Establishment of a 12-gene expression signature to predict colon cancer prognosis

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Dalong Sun

2018-06-01

Full Text Available A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA. The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS: Kaplan Meier (KM Log Rank p = 0.0034; overall survival (OS: KM Log Rank p = 0.0336 in GSE17538. For patients with proficient mismatch repair system (pMMR in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS: KM Log Rank p = 0.022. Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher’s exact test p = 0.0003. After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01 and stage II & III (Log Rank p = 0.017 in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041. Among stage II/III pMMR patients

Importance of correlation between gene expression levels: application to the type I interferon signature in rheumatoid arthritis.

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Reynier, Frédéric; Petit, Fabien; Paye, Malick; Turrel-Davin, Fanny; Imbert, Pierre-Emmanuel; Hot, Arnaud; Mougin, Bruno; Miossec, Pierre

2011-01-01

The analysis of gene expression data shows that many genes display similarity in their expression profiles suggesting some co-regulation. Here, we investigated the co-expression patterns in gene expression data and proposed a correlation-based research method to stratify individuals. Using blood from rheumatoid arthritis (RA) patients, we investigated the gene expression profiles from whole blood using Affymetrix microarray technology. Co-expressed genes were analyzed by a biclustering method, followed by gene ontology analysis of the relevant biclusters. Taking the type I interferon (IFN) pathway as an example, a classification algorithm was developed from the 102 RA patients and extended to 10 systemic lupus erythematosus (SLE) patients and 100 healthy volunteers to further characterize individuals. We developed a correlation-based algorithm referred to as Classification Algorithm Based on a Biological Signature (CABS), an alternative to other approaches focused specifically on the expression levels. This algorithm applied to the expression of 35 IFN-related genes showed that the IFN signature presented a heterogeneous expression between RA, SLE and healthy controls which could reflect the level of global IFN signature activation. Moreover, the monitoring of the IFN-related genes during the anti-TNF treatment identified changes in type I IFN gene activity induced in RA patients. In conclusion, we have proposed an original method to analyze genes sharing an expression pattern and a biological function showing that the activation levels of a biological signature could be characterized by its overall state of correlation.

The rapamycin-regulated gene expression signature determines prognosis for breast cancer

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Tsavachidis Spiridon

2009-09-01

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.

A simple and robust method for connecting small-molecule drugs using gene-expression signatures

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Gant Timothy W

2008-06-01

Full Text Available Abstract Background Interaction of a drug or chemical with a biological system can result in a gene-expression profile or signature characteristic of the event. Using a suitably robust algorithm these signatures can potentially be used to connect molecules with similar pharmacological or toxicological properties by gene expression profile. Lamb et al first proposed the Connectivity Map [Lamb et al (2006, Science 313, 1929–1935] to make successful connections among small molecules, genes, and diseases using genomic signatures. Results Here we have built on the principles of the Connectivity Map to present a simpler and more robust method for the construction of reference gene-expression profiles and for the connection scoring scheme, which importantly allows the valuation of statistical significance of all the connections observed. We tested the new method with two randomly generated gene signatures and three experimentally derived gene signatures (for HDAC inhibitors, estrogens, and immunosuppressive drugs, respectively. Our testing with this method indicates that it achieves a higher level of specificity and sensitivity and so advances the original method. Conclusion The method presented here not only offers more principled statistical procedures for testing connections, but more importantly it provides effective safeguard against false connections at the same time achieving increased sensitivity. With its robust performance, the method has potential use in the drug development pipeline for the early recognition of pharmacological and toxicological properties in chemicals and new drug candidates, and also more broadly in other 'omics sciences.

Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd

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Wang, Zichen; Monteiro, Caroline D.; Jagodnik, Kathleen M.

2016-01-01

Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene...... signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization....

Oxidative stress/reactive metabolite gene expression signature in rat liver detects idiosyncratic hepatotoxicants

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Leone, Angelique; Nie, Alex; Brandon Parker, J.; Sawant, Sharmilee; Piechta, Leigh-Anne; Kelley, Michael F., E-mail: mkelley2@its.jnj.com; Mark Kao, L.; Jim Proctor, S.; Verheyen, Geert; Johnson, Mark D.; Lord, Peter G.; McMillian, Michael K.

2014-03-15

Previously we reported a gene expression signature in rat liver for detecting a specific type of oxidative stress (OS) related to reactive metabolites (RM). High doses of the drugs disulfiram, ethinyl estradiol and nimesulide were used with another dozen paradigm OS/RM compounds, and three other drugs flutamide, phenacetin and sulindac were identified by this signature. In a second study, antiepileptic drugs were compared for covalent binding and their effects on OS/RM; felbamate, carbamazepine, and phenobarbital produced robust OS/RM gene expression. In the present study, liver RNA samples from drug-treated rats from more recent experiments were examined for statistical fit to the OS/RM signature. Of all 97 drugs examined, in addition to the nine drugs noted above, 19 more were identified as OS/RM-producing compounds—chlorpromazine, clozapine, cyproterone acetate, dantrolene, dipyridamole, glibenclamide, isoniazid, ketoconazole, methapyrilene, naltrexone, nifedipine, sulfamethoxazole, tamoxifen, coumarin, ritonavir, amitriptyline, valproic acid, enalapril, and chloramphenicol. Importantly, all of the OS/RM drugs listed above have been linked to idiosyncratic hepatotoxicity, excepting chloramphenicol, which does not have a package label for hepatotoxicity, but does have a black box warning for idiosyncratic bone marrow suppression. Most of these drugs are not acutely toxic in the rat. The OS/RM signature should be useful to avoid idiosyncratic hepatotoxicity of drug candidates. - Highlights: • 28 of 97 drugs gave a positive OS/RM gene expression signature in rat liver. • The specificity of the signature for human idiosyncratic hepatotoxicants was 98%. • The sensitivity of the signature for human idiosyncratic hepatotoxicants was 75%. • The signature can help eliminate hepatotoxicants from drug development.

Gene expression signatures of radiation response are specific, durable and accurate in mice and humans.

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Sarah K Meadows

2008-04-01

Full Text Available Previous work has demonstrated the potential for peripheral blood (PB gene expression profiling for the detection of disease or environmental exposures.We have sought to determine the impact of several variables on the PB gene expression profile of an environmental exposure, ionizing radiation, and to determine the specificity of the PB signature of radiation versus other genotoxic stresses. Neither genotype differences nor the time of PB sampling caused any lessening of the accuracy of PB signatures to predict radiation exposure, but sex difference did influence the accuracy of the prediction of radiation exposure at the lowest level (50 cGy. A PB signature of sepsis was also generated and both the PB signature of radiation and the PB signature of sepsis were found to be 100% specific at distinguishing irradiated from septic animals. We also identified human PB signatures of radiation exposure and chemotherapy treatment which distinguished irradiated patients and chemotherapy-treated individuals within a heterogeneous population with accuracies of 90% and 81%, respectively.We conclude that PB gene expression profiles can be identified in mice and humans that are accurate in predicting medical conditions, are specific to each condition and remain highly accurate over time.

Predicting cellular growth from gene expression signatures.

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Edoardo M Airoldi

2009-01-01

Full Text Available Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

Identification of Aging-Associated Gene Expression Signatures That Precede Intestinal Tumorigenesis.

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Yoshihisa Okuchi

Full Text Available Aging-associated alterations of cellular functions have been implicated in various disorders including cancers. Due to difficulties in identifying aging cells in living tissues, most studies have focused on aging-associated changes in whole tissues or certain cell pools. Thus, it remains unclear what kinds of alterations accumulate in each cell during aging. While analyzing several mouse lines expressing fluorescent proteins (FPs, we found that expression of FPs is gradually silenced in the intestinal epithelium during aging in units of single crypt composed of clonal stem cell progeny. The cells with low FP expression retained the wild-type Apc allele and the tissues composed of them did not exhibit any histological abnormality. Notably, the silencing of FPs was also observed in intestinal adenomas and the surrounding normal mucosae of Apc-mutant mice, and mediated by DNA methylation of the upstream promoter. Our genome-wide analysis then showed that the silencing of FPs reflects specific gene expression alterations during aging, and that these alterations occur in not only mouse adenomas but also human sporadic and hereditary (familial adenomatous polyposis adenomas. Importantly, pharmacological inhibition of DNA methylation, which suppresses adenoma development in Apc-mutant mice, reverted the aging-associated silencing of FPs and gene expression alterations. These results identify aging-associated gene expression signatures that are heterogeneously induced by DNA methylation and precede intestinal tumorigenesis triggered by Apc inactivation, and suggest that pharmacological inhibition of the signature genes could be a novel strategy for the prevention and treatment of intestinal tumors.

The prognostic value of temporal in vitro and in vivo derived hypoxia gene-expression signatures in breast cancer

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Starmans, Maud H.W.; Chu, Kenneth C.; Haider, Syed; Nguyen, Francis; Seigneuric, Renaud; Magagnin, Michael G.; Koritzinsky, Marianne; Kasprzyk, Arek; Boutros, Paul C.; Wouters, Bradly G.

2012-01-01

Background and purpose: Recent data suggest that in vitro and in vivo derived hypoxia gene-expression signatures have prognostic power in breast and possibly other cancers. However, both tumour hypoxia and the biological adaptation to this stress are highly dynamic. Assessment of time-dependent gene-expression changes in response to hypoxia may thus provide additional biological insights and assist in predicting the impact of hypoxia on patient prognosis. Materials and methods: Transcriptome profiling was performed for three cell lines derived from diverse tumour-types after hypoxic exposure at eight time-points, which include a normoxic time-point. Time-dependent sets of co-regulated genes were identified from these data. Subsequently, gene ontology (GO) and pathway analyses were performed. The prognostic power of these novel signatures was assessed in parallel with previous in vitro and in vivo derived hypoxia signatures in a large breast cancer microarray meta-dataset (n = 2312). Results: We identified seven recurrent temporal and two general hypoxia signatures. GO and pathway analyses revealed regulation of both common and unique underlying biological processes within these signatures. None of the new or previously published in vitro signatures consisting of hypoxia-induced genes were prognostic in the large breast cancer dataset. In contrast, signatures of repressed genes, as well as the in vivo derived signatures of hypoxia-induced genes showed clear prognostic power. Conclusions: Only a subset of hypoxia-induced genes in vitro demonstrates prognostic value when evaluated in a large clinical dataset. Despite clear evidence of temporal patterns of gene-expression in vitro, the subset of prognostic hypoxia regulated genes cannot be identified based on temporal pattern alone. In vivo derived signatures appear to identify the prognostic hypoxia induced genes. The prognostic value of hypoxia-repressed genes is likely a surrogate for the known importance of

Functional heterogeneity of cancer-associated fibroblasts from human colon tumors shows specific prognostic gene expression signature.

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Herrera, Mercedes; Islam, Abul B M M K; Herrera, Alberto; Martín, Paloma; García, Vanesa; Silva, Javier; Garcia, Jose M; Salas, Clara; Casal, Ignacio; de Herreros, Antonio García; Bonilla, Félix; Peña, Cristina

2013-11-01

Cancer-associated fibroblasts (CAF) actively participate in reciprocal communication with tumor cells and with other cell types in the microenvironment, contributing to a tumor-permissive neighborhood and promoting tumor progression. The aim of this study is the characterization of how CAFs from primary human colon tumors promote migration of colon cancer cells. Primary CAF cultures from 15 primary human colon tumors were established. Their enrichment in CAFs was evaluated by the expression of various epithelial and myofibroblast specific markers. Coculture assays of primary CAFs with different colon tumor cells were performed to evaluate promigratory CAF-derived effects on cancer cells. Gene expression profiles were developed to further investigate CAF characteristics. Coculture assays showed significant differences in fibroblast-derived paracrine promigratory effects on cancer cells. Moreover, the association between CAFs' promigratory effects on cancer cells and classic fibroblast activation or stemness markers was observed. CAF gene expression profiles were analyzed by microarray to identify deregulated genes in different promigratory CAFs. The gene expression signature, derived from the most protumorogenic CAFs, was identified. Interestingly, this "CAF signature" showed a remarkable prognostic value for the clinical outcome of patients with colon cancer. Moreover, this prognostic value was validated in an independent series of 142 patients with colon cancer, by quantitative real-time PCR (qRT-PCR), with a set of four genes included in the "CAF signature." In summary, these studies show for the first time the heterogeneity of primary CAFs' effect on colon cancer cell migration. A CAF gene expression signature able to classify patients with colon cancer into high- and low-risk groups was identified.

REDD1 induction regulates the skeletal muscle gene expression signature following acute aerobic exercise.

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Gordon, Bradley S; Steiner, Jennifer L; Rossetti, Michael L; Qiao, Shuxi; Ellisen, Leif W; Govindarajan, Subramaniam S; Eroshkin, Alexey M; Williamson, David L; Coen, Paul M

2017-12-01

The metabolic stress placed on skeletal muscle by aerobic exercise promotes acute and long-term health benefits in part through changes in gene expression. However, the transducers that mediate altered gene expression signatures have not been completely elucidated. Regulated in development and DNA damage 1 (REDD1) is a stress-induced protein whose expression is transiently increased in skeletal muscle following acute aerobic exercise. However, the role of this induction remains unclear. Because REDD1 altered gene expression in other model systems, we sought to determine whether REDD1 induction following acute exercise altered the gene expression signature in muscle. To do this, wild-type and REDD1-null mice were randomized to remain sedentary or undergo a bout of acute treadmill exercise. Exercised mice recovered for 1, 3, or 6 h before euthanization. Acute exercise induced a transient increase in REDD1 protein expression within the plantaris only at 1 h postexercise, and the induction occurred in both cytosolic and nuclear fractions. At this time point, global changes in gene expression were surveyed using microarray. REDD1 induction was required for the exercise-induced change in expression of 24 genes. Validation by RT-PCR confirmed that the exercise-mediated changes in genes related to exercise capacity, muscle protein metabolism, neuromuscular junction remodeling, and Metformin action were negated in REDD1-null mice. Finally, the exercise-mediated induction of REDD1 was partially dependent upon glucocorticoid receptor activation. In all, these data show that REDD1 induction regulates the exercise-mediated change in a distinct set of genes within skeletal muscle. Copyright © 2017 the American Physiological Society.

Gene expression signature of normal cell-of-origin predicts ovarian tumor outcomes.

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Melissa A Merritt

Full Text Available The potential role of the cell-of-origin in determining the tumor phenotype has been raised, but not adequately examined. We hypothesized that distinct cells-of-origin may play a role in determining ovarian tumor phenotype and outcome. Here we describe a new cell culture medium for in vitro culture of paired normal human ovarian (OV and fallopian tube (FT epithelial cells from donors without cancer. While these cells have been cultured individually for short periods of time, to our knowledge this is the first long-term culture of both cell types from the same donors. Through analysis of the gene expression profiles of the cultured OV/FT cells we identified a normal cell-of-origin gene signature that classified primary ovarian cancers into OV-like and FT-like subgroups; this classification correlated with significant differences in clinical outcomes. The identification of a prognostically significant gene expression signature derived solely from normal untransformed cells is consistent with the hypothesis that the normal cell-of-origin may be a source of ovarian tumor heterogeneity and the associated differences in tumor outcome.

A simple but highly effective approach to evaluate the prognostic performance of gene expression signatures.

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Maud H W Starmans

Full Text Available BACKGROUND: Highly parallel analysis of gene expression has recently been used to identify gene sets or 'signatures' to improve patient diagnosis and risk stratification. Once a signature is generated, traditional statistical testing is used to evaluate its prognostic performance. However, due to the dimensionality of microarrays, this can lead to false interpretation of these signatures. PRINCIPAL FINDINGS: A method was developed to test batches of a user-specified number of randomly chosen signatures in patient microarray datasets. The percentage of random generated signatures yielding prognostic value was assessed using ROC analysis by calculating the area under the curve (AUC in six public available cancer patient microarray datasets. We found that a signature consisting of randomly selected genes has an average 10% chance of reaching significance when assessed in a single dataset, but can range from 1% to ∼40% depending on the dataset in question. Increasing the number of validation datasets markedly reduces this number. CONCLUSIONS: We have shown that the use of an arbitrary cut-off value for evaluation of signature significance is not suitable for this type of research, but should be defined for each dataset separately. Our method can be used to establish and evaluate signature performance of any derived gene signature in a dataset by comparing its performance to thousands of randomly generated signatures. It will be of most interest for cases where few data are available and testing in multiple datasets is limited.

Pancreatic cancer circulating tumour cells express a cell motility gene signature that predicts survival after surgery

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Sergeant, Gregory; Eijsden, Rudy van; Roskams, Tania; Van Duppen, Victor; Topal, Baki

2012-01-01

Most cancer deaths are caused by metastases, resulting from circulating tumor cells (CTC) that detach from the primary cancer and survive in distant organs. The aim of the present study was to develop a CTC gene signature and to assess its prognostic relevance after surgery for pancreatic ductal adenocarcinoma (PDAC). Negative depletion fluorescence activated cell sorting (FACS) was developed and validated with spiking experiments using cancer cell lines in whole human blood samples. This FACS-based method was used to enrich for CTC from the blood of 10 patients who underwent surgery for PDAC. Total RNA was isolated from 4 subgroup samples, i.e. CTC, haematological cells (G), original tumour (T), and non-tumoural pancreatic control tissue (P). After RNA quality control, samples of 6 patients were eligible for further analysis. Whole genome microarray analysis was performed after double linear amplification of RNA. ‘Ingenuity Pathway Analysis’ software and AmiGO were used for functional data analyses. A CTC gene signature was developed and validated with the nCounter system on expression data of 78 primary PDAC using Cox regression analysis for disease-free (DFS) and overall survival (OS). Using stringent statistical analysis, we retained 8,152 genes to compare expression profiles of CTC vs. other subgroups, and found 1,059 genes to be differentially expressed. The pathway with the highest expression ratio in CTC was p38 mitogen-activated protein kinase (p38 MAPK) signaling, known to be involved in cancer cell migration. In the p38 MAPK pathway, TGF-β1, cPLA2, and MAX were significantly upregulated. In addition, 9 other genes associated with both p38 MAPK signaling and cell motility were overexpressed in CTC. High co-expression of TGF-β1 and our cell motility panel (≥ 4 out of 9 genes for DFS and ≥ 6 out of 9 genes for OS) in primary PDAC was identified as an independent predictor of DFS (p=0.041, HR (95% CI) = 1.885 (1.025 – 3.559)) and OS (p=0.047, HR

An algorithm to discover gene signatures with predictive potential

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Hallett Robin M

2010-09-01

Full Text Available Abstract Background The advent of global gene expression profiling has generated unprecedented insight into our molecular understanding of cancer, including breast cancer. For example, human breast cancer patients display significant diversity in terms of their survival, recurrence, metastasis as well as response to treatment. These patient outcomes can be predicted by the transcriptional programs of their individual breast tumors. Predictive gene signatures allow us to correctly classify human breast tumors into various risk groups as well as to more accurately target therapy to ensure more durable cancer treatment. Results Here we present a novel algorithm to generate gene signatures with predictive potential. The method first classifies the expression intensity for each gene as determined by global gene expression profiling as low, average or high. The matrix containing the classified data for each gene is then used to score the expression of each gene based its individual ability to predict the patient characteristic of interest. Finally, all examined genes are ranked based on their predictive ability and the most highly ranked genes are included in the master gene signature, which is then ready for use as a predictor. This method was used to accurately predict the survival outcomes in a cohort of human breast cancer patients. Conclusions We confirmed the capacity of our algorithm to generate gene signatures with bona fide predictive ability. The simplicity of our algorithm will enable biological researchers to quickly generate valuable gene signatures without specialized software or extensive bioinformatics training.

Sex hormones and gene expression signatures in peripheral blood from postmenopausal women - the NOWAC postgenome study

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Rylander Charlotta

2011-03-01

Full Text Available Abstract Background Postmenopausal hormone therapy (HT influences endogenous hormone concentrations and increases the risk of breast cancer. Gene expression profiling may reveal the mechanisms behind this relationship. Our objective was to explore potential associations between sex hormones and gene expression in whole blood from a population-based, random sample of postmenopausal women Methods Gene expression, as measured by the Applied Biosystems microarray platform, was compared between hormone therapy (HT users and non-users and between high and low hormone plasma concentrations using both gene-wise analysis and gene set analysis. Gene sets found to be associated with HT use were further analysed for enrichment in functional clusters and network predictions. The gene expression matrix included 285 samples and 16185 probes and was adjusted for significant technical variables. Results Gene-wise analysis revealed several genes significantly associated with different types of HT use. The functional cluster analyses provided limited information on these genes. Gene set analysis revealed 22 gene sets that were enriched between high and low estradiol concentration (HT-users excluded. Among these were seven oestrogen related gene sets, including our gene list associated with systemic estradiol use, which thereby represents a novel oestrogen signature. Seven gene sets were related to immune response. Among the 15 gene sets enriched for progesterone, 11 overlapped with estradiol. No significant gene expression patterns were found for testosterone, follicle stimulating hormone (FSH or sex hormone binding globulin (SHBG. Conclusions Distinct gene expression patterns associated with sex hormones are detectable in a random group of postmenopausal women, as demonstrated by the finding of a novel oestrogen signature.

Exploring gene expression signatures for predicting disease free survival after resection of colorectal cancer liver metastases.

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Nikol Snoeren

Full Text Available BACKGROUND AND OBJECTIVES: This study was designed to identify and validate gene signatures that can predict disease free survival (DFS in patients undergoing a radical resection for their colorectal liver metastases (CRLM. METHODS: Tumor gene expression profiles were collected from 119 patients undergoing surgery for their CRLM in the Paul Brousse Hospital (France and the University Medical Center Utrecht (The Netherlands. Patients were divided into high and low risk groups. A randomly selected training set was used to find predictive gene signatures. The ability of these gene signatures to predict DFS was tested in an independent validation set comprising the remaining patients. Furthermore, 5 known clinical risk scores were tested in our complete patient cohort. RESULT: No gene signature was found that significantly predicted DFS in the validation set. In contrast, three out of five clinical risk scores were able to predict DFS in our patient cohort. CONCLUSIONS: No gene signature was found that could predict DFS in patients undergoing CRLM resection. Three out of five clinical risk scores were able to predict DFS in our patient cohort. These results emphasize the need for validating risk scores in independent patient groups and suggest improved designs for future studies.

A meta-analysis of gene expression signatures of blood pressure and hypertension.

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Tianxiao Huan

2015-03-01

Full Text Available Genome-wide association studies (GWAS have uncovered numerous genetic variants (SNPs that are associated with blood pressure (BP. Genetic variants may lead to BP changes by acting on intermediate molecular phenotypes such as coded protein sequence or gene expression, which in turn affect BP variability. Therefore, characterizing genes whose expression is associated with BP may reveal cellular processes involved in BP regulation and uncover how transcripts mediate genetic and environmental effects on BP variability. A meta-analysis of results from six studies of global gene expression profiles of BP and hypertension in whole blood was performed in 7017 individuals who were not receiving antihypertensive drug treatment. We identified 34 genes that were differentially expressed in relation to BP (Bonferroni-corrected p<0.05. Among these genes, FOS and PTGS2 have been previously reported to be involved in BP-related processes; the others are novel. The top BP signature genes in aggregate explain 5%-9% of inter-individual variance in BP. Of note, rs3184504 in SH2B3, which was also reported in GWAS to be associated with BP, was found to be a trans regulator of the expression of 6 of the transcripts we found to be associated with BP (FOS, MYADM, PP1R15A, TAGAP, S100A10, and FGBP2. Gene set enrichment analysis suggested that the BP-related global gene expression changes include genes involved in inflammatory response and apoptosis pathways. Our study provides new insights into molecular mechanisms underlying BP regulation, and suggests novel transcriptomic markers for the treatment and prevention of hypertension.

Identification of a 251 gene expression signature that can accurately detect M. tuberculosis in patients with and without HIV co-infection.

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Noor Dawany

Full Text Available BACKGROUND: Co-infection with tuberculosis (TB is the leading cause of death in HIV-infected individuals. However, diagnosis of TB, especially in the presence of an HIV co-infection, can be limiting due to the high inaccuracy associated with the use of conventional diagnostic methods. Here we report a gene signature that can identify a tuberculosis infection in patients co-infected with HIV as well as in the absence of HIV. METHODS: We analyzed global gene expression data from peripheral blood mononuclear cell (PBMC samples of patients that were either mono-infected with HIV or co-infected with HIV/TB and used support vector machines to identify a gene signature that can distinguish between the two classes. We then validated our results using publically available gene expression data from patients mono-infected with TB. RESULTS: Our analysis successfully identified a 251-gene signature that accurately distinguishes patients co-infected with HIV/TB from those infected with HIV only, with an overall accuracy of 81.4% (sensitivity = 76.2%, specificity = 86.4%. Furthermore, we show that our 251-gene signature can also accurately distinguish patients with active TB in the absence of an HIV infection from both patients with a latent TB infection and healthy controls (88.9-94.7% accuracy; 69.2-90% sensitivity and 90.3-100% specificity. We also demonstrate that the expression levels of the 251-gene signature diminish as a correlate of the length of TB treatment. CONCLUSIONS: A 251-gene signature is described to (a detect TB in the presence or absence of an HIV co-infection, and (b assess response to treatment following anti-TB therapy.

A hemocyte gene expression signature correlated with predictive capacity of oysters to survive Vibrio infections

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Rosa Rafael

2012-06-01

Full Text Available Abstract Background The complex balance between environmental and host factors is an important determinant of susceptibility to infection. Disturbances of this equilibrium may result in multifactorial diseases as illustrated by the summer mortality syndrome, a worldwide and complex phenomenon that affects the oysters, Crassostrea gigas. The summer mortality syndrome reveals a physiological intolerance making this oyster species susceptible to diseases. Exploration of genetic basis governing the oyster resistance or susceptibility to infections is thus a major goal for understanding field mortality events. In this context, we used high-throughput genomic approaches to identify genetic traits that may characterize inherent survival capacities in C. gigas. Results Using digital gene expression (DGE, we analyzed the transcriptomes of hemocytes (immunocompetent cells of oysters able or not able to survive infections by Vibrio species shown to be involved in summer mortalities. Hemocytes were nonlethally collected from oysters before Vibrio experimental infection, and two DGE libraries were generated from individuals that survived or did not survive. Exploration of DGE data and microfluidic qPCR analyses at individual level showed an extraordinary polymorphism in gene expressions, but also a set of hemocyte-expressed genes whose basal mRNA levels discriminate oyster capacity to survive infections by the pathogenic V. splendidus LGP32. Finally, we identified a signature of 14 genes that predicted oyster survival capacity. Their expressions are likely driven by distinct transcriptional regulation processes associated or not associated to gene copy number variation (CNV. Conclusions We provide here for the first time in oyster a gene expression survival signature that represents a useful tool for understanding mortality events and for assessing genetic traits of interest for disease resistance selection programs.

Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures

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Liu Yufeng

2011-01-01

Full Text Available Abstract Background Multiple breast cancer gene expression profiles have been developed that appear to provide similar abilities to predict outcome and may outperform clinical-pathologic criteria; however, the extent to which seemingly disparate profiles provide additive prognostic information is not known, nor do we know whether prognostic profiles perform equally across clinically defined breast cancer subtypes. We evaluated whether combining the prognostic powers of standard breast cancer clinical variables with a large set of gene expression signatures could improve on our ability to predict patient outcomes. Methods Using clinical-pathological variables and a collection of 323 gene expression "modules", including 115 previously published signatures, we build multivariate Cox proportional hazards models using a dataset of 550 node-negative systemically untreated breast cancer patients. Models predictive of pathological complete response (pCR to neoadjuvant chemotherapy were also built using this approach. Results We identified statistically significant prognostic models for relapse-free survival (RFS at 7 years for the entire population, and for the subgroups of patients with ER-positive, or Luminal tumors. Furthermore, we found that combined models that included both clinical and genomic parameters improved prognostication compared with models with either clinical or genomic variables alone. Finally, we were able to build statistically significant combined models for pathological complete response (pCR predictions for the entire population. Conclusions Integration of gene expression signatures and clinical-pathological factors is an improved method over either variable type alone. Highly prognostic models could be created when using all patients, and for the subset of patients with lymph node-negative and ER-positive breast cancers. Other variables beyond gene expression and clinical-pathological variables, like gene mutation status or DNA

Histone methylation mediates plasticity of human FOXP3(+) regulatory T cells by modulating signature gene expressions.

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He, Haiqi; Ni, Bing; Tian, Yi; Tian, Zhiqiang; Chen, Yanke; Liu, Zhengwen; Yang, Xiaomei; Lv, Yi; Zhang, Yong

2014-03-01

CD4(+) FOXP3(+) regulatory T (Treg) cells constitute a heterogeneous and plastic T-cell lineage that plays a pivotal role in maintaining immune homeostasis and immune tolerance. However, the fate of human Treg cells after loss of FOXP3 expression and the epigenetic mechanisms contributing to such a phenotype switch remain to be fully elucidated. In the current study, we demonstrate that human CD4(+) CD25(high) CD127(low/-) Treg cells convert to two subpopulations with distinctive FOXP3(+) and FOXP3(-) phenotypes following in vitro culture with anti-CD3/CD28 and interleukin-2. Digital gene expression analysis showed that upon in vitro expansion, human Treg cells down-regulated Treg cell signature genes, such as FOXP3, CTLA4, ICOS, IKZF2 and LRRC32, but up-regulated a set of T helper lineage-associated genes, especially T helper type 2 (Th2)-associated, such as GATA3, GFI1 and IL13. Subsequent chromatin immunoprecipitation-sequencing of these subpopulations yielded genome-wide maps of their H3K4me3 and H3K27me3 profiles. Surprisingly, reprogramming of Treg cells was associated with differential histone modifications, as evidenced by decreased abundance of permissive H3K4me3 within the down-regulated Treg cell signature genes, such as FOXP3, CTLA4 and LRRC32 loci, and increased abundance of H3K4me3 within the Th2-associated genes, such as IL4 and IL5; however, the H3K27me3 modification profile was not significantly different between the two subpopulations. In conclusion, this study revealed that loss of FOXP3 expression from human Treg cells during in vitro expansion can induce reprogramming to a T helper cell phenotype with a gene expression signature dominated by Th2 lineage-associated genes, and that this cell type conversion may be mediated by histone methylation events. © 2013 John Wiley & Sons Ltd.

Histone methylation mediates plasticity of human FOXP3+ regulatory T cells by modulating signature gene expressions

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He, Haiqi; Ni, Bing; Tian, Yi; Tian, Zhiqiang; Chen, Yanke; Liu, Zhengwen; Yang, Xiaomei; Lv, Yi; Zhang, Yong

2014-01-01

CD4+ FOXP3+ regulatory T (Treg) cells constitute a heterogeneous and plastic T-cell lineage that plays a pivotal role in maintaining immune homeostasis and immune tolerance. However, the fate of human Treg cells after loss of FOXP3 expression and the epigenetic mechanisms contributing to such a phenotype switch remain to be fully elucidated. In the current study, we demonstrate that human CD4+ CD25high CD127low/− Treg cells convert to two subpopulations with distinctive FOXP3+ and FOXP3− phenotypes following in vitro culture with anti-CD3/CD28 and interleukin-2. Digital gene expression analysis showed that upon in vitro expansion, human Treg cells down-regulated Treg cell signature genes, such as FOXP3, CTLA4, ICOS, IKZF2 and LRRC32, but up-regulated a set of T helper lineage-associated genes, especially T helper type 2 (Th2)-associated, such as GATA3, GFI1 and IL13. Subsequent chromatin immunoprecipitation-sequencing of these subpopulations yielded genome-wide maps of their H3K4me3 and H3K27me3 profiles. Surprisingly, reprogramming of Treg cells was associated with differential histone modifications, as evidenced by decreased abundance of permissive H3K4me3 within the down-regulated Treg cell signature genes, such as FOXP3, CTLA4 and LRRC32 loci, and increased abundance of H3K4me3 within the Th2-associated genes, such as IL4 and IL5; however, the H3K27me3 modification profile was not significantly different between the two subpopulations. In conclusion, this study revealed that loss of FOXP3 expression from human Treg cells during in vitro expansion can induce reprogramming to a T helper cell phenotype with a gene expression signature dominated by Th2 lineage-associated genes, and that this cell type conversion may be mediated by histone methylation events. PMID:24152290

Reprogramming LCLs to iPSCs Results in Recovery of Donor-Specific Gene Expression Signature.

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Samantha M Thomas

2015-05-01

Full Text Available Renewable in vitro cell cultures, such as lymphoblastoid cell lines (LCLs, have facilitated studies that contributed to our understanding of genetic influence on human traits. However, the degree to which cell lines faithfully maintain differences in donor-specific phenotypes is still debated. We have previously reported that standard cell line maintenance practice results in a loss of donor-specific gene expression signatures in LCLs. An alternative to the LCL model is the induced pluripotent stem cell (iPSC system, which carries the potential to model tissue-specific physiology through the use of differentiation protocols. Still, existing LCL banks represent an important source of starting material for iPSC generation, and it is possible that the disruptions in gene regulation associated with long-term LCL maintenance could persist through the reprogramming process. To address this concern, we studied the effect of reprogramming mature LCL cultures from six unrelated donors to iPSCs on the ensuing gene expression patterns within and between individuals. We show that the reprogramming process results in a recovery of donor-specific gene regulatory signatures, increasing the number of genes with a detectable donor effect by an order of magnitude. The proportion of variation in gene expression statistically attributed to donor increases from 6.9% in LCLs to 24.5% in iPSCs (P < 10-15. Since environmental contributions are unlikely to be a source of individual variation in our system of highly passaged cultured cell lines, our observations suggest that the effect of genotype on gene regulation is more pronounced in iPSCs than in LCLs. Our findings indicate that iPSCs can be a powerful model system for studies of phenotypic variation across individuals in general, and the genetic association with variation in gene regulation in particular. We further conclude that LCLs are an appropriate starting material for iPSC generation.

Prediction of the prognosis of breast cancer in routine histologic specimens using a simplified, low-cost gene expression signature

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Marcell, S.A.; Balazs, A.; Emese, A.

2013-01-01

Prediction of the prognosis of breast cancer in routine histologic specimens using a simplified, low-cost gene expression signature Background: Grade 2 breast carcinomas do not form a uniform prognostic group. Aim: To extend the number of patients and the investigated genes of a previously...... grade 2 breast carcinomas into prognostic groups. Gene expression was investigated by polymerase chain reaction in 249 formalin-fixed, paraffin-embedded breast tumors. The results were correlated with relapse-free survival. Results: Histologically grade 2 carcinomas were split into good and a poor...... identified prognostic signature described by the authors that reflect chromosomal instability in order to refine characterization of grade 2 breast cancers and identify driver genes. Methods: Using publicly available databases, the authors selected 9 target and 3 housekeeping genes that are capable to divide...

