variables was calculated by Chi-square test or Fisher's exact test. Patient survival differences were calculated by the Kaplan-Meier method. Prognostic factors were determined with Log-rank test and Cox regression model.LAPTM4B *1/1 was more frequently detected in colon cancer patients with lymph node metastasis and TNM III+IV stages in total colon cancer (discovery + testing cohorts. LAPTM4B *2/2 decreased in recurrent patients in total colon cancer patients (P = 0.045. Kaplan-Meier survival curves and Log-rank test showed that LAPTM4B*1 was correlated with shorter overall survival (OS in discovery and testing cohorts of colon cancer (P = 0.0254 and 0.0292, respectively, but not in rectal and esophageal cancer cases (P = 0.7669 and 0.9356, respectively. Multivariate analysis showed that LAPTM4B genotype was an independent prognostic factor for OS in total colon cancer [P = 0.004, hazard ratio (HR = 0.432; 95% confidence interval (CI = 0.243-0.768], but not in rectal and esophageal cancers (P = 0.791, HR = 1.073, 95% CI = 0.638-1.804 and 0.998, HR = 1.000, 95% CI = 0.663-1.530, respectively.These findings suggested that LAPTM4B allele *1 was a risk factor associated with poor prognosis in patients with colon cancer, but not in patients with rectal or esophageal cancers. LAPTM4B genotype status might be a useful prognostic indicator for
Paul F. Meeh
Full Text Available We used digital long serial analysis of gene expression to discover gene expression differences between node-negative and node-positive colorectal tumors and developed a multigene classifier able to discriminate between these two tumor types. We prepared and sequenced long serial analysis of gene expression libraries from one node-negative and one node-positive colorectal tumor, sequenced to a depth of 26,060 unique tags, and identified 262 tags significantly differentially expressed between these two tumors (P < 2 x 10-6. We confirmed the tag-to-gene assignments and differential expression of 31 genes by quantitative real-time polymerase chain reaction, 12 of which were elevated in the node-positive tumor. We analyzed the expression levels of these 12 upregulated genes in a validation panel of 23 additional tumors and developed an optimized seven-gene logistic regression classifier. The classifier discriminated between node-negative and node-positive tumors with 86% sensitivity and 80% specificity. Receiver operating characteristic analysis of the classifier revealed an area under the curve of 0.86. Experimental manipulation of the function of one classification gene, Fibronectin, caused profound effects on invasion and migration of colorectal cancer cells in vitro. These results suggest that the development of node-positive colorectal cancer occurs in part through elevated epithelial FN1 expression and suggest novel strategies for the diagnosis and treatment of advanced disease.
Full Text Available BACKGROUND: There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached. RESULTS: In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR control approach and that the reproducibility of DE peak detection could thereby be increased. CONCLUSIONS: Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers.
Xu, Yan; Zou, Peng; Liu, Yao; Deng, Fengjiao
Genes specifically expressed in the notochord may be crucial for proper notochord development. Using the digital differential display program offered by the National Center for Biotechnology Information, we identified a novel EST sequence from a zebrafish ovary library (No. XM_701450). The full-length cDNA of this transcript was cloned by performing 3' and 5'-RACE and was further confirmed by PCR and sequencing. The resulting 614 bp gene was found to encode a novel 94 amino acid protein that did not share significant homology with any other known protein. Characterization of the genomic sequence revealed that the gene spanned 4.9 kb and was composed of four exons and three introns. RT-PCR gene expression analysis revealed that our gene of interest was expressed in ovary, kidney, brain, mature oocytes and during the early stages of embryogenesis. During embryonic development, znfr mRNA was found to be expressed in the embryonic shield, chordamesoderm and the vacuolated notochord cells by in situ hybridization. Based on this information, we hypothesize that this novel gene is an important maternal factor required for zebrafish notochord formation during early embryonic development. We have thus named this gene znfr (zebrafish notochord formation related).
Full Text Available Abstract Background Grosmannia clavigera is a bark beetle-vectored fungal pathogen of pines that causes wood discoloration and may kill trees by disrupting nutrient and water transport. Trees respond to attacks from beetles and associated fungi by releasing terpenoid and phenolic defense compounds. It is unclear which genes are important for G. clavigera's ability to overcome antifungal pine terpenoids and phenolics. Results We constructed seven cDNA libraries from eight G. clavigera isolates grown under various culture conditions, and Sanger sequenced the 5' and 3' ends of 25,000 cDNA clones, resulting in 44,288 high quality ESTs. The assembled dataset of unique transcripts (unigenes consists of 6,265 contigs and 2,459 singletons that mapped to 6,467 locations on the G. clavigera reference genome, representing ~70% of the predicted G. clavigera genes. Although only 54% of the unigenes matched characterized proteins at the NCBI database, this dataset extensively covers major metabolic pathways, cellular processes, and genes necessary for response to environmental stimuli and genetic information processing. Furthermore, we identified genes expressed in spores prior to germination, and genes involved in response to treatment with lodgepole pine phloem extract (LPPE. Conclusions We provide a comprehensively annotated EST dataset for G. clavigera that represents a rich resource for gene characterization in this and other ophiostomatoid fungi. Genes expressed in response to LPPE treatment are indicative of fungal oxidative stress response. We identified two clusters of potentially functionally related genes responsive to LPPE treatment. Furthermore, we report a simple method for identifying contig misassemblies in de novo assembled EST collections caused by gene overlap on the genome.
Prostate cancer (PC) is one of the most commonly diagnosed cancers in men. PC is relatively difficult to diagnose due to a lack of clear early symptoms. Extensive research of PC has led to the availability of a large amount of data on PC. Several hundred genes are implicated in different stages of PC, which may help in developing diagnostic methods or even cures. In spite of this accumulated information, effective diagnostics and treatments remain evasive. We have developed Dragon Database of Genes associated with Prostate Cancer (DDPC) as an integrated knowledgebase of genes experimentally verified as implicated in PC. DDPC is distinctive from other databases in that (i) it provides pre-compiled biomedical text-mining information on PC, which otherwise require tedious computational analyses, (ii) it integrates data on molecular interactions, pathways, gene ontologies, gene regulation at molecular level, predicted transcription factor binding sites on promoters of PC implicated genes and transcription factors that correspond to these binding sites and (iii) it contains DrugBank data on drugs associated with PC. We believe this resource will serve as a source of useful information for research on PC. DDPC is freely accessible for academic and non-profit users via http://apps.sanbi.ac.za/ddpc/ and http://cbrc .kaust.edu.sa/ddpc/. The Author(s) 2010.
Full Text Available In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of $351$ patient samples. In order to elucidate the functional relevance of the inferred network, we are performing a Gene Ontology (GO analysis for its structural components. Our analysis reveals that most significant GO-terms we find for the breast cancer network represent functional modules of biological processes that are described by known cancer hallmarks, including translation, immune response, cell cycle, organelle fission, mitosis, cell adhesion, RNA processing, RNA splicing and response to wounding. Furthermore, by using a curated list of census cancer genes, we find an enrichment in these functional modules. Finally, we study cooperative effects of chromosomes based on information of interacting genes in the beast cancer network. We find that chromosome $21$ is most coactive with other chromosomes. To our knowledge this is the first study investigating the genome-scale breast cancer network.
Gianni, Luca; Zambetti, Milvia; Clark, Kim; Baker, Joffre; Cronin, Maureen; Wu, Jenny; Mariani, Gabriella; Rodriguez, Jaime; Carcangiu, Marialuisa; Watson, Drew; Valagussa, Pinuccia; Rouzier, Roman; Symmans, W Fraser; Ross, Jeffrey S; Hortobagyi, Gabriel N; Pusztai, Lajos; Shak, Steven
We sought to identify gene expression markers that predict the likelihood of chemotherapy response. We also tested whether chemotherapy response is correlated with the 21-gene Recurrence Score assay that quantifies recurrence risk. Patients with locally advanced breast cancer received neoadjuvant paclitaxel and doxorubicin. RNA was extracted from the pretreatment formalin-fixed paraffin-embedded core biopsies. The expression of 384 genes was quantified using reverse transcriptase polymerase chain reaction and correlated with pathologic complete response (pCR). The performance of genes predicting for pCR was tested in patients from an independent neoadjuvant study where gene expression was obtained using DNA microarrays. Of 89 assessable patients (mean age, 49.9 years; mean tumor size, 6.4 cm), 11 (12%) had a pCR. Eighty-six genes correlated with pCR (unadjusted P < .05); pCR was more likely with higher expression of proliferation-related genes and immune-related genes, and with lower expression of estrogen receptor (ER) -related genes. In 82 independent patients treated with neoadjuvant paclitaxel and doxorubicin, DNA microarray data were available for 79 of the 86 genes. In univariate analysis, 24 genes correlated with pCR with P < .05 (false discovery, four genes) and 32 genes showed correlation with P < .1 (false discovery, eight genes). The Recurrence Score was positively associated with the likelihood of pCR (P = .005), suggesting that the patients who are at greatest recurrence risk are more likely to have chemotherapy benefit. Quantitative expression of ER-related genes, proliferation genes, and immune-related genes are strong predictors of pCR in women with locally advanced breast cancer receiving neoadjuvant anthracyclines and paclitaxel.
Bager, Peter; Wohlfahrt, Jan; Sørensen, Erik
BACKGROUND: As carriers of filaggrin gene (FLG) mutations may have a compromised cervical mucosal barrier against human papillomavirus infection, our primary objective was to study their risk of cervical cancer. METHODS: We genotyped 586 cervical cancer patients for the two most common FLG...... mutations, R501X and 2282del4, using blood from the Copenhagen Hospital Biobank, Denmark. Controls (n = 8050) were genotyped in previous population-based studies. Information on cervical cancer, mortality and emigration were obtained from national registers. Odds ratios (OR) were estimated by logistic...... and stratification by cancer stage. RESULTS: The primary results showed that FLG mutations were not associated with the risk of cervical cancer (6.3% of cases and 7.7% of controls were carriers; OR adjusted 0.81, 95% CI 0.57-1.14; OR adjusted+ weighted 0.96, 95% CI 0.58-1.57). Among cases, FLG mutations increased...
Linda M Dong
Full Text Available We conducted a case-control study of renal cancer (987 cases and 1298 controls in Central and Eastern Europe and analyzed genomic DNA for 319 tagging single-nucleotide polymorphisms (SNPs in 21 genes involved in cellular growth, differentiation and apoptosis using an Illumina Oligo Pool All (OPA. A haplotype-based method (sliding window analysis of consecutive SNPs was used to identify chromosome regions of interest that remained significant at a false discovery rate of 10%. Subsequently, risk estimates were generated for regions with a high level of signal and individual SNPs by unconditional logistic regression adjusting for age, gender and study center. Three regions containing genes associated with renal cancer were identified: caspase 1/5/4/12(CASP 1/5/4/12, epidermal growth factor receptor (EGFR, and insulin-like growth factor binding protein-3 (IGFBP3. We observed that individuals with CASP1/5/4/12 haplotype (spanning area upstream of CASP1 through exon 2 of CASP5 GGGCTCAGT were at higher risk of renal cancer compared to individuals with the most common haplotype (OR:1.40, 95% CI:1.10-1.78, p-value = 0.007. Analysis of EGFR revealed three strong signals within intron 1, particularly a region centered around rs759158 with a global p = 0.006 (GGG: OR:1.26, 95% CI:1.04-1.53 and ATG: OR:1.55, 95% CI:1.14-2.11. A region in IGFBP3 was also associated with increased risk (global p = 0.04. In addition, the number of statistically significant (p-value<0.05 SNP associations observed within these three genes was higher than would be expected by chance on a gene level. To our knowledge, this is the first study to evaluate these genes in relation to renal cancer and there is need to replicate and extend our findings. The specific regions associated with risk may have particular relevance for gene function and/or carcinogenesis. In conclusion, our evaluation has identified common genetic variants in CASP1, CASP5, EGFR, and IGFBP3 that could be
Goebel, Katie; Merner, Nancy D
Canines are excellent models for cancer studies due to their similar physiology and genomic sequence to humans, companion status and limited intra-breed heterogeneity. Due to their affliction to mammary cancers, canines can serve as powerful genetic models of hereditary breast cancers. Variants within known human breast cancer susceptibility genes only explain a fraction of familial cases. Thus, further discovery is necessary but such efforts have been thwarted by genetic heterogeneity. Reducing heterogeneity is key, and studying isolated human populations have helped in the endeavour. An alternative is to study dog pedigrees, since artificial selection has resulted in extreme homogeneity. Identifying the genetic predisposition to canine mammary tumours can translate to human discoveries - a strategy currently underutilized. To explore this potential, we reviewed published canine mammary tumour genetic studies and proposed benefits of next generation sequencing canine cohorts to facilitate moving beyond incremental advances.
van Poppel, Hein; Haese, Alexander; Graefen, Markus; de la Taille, Alexandre; Irani, Jacques; de Reijke, Theo; Remzi, Mesut; Marberger, Michael
OBJECTIVE To evaluate the relationship between Prostate CAncer gene 3 (PCA3) and prostate cancer significance. PATIENTS AND METHODS Clinical data from two multi-centre European open-label, prospective studies evaluating the clinical utility of the PCA3 assay in guiding initial and repeat biopsy
As we enter the era of precision medicine, characterization of cancer genomes will directly influence therapeutic decisions in the clinic. Here we describe a platform enabling functionalization of rare gene mutations through their high-throughput construction, molecular barcoding and delivery to cancer models for in vivo tumour driver screens. We apply these technologies to identify oncogenic drivers of pancreatic ductal adenocarcinoma (PDAC).
Lund, Anders H; van Lohuizen, Maarten
The RUNX family of transcription factors plays pivotal roles during normal development and in neoplasias. Recent data involve RUNX3 as an important tumor suppressor in gastric cancers and pose interesting questions about how perturbed levels and interspecific competition among RUNX family members...
The S100 gene family encode low molecular weight proteins implicated in cancer progression. In this study, we analyzed the expression of four S100 genes in one cohort of patients with breast cancer and 16 S100 genes in a second cohort. In both cohorts, the expression of S100A8 and S1009 mRNA level was elevated in high-grade compared to low-grade tumors and in estrogen receptor-negative compared to estrogen receptor-positive tumors. None of the S100 transcripts investigated were significantly associated with the presence of lymph node metastasis. Notably, multiple S100 genes, including S100A1, S100A2, S100A4, S100A6, S100A8, S100A9, S100A10, S100A11, and S100A14 were upregulated in basal-type breast cancers compared to non-basal types. Using Spearman\\'s correlation analysis, several S100 transcripts correlated significantly with each other, the strongest correlation has been found between S100A8 and S100A9 (r = 0.889, P < 0.001, n = 295). Of the 16 S100 transcripts investigated, only S100A11 and S100A14 were significantly associated with patient outcome. Indeed, these two transcripts predicted outcome in the cohort of patients that did not receive systemic adjuvant therapy. Based on our findings, we conclude that the different S100 genes play varying roles in breast cancer progression. Specific S100 genes are potential targets for the treatment of basal-type breast cancers.
The S100 gene family encode low molecular weight proteins implicated in cancer progression. In this study, we analyzed the expression of four S100 genes in one cohort of patients with breast cancer and 16 S100 genes in a second cohort. In both cohorts, the expression of S100A8 and S1009 mRNA level was elevated in high-grade compared to low-grade tumors and in estrogen receptor-negative compared to estrogen receptor-positive tumors. None of the S100 transcripts investigated were significantly associated with the presence of lymph node metastasis. Notably, multiple S100 genes, including S100A1, S100A2, S100A4, S100A6, S100A8, S100A9, S100A10, S100A11, and S100A14 were upregulated in basal-type breast cancers compared to non-basal types. Using Spearman\\'s correlation analysis, several S100 transcripts correlated significantly with each other, the strongest correlation has been found between S100A8 and S100A9 (r = 0.889, P < 0.001, n = 295). Of the 16 S100 transcripts investigated, only S100A11 and S100A14 were significantly associated with patient outcome. Indeed, these two transcripts predicted outcome in the cohort of patients that did not receive systemic adjuvant therapy. Based on our findings, we conclude that the different S100 genes play varying roles in breast cancer progression. Specific S100 genes are potential targets for the treatment of basal-type breast cancers.
Salem, Saeed; Alroobi, Rami; Banitaan, Shadi; Seridi, Loqmane; Aljarah, Ibrahim; Brewer, James
networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional
Meehan, Terrence F.; Conte, Nathalie; West, David B.; Jacobsen, Julius O.; Mason, Jeremy; Warren, Jonathan; Chen, Chao-Kung; Tudose, Ilinca; Relac, Mike; Matthews, Peter; Karp, Natasha; Santos, Luis; Fiegel, Tanja; Ring, Natalie; Westerberg, Henrik; Greenaway, Simon; Sneddon, Duncan; Morgan, Hugh; Codner, Gemma F; Stewart, Michelle E; Brown, James; Horner, Neil; Haendel, Melissa; Washington, Nicole; Mungall, Christopher J.; Reynolds, Corey L; Gallegos, Juan; Gailus-Durner, Valerie; Sorg, Tania; Pavlovic, Guillaume; Bower, Lynette R; Moore, Mark; Morse, Iva; Gao, Xiang; Tocchini-Valentini, Glauco P; Obata, Yuichi; Cho, Soo Young; Seong, Je Kyung; Seavitt, John; Beaudet, Arthur L.; Dickinson, Mary E.; Herault, Yann; Wurst, Wolfgang; de Angelis, Martin Hrabe; Lloyd, K.C. Kent; Flenniken, Ann M; Nutter, Lauryl MJ; Newbigging, Susan; McKerlie, Colin; Justice, Monica J.; Murray, Stephen A.; Svenson, Karen L.; Braun, Robert E.; White, Jacqueline K.; Bradley, Allan; Flicek, Paul; Wells, Sara; Skarnes, William C.; Adams, David J.; Parkinson, Helen; Mallon, Ann-Marie; Brown, Steve D.M.; Smedley, Damian
Although next generation sequencing has revolutionised the ability to associate variants with human diseases, diagnostic rates and development of new therapies are still limited by our lack of knowledge of function and pathobiological mechanism for most genes. To address this challenge, the International Mouse Phenotyping Consortium (IMPC) is creating a genome- and phenome-wide catalogue of gene function by characterizing new knockout mouse strains across diverse biological systems through a broad set of standardised phenotyping tests, with all mice made readily available to the biomedical community. Analysing the first 3328 genes reveals models for 360 diseases including the first for type C Bernard-Soulier, Bardet-Biedl-5 and Gordon Holmes syndromes. 90% of our phenotype annotations are novel, providing the first functional evidence for 1092 genes and candidates in unsolved diseases such as Arrhythmogenic Right Ventricular Dysplasia 3. Finally, we describe our role in variant functional validation with the 100,000 Genomes and other projects. PMID:28650483
Landmark-Hoyvik, Hege; Dumeaux, Vanessa; Reinertsen, Kristin V.; Edvardsen, Hege; Fossa, Sophie D.; Borresen-Dale, Anne-Lise
Purpose: To extend knowledge on the mechanisms and pathways involved in maintenance of radiation-induced fibrosis (RIF) by performing gene expression profiling of whole blood from breast cancer (BC) survivors with and without fibrosis 3-7 years after end of radiotherapy treatment. Methods and Materials: Gene expression profiles from blood were obtained for 254 BC survivors derived from a cohort of survivors, treated with adjuvant radiotherapy for breast cancer 3-7 years earlier. Analyses of transcriptional differences in blood gene expression between BC survivors with fibrosis (n = 31) and BC survivors without fibrosis (n = 223) were performed using R version 2.8.0 and tools from the Bioconductor project. Gene sets extracted through a literature search on fibrosis and breast cancer were subsequently used in gene set enrichment analysis. Results: Substantial differences in blood gene expression between BC survivors with and without fibrosis were observed, and 87 differentially expressed genes were identified through linear analysis. Transforming growth factor-β1 signaling was identified as the most significant gene set, showing a down-regulation of most of the core genes, together with up-regulation of a transcriptional activator of the inhibitor of fibrinolysis, Plasminogen activator inhibitor 1 in the BC survivors with fibrosis. Conclusion: Transforming growth factor-β1 signaling was found down-regulated during the maintenance phase of fibrosis as opposed to the up-regulation reported during the early, initiating phase of fibrosis. Hence, once the fibrotic tissue has developed, the maintenance phase might rather involve a deregulation of fibrinolysis and altered degradation of extracellular matrix components.
Full Text Available The incidence and mortality of colorectal cancer (CRC is higher in African Americans (AAs than other ethnic groups in the U. S., but reasons for the disparities are unknown. We performed gene expression profiling of sporadic CRCs from AAs vs. European Americans (EAs to assess the contribution to CRC disparities. We evaluated the gene expression of 43 AA and 43 EA CRC tumors matched by stage and 40 matching normal colorectal tissues using the Agilent human whole genome 4x44K cDNA arrays. Gene and pathway analyses were performed using Significance Analysis of Microarrays (SAM, Ten-fold cross validation, and Ingenuity Pathway Analysis (IPA. SAM revealed that 95 genes were differentially expressed between AA and EA patients at a false discovery rate of ≤5%. Using IPA we determined that most prominent disease and pathway associations of differentially expressed genes were related to inflammation and immune response. Ten-fold cross validation demonstrated that following 10 genes can predict ethnicity with an accuracy of 94%: CRYBB2, PSPH, ADAL, VSIG10L, C17orf81, ANKRD36B, ZNF835, ARHGAP6, TRNT1 and WDR8. Expression of these 10 genes was validated by qRT-PCR in an independent test set of 28 patients (10 AA, 18 EA. Our results are the first to implicate differential gene expression in CRC racial disparities and indicate prominent difference in CRC inflammation between AA and EA patients. Differences in susceptibility to inflammation support the existence of distinct tumor microenvironments in these two patient populations.
Zapata, Andres; Neme, Rafik; Sanabria, Carolina; Lopez, Camilo
Cassava (Manihot esculenta) is the main source of calories for more than 1,000 millions of people around the world and has been consolidated as the fourth most important crop after rice, corn and wheat. Cassava is considered tolerant to abiotic and biotic stress conditions; nevertheless these characteristics are mainly present in non-commercial varieties. Genetic breeding strategies represent an alternative to introduce the desirable characteristics into commercial varieties. A fundamental step for accelerating the genetic breeding process in cassava requires the identification of genes associated to these characteristics. One rapid strategy for the identification of genes is the possibility to have a large collection of ESTs (expressed sequence tag). In this study, a complete analysis of cassava ESTs was done. The cassava ESTs represent 80,459 sequences which were assembled in a set of 29,231 unique genes (unigen), comprising 10,945 contigs and 18,286 singletones. These 29,231 unique genes represent about 80% of the genes of the cassava's genome. Between 5% and 10% of the unigenes of cassava not show similarity to any sequences present in the NCBI database and could be consider as cassava specific genes. a functional category was assigned to a group of sequences of the unigen set (29%) following the Gene Ontology Vocabulary. the molecular function component was the best represented with 43% of the sequences, followed by the biological process component (38%) and finally the cellular component with 19%. in the cassava ESTs collection, 3,709 microsatellites were identified and they could be used as molecular markers. this study represents an important contribution to the knowledge of the functional genomic structure of cassava and constitutes an important tool for the identification of genes associated to agricultural characteristics of interest that could be employed in cassava breeding programs.
Yu, Guotai; Champouret, Nicolas; Steuernagel, Burkhard; Olivera, Pablo D; Simmons, Jamie; Williams, Cole; Johnson, Ryan; Moscou, Matthew J; Hernández-Pinzón, Inmaculada; Green, Phon; Sela, Hanan; Millet, Eitan; Jones, Jonathan D G; Ward, Eric R; Steffenson, Brian J; Wulff, Brande B H
We identified two novel wheat stem rust resistance genes, Sr-1644-1Sh and Sr-1644-5Sh in Aegilops sharonensis that are effective against widely virulent African races of the wheat stem rust pathogen. Stem rust is one of the most important diseases of wheat in the world. When single stem rust resistance (Sr) genes are deployed in wheat, they are often rapidly overcome by the pathogen. To this end, we initiated a search for novel sources of resistance in diverse wheat relatives and identified the wild goatgrass species Aegilops sharonesis (Sharon goatgrass) as a rich reservoir of resistance to wheat stem rust. The objectives of this study were to discover and map novel Sr genes in Ae. sharonensis and to explore the possibility of identifying new Sr genes by genome-wide association study (GWAS). We developed two biparental populations between resistant and susceptible accessions of Ae. sharonensis and performed QTL and linkage analysis. In an F 6 recombinant inbred line and an F 2 population, two genes were identified that mapped to the short arm of chromosome 1S sh , designated as Sr-1644-1Sh, and the long arm of chromosome 5S sh , designated as Sr-1644-5Sh. The gene Sr-1644-1Sh confers a high level of resistance to race TTKSK (a member of the Ug99 race group), while the gene Sr-1644-5Sh conditions strong resistance to TRTTF, another widely virulent race found in Yemen. Additionally, GWAS was conducted on 125 diverse Ae. sharonensis accessions for stem rust resistance. The gene Sr-1644-1Sh was detected by GWAS, while Sr-1644-5Sh was not detected, indicating that the effectiveness of GWAS might be affected by marker density, population structure, low allele frequency and other factors.
Full Text Available Puccinellia tenuiflora is a monocotyledonous halophyte that is able to survive in extreme saline soil environments at an alkaline pH range of 9–10. In this study, we transformed full-length cDNAs of P. tenuiflora into Saccharomyces cerevisiae by using the full-length cDNA over-expressing gene-hunting system to identify novel salt-tolerance genes. In all, 32 yeast clones overexpressing P. tenuiflora cDNA were obtained by screening under NaCl stress conditions; of these, 31 clones showed stronger tolerance to NaCl and were amplified using polymerase chain reaction (PCR and sequenced. Four novel genes encoding proteins with unknown function were identified; these genes had no homology with genes from higher plants. Of the four isolated genes, two that encoded proteins with two transmembrane domains showed the strongest resistance to 1.3 M NaCl. RT-PCR and northern blot analysis of P. tenuiflora cultured cells confirmed the endogenous NaCl-induced expression of the two proteins. Both of the proteins conferred better tolerance in yeasts to high salt, alkaline and osmotic conditions, some heavy metals and H2O2 stress. Thus, we inferred that the two novel proteins might alleviate oxidative and other stresses in P. tenuiflora.
Gustavo A Gomez
Full Text Available The transcription factor Etsrp is required for vasculogenesis and primitive myelopoiesis in zebrafish. When ectopically expressed, etsrp is sufficient to induce the expression of many vascular and myeloid genes in zebrafish. The mammalian homolog of etsrp, ER71/Etv2, is also essential for vascular and hematopoietic development. To identify genes downstream of etsrp, gain-of-function experiments were performed for etsrp in zebrafish embryos followed by transcription profile analysis by microarray. Subsequent in vivo expression studies resulted in the identification of fourteen genes with blood and/or vascular expression, six of these being completely novel. Regulation of these genes by etsrp was confirmed by ectopic induction in etsrp overexpressing embryos and decreased expression in etsrp deficient embryos. Additional functional analysis of two newly discovered genes, hapln1b and sh3gl3, demonstrates their importance in embryonic vascular development. The results described here identify a group of genes downstream of etsrp likely to be critical for vascular and/or myeloid development.
Raskin, Leon; Guo, Yan; Du, Liping; Clendenning, Mark; Rosty, Christophe; Lindor, Noralane M; Gruber, Stephen B; Buchanan, Daniel D
The underlying genetic cause of colorectal cancer (CRC) can be identified for 5-10% of all cases, while at least 20% of CRC cases are thought to be due to inherited genetic factors. Screening for highly penetrant mutations in genes associated with Mendelian cancer syndromes using next-generation sequencing (NGS) can be prohibitively expensive for studies requiring large samples sizes. The aim of the study was to identify rare single nucleotide variants and small indels in 40 established or candidate CRC susceptibility genes in 1,046 familial CRC cases (including both MSS and MSI-H tumor subtypes) and 1,006 unrelated controls from the Colon Cancer Family Registry Cohort using a robust and cost-effective DNA pooling NGS strategy. We identified 264 variants in 38 genes that were observed only in cases, comprising either very rare (minor allele frequency cancer susceptibility genes BAP1, CDH1, CHEK2, ENG, and MSH3 . For the candidate CRC genes, we identified likely pathogenic variants in the helicase domain of POLQ and in the LRIG1 , SH2B3 , and NOS1 genes and present their clinicopathological characteristics. Using a DNA pooling NGS strategy, we identified novel germline mutations in established CRC susceptibility genes in familial CRC cases. Further studies are required to support the role of POLQ , LRIG1 , SH2B3 and NOS1 as CRC susceptibility genes.
Chen, I-Hsuan; Aguilar, Hillary Andaluz; Paez Paez, J Sebastian; Wu, Xiaofeng; Pan, Li; Wendt, Michael K; Iliuk, Anton B; Zhang, Ying; Tao, W Andy
Glycoproteins comprise more than half of current FDA-approved protein cancer markers, but the development of new glycoproteins as disease biomarkers has been stagnant. Here we present a pipeline to develop glycoproteins from extracellular vesicles (EVs) through integrating quantitative glycoproteomics with a novel reverse phase glycoprotein array and then apply it to identify novel biomarkers for breast cancer. EV glycoproteomics show promise in circumventing the problems plaguing current serum/plasma glycoproteomics and allowed us to identify hundreds of glycoproteins that have not been identified in blood. We identified 1,453 unique glycopeptides representing 556 glycoproteins in EVs, among which 20 were verified significantly higher in individual breast cancer patients. We further applied a novel glyco-specific reverse phase protein array to quantify a subset of the candidates. Together, this study demonstrates the great potential of this integrated pipeline for biomarker discovery.
Sep 29, 2015 ... mance of GFI is compared with 19 exiting cluster validity indices. The results .... Using k-means algorithm on human lung expression data, we have found ... of possible genes that mediate the development of a cancer. In other ...
Heineman, Richard H.
These three biology songs can be used for educational purposes to teach about biochemical concepts. They touch on three different topics: (1) cancer progression and germ cells, (2) gene expression, promoters, and repressors, and (3) electronegativity and the biochemical basis of photosynthesis.
de Vrij, J.; Willemsen, R. A.; Lindholm, L.; Hoeben, R. C.; Bangma, Ch. H.; Barber, Ch.; Behr, J.-P.; Briggs, S.; Carlisle, R.; Cheng, W.-S.; Dautzenberg, I. J. C.; de Ridder, C.; Dzojic, H.; Erbacher, P.; Essand, M.; Fisher, K.; Frazier, A.; Georgopoulos, L. J.; Jennings, I.; Kochanek, S.; Koppers-Lalic, D.; Kraaij, R.; Kreppel, F.; Magnusson, M.; Maitland, N.; Neuberg, P.; Nugent, R.; Ogris, M.; Remy, J.-S.; Scaife, M.; Schenk, E.; Schooten, E.; Seymour, L.; Slade, M.; Szyjanowicz, P.; Totterman, T.; Uil, T. G.; Ulbrich, Karel; van der Weel, L.; van Weerden, W.; Wagner, E.; Zuber, G.
Roč. 21, č. 7 (2010), s. 795-805 ISSN 1043-0342 EU Projects: European Commission(XE) 512087 - GIANT Keywords : adenovirus * gene delivery * prostate cancer Subject RIV: CD - Macromolecular Chemistry Impact factor: 4.829, year: 2010
The Food and Drug Administration has approved olaparib (Lynparza®) to treat metastatic breast cancers that have inherited mutations in the BRCA1 or BRCA2 genes as well as a companion diagnostic test for selecting candidates for the therapy.
Christensen, C.L.; Zandi, R.; Gjetting, T.
Small-cell lung cancer (SCLC) is a highly malignant disease with poor prognosis. Hence, there is great demand for new therapies that can replace or supplement the current available treatment regimes. Gene therapy constitutes a promising strategy and relies on the principle of introducing exogenous...
Yardy, George W; Bicknell, David C; Wilding, Jennifer L
The Wnt signalling pathway directs aspects of embryogenesis and is thought to contribute to maintenance of certain stem cell populations. Disruption of the pathway has been observed in many different tumour types. In bowel, stomach, and endometrial cancer, this is usually due to mutation of genes...
A hypothesis is presented in which the process of "malignant transformation" which ultimately results in the rapidly dividing tumor(s)(cells) causing "cancer", is regarded as an evolved reproductive strategy of "ultra-selfish" (proto-)(onco-) genes, already present in the genome, or introduced by a
Schuiling, G A
A hypothesis is presented in which the process of "malignant transformation" which ultimately results in the rapidly dividing tumor(s)(cells) causing "cancer", is regarded as an evolved reproductive strategy of "ultra-selfish" (proto-)(onco-) genes, already present in the genome, or introduced by a virus.
Burada, F.; Plantinga, T.S.; Ioana, M.; Rosentul, D.; Angelescu, C.; Joosten, L.A.B.; Netea, M.G.; Saftoiu, A.
OBJECTIVE: The study aimed to assess the possible association of polymorphisms in the autophagy gene IRGM (rs13361189 and rs4958847) with the risk of gastric cancer. METHODS: A total of 102 patients with gastric adenocarcinoma, 52 with chronic gastritis and 351 healthy controls were included in this
Abdulkarim Yasin Karim
Full Text Available Purpose: Gastric cancer has high incidence and mortality rate in several countries and is still one of the most frequent and lethal disease. In this study, we aimed to determine diagnostic markers in gastric cancer by molecular techniques; include mRNA expression analysis of FABP4 gene. Fatty acid binding protein 4 (FABP4 gene encodes the fatty acid binding protein found in adipocytes. The protein encoded by FABP4 are a family of small, highly conserved, cytoplasmic proteins that bind long-chain fatty acids and other hydrophobic ligands. It is thought that FABPs roles include fatty acid uptake, transport, and metabolism. Material and Methods: Total RNA were extracted from paired tumor and normal tissues of 47 gastric cancer. The mRNA expression level of FABP4 was measured employing semi- quantitative reverse transcription- polymerase chain reaction (RT- PCR. Results: The mRNA expression level of FABP4 was significantly decreased (down- regulated. Conclusion: Down-regulation of FABP4 gene seems to occur at the initial steps of gastric cancer development. In order to confirm the relationship between the gastric tumor and FABP4 gene, further analysis like immunohistochemistry and epigenetc techniques are necessary. [Cukurova Med J 2016; 41(2.000: 248-252
D. Gasi (Delila)
markdownabstract__Abstract__ Prostate cancer is a heterogeneous disease that is very common in elderly men in developed countries. Understanding the molecular and biological processes that contribute to tumor development and progressive growth is a challenging task. The fusion of the genes ERG
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.