EG-05COMBINATION OF GENE COPY GAIN AND EPIGENETIC DEREGULATION ARE ASSOCIATED WITH THE ABERRANT EXPRESSION OF A STEM CELL RELATED HOX-SIGNATURE IN GLIOBLASTOMA

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Kurscheid, Sebastian; Bady, Pierre; Sciuscio, Davide; Samarzija, Ivana; Shay, Tal; Vassallo, Irene; Van Criekinge, Wim; Domany, Eytan; Stupp, Roger; Delorenzi, Mauro; Hegi, Monika

2014-01-01

We previously reported a stem cell related HOX gene signature associated with resistance to chemo-radiotherapy (TMZ/RT- > TMZ) in glioblastoma. However, underlying mechanisms triggering overexpression remain mostly elusive. Interestingly, HOX genes are neither involved in the developing brain, nor expressed in normal brain, suggestive of an acquired gene expression signature during gliomagenesis. HOXA genes are located on CHR 7 that displays trisomy in most glioblastoma which strongly impacts gene expression on this chromosome, modulated by local regulatory elements. Furthermore we observed more pronounced DNA methylation across the HOXA locus as compared to non-tumoral brain (Human methylation 450K BeadChip Illumina; 59 glioblastoma, 5 non-tumoral brain sampes). CpG probes annotated for HOX-signature genes, contributing most to the variability, served as input into the analysis of DNA methylation and expression to identify key regulatory regions. The structural similarity of the observed correlation matrices between DNA methylation and gene expression in our cohort and an independent data-set from TCGA (106 glioblastoma) was remarkable (RV-coefficient, 0.84; p-value < 0.0001). We identified a CpG located in the promoter region of the HOXA10 locus exerting the strongest mean negative correlation between methylation and expression of the whole HOX-signature. Applying this analysis the same CpG emerged in the external set. We then determined the contribution of both, gene copy aberration (CNA) and methylation at the selected probe to explain expression of the HOX-signature using a linear model. Statistically significant results suggested an additive effect between gene dosage and methylation at the key CpG identified. Similarly, such an additive effect was also observed in the external data-set. Taken together, we hypothesize that overexpression of the stem-cell related HOX signature is triggered by gain of trisomy 7 and escape from compensatory DNA methylation at

A network-based predictive gene-expression signature for adjuvant chemotherapy benefit in stage II colorectal cancer.

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Cao, Bangrong; Luo, Liping; Feng, Lin; Ma, Shiqi; Chen, Tingqing; Ren, Yuan; Zha, Xiao; Cheng, Shujun; Zhang, Kaitai; Chen, Changmin

2017-12-13

The clinical benefit of adjuvant chemotherapy for stage II colorectal cancer (CRC) is controversial. This study aimed to explore novel gene signature to predict outcome benefit of postoperative 5-Fu-based therapy in stage II CRC. Gene-expression profiles of stage II CRCs from two datasets with 5-Fu-based adjuvant chemotherapy (training dataset, n = 212; validation dataset, n = 85) were analyzed to identify the indicator. A systemic approach by integrating gene-expression and protein-protein interaction (PPI) network was implemented to develop the predictive signature. Kaplan-Meier curves and Cox proportional hazards model were used to determine the survival benefit of adjuvant chemotherapy. Experiments with shRNA knock-down were carried out to confirm the signature identified in this study. In the training dataset, we identified 44 PPI sub-modules, by which we separate patients into two clusters (1 and 2) having different chemotherapeutic benefit. A predictor of 11 PPI sub-modules (11-PPI-Mod) was established to discriminate the two sub-groups, with an overall accuracy of 90.1%. This signature was independently validated in an external validation dataset. Kaplan-Meier curves showed an improved outcome for patients who received adjuvant chemotherapy in Cluster 1 sub-group, but even worse survival for those in Cluster 2 sub-group. Similar results were found in both the training and the validation dataset. Multivariate Cox regression revealed an interaction effect between 11-PPI-Mod signature and adjuvant therapy treatment in the training dataset (RFS, p = 0.007; OS, p = 0.006) and the validation dataset (RFS, p = 0.002). From the signature, we found that PTGES gene was up-regulated in CRC cells which were more resistant to 5-Fu. Knock-down of PTGES indicated a growth inhibition and up-regulation of apoptotic markers induced by 5-Fu in CRC cells. Only a small proportion of stage II CRC patients could benefit from adjuvant therapy. The 11-PPI-Mod as

A genome-wide gene expression signature of environmental geography in leukocytes of Moroccan Amazighs.

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Youssef Idaghdour

2008-04-01

Full Text Available The different environments that humans experience are likely to impact physiology and disease susceptibility. In order to estimate the magnitude of the impact of environment on transcript abundance, we examined gene expression in peripheral blood leukocyte samples from 46 desert nomadic, mountain agrarian and coastal urban Moroccan Amazigh individuals. Despite great expression heterogeneity in humans, as much as one third of the leukocyte transcriptome was found to be associated with differences among regions. Genome-wide polymorphism analysis indicates that genetic differentiation in the total sample is limited and is unlikely to explain the expression divergence. Methylation profiling of 1,505 CpG sites suggests limited contribution of methylation to the observed differences in gene expression. Genetic network analysis further implies that specific aspects of immune function are strongly affected by regional factors and may influence susceptibility to respiratory and inflammatory disease. Our results show a strong genome-wide gene expression signature of regional population differences that presumably include lifestyle, geography, and biotic factors, implying that these can play at least as great a role as genetic divergence in modulating gene expression variation in humans.

Liver regeneration signature in hepatitis B virus (HBV-associated acute liver failure identified by gene expression profiling.

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Oriel Nissim

Full Text Available The liver has inherent regenerative capacity via mitotic division of mature hepatocytes or, when the hepatic loss is massive or hepatocyte proliferation is impaired, through activation of hepatic stem/progenitor cells (HSPC. The dramatic clinical course of acute liver failure (ALF has posed major limitations to investigating the molecular mechanisms of liver regeneration and the role of HSPC in this setting. We investigated the molecular mechanisms of liver regeneration in 4 patients who underwent liver transplantation for hepatitis B virus (HBV-associated ALF.Gene expression profiling of 17 liver specimens from the 4 ALF cases and individual specimens from 10 liver donors documented a distinct gene signature for ALF. However, unsupervised multidimensional scaling and hierarchical clustering identified two clusters of ALF that segregated according to histopathological severity massive hepatic necrosis (MHN; 2 patients and submassive hepatic necrosis (SHN; 2 patients. We found that ALF is characterized by a strong HSPC gene signature, along with ductular reaction, both of which are more prominent in MHN. Interestingly, no evidence of further lineage differentiation was seen in MHN, whereas in SHN we detected cells with hepatocyte-like morphology. Strikingly, ALF was associated with a strong tumorigenesis gene signature. MHN had the greatest upregulation of stem cell genes (EpCAM, CK19, CK7, whereas the most up-regulated genes in SHN were related to cellular growth and proliferation. The extent of liver necrosis correlated with an overriding fibrogenesis gene signature, reflecting the wound-healing process.Our data provide evidence for a distinct gene signature in HBV-associated ALF whose intensity is directly correlated with the histopathological severity. HSPC activation and fibrogenesis positively correlated with the extent of liver necrosis. Moreover, we detected a tumorigenesis gene signature in ALF, emphasizing the close relationship between

Signature gene expression reveals novel clues to the molecular mechanisms of dimorphic transition in Penicillium marneffei.

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Ence Yang

2014-10-01

Full Text Available Systemic dimorphic fungi cause more than one million new infections each year, ranking them among the significant public health challenges currently encountered. Penicillium marneffei is a systemic dimorphic fungus endemic to Southeast Asia. The temperature-dependent dimorphic phase transition between mycelium and yeast is considered crucial for the pathogenicity and transmission of P. marneffei, but the underlying mechanisms are still poorly understood. Here, we re-sequenced P. marneffei strain PM1 using multiple sequencing platforms and assembled the genome using hybrid genome assembly. We determined gene expression levels using RNA sequencing at the mycelial and yeast phases of P. marneffei, as well as during phase transition. We classified 2,718 genes with variable expression across conditions into 14 distinct groups, each marked by a signature expression pattern implicated at a certain stage in the dimorphic life cycle. Genes with the same expression patterns tend to be clustered together on the genome, suggesting orchestrated regulations of the transcriptional activities of neighboring genes. Using qRT-PCR, we validated expression levels of all genes in one of clusters highly expressed during the yeast-to-mycelium transition. These included madsA, a gene encoding MADS-box transcription factor whose gene family is exclusively expanded in P. marneffei. Over-expression of madsA drove P. marneffei to undergo mycelial growth at 37°C, a condition that restricts the wild-type in the yeast phase. Furthermore, analyses of signature expression patterns suggested diverse roles of secreted proteins at different developmental stages and the potential importance of non-coding RNAs in mycelium-to-yeast transition. We also showed that RNA structural transition in response to temperature changes may be related to the control of thermal dimorphism. Together, our findings have revealed multiple molecular mechanisms that may underlie the dimorphic transition

Longitudinal Transcriptome Analysis Reveals a Sustained Differential Gene Expression Signature in Patients Treated for Acute Lyme Disease.

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Bouquet, Jerome; Soloski, Mark J; Swei, Andrea; Cheadle, Chris; Federman, Scot; Billaud, Jean-Noel; Rebman, Alison W; Kabre, Beniwende; Halpert, Richard; Boorgula, Meher; Aucott, John N; Chiu, Charles Y

2016-02-12

Lyme disease is a tick-borne illness caused by the bacterium Borrelia burgdorferi, and approximately 10 to 20% of patients report persistent symptoms lasting months to years despite appropriate treatment with antibiotics. To gain insights into the molecular basis of acute Lyme disease and the ensuing development of post-treatment symptoms, we conducted a longitudinal transcriptome study of 29 Lyme disease patients (and 13 matched controls) enrolled at the time of diagnosis and followed for up to 6 months. The differential gene expression signature of Lyme disease following the acute phase of infection persisted for at least 3 weeks and had fewer than 44% differentially expressed genes (DEGs) in common with other infectious or noninfectious syndromes. Early Lyme disease prior to antibiotic therapy was characterized by marked upregulation of Toll-like receptor signaling but lack of activation of the inflammatory T-cell apoptotic and B-cell developmental pathways seen in other acute infectious syndromes. Six months after completion of therapy, Lyme disease patients were found to have 31 to 60% of their pathways in common with three different immune-mediated chronic diseases. No differential gene expression signature was observed between Lyme disease patients with resolved illness to those with persistent symptoms at 6 months post-treatment. The identification of a sustained differential gene expression signature in Lyme disease suggests that a panel of selected human host-based biomarkers may address the need for sensitive clinical diagnostics during the "window period" of infection prior to the appearance of a detectable antibody response and may also inform the development of new therapeutic targets. Lyme disease is the most common tick-borne infection in the United States, and some patients report lingering symptoms lasting months to years despite antibiotic treatment. To better understand the role of the human host response in acute Lyme disease and the

Age gene expression and coexpression progressive signatures in peripheral blood leukocytes.

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Irizar, Haritz; Goñi, Joaquín; Alzualde, Ainhoa; Castillo-Triviño, Tamara; Olascoaga, Javier; Lopez de Munain, Adolfo; Otaegui, David

2015-12-01

Both cellular senescence and organismic aging are known to be dynamic processes that start early in life and progress constantly during the whole life of the individual. In this work, with the objective of identifying signatures of age-related progressive change at the transcriptomic level, we have performed a whole-genome gene expression analysis of peripheral blood leukocytes in a group of healthy individuals with ages ranging from 14 to 93 years. A set of genes with progressively changing gene expression (either increase or decrease with age) has been identified and contextualized in a coexpression network. A modularity analysis has been performed on this network and biological-term and pathway enrichment analyses have been used for biological interpretation of each module. In summary, the results of the present work reveal the existence of a transcriptomic component that shows progressive expression changes associated to age in peripheral blood leukocytes, highlighting both the dynamic nature of the process and the need to complement young vs. elder studies with longitudinal studies that include middle aged individuals. From the transcriptional point of view, immunosenescence seems to be occurring from a relatively early age, at least from the late 20s/early 30s, and the 49-56 year old age-range appears to be critical. In general, the genes that, according to our results, show progressive expression changes with aging are involved in pathogenic/cellular processes that have classically been linked to aging in humans: cancer, immune processes and cellular growth vs. maintenance. Copyright © 2015 Elsevier Inc. All rights reserved.

CRC-113 gene expression signature for predicting prognosis in patients with colorectal cancer.

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Nguyen, Minh Nam; Choi, Tae Gyu; Nguyen, Dinh Truong; Kim, Jin-Hwan; Jo, Yong Hwa; Shahid, Muhammad; Akter, Salima; Aryal, Saurav Nath; Yoo, Ji Youn; Ahn, Yong-Joo; Cho, Kyoung Min; Lee, Ju-Seog; Choe, Wonchae; Kang, Insug; Ha, Joohun; Kim, Sung Soo

2015-10-13

Colorectal cancer (CRC) is the third leading cause of global cancer mortality. Recent studies have proposed several gene signatures to predict CRC prognosis, but none of those have proven reliable for predicting prognosis in clinical practice yet due to poor reproducibility and molecular heterogeneity. Here, we have established a prognostic signature of 113 probe sets (CRC-113) that include potential biomarkers and reflect the biological and clinical characteristics. Robustness and accuracy were significantly validated in external data sets from 19 centers in five countries. In multivariate analysis, CRC-113 gene signature showed a stronger prognostic value for survival and disease recurrence in CRC patients than current clinicopathological risk factors and molecular alterations. We also demonstrated that the CRC-113 gene signature reflected both genetic and epigenetic molecular heterogeneity in CRC patients. Furthermore, incorporation of the CRC-113 gene signature into a clinical context and molecular markers further refined the selection of the CRC patients who might benefit from postoperative chemotherapy. Conclusively, CRC-113 gene signature provides new possibilities for improving prognostic models and personalized therapeutic strategies.

Longitudinal Transcriptome Analysis Reveals a Sustained Differential Gene Expression Signature in Patients Treated for Acute Lyme Disease

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Bouquet, Jerome; Soloski, Mark J.; Swei, Andrea; Cheadle, Chris; Federman, Scot; Billaud, Jean-Noel; Rebman, Alison W.; Kabre, Beniwende; Halpert, Richard; Boorgula, Meher

2016-01-01

ABSTRACT Lyme disease is a tick-borne illness caused by the bacterium Borrelia burgdorferi, and approximately 10 to 20% of patients report persistent symptoms lasting months to years despite appropriate treatment with antibiotics. To gain insights into the molecular basis of acute Lyme disease and the ensuing development of post-treatment symptoms, we conducted a longitudinal transcriptome study of 29 Lyme disease patients (and 13 matched controls) enrolled at the time of diagnosis and followed for up to 6 months. The differential gene expression signature of Lyme disease following the acute phase of infection persisted for at least 3 weeks and had fewer than 44% differentially expressed genes (DEGs) in common with other infectious or noninfectious syndromes. Early Lyme disease prior to antibiotic therapy was characterized by marked upregulation of Toll-like receptor signaling but lack of activation of the inflammatory T-cell apoptotic and B-cell developmental pathways seen in other acute infectious syndromes. Six months after completion of therapy, Lyme disease patients were found to have 31 to 60% of their pathways in common with three different immune-mediated chronic diseases. No differential gene expression signature was observed between Lyme disease patients with resolved illness to those with persistent symptoms at 6 months post-treatment. The identification of a sustained differential gene expression signature in Lyme disease suggests that a panel of selected human host-based biomarkers may address the need for sensitive clinical diagnostics during the “window period” of infection prior to the appearance of a detectable antibody response and may also inform the development of new therapeutic targets. PMID:26873097

Gene Expression Music Algorithm-Based Characterization of the Ewing Sarcoma Stem Cell Signature

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Martin Sebastian Staege

2016-01-01

Full Text Available Gene Expression Music Algorithm (GEMusicA is a method for the transformation of DNA microarray data into melodies that can be used for the characterization of differentially expressed genes. Using this method we compared gene expression profiles from endothelial cells (EC, hematopoietic stem cells, neuronal stem cells, embryonic stem cells (ESC, and mesenchymal stem cells (MSC and defined a set of genes that can discriminate between the different stem cell types. We analyzed the behavior of public microarray data sets from Ewing sarcoma (“Ewing family tumors,” EFT cell lines and biopsies in GEMusicA after prefiltering DNA microarray data for the probe sets from the stem cell signature. Our results demonstrate that individual Ewing sarcoma cell lines have a high similarity to ESC or EC. Ewing sarcoma cell lines with inhibited Ewing sarcoma breakpoint region 1-Friend leukemia virus integration 1 (EWSR1-FLI1 oncogene retained the similarity to ESC and EC. However, correlation coefficients between GEMusicA-processed expression data between EFT and ESC decreased whereas correlation coefficients between EFT and EC as well as between EFT and MSC increased after knockdown of EWSR1-FLI1. Our data support the concept of EFT being derived from cells with features of embryonic and endothelial cells.

Predictive gene signatures: molecular markers distinguishing colon adenomatous polyp and carcinoma.

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Janice E Drew

Full Text Available Cancers exhibit abnormal molecular signatures associated with disease initiation and progression. Molecular signatures could improve cancer screening, detection, drug development and selection of appropriate drug therapies for individual patients. Typically only very small amounts of tissue are available from patients for analysis and biopsy samples exhibit broad heterogeneity that cannot be captured using a single marker. This report details application of an in-house custom designed GenomeLab System multiplex gene expression assay, the hCellMarkerPlex, to assess predictive gene signatures of normal, adenomatous polyp and carcinoma colon tissue using archived tissue bank material. The hCellMarkerPlex incorporates twenty-one gene markers: epithelial (EZR, KRT18, NOX1, SLC9A2, proliferation (PCNA, CCND1, MS4A12, differentiation (B4GANLT2, CDX1, CDX2, apoptotic (CASP3, NOX1, NTN1, fibroblast (FSP1, COL1A1, structural (ACTG2, CNN1, DES, gene transcription (HDAC1, stem cell (LGR5, endothelial (VWF and mucin production (MUC2. Gene signatures distinguished normal, adenomatous polyp and carcinoma. Individual gene targets significantly contributing to molecular tissue types, classifier genes, were further characterised using real-time PCR, in-situ hybridisation and immunohistochemistry revealing aberrant epithelial expression of MS4A12, LGR5 CDX2, NOX1 and SLC9A2 prior to development of carcinoma. Identified gene signatures identify aberrant epithelial expression of genes prior to cancer development using in-house custom designed gene expression multiplex assays. This approach may be used to assist in objective classification of disease initiation, staging, progression and therapeutic responses using biopsy material.

Comprehensive evaluation of gene expression signatures in response to electroacupuncture stimulation at Zusanli (ST36) acupoint by transcriptomic analysis.

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Wu, Jing-Shan; Lo, Hsin-Yi; Li, Chia-Cheng; Chen, Feng-Yuan; Hsiang, Chien-Yun; Ho, Tin-Yun

2017-08-15

Electroacupuncture (EA) has been applied to treat and prevent diseases for years. However, molecular events happened in both the acupunctured site and the internal organs after EA stimulation have not been clarified. Here we applied transcriptomic analysis to explore the gene expression signatures after EA stimulation. Mice were applied EA stimulation at ST36 for 15 min and nine tissues were collected three hours later for microarray analysis. We found that EA affected the expression of genes not only in the acupunctured site but also in the internal organs. EA commonly affected biological networks involved in cytoskeleton and cell adhesion, and also regulated unique process networks in specific organs, such as γ-aminobutyric acid-ergic neurotransmission in brain and inflammation process in lung. In addition, EA affected the expression of genes related to various diseases, such as neurodegenerative diseases in brain and obstructive pulmonary diseases in lung. This report applied, for the first time, a global comprehensive genome-wide approach to analyze the gene expression profiling of acupunctured site and internal organs after EA stimulation. The connection between gene expression signatures, biological processes, and diseases might provide a basis for prediction and explanation on the therapeutic potentials of acupuncture in organs.

Meta-analysis of gene expression signatures defining the epithelial to mesenchymal transition during cancer progression.

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Christian J Gröger

Full Text Available The epithelial to mesenchymal transition (EMT represents a crucial event during cancer progression and dissemination. EMT is the conversion of carcinoma cells from an epithelial to a mesenchymal phenotype that associates with a higher cell motility as well as enhanced chemoresistance and cancer stemness. Notably, EMT has been increasingly recognized as an early event of metastasis. Numerous gene expression studies (GES have been conducted to obtain transcriptome signatures and marker genes to understand the regulatory mechanisms underlying EMT. Yet, no meta-analysis considering the multitude of GES of EMT has been performed to comprehensively elaborate the core genes in this process. Here we report the meta-analysis of 18 independent and published GES of EMT which focused on different cell types and treatment modalities. Computational analysis revealed clustering of GES according to the type of treatment rather than to cell type. GES of EMT induced via transforming growth factor-β and tumor necrosis factor-α treatment yielded uniformly defined clusters while GES of models with alternative EMT induction clustered in a more complex fashion. In addition, we identified those up- and downregulated genes which were shared between the multitude of GES. This core gene list includes well known EMT markers as well as novel genes so far not described in this process. Furthermore, several genes of the EMT-core gene list significantly correlated with impaired pathological complete response in breast cancer patients. In conclusion, this meta-analysis provides a comprehensive survey of available EMT expression signatures and shows fundamental insights into the mechanisms that are governing carcinoma progression.

No specific gene expression signature in human granulosa and cumulus cells for prediction of oocyte fertilisation and embryo implantation.

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Tanja Burnik Papler

Full Text Available In human IVF procedures objective and reliable biomarkers of oocyte and embryo quality are needed in order to increase the use of single embryo transfer (SET and thus prevent multiple pregnancies. During folliculogenesis there is an intense bi-directional communication between oocyte and follicular cells. For this reason gene expression profile of follicular cells could be an important indicator and biomarker of oocyte and embryo quality. The objective of this study was to identify gene expression signature(s in human granulosa (GC and cumulus (CC cells predictive of successful embryo implantation and oocyte fertilization. Forty-one patients were included in the study and individual GC and CC samples were collected; oocytes were cultivated separately, allowing a correlation with IVF outcome and elective SET was performed. Gene expression analysis was performed using microarrays, followed by a quantitative real-time PCR validation. After statistical analysis of microarray data, there were no significantly differentially expressed genes (FDR<0,05 between non-fertilized and fertilized oocytes and non-implanted and implanted embryos in either of the cell type. Furthermore, the results of quantitative real-time PCR were in consent with microarray data as there were no significant differences in gene expression of genes selected for validation. In conclusion, we did not find biomarkers for prediction of oocyte fertilization and embryo implantation in IVF procedures in the present study.

Early and long-standing rheumatoid arthritis: distinct molecular signatures identified by gene-expression profiling in synovia

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Lequerré, Thierry; Bansard, Carine; Vittecoq, Olivier; Derambure, Céline; Hiron, Martine; Daveau, Maryvonne; Tron, François; Ayral, Xavier; Biga, Norman; Auquit-Auckbur, Isabelle; Chiocchia, Gilles; Le Loët, Xavier; Salier, Jean-Philippe

2009-01-01

Introduction Rheumatoid arthritis (RA) is a heterogeneous disease and its underlying molecular mechanisms are still poorly understood. Because previous microarray studies have only focused on long-standing (LS) RA compared to osteoarthritis, we aimed to compare the molecular profiles of early and LS RA versus control synovia. Methods Synovial biopsies were obtained by arthroscopy from 15 patients (4 early untreated RA, 4 treated LS RA and 7 controls, who had traumatic or mechanical lesions). Extracted mRNAs were used for large-scale gene-expression profiling. The different gene-expression combinations identified by comparison of profiles of early, LS RA and healthy synovia were linked to the biological processes involved in each situation. Results Three combinations of 719, 116 and 52 transcripts discriminated, respectively, early from LS RA, and early or LS RA from healthy synovia. We identified several gene clusters and distinct molecular signatures specifically expressed during early or LS RA, thereby suggesting the involvement of different pathophysiological mechanisms during the course of RA. Conclusions Early and LS RA have distinct molecular signatures with different biological processes participating at different times during the course of the disease. These results suggest that better knowledge of the main biological processes involved at a given RA stage might help to choose the most appropriate treatment. PMID:19563633

DrugSig: A resource for computational drug repositioning utilizing gene expression signatures.

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Hongyu Wu

Full Text Available Computational drug repositioning has been proved as an effective approach to develop new drug uses. However, currently existing strategies strongly rely on drug response gene signatures which scattered in separated or individual experimental data, and resulted in low efficient outputs. So, a fully drug response gene signatures database will be very helpful to these methods. We collected drug response microarray data and annotated related drug and targets information from public databases and scientific literature. By selecting top 500 up-regulated and down-regulated genes as drug signatures, we manually established the DrugSig database. Currently DrugSig contains more than 1300 drugs, 7000 microarray and 800 targets. Moreover, we developed the signature based and target based functions to aid drug repositioning. The constructed database can serve as a resource to quicken computational drug repositioning. Database URL: http://biotechlab.fudan.edu.cn/database/drugsig/.

Gene expression signature analysis identifies vorinostat as a candidate therapy for gastric cancer.

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Sofie Claerhout

Full Text Available Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future.Using microarray technology, we generated a gene expression profile of human gastric cancer-specific genes from human gastric cancer tissue samples. We used this profile in the Broad Institute's Connectivity Map analysis to identify candidate therapeutic compounds for gastric cancer. We found the histone deacetylase inhibitor vorinostat as the lead compound and thus a potential therapeutic drug for gastric cancer. Vorinostat induced both apoptosis and autophagy in gastric cancer cell lines. Pharmacological and genetic inhibition of autophagy however, increased the therapeutic efficacy of vorinostat, indicating that a combination of vorinostat with autophagy inhibitors may therapeutically be more beneficial. Moreover, gene expression analysis of gastric cancer identified a collection of genes (ITGB5, TYMS, MYB, APOC1, CBX5, PLA2G2A, and KIF20A whose expression was elevated in gastric tumor tissue and downregulated more than 2-fold by vorinostat treatment in gastric cancer cell lines. In contrast, SCGB2A1, TCN1, CFD, APLP1, and NQO1 manifested a reversed pattern.We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment.

Exploring the molecular mechanisms of Traditional Chinese Medicine components using gene expression signatures and connectivity map.

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Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kim, Jihye; Kang, Jaewoo; Tan, Aik Choon

2018-04-04

Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the "multi-component, multi-target" nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map. We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource. We performed systematic data mining and analysis on the mechanism of action (MoA) of these TCM components based on the CMap results. We clustered the 102 TCM components into four groups based on their MoAs using next generation CMap resource. We performed gene set enrichment analysis on these components to provide additional supports for explaining these molecular mechanisms. We also provided literature evidence to validate the MoAs identified through this bioinformatics analysis. Finally, we developed the Traditional Chinese Medicine Drug Repurposing Hub (TCM Hub) - a connectivity map resource to facilitate the elucidation of TCM MoA for drug repurposing research. TCMHub is freely available in http://tanlab.ucdenver.edu/TCMHub. Molecular mechanisms of TCM could be uncovered by using gene expression signatures and connectivity map. Through this analysis, we identified many of the TCM components possess diverse MoAs, this may explain the applications of TCM in treating various symptoms and diseases. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Hormone-induced protection against mammary tumorigenesis is conserved in multiple rat strains and identifies a core gene expression signature induced by pregnancy.

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Blakely, Collin M; Stoddard, Alexander J; Belka, George K; Dugan, Katherine D; Notarfrancesco, Kathleen L; Moody, Susan E; D'Cruz, Celina M; Chodosh, Lewis A

2006-06-15

Women who have their first child early in life have a substantially lower lifetime risk of breast cancer. The mechanism for this is unknown. Similar to humans, rats exhibit parity-induced protection against mammary tumorigenesis. To explore the basis for this phenomenon, we identified persistent pregnancy-induced changes in mammary gene expression that are tightly associated with protection against tumorigenesis in multiple inbred rat strains. Four inbred rat strains that exhibit marked differences in their intrinsic susceptibilities to carcinogen-induced mammary tumorigenesis were each shown to display significant protection against methylnitrosourea-induced mammary tumorigenesis following treatment with pregnancy levels of estradiol and progesterone. Microarray expression profiling of parous and nulliparous mammary tissue from these four strains yielded a common 70-gene signature. Examination of the genes constituting this signature implicated alterations in transforming growth factor-beta signaling, the extracellular matrix, amphiregulin expression, and the growth hormone/insulin-like growth factor I axis in pregnancy-induced alterations in breast cancer risk. Notably, related molecular changes have been associated with decreased mammographic density, which itself is strongly associated with decreased breast cancer risk. Our findings show that hormone-induced protection against mammary tumorigenesis is widely conserved among divergent rat strains and define a gene expression signature that is tightly correlated with reduced mammary tumor susceptibility as a consequence of a normal developmental event. Given the conservation of this signature, these pathways may contribute to pregnancy-induced protection against breast cancer.

Gene Expression Signature Analysis Identifies Vorinostat as a Candidate Therapy for Gastric Cancer

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Choi, Woonyoung; Park, Yun-Yong; Kim, KyoungHyun; Kim, Sang-Bae; Lee, Ju-Seog; Mills, Gordon B.; Cho, Jae Yong

2011-01-01

Background Gastric cancer continues to be one of the deadliest cancers in the world and therefore identification of new drugs targeting this type of cancer is thus of significant importance. The purpose of this study was to identify and validate a therapeutic agent which might improve the outcomes for gastric cancer patients in the future. Methodology/Principal Findings Using microarray technology, we generated a gene expression profile of human gastric cancer–specific genes from human gastric cancer tissue samples. We used this profile in the Broad Institute's Connectivity Map analysis to identify candidate therapeutic compounds for gastric cancer. We found the histone deacetylase inhibitor vorinostat as the lead compound and thus a potential therapeutic drug for gastric cancer. Vorinostat induced both apoptosis and autophagy in gastric cancer cell lines. Pharmacological and genetic inhibition of autophagy however, increased the therapeutic efficacy of vorinostat, indicating that a combination of vorinostat with autophagy inhibitors may therapeutically be more beneficial. Moreover, gene expression analysis of gastric cancer identified a collection of genes (ITGB5, TYMS, MYB, APOC1, CBX5, PLA2G2A, and KIF20A) whose expression was elevated in gastric tumor tissue and downregulated more than 2-fold by vorinostat treatment in gastric cancer cell lines. In contrast, SCGB2A1, TCN1, CFD, APLP1, and NQO1 manifested a reversed pattern. Conclusions/Significance We showed that analysis of gene expression signature may represent an emerging approach to discover therapeutic agents for gastric cancer, such as vorinostat. The observation of altered gene expression after vorinostat treatment may provide the clue to identify the molecular mechanism of vorinostat and those patients likely to benefit from vorinostat treatment. PMID:21931799

Development of multigene expression signature maps at the protein level from digitized immunohistochemistry slides.

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Gregory J Metzger

Full Text Available Molecular classification of diseases based on multigene expression signatures is increasingly used for diagnosis, prognosis, and prediction of response to therapy. Immunohistochemistry (IHC is an optimal method for validating expression signatures obtained using high-throughput genomics techniques since IHC allows a pathologist to examine gene expression at the protein level within the context of histologically interpretable tissue sections. Additionally, validated IHC assays may be readily implemented as clinical tests since IHC is performed on routinely processed clinical tissue samples. However, methods have not been available for automated n-gene expression profiling at the protein level using IHC data. We have developed methods to compute expression level maps (signature maps of multiple genes from IHC data digitized on a commercial whole slide imaging system. Areas of cancer for these expression level maps are defined by a pathologist on adjacent, co-registered H&E slides, allowing assessment of IHC statistics and heterogeneity within the diseased tissue. This novel way of representing multiple IHC assays as signature maps will allow the development of n-gene expression profiling databases in three dimensions throughout virtual whole organ reconstructions.

Gene Expression Signature in Adipose Tissue of Acromegaly Patients

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Hochberg, Irit; Tran, Quynh T.; Barkan, Ariel L.; Saltiel, Alan R.; Chandler, William F.; Bridges, Dave

2015-01-01

To study the effect of chronic excess growth hormone on adipose tissue, we performed RNA sequencing in adipose tissue biopsies from patients with acromegaly (n = 7) or non-functioning pituitary adenomas (n = 11). The patients underwent clinical and metabolic profiling including assessment of HOMA-IR. Explants of adipose tissue were assayed ex vivo for lipolysis and ceramide levels. Patients with acromegaly had higher glucose, higher insulin levels and higher HOMA-IR score. We observed several previously reported transcriptional changes (IGF1, IGFBP3, CISH, SOCS2) that are known to be induced by GH/IGF-1 in liver but are also induced in adipose tissue. We also identified several novel transcriptional changes, some of which may be important for GH/IGF responses (PTPN3 and PTPN4) and the effects of acromegaly on growth and proliferation. Several differentially expressed transcripts may be important in GH/IGF-1-induced metabolic changes. Specifically, induction of LPL, ABHD5, and NRIP1 can contribute to enhanced lipolysis and may explain the elevated adipose tissue lipolysis in acromegalic patients. Higher expression of TCF7L2 and the fatty acid desaturases FADS1, FADS2 and SCD could contribute to insulin resistance. Ceramides were not different between the two groups. In summary, we have identified the acromegaly gene expression signature in human adipose tissue. The significance of altered expression of specific transcripts will enhance our understanding of the metabolic and proliferative changes associated with acromegaly. PMID:26087292

Prognostic Biomarker Identification Through Integrating the Gene Signatures of Hepatocellular Carcinoma Properties

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Jialin Cai

2017-05-01

Full Text Available Many molecular classification and prognostic gene signatures for hepatocellular carcinoma (HCC patients have been established based on genome-wide gene expression profiling; however, their generalizability is unclear. Herein, we systematically assessed the prognostic effects of these gene signatures and identified valuable prognostic biomarkers by integrating these gene signatures. With two independent HCC datasets (GSE14520, N = 242 and GSE54236, N = 78, 30 published gene signatures were evaluated, and 11 were significantly associated with the overall survival (OS of postoperative HCC patients in both datasets. The random survival forest models suggested that the gene signatures were superior to clinical characteristics for predicting the prognosis of the patients. Based on the 11 gene signatures, a functional protein-protein interaction (PPI network with 1406 nodes and 10,135 edges was established. With tissue microarrays of HCC patients (N = 60, we determined the prognostic values of the core genes in the network and found that RAD21, CDK1, and HDAC2 expression levels were negatively associated with OS for HCC patients. The multivariate Cox regression analyses suggested that CDK1 was an independent prognostic factor, which was validated in an independent case cohort (N = 78. In cellular models, inhibition of CDK1 by siRNA or a specific inhibitor, RO-3306, reduced cellular proliferation and viability for HCC cells. These results suggest that the prognostic predictive capacities of these gene signatures are reproducible and that CDK1 is a potential prognostic biomarker or therapeutic target for HCC patients.

Identification of a developmental gene expression signature, including HOX genes, for the normal human colonic crypt stem cell niche: overexpression of the signature parallels stem cell overpopulation during colon tumorigenesis.

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Bhatlekar, Seema; Addya, Sankar; Salunek, Moreh; Orr, Christopher R; Surrey, Saul; McKenzie, Steven; Fields, Jeremy Z; Boman, Bruce M

2014-01-15

Our goal was to identify a unique gene expression signature for human colonic stem cells (SCs). Accordingly, we determined the gene expression pattern for a known SC-enriched region--the crypt bottom. Colonic crypts and isolated crypt subsections (top, middle, and bottom) were purified from fresh, normal, human, surgical specimens. We then used an innovative strategy that used two-color microarrays (∼18,500 genes) to compare gene expression in the crypt bottom with expression in the other crypt subsections (middle or top). Array results were validated by PCR and immunostaining. About 25% of genes analyzed were expressed in crypts: 88 preferentially in the bottom, 68 in the middle, and 131 in the top. Among genes upregulated in the bottom, ∼30% were classified as growth and/or developmental genes including several in the PI3 kinase pathway, a six-transmembrane protein STAMP1, and two homeobox (HOXA4, HOXD10) genes. qPCR and immunostaining validated that HOXA4 and HOXD10 are selectively expressed in the normal crypt bottom and are overexpressed in colon carcinomas (CRCs). Immunostaining showed that HOXA4 and HOXD10 are co-expressed with the SC markers CD166 and ALDH1 in cells at the normal crypt bottom, and the number of these co-expressing cells is increased in CRCs. Thus, our findings show that these two HOX genes are selectively expressed in colonic SCs and that HOX overexpression in CRCs parallels the SC overpopulation that occurs during CRC development. Our study suggests that developmental genes play key roles in the maintenance of normal SCs and crypt renewal, and contribute to the SC overpopulation that drives colon tumorigenesis.