Biankin, Andrew V; Waddell, Nicola; Kassahn, Karin S; Gingras, Marie-Claude; Muthuswamy, Lakshmi B; Johns, Amber L; Miller, David K; Wilson, Peter J; Patch, Ann-Marie; Wu, Jianmin; Chang, David K; Cowley, Mark J; Gardiner, Brooke B; Song, Sarah; Harliwong, Ivon; Idrisoglu, Senel; Nourse, Craig; Nourbakhsh, Ehsan; Manning, Suzanne; Wani, Shivangi; Gongora, Milena; Pajic, Marina; Scarlett, Christopher J; Gill, Anthony J; Pinho, Andreia V; Rooman, Ilse; Anderson, Matthew; Holmes, Oliver; Leonard, Conrad; Taylor, Darrin; Wood, Scott; Xu, Qinying; Nones, Katia; Fink, J Lynn; Christ, Angelika; Bruxner, Tim; Cloonan, Nicole; Kolle, Gabriel; Newell, Felicity; Pinese, Mark; Mead, R Scott; Humphris, Jeremy L; Kaplan, Warren; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chou, Angela; Chin, Venessa T; Chantrill, Lorraine A; Mawson, Amanda; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Daly, Roger J; Merrett, Neil D; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Kakkar, Nipun; Zhao, Fengmei; Wu, Yuan Qing; Wang, Min; Muzny, Donna M; Fisher, William E; Brunicardi, F Charles; Hodges, Sally E; Reid, Jeffrey G; Drummond, Jennifer; Chang, Kyle; Han, Yi; Lewis, Lora R; Dinh, Huyen; Buhay, Christian J; Beck, Timothy; Timms, Lee; Sam, Michelle; Begley, Kimberly; Brown, Andrew; Pai, Deepa; Panchal, Ami; Buchner, Nicholas; De Borja, Richard; Denroche, Robert E; Yung, Christina K; Serra, Stefano; Onetto, Nicole; Mukhopadhyay, Debabrata; Tsao, Ming-Sound; Shaw, Patricia A; Petersen, Gloria M; Gallinger, Steven; Hruban, Ralph H; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Schulick, Richard D; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Capelli, Paola; Corbo, Vincenzo; Scardoni, Maria; Tortora, Giampaolo; Tempero, Margaret A; Mann, Karen M; Jenkins, Nancy A; Perez-Mancera, Pedro A; Adams, David J; Largaespada, David A; Wessels, Lodewyk F A; Rust, Alistair G; Stein, Lincoln D; Tuveson, David A; Copeland, Neal G; Musgrove, Elizabeth A; Scarpa, Aldo; Eshleman, James R; Hudson, Thomas J; Sutherland, Robert L; Wheeler, David A; Pearson, John V; McPherson, John D; Gibbs, Richard A; Grimmond, Sean M
Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.
Choudhary, Neeraj; Bawa, Vanya; Paliwal, Rajneesh; Singh, Bikram; Bhat, Mohd Ashraf; Mir, Javid Iqbal; Gupta, Moni; Sofi, Parvaze A; Thudi, Mahendar; Varshney, Rajeev K; Mir, Reyazul Rouf
Common bean (Phaseolus vulgaris L.) is one of the most important grain legume crops in the world. The beans grown in north-western Himalayas possess huge diversity for seed color, shape and size but are mostly susceptible to Anthracnose disease caused by seed born fungus Colletotrichum lindemuthianum. Dozens of QTLs/genes have been already identified for this disease in common bean world-wide. However, this is the first report of gene/QTL discovery for Anthracnose using bean germplasm from north-western Himalayas of state Jammu & Kashmir, India. A core set of 96 bean lines comprising 54 indigenous local landraces from 11 hot-spots and 42 exotic lines from 10 different countries were phenotyped at two locations (SKUAST-Jammu and Bhaderwah, Jammu) for Anthracnose resistance. The core set was also genotyped with genome-wide (91) random and trait linked SSR markers. The study of marker-trait associations (MTAs) led to the identification of 10 QTLs/genes for Anthracnose resistance. Among the 10 QTLs/genes identified, two MTAs are stable (BM45 & BM211), two MTAs (PVctt1 & BM211) are major explaining more than 20% phenotypic variation for Anthracnose and one MTA (BM211) is both stable and major. Six (06) genomic regions are reported for the first time, while as four (04) genomic regions validated the already known QTL/gene regions/clusters for Anthracnose. The major, stable and validated markers reported during the present study associated with Anthracnose resistance will prove useful in common bean molecular breeding programs aimed at enhancing Anthracnose resistance of local bean landraces grown in north-western Himalayas of state Jammu and Kashmir.
Warden Craig H
Full Text Available Abstract Background It has been proposed that the use of gene expression microarrays in nonrecombinant parental or congenic strains can accelerate the process of isolating individual genes underlying quantitative trait loci (QTL. However, the effectiveness of this approach has not been assessed. Results Thirty-seven studies that have implemented the QTL/microarray approach in rodents were reviewed. About 30% of studies showed enrichment for QTL candidates, mostly in comparisons between congenic and background strains. Three studies led to the identification of an underlying QTL gene. To complement the literature results, a microarray experiment was performed using three mouse congenic strains isolating the effects of at least 25 biometric QTL. Results show that genes in the congenic donor regions were preferentially selected. However, within donor regions, the distribution of differentially expressed genes was homogeneous once gene density was accounted for. Genes within identical-by-descent (IBD regions were less likely to be differentially expressed in chromosome 2, but not in chromosomes 11 and 17. Furthermore, expression of QTL regulated in cis (cis eQTL showed higher expression in the background genotype, which was partially explained by the presence of single nucleotide polymorphisms (SNP. Conclusions The literature shows limited successes from the QTL/microarray approach to identify QTL genes. Our own results from microarray profiling of three congenic strains revealed a strong tendency to select cis-eQTL over trans-eQTL. IBD regions had little effect on rate of differential expression, and we provide several reasons why IBD should not be used to discard eQTL candidates. In addition, mismatch probes produced false cis-eQTL that could not be completely removed with the current strains genotypes and low probe density microarrays. The reviewed studies did not account for lack of coverage from the platforms used and therefore removed genes
been shown to induce DN A amplification in yeast (Gopalakrishnan et al., 2001; Nguy en et al., 2001; Green et al., 2006) an d increased Cdt1 results in...re-replication in human cells (Dorn et al., 2008). The N- terminus of Cdt1 is important for re-replication, perhaps through interactions with PCNA...evolution of a cancer genome. Genome Res. (Epub. Dec. 3, 2008). Harris TD, Buzby PR, Babcock H, Beer E, Bowers J, Bras lavsky I, Causey M
Potta, Thrimoorthy; Zhen, Zhuo; Grandhi, Taraka Sai Pavan; Christensen, Matthew D.; Ramos, James; Breneman, Curt M.; Rege, Kaushal
We describe the combinatorial synthesis and cheminformatics modeling of aminoglycoside antibiotics-derived polymers for transgene delivery and expression. Fifty-six polymers were synthesized by polymerizing aminoglycosides with diglycidyl ether cross-linkers. Parallel screening resulted in identification of several lead polymers that resulted in high transgene expression levels in cells. The role of polymer physicochemical properties in determining efficacy of transgene expression was investigated using Quantitative Structure-Activity Relationship (QSAR) cheminformatics models based on Support Vector Regression (SVR) and ‘building block’ polymer structures. The QSAR model exhibited high predictive ability, and investigation of descriptors in the model, using molecular visualization and correlation plots, indicated that physicochemical attributes related to both, aminoglycosides and diglycidyl ethers facilitated transgene expression. This work synergistically combines combinatorial synthesis and parallel screening with cheminformatics-based QSAR models for discovery and physicochemical elucidation of effective antibiotics-derived polymers for transgene delivery in medicine and biotechnology. PMID:24331709
Cho, Jae Il; Shim, Yung Mok; Kim, Chang Min
Retinoblastoma(RB) gene is the prototype of tumor suppressor gene and it's alteration have been frequently observed in a large number of human tumors. To investigate the role of RB in esophageal cancer, we studied 36 esophageal cancer tissues with Southern blot analysis to detect gross LOH and PCR-SSCP method to find minute LOH and mutation, if any. In the cases with abnormalities, the nucleotide sequence analysis was performed. Allelic loss of chromosome 13q14 occurred in 20 out of 32 informative cases (62.5%) by Southern analysis. Furthermore, PCR-LOH added three positive cases. Mobility shift by PCR-SSCP was observed in one case at exon 22, which showed 1 bp deletion in codon 771 of RB gene resulting in frame shift mutation. Besides, nine PCR-band alteration in tumor tissue compared with normal tissue were observed in exon 14 and 22, but mutation was not found on sequencing analysis suggesting the epigenetic alteration in tumor tissue. Analysis of the clinical data did not show any difference depending upon RB alteration. However, the total incidence of RB gene may play an important role in the development of esophageal cancer. The main genetic alteration of RB gene was deletion detected by Southern blot and one bp deletion leading to frame shift was also observed. 8 figs, 5 tabs. (Author)
Cho, Jae Il; Shim, Yung Mok; Kim, Chang Min [Korea Cancer Center Hospital of Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)
Retinoblastoma(RB) gene is the prototype of tumor suppressor gene and it`s alteration have been frequently observed in a large number of human tumors. To investigate the role of RB in esophageal cancer, we studied 36 esophageal cancer tissues with Southern blot analysis to detect gross LOH and PCR-SSCP method to find minute LOH and mutation, if any. In the cases with abnormalities, the nucleotide sequence analysis was performed. Allelic loss of chromosome 13q14 occurred in 20 out of 32 informative cases (62.5%) by Southern analysis. Furthermore, PCR-LOH added three positive cases. Mobility shift by PCR-SSCP was observed in one case at exon 22, which showed 1 bp deletion in codon 771 of RB gene resulting in frame shift mutation. Besides, nine PCR-band alteration in tumor tissue compared with normal tissue were observed in exon 14 and 22, but mutation was not found on sequencing analysis suggesting the epigenetic alteration in tumor tissue. Analysis of the clinical data did not show any difference depending upon RB alteration. However, the total incidence of RB gene may play an important role in the development of esophageal cancer. The main genetic alteration of RB gene was deletion detected by Southern blot and one bp deletion leading to frame shift was also observed. 8 figs, 5 tabs. (Author).
Mirecka, Aneta; Paszkowska-Szczur, Katarzyna; Scott, Rodney J; Górski, Bohdan; van de Wetering, Thierry; Wokołorczyk, Dominika; Gromowski, Tomasz; Serrano-Fernandez, Pablo; Cybulski, Cezary; Kashyap, Aniruddh; Gupta, Satish; Gołąb, Adam; Słojewski, Marcin; Sikorski, Andrzej; Lubiński, Jan; Dębniak, Tadeusz
The genetic basis of prostate cancer (PC) is complex and appears to involve multiple susceptibility genes. A number of studies have evaluated a possible correlation between several NER gene polymorphisms and PC risk, but most of them evaluated only single SNPs among XP genes and the results remain inconsistent. Out of 94 SNPs located in seven XP genes (XPA-XPG) a total of 15 SNPs were assayed in 720 unselected patients with PC and compared to 1121 healthy adults. An increased risk of disease was associated with the XPD SNP, rs1799793 (Asp312Asn) AG genotype (OR=2.60; p<0.001) and with the AA genotype (OR=531; p<0.0001) compared to the control population. Haplotype analysis of XPD revealed one protective haplotype and four associated with an increased disease risk, which showed that the A allele (XPD rs1799793) appeared to drive the main effect on promoting prostate cancer risk. Polymorphism in XPD gene appears to be associated with the risk of prostate cancer. Copyright © 2014. Published by Elsevier B.V.
Full Text Available Abstract Background The diagnostic tools to predict the prognosis in patients suffering from breast cancer (BC need further improvements. New technological achievements like the gene profiling of circulating tumour cells (CTC could help identify new prognostic markers in the clinical setting. Furthermore, gene expression patterns of CTC might provide important informations on the mechanisms of tumour cell metastasation. Materials and methods We performed realtime-PCR and multiplex-PCR analyses following immunomagnetic separation of CTC. Peripheral blood (PB samples of 63 patients with breast cancer of various stages were analyzed and compared to a control group of 14 healthy individuals. After reverse-transcription, we performed multiplex PCR using primers for the genes ga733.3, muc-1 and c-erbB2. Mammaglobin1, spdef and c-erbB2 were analyzed applying realtime-PCR. Results ga733.2 overexpression was found in 12.7% of breast cancer cases, muc-1 in 15.9%, mgb1 in 9.1% and spdef in 12.1%. In this study, c-erbB2 did not show any significant correlation to BC, possibly due to a highly ambient expression. Besides single gene analyses, gene profiles were additionally evaluated. Highly significant correlations to BC were found in single gene analyses of ga733.2 and muc-1 and in gene profile analyses of ga733.3*muc-1 and GA7 ga733.3*muc-1*mgb1*spdef. Conclusion Our study reveals that the single genes ga733.3, muc-1 and the gene profiles ga733.3*muc-1 and ga733.3*3muc-1*mgb1*spdef can serve as markers for the detection of CTC in BC. The multigene analyses found highly positive levels in BC patients. Our study indicates that not single gene analyses but subtle patterns of multiple genes lead to rising accuracy and low loss of specificity in detection of breast cancer cases.
He, Feng Q; Ollert, Markus
Identification of key genes for a given physiological or pathological process is an essential but still very challenging task for the entire biomedical research community. Statistics-based approaches, such as genome-wide association study (GWAS)- or quantitative trait locus (QTL)-related analysis...... have already made enormous contributions to identifying key genes associated with a given disease or phenotype, the success of which is however very much dependent on a huge number of samples. Recent advances in network biology, especially network inference directly from genome-scale data...
Faramarzi, Sepideh; Ghafouri-Fard, Soudeh
Prostate cancer is a prevalent disorder among men with a heterogeneous etiological background. Several molecular events and signaling perturbations have been found in this disorder. Among genes whose expressions have been altered during the prostate cancer development are cancer-testis antigens (CTAs). This group of antigens has limited expression in the normal adult tissues but aberrant expression in cancers. This property provides them the possibility to be used as cancer biomarkers and immunotherapeutic targets. Several CTAs have been shown to be immunogenic in prostate cancer patients and some of the have entered clinical trials. Based on the preliminary data obtained from these trials, it is expected that CTA-based therapeutic options are beneficial for at least a subset of prostate cancer patients.
Full Text Available Abstract Background Identification of essential proteins is always a challenging task since it requires experimental approaches that are time-consuming and laborious. With the advances in high throughput technologies, a large number of protein-protein interactions are available, which have produced unprecedented opportunities for detecting proteins' essentialities from the network level. There have been a series of computational approaches proposed for predicting essential proteins based on network topologies. However, the network topology-based centrality measures are very sensitive to the robustness of network. Therefore, a new robust essential protein discovery method would be of great value. Results In this paper, we propose a new centrality measure, named PeC, based on the integration of protein-protein interaction and gene expression data. The performance of PeC is validated based on the protein-protein interaction network of Saccharomyces cerevisiae. The experimental results show that the predicted precision of PeC clearly exceeds that of the other fifteen previously proposed centrality measures: Degree Centrality (DC, Betweenness Centrality (BC, Closeness Centrality (CC, Subgraph Centrality (SC, Eigenvector Centrality (EC, Information Centrality (IC, Bottle Neck (BN, Density of Maximum Neighborhood Component (DMNC, Local Average Connectivity-based method (LAC, Sum of ECC (SoECC, Range-Limited Centrality (RL, L-index (LI, Leader Rank (LR, Normalized α-Centrality (NC, and Moduland-Centrality (MC. Especially, the improvement of PeC over the classic centrality measures (BC, CC, SC, EC, and BN is more than 50% when predicting no more than 500 proteins. Conclusions We demonstrate that the integration of protein-protein interaction network and gene expression data can help improve the precision of predicting essential proteins. The new centrality measure, PeC, is an effective essential protein discovery method.
Surya Narayan Rath
Full Text Available Solid tumor is generally observed in tissues of epithelial or endothelial cells of lung, breast, prostate, pancreases, colorectal, stomach, and bladder, where several genes transcription is regulated by the microRNAs (miRNAs. Argonaute (AGO protein is a family of protein which assists in miRNAs to bind with mRNAs of the target genes. Hence, study of the binding mechanism between AGO protein and miRNAs, and also with miRNAs-mRNAs duplex is crucial for understanding the RNA silencing mechanism. In the current work, 64 genes and 23 miRNAs have been selected from literatures, whose deregulation is well established in seven types of solid cancer like lung, breast, prostate, pancreases, colorectal, stomach, and bladder cancer. In silico study reveals, miRNAs namely, miR-106a, miR-21, and miR-29b-2 have a strong binding affinity towards PTEN, TGFBR2, and VEGFA genes, respectively, suggested as important factors in RNA silencing mechanism. Furthermore, interaction between AGO protein (PDB ID-3F73, chain A with selected miRNAs and with miRNAs-mRNAs duplex were studied computationally to understand their binding at molecular level. The residual interaction and hydrogen bonding are inspected in Discovery Studio 3.5 suites. The current investigation throws light on understanding miRNAs based gene silencing mechanism in solid cancer.
Vago, Riccardo; Collico, Veronica; Zuppone, Stefania; Prosperi, Davide; Colombo, Miriam
Conventional chemotherapeutics have been employed in cancer treatment for decades due to their efficacy in killing the malignant cells, but the other side of the coin showed off-target effects, onset of drug resistance and recurrences. To overcome these limitations, different approaches have been investigated and suicide gene therapy has emerged as a promising alternative. This approach consists in the introduction of genetic materials into cancerous cells or the surrounding tissue to cause cell death or retard the growth of the tumor mass. Despite promising results obtained both in vitro and in vivo, this innovative approach has been limited, for long time, to the treatment of localized tumors, due to the suboptimal efficiency in introducing suicide genes into cancer cells. Nanoparticles represent a valuable non-viral delivery system to protect drugs in the bloodstream, to improve biodistribution, and to limit side effects by achieving target selectivity through surface ligands. In this scenario, the real potential of suicide genes can be translated into clinically viable treatments for patients. In the present review, we summarize the recent advances of inorganic nanoparticles as non-viral vectors in terms of therapeutic efficacy, targeting capacity and safety issues. We describe the main suicide genes currently used in therapy, with particular emphasis on toxin-encoding genes of bacterial and plant origin. In addition, we discuss the relevance of molecular targeting and tumor-restricted expression to improve treatment specificity to cancer tissue. Finally, we analyze the main clinical applications, limitations and future perspectives of suicide gene therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.
Full Text Available BACKGROUND: Pancreatic cancer cells generate metastases because they can survive the stress imposed by the new environment of the host tissue. To mimic this process, pancreatic cancer cells which are not stressed in standard culture conditions are injected into nude mice. Because they develop xenografts, they should have developed adequate stress response. Characterizing that response might provide new strategies to interfere with pancreatic cancer metastasis. METHODOLOGY/PRINCIPAL FINDINGS: In the human pancreatic cancer cell lines Panc-1, Mia-PaCa2, Capan-1, Capan-2 and BxPC3, we used Affymetrix DNA microarrays to compare the expressions of 22.000 genes in vitro and in the corresponding xenografts. We identified 228 genes overexpressed in xenografts and characterized the implication of one of them, WSB1, in the control of apoptosis and cell proliferation. WSB1 generates 3 alternatively spliced transcripts encoding distinct protein isoforms. In xenografts and in human pancreatic tumors, global expression of WSB1 mRNA is modestly increased whereas isoform 3 is strongly overexpressed and isoforms 1 and 2 are down-regulated. Treating Mia-PaCa2 cells with stress-inducing agents induced similar changes. Whereas retrovirus-forced expression of WSB1 isoforms 1 and 2 promoted cell growth and sensitized the cells to gemcitabine- and doxorubicin-induced apoptosis, WSB1 isoform 3 expression reduced cell proliferation and enhanced resistance to apoptosis, showing that stress-induced modulation of WSB1 alternative splicing increases resistance to apoptosis of pancreatic cancer cells. CONCLUSIONS/SIGNIFICANCE: Data on WSB1 regulation support the hypothesis that activation of stress-response mechanisms helps cancer cells establishing metastases and suggest relevance to cancer development of other genes overexpressed in xenografts.
Good, Benjamin M; Loguercio, Salvatore; Griffith, Obi L; Nanis, Max; Wu, Chunlei; Su, Andrew I
Molecular signatures for predicting breast cancer prognosis could greatly improve care through personalization of treatment. Computational analyses of genome-wide expression datasets have identified such signatures, but these signatures leave much to be desired in terms of accuracy, reproducibility, and biological interpretability. Methods that take advantage of structured prior knowledge (eg, protein interaction networks) show promise in helping to define better signatures, but most knowledge remains unstructured. Crowdsourcing via scientific discovery games is an emerging methodology that has the potential to tap into human intelligence at scales and in modes unheard of before. The main objective of this study was to test the hypothesis that knowledge linking expression patterns of specific genes to breast cancer outcomes could be captured from players of an open, Web-based game. We envisioned capturing knowledge both from the player's prior experience and from their ability to interpret text related to candidate genes presented to them in the context of the game. We developed and evaluated an online game called The Cure that captured information from players regarding genes for use as predictors of breast cancer survival. Information gathered from game play was aggregated using a voting approach, and used to create rankings of genes. The top genes from these rankings were evaluated using annotation enrichment analysis, comparison to prior predictor gene sets, and by using them to train and test machine learning systems for predicting 10 year survival. Between its launch in September 2012 and September 2013, The Cure attracted more than 1000 registered players, who collectively played nearly 10,000 games. Gene sets assembled through aggregation of the collected data showed significant enrichment for genes known to be related to key concepts such as cancer, disease progression, and recurrence. In terms of the predictive accuracy of models trained using this
Birnbaum, Mark J.; Picco, Jenna; Clements, Meghan; Witwicka, Hanna; Yang, Meiheng; Hoey, Margaret T.; Odgren, Paul R.
A key goal of molecular/cell biology/biotechnology is to identify essential genes in virtually every physiological process to uncover basic mechanisms of cell function and to establish potential targets of drug therapy combating human disease. This article describes a semester-long, project-oriented molecular/cellular/biotechnology laboratory…
I. Jansen (Iris); Ye, H. (Hui); Heetveld, S. (Sasja); Lechler, M.C. (Marie C.); Michels, H. (Helen); Seinstra, R.I. (Renée I.); Lubbe, S.J. (Steven J.); Drouet, V. (Valérie); S. Lesage (Suzanne); E. Majounie (Elisa); Gibbs, J.R. (J.Raphael); M.A. Nalls (Michael); M. Ryten (Mina); Botia, J.A. (Juan A.); J. Vandrovcova (Jana); J. Simón-Sánchez (Javier); Castillo-Lizardo, M. (Melissa); P. Rizzu (Patrizia); Blauwendraat, C. (Cornelis); Chouhan, A.K. (Amit K.); Li, Y. (Yarong); Yogi, P. (Puja); N. Amin (Najaf); C.M. van Duijn (Cornelia); Morris, H.R. (Huw R.); Brice, A. (Alexis); A. Singleton (Andrew); David, D.C. (Della C.); Nollen, E.A. (Ellen A.); A. Jain (Ashok); J.M. Shulman; P. Heutink (Peter); D.G. Hernandez (Dena); S. Arepalli (Sampath); J. Brooks (Janet); Price, R. (Ryan); Nicolas, A. (Aude); S. Chong (Sean); M.R. Cookson (Mark); A. Dillman (Allissa); M. Moore (Matt); B.J. Traynor (Bryan); A. Singleton (Andrew); V. Plagnol (Vincent); Nicholas W Wood,; U.-M. Sheerin (Una-Marie); Jose M Bras,; K. Charlesworth (Kate); M. Gardner (Mac); R. Guerreiro (Rita); D. Trabzuni (Danyah); Hardy, J. (John); M. Sharma; M. Saad (Mohamad); Javier Simón-Sánchez,; C. Schulte (Claudia); J.C. Corvol (Jean-Christophe); Dürr, A. (Alexandra); M. Vidailhet (M.); S. Sveinbjörnsdóttir (Sigurlaug); R.A. Barker (Roger); Caroline H Williams-Gray,; Y. Ben-Shlomo; H.W. Berendse (Henk W.); K.D. van Dijk (Karin); D. Berg (Daniela); K. Brockmann; K.D. Wurster (Kathrin); Mätzler, W. (Walter); Gasser, T. (Thomas); M. Martinez (Maria); R.M.A. de Bie (Rob); A. Biffi (Alessandro); D. Velseboer (Daan); B.R. Bloem (Bastiaan); B. Post (Bart); M. Wickremaratchi (Mirdhu); B. van de Warrenburg (Bart); Z. Bochdanovits (Zoltan); M. von Bonin (Malte); H. Pétursson (Hjörvar); O. Riess (Olaf); D.J. Burn (David); Lubbe, S. (Steven); Cooper, J.M. (J Mark); N.H. McNeill (Nathan); Schapira, A. (Anthony); Lungu, C. (Codrin); Chen, H. (Honglei); Dong, J. (Jing); Chinnery, P.F. (Patrick F.); G. Hudson (Gavin); Clarke, C.E. (Carl E.); C. Moorby (Catriona); C. Counsell (Carl); P. Damier (Philippe); J.-F. Dartigues; P. Deloukas (Panagiotis); E. Gray (Emma); T. Edkins (Ted); Hunt, S.E. (Sarah E.); S.C. Potter (Simon); A. Tashakkori-Ghanbaria (Avazeh); G. Deuschl (Günther); D. Lorenz (Delia); D.T. Dexter (David); F. Durif (Frank); J. Evans (Jonathan Mark); Langford, C. (Cordelia); T. Foltynie (Thomas); A.M. Goate (Alison); C. Harris (Clare); J.J. van Hilten (Jacobus); A. Hofman (Albert); J.R. Hollenbeck (John R.); J.L. Holton (Janice); Hu, M. (Michele); X. Huang (Xiaohong); Illig, T. (Thomas); P.V. Jónsson (Pálmi); J.-C. Lambert; S.S. O'Sullivan (Sean); T. Revesz (Tamas); K. Shaw (Karen); A.J. Lees (Andrew); P. Lichtner (Peter); P. Limousin (Patricia); G. Lopez; Escott-Price, V. (Valentina); J. Pearson (Justin); N. Williams (Nigel); E. Mudanohwo (Ese); J.S. Perlmutter (Joel); Pollak, P. (Pierre); F. Rivadeneira Ramirez (Fernando); A.G. Uitterlinden (André); S.J. Sawcer (Stephen); H. Scheffer (Hans); I. Shoulson (Ira); L. Shulman (Lee); Smith, C. (Colin); R. Walker (Robert); C.C.A. Spencer (Chris C.); A. Strange (Amy); H. Stefansson (Hreinn); F. Bettella (Francesco); J-A. Zwart (John-Anker); Stockton, J.D. (Joanna D.); D. Talbot; C.M. Tanner (Carlie); F. Tison (François); S. Winder-Rhodes (Sophie); K.P. Bhatia (Kailash)
textabstractBackground: Whole-exome sequencing (WES) has been successful in identifying genes that cause familial Parkinson's disease (PD). However, until now this approach has not been deployed to study large cohorts of unrelated participants. To discover rare PD susceptibility variants, we
Adam Y Ye
Full Text Available Transporters are essential in homeostatic exchange of endogenous and exogenous substances at the systematic, organic, cellular, and subcellular levels. Gene mutations of transporters are often related to pharmacogenetics traits. Recent developments in high throughput technologies on genomics, transcriptomics and proteomics allow in depth studies of transporter genes in normal cellular processes and diverse disease conditions. The flood of high throughput data have resulted in urgent need for an updated knowledgebase with curated, organized, and annotated human transporters in an easily accessible way. Using a pipeline with the combination of automated keywords query, sequence similarity search and manual curation on transporters, we collected 1,555 human non-redundant transporter genes to develop the Human Transporter Database (HTD (http://htd.cbi.pku.edu.cn. Based on the extensive annotations, global properties of the transporter genes were illustrated, such as expression patterns and polymorphisms in relationships with their ligands. We noted that the human transporters were enriched in many fundamental biological processes such as oxidative phosphorylation and cardiac muscle contraction, and significantly associated with Mendelian and complex diseases such as epilepsy and sudden infant death syndrome. Overall, HTD provides a well-organized interface to facilitate research communities to search detailed molecular and genetic information of transporters for development of personalized medicine.
O'Mahony, Máirín; Hegarty, Josephine; Rooney, Vivien M
Breast cancer continues to be a major public health problem for women. Early detection and treatment are key to improved outcomes. Whereas most women seek help promptly, some postpone seeking help for self-discovered breast symptoms. Investigation of women's help-seeking behavior and the associated influencing factors on self-discovery of a breast symptom were sought. The aim of this article is to report the qualitative data from women who had self-discovered a breast symptom. Women (n = 167) with a self-discovered breast symptom (who were part of a large quantitative correlational study) commented in an open-ended question on their overall experience. Comments were analyzed using Discourse Analysis. Four linked discourses were identified: (1) "being and remaining normal," (2) "emotion," (3) "becoming and being abnormal," and (4) "rationality." A sidelined discourse of emotion is drawn on to defer taking action based on rational knowledge. The tension between discourses "emotion" and "rationality" further informs our understanding of women's help-seeking behavior following self-discovered symptoms. Findings provide a deeper understanding of the emotional aspects of women's experience around symptom discovery. Findings will be of benefit to all healthcare professionals involved in assessment and screening of breast changes suggestive of breast cancer. They provide a novel insight into the meaning of breast cancer, its diagnosis and treatment, and how this impacts women's emotions as they await consultation in a breast clinic.
Full Text Available Abstract Background Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results. Results GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (e.g. by level of expression or of differential expression. GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list. Building on a complete theoretical characterization of the underlying distribution, called mHG, GOrilla computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations. This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds. The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms. Conclusion GOrilla is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools. GOrilla's unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation. GOrilla is publicly available at: http://cbl-gorilla.cs.technion.ac.il
Nicholas R Polato
Full Text Available BACKGROUND: Cnidarians, including corals and anemones, offer unique insights into metazoan evolution because they harbor genetic similarities with vertebrates beyond that found in model invertebrates and retain genes known only from non-metazoans. Cataloging genes expressed in Acropora palmata, a foundation-species of reefs in the Caribbean and western Atlantic, will advance our understanding of the genetic basis of ecologically important traits in corals and comes at a time when sequencing efforts in other cnidarians allow for multi-species comparisons. RESULTS: A cDNA library from a sample enriched for symbiont free larval tissue was sequenced on the 454 GS-FLX platform. Over 960,000 reads were obtained and assembled into 42,630 contigs. Annotation data was acquired for 57% of the assembled sequences. Analysis of the assembled sequences indicated that 83-100% of all A. palmata transcripts were tagged, and provided a rough estimate of the total number genes expressed in our samples (~18,000-20,000. The coral annotation data contained many of the same molecular components as in the Bilateria, particularly in pathways associated with oxidative stress and DNA damage repair, and provided evidence that homologs of p53, a key player in DNA repair pathways, has experienced selection along the branch separating Cnidaria and Bilateria. Transcriptome wide screens of paralog groups and transition/transversion ratios highlighted genes including: green fluorescent proteins, carbonic anhydrase, and oxidative stress proteins; and functional groups involved in protein and nucleic acid metabolism, and the formation of structural molecules. These results provide a starting point for study of adaptive evolution in corals. CONCLUSIONS: Currently available transcriptome data now make comparative studies of the mechanisms underlying coral's evolutionary success possible. Here we identified candidate genes that enable corals to maintain genomic integrity despite
Polato, Nicholas R; Vera, J Cristobal; Baums, Iliana B
Cnidarians, including corals and anemones, offer unique insights into metazoan evolution because they harbor genetic similarities with vertebrates beyond that found in model invertebrates and retain genes known only from non-metazoans. Cataloging genes expressed in Acropora palmata, a foundation-species of reefs in the Caribbean and western Atlantic, will advance our understanding of the genetic basis of ecologically important traits in corals and comes at a time when sequencing efforts in other cnidarians allow for multi-species comparisons. A cDNA library from a sample enriched for symbiont free larval tissue was sequenced on the 454 GS-FLX platform. Over 960,000 reads were obtained and assembled into 42,630 contigs. Annotation data was acquired for 57% of the assembled sequences. Analysis of the assembled sequences indicated that 83-100% of all A. palmata transcripts were tagged, and provided a rough estimate of the total number genes expressed in our samples (~18,000-20,000). The coral annotation data contained many of the same molecular components as in the Bilateria, particularly in pathways associated with oxidative stress and DNA damage repair, and provided evidence that homologs of p53, a key player in DNA repair pathways, has experienced selection along the branch separating Cnidaria and Bilateria. Transcriptome wide screens of paralog groups and transition/transversion ratios highlighted genes including: green fluorescent proteins, carbonic anhydrase, and oxidative stress proteins; and functional groups involved in protein and nucleic acid metabolism, and the formation of structural molecules. These results provide a starting point for study of adaptive evolution in corals. Currently available transcriptome data now make comparative studies of the mechanisms underlying coral's evolutionary success possible. Here we identified candidate genes that enable corals to maintain genomic integrity despite considerable exposure to genotoxic stress over long life
Chang, D D; Park, N H; Denny, C T; Nelson, S F; Pe, M
A cDNA representational difference analysis (cDNA-RDA) and an arrayed filter technique were used to characterize transformation-related genes in oral cancer. From an initial comparison of normal oral epithelial cells and a human papilloma virus (HPV)-immortalized oral epithelial cell line, we obtained 384 differentially expressed gene fragments and arrayed them on a filter. Two hundred and twelve redundant clones were identified by three rounds of back hybridization. Sequence analysis of the remaining clones revealed 99 unique clones corresponding to 69 genes. The expression of these transformation related gene fragments in three nontumorigenic HPV-immortalized oral epithelial cell lines and three oral cancer cell lines were simultaneously monitored using a cDNA array hybridization. Although there was a considerable cell line-to-cell line variability in the expression of these clones, a reliable prediction of their expression could be made from the cDNA array hybridization. Our study demonstrates the utility of combining cDNA-RDA and arrayed filters in high-throughput gene expression difference analysis. The differentially expressed genes identified in this study should be informative in studying oral epithelial cell carcinogenesis.
Valentin, Mev; Therkildsen, Christina; Veerla, Srinivas
Heredity is estimated to cause at least 20% of colorectal cancer. The hereditary nonpolyposis colorectal cancer subset is divided into Lynch syndrome and familial colorectal cancer type X (FCCTX) based on presence of mismatch repair (MMR) gene defects.......Heredity is estimated to cause at least 20% of colorectal cancer. The hereditary nonpolyposis colorectal cancer subset is divided into Lynch syndrome and familial colorectal cancer type X (FCCTX) based on presence of mismatch repair (MMR) gene defects....