RNA Sequencing Reveals that Kaposi Sarcoma-Associated Herpesvirus Infection Mimics Hypoxia Gene Expression Signature

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Viollet, Coralie; Davis, David A.; Tekeste, Shewit S.; Reczko, Martin; Pezzella, Francesco; Ragoussis, Jiannis

2017-01-01

Kaposi sarcoma-associated herpesvirus (KSHV) causes several tumors and hyperproliferative disorders. Hypoxia and hypoxia-inducible factors (HIFs) activate latent and lytic KSHV genes, and several KSHV proteins increase the cellular levels of HIF. Here, we used RNA sequencing, qRT-PCR, Taqman assays, and pathway analysis to explore the miRNA and mRNA response of uninfected and KSHV-infected cells to hypoxia, to compare this with the genetic changes seen in chronic latent KSHV infection, and to explore the degree to which hypoxia and KSHV infection interact in modulating mRNA and miRNA expression. We found that the gene expression signatures for KSHV infection and hypoxia have a 34% overlap. Moreover, there were considerable similarities between the genes up-regulated by hypoxia in uninfected (SLK) and in KSHV-infected (SLKK) cells. hsa-miR-210, a HIF-target known to have pro-angiogenic and anti-apoptotic properties, was significantly up-regulated by both KSHV infection and hypoxia using Taqman assays. Interestingly, expression of KSHV-encoded miRNAs was not affected by hypoxia. These results demonstrate that KSHV harnesses a part of the hypoxic cellular response and that a substantial portion of hypoxia-induced changes in cellular gene expression are induced by KSHV infection. Therefore, targeting hypoxic pathways may be a useful way to develop therapeutic strategies for KSHV-related diseases. PMID:28046107

Identification of a gene expression core signature for Duchenne Muscular Dystrophy (DMD) via integrative analysis reveals novel potential compounds for treatment

KAUST Repository

Ichim-Moreno, Norú

2010-05-01

Duchenne muscular dystrophy (DMD) is a recessive X-linked form of muscular dystrophy and one of the most prevalent genetic disorders of childhood. DMD is characterized by rapid progression of muscle degeneration, and ultimately death. Currently, glucocorticoids are the only available treatment for DMD, but they have been shown to result in serious side effects. The purpose of this research was to define a core signature of gene expression related to DMD via integrative analysis of mouse and human datasets. This core signature was subsequently used to screen for novel potential compounds that antagonistically affect the expression of signature genes. With this approach we were able to identify compounds that are 1) already used to treat DMD, 2) currently under investigation for treatment, and 3) so far unknown but promising candidates. Our study highlights the potential of meta-analyses through the combination of datasets to unravel previously unrecognized associations and reveal new relationships. © IEEE.

A gene signature in histologically normal surgical margins is predictive of oral carcinoma recurrence

International Nuclear Information System (INIS)

Reis, Patricia P; Simpson, Colleen; Goldstein, David; Brown, Dale; Gilbert, Ralph; Gullane, Patrick; Irish, Jonathan; Jurisica, Igor; Kamel-Reid, Suzanne; Waldron, Levi; Perez-Ordonez, Bayardo; Pintilie, Melania; Galloni, Natalie Naranjo; Xuan, Yali; Cervigne, Nilva K; Warner, Giles C; Makitie, Antti A

2011-01-01

Oral Squamous Cell Carcinoma (OSCC) is a major cause of cancer death worldwide, which is mainly due to recurrence leading to treatment failure and patient death. Histological status of surgical margins is a currently available assessment for recurrence risk in OSCC; however histological status does not predict recurrence, even in patients with histologically negative margins. Therefore, molecular analysis of histologically normal resection margins and the corresponding OSCC may aid in identifying a gene signature predictive of recurrence. We used a meta-analysis of 199 samples (OSCCs and normal oral tissues) from five public microarray datasets, in addition to our microarray analysis of 96 OSCCs and histologically normal margins from 24 patients, to train a gene signature for recurrence. Validation was performed by quantitative real-time PCR using 136 samples from an independent cohort of 30 patients. We identified 138 significantly over-expressed genes (> 2-fold, false discovery rate of 0.01) in OSCC. By penalized likelihood Cox regression, we identified a 4-gene signature with prognostic value for recurrence in our training set. This signature comprised the invasion-related genes MMP1, COL4A1, P4HA2, and THBS2. Over-expression of this 4-gene signature in histologically normal margins was associated with recurrence in our training cohort (p = 0.0003, logrank test) and in our independent validation cohort (p = 0.04, HR = 6.8, logrank test). Gene expression alterations occur in histologically normal margins in OSCC. Over-expression of the 4-gene signature in histologically normal surgical margins was validated and highly predictive of recurrence in an independent patient cohort. Our findings may be applied to develop a molecular test, which would be clinically useful to help predict which patients are at a higher risk of local recurrence

Analytical validation of a melanoma diagnostic gene signature using formalin-fixed paraffin-embedded melanocytic lesions.

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Warf, M Bryan; Flake, Darl D; Adams, Doug; Gutin, Alexander; Kolquist, Kathryn A; Wenstrup, Richard J; Roa, Benjamin B

2015-01-01

These studies were to validate the analytical performance of a gene expression signature that differentiates melanoma and nevi, using RNA expression from 14 signature genes and nine normalization genes that generates a melanoma diagnostic score (MDS). Formalin-fixed paraffin-embedded melanocytic lesions were evaluated in these studies. The overall SD of the assay was determined to be 0.69 MDS units. Individual amplicons within the signature had an average amplification efficiency of 92% and a SD less than 0.5 CT. The MDS was reproducible across a 2000-fold dilution range of input RNA. Melanin, an inhibitor of PCR, does not interfere with the signature. These studies indicate this signature is robust and reproducible and is analytically validated on formalin-fixed paraffin-embedded melanocytic lesions.

Gene expression signature of cigarette smoking and its role in lung adenocarcinoma development and survival.

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Maria Teresa Landi

2008-02-01

Full Text Available Tobacco smoking is responsible for over 90% of lung cancer cases, and yet the precise molecular alterations induced by smoking in lung that develop into cancer and impact survival have remained obscure.We performed gene expression analysis using HG-U133A Affymetrix chips on 135 fresh frozen tissue samples of adenocarcinoma and paired noninvolved lung tissue from current, former and never smokers, with biochemically validated smoking information. ANOVA analysis adjusted for potential confounders, multiple testing procedure, Gene Set Enrichment Analysis, and GO-functional classification were conducted for gene selection. Results were confirmed in independent adenocarcinoma and non-tumor tissues from two studies. We identified a gene expression signature characteristic of smoking that includes cell cycle genes, particularly those involved in the mitotic spindle formation (e.g., NEK2, TTK, PRC1. Expression of these genes strongly differentiated both smokers from non-smokers in lung tumors and early stage tumor tissue from non-tumor tissue (p1.5, for each comparison, consistent with an important role for this pathway in lung carcinogenesis induced by smoking. These changes persisted many years after smoking cessation. NEK2 (p<0.001 and TTK (p = 0.002 expression in the noninvolved lung tissue was also associated with a 3-fold increased risk of mortality from lung adenocarcinoma in smokers.Our work provides insight into the smoking-related mechanisms of lung neoplasia, and shows that the very mitotic genes known to be involved in cancer development are induced by smoking and affect survival. These genes are candidate targets for chemoprevention and treatment of lung cancer in smokers.

MicroRNA and gene signature of severe cutaneous drug ...

African Journals Online (AJOL)

Purpose: To build a microRNA and gene signature of severe cutaneous adverse drug reactions (SCAR), including Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). Methods: MicroRNA expression profiles were downloaded from miRNA expression profile of patients' skin suffering from TEN using an ...

A 6-gene signature identifies four molecular subgroups of neuroblastoma

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2011-01-01

Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p INSS stage 4 and/or dead of disease, p < 0.05, Fisher's exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics. PMID:21492432

Maximizing biomarker discovery by minimizing gene signatures

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Chang Chang

2011-12-01

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

Combining Gene Signatures Improves Prediction of Breast Cancer Survival

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Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

2011-01-01

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

Combining gene signatures improves prediction of breast cancer survival.

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Xi Zhao

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

Inflammation, Adenoma and Cancer: Objective Classification of Colon Biopsy Specimens with Gene Expression Signature

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Orsolya Galamb

2008-01-01

Full Text Available Gene expression analysis of colon biopsies using high-density oligonucleotide microarrays can contribute to the understanding of local pathophysiological alterations and to functional classification of adenoma (15 samples, colorectal carcinomas (CRC (15 and inflammatory bowel diseases (IBD (14. Total RNA was extracted, amplified and biotinylated from frozen colonic biopsies. Genome-wide gene expression profile was evaluated by HGU133plus2 microarrays and verified by RT-PCR. We applied two independent methods for data normalization and used PAM for feature selection. Leave one-out stepwise discriminant analysis was performed. Top validated genes included collagenIVα1, lipocalin-2, calumenin, aquaporin-8 genes in CRC; CD44, met proto-oncogene, chemokine ligand-12, ADAM-like decysin-1 and ATP-binding casette-A8 genes in adenoma; and lipocalin-2, ubiquitin D and IFITM2 genes in IBD. Best differentiating markers between Ulcerative colitis and Crohn's disease were cyclin-G2; tripartite motif-containing-31; TNFR shedding aminopeptidase regulator-1 and AMICA. The discriminant analysis was able to classify the samples in overall 96.2% using 7 discriminatory genes (indoleamine-pyrrole-2,3-dioxygenase, ectodermal-neural cortex, TIMP3, fucosyltransferase-8, collectin sub-family member 12, carboxypeptidase D, and transglutaminase-2. Using routine biopsy samples we successfully performed whole genomic microarray analysis to identify discriminative signatures. Our results provide further insight into the pathophysiological background of colonic diseases. The results set up data warehouse which can be mined further.

Gene-expression signature regulated by the KEAP1-NRF2-CUL3 axis is associated with a poor prognosis in head and neck squamous cell cancer.

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Namani, Akhileshwar; Matiur Rahaman, Md; Chen, Ming; Tang, Xiuwen

2018-01-06

NRF2 is the key regulator of oxidative stress in normal cells and aberrant expression of the NRF2 pathway due to genetic alterations in the KEAP1 (Kelch-like ECH-associated protein 1)-NRF2 (nuclear factor erythroid 2 like 2)-CUL3 (cullin 3) axis leads to tumorigenesis and drug resistance in many cancers including head and neck squamous cell cancer (HNSCC). The main goal of this study was to identify specific genes regulated by the KEAP1-NRF2-CUL3 axis in HNSCC patients, to assess the prognostic value of this gene signature in different cohorts, and to reveal potential biomarkers. RNA-Seq V2 level 3 data from 279 tumor samples along with 37 adjacent normal samples from patients enrolled in the The Cancer Genome Atlas (TCGA)-HNSCC study were used to identify upregulated genes using two methods (altered KEAP1-NRF2-CUL3 versus normal, and altered KEAP1-NRF2-CUL3 versus wild-type). We then used a new approach to identify the combined gene signature by integrating both datasets and subsequently tested this signature in 4 independent HNSCC datasets to assess its prognostic value. In addition, functional annotation using the DAVID v6.8 database and protein-protein interaction (PPI) analysis using the STRING v10 database were performed on the signature. A signature composed of a subset of 17 genes regulated by the KEAP1-NRF2-CUL3 axis was identified by overlapping both the upregulated genes of altered versus normal (251 genes) and altered versus wild-type (25 genes) datasets. We showed that increased expression was significantly associated with poor survival in 4 independent HNSCC datasets, including the TCGA-HNSCC dataset. Furthermore, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and PPI analysis revealed that most of the genes in this signature are associated with drug metabolism and glutathione metabolic pathways. Altogether, our study emphasizes the discovery of a gene signature regulated by the KEAP1-NRF2-CUL3 axis which is strongly associated with

Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype

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Kanth, Priyanka; Bronner, Mary P.; Boucher, Kenneth M.; Burt, Randall W.; Neklason, Deborah W.; Hagedorn, Curt H.; Delker, Don A.

2016-01-01

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

A gene expression signature for RSV: clinical implications and limitations.

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Peter J M Openshaw

2013-11-01

Full Text Available Peter Openshaw discusses the challenges in advancing respiratory syncytial virus (RSV treatments and the implications of a study by Mejias and colleagues using a newly identified gene signature for diagnosis and prediction of RSV severity. Please see later in the article for the Editors' Summary.

Operator dependent choice of prostate cancer biopsy has limited impact on a gene signature analysis for the highly expressed genes IGFBP3 and F3 in prostate cancer epithelial cells.

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Zhuochun Peng

Full Text Available BACKGROUND: Predicting the prognosis of prostate cancer disease through gene expression analysis is receiving increasing interest. In many cases, such analyses are based on formalin-fixed, paraffin embedded (FFPE core needle biopsy material on which Gleason grading for diagnosis has been conducted. Since each patient typically has multiple biopsy samples, and since Gleason grading is an operator dependent procedure known to be difficult, the impact of the operator's choice of biopsy was evaluated. METHODS: Multiple biopsy samples from 43 patients were evaluated using a previously reported gene signature of IGFBP3, F3 and VGLL3 with potential prognostic value in estimating overall survival at diagnosis of prostate cancer. A four multiplex one-step qRT-PCR test kit, designed and optimized for measuring the signature in FFPE core needle biopsy samples was used. Concordance of gene expression levels between primary and secondary Gleason tumor patterns, as well as benign tissue specimens, was analyzed. RESULTS: The gene expression levels of IGFBP3 and F3 in prostate cancer epithelial cell-containing tissue representing the primary and secondary Gleason patterns were high and consistent, while the low expressed VGLL3 showed more variation in its expression levels. CONCLUSION: The assessment of IGFBP3 and F3 gene expression levels in prostate cancer tissue is independent of Gleason patterns, meaning that the impact of operator's choice of biopsy is low.

A 65‑gene signature for prognostic prediction in colon adenocarcinoma.

Science.gov (United States)

Jiang, Hui; Du, Jun; Gu, Jiming; Jin, Liugen; Pu, Yong; Fei, Bojian

2018-04-01

The aim of the present study was to examine the molecular factors associated with the prognosis of colon cancer. Gene expression datasets were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases to screen differentially expressed genes (DEGs) between colon cancer samples and normal samples. Survival‑related genes were selected from the DEGs using the Cox regression method. A co‑expression network of survival‑related genes was then constructed, and functional clusters were extracted from this network. The significantly enriched functions and pathways of the genes in the network were identified. Using Bayesian discriminant analysis, a prognostic prediction system was established to distinguish the positive from negative prognostic samples. The discrimination efficacy of the system was validated in the GSE17538 dataset using Kaplan‑Meier survival analysis. A total of 636 and 1,892 DEGs between the colon cancer samples and normal samples were screened from the TCGA and GSE44861 dataset, respectively. There were 155 survival‑related genes selected. The co‑expression network of survival‑related genes included 138 genes, 534 lines (connections) and five functional clusters, including the signaling pathway, cellular response to cAMP, and immune system process functional clusters. The molecular function, cellular components and biological processes were the significantly enriched functions. The peroxisome proliferator‑activated receptor signaling pathway, Wnt signaling pathway, B cell receptor signaling pathway, and cytokine‑cytokine receptor interactions were the significant pathways. A prognostic prediction system based on a 65‑gene signature was established using this co‑expression network. Its discriminatory effect was validated in the TCGA dataset (P=3.56e‑12) and the GSE17538 dataset (P=1.67e‑6). The 65‑gene signature included kallikrein‑related peptidase 6 (KLK6), collagen type XI α1 (COL11A1), cartilage

eXpression2Kinases (X2K) Web: linking expression signatures to upstream cell signaling networks.

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Clarke, Daniel J B; Kuleshov, Maxim V; Schilder, Brian M; Torre, Denis; Duffy, Mary E; Keenan, Alexandra B; Lachmann, Alexander; Feldmann, Axel S; Gundersen, Gregory W; Silverstein, Moshe C; Wang, Zichen; Ma'ayan, Avi

2018-05-25

While gene expression data at the mRNA level can be globally and accurately measured, profiling the activity of cell signaling pathways is currently much more difficult. eXpression2Kinases (X2K) computationally predicts involvement of upstream cell signaling pathways, given a signature of differentially expressed genes. X2K first computes enrichment for transcription factors likely to regulate the expression of the differentially expressed genes. The next step of X2K connects these enriched transcription factors through known protein-protein interactions (PPIs) to construct a subnetwork. The final step performs kinase enrichment analysis on the members of the subnetwork. X2K Web is a new implementation of the original eXpression2Kinases algorithm with important enhancements. X2K Web includes many new transcription factor and kinase libraries, and PPI networks. For demonstration, thousands of gene expression signatures induced by kinase inhibitors, applied to six breast cancer cell lines, are provided for fetching directly into X2K Web. The results are displayed as interactive downloadable vector graphic network images and bar graphs. Benchmarking various settings via random permutations enabled the identification of an optimal set of parameters to be used as the default settings in X2K Web. X2K Web is freely available from http://X2K.cloud.

Epigenetic regulation on the gene expression signature in esophagus adenocarcinoma.

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Xi, Ting; Zhang, Guizhi

2017-02-01

Understanding the molecular mechanisms represents an important step in the development of diagnostic and therapeutic measures of esophagus adenocarcinoma (NOS). The objective of this study is to identify the epigenetic regulation on gene expression in NOS, shedding light on the molecular mechanisms of NOS. In this study, 78 patients with NOS were included and the data of mRNA, miRNA and DNA methylation of were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis between NOS and controls was performed in terms of gene expression, miRNA expression, and DNA methylation. Bioinformatic analysis was followed to explore the regulation mechanisms of miRNA and DNA methylationon gene expression. Totally, up to 1320 differentially expressed genes (DEGs) and 32 differentially expressed miRNAs were identified. 240 DEGs that were not only the target genes but also negatively correlated with the screened differentially expressed miRNAs. 101 DEGs were found to be highlymethylated in CpG islands. Then, 8 differentially methylated genes (DMGs) were selected, which showed down-regulated expression in NOS. Among of these genes, 6 genes including ADHFE1, DPP6, GRIA4, CNKSR2, RPS6KA6 and ZNF135 were target genes of differentially expressed miRNAs (hsa-mir-335, hsa-mir-18a, hsa-mir-93, hsa-mir-106b and hsa-mir-21). The identified altered miRNA, genes and DNA methylation site may be applied as biomarkers for diagnosis and prognosis of NOS. Copyright © 2016 Elsevier GmbH. All rights reserved.

Pathway analysis of gene signatures predicting metastasis of node-negative primary breast cancer

International Nuclear Information System (INIS)

Yu, Jack X; Sieuwerts, Anieta M; Zhang, Yi; Martens, John WM; Smid, Marcel; Klijn, Jan GM; Wang, Yixin; Foekens, John A

2007-01-01

Published prognostic gene signatures in breast cancer have few genes in common. Here we provide a rationale for this observation by studying the prognostic power and the underlying biological pathways of different gene signatures. Gene signatures to predict the development of metastases in estrogen receptor-positive and estrogen receptor-negative tumors were identified using 500 re-sampled training sets and mapping to Gene Ontology Biological Process to identify over-represented pathways. The Global Test program confirmed that gene expression profilings in the common pathways were associated with the metastasis of the patients. The apoptotic pathway and cell division, or cell growth regulation and G-protein coupled receptor signal transduction, were most significantly associated with the metastatic capability of estrogen receptor-positive or estrogen-negative tumors, respectively. A gene signature derived of the common pathways predicted metastasis in an independent cohort. Mapping of the pathways represented by different published prognostic signatures showed that they share 53% of the identified pathways. We show that divergent gene sets classifying patients for the same clinical endpoint represent similar biological processes and that pathway-derived signatures can be used to predict prognosis. Furthermore, our study reveals that the underlying biology related to aggressiveness of estrogen receptor subgroups of breast cancer is quite different

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

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Loboda, Andrey; Nebozhyn, Michael; Klinghoffer, Rich; Frazier, Jason; Chastain, Michael; Arthur, William; Roberts, Brian; Zhang, Theresa; Chenard, Melissa; Haines, Brian; Andersen, Jannik; Nagashima, Kumiko; Paweletz, Cloud; Lynch, Bethany; Feldman, Igor; Dai, Hongyue; Huang, Pearl; Watters, James

2010-06-30

Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast tumors.

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors

Directory of Open Access Journals (Sweden)

Paweletz Cloud

2010-06-01

Full Text Available Abstract Background Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. Methods We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. Results The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90% sensitivity but relatively low (50% specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. Conclusions These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical

A 6-gene signature identifies four molecular subgroups of neuroblastoma

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Kogner Per

2011-04-01

Full Text Available Abstract Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB; Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples. Four distinct clusters were identified by Principal Components Analysis (PCA in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and/or dead of disease, p Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group's specific characteristics.

Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes.

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Taube, Joseph H; Herschkowitz, Jason I; Komurov, Kakajan; Zhou, Alicia Y; Gupta, Supriya; Yang, Jing; Hartwell, Kimberly; Onder, Tamer T; Gupta, Piyush B; Evans, Kurt W; Hollier, Brett G; Ram, Prahlad T; Lander, Eric S; Rosen, Jeffrey M; Weinberg, Robert A; Mani, Sendurai A

2010-08-31

The epithelial-to-mesenchymal transition (EMT) produces cancer cells that are invasive, migratory, and exhibit stem cell characteristics, hallmarks of cells that have the potential to generate metastases. Inducers of the EMT include several transcription factors (TFs), such as Goosecoid, Snail, and Twist, as well as the secreted TGF-beta1. Each of these factors is capable, on its own, of inducing an EMT in the human mammary epithelial (HMLE) cell line. However, the interactions between these regulators are poorly understood. Overexpression of each of the above EMT inducers up-regulates a subset of other EMT-inducing TFs, with Twist, Zeb1, Zeb2, TGF-beta1, and FOXC2 being commonly induced. Up-regulation of Slug and FOXC2 by either Snail or Twist does not depend on TGF-beta1 signaling. Gene expression signatures (GESs) derived by overexpressing EMT-inducing TFs reveal that the Twist GES and Snail GES are the most similar, although the Goosecoid GES is the least similar to the others. An EMT core signature was derived from the changes in gene expression shared by up-regulation of Gsc, Snail, Twist, and TGF-beta1 and by down-regulation of E-cadherin, loss of which can also trigger an EMT in certain cell types. The EMT core signature associates closely with the claudin-low and metaplastic breast cancer subtypes and correlates negatively with pathological complete response. Additionally, the expression level of FOXC1, another EMT inducer, correlates strongly with poor survival of breast cancer patients.

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

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Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

2018-04-23

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis

Gene expression profiles in stages II and III colon cancers

DEFF Research Database (Denmark)

Thorsteinsson, Morten; Kirkeby, Lene T; Hansen, Raino

2012-01-01

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...

Effects of sample size on robustness and prediction accuracy of a prognostic gene signature

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Kim Seon-Young

2009-05-01

Full Text Available Abstract Background Few overlap between independently developed gene signatures and poor inter-study applicability of gene signatures are two of major concerns raised in the development of microarray-based prognostic gene signatures. One recent study suggested that thousands of samples are needed to generate a robust prognostic gene signature. Results A data set of 1,372 samples was generated by combining eight breast cancer gene expression data sets produced using the same microarray platform and, using the data set, effects of varying samples sizes on a few performances of a prognostic gene signature were investigated. The overlap between independently developed gene signatures was increased linearly with more samples, attaining an average overlap of 16.56% with 600 samples. The concordance between predicted outcomes by different gene signatures also was increased with more samples up to 94.61% with 300 samples. The accuracy of outcome prediction also increased with more samples. Finally, analysis using only Estrogen Receptor-positive (ER+ patients attained higher prediction accuracy than using both patients, suggesting that sub-type specific analysis can lead to the development of better prognostic gene signatures Conclusion Increasing sample sizes generated a gene signature with better stability, better concordance in outcome prediction, and better prediction accuracy. However, the degree of performance improvement by the increased sample size was different between the degree of overlap and the degree of concordance in outcome prediction, suggesting that the sample size required for a study should be determined according to the specific aims of the study.

A gene signature to determine metastatic behavior in thymomas.

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Yesim Gökmen-Polar

Full Text Available PURPOSE: Thymoma represents one of the rarest of all malignancies. Stage and completeness of resection have been used to ascertain postoperative therapeutic strategies albeit with limited prognostic accuracy. A molecular classifier would be useful to improve the assessment of metastatic behaviour and optimize patient management. METHODS: qRT-PCR assay for 23 genes (19 test and four reference genes was performed on multi-institutional archival primary thymomas (n = 36. Gene expression levels were used to compute a signature, classifying tumors into classes 1 and 2, corresponding to low or high likelihood for metastases. The signature was validated in an independent multi-institutional cohort of patients (n = 75. RESULTS: A nine-gene signature that can predict metastatic behavior of thymomas was developed and validated. Using radial basis machine modeling in the training set, 5-year and 10-year metastasis-free survival rates were 77% and 26% for predicted low (class 1 and high (class 2 risk of metastasis (P = 0.0047, log-rank, respectively. For the validation set, 5-year metastasis-free survival rates were 97% and 30% for predicted low- and high-risk patients (P = 0.0004, log-rank, respectively. The 5-year metastasis-free survival rates for the validation set were 49% and 41% for Masaoka stages I/II and III/IV (P = 0.0537, log-rank, respectively. In univariate and multivariate Cox models evaluating common prognostic factors for thymoma metastasis, the nine-gene signature was the only independent indicator of metastases (P = 0.036. CONCLUSION: A nine-gene signature was established and validated which predicts the likelihood of metastasis more accurately than traditional staging. This further underscores the biologic determinants of the clinical course of thymoma and may improve patient management.

Gene expression patterns associated with p53 status in breast cancer

International Nuclear Information System (INIS)

Troester, Melissa A; Herschkowitz, Jason I; Oh, Daniel S; He, Xiaping; Hoadley, Katherine A; Barbier, Claire S; Perou, Charles M

2006-01-01

Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function). The p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. The cell line signatures were compared with p53-mutation associated genes in breast tumors. Each cell line displayed distinct patterns of p53-dependent gene expression, but cell type specific (basal vs. luminal) commonalities were evident. Further, a common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss/mutation status in primary breast tumors. Moreover, the common cell-line tumor signature excluded genes that were breast cancer subtype-associated, but not downstream of p53. To validate the biological relevance of the common signature, we demonstrated that this gene set predicted relapse-free, disease-specific, and overall survival in independent test data. In the presence of breast cancer heterogeneity, experimental and biologically-based methods for assessing gene expression in relation to p53 status provide prognostic and biologically-relevant gene lists. Our biologically-based refinements excluded genes

A feature selection approach for identification of signature genes from SAGE data

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Silva Paulo JS

2007-05-01

Full Text Available Abstract Background One goal of gene expression profiling is to identify signature genes that robustly distinguish different types or grades of tumors. Several tumor classifiers based on expression profiling have been proposed using microarray technique. Due to important differences in the probabilistic models of microarray and SAGE technologies, it is important to develop suitable techniques to select specific genes from SAGE measurements. Results A new framework to select specific genes that distinguish different biological states based on the analysis of SAGE data is proposed. The new framework applies the bolstered error for the identification of strong genes that separate the biological states in a feature space defined by the gene expression of a training set. Credibility intervals defined from a probabilistic model of SAGE measurements are used to identify the genes that distinguish the different states with more reliability among all gene groups selected by the strong genes method. A score taking into account the credibility and the bolstered error values in order to rank the groups of considered genes is proposed. Results obtained using SAGE data from gliomas are presented, thus corroborating the introduced methodology. Conclusion The model representing counting data, such as SAGE, provides additional statistical information that allows a more robust analysis. The additional statistical information provided by the probabilistic model is incorporated in the methodology described in the paper. The introduced method is suitable to identify signature genes that lead to a good separation of the biological states using SAGE and may be adapted for other counting methods such as Massive Parallel Signature Sequencing (MPSS or the recent Sequencing-By-Synthesis (SBS technique. Some of such genes identified by the proposed method may be useful to generate classifiers.

Gene expression in the urinary bladder: a common carcinoma in situ gene expression signature exists disregarding histopathological classification

DEFF Research Database (Denmark)

Andersen, Lars Dyrskjøt; Kruhøffer, Mogens; Andersen, Thomas Thykjær

2004-01-01

not only in CIS biopsies but also in sTCC, mTCC, and, remarkably, in histologically normal urothelium from bladders with CIS. Identification of this expression signature could provide guidance for the selection of therapy and follow-up regimen in patients with early stage bladder cancer....

Signature pathways identified from gene expression profiles in the human uterine cervix before and after spontaneous term parturition

Science.gov (United States)

HASSAN, Sonia S.; ROMERO, Roberto; TARCA, Adi L.; DRAGHICI, Sorin; PINELES, Beth; BUGRIM, Andrej; KHALEK, Nahla; CAMACHO, Natalia; MITTAL, Pooja; YOON, Bo Hyun; ESPINOZA, Jimmy; KIM, Chong Jai; SOROKIN, Yoram; MALONE, John

2008-01-01

Objective This study aimed to discover ‘signature pathways’ characterizing biological processes based on genes differentially expressed in the uterine cervix before and after spontaneous labor. Study Design The cervical transcriptome was previously characterized from biopsies taken before and after term labor. Pathway analysis was used to study the differentially expressed genes based on two gene-to-pathway annotation databases (KEGG and Metacore™). Over-represented and highly impacted pathways and connectivity nodes were identified. Results Fifty-two pathways in the Metacore™ database were significantly enriched in differentially expressed genes. Three of the top 5 pathways were known to be involved in cervical remodeling.Two novel pathways were: plasmin signaling and plasminogen activator urokinase (PLAU) signaling. The same analysis in the KEGG database identified 4 significant pathways, of which impact analysis confirmed. Multiple nodes providing connectivity within the plasmin and PLAU signaling pathways were identified.. Conclusions Three strategies for pathway analysis were consistent in their identification of novel, unexpected as well as expected networks, suggesting that this approach is both valid and effective for the elucidation of biological mechanisms involved in cervical dilation and remodeling. PMID:17826407

A 6-gene signature identifies four molecular subgroups of neuroblastoma

LENUS (Irish Health Repository)

Abel, Frida

2011-04-14

Abstract Background There are currently three postulated genomic subtypes of the childhood tumour neuroblastoma (NB); Type 1, Type 2A, and Type 2B. The most aggressive forms of NB are characterized by amplification of the oncogene MYCN (MNA) and low expression of the favourable marker NTRK1. Recently, mutations or high expression of the familial predisposition gene Anaplastic Lymphoma Kinase (ALK) was associated to unfavourable biology of sporadic NB. Also, various other genes have been linked to NB pathogenesis. Results The present study explores subgroup discrimination by gene expression profiling using three published microarray studies on NB (47 samples). Four distinct clusters were identified by Principal Components Analysis (PCA) in two separate data sets, which could be verified by an unsupervised hierarchical clustering in a third independent data set (101 NB samples) using a set of 74 discriminative genes. The expression signature of six NB-associated genes ALK, BIRC5, CCND1, MYCN, NTRK1, and PHOX2B, significantly discriminated the four clusters (p < 0.05, one-way ANOVA test). PCA clusters p1, p2, and p3 were found to correspond well to the postulated subtypes 1, 2A, and 2B, respectively. Remarkably, a fourth novel cluster was detected in all three independent data sets. This cluster comprised mainly 11q-deleted MNA-negative tumours with low expression of ALK, BIRC5, and PHOX2B, and was significantly associated with higher tumour stage, poor outcome and poor survival compared to the Type 1-corresponding favourable group (INSS stage 4 and\\/or dead of disease, p < 0.05, Fisher\\'s exact test). Conclusions Based on expression profiling we have identified four molecular subgroups of neuroblastoma, which can be distinguished by a 6-gene signature. The fourth subgroup has not been described elsewhere, and efforts are currently made to further investigate this group\\'s specific characteristics.

Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection

KAUST Repository

Dhavala, Soma S.

2010-09-01

Massively Parallel Signature Sequencing (MPSS) is a high-throughput, counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different strains of Salmonella obtained using the MPSS technology. In this article, we develop an exact ANOVA type model for this count data using a zero-inflatedPoisson distribution, different from existing methods that assume continuous densities. We adopt two Bayesian hierarchical models-one parametric and the other semiparametric with a Dirichlet process prior that has the ability to "borrow strength" across related signatures, where a signature is a specific arrangement of the nucleotides, usually 16-21 base pairs long. We utilize the discreteness of Dirichlet process prior to cluster signatures that exhibit similar differential expression profiles. Tests for differential expression are carried out using nonparametric approaches, while controlling the false discovery rate. We identify several differentially expressed genes that have important biological significance and conclude with a summary of the biological discoveries. This article has supplementary materials online. © 2010 American Statistical Association.

Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection

KAUST Repository

Dhavala, Soma S.; Datta, Sujay; Mallick, Bani K.; Carroll, Raymond J.; Khare, Sangeeta; Lawhon, Sara D.; Adams, L. Garry

2010-01-01

Massively Parallel Signature Sequencing (MPSS) is a high-throughput, counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different strains of Salmonella obtained using the MPSS technology. In this article, we develop an exact ANOVA type model for this count data using a zero-inflatedPoisson distribution, different from existing methods that assume continuous densities. We adopt two Bayesian hierarchical models-one parametric and the other semiparametric with a Dirichlet process prior that has the ability to "borrow strength" across related signatures, where a signature is a specific arrangement of the nucleotides, usually 16-21 base pairs long. We utilize the discreteness of Dirichlet process prior to cluster signatures that exhibit similar differential expression profiles. Tests for differential expression are carried out using nonparametric approaches, while controlling the false discovery rate. We identify several differentially expressed genes that have important biological significance and conclude with a summary of the biological discoveries. This article has supplementary materials online. © 2010 American Statistical Association.

Gene expression signatures that predict radiation exposure in mice and humans.

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Holly K Dressman

2007-04-01

Full Text Available The capacity to assess environmental inputs to biological phenotypes is limited by methods that can accurately and quantitatively measure these contributions. One such example can be seen in the context of exposure to ionizing radiation.We have made use of gene expression analysis of peripheral blood (PB mononuclear cells to develop expression profiles that accurately reflect prior radiation exposure. We demonstrate that expression profiles can be developed that not only predict radiation exposure in mice but also distinguish the level of radiation exposure, ranging from 50 cGy to 1,000 cGy. Likewise, a molecular signature of radiation response developed solely from irradiated human patient samples can predict and distinguish irradiated human PB samples from nonirradiated samples with an accuracy of 90%, sensitivity of 85%, and specificity of 94%. We further demonstrate that a radiation profile developed in the mouse can correctly distinguish PB samples from irradiated and nonirradiated human patients with an accuracy of 77%, sensitivity of 82%, and specificity of 75%. Taken together, these data demonstrate that molecular profiles can be generated that are highly predictive of different levels of radiation exposure in mice and humans.We suggest that this approach, with additional refinement, could provide a method to assess the effects of various environmental inputs into biological phenotypes as well as providing a more practical application of a rapid molecular screening test for the diagnosis of radiation exposure.

Cell-type independent MYC target genes reveal a primordial signature involved in biomass accumulation.