Full Text Available Identification and characterization of crucial gene target(s that will allow focused therapeutics development remains a challenge. We have interrogated the putative therapeutic targets associated with the transcription factor Grainy head-like 2 (GRHL2, a critical epithelial regulatory factor. We demonstrate the possibility to define the molecular functions of critical genes in terms of their personalized expression profiles, allowing appropriate functional conclusions to be derived. A novel methodology, relative expression analysis with gene-set pairs (RXA-GSP, is designed to explore the potential clinical utility of cancer-biology discovery. Observing that Grhl2-overexpression leads to increased metastatic potential in vitro, we established a model assuming Grhl2-induced or -inhibited genes confer poor or favorable prognosis respectively for cancer metastasis. Training on public gene expression profiles of 995 breast cancer patients, this method prioritized one gene-set pair (GRHL2, CDH2, FN1, CITED2, MKI67 versus CTNNB1 and CTNNA3 from all 2717 possible gene-set pairs (GSPs. The identified GSP significantly dichotomized 295 independent patients for metastasis-free survival (log-rank tested p = 0.002; severe empirical p = 0.035. It also showed evidence of clinical prognostication in another independent 388 patients collected from three studies (log-rank tested p = 3.3e-6. This GSP is independent of most traditional prognostic indicators, and is only significantly associated with the histological grade of breast cancer (p = 0.0017, a GRHL2-associated clinical character (p = 6.8e-6, Spearman correlation, suggesting that this GSP is reflective of GRHL2-mediated events. Furthermore, a literature review indicates the therapeutic potential of the identified genes. This research demonstrates a novel strategy to integrate both biological experiments and clinical gene expression profiles for extracting and elucidating the genomic
Background DNA transposons have emerged as indispensible tools for manipulating vertebrate genomes with applications ranging from insertional mutagenesis and transgenesis to gene therapy. To fully explore the potential of two highly active DNA transposons, piggyBac and Tol2, as mammalian genetic tools, we have conducted a side-by-side comparison of the two transposon systems in the same setting to evaluate their advantages and disadvantages for use in gene therapy and gene discovery. Results We have observed that (1) the Tol2 transposase (but not piggyBac) is highly sensitive to molecular engineering; (2) the piggyBac donor with only the 40 bp 3'-and 67 bp 5'-terminal repeat domain is sufficient for effective transposition; and (3) a small amount of piggyBac transposases results in robust transposition suggesting the piggyBac transpospase is highly active. Performing genome-wide target profiling on data sets obtained by retrieving chromosomal targeting sequences from individual clones, we have identified several piggyBac and Tol2 hotspots and observed that (4) piggyBac and Tol2 display a clear difference in targeting preferences in the human genome. Finally, we have observed that (5) only sites with a particular sequence context can be targeted by either piggyBac or Tol2. Conclusions The non-overlapping targeting preference of piggyBac and Tol2 makes them complementary research tools for manipulating mammalian genomes. PiggyBac is the most promising transposon-based vector system for achieving site-specific targeting of therapeutic genes due to the flexibility of its transposase for being molecularly engineered. Insights from this study will provide a basis for engineering piggyBac transposases to achieve site-specific therapeutic gene targeting. PMID:21447194
Scott, Eric M; Halees, Anason; Itan, Yuval; Spencer, Emily G; He, Yupeng; Azab, Mostafa Abdellateef; Gabriel, Stacey B; Belkadi, Aziz; Boisson, Bertrand; Abel, Laurent; Clark, Andrew G; Alkuraya, Fowzan S; Casanova, Jean-Laurent; Gleeson, Joseph G
The Greater Middle East (GME) has been a central hub of human migration and population admixture. The tradition of consanguinity, variably practiced in the Persian Gulf region, North Africa, and Central Asia, has resulted in an elevated burden of recessive disease. Here we generated a whole-exome GME variome from 1,111 unrelated subjects. We detected substantial diversity and admixture in continental and subregional populations, corresponding to several ancient founder populations with little evidence of bottlenecks. Measured consanguinity rates were an order of magnitude above those in other sampled populations, and the GME population exhibited an increased burden of runs of homozygosity (ROHs) but showed no evidence for reduced burden of deleterious variation due to classically theorized 'genetic purging'. Applying this database to unsolved recessive conditions in the GME population reduced the number of potential disease-causing variants by four- to sevenfold. These results show variegated genetic architecture in GME populations and support future human genetic discoveries in Mendelian and population genetics.
Peña, Alejandro; Del Carratore, Francesco; Cummings, Matthew; Takano, Eriko; Breitling, Rainer
The rapid increase of publicly available microbial genome sequences has highlighted the presence of hundreds of thousands of biosynthetic gene clusters (BGCs) encoding valuable secondary metabolites. The experimental characterization of new BGCs is extremely laborious and struggles to keep pace with the in silico identification of potential BGCs. Therefore, the prioritisation of promising candidates among computationally predicted BGCs represents a pressing need. Here, we propose an output ordering and prioritisation system (OOPS) which helps sorting identified BGCs by a wide variety of custom-weighted biological and biochemical criteria in a flexible and user-friendly interface. OOPS facilitates a judicious prioritisation of BGCs using G+C content, coding sequence length, gene number, cluster self-similarity and codon bias parameters, as well as enabling the user to rank BGCs based upon BGC type, novelty, and taxonomic distribution. Effective prioritisation of BGCs will help to reduce experimental attrition rates and improve the breadth of bioactive metabolites characterized.
Berrios, Daniel C.; Costes, Sylvain V.; Tran, Peter B.
GeneLab is currently being developed by NASA to accelerate 'open science' biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics ('omics') data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.
Berrios, Daniel C.; Costes, Sylvain; Tran, Peter
GeneLab is currently being developed by NASA to accelerate open science biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics (omics) data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.
Bevilacqua, E.; Frankenberger, C.A.; Rosner, M.R.
In the past decade cancer research has recognized the importance of tumor stroma interactions for the progression of primary tumors to an aggressive and invasive phenotype and for colonization of new organs in the context of metastasis. The dialogue between tumor cells and the surrounding stroma is a complex and dynamic phenomenon, as many cell types and soluble factors are involved. While the function of many of the players involved in this cross talk have been studied, the regulatory mechanisms and signaling pathways that control their expression have not been investigated in depth. By using a novel, interdisciplinary approach applied to the mechanism of action of the metastasis suppressor, Raf kinase inhibitory protein (RKIP), we identified a signaling pathway that suppresses invasion and metastasis through regulation of stroma-associated genes. Conceptually, the approach we developed uses a master regulator and expression arrays from breast cancer patients to formulate hypotheses based on clinical data. Experimental validation is followed by further bioinformatics analysis to establish the clinical significance of discoveries. Using RKIP as an example we show here that this multi-step approach can be used to identify gene regulatory mechanisms that affect tumor-stroma interactions that in turn influence metastasis to the bone or other organs
Full Text Available Oncogenic transformation of normal cells often involves epigenetic alterations, including histone modification and DNA methylation. We conducted whole-genome bisulfite sequencing to determine the DNA methylomes of normal breast, fibroadenoma, invasive ductal carcinomas and MCF7. The emergence, disappearance, expansion and contraction of kilobase-sized hypomethylated regions (HMRs and the hypomethylation of the megabase-sized partially methylated domains (PMDs are the major forms of methylation changes observed in breast tumor samples. Hierarchical clustering of HMR revealed tumor-specific hypermethylated clusters and differential methylated enhancers specific to normal or breast cancer cell lines. Joint analysis of gene expression and DNA methylation data of normal breast and breast cancer cells identified differentially methylated and expressed genes associated with breast and/or ovarian cancers in cancer-specific HMR clusters. Furthermore, aberrant patterns of X-chromosome inactivation (XCI was found in breast cancer cell lines as well as breast tumor samples in the TCGA BRCA (breast invasive carcinoma dataset. They were characterized with differentially hypermethylated XIST promoter, reduced expression of XIST, and over-expression of hypomethylated X-linked genes. High expressions of these genes were significantly associated with lower survival rates in breast cancer patients. Comprehensive analysis of the normal and breast tumor methylomes suggests selective targeting of DNA methylation changes during breast cancer progression. The weak causal relationship between DNA methylation and gene expression observed in this study is evident of more complex role of DNA methylation in the regulation of gene expression in human epigenetics that deserves further investigation.
Full Text Available Any type of breast cancer not expressing genes of the estrogen receptor (ER, progesterone receptor (PR, or human epidermal growth factor receptor 2 (HER2 is referred to as triple-negative breast cancer (TNBC. Accordingly, TNBCs do not respond to hormonal therapies or medicines targeting the ER, PR, or HER2. Systemic chemotherapy is therefore the only treatment option available today and prognoses remain poor. We report the discovery and characterization of N-(naphtho[1,2-b]furan-5-ylbenzenesulfonamides as selective inhibitors of TNBCs. These inhibitors were identified by virtual screening and inhibited different TNBC cell lines with IC50 values of 2–3 μM. The compounds did not inhibit normal (i.e. MCF-7 and MCF-10A cells in vitro, indicating their selectivity against TNBC cells. Considering the selectivity of these inhibitors for TNBC, these compounds and analogs can serve as a promising starting point for further research on effective TNBC inhibitors.
thymidine kinase transfected EL4 cells . Further exploration of Tc-99m conjugated potential HSV1-TK substrates is still undergoing in our laboratory...prostate cancer cells , has been demonstrated the utility for tissue-specific toxic gene therapy for prostate cancer[10, 11]. Therefore, an adenovirus...BJ5183 together with pAdeasy-1, the viral DNA plasmid. The pAdeasy-1 is E1 and E3 deleted, its E1 function can be complemented in 293A cells . The
Tong, Ying; Zhang, Yang; Huang, Jiaomei; Xiao, Shu; Zhang, Yuehuan; Li, Jun; Chen, Jinhui; Yu, Ziniu
Background The reproductive mechanisms of mollusk species have been interesting targets in biological research because of the diverse reproductive strategies observed in this phylum. These species have also been studied for the development of fishery technologies in molluscan aquaculture. Although the molecular mechanisms underlying the reproductive process have been well studied in animal models, the relevant information from mollusks remains limited, particularly in species of great commercial interest. Crassostrea hongkongensis is the dominant oyster species that is distributed along the coast of the South China Sea and little genomic information on this species is available. Currently, high-throughput sequencing techniques have been widely used for investigating the basis of physiological processes and facilitating the establishment of adequate genetic selection programs. Results The C.hongkongensis transcriptome included a total of 1,595,855 reads, which were generated by 454 sequencing and were assembled into 41,472 contigs using de novo methods. Contigs were clustered into 33,920 isotigs and further grouped into 22,829 isogroups. Approximately 77.6% of the isogroups were successfully annotated by the Nr database. More than 1,910 genes were identified as being related to reproduction. Some key genes involved in germline development, sex determination and differentiation were identified for the first time in C.hongkongensis (nanos, piwi, ATRX, FoxL2, β-catenin, etc.). Gene expression analysis indicated that vasa, nanos, piwi, ATRX, FoxL2, β-catenin and SRD5A1 were highly or specifically expressed in C.hongkongensis gonads. Additionally, 94,056 single nucleotide polymorphisms (SNPs) and 1,699 simple sequence repeats (SSRs) were compiled. Conclusions Our study significantly increased C.hongkongensis genomic information based on transcriptomics analysis. The group of reproduction-related genes identified in the present study constitutes a new tool for research
Full Text Available The reproductive mechanisms of mollusk species have been interesting targets in biological research because of the diverse reproductive strategies observed in this phylum. These species have also been studied for the development of fishery technologies in molluscan aquaculture. Although the molecular mechanisms underlying the reproductive process have been well studied in animal models, the relevant information from mollusks remains limited, particularly in species of great commercial interest. Crassostrea hongkongensis is the dominant oyster species that is distributed along the coast of the South China Sea and little genomic information on this species is available. Currently, high-throughput sequencing techniques have been widely used for investigating the basis of physiological processes and facilitating the establishment of adequate genetic selection programs.The C.hongkongensis transcriptome included a total of 1,595,855 reads, which were generated by 454 sequencing and were assembled into 41,472 contigs using de novo methods. Contigs were clustered into 33,920 isotigs and further grouped into 22,829 isogroups. Approximately 77.6% of the isogroups were successfully annotated by the Nr database. More than 1,910 genes were identified as being related to reproduction. Some key genes involved in germline development, sex determination and differentiation were identified for the first time in C.hongkongensis (nanos, piwi, ATRX, FoxL2, β-catenin, etc.. Gene expression analysis indicated that vasa, nanos, piwi, ATRX, FoxL2, β-catenin and SRD5A1 were highly or specifically expressed in C.hongkongensis gonads. Additionally, 94,056 single nucleotide polymorphisms (SNPs and 1,699 simple sequence repeats (SSRs were compiled.Our study significantly increased C.hongkongensis genomic information based on transcriptomics analysis. The group of reproduction-related genes identified in the present study constitutes a new tool for research on bivalve
Lawler, Mark; Siu, Lillian L; Rehm, Heidi L; Chanock, Stephen J; Alterovitz, Gil; Burn, John; Calvo, Fabien; Lacombe, Denis; Teh, Bin Tean; North, Kathryn N; Sawyers, Charles L
The recent explosion of genetic and clinical data generated from tumor genome analysis presents an unparalleled opportunity to enhance our understanding of cancer, but this opportunity is compromised by the reluctance of many in the scientific community to share datasets and the lack of interoperability between different data platforms. The Global Alliance for Genomics and Health is addressing these barriers and challenges through a cooperative framework that encourages "team science" and responsible data sharing, complemented by the development of a series of application program interfaces that link different data platforms, thus breaking down traditional silos and liberating the data to enable new discoveries and ultimately benefit patients. ©2015 American Association for Cancer Research.
Cameron M Scott
Full Text Available DNA methylation can mimic the effects of both germline and somatic mutations for cancer predisposition genes such as BRCA1 and p16INK4a. Constitutional DNA methylation of the BRCA1 promoter has been well described and is associated with an increased risk of early-onset breast cancers that have BRCA1-mutation associated histological features. The role of methylation in the context of other breast cancer predisposition genes has been less well studied and often with conflicting or ambiguous outcomes. We examined the role of methylation in known breast cancer susceptibility genes in breast cancer predisposition and tumor development. We applied the Infinium HumanMethylation450 Beadchip (HM450K array to blood and tumor-derived DNA from 43 women diagnosed with breast cancer before the age of 40 years and measured the methylation profiles across promoter regions of BRCA1, BRCA2, ATM, PALB2, CDH1, TP53, FANCM, CHEK2, MLH1, MSH2, MSH6 and PMS2. Prior genetic testing had demonstrated that these women did not carry a germline mutation in BRCA1, ATM, CHEK2, PALB2, TP53, BRCA2, CDH1 or FANCM. In addition to the BRCA1 promoter region, this work identified regions with variable methylation at multiple breast cancer susceptibility genes including PALB2 and MLH1. Methylation at the region of MLH1 in these breast cancers was not associated with microsatellite instability. This work informs future studies of the role of methylation in breast cancer susceptibility gene silencing.
Gu, Fangyi; Zhang, Han; Hyland, Paula L; Berndt, Sonja; Gapstur, Susan M; Wheeler, William; Ellipse Consortium, The; Amos, Christopher I; Bezieau, Stephane; Bickeböller, Heike; Brenner, Hermann; Brennan, Paul; Chang-Claude, Jenny; Conti, David V; Doherty, Jennifer Anne; Gruber, Stephen B; Harrison, Tabitha A; Hayes, Richard B; Hoffmeister, Michael; Houlston, Richard S; Hung, Rayjean J; Jenkins, Mark A; Kraft, Peter; Lawrenson, Kate; McKay, James; Markt, Sarah; Mucci, Lorelei; Phelan, Catherine M; Qu, Conghui; Risch, Angela; Rossing, Mary Anne; Wichmann, H-Erich; Shi, Jianxin; Schernhammer, Eva; Yu, Kai; Landi, Maria Teresa; Caporaso, Neil E
Circadian disruption has been linked to carcinogenesis in animal models, but the evidence in humans is inconclusive. Genetic variation in circadian rhythm genes provides a tool to investigate such associations. We examined associations of genetic variation in nine core circadian rhythm genes and six melatonin pathway genes with risk of colorectal, lung, ovarian and prostate cancers using data from the Genetic Associations and Mechanisms in Oncology (GAME-ON) network. The major results for prostate cancer were replicated in the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial, and for colorectal cancer in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). The total number of cancer cases and controls was 15,838/18,159 for colorectal, 14,818/14,227 for prostate, 12,537/17,285 for lung and 4,369/9,123 for ovary. For each cancer site, we conducted gene-based and pathway-based analyses by applying the summary-based Adaptive Rank Truncated Product method (sARTP) on the summary association statistics for each SNP within the candidate gene regions. Aggregate genetic variation in circadian rhythm and melatonin pathways were significantly associated with the risk of prostate cancer in data combining GAME-ON and PLCO, after Bonferroni correction (p pathway circadian rhythm pathway in GAME-ON (p pathway = 0.021); this association was not confirmed in GECCO (p pathway = 0.76) or the combined data (p pathway = 0.17). No significant association was observed for ovarian and lung cancer. These findings support a potential role for circadian rhythm and melatonin pathways in prostate carcinogenesis. Further functional studies are needed to better understand the underlying biologic mechanisms. © 2017 UICC.
Wang, Tiehui; Gorgoglione, Bartolomeo; Maehr, Tanja; Holland, Jason W.; Vecino, Jose L. González; Wadsworth, Simon; Secombes, Christopher J.
The intracellular suppressors of cytokine signaling (SOCS) family members, including CISH and SOCS1 to 7 in mammals, are important regulators of cytokine signaling pathways. So far, the orthologues of all the eight mammalian SOCS members have been identified in fish, with several of them having multiple copies. Whilst fish CISH, SOCS3, and SOCS5 paralogues are possibly the result of the fish-specific whole genome duplication event, gene duplication or lineage-specific genome duplication may also contribute to some paralogues, as with the three trout SOCS2s and three zebrafish SOCS5s. Fish SOCS genes are broadly expressed and also show species-specific expression patterns. They can be upregulated by cytokines, such as IFN-γ, TNF-α, IL-1β, IL-6, and IL-21, by immune stimulants such as LPS, poly I:C, and PMA, as well as by viral, bacterial, and parasitic infections in member- and species-dependent manners. Initial functional studies demonstrate conserved mechanisms of fish SOCS action via JAK/STAT pathways. PMID:22203897
Full Text Available BACKGROUND: Paspalum dilatatum Poir. (common name dallisgrass is a native grass species of South America, with special relevance to dairy and red meat production. P. dilatatum exhibits higher forage quality than other C4 forage grasses and is tolerant to frost and water stress. This species is predominantly cultivated in an apomictic monoculture, with an inherent high risk that biotic and abiotic stresses could potentially devastate productivity. Therefore, advanced breeding strategies that characterise and use available genetic diversity, or assess germplasm collections effectively are required to deliver advanced cultivars for production systems. However, there are limited genomic resources available for this forage grass species. RESULTS: Transcriptome sequencing using second-generation sequencing platforms has been employed using pooled RNA from different tissues (stems, roots, leaves and inflorescences at the final reproductive stage of P. dilatatum cultivar Primo. A total of 324,695 sequence reads were obtained, corresponding to c. 102 Mbp. The sequences were assembled, generating 20,169 contigs of a combined length of 9,336,138 nucleotides. The contigs were BLAST analysed against the fully sequenced grass species of Oryza sativa subsp. japonica, Brachypodium distachyon, the closely related Sorghum bicolor and foxtail millet (Setaria italica genomes as well as against the UniRef 90 protein database allowing a comprehensive gene ontology analysis to be performed. The contigs generated from the transcript sequencing were also analysed for the presence of simple sequence repeats (SSRs. A total of 2,339 SSR motifs were identified within 1,989 contigs and corresponding primer pairs were designed. Empirical validation of a cohort of 96 SSRs was performed, with 34% being polymorphic between sexual and apomictic biotypes. CONCLUSIONS: The development of genetic and genomic resources for P. dilatatum will contribute to gene discovery and expression
Lahtz, Christoph; Pfeifer, Gerd P
'Every Hour Hurts, The Last One Kills'. That is an old saying about getting old. Every day, thousands of DNA damaging events take place in each cell of our body, but efficient DNA repair systems have evolved to prevent that. However, our DNA repair system and that of most other organisms are not as perfect as that of Deinococcus radiodurans, for example, which is able to repair massive amounts of DNA damage at one time. In many instances, accumulation of DNA damage has been linked to cancer, and genetic deficiencies in specific DNA repair genes are associated with tumor-prone phenotypes. In addition to mutations, which can be either inherited or somatically acquired, epigenetic silencing of DNA repair genes may promote tumorigenesis. This review will summarize current knowledge of the epigenetic inactivation of different DNA repair components in human cancer.
The mass-action law based system analysis via mathematical induction and deduction lead to the generalized theory and algorithm that allows computerized simulation of dose-effect dynamics with small size experiments using a small number of data points in vitro, in animals, and in humans. The median-effect equation of the mass-action law deduced from over 300 mechanism specific-equations has been shown to be the unified theory that serves as the common-link for complicated biomedical systems. After using the median-effect principle as the common denominator, its applications are mechanism-independent, drug unit-independent, and dynamic order-independent; and can be used generally for single drug analysis or for multiple drug combinations in constant-ratio or non-constant ratios. Since the "median" is the common link and universal reference point in biological systems, these general enabling lead to computerized quantitative bio-informatics for econo-green bio-research in broad disciplines. Specific applications of the theory, especially relevant to drug discovery, drug combination, and clinical trials, have been cited or illustrated in terms of algorithms, experimental design and computerized simulation for data analysis. Lessons learned from cancer research during the past fifty years provide a valuable opportunity to reflect, and to improve the conventional divergent approach and to introduce a new convergent avenue, based on the mass-action law principle, for the efficient cancer drug discovery and the low-cost drug development.
Salemi, Michele; Barone, Nunziata; La Vignera, Sandro; Condorelli, Rosita A.; Recupero, Domenico; Galia, Antonio; Fraggetta, Filippo; Aiello, Anna Maria; Pepe, Pietro; Castiglione, Roberto; Vicari, Enzo; Calogero, Aldo E.
Numerous genetic alterations have been implicated in the development of prostate cancer (PCa). DNA and protein microarrays have enabled the identification of genes associated with apoptosis, which is important in PCa development. Despite the molecular mechanisms are not entirely understood, inhibition of apoptosis is a critical pathophysiological factor that contributes to the onset and progression of PCa. Leucine zipper, down-regulated in cancer 1 (LDOC-1) is a known regulator of the nuclear...
Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel
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.
Saville Barry J
Full Text Available Abstract Background Ustilago maydis is the basidiomycete fungus responsible for common smut of corn and is a model organism for the study of fungal phytopathogenesis. To aid in the annotation of the genome sequence of this organism, several expressed sequence tag (EST libraries were generated from a variety of U. maydis cell types. In addition to utility in the context of gene identification and structure annotation, the ESTs were analyzed to identify differentially abundant transcripts and to detect evidence of alternative splicing and anti-sense transcription. Results Four cDNA libraries were constructed using RNA isolated from U. maydis diploid teliospores (U. maydis strains 518 × 521 and haploid cells of strain 521 grown under nutrient rich, carbon starved, and nitrogen starved conditions. Using the genome sequence as a scaffold, the 15,901 ESTs were assembled into 6,101 contiguous expressed sequences (contigs; among these, 5,482 corresponded to predicted genes in the MUMDB (MIPS Ustilago maydis database, while 619 aligned to regions of the genome not yet designated as genes in MUMDB. A comparison of EST abundance identified numerous genes that may be regulated in a cell type or starvation-specific manner. The transcriptional response to nitrogen starvation was assessed using RT-qPCR. The results of this suggest that there may be cross-talk between the nitrogen and carbon signalling pathways in U. maydis. Bioinformatic analysis identified numerous examples of alternative splicing and anti-sense transcription. While intron retention was the predominant form of alternative splicing in U. maydis, other varieties were also evident (e.g. exon skipping. Selected instances of both alternative splicing and anti-sense transcription were independently confirmed using RT-PCR. Conclusion Through this work: 1 substantial sequence information has been provided for U. maydis genome annotation; 2 new genes were identified through the discovery of 619
Chioniso Patience Masamha
Full Text Available Abstract The t(11;14 translocation resulting in constitutive cyclin D1 expression is an early event in mantle cell lymphoma (MCL transformation. Patients with a highly proliferative phenotype produce cyclin D1 transcripts with truncated 3′UTRs that evade miRNA regulation. Here, we report the recurrence of a novel gene fusion in MCL cell lines and MCL patient isolates that consists of the full protein coding region of cyclin D1 (CCND1 and a 3′UTR consisting of sequences from both the CCND1 3′UTR and myotonic dystrophy kinase-related Cdc42-binding kinase's (MRCK intron one. The resulting CCND1/MRCK mRNA is resistant to CCND1-targeted miRNA regulation, and targeting the MRCK region of the chimeric 3′UTR with siRNA results in decreased CCND1 levels.
Hahn Daniel A
Full Text Available Abstract Background Flesh flies in the genus Sarcophaga are important models for investigating endocrinology, diapause, cold hardiness, reproduction, and immunity. Despite the prominence of Sarcophaga flesh flies as models for insect physiology and biochemistry, and in forensic studies, little genomic or transcriptomic data are available for members of this genus. We used massively parallel pyrosequencing on the Roche 454-FLX platform to produce a substantial EST dataset for the flesh fly Sarcophaga crassipalpis. To maximize sequence diversity, we pooled RNA extracted from whole bodies of all life stages and normalized the cDNA pool after reverse transcription. Results We obtained 207,110 ESTs with an average read length of 241 bp. These reads assembled into 20,995 contigs and 31,056 singletons. Using BLAST searches of the NR and NT databases we were able to identify 11,757 unique gene elements (ES. crassipalpis unigenes among GO Biological Process functional groups with that of the Drosophila melanogaster transcriptome suggests that our ESTs are broadly representative of the flesh fly transcriptome. Insertion and deletion errors in 454 sequencing present a serious hurdle to comparative transcriptome analysis. Aided by a new approach to correcting for these errors, we performed a comparative analysis of genetic divergence across GO categories among S. crassipalpis, D. melanogaster, and Anopheles gambiae. The results suggest that non-synonymous substitutions occur at similar rates across categories, although genes related to response to stimuli may evolve slightly faster. In addition, we identified over 500 potential microsatellite loci and more than 12,000 SNPs among our ESTs. Conclusion Our data provides the first large-scale EST-project for flesh flies, a much-needed resource for exploring this model species. In addition, we identified a large number of potential microsatellite and SNP markers that could be used in population and systematic
Full Text Available Hanwoo, a Korean native cattle (Bos taurus coreana, has great economic value due to high meat quality. Also, the breed has genetic variations that are associated with production traits such as health, disease resistance, reproduction, growth as well as carcass quality. In this study, next generation sequencing technologies and the availability of an appropriate reference genome were applied to discover a large amount of single nucleotide polymorphisms (SNPs in ten Hanwoo bulls. Analysis of whole-genome resequencing generated a total of 26.5 Gb data, of which 594,716,859 and 592,990,750 reads covered 98.73% and 93.79% of the bovine reference genomes of UMD 3.1 and Btau 4.6.1, respectively. In total, 2,473,884 and 2,402,997 putative SNPs were discovered, of which 1,095,922 (44.3% and 982,674 (40.9% novel SNPs were discovered against UMD3.1 and Btau 4.6.1, respectively. Among the SNPs, the 46,301 (UMD 3.1 and 28,613 SNPs (Btau 4.6.1 that were identified as Hanwoo-specific SNPs were included in the functional genes that may be involved in the mechanisms of milk production, tenderness, juiciness, marbling of Hanwoo beef and yellow hair. Most of the Hanwoo-specific SNPs were identified in the promoter region, suggesting that the SNPs influence differential expression of the regulated genes relative to the relevant traits. In particular, the non-synonymous (ns SNPs found in CORIN, which is a negative regulator of Agouti, might be a causal variant to determine yellow hair of Hanwoo. Our results will provide abundant genetic sources of variation to characterize Hanwoo genetics and for subsequent breeding.
Gerald William L
Full Text Available Abstract Background The androgen receptor (AR plays critical roles in both androgen-dependent and castrate-resistant prostate cancer (PCa. However, little is known about AR target genes that mediate the receptor's roles in disease progression. Results Using Chromatin Immunoprecipitation (ChIP Display, we discovered 19 novel loci occupied by the AR in castrate resistant C4-2B PCa cells. Only four of the 19 AR-occupied regions were within 10-kb 5'-flanking regulatory sequences. Three were located up to 4-kb 3' of the nearest gene, eight were intragenic and four were in gene deserts. Whereas the AR occupied the same loci in C4-2B (castrate resistant and LNCaP (androgen-dependent PCa cells, differences between the two cell lines were observed in the response of nearby genes to androgens. Among the genes strongly stimulated by DHT in C4-2B cells – D-dopachrome tautomerase (DDT, Protein kinase C delta (PRKCD, Glutathione S- transferase theta 2 (GSTT2, Transient receptor potential cation channel subfamily V member 3 (TRPV3, and Pyrroline-5-carboxylate reductase 1 (PYCR1 – most were less strongly or hardly stimulated in LNCaP cells. Another AR target gene, ornithine aminotransferase (OAT, was AR-stimulated in a ligand-independent manner, since it was repressed by AR siRNA knockdown, but not stimulated by DHT. We also present evidence for in vivo AR-mediated regulation of several genes identified by ChIP Display. For example, PRKCD and PYCR1, which may contribute to PCa cell growth and survival, are expressed in PCa biopsies from primary tumors before and after ablation and in metastatic lesions in a manner consistent with AR-mediated stimulation. Conclusion AR genomic occupancy is similar between LNCaP and C4-2B cells and is not biased towards 5' gene flanking sequences. The AR transcriptionally regulates less than half the genes nearby AR-occupied regions, usually but not always, in a ligand-dependent manner. Most are stimulated and a few are
Barar, Jaleh; Omidi, Yadollah
It seems solid tumors are developing smart organs with specialized cells creating specified bio-territory, the so called "tumor microenvironment (TME)", in which there is reciprocal crosstalk among cancer cells, immune system cells and stromal cells. TME as an intricate milieu also consists of cancer stem cells (CSCs) that can resist against chemotherapies. In solid tumors, metabolism and vascularization appears to be aberrant and tumor interstitial fluid (TIF) functions as physiologic barrier. Thus, chemotherapy, immunotherapy and gene therapy often fail to provide cogent clinical outcomes. It looms that it is the time to accept the fact that initiation of cancer could be generation of another form of life that involves a cluster of thousands of genes, while we have failed to observe all aspects of it. Hence, the current treatment modalities need to be re-visited to cover all key aspects of disease using combination therapy based on the condition of patients. Perhaps personalized cluster of genes need to be simultaneously targeted.
Full Text Available It seems solid tumors are developing smart organs with specialized cells creating specified bio-territory, the so called “tumor microenvironment (TME”, in which there is reciprocal crosstalk among cancer cells, immune system cells and stromal cells. TME as an intricate milieu also consists of cancer stem cells (CSCs that can resist against chemotherapies. In solid tumors, metabolism and vascularization appears to be aberrant and tumor interstitial fluid (TIF functions as physiologic barrier. Thus, chemotherapy, immunotherapy and gene therapy often fail to provide cogent clinical outcomes. It looms that it is the time to accept the fact that initiation of cancer could be generation of another form of life that involves a cluster of thousands of genes, while we have failed to observe all aspects of it. Hence, the current treatment modalities need to be re-visited to cover all key aspects of disease using combination therapy based on the condition of patients. Perhaps personalized cluster of genes need to be simultaneously targeted.
Tyson, Jess; Majerus, Tamsin M O; Walker, Susan; Armour, John A L
For most cases of colorectal cancer that arise without a family history of the disease, it is proposed that an appreciable heritable component of predisposition is the result of contributions from many loci. Although progress has been made in identifying single nucleotide variants associated with colorectal cancer risk, the involvement of low-penetrance copy number variants is relatively unexplored. We have used multiplex amplifiable probe hybridization (MAPH) in a fourfold multiplex (QuadMAPH), positioned at an average resolution of one probe per 2 kb, to screen a total of 1.56 Mb of genomic DNA for copy number variants around the genes APC, AXIN1, BRCA1, BRCA2, CTNNB1, HRAS, MLH1, MSH2, and TP53. Two deletion events were detected, one upstream of MLH1 in a control individual and the other in APC in a colorectal cancer patient, but these do not seem to correspond to copy number polymorphisms with measurably high population frequencies. In summary, by means of our QuadMAPH assay, copy number measurement data were of sufficient resolution and accuracy to detect any copy number variants with high probability. However, this study has demonstrated a very low incidence of deletion and duplication variants within intronic and flanking regions of these nine genes, in both control individuals and colorectal cancer patients. Copyright © 2010 Elsevier Inc. All rights reserved.
Liu, Xiaoming; Yang, Jiasheng; Zhang, Yi; Fang, Yun; Wang, Fayou; Wang, Jun; Zheng, Xiaoqi; Yang, Jialiang
We have studied drug-response associated (DRA) gene expressions by applying a systems biology framework to the Cancer Cell Line Encyclopedia data. More than 4,000 genes are inferred to be DRA for at least one drug, while the number of DRA genes for each drug varies dramatically from almost 0 to 1,226. Functional enrichment analysis shows that the DRA genes are significantly enriched in genes associated with cell cycle and plasma membrane. Moreover, there might be two patterns of DRA genes between genders. There are significantly shared DRA genes between male and female for most drugs, while very little DRA genes tend to be shared between the two genders for a few drugs targeting sex-specific cancers (e.g., PD-0332991 for breast cancer and ovarian cancer). Our analyses also show substantial difference for DRA genes between young and old samples, suggesting the necessity of considering the age effects for personalized medicine in cancers. Lastly, differential module and key driver analyses confirm cell cycle related modules as top differential ones for drug sensitivity. The analyses also reveal the role of TSPO, TP53, and many other immune or cell cycle related genes as important key drivers for DRA network modules. These key drivers provide new drug targets to improve the sensitivity of cancer therapy.
Yoon, Joon Kee; Lee, Myung Hoon; Joh, Chul Woo; Yoon, Seok Nam; Soh, Eui Young
Low sensitivity of diagnostic whole body iodine scintigraphy and intermediate range of serum thyroglobulin (Tg) with or without anti-Tg antibody make it difficult to select the patients with differentiated thyroid cancer who need further treatment. Surfaced Enhanced Laser Desorption /Ionization - Time of Flight - Mass Spectrometry (SELDI TOF MS) is a useful method to evaluate cancer proteome, biomarkers and patterns of biomarkers. In this preliminary study, we evaluated and developed protein profiles for the discrimination between patients with differentiated thyroid cancer and non-cancer controls using SELDI technology. Serum samples from 10 healthy controls and from 14 patients with papillary thyroid cancer before thyroidectomy were analyzed by SELDI MS. Multiple protein peaks detected were analyzed by the computer software to develop a classifier for separating cancer patients form controls. The classifier was then challenged to 24 serum samples to determine the validity and accuracy of the classification system. All patients with papillary thyroid cancer had no other concomitant cancer or thyroiditis. Their serum Tg concentration was 55.8 (1.5 - 249.7) and 2 patients had extra-thyroidal extension. According to the SELDI analysis, protein peaks at 3696 Da, 4178 Da, and 8149 Da were more prominent in cancer patients than controls in various degrees. Among those, protein peak at 4178 Da was determined as classifier by computer software, and the sensitivity, specificity and accuracy for discrimination of cancer patients from controls was 92.9% (13/14), 90% (9/10) and 91.7% respectively. This preliminary study suggests that serum protein profiles of differentiated thyroid cancer can be used for differentiation between cancer patients and non-cancer controls. And further clinical studies in various test sets will offer useful information in selecting patients who require treatment
Yoon, Joon Kee; Lee, Myung Hoon; Joh, Chul Woo; Yoon, Seok Nam; Soh, Eui Young [College of Medicine, Univ. of Ajou, Suwon (Korea, Republic of)
Low sensitivity of diagnostic whole body iodine scintigraphy and intermediate range of serum thyroglobulin (Tg) with or without anti-Tg antibody make it difficult to select the patients with differentiated thyroid cancer who need further treatment. Surfaced Enhanced Laser Desorption /Ionization - Time of Flight - Mass Spectrometry (SELDI TOF MS) is a useful method to evaluate cancer proteome, biomarkers and patterns of biomarkers. In this preliminary study, we evaluated and developed protein profiles for the discrimination between patients with differentiated thyroid cancer and non-cancer controls using SELDI technology. Serum samples from 10 healthy controls and from 14 patients with papillary thyroid cancer before thyroidectomy were analyzed by SELDI MS. Multiple protein peaks detected were analyzed by the computer software to develop a classifier for separating cancer patients form controls. The classifier was then challenged to 24 serum samples to determine the validity and accuracy of the classification system. All patients with papillary thyroid cancer had no other concomitant cancer or thyroiditis. Their serum Tg concentration was 55.8 (1.5 - 249.7) and 2 patients had extra-thyroidal extension. According to the SELDI analysis, protein peaks at 3696 Da, 4178 Da, and 8149 Da were more prominent in cancer patients than controls in various degrees. Among those, protein peak at 4178 Da was determined as classifier by computer software, and the sensitivity, specificity and accuracy for discrimination of cancer patients from controls was 92.9% (13/14), 90% (9/10) and 91.7% respectively. This preliminary study suggests that serum protein profiles of differentiated thyroid cancer can be used for differentiation between cancer patients and non-cancer controls. And further clinical studies in various test sets will offer useful information in selecting patients who require treatment.