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Hongkai Ji

Full Text Available The functions of key oncogenic transcription factors independent of context have not been fully delineated despite our richer understanding of the genetic alterations in human cancers. The MYC oncogene, which produces the Myc transcription factor, is frequently altered in human cancer and is a major regulatory hub for many cancers. In this regard, we sought to unravel the primordial signature of Myc function by using high-throughput genomic approaches to identify the cell-type independent core Myc target gene signature. Using a model of human B lymphoma cells bearing inducible MYC, we identified a stringent set of direct Myc target genes via chromatin immunoprecipitation (ChIP, global nuclear run-on assay, and changes in mRNA levels. We also identified direct Myc targets in human embryonic stem cells (ESCs. We further document that a Myc core signature (MCS set of target genes is shared in mouse and human ESCs as well as in four other human cancer cell types. Remarkably, the expression of the MCS correlates with MYC expression in a cell-type independent manner across 8,129 microarray samples, which include 312 cell and tissue types. Furthermore, the expression of the MCS is elevated in vivo in Eμ-Myc transgenic murine lymphoma cells as compared with premalignant or normal B lymphocytes. Expression of the MCS in human B cell lymphomas, acute leukemia, lung cancers or Ewing sarcomas has the highest correlation with MYC expression. Annotation of this gene signature reveals Myc's primordial function in RNA processing, ribosome biogenesis and biomass accumulation as its key roles in cancer and stem cells.

GOBO: gene expression-based outcome for breast cancer online.

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Markus Ringnér

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.

ArrayVigil: a methodology for statistical comparison of gene signatures using segregated-one-tailed (SOT) Wilcoxon's signed-rank test.

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Khan, Haseeb Ahmad

2005-01-28

Due to versatile diagnostic and prognostic fidelity molecular signatures or fingerprints are anticipated as the most powerful tools for cancer management in the near future. Notwithstanding the experimental advancements in microarray technology, methods for analyzing either whole arrays or gene signatures have not been firmly established. Recently, an algorithm, ArraySolver has been reported by Khan for two-group comparison of microarray gene expression data using two-tailed Wilcoxon signed-rank test. Most of the molecular signatures are composed of two sets of genes (hybrid signatures) wherein up-regulation of one set and down-regulation of the other set collectively define the purpose of a gene signature. Since the direction of a selected gene's expression (positive or negative) with respect to a particular disease condition is known, application of one-tailed statistics could be a more relevant choice. A novel method, ArrayVigil, is described for comparing hybrid signatures using segregated-one-tailed (SOT) Wilcoxon signed-rank test and the results compared with integrated-two-tailed (ITT) procedures (SPSS and ArraySolver). ArrayVigil resulted in lower P values than those obtained from ITT statistics while comparing real data from four signatures.

Multi-platform whole-genome microarray analyses refine the epigenetic signature of breast cancer metastasis with gene expression and copy number.

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Joseph Andrews

2010-01-01

Full Text Available We have previously identified genome-wide DNA methylation changes in a cell line model of breast cancer metastasis. These complex epigenetic changes that we observed, along with concurrent karyotype analyses, have led us to hypothesize that complex genomic alterations in cancer cells (deletions, translocations and ploidy are superimposed over promoter-specific methylation events that are responsible for gene-specific expression changes observed in breast cancer metastasis.We undertook simultaneous high-resolution, whole-genome analyses of MDA-MB-468GFP and MDA-MB-468GFP-LN human breast cancer cell lines (an isogenic, paired lymphatic metastasis cell line model using Affymetrix gene expression (U133, promoter (1.0R, and SNP/CNV (SNP 6.0 microarray platforms to correlate data from gene expression, epigenetic (DNA methylation, and combination copy number variant/single nucleotide polymorphism microarrays. Using Partek Software and Ingenuity Pathway Analysis we integrated datasets from these three platforms and detected multiple hypomethylation and hypermethylation events. Many of these epigenetic alterations correlated with gene expression changes. In addition, gene dosage events correlated with the karyotypic differences observed between the cell lines and were reflected in specific promoter methylation patterns. Gene subsets were identified that correlated hyper (and hypo methylation with the loss (or gain of gene expression and in parallel, with gene dosage losses and gains, respectively. Individual gene targets from these subsets were also validated for their methylation, expression and copy number status, and susceptible gene pathways were identified that may indicate how selective advantage drives the processes of tumourigenesis and metastasis.Our approach allows more precisely profiling of functionally relevant epigenetic signatures that are associated with cancer progression and metastasis.

A five-gene hedgehog signature developed as a patient preselection tool for hedgehog inhibitor therapy in medulloblastoma.

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Shou, Yaping; Robinson, Douglas M; Amakye, Dereck D; Rose, Kristine L; Cho, Yoon-Jae; Ligon, Keith L; Sharp, Thad; Haider, Asifa S; Bandaru, Raj; Ando, Yuichi; Geoerger, Birgit; Doz, François; Ashley, David M; Hargrave, Darren R; Casanova, Michela; Tawbi, Hussein A; Rodon, Jordi; Thomas, Anne L; Mita, Alain C; MacDonald, Tobey J; Kieran, Mark W

2015-02-01

Distinct molecular subgroups of medulloblastoma, including hedgehog (Hh) pathway-activated disease, have been reported. We identified and clinically validated a five-gene Hh signature assay that can be used to preselect patients with Hh pathway-activated medulloblastoma. Gene characteristics of the Hh medulloblastoma subgroup were identified through published bioinformatic analyses. Thirty-two genes shown to be differentially expressed in fresh-frozen and formalin-fixed paraffin-embedded tumor samples and reproducibly analyzed by RT-PCR were measured in matched samples. These data formed the basis for building a multi-gene logistic regression model derived through elastic net methods from which the five-gene Hh signature emerged after multiple iterations. On the basis of signature gene expression levels, the model computed a propensity score to determine Hh activation using a threshold set a priori. The association between Hh activation status and tumor response to the Hh pathway inhibitor sonidegib (LDE225) was analyzed. Five differentially expressed genes in medulloblastoma (GLI1, SPHK1, SHROOM2, PDLIM3, and OTX2) were found to associate with Hh pathway activation status. In an independent validation study, Hh activation status of 25 medulloblastoma samples showed 100% concordance between the five-gene signature and Affymetrix profiling. Further, in medulloblastoma samples from 50 patients treated with sonidegib, all 6 patients who responded were found to have Hh-activated tumors. Three patients with Hh-activated tumors had stable or progressive disease. No patients with Hh-nonactivated tumors responded. This five-gene Hh signature can robustly identify Hh-activated medulloblastoma and may be used to preselect patients who might benefit from sonidegib treatment. ©2014 American Association for Cancer Research.

Gene expression variation to predict 10-year survival in lymph-node-negative breast cancer

International Nuclear Information System (INIS)

Karlsson, Elin; Delle, Ulla; Danielsson, Anna; Olsson, Björn; Abel, Frida; Karlsson, Per; Helou, Khalil

2008-01-01

It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used for evaluation of the gene lists, a correlation-based classifier and a Voting Features Interval (VFI) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients. They had both developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients may have benefited from different adjuvant treatment than they recieved. The research on these tumours was approved by the Medical Faculty Research

Glycosyltransferase Gene Expression Profiles Classify Cancer Types and Propose Prognostic Subtypes

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Ashkani, Jahanshah; Naidoo, Kevin J.

2016-05-01

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.

From big data to diagnosis and prognosis: gene expression signatures in liver hepatocellular carcinoma

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Hong Yang

2017-03-01

Full Text Available Background Liver hepatocellular carcinoma accounts for the overwhelming majority of primary liver cancers and its belated diagnosis and poor prognosis call for novel biomarkers to be discovered, which, in the era of big data, innovative bioinformatics and computational techniques can prove to be highly helpful in. Methods Big data aggregated from The Cancer Genome Atlas and Natural Language Processing were integrated to generate differentially expressed genes. Relevant signaling pathways of differentially expressed genes went through Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes and Panther pathway enrichment analysis and protein-protein interaction network. The pathway ranked high in the enrichment analysis was further investigated, and selected genes with top priority were evaluated and assessed in terms of their diagnostic and prognostic values. Results A list of 389 genes was generated by overlapping genes from The Cancer Genome Atlas and Natural Language Processing. Three pathways demonstrated top priorities, and the one with specific associations with cancers, ‘pathways in cancer,’ was analyzed with its four highlighted genes, namely, BIRC5, E2F1, CCNE1, and CDKN2A, which were validated using Oncomine. The detection pool composed of the four genes presented satisfactory diagnostic power with an outstanding integrated AUC of 0.990 (95% CI [0.982–0.998], P < 0.001, sensitivity: 96.0%, specificity: 96.5%. BIRC5 (P = 0.021 and CCNE1 (P = 0.027 were associated with poor prognosis, while CDKN2A (P = 0.066 and E2F1 (P = 0.088 demonstrated no statistically significant differences. Discussion The study illustrates liver hepatocellular carcinoma gene signatures, related pathways and networks from the perspective of big data, featuring the cancer-specific pathway with priority, ‘pathways in cancer.’ The detection pool of the four highlighted genes, namely BIRC5, E2F1, CCNE1 and CDKN2A, should be

Transcriptional profiling of whole blood identifies a unique 5-gene signature for myelofibrosis and imminent myelofibrosis transformation.

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Hans Carl Hasselbalch

Full Text Available Identifying a distinct gene signature for myelofibrosis may yield novel information of the genes, which are responsible for progression of essential thrombocythemia and polycythemia vera towards myelofibrosis. We aimed at identifying a simple gene signature - composed of a few genes - which were selectively and highly deregulated in myelofibrosis patients. Gene expression microarray studies have been performed on whole blood from 69 patients with myeloproliferative neoplasms. Amongst the top-20 of the most upregulated genes in PMF compared to controls, we identified 5 genes (DEFA4, ELA2, OLFM4, CTSG, and AZU1, which were highly significantly deregulated in PMF only. None of these genes were significantly regulated in ET and PV patients. However, hierarchical cluster analysis showed that these genes were also highly expressed in a subset of patients with ET (n = 1 and PV (n = 4 transforming towards myelofibrosis and/or being featured by an aggressive phenotype. We have identified a simple 5-gene signature, which is uniquely and highly significantly deregulated in patients in transitional stages of ET and PV towards myelofibrosis and in patients with PMF only. Some of these genes are considered to be responsible for the derangement of bone marrow stroma in myelofibrosis. Accordingly, this gene-signature may reflect key processes in the pathogenesis and pathophysiology of myelofibrosis development.

ColoLipidGene: signature of lipid metabolism-related genes to predict prognosis in stage-II colon cancer patients

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Vargas, Teodoro; Moreno-Rubio, Juan; Herranz, Jesús; Cejas, Paloma; Molina, Susana; González-Vallinas, Margarita; Mendiola, Marta; Burgos, Emilio; Aguayo, Cristina; Custodio, Ana B.; Machado, Isidro; Ramos, David; Gironella, Meritxell; Espinosa-Salinas, Isabel; Ramos, Ricardo; Martín-Hernández, Roberto; Risueño, Alberto; De Las Rivas, Javier; Reglero, Guillermo; Yaya, Ricardo; Fernández-Martos, Carlos; Aparicio, Jorge; Maurel, Joan; Feliu, Jaime; de Molina, Ana Ramírez

2015-01-01

Lipid metabolism plays an essential role in carcinogenesis due to the requirements of tumoral cells to sustain increased structural, energetic and biosynthetic precursor demands for cell proliferation. We investigated the association between expression of lipid metabolism-related genes and clinical outcome in intermediate-stage colon cancer patients with the aim of identifying a metabolic profile associated with greater malignancy and increased risk of relapse. Expression profile of 70 lipid metabolism-related genes was determined in 77 patients with stage II colon cancer. Cox regression analyses using c-index methodology was applied to identify a metabolic-related signature associated to prognosis. The metabolic signature was further confirmed in two independent validation sets of 120 patients and additionally, in a group of 264 patients from a public database. The combined analysis of these 4 genes, ABCA1, ACSL1, AGPAT1 and SCD, constitutes a metabolic-signature (ColoLipidGene) able to accurately stratify stage II colon cancer patients with 5-fold higher risk of relapse with strong statistical power in the four independent groups of patients. The identification of a group of 4 genes that predict survival in intermediate-stage colon cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy, and avoids the toxic and unnecessary chemotherapy in patients classified as low-risk group. PMID:25749516

Systematic assessment of prognostic gene signatures for breast cancer shows distinct influence of time and ER status

International Nuclear Information System (INIS)

Zhao, Xi; Rødland, Einar Andreas; Sørlie, Therese; Vollan, Hans Kristian Moen; Russnes, Hege G; Kristensen, Vessela N; Lingjærde, Ole Christian; Børresen-Dale, Anne-Lise

2014-01-01

The aim was to assess and compare prognostic power of nine breast cancer gene signatures (Intrinsic, PAM50, 70-gene, 76-gene, Genomic-Grade-Index, 21-gene-Recurrence-Score, EndoPredict, Wound-Response and Hypoxia) in relation to ER status and follow-up time. A gene expression dataset from 947 breast tumors was used to evaluate the signatures for prediction of Distant Metastasis Free Survival (DMFS). A total of 912 patients had available DMFS status. The recently published METABRIC cohort was used as an additional validation set. Survival predictions were fairly concordant across most signatures. Prognostic power declined with follow-up time. During the first 5 years of followup, all signatures except for Hypoxia were predictive for DMFS in ER-positive disease, and 76-gene, Hypoxia and Wound-Response were prognostic in ER-negative disease. After 5 years, the signatures had little prognostic power. Gene signatures provide significant prognostic information beyond tumor size, node status and histological grade. Generally, these signatures performed better for ER-positive disease, indicating that risk within each ER stratum is driven by distinct underlying biology. Most of the signatures were strong risk predictors for DMFS during the first 5 years of follow-up. Combining gene signatures with histological grade or tumor size, could improve the prognostic power, perhaps also of long-term survival

Determinants of human adipose tissue gene expression

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Viguerie, Nathalie; Montastier, Emilie; Maoret, Jean-José

2012-01-01

weight maintenance diets. For 175 genes, opposite regulation was observed during calorie restriction and weight maintenance phases, independently of variations in body weight. Metabolism and immunity genes showed inverse profiles. During the dietary intervention, network-based analyses revealed strong...... interconnection between expression of genes involved in de novo lipogenesis and components of the metabolic syndrome. Sex had a marked influence on AT expression of 88 transcripts, which persisted during the entire dietary intervention and after control for fat mass. In women, the influence of body mass index...... on expression of a subset of genes persisted during the dietary intervention. Twenty-two genes revealed a metabolic syndrome signature common to men and women. Genetic control of AT gene expression by cis signals was observed for 46 genes. Dietary intervention, sex, and cis genetic variants independently...

University of Texas Southwestern Medical Center: Functional Signature Ontology Tool: Triplicate Measurements of Reporter Gene Expression in Response to Individual Genetic and Chemical Perturbations in HCT116 Cells | Office of Cancer Genomics

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The goal of this project is to use an eight-gene expression profile to define functional signatures for small molecules and natural products with heretofore undefined mechanism of action. Two genes in the eight gene set are used as internal controls and do not vary across gene expression array data collected from the public domain. The remaining six genes are found to vary independently across a large collection of publically available gene expression array datasets.  Read the abstract

Analysis of multiplex gene expression maps obtained by voxelation

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An, L; Xie, H; Chin, MH; Obradovic, Z; Smith, DJ; Megalooikonomou, V

2009-01-01

Abstract Background Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we presen...

A prognostic gene signature for metastasis-free survival of triple negative breast cancer patients.

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Lee, Unjin; Frankenberger, Casey; Yun, Jieun; Bevilacqua, Elena; Caldas, Carlos; Chin, Suet-Feung; Rueda, Oscar M; Reinitz, John; Rosner, Marsha Rich

2013-01-01

Although triple negative breast cancers (TNBC) are the most aggressive subtype of breast cancer, they currently lack targeted therapies. Because this classification still includes a heterogeneous collection of tumors, new tools to classify TNBCs are urgently required in order to improve our prognostic capability for high risk patients and predict response to therapy. We previously defined a gene expression signature, RKIP Pathway Metastasis Signature (RPMS), based upon a metastasis-suppressive signaling pathway initiated by Raf Kinase Inhibitory Protein (RKIP). We have now generated a new BACH1 Pathway Metastasis gene signature (BPMS) that utilizes targets of the metastasis regulator BACH1. Specifically, we substituted experimentally validated target genes to generate a new BACH1 metagene, developed an approach to optimize patient tumor stratification, and reduced the number of signature genes to 30. The BPMS significantly and selectively stratified metastasis-free survival in basal-like and, in particular, TNBC patients. In addition, the BPMS further stratified patients identified as having a good or poor prognosis by other signatures including the Mammaprint® and Oncotype® clinical tests. The BPMS is thus complementary to existing signatures and is a prognostic tool for high risk ER-HER2- patients. We also demonstrate the potential clinical applicability of the BPMS as a single sample predictor. Together, these results reveal the potential of this pathway-based BPMS gene signature to identify high risk TNBC patients that can respond effectively to targeted therapy, and highlight BPMS genes as novel drug targets for therapeutic development.

A prognostic gene signature for metastasis-free survival of triple negative breast cancer patients.

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Unjin Lee

Full Text Available Although triple negative breast cancers (TNBC are the most aggressive subtype of breast cancer, they currently lack targeted therapies. Because this classification still includes a heterogeneous collection of tumors, new tools to classify TNBCs are urgently required in order to improve our prognostic capability for high risk patients and predict response to therapy. We previously defined a gene expression signature, RKIP Pathway Metastasis Signature (RPMS, based upon a metastasis-suppressive signaling pathway initiated by Raf Kinase Inhibitory Protein (RKIP. We have now generated a new BACH1 Pathway Metastasis gene signature (BPMS that utilizes targets of the metastasis regulator BACH1. Specifically, we substituted experimentally validated target genes to generate a new BACH1 metagene, developed an approach to optimize patient tumor stratification, and reduced the number of signature genes to 30. The BPMS significantly and selectively stratified metastasis-free survival in basal-like and, in particular, TNBC patients. In addition, the BPMS further stratified patients identified as having a good or poor prognosis by other signatures including the Mammaprint® and Oncotype® clinical tests. The BPMS is thus complementary to existing signatures and is a prognostic tool for high risk ER-HER2- patients. We also demonstrate the potential clinical applicability of the BPMS as a single sample predictor. Together, these results reveal the potential of this pathway-based BPMS gene signature to identify high risk TNBC patients that can respond effectively to targeted therapy, and highlight BPMS genes as novel drug targets for therapeutic development.

University of Texas Southwestern Medical Center (UTSW): Functional Signature Ontology Tool: Triplicate Measurements of Reporter Gene Expression in Response to Individual Genetic and Chemical Perturbations in HCT116 Cells | Office of Cancer Genomics

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The goal of this project is to use an eight-gene expression profile to define functional signatures for small molecules and natural products with heretofore undefined mechanism of action. Two genes in the eight gene set are used as internal controls and do not vary across gene expression array data collected from the public domain. The remaining six genes are found to vary independently across a large collection of publically available gene expression array datasets.  Read the abstract

Ensemble of gene signatures identifies novel biomarkers in colorectal cancer activated through PPARγ and TNFα signaling.

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Stefano Maria Pagnotta

Full Text Available We describe a novel bioinformatic and translational pathology approach, gene Signature Finder Algorithm (gSFA to identify biomarkers associated with Colorectal Cancer (CRC survival. Here a robust set of CRC markers is selected by an ensemble method. By using a dataset of 232 gene expression profiles, gSFA discovers 16 highly significant small gene signatures. Analysis of dichotomies generated by the signatures results in a set of 133 samples stably classified in good prognosis group and 56 samples in poor prognosis group, whereas 43 remain unreliably classified. AKAP12, DCBLD2, NT5E and SPON1 are particularly represented in the signatures and selected for validation in vivo on two independent patients cohorts comprising 140 tumor tissues and 60 matched normal tissues. Their expression and regulatory programs are investigated in vitro. We show that the coupled expression of NT5E and DCBLD2 robustly stratifies our patients in two groups (one of which with 100% survival at five years. We show that NT5E is a target of the TNF-α signaling in vitro; the tumor suppressor PPARγ acts as a novel NT5E antagonist that positively and concomitantly regulates DCBLD2 in a cancer cell context-dependent manner.

A six-gene signature predicts survival of patients with localized pancreatic ductal adenocarcinoma.

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Jeran K Stratford

2010-07-01

Full Text Available Pancreatic ductal adenocarcinoma (PDAC remains a lethal disease. For patients with localized PDAC, surgery is the best option, but with a median survival of less than 2 years and a difficult and prolonged postoperative course for most, there is an urgent need to better identify patients who have the most aggressive disease.We analyzed the gene expression profiles of primary tumors from patients with localized compared to metastatic disease and identified a six-gene signature associated with metastatic disease. We evaluated the prognostic potential of this signature in a training set of 34 patients with localized and resected PDAC and selected a cut-point associated with outcome using X-tile. We then applied this cut-point to an independent test set of 67 patients with localized and resected PDAC and found that our signature was independently predictive of survival and superior to established clinical prognostic factors such as grade, tumor size, and nodal status, with a hazard ratio of 4.1 (95% confidence interval [CI] 1.7-10.0. Patients defined to be high-risk patients by the six-gene signature had a 1-year survival rate of 55% compared to 91% in the low-risk group.Our six-gene signature may be used to better stage PDAC patients and assist in the difficult treatment decisions of surgery and to select patients whose tumor biology may benefit most from neoadjuvant therapy. The use of this six-gene signature should be investigated in prospective patient cohorts, and if confirmed, in future PDAC clinical trials, its potential as a biomarker should be investigated. Genes in this signature, or the pathways that they fall into, may represent new therapeutic targets. Please see later in the article for the Editors' Summary.

A core invasiveness gene signature reflects epithelial-to-mesenchymal transition but not metastatic potential in breast cancer cell lines and tissue samples.

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Melike Marsan

Full Text Available INTRODUCTION: Metastases remain the primary cause of cancer-related death. The acquisition of invasive tumour cell behaviour is thought to be a cornerstone of the metastatic cascade. Therefore, gene signatures related to invasiveness could aid in stratifying patients according to their prognostic profile. In the present study we aimed at identifying an invasiveness gene signature and investigated its biological relevance in breast cancer. METHODS & RESULTS: We collected a set of published gene signatures related to cell motility and invasion. Using this collection, we identified 16 genes that were represented at a higher frequency than observed by coincidence, hereafter named the core invasiveness gene signature. Principal component analysis showed that these overrepresented genes were able to segregate invasive and non-invasive breast cancer cell lines, outperforming sets of 16 randomly selected genes (all P<0.001. When applied onto additional data sets, the expression of the core invasiveness gene signature was significantly elevated in cell lines forced to undergo epithelial-mesenchymal transition. The link between core invasiveness gene expression and epithelial-mesenchymal transition was also confirmed in a dataset consisting of 2420 human breast cancer samples. Univariate and multivariate Cox regression analysis demonstrated that CIG expression is not associated with a shorter distant metastasis free survival interval (HR = 0.956, 95%C.I. = 0.896-1.019, P = 0.186. DISCUSSION: These data demonstrate that we have identified a set of core invasiveness genes, the expression of which is associated with epithelial-mesenchymal transition in breast cancer cell lines and in human tissue samples. Despite the connection between epithelial-mesenchymal transition and invasive tumour cell behaviour, we were unable to demonstrate a link between the core invasiveness gene signature and enhanced metastatic potential.

Single-gene prognostic signatures for advanced stage serous ovarian cancer based on 1257 patient samples.

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Zhang, Fan; Yang, Kai; Deng, Kui; Zhang, Yuanyuan; Zhao, Weiwei; Xu, Huan; Rong, Zhiwei; Li, Kang

2018-04-16

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.

A high resolution atlas of gene expression in the domestic sheep (Ovis aries).

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Clark, Emily L; Bush, Stephen J; McCulloch, Mary E B; Farquhar, Iseabail L; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G; Wu, Chunlei; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C Bruce; Freeman, Tom C; Summers, Kim M; Archibald, Alan L; Hume, David A

2017-09-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

Gene expression profiles of lung adenocarcinoma linked to histopathological grading and survival but not to EGF-R status: a microarray study

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Passlick Bernward

2010-03-01

Full Text Available Abstract Background Several different gene expression signatures have been proposed to predict response to therapy and clinical outcome in lung adenocarcinoma. Herein, we investigate if elements of published gene sets can be reproduced in a small dataset, and how gene expression profiles based on limited sample size relate to clinical parameters including histopathological grade and EGFR protein expression. Methods Affymetrix Human Genome U133A platform was used to obtain gene expression profiles of 28 pathologically and clinically annotated adenocarcinomas of the lung. EGFR status was determined by fluorescent in situ hybridization and immunohistochemistry. Results Using unsupervised clustering algorithms, the predominant gene expression signatures correlated with the histopathological grade but not with EGFR protein expression as detected by immunohistochemistry. In a supervised analysis, the signature of high grade tumors but not of EGFR overexpressing cases showed significant enrichment of gene sets reflecting MAPK activation and other potential signaling cascades downstream of EGFR. Out of four different previously published gene sets that had been linked to prognosis, three showed enrichment in the gene expression signature associated with favorable prognosis. Conclusions In this dataset, histopathological tumor grades but not EGFR status were associated with dominant gene expression signatures and gene set enrichment reflecting oncogenic pathway activation, suggesting that high immunohistochemistry EGFR scores may not necessarily be linked to downstream effects that cause major changes in gene expression patterns. Published gene sets showed association with patient survival; however, the small sample size of this study limited the options for a comprehensive validation of previously reported prognostic gene expression signatures.

Angiogenic Gene Signature Derived from Subtype Specific Cell Models Segregate Proneural and Mesenchymal Glioblastoma

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Aman Sharma

2017-07-01

Full Text Available Intertumoral molecular heterogeneity in glioblastoma identifies four major subtypes based on expression of molecular markers. Among them, the two clinically interrelated subtypes, proneural and mesenchymal, are the most aggressive with proneural liable for conversion to mesenchymal upon therapy. Using two patient-derived novel primary cell culture models (MTA10 and KW10, we developed a minimal but unique four-gene signature comprising genes vascular endothelial growth factor A (VEGF-A, vascular endothelial growth factor B (VEGF-B and angiopoietin 1 (ANG1, angiopoietin 2 (ANG2 that effectively segregated the proneural (MTA10 and mesenchymal (KW10 glioblastoma subtypes. The cell culture preclassified as mesenchymal showed elevated expression of genes VEGF-A, VEGF-B and ANG1, ANG2 as compared to the other cell culture model that mimicked the proneural subtype. The differentially expressed genes in these two cell culture models were confirmed by us using TCGA and Verhaak databases and we refer to it as a minimal multigene signature (MMS. We validated this MMS on human glioblastoma tissue sections with the use of immunohistochemistry on preclassified (YKL-40 high or mesenchymal glioblastoma and OLIG2 high or proneural glioblastoma tumor samples (n = 30. MMS segregated mesenchymal and proneural subtypes with 83% efficiency using a simple histopathology scoring approach (p = 0.008 for ANG2 and p = 0.01 for ANG1. Furthermore, MMS expression negatively correlated with patient survival. Importantly, MMS staining demonstrated spatiotemporal heterogeneity within each subclass, adding further complexity to subtype identification in glioblastoma. In conclusion, we report a novel and simple sequencing-independent histopathology-based biomarker signature comprising genes VEGF-A, VEGF-B and ANG1, ANG2 for subtyping of proneural and mesenchymal glioblastoma.

A robust prognostic gene expression signature for early stage lung adenocarcinoma

DEFF Research Database (Denmark)

Krzystanek, Marcin; Moldvay, Judit; Szüts, David

2016-01-01

Stage I lung adenocarcinoma is usually not treated with adjuvant chemotherapy; however, around half of these patients do not survive 5 years. Therefore, a reliable prognostic biomarker for early stage patients would be critical to identify those most likely to benefit from early additional treatm...... not given adjuvant therapy. Seven genes consistently obtained statistical significance in Cox regression for overall survival. The combined signature has a weighted mean hazard ratio of 3.2 in all cohorts and 3.0 (C.I. 1.3-7.4, p ...

Gene expression-signature of belinostat in cell lines is specific for histone deacetylase inhibitor treatment, with a corresponding signature in xenografts

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Monks, A.; Hose, C.D.; Pezzoli, P.

2009-01-01

gene modulation were significantly correlated. A belinostat-gene profile was specific for HDACi in three cell lines when compared with equipotent concentrations of four mechanistically different chemotherapeutic agents: 5-fluorouracil, cisplatin, paclitaxel, and thiotepa. Belinostat- and trichostatin...... in a drug-sensitive tumor than a more resistant model. We have demonstrated a gene signature that is selectively regulated by HDACi when compared with other clinical agents allowing us to distinguish HDACi responses from those related to other mechanisms Udgivelsesdato: 2009/9...

Tumor Microenvironment Gene Signature as a Prognostic Classifier and Therapeutic Target

Science.gov (United States)

2016-06-01

AWARD NUMBER: W81XWH-14-1-0107 TITLE: Tumor Microenvironment Gene Signature as a Prognostic Classifier and Therapeutic Target PRINCIPAL...AND SUBTITLE Tumor Microenvironment Gene Signature as a 5a. CONTRACT NUMBER W81XWH-14-1-0107 Prognostic Classifier and Therapeutic Target 5b...gene signature that correlates with poor survival in ovarian cancer patients. We are refining this gene signature to develop biomarkers for the

Muscle myeloid type I interferon gene expression may predict therapeutic responses to rituximab in myositis patients.

Science.gov (United States)

Nagaraju, Kanneboyina; Ghimbovschi, Svetlana; Rayavarapu, Sree; Phadke, Aditi; Rider, Lisa G; Hoffman, Eric P; Miller, Frederick W

2016-09-01

To identify muscle gene expression patterns that predict rituximab responses and assess the effects of rituximab on muscle gene expression in PM and DM. In an attempt to understand the molecular mechanism of response and non-response to rituximab therapy, we performed Affymetrix gene expression array analyses on muscle biopsy specimens taken before and after rituximab therapy from eight PM and two DM patients in the Rituximab in Myositis study. We also analysed selected muscle-infiltrating cell phenotypes in these biopsies by immunohistochemical staining. Partek and Ingenuity pathway analyses assessed the gene pathways and networks. Myeloid type I IFN signature genes were expressed at higher levels at baseline in the skeletal muscle of rituximab responders than in non-responders, whereas classic non-myeloid IFN signature genes were expressed at higher levels in non-responders at baseline. Also, rituximab responders have a greater reduction of the myeloid and non-myeloid type I IFN signatures than non-responders. The decrease in the type I IFN signature following administration of rituximab may be associated with the decreases in muscle-infiltrating CD19(+) B cells and CD68(+) macrophages in responders. Our findings suggest that high levels of myeloid type I IFN gene expression in skeletal muscle predict responses to rituximab in PM/DM and that rituximab responders also have a greater decrease in the expression of these genes. These data add further evidence to recent studies defining the type I IFN signature as both a predictor of therapeutic responses and a biomarker of myositis disease activity. Published by Oxford University Press on behalf British Society for Rheumatology 2016. This work is written by US Government employees and is in the public domain in the US.

Identifying potential maternal genes of Bombyx mori using digital gene expression profiling

Science.gov (United States)

Xu, Pingzhen

2018-01-01

Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of gene expression. The expressed genes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital gene expression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

A distinguishing gene signature shared by tumor-infiltrating Tie2-expressing monocytes, blood "resident" monocytes, and embryonic macrophages suggests common functions and developmental relationships.

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Pucci, Ferdinando; Venneri, Mary Anna; Biziato, Daniela; Nonis, Alessandro; Moi, Davide; Sica, Antonio; Di Serio, Clelia; Naldini, Luigi; De Palma, Michele

2009-07-23

We previously showed that Tie2-expressing monocytes (TEMs) have nonredundant proangiogenic activity in tumors. Here, we compared the gene expression profile of tumor-infiltrating TEMs with that of tumor-associated macrophages (TAMs), spleen-derived Gr1(+)Cd11b(+) neutrophils/myeloid-derived suppressor cells, circulating "inflammatory" and "resident" monocytes, and tumor-derived endothelial cells (ECs) by quantitative polymerase chain reaction-based gene arrays. TEMs sharply differed from ECs and Gr1(+)Cd11b(+) cells but were highly related to TAMs. Nevertheless, several genes were differentially expressed between TEMs and TAMs, highlighting a TEM signature consistent with enhanced proangiogenic/tissue-remodeling activity and lower proinflammatory activity. We validated these findings in models of oncogenesis and transgenic mice expressing a microRNA-regulated Tie2-GFP reporter. Remarkably, resident monocytes and TEMs on one hand, and inflammatory monocytes and TAMs on the other hand, expressed coordinated gene expression profiles, suggesting that the 2 blood monocyte subsets are committed to distinct extravascular fates in the tumor microenvironment. We further showed that a prominent proportion of embryonic/fetal macrophages, which participate in tissue morphogenesis, expressed distinguishing TEM genes. It is tempting to speculate that Tie2(+) embryonic/fetal macrophages, resident blood monocytes, and tumor-infiltrating TEMs represent distinct developmental stages of a TEM lineage committed to execute physiologic proangiogenic and tissue-remodeling programs, which can be co-opted by tumors.

A gene expression signature of confinement in peripheral blood of red wolves (Canis rufus).

Science.gov (United States)

Kennerly, Erin; Ballmann, Anne; Martin, Stanton; Wolfinger, Russ; Gregory, Simon; Stoskopf, Michael; Gibson, Greg

2008-06-01

The stresses that animals experience as a result of modification of their ecological circumstances induce physiological changes that leave a signature in profiles of gene expression. We illustrate this concept in a comparison of free range and confined North American red wolves (Canis rufus). Transcription profiling of peripheral blood samples from 13 red wolf individuals in the Alligator River region of North Carolina revealed a strong signal of differentiation. Four hundred eighty-two out of 2980 transcripts detected on Illumina HumanRef8 oligonucleotide bead arrays were found to differentiate free range and confined wolves at a false discovery rate of 12.8% and P stress responses in confined animals. Consequently, characterization of differential transcript abundance in an accessible tissue such as peripheral blood identifies biomarkers that could be useful in animal management practices and for evaluating the impact of habitat changes on population health, particularly as attention turns to the impact of climate change on physiology and in turn species distributions.