Wu, Mingsong; Tu, Tao; Huang, Yunchao; Cao, Yi
To understand the carcinogenesis caused by accumulated genetic and epigenetic alterations and seek novel biomarkers for various cancers, studying differentially expressed genes between cancerous and normal tissues is crucial. In the study, two cDNA libraries of lung cancer were constructed and screened for identification of differentially expressed genes. Two cDNA libraries of differentially expressed genes were constructed using lung adenocarcinoma tissue and adjacent nonmalignant lung tissue by suppression subtractive hybridization. The data of the cDNA libraries were then analyzed and compared using bioinformatics analysis. Levels of mRNA and protein were measured by quantitative real-time polymerase chain reaction (q-RT-PCR) and western blot respectively, as well as expression and localization of proteins were determined by immunostaining. Gene functions were investigated using proliferation and migration assays after gene silencing and gene over-expression. Two libraries of differentially expressed genes were obtained. The forward-subtracted library (FSL) and the reverse-subtracted library (RSL) contained 177 and 59 genes, respectively. Bioinformatic analysis demonstrated that these genes were involved in a wide range of cellular functions. The vast majority of these genes were newly identified to be abnormally expressed in lung cancer. In the first stage of the screening for 16 genes, we compared lung cancer tissues with their adjacent non-malignant tissues at the mRNA level, and found six genes (ERGIC3, DDR1, HSP90B1, SDC1, RPSA, and LPCAT1) from the FSL were significantly up-regulated while two genes (GPX3 and TIMP3) from the RSL were significantly down-regulated (P < 0.05). The ERGIC3 protein was also over-expressed in lung cancer tissues and cultured cells, and expression of ERGIC3 was correlated with the differentiated degree and histological type of lung cancer. The up-regulation of ERGIC3 could promote cellular migration and proliferation in vitro. The
Guo, Zhiai; Song, Yanxia; Zhou, Ronghua; Ren, Zhenglong; Jia, Jizeng
Ppd-D1 is one of the most potent genes affecting the photoperiod response of wheat (Triticum aestivum). Only two alleles, insensitive Ppd-D1a and sensitive Ppd-D1b, were known previously, and these did not adequately explain the broad adaptation of wheat to photoperiod variation. In this study, five diagnostic molecular markers were employed to identify Ppd-D1 haplotypes in 492 wheat varieties from diverse geographic locations and 55 accessions of Aegilops tauschii, the D genome donor species of wheat. Six Ppd-D1 haplotypes, designated I-VI, were identified. Types II, V and VI were considered to be more ancient and types I, III and IV were considered to be derived from type II. The transcript abundances of the Ppd-D1 haplotypes showed continuous variation, being highest for haplotype I, lowest for haplotype III, and correlating negatively with varietal differences in heading time. These haplotypes also significantly affected other agronomic traits. The distribution frequency of Ppd-D1 haplotypes showed partial correlations with both latitudes and altitudes of wheat cultivation regions. The evolution, expression and distribution of Ppd-D1 haplotypes were consistent evidentially with each other. What was regarded as a pair of alleles in the past can now be considered a series of alleles leading to continuous variation.
Minafra, Luigi; Bravatà, Valentina; Cammarata, Francesco P; Russo, Giorgio; Gilardi, Maria C; Forte, Giusi I
In breast cancer (BC) care, radiation therapy (RT) is an efficient treatment to control localized tumor. Radiobiological research is needed to understand molecular differences that affect radiosensitivity of different tumor subtypes and the response variability. The aim of this study was to analyze gene expression profiling (GEP) in primary BC cells following irradiation with doses of 9 Gy and 23 Gy delivered by intraoperative electron radiation therapy (IOERT) in order to define gene signatures of response to high doses of ionizing radiation. We performed GEP by cDNA microarrays and evaluated cell survival after IOERT treatment in primary BC cell cultures. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to validate candidate genes. We showed, for the first time, a 4-gene and a 6-gene signature, as new molecular biomarkers, in two primary BC cell cultures after exposure at 9 Gy and 23 Gy respectively, for which we observed a significantly high survival rate. Gene signatures activated by different doses of ionizing radiation may predict response to RT and contribute to defining a personalized biological-driven treatment plan. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.
.8% in molecular function. Further, 19 genes were identified differentially expressed between FW- responsive genotypes and 20 between SMD- responsive genotypes. Generated ESTs were compiled together with 908 ESTs available in public domain, at the time of analysis, and a set of 5,085 unigenes were defined that were used for identification of molecular markers in pigeonpea. For instance, 3,583 simple sequence repeat (SSR motifs were identified in 1,365 unigenes and 383 primer pairs were designed. Assessment of a set of 84 primer pairs on 40 elite pigeonpea lines showed polymorphism with 15 (28.8% markers with an average of four alleles per marker and an average polymorphic information content (PIC value of 0.40. Similarly, in silico mining of 133 contigs with ≥ 5 sequences detected 102 single nucleotide polymorphisms (SNPs in 37 contigs. As an example, a set of 10 contigs were used for confirming in silico predicted SNPs in a set of four genotypes using wet lab experiments. Occurrence of SNPs were confirmed for all the 6 contigs for which scorable and sequenceable amplicons were generated. PCR amplicons were not obtained in case of 4 contigs. Recognition sites for restriction enzymes were identified for 102 SNPs in 37 contigs that indicates possibility of assaying SNPs in 37 genes using cleaved amplified polymorphic sequences (CAPS assay. Conclusion The pigeonpea EST dataset generated here provides a transcriptomic resource for gene discovery and development of functional markers associated with biotic stress resistance. Sequence analyses of this dataset have showed conservation of a considerable number of pigeonpea transcripts across legume and model plant species analysed as well as some putative pigeonpea specific genes. Validation of identified biotic stress responsive genes should provide candidate genes for allele mining as well as candidate markers for molecular breeding.
Magnotti, Elizabeth; Marasco, Wayne A
Epithelial ovarian cancer is a heterogeneous disease classified into five subtypes, each with a different molecular profile. Most cases of ovarian cancer are diagnosed after metastasis of the primary tumor and are resistant to traditional platinum-based chemotherapeutics. Mouse models of ovarian cancer have been utilized to discern ovarian cancer tumorigenesis and the tumor's response to therapeutics. Areas covered: The authors provide a review of mouse models currently employed to understand ovarian cancer. This article focuses on advances in the development of orthotopic and patient-derived tumor xenograft (PDX) mouse models of ovarian cancer and discusses current humanized mouse models of ovarian cancer. Expert opinion: The authors suggest that humanized mouse models of ovarian cancer will provide new insight into the role of the human immune system in combating and augmenting ovarian cancer and aid in the development of novel therapeutics. Development of humanized mouse models will take advantage of the NSG and NSG-SGM3 strains of mice as well as new strains that are actively being derived.
Zhou, Xionghui; Liu, Juan
Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for
Full Text Available Pancreatic cancer is the fourth most frequent cause of cancer-related deaths and is characterized by early metastasis and pronounced resistance to chemotherapy and radiation therapy. Despite extensive esearch efforts, there is not any substantial progress regarding the identification of novel drugs against pancreatic cancer. Although the introduction of the chemotherapeutic agent gemcitabine improved clinical response, the prognosis of these patients remained extremely poor with a 5-year survival rate of 3-5%. Thus, the identification of the novel molecular pathways involved in pancreatic oncogenesis and the development of new and potent therapeutic options are highly desirable. Here, we describe how microRNAs control signaling pathways that are frequently deregulated during pancreatic oncogenesis. In addition, we provide evidence that microRNAs could be potentially used as novel pancreatic cancer therapeutics through reversal of chemotherapy and radiotherapy resistance or regulation of essential molecular pathways. Further studies should integrate the deregulated genes and microRNAs into molecular networks in order to identify the central regulators of pancreatic oncogenesis. Targeting these central regulators could lead to the development of novel targeted therapeutic approaches for pancreatic cancer patients.
Kopp, Tine Iskov
The incidence of cancer in the western world has increased steeply during the last 50 years. For three of the most prevalent cancer types in Denmark, prostate, breast and colorectal cancer (PC, BC and CRC, respectively), only a small fraction (1-15%) of the incidences are caused by highly penetrant...... in alcohol-related BC in postmenopausal women involving a specific polymorphism in PPARG (coding the peroxisome proliferatoractivated receptor (PPARγ)) and its interaction with the aromatase (encoded by CYP19A1) was investigated (Paper V-VI). The Danish prospective “Diet, Cancer and Health” cohort study...... as having strong influence on carcinogenesis. Therefore, very frequent, low effect polymorphisms may have a greater contribution on a population level in combination with environmental factors. Indeed, several dietary and life style factors are now well-established risk factors for different cancer types...
Full Text Available Abstract Background Molecular signatures are sets of genes, proteins, genetic variants or other variables that can be used as markers for a particular phenotype. Reliable signature discovery methods could yield valuable insight into cell biology and mechanisms of human disease. However, it is currently not clear how to control error rates such as the false discovery rate (FDR in signature discovery. Moreover, signatures for cancer gene expression have been shown to be unstable, that is, difficult to replicate in independent studies, casting doubts on their reliability. Results We demonstrate that with modern prediction methods, signatures that yield accurate predictions may still have a high FDR. Further, we show that even signatures with low FDR may fail to replicate in independent studies due to limited statistical power. Thus, neither stability nor predictive accuracy are relevant when FDR control is the primary goal. We therefore develop a general statistical hypothesis testing framework that for the first time provides FDR control for signature discovery. Our method is demonstrated to be correct in simulation studies. When applied to five cancer data sets, the method was able to discover molecular signatures with 5% FDR in three cases, while two data sets yielded no significant findings. Conclusion Our approach enables reliable discovery of molecular signatures from genome-wide data with current sample sizes. The statistical framework developed herein is potentially applicable to a wide range of prediction problems in bioinformatics.
Full Text Available Molecular heterogeneity of cancer, partially caused by various chromosomal aberrations or gene mutations, can yield substantial heterogeneity in gene expression profile in cancer samples. To detect cancer-related genes which are active only in a subset of cancer samples or cancer outliers, several methods have been proposed in the context of multiple testing. Such cancer outlier analyses will generally suffer from a serious lack of power, compared with the standard multiple testing setting where common activation of genes across all cancer samples is supposed. In this paper, we consider information sharing across genes and cancer samples, via a parametric normal mixture modeling of gene expression levels of cancer samples across genes after a standardization using the reference, normal sample data. A gene-based statistic for gene selection is developed on the basis of a posterior probability of cancer outlier for each cancer sample. Some efficiency improvement by using our method was demonstrated, even under settings with misspecified, heavy-tailed t-distributions. An application to a real dataset from hematologic malignancies is provided.
Cancer is a genetic disease. Step-wise alteration of genes that have a normal function in the cell can lead to the transformation of a healthy cell into a malignant cancer cell. Cancer genes provide several traits to the cell that allow it to become malignant. These traits have been researched for
Rousseau, François; Labelle, Yves; Bussières, Johanne; Lindsay, Carmen
The fragile X mental retardation (FXMR) syndrome is one of the most frequent causes of mental retardation. Affected individuals display a wide range of additional characteristic features including behavioural and physical phenotypes, and the extent to which individuals are affected is highly variable. For these reasons, elucidation of the pathophysiology of this disease has been an important challenge to the scientific community. 1991 marks the year of the discovery of both the FMR1 gene mutations involved in this disease, and of their dynamic nature. Although a mouse model for the disease has been available for 16 years and extensive research has been performed on the FMR1 protein (FMRP), we still understand little about how the disease develops, and no treatment has yet been shown to be effective. In this review, we summarise current knowledge on FXMR with an emphasis on the technical challenges of molecular diagnostics, on its prevalence and dynamics among populations, and on the potential of screening for FMR1 mutations.
Rousseau, François; Labelle, Yves; Bussières, Johanne; Lindsay, Carmen
The fragile X mental retardation (FXMR) syndrome is one of the most frequent causes of mental retardation. Affected individuals display a wide range of additional characteristic features including behavioural and physical phenotypes, and the extent to which individuals are affected is highly variable. For these reasons, elucidation of the pathophysiology of this disease has been an important challenge to the scientific community. 1991 marks the year of the discovery of both the FMR1 gene mutations involved in this disease, and of their dynamic nature. Although a mouse model for the disease has been available for 16 years and extensive research has been performed on the FMR1 protein (FMRP), we still understand little about how the disease develops, and no treatment has yet been shown to be effective. In this review, we summarise current knowledge on FXMR with an emphasis on the technical challenges of molecular diagnostics, on its prevalence and dynamics among populations, and on the potential of screening for FMR1 mutations. PMID:21912443
Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia
To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.
In the present thesis I develop, implement and apply statistical methods for detecting genomic elements implicated in cancer development and progression. This is done in two separate bodies of work. The first uses the somatic mutation burden to distinguish cancer driver mutations from passenger m...
efficiency of drug discovery and make a potential impact on modern pharmaceutical industries . 15. SUBJECT TERMS ODOC carriers, barcode, split-mix...approach4-7. Array technologies can construct high density of molecules in an array format on a solid substrate (microchip), from which the chemical...and-play microfluidic packaging scheme, known as Microflego – 3D Microfluidic Assembly, to facilely establish complex 3D microfluidic networks using
Sakoparnig, Thomas; Fried, Patrick; Beerenwinkel, Niko
Cancer drivers are genomic alterations that provide cells containing them with a selective advantage over their local competitors, whereas neutral passengers do not change the somatic fitness of cells. Cancer-driving mutations are usually discriminated from passenger mutations by their higher degree of recurrence in tumor samples. However, there is increasing evidence that many additional driver mutations may exist that occur at very low frequencies among tumors. This observation has prompted alternative methods for driver detection, including finding groups of mutually exclusive mutations and incorporating prior biological knowledge about gene function or network structure. Dependencies among drivers due to epistatic interactions can also result in low mutation frequencies, but this effect has been ignored in driver detection so far. Here, we present a new computational approach for identifying genomic alterations that occur at low frequencies because they depend on other events. Unlike passengers, these constrained mutations display punctuated patterns of occurrence in time. We test this driver–passenger discrimination approach based on mutation timing in extensive simulation studies, and we apply it to cross-sectional copy number alteration (CNA) data from ovarian cancer, CNA and single-nucleotide variant (SNV) data from breast tumors and SNV data from colorectal cancer. Among the top ranked predicted drivers, we find low-frequency genes that have already been shown to be involved in carcinogenesis, as well as many new candidate drivers. The mutation timing approach is orthogonal and complementary to existing driver prediction methods. It will help identifying from cancer genome data the alterations that drive tumor progression. PMID:25569148
Ovarian cancer is one of the most severe of oncological diseases. Inherited mutations in cancer susceptibility genes play a causal role in 5–10% of newly diagnosed tumours. BRCA1 and BRCA2 gene alterations are found in the majority of these cases. The aim of this study was to analyse the BRCA1 gene in the ovarian ...
J. Sunil Rao
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.
Ernest K Amankwah
Full Text Available Alterations in stromal tissue components can inhibit or promote epithelial tumorigenesis. Decorin (DCN and lumican (LUM show reduced stromal expression in serous epithelial ovarian cancer (sEOC. We hypothesized that common variants in these genes associate with risk. Associations with sEOC among Caucasians were estimated with odds ratios (OR among 397 cases and 920 controls in two U.S.-based studies (discovery set, 436 cases and 1,098 controls in Australia (replication set 1 and a consortium of 15 studies comprising 1,668 cases and 4,249 controls (replication set 2. The discovery set and replication set 1 (833 cases and 2,013 controls showed statistically homogeneous (P(heterogeneity≥0.48 decreased risks of sEOC at four variants: DCN rs3138165, rs13312816 and rs516115, and LUM rs17018765 (OR = 0.6 to 0.9; P(trend = 0.001 to 0.03. Results from replication set 2 were statistically homogeneous (P(heterogeneity≥0.13 and associated with increased risks at DCN rs3138165 and rs13312816, and LUM rs17018765: all ORs = 1.2; P(trend≤0.02. The ORs at the four variants were statistically heterogeneous across all 18 studies (P(heterogeneity≤0.03, which precluded combining. In post-hoc analyses, interactions were observed between each variant and recruitment period (P(interaction≤0.003, age at diagnosis (P(interaction = 0.04, and year of diagnosis (P(interaction = 0.05 in the five studies with available information (1,044 cases, 2,469 controls. We conclude that variants in DCN and LUM are not directly associated with sEOC, and that confirmation of possible effect modification of the variants by non-genetic factors is required.