Bronchial airway gene expression in smokers with lung or head and neck cancer

International Nuclear Information System (INIS)

Van Dyck, Eric; Nazarov, Petr V; Muller, Arnaud; Nicot, Nathalie; Bosseler, Manon; Pierson, Sandrine; Van Moer, Kris; Palissot, Valérie; Mascaux, Céline; Knolle, Ulrich; Ninane, Vincent; Nati, Romain; Bremnes, Roy M; Vallar, Laurent; Berchem, Guy; Schlesser, Marc

2014-01-01

Cigarette smoking is the major cause of cancers of the respiratory tract, including non-small cell lung cancer (NSCLC) and head and neck cancer (HNC). In order to better understand carcinogenesis of the lung and upper airways, we have compared the gene expression profiles of tumor-distant, histologically normal bronchial biopsy specimens obtained from current smokers with NSCLC or HNC (SC, considered as a single group), as well as nonsmokers (NS) and smokers without cancer (SNC). RNA from a total of 97 biopsies was used for gene expression profiling (Affymetrix HG-U133 Plus 2.0 array). Differentially expressed genes were used to compare NS, SNC, and SC, and functional analysis was carried out using Ingenuity Pathway Analysis (IPA). Smoking-related cancer of the respiratory tract was found to affect the expression of genes encoding xenobiotic biotransformation proteins, as well as proteins associated with crucial inflammation/immunity pathways and other processes that protect the airway from the chemicals in cigarette smoke or contribute to carcinogenesis. Finally, we used the prediction analysis for microarray (PAM) method to identify gene signatures of cigarette smoking and cancer, and uncovered a 15-gene signature that distinguished between SNC and SC with an accuracy of 83%. Thus, gene profiling of histologically normal bronchial biopsy specimens provided insight into cigarette-induced carcinogenesis of the respiratory tract and gene signatures of cancer in smokers

An expression meta-analysis of predicted microRNA targets identifies a diagnostic signature for lung cancer

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Liang Yu

2008-12-01

Full Text Available Abstract Background Patients diagnosed with lung adenocarcinoma (AD and squamous cell carcinoma (SCC, two major histologic subtypes of lung cancer, currently receive similar standard treatments, but resistance to adjuvant chemotherapy is prevalent. Identification of differentially expressed genes marking AD and SCC may prove to be of diagnostic value and help unravel molecular basis of their histogenesis and biologies, and deliver more effective and specific systemic therapy. Methods MiRNA target genes were predicted by union of miRanda, TargetScan, and PicTar, followed by screening for matched gene symbols in NCBI human sequences and Gene Ontology (GO terms using the PANTHER database that was also used for analyzing the significance of biological processes and pathways within each ontology term. Microarray data were extracted from Gene Expression Omnibus repository, and tumor subtype prediction by gene expression used Prediction Analysis of Microarrays. Results Computationally predicted target genes of three microRNAs, miR-34b/34c/449, that were detected in human lung, testis, and fallopian tubes but not in other normal tissues, were filtered by representation of GO terms and their ability to classify lung cancer subtypes, followed by a meta-analysis of microarray data to classify AD and SCC. Expression of a minimal set of 17 predicted miR-34b/34c/449 target genes derived from the developmental process GO category was identified from a training set to classify 41 AD and 17 SCC, and correctly predicted in average 87% of 354 AD and 82% of 282 SCC specimens from total 9 independent published datasets. The accuracy of prediction still remains comparable when classifying 103 AD and 79 SCC samples from another 4 published datasets that have only 14 to 16 of the 17 genes available for prediction (84% and 85% for AD and SCC, respectively. Expression of this signature in two published datasets of epithelial cells obtained at bronchoscopy from cigarette

Transcriptomic analysis in the developing zebrafish embryo after compound exposure: Individual gene expression and pathway regulation

Energy Technology Data Exchange (ETDEWEB)

Hermsen, Sanne A.B., E-mail: Sanne.Hermsen@rivm.nl [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands); Pronk, Tessa E. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Department of Toxicogenomics, Maastricht University, P.O. Box 616, 6200 MD, Maastricht (Netherlands); Brandhof, Evert-Jan van den [Centre for Environmental Quality, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Ven, Leo T.M. van der [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Piersma, Aldert H. [Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven (Netherlands); Institute for Risk Assessment Sciences (IRAS), Utrecht University, P.O. Box 80.178, 3508 TD, Utrecht (Netherlands)

2013-10-01

The zebrafish embryotoxicity test is a promising alternative assay for developmental toxicity. Classically, morphological assessment of the embryos is applied to evaluate the effects of compound exposure. However, by applying differential gene expression analysis the sensitivity and predictability of the test may be increased. For defining gene expression signatures of developmental toxicity, we explored the possibility of using gene expression signatures of compound exposures based on commonly expressed individual genes as well as based on regulated gene pathways. Four developmental toxic compounds were tested in concentration-response design, caffeine, carbamazepine, retinoic acid and valproic acid, and two non-embryotoxic compounds, D-mannitol and saccharin, were included. With transcriptomic analyses we were able to identify commonly expressed genes, which were mostly development related, after exposure to the embryotoxicants. We also identified gene pathways regulated by the embryotoxicants, suggestive of their modes of action. Furthermore, whereas pathways may be regulated by all compounds, individual gene expression within these pathways can differ for each compound. Overall, the present study suggests that the use of individual gene expression signatures as well as pathway regulation may be useful starting points for defining gene biomarkers for predicting embryotoxicity. - Highlights: • The zebrafish embryotoxicity test in combination with transcriptomics was used. • We explored two approaches of defining gene biomarkers for developmental toxicity. • Four compounds in concentration-response design were tested. • We identified commonly expressed individual genes as well as regulated gene pathways. • Both approaches seem suitable starting points for defining gene biomarkers.

Long non-coding RNAs as novel expression signatures modulate DNA damage and repair in cadmium toxicology

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Zhou, Zhiheng; Liu, Haibai; Wang, Caixia; Lu, Qian; Huang, Qinhai; Zheng, Chanjiao; Lei, Yixiong

2015-10-01

Increasing evidence suggests that long non-coding RNAs (lncRNAs) are involved in a variety of physiological and pathophysiological processes. Our study was to investigate whether lncRNAs as novel expression signatures are able to modulate DNA damage and repair in cadmium(Cd) toxicity. There were aberrant expression profiles of lncRNAs in 35th Cd-induced cells as compared to untreated 16HBE cells. siRNA-mediated knockdown of ENST00000414355 inhibited the growth of DNA-damaged cells and decreased the expressions of DNA-damage related genes (ATM, ATR and ATRIP), while increased the expressions of DNA-repair related genes (DDB1, DDB2, OGG1, ERCC1, MSH2, RAD50, XRCC1 and BARD1). Cadmium increased ENST00000414355 expression in the lung of Cd-exposed rats in a dose-dependent manner. A significant positive correlation was observed between blood ENST00000414355 expression and urinary/blood Cd concentrations, and there were significant correlations of lncRNA-ENST00000414355 expression with the expressions of target genes in the lung of Cd-exposed rats and the blood of Cd exposed workers. These results indicate that some lncRNAs are aberrantly expressed in Cd-treated 16HBE cells. lncRNA-ENST00000414355 may serve as a signature for DNA damage and repair related to the epigenetic mechanisms underlying the cadmium toxicity and become a novel biomarker of cadmium toxicity.

A gene expression signature associated with survival in metastatic melanoma

Science.gov (United States)

Mandruzzato, Susanna; Callegaro, Andrea; Turcatel, Gianluca; Francescato, Samuela; Montesco, Maria C; Chiarion-Sileni, Vanna; Mocellin, Simone; Rossi, Carlo R; Bicciato, Silvio; Wang, Ena; Marincola, Francesco M; Zanovello, Paola

2006-01-01

Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells. PMID:17129373

A gene expression signature associated with survival in metastatic melanoma

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Rossi Carlo R

2006-11-01

Full Text Available Abstract Background Current clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival. Methods Forty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM to identify genes associated with patient survival, and supervised principal components (SPC to determine survival prediction. Results SAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival. Conclusion The longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells.

Astrocyte-specific overexpressed gene signatures in response to methamphetamine exposure in vitro

KAUST Repository

Bortell, Nikki; Basova, Liana; Semenova, Svetlana; Fox, Howard S.; Ravasi, Timothy; Marcondes, Maria Cecilia G.

2017-01-01

BackgroundAstrocyte activation is one of the earliest findings in the brain of methamphetamine (Meth) abusers. Our goal in this study was to identify the characteristics of the astrocytic acute response to the drug, which may be critical in pathogenic outcomes secondary to the use.MethodsWe developed an integrated analysis of gene expression data to study the acute gene changes caused by the direct exposure to Meth treatment of astrocytes in vitro, and to better understand how astrocytes respond, what are the early molecular markers associated with this response. We examined the literature in search of similar changes in gene signatures that are found in central nervous system disorders.ResultsWe identified overexpressed gene networks represented by genes of an inflammatory and immune nature and that are implicated in neuroactive ligand-receptor interactions. The overexpressed networks are linked to molecules that were highly upregulated in astrocytes by all doses of methamphetamine tested and that could play a role in the central nervous system. The strongest overexpressed signatures were the upregulation of MAP2K5, GPR65, and CXCL5, and the gene networks individually associated with these molecules. Pathway analysis revealed that these networks are involved both in neuroprotection and in neuropathology. We have validated several targets associated to these genes.ConclusionsGene signatures for the astrocytic response to Meth were identified among the upregulated gene pool, using an in vitro system. The identified markers may participate in dysfunctions of the central nervous system but could also provide acute protection to the drug exposure. Further in vivo studies are necessary to establish the role of these gene networks in drug abuse pathogenesis.

Astrocyte-specific overexpressed gene signatures in response to methamphetamine exposure in vitro

KAUST Repository

Bortell, Nikki

2017-03-09

BackgroundAstrocyte activation is one of the earliest findings in the brain of methamphetamine (Meth) abusers. Our goal in this study was to identify the characteristics of the astrocytic acute response to the drug, which may be critical in pathogenic outcomes secondary to the use.MethodsWe developed an integrated analysis of gene expression data to study the acute gene changes caused by the direct exposure to Meth treatment of astrocytes in vitro, and to better understand how astrocytes respond, what are the early molecular markers associated with this response. We examined the literature in search of similar changes in gene signatures that are found in central nervous system disorders.ResultsWe identified overexpressed gene networks represented by genes of an inflammatory and immune nature and that are implicated in neuroactive ligand-receptor interactions. The overexpressed networks are linked to molecules that were highly upregulated in astrocytes by all doses of methamphetamine tested and that could play a role in the central nervous system. The strongest overexpressed signatures were the upregulation of MAP2K5, GPR65, and CXCL5, and the gene networks individually associated with these molecules. Pathway analysis revealed that these networks are involved both in neuroprotection and in neuropathology. We have validated several targets associated to these genes.ConclusionsGene signatures for the astrocytic response to Meth were identified among the upregulated gene pool, using an in vitro system. The identified markers may participate in dysfunctions of the central nervous system but could also provide acute protection to the drug exposure. Further in vivo studies are necessary to establish the role of these gene networks in drug abuse pathogenesis.

PhysioSpace: relating gene expression experiments from heterogeneous sources using shared physiological processes.

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Michael Lenz

Full Text Available Relating expression signatures from different sources such as cell lines, in vitro cultures from primary cells and biopsy material is an important task in drug development and translational medicine as well as for tracking of cell fate and disease progression. Especially the comparison of large scale gene expression changes to tissue or cell type specific signatures is of high interest for the tracking of cell fate in (trans- differentiation experiments and for cancer research, which increasingly focuses on shared processes and the involvement of the microenvironment. These signature relation approaches require robust statistical methods to account for the high biological heterogeneity in clinical data and must cope with small sample sizes in lab experiments and common patterns of co-expression in ubiquitous cellular processes. We describe a novel method, called PhysioSpace, to position dynamics of time series data derived from cellular differentiation and disease progression in a genome-wide expression space. The PhysioSpace is defined by a compendium of publicly available gene expression signatures representing a large set of biological phenotypes. The mapping of gene expression changes onto the PhysioSpace leads to a robust ranking of physiologically relevant signatures, as rigorously evaluated via sample-label permutations. A spherical transformation of the data improves the performance, leading to stable results even in case of small sample sizes. Using PhysioSpace with clinical cancer datasets reveals that such data exhibits large heterogeneity in the number of significant signature associations. This behavior was closely associated with the classification endpoint and cancer type under consideration, indicating shared biological functionalities in disease associated processes. Even though the time series data of cell line differentiation exhibited responses in larger clusters covering several biologically related patterns, top scoring

Research Article Gene expression profiling for coronary artery ...

Indian Academy of Sciences (India)

Shiridhar Kashyap

stored at -80˚C in nuclease free water for gene expression experiments. ..... So, identification of a unique signature for CAD globally as treatment target and early diagnostic biomarker needs ..... The colour of bar, blue, brown, grey and yellow.

Understanding Autoimmune Mechanisms in Multiple Sclerosis Using Gene Expression Microarrays: Treatment Effect and Cytokine-related Pathways

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A. Achiron

2004-01-01

Full Text Available Multiple sclerosis (MS is a central nervous system disease in which activated autoreactive T-cells invade the blood brain barrier and initiate an inflammatory response that leads to myelin destruction and axonal loss. The etiology of MS, as well as the mechanisms associated with its unexpected onset, the unpredictable clinical course spanning decades, and the different rates of progression leading to disability over time, remains an enigma. We have applied gene expression microarrays technology in peripheral blood mononuclear cells (PBMC to better understand MS pathogenesis and better target treatment approaches. A signature of 535 genes were found to distinguish immunomodulatory treatment effects between 13 treated and 13 untreated MS patients. In addition, the expression pattern of 1109 gene transcripts that were previously reported to significantly differentiate between MS patients and healthy subjects were further analyzed to study the effect of cytokine-related pathways on disease pathogenesis. When relative gene expression for 26 MS patients was compared to 18 healthy controls, 30 genes related to various cytokine-associated pathways were identified. These genes belong to a variety of families such as interleukins, small inducible cytokine subfamily and tumor necrosis factor ligand and receptor. Further analysis disclosed seven cytokine-associated genes within the immunomodulatory treatment signature, and two cytokine-associated genes SCYA4 (small inducible cytokine A4 and FCAR (Fc fragment of IgA, CD89 that were common to both the MS gene expression signature and the immunomodulatory treatment gene expression signature. Our results indicate that cytokine-associated genes are involved in various pathogenic pathways in MS and also related to immunomodulatory treatment effects.

Biomarker Gene Signature Discovery Integrating Network Knowledge

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Holger Fröhlich

2012-02-01

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.

Whole genome transcript profiling of drug induced steatosis in rats reveals a gene signature predictive of outcome.

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Nishika Sahini

Full Text Available Drug induced steatosis (DIS is characterised by excess triglyceride accumulation in the form of lipid droplets (LD in liver cells. To explore mechanisms underlying DIS we interrogated the publically available microarray data from the Japanese Toxicogenomics Project (TGP to study comprehensively whole genome gene expression changes in the liver of treated rats. For this purpose a total of 17 and 12 drugs which are diverse in molecular structure and mode of action were considered based on their ability to cause either steatosis or phospholipidosis, respectively, while 7 drugs served as negative controls. In our efforts we focused on 200 genes which are considered to be mechanistically relevant in the process of lipid droplet biogenesis in hepatocytes as recently published (Sahini and Borlak, 2014. Based on mechanistic considerations we identified 19 genes which displayed dose dependent responses while 10 genes showed time dependency. Importantly, the present study defined 9 genes (ANGPTL4, FABP7, FADS1, FGF21, GOT1, LDLR, GK, STAT3, and PKLR as signature genes to predict DIS. Moreover, cross tabulation revealed 9 genes to be regulated ≥10 times amongst the various conditions and included genes linked to glucose metabolism, lipid transport and lipogenesis as well as signalling events. Additionally, a comparison between drugs causing phospholipidosis and/or steatosis revealed 26 genes to be regulated in common including 4 signature genes to predict DIS (PKLR, GK, FABP7 and FADS1. Furthermore, a comparison between in vivo single dose (3, 6, 9 and 24 h and findings from rat hepatocyte studies (2 h, 8 h, 24 h identified 10 genes which are regulated in common and contained 2 DIS signature genes (FABP7, FGF21. Altogether, our studies provide comprehensive information on mechanistically linked gene expression changes of a range of drugs causing steatosis and phospholipidosis and encourage the screening of DIS signature genes at the preclinical stage.

Peripheral blood gene expression as a novel genomic biomarker in complicated sarcoidosis.

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Tong Zhou

Full Text Available Sarcoidosis, a systemic granulomatous syndrome invariably affecting the lung, typically spontaneously remits but in ~20% of cases progresses with severe lung dysfunction or cardiac and neurologic involvement (complicated sarcoidosis. Unfortunately, current biomarkers fail to distinguish patients with remitting (uncomplicated sarcoidosis from other fibrotic lung disorders, and fail to identify individuals at risk for complicated sarcoidosis. We utilized genome-wide peripheral blood gene expression analysis to identify a 20-gene sarcoidosis biomarker signature distinguishing sarcoidosis (n = 39 from healthy controls (n = 35, 86% classification accuracy and which served as a molecular signature for complicated sarcoidosis (n = 17. As aberrancies in T cell receptor (TCR signaling, JAK-STAT (JS signaling, and cytokine-cytokine receptor (CCR signaling are implicated in sarcoidosis pathogenesis, a 31-gene signature comprised of T cell signaling pathway genes associated with sarcoidosis (TCR/JS/CCR was compared to the unbiased 20-gene biomarker signature but proved inferior in prediction accuracy in distinguishing complicated from uncomplicated sarcoidosis. Additional validation strategies included significant association of single nucleotide polymorphisms (SNPs in signature genes with sarcoidosis susceptibility and severity (unbiased signature genes - CX3CR1, FKBP1A, NOG, RBM12B, SENS3, TSHZ2; T cell/JAK-STAT pathway genes such as AKT3, CBLB, DLG1, IFNG, IL2RA, IL7R, ITK, JUN, MALT1, NFATC2, PLCG1, SPRED1. In summary, this validated peripheral blood molecular gene signature appears to be a valuable biomarker in identifying cases with sarcoidoisis and predicting risk for complicated sarcoidosis.

MYC/BCL2 protein coexpression contributes to the inferior survival of activated B-cell subtype of diffuse large B-cell lymphoma and demonstrates high-risk gene expression signatures

DEFF Research Database (Denmark)

Hu, Shimin; Xu-Monette, Zijun Y; Tzankov, Alexander

2013-01-01

Diffuse large B-cell lymphoma (DLBCL) is stratified into prognostically favorable germinal center B-cell (GCB)-like and unfavorable activated B-cell (ABC)-like subtypes based on gene expression signatures. In this study, we analyzed 893 de novo DLBCL patients treated with R-CHOP (rituximab, cyclo...

CCR 20th Anniversary Commentary: Gene-Expression Signature in Breast Cancer--Where Did It Start and Where Are We Now?

Science.gov (United States)

Gingras, Isabelle; Desmedt, Christine; Ignatiadis, Michail; Sotiriou, Christos

2015-11-01

Desmedt and colleagues published two articles, one in the June 1, 2007 issue, and the other in the August 15, 2008, issue of Clinical Cancer Research, that showed gene-expression signatures to be proliferation driven and time dependent, with their prognostic power decreasing with increasing follow-up years. Moreover, the articles showed that immune response is a crucial determinant of prognosis in the HER2-positive and estrogen receptor-negative/HER2-negative subtypes, providing a rationale to further explore the role of the antitumor immune response in these breast cancer subtypes. ©2015 American Association for Cancer Research.

Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

Science.gov (United States)

Zhou, Xionghui; Liu, Juan

2014-01-01

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

Spatio-Temporal Gene Expression Profiling during In Vivo Early Ovarian Folliculogenesis: Integrated Transcriptomic Study and Molecular Signature of Early Follicular Growth.

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Agnes Bonnet

Full Text Available The successful achievement of early ovarian folliculogenesis is important for fertility and reproductive life span. This complex biological process requires the appropriate expression of numerous genes at each developmental stage, in each follicular compartment. Relatively little is known at present about the molecular mechanisms that drive this process, and most gene expression studies have been performed in rodents and without considering the different follicular compartments.We used RNA-seq technology to explore the sheep transcriptome during early ovarian follicular development in the two main compartments: oocytes and granulosa cells. We documented the differential expression of 3,015 genes during this phase and described the gene expression dynamic specific to these compartments. We showed that important steps occurred during primary/secondary transition in sheep. We also described the in vivo molecular course of a number of pathways. In oocytes, these pathways documented the chronology of the acquisition of meiotic competence, migration and cellular organization, while in granulosa cells they concerned adhesion, the formation of cytoplasmic projections and steroid synthesis. This study proposes the involvement in this process of several members of the integrin and BMP families. The expression of genes such as Kruppel-like factor 9 (KLF9 and BMP binding endothelial regulator (BMPER was highlighted for the first time during early follicular development, and their proteins were also predicted to be involved in gene regulation. Finally, we selected a data set of 24 biomarkers that enabled the discrimination of early follicular stages and thus offer a molecular signature of early follicular growth. This set of biomarkers includes known genes such as SPO11 meiotic protein covalently bound to DSB (SPO11, bone morphogenetic protein 15 (BMP15 and WEE1 homolog 2 (S. pombe(WEE2 which play critical roles in follicular development but other biomarkers

Gene signature associated with benign neurofibroma transformation to malignant peripheral nerve sheath tumors.

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Marta Martínez

Full Text Available Benign neurofibromas, the main phenotypic manifestations of the rare neurological disorder neurofibromatosis type 1, degenerate to malignant tumors associated to poor prognosis in about 10% of patients. Despite efforts in the field of (epigenomics, the lack of prognostic biomarkers with which to predict disease evolution frustrates the adoption of appropriate early therapeutic measures. To identify potential biomarkers of malignant neurofibroma transformation, we integrated four human experimental studies and one for mouse, using a gene score-based meta-analysis method, from which we obtained a score-ranked signature of 579 genes. Genes with the highest absolute scores were classified as promising disease biomarkers. By grouping genes with similar neurofibromatosis-related profiles, we derived panels of potential biomarkers. The addition of promoter methylation data to gene profiles indicated a panel of genes probably silenced by hypermethylation. To identify possible therapeutic treatments, we used the gene signature to query drug expression databases. Trichostatin A and other histone deacetylase inhibitors, as well as cantharidin and tamoxifen, were retrieved as putative therapeutic means to reverse the aberrant regulation that drives to malignant cell proliferation and metastasis. This in silico prediction corroborated reported experimental results that suggested the inclusion of these compounds in clinical trials. This experimental validation supported the suitability of the meta-analysis method used to integrate several sources of public genomic information, and the reliability of the gene signature associated to the malignant evolution of neurofibromas to generate working hypotheses for prognostic and drug-responsive biomarkers or therapeutic measures, thus showing the potential of this in silico approach for biomarker discovery.

The Molecular Signatures Database (MSigDB) hallmark gene set collection.

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Liberzon, Arthur; Birger, Chet; Thorvaldsdóttir, Helga; Ghandi, Mahmoud; Mesirov, Jill P; Tamayo, Pablo

2015-12-23

The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.

Evolutionary signatures amongst disease genes permit novel methods for gene prioritization and construction of informative gene-based networks.

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Nolan Priedigkeit

2015-02-01

Full Text Available Genes involved in the same function tend to have similar evolutionary histories, in that their rates of evolution covary over time. This coevolutionary signature, termed Evolutionary Rate Covariation (ERC, is calculated using only gene sequences from a set of closely related species and has demonstrated potential as a computational tool for inferring functional relationships between genes. To further define applications of ERC, we first established that roughly 55% of genetic diseases posses an ERC signature between their contributing genes. At a false discovery rate of 5% we report 40 such diseases including cancers, developmental disorders and mitochondrial diseases. Given these coevolutionary signatures between disease genes, we then assessed ERC's ability to prioritize known disease genes out of a list of unrelated candidates. We found that in the presence of an ERC signature, the true disease gene is effectively prioritized to the top 6% of candidates on average. We then apply this strategy to a melanoma-associated region on chromosome 1 and identify MCL1 as a potential causative gene. Furthermore, to gain global insight into disease mechanisms, we used ERC to predict molecular connections between 310 nominally distinct diseases. The resulting "disease map" network associates several diseases with related pathogenic mechanisms and unveils many novel relationships between clinically distinct diseases, such as between Hirschsprung's disease and melanoma. Taken together, these results demonstrate the utility of molecular evolution as a gene discovery platform and show that evolutionary signatures can be used to build informative gene-based networks.

Gene expression patterns in blood leukocytes discriminate patients with acute infections

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Allman, Windy; Chung, Wendy; Mejias, Asuncion; Ardura, Monica; Glaser, Casey; Wittkowski, Knut M.; Piqueras, Bernard; Banchereau, Jacques; Palucka, A. Karolina; Chaussabel, Damien

2007-01-01

Each infectious agent represents a unique combination of pathogen-associated molecular patterns that interact with specific pattern-recognition receptors expressed on immune cells. Therefore, we surmised that the blood immune cells of individuals with different infections might bear discriminative transcriptional signatures. Gene expression profiles were obtained for 131 peripheral blood samples from pediatric patients with acute infections caused by influenza A virus, Gram-negative (Escherichia coli) or Gram-positive (Staphylococcus aureus and Streptococcus pneumoniae) bacteria. Thirty-five genes were identified that best discriminate patients with influenza A virus infection from patients with either E coli or S pneumoniae infection. These genes classified with 95% accuracy (35 of 37 samples) an independent set of patients with either influenza A, E coli, or S pneumoniae infection. A different signature discriminated patients with E coli versus S aureus infections with 85% accuracy (34 of 40). Furthermore, distinctive gene expression patterns were observed in patients presenting with respiratory infections of different etiologies. Thus, microarray analyses of patient peripheral blood leukocytes might assist in the differential diagnosis of infectious diseases. PMID:17105821

Characteristic Changes in Decidual Gene Expression Signature in Spontaneous Term Parturition

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Haidy El-Azzamy

2017-05-01

Full Text Available Background The decidua has been implicated in the “terminal pathway” of human term parturition, which is characterized by the activation of pro-inflammatory pathways in gestational tissues. However, the transcriptomic changes in the decidua leading to terminal pathway activation have not been systematically explored. This study aimed to compare the decidual expression of developmental signaling and inflammation-related genes before and after spontaneous term labor in order to reveal their involvement in this process. Methods Chorioamniotic membranes were obtained from normal pregnant women who delivered at term with spontaneous labor (TIL, n = 14 or without labor (TNL, n = 15. Decidual cells were isolated from snap-frozen chorioamniotic membranes with laser microdissection. The expression of 46 genes involved in decidual development, sex steroid and prostaglandin signaling, as well as pro- and anti-inflammatory pathways, was analyzed using high-throughput quantitative real-time polymerase chain reaction (qRT-PCR. Chorioamniotic membrane sections were immunostained and then semi-quantified for five proteins, and immunoassays for three chemokines were performed on maternal plasma samples. Results The genes with the highest expression in the decidua at term gestation included insulin-like growth factor-binding protein 1 (IGFBP1, galectin-1 (LGALS1, and progestogen-associated endometrial protein (PAEP; the expression of estrogen receptor 1 (ESR1, homeobox A11 (HOXA11, interleukin 1β (IL1B, IL8, progesterone receptor membrane component 2 (PGRMC2, and prostaglandin E synthase (PTGES was higher in TIL than in TNL cases; the expression of chemokine C-C motif ligand 2 (CCL2, CCL5, LGALS1, LGALS3, and PAEP was lower in TIL than in TNL cases; immunostaining confirmed qRT-PCR data for IL-8, CCL2, galectin-1, galectin-3, and PAEP; and no correlations between the decidual gene expression and the maternal plasma protein concentrations of CCL2, CCL5, and

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans.

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Gottlieb, Assaf; Daneshjou, Roxana; DeGorter, Marianne; Bourgeois, Stephane; Svensson, Peter J; Wadelius, Mia; Deloukas, Panos; Montgomery, Stephen B; Altman, Russ B

2017-11-24

Genome-wide association studies are useful for discovering genotype-phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into "gene level" effects. Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression-on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort.

Computational integration of homolog and pathway gene module expression reveals general stemness signatures.

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Martina Koeva

Full Text Available The stemness hypothesis states that all stem cells use common mechanisms to regulate self-renewal and multi-lineage potential. However, gene expression meta-analyses at the single gene level have failed to identify a significant number of genes selectively expressed by a broad range of stem cell types. We hypothesized that stemness may be regulated by modules of homologs. While the expression of any single gene within a module may vary from one stem cell type to the next, it is possible that the expression of the module as a whole is required so that the expression of different, yet functionally-synonymous, homologs is needed in different stem cells. Thus, we developed a computational method to test for stem cell-specific gene expression patterns from a comprehensive collection of 49 murine datasets covering 12 different stem cell types. We identified 40 individual genes and 224 stemness modules with reproducible and specific up-regulation across multiple stem cell types. The stemness modules included families regulating chromatin remodeling, DNA repair, and Wnt signaling. Strikingly, the majority of modules represent evolutionarily related homologs. Moreover, a score based on the discovered modules could accurately distinguish stem cell-like populations from other cell types in both normal and cancer tissues. This scoring system revealed that both mouse and human metastatic populations exhibit higher stemness indices than non-metastatic populations, providing further evidence for a stem cell-driven component underlying the transformation to metastatic disease.

Resistance gene expression determines the in vitro chemosensitivity of non-small cell lung cancer (NSCLC)

International Nuclear Information System (INIS)

Glaysher, Sharon; Modi, Paul; Rahamim, Joe; Smith, Mark E; Amer, Khalid; Addis, Bruce; Poole, Matthew; Narayanan, Ajit; Gulliford, Tim J; Andreotti, Peter E; Cree, Ian A; Yiannakis, Dennis; Gabriel, Francis G; Johnson, Penny; Polak, Marta E; Knight, Louise A; Goldthorpe, Zoe; Peregrin, Katharine; Gyi, Mya

2009-01-01

NSCLC exhibits considerable heterogeneity in its sensitivity to chemotherapy and similar heterogeneity is noted in vitro in a variety of model systems. This study has tested the hypothesis that the molecular basis of the observed in vitro chemosensitivity of NSCLC lies within the known resistance mechanisms inherent to these patients' tumors. The chemosensitivity of a series of 49 NSCLC tumors was assessed using the ATP-based tumor chemosensitivity assay (ATP-TCA) and compared with quantitative expression of resistance genes measured by RT-PCR in a Taqman Array™ following extraction of RNA from formalin-fixed paraffin-embedded (FFPE) tissue. There was considerable heterogeneity between tumors within the ATP-TCA, and while this showed no direct correlation with individual gene expression, there was strong correlation of multi-gene signatures for many of the single agents and combinations tested. For instance, docetaxel activity showed some dependence on the expression of drug pumps, while cisplatin activity showed some dependence on DNA repair enzyme expression. Activity of both drugs was influenced more strongly still by the expression of anti- and pro-apoptotic genes by the tumor for both docetaxel and cisplatin. The doublet combinations of cisplatin with gemcitabine and cisplatin with docetaxel showed gene expression signatures incorporating resistance mechanisms for both agents. Genes predicted to be involved in known mechanisms drug sensitivity and resistance correlate well with in vitro chemosensitivity and may allow the definition of predictive signatures to guide individualized chemotherapy in lung cancer

Differentially expressed genes in the pre-eclamptic placenta: a systematic review and meta-analysis

NARCIS (Netherlands)

Kleinrouweler, C. Emily; van Uitert, Miranda; Moerland, Perry D.; Ris-Stalpers, Carrie; van der Post, Joris A. M.; Afink, Gijs B.

2013-01-01

To systematically review the literature on human gene expression data of placental tissue in pre-eclampsia and to characterize a meta-signature of differentially expressed genes in order to identify novel putative diagnostic markers. Medline through 11 February 2011 using MeSH terms and keywords

Robust assignment of cancer subtypes from expression data using a uni-variate gene expression average as classifier

International Nuclear Information System (INIS)

Lauss, Martin; Frigyesi, Attila; Ryden, Tobias; Höglund, Mattias

2010-01-01

Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms. The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies. We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package rocc is freely available at http://cran.r-project.org/web/packages/rocc/index.html

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

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Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

Gene expression profiling reveals distinct molecular signatures associated with the rupture of intracranial aneurysm.

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Nakaoka, Hirofumi; Tajima, Atsushi; Yoneyama, Taku; Hosomichi, Kazuyoshi; Kasuya, Hidetoshi; Mizutani, Tohru; Inoue, Ituro

2014-08-01

The rupture of intracranial aneurysm (IA) causes subarachnoid hemorrhage associated with high morbidity and mortality. We compared gene expression profiles in aneurysmal domes between unruptured IAs and ruptured IAs (RIAs) to elucidate biological mechanisms predisposing to the rupture of IA. We determined gene expression levels of 8 RIAs, 5 unruptured IAs, and 10 superficial temporal arteries with the Agilent microarrays. To explore biological heterogeneity of IAs, we classified the samples into subgroups showing similar gene expression patterns, using clustering methods. The clustering analysis identified 4 groups: superficial temporal arteries and unruptured IAs were aggregated into their own clusters, whereas RIAs segregated into 2 distinct subgroups (early and late RIAs). Comparing gene expression levels between early RIAs and unruptured IAs, we identified 430 upregulated and 617 downregulated genes in early RIAs. The upregulated genes were associated with inflammatory and immune responses and phagocytosis including S100/calgranulin genes (S100A8, S100A9, and S100A12). The downregulated genes suggest mechanical weakness of aneurysm walls. The expressions of Krüppel-like family of transcription factors (KLF2, KLF12, and KLF15), which were anti-inflammatory regulators, and CDKN2A, which was located on chromosome 9p21 that was the most consistently replicated locus in genome-wide association studies of IA, were also downregulated. We demonstrate that gene expression patterns of RIAs were different according to the age of patients. The results suggest that macrophage-mediated inflammation is a key biological pathway for IA rupture. The identified genes can be good candidates for molecular markers of rupture-prone IAs and therapeutic targets. © 2014 American Heart Association, Inc.

Metformin induces a Senescence-associated gene Signature in Breast Cancer Cells

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Williams, Christopher C.; Singleton, Brittany A.; Llopis, Shawn D.; Skripnikova, Elena V.

2013-01-01

Diabetic patients taking metformin have lower incidence of breast cancer than those taking other anti-diabetic medications. Additionally, triple negative breast cancer (TNBC), a form of breast cancer disproportionately afflicting premenopausal African American women, shows atypical susceptibility to metformin’s antiproliferative effect. The mechanisms involved in metformin’s function in TNBC has not yet been fully elucidated. Therefore, we sought to identify pathways regulated by metformin in using the MDA-MB-468 TNBC cell model. Metformin dose-dependently caused apoptosis, decreased cell viability, and induced cell morphology/chromatin condensation consistent with the permanent proliferative arrest. Furthermore, gene expression arrays revealed that metformin caused expression of stress markers DDIT3, CYP1A1, and GDF-15 and a concomitant reduction in PTGS1 expression. Our findings show that metformin may affect the viability and proliferative capacity of TNBC by inducing an antiproliferative gene signature, and that metformin may be effective in the treatment/prevention of TNBC. PMID:23395946

mRNA/microRNA gene expression profile in microsatellite unstable colorectal cancer

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Calin George A

2007-08-01

Full Text Available Abstract Background Colorectal cancer develops through two main genetic instability pathways characterized by distinct pathologic features and clinical outcome. Results We investigated colon cancer samples (23 characterized by microsatellite stability, MSS, and 16 by high microsatellite instability, MSI-H for genome-wide expression of microRNA (miRNA and mRNA. Based on combined miRNA and mRNA gene expression, a molecular signature consisting of twenty seven differentially expressed genes, inclusive of 8 miRNAs, could correctly distinguish MSI-H versus MSS colon cancer samples. Among the differentially expressed miRNAs, various members of the oncogenic miR-17-92 family were significantly up-regulated in MSS cancers. The majority of protein coding genes were also up-regulated in MSS cancers. Their functional classification revealed that they were most frequently associated with cell cycle, DNA replication, recombination, repair, gastrointestinal disease and immune response. Conclusion This is the first report that indicates the existence of differences in miRNA expression between MSS versus MSI-H colorectal cancers. In addition, the work suggests that the combination of mRNA/miRNA expression signatures may represent a general approach for improving bio-molecular classification of human cancer.