Alanazi, Mohammed; Pathan, Akbar Ali Khan; Shaik, Jilani P; Alhadheq, Abdullah; Khan, Zahid; Khan, Wajahatullah; Al Naeem, Abdulrahman; Parine, Narasimha Reddy
The purpose of this study was to test the association between human 8-oxoguanine glycosylase 1 (hOGG1) gene polymorphisms and susceptibility to breast cancer in Saudi population. We have also aimed to screen the hOGG1 Ser326Cys polymorphism effect on structural and functional properties of the hOGG1 protein using in silico tools. We have analyzed four SNPs of hOGG1 gene among Saudi breast cancer patients along with healthy controls. Genotypes were screened using TaqMan SNP genotype analysis method. Experimental data was analyzed using Chi-square, t test and logistic regression analysis using SPSS software (v.16). In silco analysis was conducted using discovery studio and HOPE program. Genotypic analysis showed that hOGG1 rs1052133 (Ser326Cys) is significantly associated with breast cancer samples in Saudi population, however rs293795 (T >C), rs2072668 (C>G) and rs2075747 (G >A) did not show any association with breast cancer. The hOGG1 SNP rs1052133 (Ser326Cys) minor allele T showed a significant association with breast cancer samples (OR = 1.78, χ2 = 7.86, p = 0.02024). In silico structural analysis was carried out to compare the wild type (Ser326) and mutant (Cys326) protein structures. The structural prediction studies revealed that Ser326Cys variant may destabilize the protein structure and it may disturb the hOGG1 function. Taken together this is the first In silico study report to confirm Ser326Cys variant effect on structural and functional properties of hOGG1 gene and Ser326Cys role in breast cancer susceptibility in Saudi population.
Sayed-Ahmed, Mohamed M.
During the last three decades, important and considerable research efforts had been performed to investigate the mechanism through which cancer cells overcome the cytotoxic effects of a variety of chemotherapeutic drugs. Most of the previously published work has been focused on the resistance of tumor cells to those anticancer drugs of natural source. Multidrug resistance (MDR) is a cellular cross-resistance to a broad spectrum of natural products used in cancer chemotherapy and is believed to be the major cause of the therapeutic failures of the drugs belonging to different naturally obtained or semisynthetic groups including vinca alkaloids, taxans, epipodophyllotoxins and certain antibiotics. This phenomenon results from overexpression of four MDR genes and their corresponding proteins that act as membrane-bound ATP consuming pumps. These proteins mediate the efflux of many structurally and functionally unrelated anticancer drugs of natural source. MDR may be intrinsic or acquired following exposure to chemotherapy. The existence of intrinsically resistant tumor cell clone before and following chemotherapeutic treatment has been associated with a worse final outcome because of increased incidence of distant metasis. In view of irreplaceability of natural product anticancer drugs as effective chemotherapeutic agents, and in view of MDR as a major obstacle to successful chemotherapy, this review is aimed to highlight the genes involved in MDR, classical MDR blockers and gene therapy approaches to overcome MDR. (author)
Xing Chungen; Yang Xiaodong; Zhou Liying; Wu Yongyou; Jiang Yinfen; Dai Hong; Lv Xiaodong; Gong Wei
The screening of radiosensitive genes of human colorectal cancer was made by gene chip. Two human colorectal cancer cell lines LOVO and SW480 were cultivated and the total RNA was extracted from at least lxl0 7 cells. Then the gene expression profiling was performed by HG-U133 Plus 2.0 Array and the difference of gene expression has been analyzed. The results shows that there are 16882 genes expressed in LOVO cell and 17114 genes expressed in SW480 cell through gene expression profiling. It has been found that the genes with 2-fold expressed differentially include 908 genes up-regulated and 1312 genes down-regulated. The same genes, such as Fas and NFkB which is up-regulated, Caspas6, and RAD21 which is down-regulated, have been proved to be related to radiosensitivity. The genes with high expression level including CEACAM5, THBS1, SERPINE2, ARL7, HPGD in LOVO cell may also be related to the radiosensitivity. And the genes with high expression level including SCD, NQ01, LYZ, KRT20, ATP1B1 in SW480 cell may be related to the radioresistance of human colorectal cancer. It could be concluded that the radiosensitivity of colorectal cancer can be reflected from gene and protein expression level. And gene expression profiling is a fast and sensitive tool to predict the radiosensitivity and screen radiosensitive genes of colorectal cancer. (authors)
adequately-sensitive instrument, we found that a new type of CE, originally called a HDA -GT12 Genetic Analyzer from eGene, Inc. (Irvine, CA) (now called...emitting diode-induced fluorescence detectors (12-CE-LED-IF) (originally called HDA -GT12 Genetic Analyzer by eGene, Inc. (Irvine, CA, USA), now
de Sousa E Melo, Felipe; Colak, Selcuk; Buikhuisen, Joyce; Koster, Jan; Cameron, Kate; de Jong, Joan H.; Tuynman, Jurriaan B.; Prasetyanti, Pramudita R.; Fessler, Evelyn; van den Bergh, Saskia P.; Rodermond, Hans; Dekker, Evelien; van der Loos, Chris M.; Pals, Steven T.; van de Vijver, Marc J.; Versteeg, Rogier; Richel, Dick J.; Vermeulen, Louis; Medema, Jan Paul
Gene signatures derived from cancer stem cells (CSCs) predict tumor recurrence for many forms of cancer. Here, we derived a gene signature for colorectal CSCs defined by high Wnt signaling activity, which in agreement with previous observations predicts poor prognosis. Surprisingly, however, we
Full Text Available A safe and efficacious cancer medicine is necessary due to the increasing population of cancer patients whose particular diseases cannot be cured by the currently available treatment. Adenoviral (Ad vectors represent a promising therapeutic medicine for human cancer therapy. However, several improvements are needed in order for Ad vectors to be effective cancer therapeutics, which include, but are not limited to, improvement of cellular uptake, enhanced cancer cell killing activity, and the capability of vector visualization and tracking once injected into the patients. To this end, we attempted to develop an Ad as a multifunctional platform incorporating targeting, imaging, and therapeutic motifs. In this study, we explored the utility of this proposed platform by generating an Ad vector containing the poly-lysine (pK, the herpes simplex virus type 1 (HSV-1 thymidine kinase (TK, and the monomeric red fluorescent protein (mRFP1 as targeting, tumor cell killing, and imaging motifs, respectively. Our study herein demonstrates the generation of the triple mosaic Ad vector with pK, HSV-1 TK, and mRFP1 at the carboxyl termini of Ad minor capsid protein IX (pIX. In addition, the functionalities of pK, HSV-1 TK, and mRFP1 proteins on the Ad vector were retained as confirmed by corresponding functional assays, indicating the potential multifunctional application of this new Ad vector for cancer gene therapy. The validation of the triple mosaic Ad vectors also argues for the ability of pIX modification as a base for the development of multifunctional Ad vectors.
Gold, Laura S; Klein, Gregory; Carr, Lauren; Kessler, Larry; Sullivan, Sean D
In this article, we trace the chronology of developments in breast imaging technologies that are used for diagnosis and staging of breast cancer, including mammography, ultrasonography, magnetic resonance imaging, computed tomography, and positron emission tomography. We explore factors that affected clinical acceptance and utilization of these technologies from discovery to clinical use, including milestones in peer-reviewed publication, US Food and Drug Administration approval, reimbursement by payers, and adoption into clinical guidelines. The factors driving utilization of new imaging technologies are mainly driven by regulatory approval and reimbursement by payers rather than evidence that they provide benefits to patients. Comparative effectiveness research can serve as a useful tool to investigate whether these imaging modalities provide information that improves patient outcomes in real-world settings.
Task 2: Prepare fluorinated RNA aptamer library for screening indolent and aggressive LNCaP cells. The pool of RNA aptamers is amplified from the...transcribed Fluorination of the nucleic acid backbone stabilizes the RNA aptamers against RNAse degradation. Status: completed. Task 3: Perform first...to metastasis-prone prostate cancer cell surface targets, and exert cell- specific toxicity . We propose that these aptamers may help to discriminate between progressive and indolent prostate cancer in clinical applications.
Full Text Available Yubin Kou,1,2* Suya Zhang,3* Xiaoping Chen,2 Sanyuan Hu1 1Department of General Surgery, Qilu Hospital of Shandong University, Jinan, People’s Republic of China; 2Department of General Surgery, 3Department of Neurology, Shuguang Hospital Baoshan Branch, Shanghai, People’s Republic of China *These authors contributed equally to this work Abstract: This study aimed to explore the underlying molecular mechanisms of colorectal cancer (CRC using bioinformatics analysis. Using GSE4107 datasets downloaded from the Gene Expression Omnibus, the differentially expressed genes (DEGs were screened by comparing the RNA expression from the colonic mucosa between 12 CRC patients and ten healthy controls using a paired t-test. The Gene Ontology (GO functional and pathway enrichment analyses of DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID software followed by the construction of a protein–protein interaction (PPI network. In addition, hub gene identification and GO functional and pathway enrichment analyses of the modules were performed. A total of 612 up- and 639 downregulated genes were identified. The upregulated DEGs were mainly involved in the regulation of cell growth, migration, and the MAPK signaling pathway. The downregulated DEGs were significantly associated with oxidative phosphorylation, Alzheimer’s disease, and Parkinson’s disease. Moreover, FOS, FN1, PPP1CC, and CYP2B6 were selected as hub genes in the PPI networks. Two modules (up-A and up-B in the upregulated PPI network and three modules (d-A, d-B, and d-C in the downregulated PPI were identified with the threshold of Molecular Complex Detection (MCODE Molecular Complex Detection (MCODE score ≥4 and nodes ≥6. The genes in module up-A were significantly enriched in neuroactive ligand–receptor interactions and the calcium signaling pathway. The genes in module d-A were enriched in four pathways, including oxidative
Ghoussaini, M.; Song, H.; Koessler, T.
this gene desert were specifically associated with risks of different cancers. One block was solely associated with risk of breast cancer, three others were associated solely with the risk of prostate cancer, and a fifth was associated with the risk of prostate, colorectal, and ovarian cancer...
Meijer, Danielle; van Agthoven, Ton; Bosma, Peter T.; Nooter, Kees; Dorssers, Lambert C. J.
Antiestrogens, such as tamoxifen, are widely used for endocrine treatment of estrogen receptor-positive breast cancer. However, as breast cancer progresses, development of tamoxifen resistance is inevitable. The mechanisms underlying this resistance are not well understood. To identify genes
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
Kohno, Takashi; Otsuka, Ayaka; Girard, Luc; Sato, Masanori; Iwakawa, Reika; Ogiwara, Hideaki; Sanchez-Cespedes, Montse; Minna, John D.; Yokota, Jun
A total of 176 genes homozygously deleted in human lung cancer were identified by DNA array-based whole genome scanning of 52 lung cancer cell lines and subsequent genomic PCR in 74 cell lines, including the 52 cell lines scanned. One or more exons of these genes were homozygously deleted in one (1%) to 20 (27%) cell lines. These genes included known tumor suppressor genes, e.g., CDKN2A/p16, RB1, and SMAD4, and candidate tumor suppressor genes whose hemizygous or homozygous deletions were reported in several types of human cancers, such as FHIT, KEAP1, and LRP1B/LRP-DIP. CDKN2A/p16 and p14ARF located in 9p21 were most frequently deleted (20/74, 27%). The PTPRD gene was most frequently deleted (8/74, 11%) among genes mapping to regions other than 9p21. Somatic mutations, including a nonsense mutation, of the PTPRD gene were detected in 8/74 (11%) of cell lines and 4/95 (4%) of surgical specimens of lung cancer. Reduced PTPRD expression was observed in the majority (>80%) of cell lines and surgical specimens of lung cancer. Therefore, PTPRD is a candidate tumor suppressor gene in lung cancer. Microarray-based expression profiling of 19 lung cancer cell lines also indicated that some of the 176 genes, such as KANK and ADAMTS1, are preferentially inactivated by epigenetic alterations. Genetic/epigenetic as well as functional studies of these 176 genes will increase our understanding of molecular mechanisms behind lung carcinogenesis. PMID:20073072
Birkeland, Andrew C; Ludwig, Megan L; Spector, Matthew E; Brenner, J Chad
Head and neck squamous cell carcinoma remains a highly morbid and fatal disease. Importantly, genomic sequencing of head and neck cancers has identified frequent mutations in tumor suppressor genes. While targeted therapeutics increasingly are being investigated in head and neck cancer, the majority of these agents are against overactive/overexpressed oncogenes. Therapy to restore lost tumor suppressor gene function remains a key and under-addressed niche in trials for head and neck cancer. Recent advances in gene editing have captured the interest of both the scientific community and the public. As our technology for gene editing and gene expression modulation improves, addressing lost tumor suppressor gene function in head and neck cancers is becoming a reality. This review will summarize new techniques, challenges to implementation, future directions, and ethical ramifications of gene therapy in head and neck cancer.
Yan Ting Chiang
Full Text Available Metastatic prostate cancer is currently incurable. Metastasis is thought to result from changes in the expression of specific metastasis-driving genes in nonmetastatic prostate cancer tissue, leading to a cascade of activated downstream genes that set the metastatic process in motion. Such genes could potentially serve as effective therapeutic targets for improved management of the disease. They could be identified by comparative analysis of gene expression profiles of patient-derived metastatic and nonmetastatic prostate cancer tissues to pinpoint genes showing altered expression, followed by determining whether silencing of such genes can lead to inhibition of metastatic properties. Various hurdles encountered in this approach are discussed, including (i the need for clinically relevant, nonmetastatic and metastatic prostate cancer tissues such as xenografts of patients' prostate cancers developed via subrenal capsule grafting technology and (ii limitations in the currently available methodology for identification of master regulatory genes.
Li, Junyan; Jing, Ruilin; Wei, Hongyi; Wang, Minghao; Qi, Xiaowei; Liu, Haoxi; Liu, Jian; Ou, Jianghua; Jiang, Weihua; Tian, Fuguo; Sheng, Yuan; Li, Hengyu; Xu, Hong; Zhang, Ruishan; Guan, Aihua; Liu, Ke; Jiang, Hongchuan; Ren, Yu; He, Jianjun; Huang, Weiwei; Liao, Ning; Cai, Xiangjun; Ming, Jia; Ling, Rui; Xu, Yan; Hu, Chunyan; Zhang, Jianguo; Guo, Baoliang; Ouyang, Lizhi; Shuai, Ping; Liu, Zhenzhen; Zhong, Ling; Zeng, Zhen; Zhang, Ting; Xuan, Zhaoling; Tan, Xuanni; Liang, Junbin; Pan, Qinwen; Chen, Li; Zhang, Fan; Fan, Linjun; Zhang, Yi; Yang, Xinhua; Li, Jingbo; Chen, Chongjian; Jiang, Jun
Multigene panel testing of breast cancer predisposition genes have been extensively conducted in Europe and America, which is relatively rare in Asia however. In this study, we assessed the frequency of germline mutations in 40 cancer predisposition genes, including BRCA1 and BRCA2, among a large cohort of Chinese patients with high hereditary risk of BC. From 2015 to 2016, consecutive BC patients from 26 centers of China with high hereditary risk were recruited (n=937). Clinical information was collected and next-generation sequencing (NGS) was performed using blood samples of participants to identify germline mutations. In total, we acquired 223 patients with putative germline mutations, including 159 in BRCA1/2, 61 in 15 other BC susceptibility genes and 3 in both BRCA1/2 and non-BRCA1/2 gene. Major mutant non-BRCA1/2 genes were TP53 (n=18), PALB2 (n=11), CHEK2 (n=6), ATM (n=6), and BARD1 (n=5). No factors predicted pathologic mutations in non-BRCA1/2 genes when treated as a whole. TP53 mutations were associated with HER-2 positive BC and younger age at diagnosis; and CHEK2 and PALB2 mutations were enriched in patients with luminal BC. Among high hereditary risk Chinese BC patients, 23.8% contained germline mutations, including 6.8% in non-BRCA1/2 genes. TP53 and PALB2 had a relatively high mutation rates (1.9% and 1.2%). Although no factors predicted for detrimental mutations in non-BRCA1/2 genes, some clinical features were associated with mutations of several particular genes. This article is protected by copyright. All rights reserved. © 2018 UICC.
Full Text Available FDA-cleared ovarian cancer biomarkers are limited to CA-125 and HE4 for monitoring and recurrence and OVA1, a multivariate panel consisting of CA-125 and four additional biomarkers, for referring patients to a specialist. Due to relatively poor performance of these tests, more accurate and broadly applicable biomarkers are needed. We evaluated the dysregulation of 259 candidate cancer markers in serum samples from 499 patients. Sera were collected prospectively at 11 monitored sites under a single well-defined protocol. All stages of ovarian cancer and common benign gynecological conditions were represented. To ensure consistency and comparability of biomarker comparisons, all measurements were performed on a single platform, at a single site, using a panel of rigorously calibrated, qualified, high-throughput, multiplexed immunoassays and all analyses were conducted using the same software. Each marker was evaluated independently for its ability to differentiate ovarian cancer from benign conditions. A total of 175 markers were dysregulated in the cancer samples. HE4 (AUC=0.933 and CA-125 (AUC=0.907 were the most informative biomarkers, followed by IL-2 receptor α, α1-antitrypsin, C-reactive protein, YKL-40, cellular fibronectin, CA-72-4 and prostasin (AUC>0.800. To improve the discrimination between cancer and benign conditions, a simple multivariate combination of markers was explored using logistic regression. When combined into a single panel, the nine most informative individual biomarkers yielded an AUC value of 0.950, significantly higher than obtained when combining the markers in the OVA1 panel (AUC 0.912. Additionally, at a threshold sensitivity of 90%, the combination of the top 9 markers gave 88.9% specificity compared to 63.4% specificity for the OVA1 markers. Although a blinded validation study has not yet been performed, these results indicate that alternative biom