Resistance gene expression determines the in vitro chemosensitivity of non-small cell lung cancer (NSCLC

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Amer Khalid

2009-08-01

Full Text Available Abstract Background NSCLC exhibits considerable heterogeneity in its sensitivity to chemotherapy and similar heterogeneity is noted in vitro in a variety of model systems. This study has tested the hypothesis that the molecular basis of the observed in vitro chemosensitivity of NSCLC lies within the known resistance mechanisms inherent to these patients' tumors. Methods The chemosensitivity of a series of 49 NSCLC tumors was assessed using the ATP-based tumor chemosensitivity assay (ATP-TCA and compared with quantitative expression of resistance genes measured by RT-PCR in a Taqman Array™ following extraction of RNA from formalin-fixed paraffin-embedded (FFPE tissue. Results There was considerable heterogeneity between tumors within the ATP-TCA, and while this showed no direct correlation with individual gene expression, there was strong correlation of multi-gene signatures for many of the single agents and combinations tested. For instance, docetaxel activity showed some dependence on the expression of drug pumps, while cisplatin activity showed some dependence on DNA repair enzyme expression. Activity of both drugs was influenced more strongly still by the expression of anti- and pro-apoptotic genes by the tumor for both docetaxel and cisplatin. The doublet combinations of cisplatin with gemcitabine and cisplatin with docetaxel showed gene expression signatures incorporating resistance mechanisms for both agents. Conclusion Genes predicted to be involved in known mechanisms drug sensitivity and resistance correlate well with in vitro chemosensitivity and may allow the definition of predictive signatures to guide individualized chemotherapy in lung cancer.

Identification of a Common Different Gene Expression Signature in Ischemic Cardiomyopathy

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Yana Li

2018-01-01

Full Text Available The molecular mechanisms underlying the development of ischemic cardiomyopathy (ICM remain poorly understood. Gene expression profiling is helpful to discover the molecular changes taking place in ICM. The aim of this study was to identify the genes that are significantly changed during the development of heart failure caused by ICM. The differentially expressed genes (DEGs were identified from 162 control samples and 227 ICM patients. PANTHER was used to perform gene ontology (GO, and Reactome for pathway enrichment analysis. A protein–protein interaction network was established using STRING and Cytoscape. A further validation was performed by real-time polymerase chain reaction (RT-PCR. A total of 255 common DEGs was found. Gene ontology, pathway enrichment, and protein–protein interaction analysis showed that nucleic acid-binding proteins, enzymes, and transcription factors accounted for a great part of the DEGs, while immune system signaling and cytokine signaling displayed the most significant changes. Furthermore, seven hub genes and nine transcription factors were identified. Interestingly, the top five upregulated DEGs were located on chromosome Y, and four of the top five downregulated DEGs were involved in immune and inflammation signaling. Further, the top DEGs were validated by RT-PCR in human samples. Our study explored the possible molecular mechanisms of heart failure caused by ischemic heart disease.

Diagnosis of partial body radiation exposure in mice using peripheral blood gene expression profiles.

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Sarah K Meadows

2010-07-01

Full Text Available In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI. However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79-100% compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16-43%, suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation.

ColoFinder: a prognostic 9-gene signature improves prognosis for 871 stage II and III colorectal cancer patients

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Mingguang Shi

2016-03-01

Full Text Available Colorectal cancer (CRC is a heterogeneous disease with a high mortality rate and is still lacking an effective treatment. Our goal is to develop a robust prognosis model for predicting the prognosis in CRC patients. In this study, 871 stage II and III CRC samples were collected from six gene expression profilings. ColoFinder was developed using a 9-gene signature based Random Survival Forest (RSF prognosis model. The 9-gene signature recurrence score was derived with a 5-fold cross validation to test the association with relapse-free survival, and the value of AUC was gained with 0.87 in GSE39582(95% CI [0.83–0.91]. The low-risk group had a significantly better relapse-free survival (HR, 14.8; 95% CI [8.17–26.8]; P < 0.001 than the high-risk group. We also found that the 9-gene signature recurrence score contributed more information about recurrence than standard clinical and pathological variables in univariate and multivariate Cox analyses when applied to GSE17536(p = 0.03 and p = 0.01 respectively. Furthermore, ColoFinder improved the predictive ability and better stratified the risk subgroups when applied to CRC gene expression datasets GSE14333, GSE17537, GSE12945and GSE24551. In summary, ColoFinder significantly improves the risk assessment in stage II and III CRC patients. The 9-gene prognostic classifier informs patient prognosis and treatment response.

Risk estimation of distant metastasis in node-negative, estrogen receptor-positive breast cancer patients using an RT-PCR based prognostic expression signature

International Nuclear Information System (INIS)

Tutt, Andrew; Shu, Henry; Springall, Robert; Cane, Paul; McCallie, Blair; Kam-Morgan, Lauren; Anderson, Steve; Buerger, Horst; Gray, Joe; Bennington, James; Esserman, Laura; Wang, Alice; Hastie, Trevor; Broder, Samuel; Sninsky, John; Brandt, Burkhard; Waldman, Fred; Rowland, Charles; Gillett, Cheryl; Lau, Kit; Chew, Karen; Dai, Hongyue; Kwok, Shirley; Ryder, Kenneth

2008-01-01

Given the large number of genes purported to be prognostic for breast cancer, it would be optimal if the genes identified are not confounded by the continuously changing systemic therapies. The aim of this study was to discover and validate a breast cancer prognostic expression signature for distant metastasis in untreated, early stage, lymph node-negative (N-) estrogen receptor-positive (ER+) patients with extensive follow-up times. 197 genes previously associated with metastasis and ER status were profiled from 142 untreated breast cancer subjects. A 'metastasis score' (MS) representing fourteen differentially expressed genes was developed and evaluated for its association with distant-metastasis-free survival (DMFS). Categorical risk classification was established from the continuous MS and further evaluated on an independent set of 279 untreated subjects. A third set of 45 subjects was tested to determine the prognostic performance of the MS in tamoxifen-treated women. A 14-gene signature was found to be significantly associated (p < 0.05) with distant metastasis in a training set and subsequently in an independent validation set. In the validation set, the hazard ratios (HR) of the high risk compared to low risk groups were 4.02 (95% CI 1.91–8.44) for the endpoint of DMFS and 1.97 (95% CI 1.28 to 3.04) for overall survival after adjustment for age, tumor size and grade. The low and high MS risk groups had 10-year estimates (95% CI) of 96% (90–99%) and 72% (64–78%) respectively, for DMFS and 91% (84–95%) and 68% (61–75%), respectively for overall survival. Performance characteristics of the signature in the two sets were similar. Ki-67 labeling index (LI) was predictive for recurrent disease in the training set, but lost significance after adjustment for the expression signature. In a study of tamoxifen-treated patients, the HR for DMFS in high compared to low risk groups was 3.61 (95% CI 0.86–15.14). The 14-gene signature is significantly

Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans

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Assaf Gottlieb

2017-11-01

Full Text Available Abstract Background Genome-wide association studies are useful for discovering genotype–phenotype associations but are limited because they require large cohorts to identify a signal, which can be population-specific. Mapping genetic variation to genes improves power and allows the effects of both protein-coding variation as well as variation in expression to be combined into “gene level” effects. Methods Previous work has shown that warfarin dose can be predicted using information from genetic variation that affects protein-coding regions. Here, we introduce a method that improves dose prediction by integrating tissue-specific gene expression. In particular, we use drug pathways and expression quantitative trait loci knowledge to impute gene expression—on the assumption that differential expression of key pathway genes may impact dose requirement. We focus on 116 genes from the pharmacokinetic and pharmacodynamic pathways of warfarin within training and validation sets comprising both European and African-descent individuals. Results We build gene-tissue signatures associated with warfarin dose in a cohort-specific manner and identify a signature of 11 gene-tissue pairs that significantly augments the International Warfarin Pharmacogenetics Consortium dosage-prediction algorithm in both populations. Conclusions Our results demonstrate that imputed expression can improve dose prediction and bridge population-specific compositions. MATLAB code is available at https://github.com/assafgo/warfarin-cohort

Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

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Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

2013-01-01

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

Supplementary Material for: Astrocyte-specific overexpressed gene signatures in response to methamphetamine exposure in vitro

KAUST Repository

Bortell, Nikki; Basova, Liana; Semenova, Svetlana; Fox, Howard; Ravasi, Timothy; Marcondes, Maria

2017-01-01

Abstract Background Astrocyte activation is one of the earliest findings in the brain of methamphetamine (Meth) abusers. Our goal in this study was to identify the characteristics of the astrocytic acute response to the drug, which may be critical in pathogenic outcomes secondary to the use. Methods We developed an integrated analysis of gene expression data to study the acute gene changes caused by the direct exposure to Meth treatment of astrocytes in vitro, and to better understand how astrocytes respond, what are the early molecular markers associated with this response. We examined the literature in search of similar changes in gene signatures that are found in central nervous system disorders. Results We identified overexpressed gene networks represented by genes of an inflammatory and immune nature and that are implicated in neuroactive ligand-receptor interactions. The overexpressed networks are linked to molecules that were highly upregulated in astrocytes by all doses of methamphetamine tested and that could play a role in the central nervous system. The strongest overexpressed signatures were the upregulation of MAP2K5, GPR65, and CXCL5, and the gene networks individually associated with these molecules. Pathway analysis revealed that these networks are involved both in neuroprotection and in neuropathology. We have validated several targets associated to these genes. Conclusions Gene signatures for the astrocytic response to Meth were identified among the upregulated gene pool, using an in vitro system. The identified markers may participate in dysfunctions of the central nervous system but could also provide acute protection to the drug exposure. Further in vivo studies are necessary to establish the role of these gene networks in drug abuse pathogenesis.

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2011-12-02

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A 7-Gene Signature Depicts the Biochemical Profile of Early Prefibrotic Myelofibrosis

DEFF Research Database (Denmark)

Skov, Vibe; Burton, Mark; Thomassen, Mads

2016-01-01

was performed in 17 and 9 patients diagnosed with ET and PMF, respectively. Using elevated LDH obtained at the time of diagnosis as a marker of prePMF, a 7-gene signature was identified which correctly predicted the prePMF group with a sensitivity of 100% and a specificity of 89%. The 7 genes included MPO......, CEACAM8, CRISP3, MS4A3, CEACAM6, HEMGN, and MMP8, which are genes known to be involved in inflammation, cell adhesion, differentiation and proliferation. Evaluation of bone marrow biopsies and the 7-gene signature showed a concordance rate of 71%, 79%, 62%, and 38%. Our 7-gene signature may be a useful...

Expression profiling of cervical cancers in Indian women at different stages to identify gene signatures during progression of the disease

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Thomas, Asha; Mahantshetty, Umesh; Kannan, Sadhana; Deodhar, Kedar; Shrivastava, Shyam K; Kumar-Sinha, Chandan; Mulherkar, Rita

2013-01-01

Cervical cancer is the second most common cancer among women worldwide, with developing countries accounting for >80% of the disease burden. Although in the West, active screening has been instrumental in reducing the incidence of cervical cancer, disease management is hampered due to lack of biomarkers for disease progression and defined therapeutic targets. Here we carried out gene expression profiling of 29 cervical cancer tissues from Indian women, spanning International Federation of Gynaecology and Obstetrics (FIGO) stages of the disease from early lesion (IA and IIA) to progressive stages (IIB and IIIA–B), and identified distinct gene expression signatures. Overall, metabolic pathways, pathways in cancer and signaling pathways were found to be significantly upregulated, while focal adhesion, cytokine–cytokine receptor interaction and WNT signaling were downregulated. Additionally, we identified candidate biomarkers of disease progression such as SPP1, proliferating cell nuclear antigen (PCNA), STK17A, and DUSP1 among others that were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in the samples used for microarray studies as well in an independent set of 34 additional samples. Integrative analysis of our results with other cervical cancer profiling studies could facilitate the development of multiplex diagnostic markers of cervical cancer progression

Peripheral blood signatures of lead exposure.

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Heather G LaBreche

Full Text Available BACKGROUND: Current evidence indicates that even low-level lead (Pb exposure can have detrimental effects, especially in children. We tested the hypothesis that Pb exposure alters gene expression patterns in peripheral blood cells and that these changes reflect dose-specific alterations in the activity of particular pathways. METHODOLOGY/PRINCIPAL FINDING: Using Affymetrix Mouse Genome 430 2.0 arrays, we examined gene expression changes in the peripheral blood of female Balb/c mice following exposure to per os lead acetate trihydrate or plain drinking water for two weeks and after a two-week recovery period. Data sets were RMA-normalized and dose-specific signatures were generated using established methods of supervised classification and binary regression. Pathway activity was analyzed using the ScoreSignatures module from GenePattern. CONCLUSIONS/SIGNIFICANCE: The low-level Pb signature was 93% sensitive and 100% specific in classifying samples a leave-one-out crossvalidation. The high-level Pb signature demonstrated 100% sensitivity and specificity in the leave-one-out crossvalidation. These two signatures exhibited dose-specificity in their ability to predict Pb exposure and had little overlap in terms of constituent genes. The signatures also seemed to reflect current levels of Pb exposure rather than past exposure. Finally, the two doses showed differential activation of cellular pathways. Low-level Pb exposure increased activity of the interferon-gamma pathway, whereas high-level Pb exposure increased activity of the E2F1 pathway.

Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping.

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Chang, Meiping; Smith, Sarah; Thorpe, Andrew; Barratt, Michael J; Karim, Farzana

2010-09-16

We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model.

Development and validation of a gene expression-based signature to predict distant metastasis in locoregionally advanced nasopharyngeal carcinoma: a retrospective, multicentre, cohort study.

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Tang, Xin-Ran; Li, Ying-Qin; Liang, Shao-Bo; Jiang, Wei; Liu, Fang; Ge, Wen-Xiu; Tang, Ling-Long; Mao, Yan-Ping; He, Qing-Mei; Yang, Xiao-Jing; Zhang, Yuan; Wen, Xin; Zhang, Jian; Wang, Ya-Qin; Zhang, Pan-Pan; Sun, Ying; Yun, Jing-Ping; Zeng, Jing; Li, Li; Liu, Li-Zhi; Liu, Na; Ma, Jun

2018-03-01

Gene expression patterns can be used as prognostic biomarkers in various types of cancers. We aimed to identify a gene expression pattern for individual distant metastatic risk assessment in patients with locoregionally advanced nasopharyngeal carcinoma. In this multicentre, retrospective, cohort analysis, we included 937 patients with locoregionally advanced nasopharyngeal carcinoma from three Chinese hospitals: the Sun Yat-sen University Cancer Center (Guangzhou, China), the Affiliated Hospital of Guilin Medical University (Guilin, China), and the First People's Hospital of Foshan (Foshan, China). Using microarray analysis, we profiled mRNA gene expression between 24 paired locoregionally advanced nasopharyngeal carcinoma tumours from patients at Sun Yat-sen University Cancer Center with or without distant metastasis after radical treatment. Differentially expressed genes were examined using digital expression profiling in a training cohort (Guangzhou training cohort; n=410) to build a gene classifier using a penalised regression model. We validated the prognostic accuracy of this gene classifier in an internal validation cohort (Guangzhou internal validation cohort, n=204) and two external independent cohorts (Guilin cohort, n=165; Foshan cohort, n=158). The primary endpoint was distant metastasis-free survival. Secondary endpoints were disease-free survival and overall survival. We identified 137 differentially expressed genes between metastatic and non-metastatic locoregionally advanced nasopharyngeal carcinoma tissues. A distant metastasis gene signature for locoregionally advanced nasopharyngeal carcinoma (DMGN) that consisted of 13 genes was generated to classify patients into high-risk and low-risk groups in the training cohort. Patients with high-risk scores in the training cohort had shorter distant metastasis-free survival (hazard ratio [HR] 4·93, 95% CI 2·99-8·16; padvanced nasopharyngeal carcinoma and might be able to predict which patients benefit

Gene expression signatures in peripheral blood cells from Japanese women exposed to environmental cadmium

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Dakeshita, Satoru; Kawai, Tomoko; Uemura, Hirokazu; Hiyoshi, Mineyoshi; Oguma, Etsuko; Horiguchi, Hyogo; Kayama, Fujio; Aoshima, Keiko; Shirahama, Satoshi; Rokutan, Kazuhito; Arisawa, Kokichi

2009-01-01

The objective of this study was to examine the effects of environmental cadmium (Cd) exposure on the gene expression profile of peripheral blood cells, using an original oligoDNA microarray. The study population consisted of 20 female residents in a Cd-polluted area (Cd-exposed group) and 20 female residents in a non-Cd-polluted area individually matched for age (control group). The mRNA levels in Cd-exposed subjects were compared with those in respective controls, using a microarray containing oligoDNA probes for 1867 genes. Median Cd concentrations in blood (3.55 μg/l) and urine (8.25 μg/g creatinine) from the Cd-exposed group were 2.4- and 1.9-times higher than those of the control group, respectively. Microarray analysis revealed that the Cd-exposed group significantly up-regulated 137 genes and down-regulated 80 genes, compared with the control group. The Ingenuity Pathway Analysis Application (IPA) revealed that differentially expressed genes were likely to modify oxidative stress and mitochondria-dependent apoptosis pathways. Among differentially expressed genes, the expression of five genes was positively correlated with Cd concentrations in blood or urine. Quantitative real-time PCR (RT-PCR) analysis validated the significant up-regulation of CASP9, TNFRSF1B, GPX3, HYOU1, SLC3A2, SLC19A1, SLC35A4 and ITGAL, and down-regulation of BCL2A1 and COX7B. After adjustment for differences in the background characteristics of the two groups, we finally identified seven Cd-responsive genes (CASP9, TNFRSF1B, GPX3, SLC3A2, ITGAL, BCL2A1, and COX7B), all of which constituted a network that controls oxidative stress response by IPA. These seven genes may be marker genes useful for the health risk assessment of chronic low level exposure to Cd

Analysis of multiplex gene expression maps obtained by voxelation

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Smith Desmond J

2009-04-01

Full Text Available Abstract Background Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. Results To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in

Analysis of multiplex gene expression maps obtained by voxelation.

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An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

2009-04-29

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental

A three-gene expression signature model for risk stratification of patients with neuroblastoma.

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Garcia, Idoia; Mayol, Gemma; Ríos, José; Domenech, Gema; Cheung, Nai-Kong V; Oberthuer, André; Fischer, Matthias; Maris, John M; Brodeur, Garrett M; Hero, Barbara; Rodríguez, Eva; Suñol, Mariona; Galvan, Patricia; de Torres, Carmen; Mora, Jaume; Lavarino, Cinzia

2012-04-01

Neuroblastoma is an embryonal tumor with contrasting clinical courses. Despite elaborate stratification strategies, precise clinical risk assessment still remains a challenge. The purpose of this study was to develop a PCR-based predictor model to improve clinical risk assessment of patients with neuroblastoma. The model was developed using real-time PCR gene expression data from 96 samples and tested on separate expression data sets obtained from real-time PCR and microarray studies comprising 362 patients. On the basis of our prior study of differentially expressed genes in favorable and unfavorable neuroblastoma subgroups, we identified three genes, CHD5, PAFAH1B1, and NME1, strongly associated with patient outcome. The expression pattern of these genes was used to develop a PCR-based single-score predictor model. The model discriminated patients into two groups with significantly different clinical outcome [set 1: 5-year overall survival (OS): 0.93 ± 0.03 vs. 0.53 ± 0.06, 5-year event-free survival (EFS): 0.85 ± 0.04 vs. 0.042 ± 0.06, both P model was an independent marker for survival (P model robustly classified patients in the total cohort and in different clinically relevant risk subgroups. We propose for the first time in neuroblastoma, a technically simple PCR-based predictor model that could help refine current risk stratification systems. ©2012 AACR.

Metastatic canine mammary carcinomas can be identified by a gene expression profile that partly overlaps with human breast cancer profiles

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Klopfleisch, Robert; Lenze, Dido; Hummel, Michael; Gruber, Achim D

2010-01-01

Similar to human breast cancer mammary tumors of the female dog are commonly associated with a fatal outcome due to the development of distant metastases. However, the molecular defects leading to metastasis are largely unknown and the value of canine mammary carcinoma as a model for human breast cancer is unclear. In this study, we analyzed the gene expression signatures associated with mammary tumor metastasis and asked for parallels with the human equivalent. Messenger RNA expression profiles of twenty-seven lymph node metastasis positive or negative canine mammary carcinomas were established by microarray analysis. Differentially expressed genes were functionally characterized and associated with molecular pathways. The findings were also correlated with published data on human breast cancer. Metastatic canine mammary carcinomas had 1,011 significantly differentially expressed genes when compared to non-metastatic carcinomas. Metastatic carcinomas had a significant up-regulation of genes associated with cell cycle regulation, matrix modulation, protein folding and proteasomal degradation whereas cell differentiation genes, growth factor pathway genes and regulators of actin organization were significantly down-regulated. Interestingly, 265 of the 1,011 differentially expressed canine genes are also related to human breast cancer and, vice versa, parts of a human prognostic gene signature were identified in the expression profiles of the metastatic canine tumors. Metastatic canine mammary carcinomas can be discriminated from non-metastatic carcinomas by their gene expression profiles. More than one third of the differentially expressed genes are also described of relevance for human breast cancer. Many of the differentially expressed genes are linked to functions and pathways which appear to be relevant for the induction and maintenance of metastatic progression and may represent new therapeutic targets. Furthermore, dogs are in some aspects suitable as a

Gene expression profiling of cutaneous wound healing

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Wang Ena

2007-02-01

Full Text Available Abstract Background Although the sequence of events leading to wound repair has been described at the cellular and, to a limited extent, at the protein level this process has yet to be fully elucidated. Genome wide transcriptional analysis tools promise to further define the global picture of this complex progression of events. Study Design This study was part of a placebo-controlled double-blind clinical trial in which basal cell carcinomas were treated topically with an immunomodifier – toll-like receptor 7 agonist: imiquimod. The fourteen patients with basal cell carcinoma in the placebo arm of the trial received placebo treatment consisting solely of vehicle cream. A skin punch biopsy was obtained immediately before treatment and at the end of the placebo treatment (after 2, 4 or 8 days. 17.5K cDNA microarrays were utilized to profile the biopsy material. Results Four gene signatures whose expression changed relative to baseline (before wound induction by the pre-treatment biopsy were identified. The largest group was comprised predominantly of inflammatory genes whose expression was increased throughout the study. Two additional signatures were observed which included preferentially pro-inflammatory genes in the early post-treatment biopsies (2 days after pre-treatment biopsies and repair and angiogenesis genes in the later (4 to 8 days biopsies. The fourth and smallest set of genes was down-regulated throughout the study. Early in wound healing the expression of markers of both M1 and M2 macrophages were increased, but later M2 markers predominated. Conclusion The initial response to a cutaneous wound induces powerful transcriptional activation of pro-inflammatory stimuli which may alert the host defense. Subsequently and in the absence of infection, inflammation subsides and it is replaced by angiogenesis and remodeling. Understanding this transition which may be driven by a change from a mixed macrophage population to predominately M2

Quantitative multiplex quantum dot in-situ hybridisation based gene expression profiling in tissue microarrays identifies prognostic genes in acute myeloid leukaemia

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Tholouli, Eleni [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); MacDermott, Sarah [The Medical School, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Hoyland, Judith [School of Biomedicine, Faculty of Medical and Human Sciences, The University of Manchester, Oxford Road, M13 9PT Manchester (United Kingdom); Yin, John Liu [Department of Haematology, Manchester Royal Infirmary, Oxford Road, Manchester, M13 9WL (United Kingdom); Byers, Richard, E-mail: richard.byers@cmft.nhs.uk [School of Cancer and Enabling Sciences, Faculty of Medical and Human Sciences, The University of Manchester, Stopford Building, Oxford Road, M13 9PT Manchester (United Kingdom)

2012-08-24

Highlights: Black-Right-Pointing-Pointer Development of a quantitative high throughput in situ expression profiling method. Black-Right-Pointing-Pointer Application to a tissue microarray of 242 AML bone marrow samples. Black-Right-Pointing-Pointer Identification of HOXA4, HOXA9, Meis1 and DNMT3A as prognostic markers in AML. -- Abstract: Measurement and validation of microarray gene signatures in routine clinical samples is problematic and a rate limiting step in translational research. In order to facilitate measurement of microarray identified gene signatures in routine clinical tissue a novel method combining quantum dot based oligonucleotide in situ hybridisation (QD-ISH) and post-hybridisation spectral image analysis was used for multiplex in-situ transcript detection in archival bone marrow trephine samples from patients with acute myeloid leukaemia (AML). Tissue-microarrays were prepared into which white cell pellets were spiked as a standard. Tissue microarrays were made using routinely processed bone marrow trephines from 242 patients with AML. QD-ISH was performed for six candidate prognostic genes using triplex QD-ISH for DNMT1, DNMT3A, DNMT3B, and for HOXA4, HOXA9, Meis1. Scrambled oligonucleotides were used to correct for background staining followed by normalisation of expression against the expression values for the white cell pellet standard. Survival analysis demonstrated that low expression of HOXA4 was associated with poorer overall survival (p = 0.009), whilst high expression of HOXA9 (p < 0.0001), Meis1 (p = 0.005) and DNMT3A (p = 0.04) were associated with early treatment failure. These results demonstrate application of a standardised, quantitative multiplex QD-ISH method for identification of prognostic markers in formalin-fixed paraffin-embedded clinical samples, facilitating measurement of gene expression signatures in routine clinical samples.

Brain Gene Expression Signatures From Cerebrospinal Fluid Exosome RNA Profiling

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Zanello, S. B.; Stevens, B.; Calvillo, E.; Tang, R.; Gutierrez Flores, B.; Hu, L.; Skog, J.; Bershad, E.

2016-01-01

While the Visual Impairment and Intracranial Pressure (VIIP) syndrome observations have focused on ocular symptoms, spaceflight has been also associated with a number of other performance and neurologic signs, such as headaches, cognitive changes, vertigo, nausea, sleep/circadian disruption and mood alterations, which, albeit likely multifactorial, can also result from elevation of intracranial pressure (ICP). We therefore hypothesize that these various symptoms are caused by disturbances in the neurophysiology of the brain structures and are correlated with molecular markers in the cerebrospinal fluid (CSF) as indicators of neurophysiological changes. Exosomes are 30-200 nm microvesicles shed into all biofluids, including blood, urine, and CSF, carrying a highly rich source of intact protein and RNA cargo. Exosomes have been identified in human CSF, and their proteome and RNA pool is a potential new reservoir for biomarker discovery in neurological disorders. The purpose of this study is to investigate changes in brain gene expression via exosome analysis in patients suffering from ICP elevation of varied severity (idiopathic intracranial hypertension -IIH), a condition which shares some of the neuroophthalmological features of VIIP, as a first step toward obtaining evidence suggesting that cognitive function and ICP levels can be correlated with biomarkers in the CSF. Our preliminary work, reported last year, validated the exosomal technology applicable to CSF analysis and demonstrated that it was possible to obtain gene expression evidence of inflammation processes in traumatic brain injury patients. We are now recruiting patients with suspected IIH requiring lumbar puncture at Baylor College of Medicine. Both CSF (5 ml) and human plasma (10 ml) are being collected in order to compare the pattern of differentially expressed genes observed in CSF and in blood. Since blood is much more accessible than CSF, we would like to determine whether plasma biomarkers for

L1000CDS2: LINCS L1000 characteristic direction signatures search engine.

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Duan, Qiaonan; Reid, St Patrick; Clark, Neil R; Wang, Zichen; Fernandez, Nicolas F; Rouillard, Andrew D; Readhead, Ben; Tritsch, Sarah R; Hodos, Rachel; Hafner, Marc; Niepel, Mario; Sorger, Peter K; Dudley, Joel T; Bavari, Sina; Panchal, Rekha G; Ma'ayan, Avi

2016-01-01

The library of integrated network-based cellular signatures (LINCS) L1000 data set currently comprises of over a million gene expression profiles of chemically perturbed human cell lines. Through unique several intrinsic and extrinsic benchmarking schemes, we demonstrate that processing the L1000 data with the characteristic direction (CD) method significantly improves signal to noise compared with the MODZ method currently used to compute L1000 signatures. The CD processed L1000 signatures are served through a state-of-the-art web-based search engine application called L1000CDS 2 . The L1000CDS 2 search engine provides prioritization of thousands of small-molecule signatures, and their pairwise combinations, predicted to either mimic or reverse an input gene expression signature using two methods. The L1000CDS 2 search engine also predicts drug targets for all the small molecules profiled by the L1000 assay that we processed. Targets are predicted by computing the cosine similarity between the L1000 small-molecule signatures and a large collection of signatures extracted from the gene expression omnibus (GEO) for single-gene perturbations in mammalian cells. We applied L1000CDS 2 to prioritize small molecules that are predicted to reverse expression in 670 disease signatures also extracted from GEO, and prioritized small molecules that can mimic expression of 22 endogenous ligand signatures profiled by the L1000 assay. As a case study, to further demonstrate the utility of L1000CDS 2 , we collected expression signatures from human cells infected with Ebola virus at 30, 60 and 120 min. Querying these signatures with L1000CDS 2 we identified kenpaullone, a GSK3B/CDK2 inhibitor that we show, in subsequent experiments, has a dose-dependent efficacy in inhibiting Ebola infection in vitro without causing cellular toxicity in human cell lines. In summary, the L1000CDS 2 tool can be applied in many biological and biomedical settings, while improving the extraction of

Microgenomic analysis in skeletal muscle: expression signatures of individual fast and slow myofibers.

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Francesco Chemello

Full Text Available BACKGROUND: Skeletal muscle is a complex, versatile tissue composed of a variety of functionally diverse fiber types. Although the biochemical, structural and functional properties of myofibers have been the subject of intense investigation for the last decades, understanding molecular processes regulating fiber type diversity is still complicated by the heterogeneity of cell types present in the whole muscle organ. METHODOLOGY/PRINCIPAL FINDINGS: We have produced a first catalogue of genes expressed in mouse slow-oxidative (type 1 and fast-glycolytic (type 2B fibers through transcriptome analysis at the single fiber level (microgenomics. Individual fibers were obtained from murine soleus and EDL muscles and initially classified by myosin heavy chain isoform content. Gene expression profiling on high density DNA oligonucleotide microarrays showed that both qualitative and quantitative improvements were achieved, compared to results with standard muscle homogenate. First, myofiber profiles were virtually free from non-muscle transcriptional activity. Second, thousands of muscle-specific genes were identified, leading to a better definition of gene signatures in the two fiber types as well as the detection of metabolic and signaling pathways that are differentially activated in specific fiber types. Several regulatory proteins showed preferential expression in slow myofibers. Discriminant analysis revealed novel genes that could be useful for fiber type functional classification. CONCLUSIONS/SIGNIFICANCE: As gene expression analyses at the single fiber level significantly increased the resolution power, this innovative approach would allow a better understanding of the adaptive transcriptomic transitions occurring in myofibers under physiological and pathological conditions.

An eleven gene molecular signature for extra-capsular spread in oral squamous cell carcinoma serves as a prognosticator of outcome in patients without nodal metastases.

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Wang, Weining; Lim, Weng Khong; Leong, Hui Sun; Chong, Fui Teen; Lim, Tony K H; Tan, Daniel S W; Teh, Bin Tean; Iyer, N Gopalakrishna

2015-04-01

Extracapsular spread (ECS) is an important prognostic factor for oral squamous cell carcinoma (OSCC) and is used to guide management. In this study, we aimed to identify an expression profile signature for ECS in node-positive OSCC using data derived from two different sources: a cohort of OSCC patients from our institution (National Cancer Centre Singapore) and The Cancer Genome Atlas (TCGA) head and neck squamous cell carcinoma (HNSCC) cohort. We also sought to determine if this signature could serve as a prognostic factor in node negative cancers. Patients with a histological diagnosis of OSCC were identified from an institutional database and fresh tumor samples were retrieved. RNA was extracted and gene expression profiling was performed using the Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray platform. RNA sequence data and corresponding clinical data for the TCGA HNSCC cohort were downloaded from the TCGA Data Portal. All data analyses were conducted using R package and SPSS. We identified an 11 gene signature (GGH, MTFR1, CDKN3, PSRC1, SMIM3, CA9, IRX4, CPA3, ZSCAN16, CBX7 and ZFP3) which was robust in segregating tumors by ECS status. In node negative patients, patients harboring this ECS signature had a significantly worse overall survival (p=0.04). An eleven gene signature for ECS was derived. Our results also suggest that this signature is prognostic in a separate subset of patients with no nodal metastasis Further validation of this signature on other datasets and immunohistochemical studies are required to establish utility of this signature in stratifying early stage OSCC patients. Copyright © 2014 Elsevier Ltd. All rights reserved.

Testing an aflatoxin B1 gene signature in rat archival tissues.

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Merrick, B Alex; Auerbach, Scott S; Stockton, Patricia S; Foley, Julie F; Malarkey, David E; Sills, Robert C; Irwin, Richard D; Tice, Raymond R

2012-05-21

Archival tissues from laboratory studies represent a unique opportunity to explore the relationship between genomic changes and agent-induced disease. In this study, we evaluated the applicability of qPCR for detecting genomic changes in formalin-fixed, paraffin-embedded (FFPE) tissues by determining if a subset of 14 genes from a 90-gene signature derived from microarray data and associated with eventual tumor development could be detected in archival liver, kidney, and lung of rats exposed to aflatoxin B1 (AFB1) for 90 days in feed at 1 ppm. These tissues originated from the same rats used in the microarray study. The 14 genes evaluated were Adam8, Cdh13, Ddit4l, Mybl2, Akr7a3, Akr7a2, Fhit, Wwox, Abcb1b, Abcc3, Cxcl1, Gsta5, Grin2c, and the C8orf46 homologue. The qPCR FFPE liver results were compared to the original liver microarray data and to qPCR results using RNA from fresh frozen liver. Archival liver paraffin blocks yielded 30 to 50 μg of degraded RNA that ranged in size from 0.1 to 4 kB. qPCR results from FFPE and fresh frozen liver samples were positively correlated (p ≤ 0.05) by regression analysis and showed good agreement in direction and proportion of change with microarray data for 11 of 14 genes. All 14 transcripts could be amplified from FFPE kidney RNA except the glutamate receptor gene Grin2c; however, only Abcb1b was significantly upregulated from control. Abundant constitutive transcripts, S18 and β-actin, could be amplified from lung FFPE samples, but the narrow RNA size range (25-500 bp length) prevented consistent detection of target transcripts. Overall, a discrete gene signature derived from prior transcript profiling and representing cell cycle progression, DNA damage response, and xenosensor and detoxication pathways was successfully applied to archival liver and kidney by qPCR and indicated that gene expression changes in response to subchronic AFB1 exposure occurred predominantly in the liver, the primary target for AFB1-induced

A compendium of canine normal tissue gene expression.

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Joseph Briggs

Full Text Available BACKGROUND: Our understanding of disease is increasingly informed by changes in gene expression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue gene expression compendium with corresponding human cross-species analysis. METHODOLOGY/PRINCIPAL FINDINGS: The Affymetrix platform was utilized to catalogue gene expression signatures of 10 normal canine tissues including: liver, kidney, heart, lung, cerebrum, lymph node, spleen, jejunum, pancreas and skeletal muscle. The quality of the database was assessed in several ways. Organ defining gene sets were identified for each tissue and functional enrichment analysis revealed themes consistent with known physio-anatomic functions for each organ. In addition, a comparison of orthologous gene expression between matched canine and human normal tissues uncovered remarkable similarity. To demonstrate the utility of this dataset, novel canine gene annotations were established based on comparative analysis of dog and human tissue selective gene expression and manual curation of canine probeset mapping. Public access, using infrastructure identical to that currently in use for human normal tissues, has been established and allows for additional comparisons across species. CONCLUSIONS/SIGNIFICANCE: These data advance our understanding of the canine genome through a comprehensive analysis of gene expression in a diverse set of tissues, contributing to improved functional annotation that has been lacking. Importantly, it will be used to inform future studies of disease in the dog as a model for human translational research and provides a novel resource to the community at large.

Clinicopathologic and gene expression parameters predict liver cancer prognosis

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Hao, Ke; Zhong, Hua; Greenawalt, Danielle; Ferguson, Mark D; Ng, Irene O; Sham, Pak C; Poon, Ronnie T; Molony, Cliona; Schadt, Eric E; Dai, Hongyue; Luk, John M; Lamb, John; Zhang, Chunsheng; Xie, Tao; Wang, Kai; Zhang, Bin; Chudin, Eugene; Lee, Nikki P; Mao, Mao

2011-01-01

The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome

76 FR 62000 - Express Mail Domestic Postage Refund Policy and Waiver of Signature

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2011-10-06

... POSTAL SERVICE 39 CFR Part 111 Express Mail Domestic Postage Refund Policy and Waiver of Signature... days to 30 days after the date of mailing, and to change the Express Mail ``waiver of signature'' standard for domestic items by obtaining an addressee's signature only when the mailer selects the...

A gene expression signature of Retinoblastoma loss-of-function predicts resistance to neoadjuvant chemotherapy in ER-positive/HER2-positive breast cancer patients.

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Risi, Emanuela; Grilli, Andrea; Migliaccio, Ilenia; Biagioni, Chiara; McCartney, Amelia; Guarducci, Cristina; Bonechi, Martina; Benelli, Matteo; Vitale, Stefania; Biganzoli, Laura; Bicciato, Silvio; Di Leo, Angelo; Malorni, Luca

2018-07-01

HER2-positive (HER2+) breast cancers show heterogeneous response to chemotherapy, with the ER-positive (ER+) subgroup deriving less benefit. Loss of retinoblastoma tumor suppressor gene (RB1) function has been suggested as a cardinal feature of breast cancers that are more sensitive to chemotherapy and conversely resistant to CDK4/6 inhibitors. We performed a retrospective analysis exploring RBsig, a gene signature of RB loss, as a potential predictive marker of response to neoadjuvant chemotherapy in ER+/HER2+ breast cancer patients. We selected clinical trials of neoadjuvant chemotherapy ± anti-HER2 therapy in HER2+ breast cancer patients with available information on gene expression data, hormone receptor status, and pathological complete response (pCR) rates. RBsig expression was computed in silico and correlated with pCR. Ten studies fulfilled the inclusion criteria and were included in the analysis (514 patients). Overall, of 211 ER+/HER2+ breast cancer patients, 49 achieved pCR (23%). The pCR rate following chemotherapy ± anti-HER2 drugs in patients with RBsig low expression was significantly lower compared to patients with RBsig high expression (16% vs. 30%, respectively; Fisher's exact test p = 0.015). The area under the ROC curve (AUC) was 0.62 (p = 0.005). In the 303 ER-negative (ER-)/HER2+ patients treated with chemotherapy ± anti-HER2 drugs, the pCR rate was 43%. No correlation was found between RBsig expression and pCR rate in this group. Low expression of RBsig identifies a subset of ER+/HER2+ patients with low pCR rates following neoadjuvant chemotherapy ± anti-HER2 therapy. These patients may potentially be spared chemotherapy in favor of anti-HER2, endocrine therapy, and CDK 4/6 inhibitor combinations.

Gene Expression Programs in Response to Hypoxia: Cell Type Specificity and Prognostic Significance in Human Cancers.

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2006-01-01

Full Text Available BACKGROUND: Inadequate oxygen (hypoxia triggers a multifaceted cellular response that has important roles in normal physiology and in many human diseases. A transcription factor, hypoxia-inducible factor (HIF, plays a central role in the hypoxia response; its activity is regulated by the oxygen-dependent degradation of the HIF-1alpha protein. Despite the ubiquity and importance of hypoxia responses, little is known about the variation in the global transcriptional response to hypoxia among different cell types or how this variation might relate to tissue- and cell-specific diseases. METHODS AND FINDINGS: We analyzed the temporal changes in global transcript levels in response to hypoxia in primary renal proximal tubule epithelial cells, breast epithelial cells, smooth muscle cells, and endothelial cells with DNA microarrays. The extent of the transcriptional response to hypoxia was greatest in the renal tubule cells. This heightened response was associated with a uniquely high level of HIF-1alpha RNA in renal cells, and it could be diminished by reducing HIF-1alpha expression via RNA interference. A gene-expression signature of the hypoxia response, derived from our studies of cultured mammary and renal tubular epithelial cells, showed coordinated variation in several human cancers, and was a strong predictor of clinical outcomes in breast and ovarian cancers. In an analysis of a large, published gene-expression dataset from breast cancers, we found that the prognostic information in the hypoxia signature was virtually independent of that provided by the previously reported wound signature and more predictive of outcomes than any of the clinical parameters in current use. CONCLUSIONS: The transcriptional response to hypoxia varies among human cells. Some of this variation is traceable to variation in expression of the HIF1A gene. A gene-expression signature of the cellular response to hypoxia is associated with a significantly poorer prognosis

Identification of upstream transcription factors (TFs) for expression signature genes in breast cancer.

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Zang, Hongyan; Li, Ning; Pan, Yuling; Hao, Jingguang

2017-03-01

Breast cancer is a common malignancy among women with a rising incidence. Our intention was to detect transcription factors (TFs) for deeper understanding of the underlying mechanisms of breast cancer. Integrated analysis of gene expression datasets of breast cancer was performed. Then, functional annotation of differentially expressed genes (DEGs) was conducted, including Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, TFs were identified and a global transcriptional regulatory network was constructed. Seven publically available GEO datasets were obtained, and a set of 1196 DEGs were identified (460 up-regulated and 736 down-regulated). Functional annotation results showed that cell cycle was the most significantly enriched pathway, which was consistent with the fact that cell cycle is closely related to various tumors. Fifty-three differentially expressed TFs were identified, and the regulatory networks consisted of 817 TF-target interactions between 46 TFs and 602 DEGs in the context of breast cancer. Top 10 TFs covering the most downstream DEGs were SOX10, NFATC2, ZNF354C, ARID3A, BRCA1, FOXO3, GATA3, ZEB1, HOXA5 and EGR1. The transcriptional regulatory networks could enable a better understanding of regulatory mechanisms of breast cancer pathology and provide an opportunity for the development of potential therapy.

Motif signatures of transcribed enhancers

KAUST Repository

Kleftogiannis, Dimitrios

2017-09-14

In mammalian cells, transcribed enhancers (TrEn) play important roles in the initiation of gene expression and maintenance of gene expression levels in spatiotemporal manner. One of the most challenging questions in biology today is how the genomic characteristics of enhancers relate to enhancer activities. This is particularly critical, as several recent studies have linked enhancer sequence motifs to specific functional roles. To date, only a limited number of enhancer sequence characteristics have been investigated, leaving space for exploring the enhancers genomic code in a more systematic way. To address this problem, we developed a novel computational method, TELS, aimed at identifying predictive cell type/tissue specific motif signatures. We used TELS to compile a comprehensive catalog of motif signatures for all known TrEn identified by the FANTOM5 consortium across 112 human primary cells and tissues. Our results confirm that distinct cell type/tissue specific motif signatures characterize TrEn. These signatures allow discriminating successfully a) TrEn from random controls, proxy of non-enhancer activity, and b) cell type/tissue specific TrEn from enhancers expressed and transcribed in different cell types/tissues. TELS codes and datasets are publicly available at http://www.cbrc.kaust.edu.sa/TELS.

Effect of chemical mutagens and carcinogens on gene expression profiles in human TK6 cells.

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Lode Godderis

Full Text Available Characterization of toxicogenomic signatures of carcinogen exposure holds significant promise for mechanistic and predictive toxicology. In vitro transcriptomic studies allow the comparison of the response to chemicals with diverse mode of actions under controlled experimental conditions. We conducted an in vitro study in TK6 cells to characterize gene expression signatures of exposure to 15 genotoxic carcinogens frequently used in European industries. We also examined the dose-responsive changes in gene expression, and perturbation of biochemical pathways in response to these carcinogens. TK6 cells were exposed at 3 dose levels for 24 h with and without S9 human metabolic mix. Since S9 had an impact on gene expression (885 genes, we analyzed the gene expression data from cells cultures incubated with S9 and without S9 independently. The ribosome pathway was affected by all chemical-dose combinations. However in general, no similar gene expression was observed among carcinogens. Further, pathways, i.e. cell cycle, DNA repair mechanisms, RNA degradation, that were common within sets of chemical-dose combination were suggested by clustergram. Linear trends in dose-response of gene expression were observed for Trichloroethylene, Benz[a]anthracene, Epichlorohydrin, Benzene, and Hydroquinone. The significantly altered genes were involved in the regulation of (anti- apoptosis, maintenance of cell survival, tumor necrosis factor-related pathways and immune response, in agreement with several other studies. Similarly in S9+ cultures, Benz[a]pyrene, Styrene and Trichloroethylene each modified over 1000 genes at high concentrations. Our findings expand our understanding of the transcriptomic response to genotoxic carcinogens, revealing the alteration of diverse sets of genes and pathways involved in cellular homeostasis and cell cycle control.

Two-gene signature improves the discriminatory power of IASLC/ATS/ERS classification to predict the survival of patients with early-stage lung adenocarcinoma

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Sun Y

2016-07-01

Full Text Available Yifeng Sun,1,* Likun Hou,2,* Yu Yang,1 Huikang Xie,2 Yang Yang,1 Zhigang Li,1 Heng Zhao,1 Wen Gao,3 Bo Su4 1Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiaotong University, 2Department of Pathology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 3Department of Thoracic Surgery, Shanghai Huadong Hospital, Fudan University School of Medicine, Shanghai, 4Central Lab, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, People’s Republic of China *These authors contributed equally to this work Background: In this study, we investigated the contribution of a gene expression–based signature (composed of BAG1, BRCA1, CDC6, CDK2AP1, ERBB3, FUT3, IL11, LCK, RND3, SH3BGR to survival prediction for early-stage lung adenocarcinoma categorized by the new International Association for the Study of Lung Cancer (IASLC/the American Thoracic Society (ATS/the European Respiratory Society (ERS classification. We also aimed to verify whether gene signature improves the risk discrimination of IASLC/ATS/ERS classification in early-stage lung adenocarcinoma. Patients and methods: Total RNA was extracted from 93 patients with pathologically confirmed TNM stage Ia and Ib lung adenocarcinoma. The mRNA expression levels of ten genes in the signature (BAG1, BRCA1, CDC6, CDK2AP1, ERBB3, FUT3, IL11, LCK, RND3, and SH3BGR were detected using real-time polymerase chain reaction. Each patient was categorized according to the new IASLC/ATS/ERS classification by accessing hematoxylin–eosin-stained slides. The corresponding Kaplan–Meier survival analysis by the log-rank statistic, multivariate Cox proportional hazards modeling, and c-index calculation were conducted using the programming language R (Version 2.15.1 with the “risksetROC” package. Results: The multivariate analysis demonstrated that the risk factor of the ten-gene expression signature can significantly improve the discriminatory

Unsupervised Bayesian linear unmixing of gene expression microarrays.

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Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

2013-03-19

This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores

Cancer as quasi-attractor in the gene expression phase space

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Giuliani, A.

2017-09-01

It takes no more than 250 tissue types to build up a metazoan, and each tissue has a specific and largely invariant gene expression signature. This implies the `viable configurations' correspondent to a given activated/inactivated expression pattern over the entire genome are very few. This points to the presence of few `low energy deep valleys' correspondent to the allowed states of the system and is a direct consequence of the fact genes do not work by alone but embedded into genetic expression networks. Statistical thermodynamics formalism focusing on the changes in the degree of correlation of the studied systems allows to detect transition behavior in gene expression phase space resembling the phase transition of physical-chemistry studies. In this realm cancer can be intended as a sort of `parasite' sub-attractor of the corresponding healthy tissue that, in the case of disease, is `kinetically entrapped' into a sub-optimal solution. The consequences of such a state of affair for cancer therapies are potentially huge.

A biology-driven approach identifies the hypoxia gene signature as a predictor of the outcome of neuroblastoma patients

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Fardin Paolo

2010-07-01

Full Text Available Abstract Background Hypoxia is a condition of low oxygen tension occurring in the tumor microenvironment and it is related to poor prognosis in human cancer. To examine the relationship between hypoxia and neuroblastoma, we generated and tested an in vitro derived hypoxia gene signature for its ability to predict patients' outcome. Results We obtained the gene expression profile of 11 hypoxic neuroblastoma cell lines and we derived a robust 62 probesets signature (NB-hypo taking advantage of the strong discriminating power of the l1-l2 feature selection technique combined with the analysis of differential gene expression. We profiled gene expression of the tumors of 88 neuroblastoma patients and divided them according to the NB-hypo expression values by K-means clustering. The NB-hypo successfully stratifies the neuroblastoma patients into good and poor prognosis groups. Multivariate Cox analysis revealed that the NB-hypo is a significant independent predictor after controlling for commonly used risk factors including the amplification of MYCN oncogene. NB-hypo increases the resolution of the MYCN stratification by dividing patients with MYCN not amplified tumors in good and poor outcome suggesting that hypoxia is associated with the aggressiveness of neuroblastoma tumor independently from MYCN amplification. Conclusions Our results demonstrate that the NB-hypo is a novel and independent prognostic factor for neuroblastoma and support the view that hypoxia is negatively correlated with tumors' outcome. We show the power of the biology-driven approach in defining hypoxia as a critical molecular program in neuroblastoma and the potential for improvement in the current criteria for risk stratification.

Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays.

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Thomas Sanford

Full Text Available To evaluate the accuracy of the sub-classification of renal cortical neoplasms using molecular signatures.A search of publicly available databases was performed to identify microarray datasets with multiple histologic sub-types of renal cortical neoplasms. Meta-analytic techniques were utilized to identify differentially expressed genes for each histologic subtype. The lists of genes obtained from the meta-analysis were used to create predictive signatures through the use of a pair-based method. These signatures were organized into an algorithm to sub-classify renal neoplasms. The use of these signatures according to our algorithm was validated on several independent datasets.We identified three Gene Expression Omnibus datasets that fit our criteria to develop a training set. All of the datasets in our study utilized the Affymetrix platform. The final training dataset included 149 samples represented by the four most common histologic subtypes of renal cortical neoplasms: 69 clear cell, 41 papillary, 16 chromophobe, and 23 oncocytomas. When validation of our signatures was performed on external datasets, we were able to correctly classify 68 of the 72 samples (94%. The correct classification by subtype was 19/20 (95% for clear cell, 14/14 (100% for papillary, 17/19 (89% for chromophobe, 18/19 (95% for oncocytomas.Through the use of meta-analytic techniques, we were able to create an algorithm that sub-classified renal neoplasms on a molecular level with 94% accuracy across multiple independent datasets. This algorithm may aid in selecting molecular therapies and may improve the accuracy of subtyping of renal cortical tumors.

Integrative Analysis of DCE-MRI and Gene Expression Profiles in Construction of a Gene Classifier for Assessment of Hypoxia-Related Risk of Chemoradiotherapy Failure in Cervical Cancer

DEFF Research Database (Denmark)

Fjeldbo, Christina S; Julin, Cathinka H; Lando, Malin

2016-01-01

platforms. The prognostic value was independent of existing clinical markers, regardless of clinical endpoints. CONCLUSIONS: A robust DCE-MRI-associated gene classifier has been constructed that may be used to achieve an early indication of patients' risk of hypoxia-related chemoradiotherapy failure.......PURPOSE: A 31-gene expression signature reflected in dynamic contrast enhanced (DCE)-MR images and correlated with hypoxia-related aggressiveness in cervical cancer was identified in previous work. We here aimed to construct a dichotomous classifier with key signature genes and a predefined...... as an indicator of hypoxia. RESULTS: Classifier candidates were constructed by integrative analysis of ABrix and gene expression profiles in the training cohort and evaluated by a leave-one-out cross-validation approach. On the basis of their ability to separate patients correctly according to hypoxia status, a 6...

A microRNA expression signature of the postprandial state in response to a high-saturated-fat challenge.

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Lopez, Sergio; Bermudez, Beatriz; Montserrat-de la Paz, Sergio; Abia, Rocio; Muriana, Francisco J G

2018-07-01

The postprandial hypertriglyceridemia is an important and largely silent disturbance involved in the genesis of numerous pathological conditions. Exaggerated and prolonged states of postprandial hypertriglyceridemia are frequently related to the ingestion of meals enriched in saturated fatty acids (SFAs). MicroRNAs are noncoding RNAs that function as gene regulators and play significant roles in both health and disease. However, differential miRNA expression between fasting and postprandial states has never been elucidated. Here, we studied the impact of a high-saturated-fat meal, mainly rich in palmitic acid, on the miRNA signature in peripheral blood mononuclear cells (PBMCs) of nine male healthy individuals in the postprandial period by using a two-step analysis: miRNA array and validation through quantitative real-time polymerase chain reaction. Compared with miRNA expression signature in PBMCs at fasting, 36 miRNAs were down-regulated and 43 miRNAs were up-regulated in PBMCs at postprandial hypertriglyceridemic peak. Six chromosomes (3, 7, 8, 12, 14 and 19) had nearly half (48.1%) of dysregulated miRNA-gene-containing regions. Down-regulated miR-300 and miR-369-3p and up-regulated miR-495-3p, miR-129-5p and miR-7-2-3p had the highest number of target genes. The differentially expressed miRNAs and their predicted target genes involved pathways in cancer, MAPK signaling pathway, endocytosis and axon guidance. Only down-regulated miRNAs notably targeted PI3K-Akt signaling pathways, whereas only up-regulated miRNAs targeted focal adhesion, Wnt signaling pathway, transcriptional misregulation in cancer and ubiquitin-mediated proteolysis. This is the first study of miRNA expression analysis of human PBMCs during postprandial hypertriglyceridemia and offers insight into new potential mechanisms by which dietary SFAs influence health or disease. Copyright © 2018 Elsevier Inc. All rights reserved.

Transcriptional profiling of cattle infected with Trypanosoma congolense highlights gene expression signatures underlying trypanotolerance and trypanosusceptibility

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Naessens Jan

2009-05-01

Full Text Available Abstract Background African animal trypanosomiasis (AAT caused by tsetse fly-transmitted protozoa of the genus Trypanosoma is a major constraint on livestock and agricultural production in Africa and is among the top ten global cattle diseases impacting on the poor. Here we show that a functional genomics approach can be used to identify temporal changes in host peripheral blood mononuclear cell (PBMC gene expression due to disease progression. We also show that major gene expression differences exist between cattle from trypanotolerant and trypanosusceptible breeds. Using bovine long oligonucleotide microarrays and real time quantitative reverse transcription PCR (qRT-PCR validation we analysed PBMC gene expression in naïve trypanotolerant and trypanosusceptible cattle experimentally challenged with Trypanosoma congolense across a 34-day infection time course. Results Trypanotolerant N'Dama cattle displayed a rapid and distinct transcriptional response to infection, with a ten-fold higher number of genes differentially expressed at day 14 post-infection compared to trypanosusceptible Boran cattle. These analyses identified coordinated temporal gene expression changes for both breeds in response to trypanosome infection. In addition, a panel of genes were identified that showed pronounced differences in gene expression between the two breeds, which may underlie the phenomena of trypanotolerance and trypanosusceptibility. Gene ontology (GO analysis demonstrate that the products of these genes may contribute to increased mitochondrial mRNA translational efficiency, a more pronounced B cell response, an elevated activation status and a heightened response to stress in trypanotolerant cattle. Conclusion This study has revealed an extensive and diverse range of cellular processes that are altered temporally in response to trypanosome infection in African cattle. Results indicate that the trypanotolerant N'Dama cattle respond more rapidly and with a

Comprehensive expression profiling of tumor cell lines identifies molecular signatures of melanoma progression.

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Byungwoo Ryu

2007-07-01

Full Text Available Gene expression profiling has revolutionized our ability to molecularly classify primary human tumors and significantly enhanced the development of novel tumor markers and therapies; however, progress in the diagnosis and treatment of melanoma over the past 3 decades has been limited, and there is currently no approved therapy that significantly extends lifespan in patients with advanced disease. Profiling studies of melanoma to date have been inconsistent due to the heterogeneous nature of this malignancy and the limited availability of informative tissue specimens from early stages of disease.In order to gain an improved understanding of the molecular basis of melanoma progression, we have compared gene expression profiles from a series of melanoma cell lines representing discrete stages of malignant progression that recapitulate critical characteristics of the primary lesions from which they were derived. Here we describe the unsupervised hierarchical clustering of profiling data from melanoma cell lines and melanocytes. This clustering identifies two distinctive molecular subclasses of melanoma segregating aggressive metastatic tumor cell lines from less-aggressive primary tumor cell lines. Further analysis of expression signatures associated with melanoma progression using functional annotations categorized these transcripts into three classes of genes: 1 Upregulation of activators of cell cycle progression, DNA replication and repair (CDCA2, NCAPH, NCAPG, NCAPG2, PBK, NUSAP1, BIRC5, ESCO2, HELLS, MELK, GINS1, GINS4, RAD54L, TYMS, and DHFR, 2 Loss of genes associated with cellular adhesion and melanocyte differentiation (CDH3, CDH1, c-KIT, PAX3, CITED1/MSG-1, TYR, MELANA, MC1R, and OCA2, 3 Upregulation of genes associated with resistance to apoptosis (BIRC5/survivin. While these broad classes of transcripts have previously been implicated in the progression of melanoma and other malignancies, the specific genes identified within each class

Mycobacterium tuberculosis strains exhibit differential and strain-specific molecular signatures in pulmonary epithelial cells.

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Mvubu, Nontobeko Eunice; Pillay, Balakrishna; Gamieldien, Junaid; Bishai, William; Pillay, Manormoney

2016-12-01

Although pulmonary epithelial cells are integral to innate and adaptive immune responses during Mycobacterium tuberculosis infection, global transcriptomic changes in these cells remain largely unknown. Changes in gene expression induced in pulmonary epithelial cells infected with M. tuberculosis F15/LAM4/KZN, F11, F28, Beijing and Unique genotypes were investigated by RNA sequencing (RNA-Seq). The Illumina HiSeq 2000 platform generated 50 bp reads that were mapped to the human genome (Hg19) using Tophat (2.0.10). Differential gene expression induced by the different strains in infected relative to the uninfected cells was quantified and compared using Cufflinks (2.1.0) and MeV (4.0.9), respectively. Gene expression varied among the strains with the total number of genes as follows: F15/LAM4/KZN (1187), Beijing (1252), F11 (1639), F28 (870), Unique (886) and H37Rv (1179). A subset of 292 genes was commonly induced by all strains, where 52 genes were down-regulated while 240 genes were up-regulated. Differentially expressed genes were compared among the strains and the number of induced strain-specific gene signatures were as follows: F15/LAM4/KZN (138), Beijing (52), F11 (255), F28 (55), Unique (186) and H37Rv (125). Strain-specific molecular gene signatures associated with functional pathways were observed only for the Unique and H37Rv strains while certain biological functions may be associated with other strain signatures. This study demonstrated that strains of M. tuberculosis induce differential gene expression and strain-specific molecular signatures in pulmonary epithelial cells. Specific signatures induced by clinical strains of M. tuberculosis can be further explored for novel host-associated biomarkers and adjunctive immunotherapies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Application of affymetrix array and massively parallel signature sequencing for identification of genes involved in prostate cancer progression

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Oudes, Asa J; Roach, Jared C; Walashek, Laura S; Eichner, Lillian J; True, Lawrence D; Vessella, Robert L; Liu, Alvin Y

2005-01-01

Affymetrix GeneChip Array and Massively Parallel Signature Sequencing (MPSS) are two high throughput methodologies used to profile transcriptomes. Each method has certain strengths and weaknesses; however, no comparison has been made between the data derived from Affymetrix arrays and MPSS. In this study, two lineage-related prostate cancer cell lines, LNCaP and C4-2, were used for transcriptome analysis with the aim of identifying genes associated with prostate cancer progression. Affymetrix GeneChip array and MPSS analyses were performed. Data was analyzed with GeneSpring 6.2 and in-house perl scripts. Expression array results were verified with RT-PCR. Comparison of the data revealed that both technologies detected genes the other did not. In LNCaP, 3,180 genes were only detected by Affymetrix and 1,169 genes were only detected by MPSS. Similarly, in C4-2, 4,121 genes were only detected by Affymetrix and 1,014 genes were only detected by MPSS. Analysis of the combined transcriptomes identified 66 genes unique to LNCaP cells and 33 genes unique to C4-2 cells. Expression analysis of these genes in prostate cancer specimens showed CA1 to be highly expressed in bone metastasis but not expressed in primary tumor and EPHA7 to be expressed in normal prostate and primary tumor but not bone metastasis. Our data indicates that transcriptome profiling with a single methodology will not fully assess the expression of all genes in a cell line. A combination of transcription profiling technologies such as DNA array and MPSS provides a more robust means to assess the expression profile of an RNA sample. Finally, genes that were differentially expressed in cell lines were also differentially expressed in primary prostate cancer and its metastases

Experimentally-derived fibroblast gene signatures identify molecular pathways associated with distinct subsets of systemic sclerosis patients in three independent cohorts.

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Michael E Johnson

Full Text Available Genome-wide expression profiling in systemic sclerosis (SSc has identified four 'intrinsic' subsets of disease (fibroproliferative, inflammatory, limited, and normal-like, each of which shows deregulation of distinct signaling pathways; however, the full set of pathways contributing to this differential gene expression has not been fully elucidated. Here we examine experimentally derived gene expression signatures in dermal fibroblasts for thirteen different signaling pathways implicated in SSc pathogenesis. These data show distinct and overlapping sets of genes induced by each pathway, allowing for a better understanding of the molecular relationship between profibrotic and immune signaling networks. Pathway-specific gene signatures were analyzed across a compendium of microarray datasets consisting of skin biopsies from three independent cohorts representing 80 SSc patients, 4 morphea, and 26 controls. IFNα signaling showed a strong association with early disease, while TGFβ signaling spanned the fibroproliferative and inflammatory subsets, was associated with worse MRSS, and was higher in lesional than non-lesional skin. The fibroproliferative subset was most strongly associated with PDGF signaling, while the inflammatory subset demonstrated strong activation of innate immune pathways including TLR signaling upstream of NF-κB. The limited and normal-like subsets did not show associations with fibrotic and inflammatory mediators such as TGFβ and TNFα. The normal-like subset showed high expression of genes associated with lipid signaling, which was absent in the inflammatory and limited subsets. Together, these data suggest a model by which IFNα is involved in early disease pathology, and disease severity is associated with active TGFβ signaling.

lncRNA Gene Signatures for Prediction of Breast Cancer Intrinsic Subtypes and Prognosis

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Silu Zhang

2018-01-01

Full Text Available Background: Breast cancer is intrinsically heterogeneous and is commonly classified into four main subtypes associated with distinct biological features and clinical outcomes. However, currently available data resources and methods are limited in identifying molecular subtyping on protein-coding genes, and little is known about the roles of long non-coding RNAs (lncRNAs, which occupies 98% of the whole genome. lncRNAs may also play important roles in subgrouping cancer patients and are associated with clinical phenotypes. Methods: The purpose of this project was to identify lncRNA gene signatures that are associated with breast cancer subtypes and clinical outcomes. We identified lncRNA gene signatures from The Cancer Genome Atlas (TCGA RNAseq data that are associated with breast cancer subtypes by an optimized 1-Norm SVM feature selection algorithm. We evaluated the prognostic performance of these gene signatures with a semi-supervised principal component (superPC method. Results: Although lncRNAs can independently predict breast cancer subtypes with satisfactory accuracy, a combined gene signature including both coding and non-coding genes will give the best clinically relevant prediction performance. We highlighted eight potential biomarkers (three from coding genes and five from non-coding genes that are significantly associated with survival outcomes. Conclusion: Our proposed methods are a novel means of identifying subtype-specific coding and non-coding potential biomarkers that are both clinically relevant and biologically significant.

Evaluation of data discretization methods to derive platform independent isoform expression signatures for multi-class tumor subtyping.

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Jung, Segun; Bi, Yingtao; Davuluri, Ramana V

2015-01-01

Many supervised learning algorithms have been applied in deriving gene signatures for patient stratification from gene expression data. However, transferring the multi-gene signatures from one analytical platform to another without loss of classification accuracy is a major challenge. Here, we compared three unsupervised data discretization methods--Equal-width binning, Equal-frequency binning, and k-means clustering--in accurately classifying the four known subtypes of glioblastoma multiforme (GBM) when the classification algorithms were trained on the isoform-level gene expression profiles from exon-array platform and tested on the corresponding profiles from RNA-seq data. We applied an integrated machine learning framework that involves three sequential steps; feature selection, data discretization, and classification. For models trained and tested on exon-array data, the addition of data discretization step led to robust and accurate predictive models with fewer number of variables in the final models. For models trained on exon-array data and tested on RNA-seq data, the addition of data discretization step dramatically improved the classification accuracies with Equal-frequency binning showing the highest improvement with more than 90% accuracies for all the models with features chosen by Random Forest based feature selection. Overall, SVM classifier coupled with Equal-frequency binning achieved the best accuracy (> 95%). Without data discretization, however, only 73.6% accuracy was achieved at most. The classification algorithms, trained and tested on data from the same platform, yielded similar accuracies in predicting the four GBM subgroups. However, when dealing with cross-platform data, from exon-array to RNA-seq, the classifiers yielded stable models with highest classification accuracies on data transformed by Equal frequency binning. The approach presented here is generally applicable to other cancer types for classification and identification of

Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes

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Amanda M. Ackermann

2016-03-01

Conclusions: We have determined the genetic landscape of human α- and β-cells based on chromatin accessibility and transcript levels, which allowed for detection of novel α- and β-cell signature genes not previously known to be expressed in islets. Using fine-mapping of open chromatin, we have identified thousands of potential cis-regulatory elements that operate in an endocrine cell type-specific fashion.

Pervasive Effects of Aging on Gene Expression in Wild Wolves

Science.gov (United States)

Charruau, Pauline; Johnston, Rachel A.; Stahler, Daniel R.; Lea, Amanda; Snyder-Mackler, Noah; Smith, Douglas W.; vonHoldt, Bridgett M.; Cole, Steven W.; Tung, Jenny; Wayne, Robert K.

2016-01-01

Abstract Gene expression levels change as an individual ages and responds to environmental conditions. With the exception of humans, such patterns have principally been studied under controlled conditions, overlooking the array of developmental and environmental influences that organisms encounter under conditions in which natural selection operates. We used high-throughput RNA sequencing (RNA-Seq) of whole blood to assess the relative impacts of social status, age, disease, and sex on gene expression levels in a natural population of gray wolves (Canis lupus). Our findings suggest that age is broadly associated with gene expression levels, whereas other examined factors have minimal effects on gene expression patterns. Further, our results reveal evolutionarily conserved signatures of senescence, such as immunosenescence and metabolic aging, between wolves and humans despite major differences in life history and environment. The effects of aging on gene expression levels in wolves exhibit conservation with humans, but the more rapid expression differences observed in aging wolves is evolutionarily appropriate given the species’ high level of extrinsic mortality due to intraspecific aggression. Some expression changes that occur with age can facilitate physical age-related changes that may enhance fitness in older wolves. However, the expression of these ancestral patterns of aging in descendant modern dogs living in highly modified domestic environments may be maladaptive and cause disease. This work provides evolutionary insight into aging patterns observed in domestic dogs and demonstrates the applicability of studying natural populations to investigate the mechanisms of aging. PMID:27189566

Gene expression signature in organized and growth arrested mammaryacini predicts good outcome in breast cancer

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Fournier, Marcia V.; Martin, Katherine J.; Kenny, Paraic A.; Xhaja, Kris; Bosch, Irene; Yaswen, Paul; Bissell, Mina J.

2006-02-08

To understand how non-malignant human mammary epithelial cells (HMEC) transit from a disorganized proliferating to an organized growth arrested state, and to relate this process to the changes that occur in breast cancer, we studied gene expression changes in non-malignant HMEC grown in three-dimensional cultures, and in a previously published panel of microarray data for 295 breast cancer samples. We hypothesized that the gene expression pattern of organized and growth arrested mammary acini would share similarities with breast tumors with good prognoses. Using Affymetrix HG-U133A microarrays, we analyzed the expression of 22,283 gene transcripts in two HMEC cell lines, 184 (finite life span) and HMT3522 S1 (immortal non-malignant), on successive days post-seeding in a laminin-rich extracellular matrix assay. Both HMECs underwent growth arrest in G0/G1 and differentiated into polarized acini between days 5 and 7. We identified gene expression changes with the same temporal pattern in both lines. We show that genes that are significantly lower in the organized, growth arrested HMEC than in their proliferating counterparts can be used to classify breast cancer patients into poor and good prognosis groups with high accuracy. This study represents a novel unsupervised approach to identifying breast cancer markers that may be of use clinically.

The effects of lymph node status on predicting outcome in ER+ /HER2- tamoxifen treated breast cancer patients using gene signatures

International Nuclear Information System (INIS)

Cockburn, Jessica G.; Hallett, Robin M.; Gillgrass, Amy E.; Dias, Kay N.; Whelan, T.; Levine, M. N.; Hassell, John A.; Bane, Anita

2016-01-01

Lymph node (LN) status is the most important prognostic variable used to guide ER positive (+) breast cancer treatment. While a positive nodal status is traditionally associated with a poor prognosis, a subset of these patients respond well to treatment and achieve long-term survival. Several gene signatures have been established as a means of predicting outcome of breast cancer patients, but the development and indication for use of these assays varies. Here we compare the capacity of two approved gene signatures and a third novel signature to predict outcome in distinct LN negative (-) and LN+ populations. We also examine biological differences between tumours associated with LN- and LN+ disease. Gene expression data from publically available data sets was used to compare the ability of Oncotype DX and Prosigna to predict Distant Metastasis Free Survival (DMFS) using an in silico platform. A novel gene signature (Ellen) was developed by including patients with both LN- and LN+ disease and using Prediction Analysis of Microarrays (PAM) software. Gene Set Enrichment Analysis (GSEA) was used to determine biological pathways associated with patient outcome in both LN- and LN+ tumors. The Oncotype DX gene signature, which only used LN- patients during development, significantly predicted outcome in LN- patients, but not LN+ patients. The Prosigna gene signature, which included both LN- and LN+ patients during development, predicted outcome in both LN- and LN+ patient groups. Ellen was also able to predict outcome in both LN- and LN+ patient groups. GSEA suggested that epigenetic modification may be related to poor outcome in LN- disease, whereas immune response may be related to good outcome in LN+ disease. We demonstrate the importance of incorporating lymph node status during the development of prognostic gene signatures. Ellen may be a useful tool to predict outcome of patients regardless of lymph node status, or for those with unknown lymph node status. Finally we

Molecular signatures associated with HCV-induced hepatocellular carcinoma and liver metastasis.

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Valeria De Giorgi

Full Text Available Hepatocellular carcinomas (HCCs are a heterogeneous group of tumors that differ in risk factors and genetic alterations. In Italy, particularly Southern Italy, chronic hepatitis C virus (HCV infection represents the main cause of HCC. Using high-density oligoarrays, we identified consistent differences in gene-expression between HCC and normal liver tissue. Expression patterns in HCC were also readily distinguishable from those associated with liver metastases. To characterize molecular events relevant to hepatocarcinogenesis and identify biomarkers for early HCC detection, gene expression profiling of 71 liver biopsies from HCV-related primary HCC and corresponding HCV-positive non-HCC hepatic tissue, as well as gastrointestinal liver metastases paired with the apparently normal peri-tumoral liver tissue, were compared to 6 liver biopsies from healthy individuals. Characteristic gene signatures were identified when normal tissue was compared with HCV-related primary HCC, corresponding HCV-positive non-HCC as well as gastrointestinal liver metastases. Pathway analysis classified the cellular and biological functions of the genes differentially expressed as related to regulation of gene expression and post-translational modification in HCV-related primary HCC; cellular Growth and Proliferation, and Cell-To-Cell Signaling and Interaction in HCV-related non HCC samples; Cellular Growth and Proliferation and Cell Cycle in metastasis. Also characteristic gene signatures were identified of HCV-HCC progression for early HCC diagnosis.A diagnostic molecular signature complementing conventional pathologic assessment was identified.

DNA copy-number alterations underlie gene expression differences between microsatellite stable and unstable colorectal cancers

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Jorissen, Robert N; Lipton, Lara; Gibbs, Peter

2008-01-01

Purpose: About 15% of colorectal cancers harbor microsatellite instability (MSI). MSI-associated gene expression changes have been identified in colorectal cancers, but little overlap exists between signatures hindering an assessment of overall consistency. Little is known about the causes...... and downstream effects of differential gene expression. Experimental Design: DNA microarray data on 89 MSI and 140 microsatellite-stable (MSS) colorectal cancers from this study and 58 MSI and 77 MSS cases from three published reports were randomly divided into test and training sets. MSI-associated gene......-number data. Results: MSI-associated gene expression changes in colorectal cancers were found to be highly consistent across multiple studies of primary tumors and cancer cell lines from patients of different ethnicities (P

HPV status, cancer stem cell marker expression, hypoxia gene signatures and tumour volume identify good prognosis subgroups in patients with HNSCC after primary radiochemotherapy: A multicentre retrospective study of the German Cancer Consortium Radiation Oncology Group (DKTK-ROG)

DEFF Research Database (Denmark)

Linge, Annett; Lohaus, Fabian; Löck, Steffen

2016-01-01

OBJECTIVE: To investigate the impact of the tumour volume, HPV status, cancer stem cell (CSC) marker expression and hypoxia gene signatures, as potential markers of radiobiological mechanisms of radioresistance, in a contemporary cohort of patients with locally advanced head and neck squamous cell...

Advanced colorectal adenoma related gene expression signature may predict prognostic for colorectal cancer patients with adenoma-carcinoma sequence.

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Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun

2015-01-01

There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinformatics software, and we analyzed the relationship between gene expression profiles of adenoma-adenocarcinoma sequence and clinical prognosis of colorectal cancer. The mRNA expressions of adenoma-carcinoma sequence were significantly different between high-grade intraepithelial neoplasia group and adenocarcinoma group. The biological process of gene ontology function enrichment analysis on differentially expressed genes between high-grade intraepithelial neoplasia group and adenocarcinoma group showed that genes enriched in the extracellular structure organization, skeletal system development, biological adhesion and itself regulated growth regulation, with the P value after FDR correction of less than 0.05. In addition, IPR-related protein mainly focused on the insulin-like growth factor binding proteins. The variable trends of gene expression profiles for adenoma-carcinoma sequence were mainly concentrated in high-grade intraepithelial neoplasia and adenocarcinoma. The differentially expressed genes are significantly correlated between high-grade intraepithelial neoplasia group and adenocarcinoma group. Bioinformatics analysis is an effective way to study the gene expression profiles in the adenoma-carcinoma sequence, and may provide an effective tool to involve colorectal cancer research strategy into colorectal adenoma or advanced adenoma.

[Analysis of gene expression pattern in peripheral blood leukocytes during experimental heat wave].

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Feoktistova, E S; Skamrov, A V; Goryunova, L E; Khaspekov, G L; Osyaeva, M K; Rodnenkov, O V; Beabealashvilli, R Sh

2017-03-01

The conditions of Moscow 2010 summer heat wave were simulated in an accommodation module. Six healthy men aged from 22 to 46 years stayed in the module for 30 days. Measurements of gene expression in peripheral blood leukocytes before, during and 3 day after simulated heat wave were performed using qRT-PCR. We observed a shift in the expression level of certain genes after heat exposure for a long time, and rapid return to the initial level, when volunteers leaved the accommodation module. Eight genes were chosen to form the "heat expression signature". EGR2, EGR3 were upregulated in all six volunteers, EGR1, SIRT1, CYP51A1, MAPK9, BAG5, MNDA were upregulated in 5 volunteers.

Can specific transcriptional regulators assemble a universal cancer signature?

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Roy, Janine; Isik, Zerrin; Pilarsky, Christian; Schroeder, Michael

2013-10-01

Recently, there is a lot of interest in using biomarker signatures derived from gene expression data to predict cancer progression. We assembled signatures of 25 published datasets covering 13 types of cancers. How do these signatures compare with each other? On one hand signatures answering the same biological question should overlap, whereas signatures predicting different cancer types should differ. On the other hand, there could also be a Universal Cancer Signature that is predictive independently of the cancer type. Initially, we generate signatures for all datasets using classical approaches such as t-test and fold change and then, we explore signatures resulting from a network-based method, that applies the random surfer model of Google's PageRank algorithm. We show that the signatures as published by the authors and the signatures generated with classical methods do not overlap - not even for the same cancer type - whereas the network-based signatures strongly overlap. Selecting 10 out of 37 universal cancer genes gives the optimal prediction for all cancers thus taking a first step towards a Universal Cancer Signature. We furthermore analyze and discuss the involved genes in terms of the Hallmarks of cancer and in particular single out SP1, JUN/FOS and NFKB1 and examine their specific role in cancer progression.

The low-recombining pericentromeric region of barley restricts gene diversity and evolution but not gene expression

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Baker, Katie; Bayer, Micha; Cook, Nicola; Dreißig, Steven; Dhillon, Taniya; Russell, Joanne; Hedley, Pete E; Morris, Jenny; Ramsay, Luke; Colas, Isabelle; Waugh, Robbie; Steffenson, Brian; Milne, Iain; Stephen, Gordon; Marshall, David; Flavell, Andrew J

2014-01-01

The low-recombining pericentromeric region of the barley genome contains roughly a quarter of the genes of the species, embedded in low-recombining DNA that is rich in repeats and repressive chromatin signatures. We have investigated the effects of pericentromeric region residency upon the expression, diversity and evolution of these genes. We observe no significant difference in average transcript level or developmental RNA specificity between the barley pericentromeric region and the rest of the genome. In contrast, all of the evolutionary parameters studied here show evidence of compromised gene evolution in this region. First, genes within the pericentromeric region of wild barley show reduced diversity and significantly weakened purifying selection compared with the rest of the genome. Second, gene duplicates (ohnolog pairs) derived from the cereal whole-genome duplication event ca. 60MYa have been completely eliminated from the barley pericentromeric region. Third, local gene duplication in the pericentromeric region is reduced by 29% relative to the rest of the genome. Thus, the pericentromeric region of barley is a permissive environment for gene expression but has restricted gene evolution in a sizeable fraction of barley's genes. PMID:24947331

GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data.

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Rue-Albrecht, Kévin; McGettigan, Paul A; Hernández, Belinda; Nalpas, Nicolas C; Magee, David A; Parnell, Andrew C; Gordon, Stephen V; MacHugh, David E

2016-03-11

Identification of gene expression profiles that differentiate experimental groups is critical for discovery and analysis of key molecular pathways and also for selection of robust diagnostic or prognostic biomarkers. While integration of differential expression statistics has been used to refine gene set enrichment analyses, such approaches are typically limited to single gene lists resulting from simple two-group comparisons or time-series analyses. In contrast, functional class scoring and machine learning approaches provide powerful alternative methods to leverage molecular measurements for pathway analyses, and to compare continuous and multi-level categorical factors. We introduce GOexpress, a software package for scoring and summarising the capacity of gene ontology features to simultaneously classify samples from multiple experimental groups. GOexpress integrates normalised gene expression data (e.g., from microarray and RNA-seq experiments) and phenotypic information of individual samples with gene ontology annotations to derive a ranking of genes and gene ontology terms using a supervised learning approach. The default random forest algorithm allows interactions between all experimental factors, and competitive scoring of expressed genes to evaluate their relative importance in classifying predefined groups of samples. GOexpress enables rapid identification and visualisation of ontology-related gene panels that robustly classify groups of samples and supports both categorical (e.g., infection status, treatment) and continuous (e.g., time-series, drug concentrations) experimental factors. The use of standard Bioconductor extension packages and publicly available gene ontology annotations facilitates straightforward integration of GOexpress within existing computational biology pipelines.

Molecular signature of the radioinduction in the thyroid tumors developed after radiotherapy

International Nuclear Information System (INIS)

Mallard, Ch.

2005-10-01

Several epidemiological studies enlightens an increase of the number of thyroid cancers among children and adolescents exposed to ionizing radiation after an internal exposure ( Chernobylsk accident) or external one as a radiotherapy. No increase arose for adults.The analysis of the transcriptome was realised with micro arrays prepared on the genomic platform of the Cea at Evry that allow to study simultaneously the expression of 6000 genes. this study allows to enlighten a signature of radioinduction constituted by series of genes specifically expressed in one or other type of cancer in function of its etiology. This signature includes 59 genes expressed differentially between the sporadic carcinomas and 45 genes in the case of adenomas. with this signature an analysis in principal components allowed to determine correctly the etiology of 12 tumors among 13, the etiology of a sporadic adenoma was not determined. Besides, the study of the expression of genes specific to thyroid (TSHR, TG, TPO, TTF1, TTF2, PAX8) in relation with the presence of arrangements RET/PTC or mutations of BRAF was made. It allowed to enlighten the loss of TPO expression in the cancers changed for BRAF as well as a new mechanism of BRAF activation. (N.C.)

Blood Gene Expression Predicts Bronchiolitis Obliterans Syndrome

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Richard Danger

2018-01-01

Full Text Available Bronchiolitis obliterans syndrome (BOS, the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray gene expression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group, and 26 samples at or after BOS diagnosis (diagnosis group. An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group. We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1, T-cell leukemia/lymphoma protein 1A (TCL1A, and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p < 0.01 and are not associated with time posttransplantation. This is the first published large-scale gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS.

Characterization of chemically induced liver injuries using gene co-expression modules.

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Gregory J Tawa

Full Text Available Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1 known biochemical pathways associated with liver injuries and 2 clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20% genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.

Distinct gene expression signatures in human embryonic stem cells differentiated towards definitive endoderm at single-cell level

DEFF Research Database (Denmark)

Norrman, Karin; Strömbeck, Anna; Semb, Henrik

2013-01-01

for the three activin A based protocols applied. Our data provide novel insights in DE gene expression at the cellular level of in vitro differentiated human embryonic stem cells, and illustrate the power of using single-cell gene expression profiling to study differentiation heterogeneity and to characterize...... of anterior definitive endoderm (DE). Here, we differentiated human embryonic stem cells towards DE using three different activin A based treatments. Differentiation efficiencies were evaluated by gene expression profiling over time at cell population level. A panel of key markers was used to study DE...... formation. Final DE differentiation was also analyzed with immunocytochemistry and single-cell gene expression profiling. We found that cells treated with activin A in combination with sodium butyrate and B27 serum-free supplement medium generated the most mature DE cells. Cell population studies were...

Transcriptional Profiling of Whole Blood Identifies a Unique 5-Gene Signature for Myelofibrosis and Imminent Myelofibrosis Transformation

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Hasselbalch, Hans Carl; Skov, Vibe; Stauffer Larsen, Thomas

2014-01-01

Identifying a distinct gene signature for myelofibrosis may yield novel information of the genes, which are responsible for progression of essential thrombocythemia and polycythemia vera towards myelofibrosis. We aimed at identifying a simple gene signature - composed of a few genes - which were...

MicroRNA signature of the human developing pancreas

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Correa-Medina Mayrin

2010-09-01

Full Text Available Abstract Background MicroRNAs are non-coding RNAs that regulate gene expression including differentiation and development by either inhibiting translation or inducing target degradation. The aim of this study is to determine the microRNA expression signature during human pancreatic development and to identify potential microRNA gene targets calculating correlations between the signature microRNAs and their corresponding mRNA targets, predicted by bioinformatics, in genome-wide RNA microarray study. Results The microRNA signature of human fetal pancreatic samples 10-22 weeks of gestational age (wga, was obtained by PCR-based high throughput screening with Taqman Low Density Arrays. This method led to identification of 212 microRNAs. The microRNAs were classified in 3 groups: Group number I contains 4 microRNAs with the increasing profile; II, 35 microRNAs with decreasing profile and III with 173 microRNAs, which remain unchanged. We calculated Pearson correlations between the expression profile of microRNAs and target mRNAs, predicted by TargetScan 5.1 and miRBase altgorithms, using genome-wide mRNA expression data. Group I correlated with the decreasing expression of 142 target mRNAs and Group II with the increasing expression of 876 target mRNAs. Most microRNAs correlate with multiple targets, just as mRNAs are targeted by multiple microRNAs. Among the identified targets are the genes and transcription factors known to play an essential role in pancreatic development. Conclusions We have determined specific groups of microRNAs in human fetal pancreas that change the degree of their expression throughout the development. A negative correlative analysis suggests an intertwined network of microRNAs and mRNAs collaborating with each other. This study provides information leading to potential two-way level of combinatorial control regulating gene expression through microRNAs targeting multiple mRNAs and, conversely, target mRNAs regulated in

A whole-blood transcriptome meta-analysis identifies gene expression signatures of cigarette smoking

NARCIS (Netherlands)

Huan, T. (Tianxiao); R. Joehanes (Roby); C. Schurmann (Claudia); K. Schramm (Katharina); L.C. Pilling (Luke); M.J. Peters (Marjolein); R. Mägi (Reedik); D.L. Demeo (Dawn L.); G.T. O'Connor (George); L. Ferrucci (Luigi); A. Teumer (Alexander); G. Homuth (Georg); R. Biffar (Reiner); U. Völker (Uwe); C. Herder (Christian); M. Waldenberger (Melanie); A. Peters (Annette); S. Zeilinger (Sonja); A. Metspalu (Andres); A. Hofman (Albert); A.G. Uitterlinden (André); D.G. Hernandez (Dena); A. Singleton (Andrew); S. Bandinelli (Stefania); P.J. Munson (Peter); H. Lin (Honghuang); E.J. Benjamin (Emelia); T. Esko (Tõnu); H.J. Grabe (Hans Jörgen); H. Prokisch (Holger); J.B.J. van Meurs (Joyce); D. Melzer (David); D. Levy (Daniel)

2016-01-01

textabstractCigarette smoking is a leading modifiable cause of death worldwide. We hypothesized that cigarette smoking induces extensive transcriptomic changes that lead to target-organ damage and smoking-related diseases. We performed a metaanalysis of transcriptome-wide gene expression using whole

Coral thermal tolerance: tuning gene expression to resist thermal stress.

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Anthony J Bellantuono

Full Text Available The acclimatization capacity of corals is a critical consideration in the persistence of coral reefs under stresses imposed by global climate change. The stress history of corals plays a role in subsequent response to heat stress, but the transcriptomic changes associated with these plastic changes have not been previously explored. In order to identify host transcriptomic changes associated with acquired thermal tolerance in the scleractinian coral Acropora millepora, corals preconditioned to a sub-lethal temperature of 3°C below bleaching threshold temperature were compared to both non-preconditioned corals and untreated controls using a cDNA microarray platform. After eight days of hyperthermal challenge, conditions under which non-preconditioned corals bleached and preconditioned corals (thermal-tolerant maintained Symbiodinium density, a clear differentiation in the transcriptional profiles was revealed among the condition examined. Among these changes, nine differentially expressed genes separated preconditioned corals from non-preconditioned corals, with 42 genes differentially expressed between control and preconditioned treatments, and 70 genes between non-preconditioned corals and controls. Differentially expressed genes included components of an apoptotic signaling cascade, which suggest the inhibition of apoptosis in preconditioned corals. Additionally, lectins and genes involved in response to oxidative stress were also detected. One dominant pattern was the apparent tuning of gene expression observed between preconditioned and non-preconditioned treatments; that is, differences in expression magnitude were more apparent than differences in the identity of genes differentially expressed. Our work revealed a transcriptomic signature underlying the tolerance associated with coral thermal history, and suggests that understanding the molecular mechanisms behind physiological acclimatization would be critical for the modeling of reefs

Transforming RNA-Seq data to improve the performance of prognostic gene signatures.

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Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques.

Transforming RNA-Seq data to improve the performance of prognostic gene signatures.

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Isabella Zwiener

Full Text Available Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques.

A qualitative signature for early diagnosis of hepatocellular carcinoma based on relative expression orderings.

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Ao, Lu; Zhang, Zimei; Guan, Qingzhou; Guo, Yating; Guo, You; Zhang, Jiahui; Lv, Xingwei; Huang, Haiyan; Zhang, Huarong; Wang, Xianlong; Guo, Zheng

2018-04-23

Currently, using biopsy specimens to confirm suspicious liver lesions of early hepatocellular carcinoma are not entirely reliable because of insufficient sampling amount and inaccurate sampling location. It is necessary to develop a signature to aid early hepatocellular carcinoma diagnosis using biopsy specimens even when the sampling location is inaccurate. Based on the within-sample relative expression orderings of gene pairs, we identified a simple qualitative signature to distinguish both hepatocellular carcinoma and adjacent non-tumour tissues from cirrhosis tissues of non-hepatocellular carcinoma patients. A signature consisting of 19 gene pairs was identified in the training data sets and validated in 2 large collections of samples from biopsy and surgical resection specimens. For biopsy specimens, 95.7% of 141 hepatocellular carcinoma tissues and all (100%) of 108 cirrhosis tissues of non-hepatocellular carcinoma patients were correctly classified. Especially, all (100%) of 60 hepatocellular carcinoma adjacent normal tissues and 77.5% of 80 hepatocellular carcinoma adjacent cirrhosis tissues were classified to hepatocellular carcinoma. For surgical resection specimens, 99.7% of 733 hepatocellular carcinoma specimens were correctly classified to hepatocellular carcinoma, while 96.1% of 254 hepatocellular carcinoma adjacent cirrhosis tissues and 95.9% of 538 hepatocellular carcinoma adjacent normal tissues were classified to hepatocellular carcinoma. In contrast, 17.0% of 47 cirrhosis from non-hepatocellular carcinoma patients waiting for liver transplantation were classified to hepatocellular carcinoma, indicating that some patients with long-lasting cirrhosis could have already gained hepatocellular carcinoma characteristics. The signature can distinguish both hepatocellular carcinoma tissues and tumour-adjacent tissues from cirrhosis tissues of non-hepatocellular carcinoma patients even using inaccurately sampled biopsy specimens, which can aid early

Signatures derived from increase in SHARPIN gene copy number are associated with poor prognosis in patients with breast cancer

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Diane Ojo

2017-12-01

Full Text Available We report three signatures produced from SHARPIN gene copy number increase (GCN-Increase and their effects on patients with breast cancer (BC. In the Metabric dataset (n = 2059, cBioPortal, SHARPIN GCN-Increase occurs preferentially or mutual exclusively with mutations in TP53, PIK3CA, and CDH1. These genomic alterations constitute a signature (SigMut that significantly correlates with reductions in overall survival (OS in BC patients (n = 1980; p = 1.081e−6. Additionally, SHARPIN GCN-Increase is associated with 4220 differentially expressed genes (DEGs. These DEGs are enriched in activation of the pathways regulating cell cycle progression, RNA transport, ribosome biosynthesis, DNA replication, and in downregulation of the pathways related to extracellular matrix. These DEGs are thus likely to facilitate the proliferation and metastasis of BC cells. Additionally, through forward (FWD and backward (BWD stepwise variate selections among the top 160 downregulated and top 200 upregulated DEGs using the Cox regression model, a 6-gene (SigFWD and a 50-gene (SigBWD signature were derived. Both signatures robustly associate with decreases in OS in BC patients within the Curtis (n = 1980; p = 6.16e−11 for SigFWD; p = 1.06e−10, for SigBWD and TCGA cohort (n = 817; p = 4.53e−4 for SigFWD and p = 0.00525 for SigBWD. After adjusting for known clinical factors, SigMut (HR 1.21, p = 0.0297, SigBWD (HR 1.25, p = 0.0263, and likely SigFWD (HR 1.17, p = 0.062 remain independent risk factors of BC deaths. Furthermore, the proportion of patients positive for these signatures is significantly increased in ER−, Her2-enriched, basal-like, and claudin-low BCs compared to ER+ and luminal BCs. Collectively, these SHARPIN GCN-Increase-derived signatures may have clinical applications in management of patients with BC.

Gene expression and gene therapy imaging

International Nuclear Information System (INIS)

Rome, Claire; Couillaud, Franck; Moonen, Chrit T.W.

2007-01-01

The fast growing field of molecular imaging has achieved major advances in imaging gene expression, an important element of gene therapy. Gene expression imaging is based on specific probes or contrast agents that allow either direct or indirect spatio-temporal evaluation of gene expression. Direct evaluation is possible with, for example, contrast agents that bind directly to a specific target (e.g., receptor). Indirect evaluation may be achieved by using specific substrate probes for a target enzyme. The use of marker genes, also called reporter genes, is an essential element of MI approaches for gene expression in gene therapy. The marker gene may not have a therapeutic role itself, but by coupling the marker gene to a therapeutic gene, expression of the marker gene reports on the expression of the therapeutic gene. Nuclear medicine and optical approaches are highly sensitive (detection of probes in the picomolar range), whereas MRI and ultrasound imaging are less sensitive and require amplification techniques and/or accumulation of contrast agents in enlarged contrast particles. Recently developed MI techniques are particularly relevant for gene therapy. Amongst these are the possibility to track gene therapy vectors such as stem cells, and the techniques that allow spatiotemporal control of gene expression by non-invasive heating (with MRI guided focused ultrasound) and the use of temperature sensitive promoters. (orig.)

Chromosomal alterations detected by comparative genomic hybridization in subgroups of gene expression-defined Burkitt's lymphoma

NARCIS (Netherlands)

Salaverria, Itziar; Zettl, Andreas; Bea, Silvia; Hartmann, Elena M.; Dave, Sandeep S.; Wright, George W.; Boerma, Evert-Jan; Kluin, Philip M.; Ott, German; Chan, Wing C.; Weisenburger, Dennis D.; Lopez-Guillermo, Armando; Gascoyne, Randy D.; Delabie, Jan; Rimsza, Lisa M.; Braziel, Rita M.; Jaffe, Elaine S.; Staudt, Louis M.; Mueller-Hermelink, Hans Konrad; Campo, Elias; Rosenwald, Andreas

Background Burkitt's lymphoma is an aggressive B-cell lymphoma characterized by typical morph 0 logical, immunophenotypic and molecular features. Gene expression profiling provided a molecular signature of Burkitt's lymphoma, but also demonstrated that a subset of aggressive B-cell lymphomas not

Four-miRNA signature as a prognostic tool for lung adenocarcinoma.

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Lin, Yan; Lv, Yufeng; Liang, Rong; Yuan, Chunling; Zhang, Jinyan; He, Dan; Zheng, Xiaowen; Zhang, Jianfeng

2018-01-01

The aim of this study was to generate a novel miRNA expression signature to accurately predict prognosis for patients with lung adenocarcinoma (LUAD). Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple miRNAs with differential expression between LUAD and paired healthy tissues. We then evaluated the prognostic values of the differentially expressed miRNAs using univariate/multivariate Cox regression analysis. This analysis was ultimately used to construct a four-miRNA signature that effectively predicted patient survival. Finally, we analyzed potential functional roles of the target genes for these four miRNAs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Based on our cutoff criteria ( P 1.0), we identified a total of 187 differentially expressed miRNAs, including 148 that were upregulated in LUAD tissues and 39 that were downregulated. Four miRNAs (miR-148a-5p, miR-31-5p, miR-548v, and miR-550a-5p) were independently associated with survival based on Kaplan-Meier analysis. We generated a signature index based on the expression of these four miRNAs and stratified patients into low- and high-risk groups. Patients in the high-risk group had significantly shorter survival times than those in the low-risk group ( P =0.002). A functional enrichment analysis suggested that the target genes of these four miRNAs were involved in protein phosphorylation and the Hippo and sphingolipid signaling pathways. Taken together, our results suggest that our four-miRNA signature can be used as a prognostic tool for patients with LUAD.

Value of a gene signature assay in patients with early breast cancer and intermediate risk: a single institution retrospective study.

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Bonneterre, Jacques; Prat, Aleix; Galván, Patricia; Morel, Pascale; Giard, Sylvia

2016-05-01

Purpose In daily clinical practice, the indication for adjuvant chemotherapy (CT) is relatively easy to make in patients with early hormone-receptor-positive (HR+) breast cancer with either very poor or very good clinicopathological prognostic variables. However, this decision is much more difficult in patients with intermediate clinicopathological prognostic variables. Here, we evaluate the value of a gene-expression profile identified by the Prosigna gene signature assay in guiding treatment decision-making in patients with these intermediate features. Methods A consecutive cohort of 577 HR + breast cancer patients surgically treated in a single institution between January 2012 and December 2012 was evaluated. From this population, pre- and post-menopausal patients with intermediate prognosis clinicopathological variables were identified and indication of adjuvant CT in these patients was recorded. The gene signature assay was performed retrospectively in this intermediate risk group. Descriptive statistics are presented. Results Among 96 intermediate-risk patients, 64 postmenopausal patients underwent gene signature testing. Subtype distribution was as follows: Luminal A (N = 33; 51.6%), Luminal B (N = 31; 48.4%). Risk of recurrence (ROR) distribution was as follows: ROR-low (n = 16; 25%); ROR-intermediate (N = 26; 40.6%); and ROR-high (N = 22; 34.4%). CT was subsequently administered in 18.7%, 53.8% and 59.0% of the ROR-low, ROR-intermediate and ROR-high groups, respectively. With the use of the gene signature assay, 59.4% of the intermediate cases were re-classified to either ROR-low or ROR-high risk categories. In the ROR-intermediate group, 11/26 patients (42.3%) had Luminal A and 15/26 (57.7%) had Luminal B. Due to follow-up time constraints, no patient outcome results were evaluated. Conclusion The gene signature assay provides clinically useful information and improved treatment decision-making in patients with intermediate risk based on

Autism-associated gene expression in peripheral leucocytes commonly observed between subjects with autism and healthy women having autistic children.

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Kuwano, Yuki; Kamio, Yoko; Kawai, Tomoko; Katsuura, Sakurako; Inada, Naoko; Takaki, Akiko; Rokutan, Kazuhito

2011-01-01

Autism spectrum disorder (ASD) is a severe neuropsychiatric disorder which has complex pathobiology with profound influences of genetic factors in its development. Although the numerous autism susceptible genes were identified, the etiology of autism is not fully explained. Using DNA microarray, we examined gene expression profiling in peripheral blood from 21 individuals in each of the four groups; young adults with ASD, age- and gender-matched healthy subjects (ASD control), healthy mothers having children with ASD (asdMO), and asdMO control. There was no blood relationship between ASD and asdMO. Comparing the ASD group with control, 19 genes were found to be significantly changed. These genes were mainly involved in cell morphology, cellular assembly and organization, and nerve system development and function. In addition, the asdMO group possessed a unique gene expression signature shown as significant alterations of protein synthesis despite of their nonautistic diagnostic status. Moreover, an ASD-associated gene expression signature was commonly observed in both individuals with ASD and asdMO. This unique gene expression profiling detected in peripheral leukocytes from affected subjects with ASD and unaffected mothers having ASD children suggest that a genetic predisposition to ASD may be detectable even in peripheral cells. Altered expression of several autism candidate genes such as FMR-1 and MECP2, could be detected in leukocytes. Taken together, these findings suggest that the ASD-associated genes identified in leukocytes are informative to explore the genetic, epigenetic, and environmental background of ASD and might become potential tools to assess the crucial factors related to the clinical onset of the disorder.

Gene Expression Analysis to Assess the Relevance of Rodent Models to Human Lung Injury.

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Sweeney, Timothy E; Lofgren, Shane; Khatri, Purvesh; Rogers, Angela J

2017-08-01

The relevance of animal models to human diseases is an area of intense scientific debate. The degree to which mouse models of lung injury recapitulate human lung injury has never been assessed. Integrating data from both human and animal expression studies allows for increased statistical power and identification of conserved differential gene expression across organisms and conditions. We sought comprehensive integration of gene expression data in experimental acute lung injury (ALI) in rodents compared with humans. We performed two separate gene expression multicohort analyses to determine differential gene expression in experimental animal and human lung injury. We used correlational and pathway analyses combined with external in vitro gene expression data to identify both potential drivers of underlying inflammation and therapeutic drug candidates. We identified 21 animal lung tissue datasets and three human lung injury bronchoalveolar lavage datasets. We show that the metasignatures of animal and human experimental ALI are significantly correlated despite these widely varying experimental conditions. The gene expression changes among mice and rats across diverse injury models (ozone, ventilator-induced lung injury, LPS) are significantly correlated with human models of lung injury (Pearson r = 0.33-0.45, P human lung injury. Predicted therapeutic targets, peptide ligand signatures, and pathway analyses are also all highly overlapping. Gene expression changes are similar in animal and human experimental ALI, and provide several physiologic and therapeutic insights to the disease.

Comparative analyses of gene copy number and mRNA expression in GBM tumors and GBM xenografts

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Hodgson, J. Graeme; Yeh, Ru-Fang; Ray, Amrita; Wang, Nicholas J.; Smirnov, Ivan; Yu, Mamie; Hariono, Sujatmi; Silber, Joachim; Feiler, Heidi S.; Gray, Joe W.; Spellman, Paul T.; Vandenberg, Scott R.; Berger, Mitchel S.; James, C. David

2009-04-03

Development of model systems that recapitulate the molecular heterogeneity observed among glioblastoma multiforme (GBM) tumors will expedite the testing of targeted molecular therapeutic strategies for GBM treatment. In this study, we profiled DNA copy number and mRNA expression in 21 independent GBM tumor lines maintained as subcutaneous xenografts (GBMX), and compared GBMX molecular signatures to those observed in GBM clinical specimens derived from the Cancer Genome Atlas (TCGA). The predominant copy number signature in both tumor groups was defined by chromosome-7 gain/chromosome-10 loss, a poor-prognosis genetic signature. We also observed, at frequencies similar to that detected in TCGA GBM tumors, genomic amplification and overexpression of known GBM oncogenes, such as EGFR, MDM2, CDK6, and MYCN, and novel genes, including NUP107, SLC35E3, MMP1, MMP13, and DDX1. The transcriptional signature of GBMX tumors, which was stable over multiple subcutaneous passages, was defined by overexpression of genes involved in M phase, DNA replication, and chromosome organization (MRC) and was highly similar to the poor-prognosis mitosis and cell-cycle module (MCM) in GBM. Assessment of gene expression in TCGA-derived GBMs revealed overexpression of MRC cancer genes AURKB, BIRC5, CCNB1, CCNB2, CDC2, CDK2, and FOXM1, which form a transcriptional network important for G2/M progression and/or checkpoint activation. Our study supports propagation of GBM tumors as subcutaneous xenografts as a useful approach for sustaining key molecular characteristics of patient tumors, and highlights therapeutic opportunities conferred by this GBMX tumor panel for testing targeted therapeutic strategies for GBM treatment.

Gene expression

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Hildebrand, C.E.; Crawford, B.D.; Walters, R.A.; Enger, M.D.

1983-01-01

We prepared probes for isolating functional pieces of the metallothionein locus. The probes enabled a variety of experiments, eventually revealing two mechanisms for metallothionein gene expression, the order of the DNA coding units at the locus, and the location of the gene site in its chromosome. Once the switch regulating metallothionein synthesis was located, it could be joined by recombinant DNA methods to other, unrelated genes, then reintroduced into cells by gene-transfer techniques. The expression of these recombinant genes could then be induced by exposing the cells to Zn 2+ or Cd 2+ . We would thus take advantage of the clearly defined switching properties of the metallothionein gene to manipulate the expression of other, perhaps normally constitutive, genes. Already, despite an incomplete understanding of how the regulatory switch of the metallothionein locus operates, such experiments have been performed successfully

An Examination of Dynamic Gene Expression Changes in the Mouse Brain During Pregnancy and the Postpartum Period

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Surjyendu Ray

2016-01-01

Full Text Available The developmental transition to motherhood requires gene expression changes that alter the brain to drive the female to perform maternal behaviors. We broadly examined the global transcriptional response in the mouse maternal brain, by examining four brain regions: hypothalamus, hippocampus, neocortex, and cerebellum, in virgin females, two pregnancy time points, and three postpartum time points. We find that overall there are hundreds of differentially expressed genes, but each brain region and time point shows a unique molecular signature, with only 49 genes differentially expressed in all four regions. Interestingly, a set of “early-response genes” is repressed in all brain regions during pregnancy and postpartum stages. Several genes previously implicated in underlying postpartum depression change expression. This study serves as an atlas of gene expression changes in the maternal brain, with the results demonstrating that pregnancy, parturition, and postpartum maternal experience substantially impact diverse brain regions.

An Examination of Dynamic Gene Expression Changes in the Mouse Brain During Pregnancy and the Postpartum Period.

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Ray, Surjyendu; Tzeng, Ruei-Ying; DiCarlo, Lisa M; Bundy, Joseph L; Vied, Cynthia; Tyson, Gary; Nowakowski, Richard; Arbeitman, Michelle N

2015-11-23

The developmental transition to motherhood requires gene expression changes that alter the brain to drive the female to perform maternal behaviors. We broadly examined the global transcriptional response in the mouse maternal brain, by examining four brain regions: hypothalamus, hippocampus, neocortex, and cerebellum, in virgin females, two pregnancy time points, and three postpartum time points. We find that overall there are hundreds of differentially expressed genes, but each brain region and time point shows a unique molecular signature, with only 49 genes differentially expressed in all four regions. Interestingly, a set of "early-response genes" is repressed in all brain regions during pregnancy and postpartum stages. Several genes previously implicated in underlying postpartum depression change expression. This study serves as an atlas of gene expression changes in the maternal brain, with the results demonstrating that pregnancy, parturition, and postpartum maternal experience substantially impact diverse brain regions. Copyright © 2016 Ray et al.

Circulating cortisol-associated signature of glucocorticoid-related gene expression in subcutaneous fat of obese subjects.

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Pavlatou, Maria G; Vickers, Kasey C; Varma, Sudhir; Malek, Rana; Sampson, Maureen; Remaley, Alan T; Gold, Philip W; Skarulis, Monica C; Kino, Tomoshige

2013-05-01

Serum cortisol concentrations fluctuate in a circadian fashion, and glucocorticoids exert strong effects on adipose tissue and induce obesity through the glucocorticoid receptor. To examine the impact of physiologic levels of circulating cortisol on subcutaneous adipose tissue, 25 overweight and obese subjects were employed, and their serum levels of morning (AM) and evening (PM) cortisol, AM/PM cortisol ratios, and 24-h urinary-free cortisol (UFC) were compared with their clinical parameters, serum cytokine levels, and mRNA expression of 93 receptor action-regulating and 93 glucocorticoid-responsive genes in abdominal subcutaneous fat. AM cortisol levels did not correlate with mRNA expression of the all genes examined, whereas PM cortisol levels, AM/PM cortisol ratios, and 24-h UFC were associated with distinct sets of these genes. Body mass index did not significantly correlate with the four cortisol parameters employed. These results suggest that physiologic levels of AM serum cortisol do not solely represent biological effects of circulating cortisol on the expression of glucocorticoid-related genes in subcutaneous adipose tissue, whereas PM levels, amplitude, and net amounts of the diurnally fluctuating serum cortisol have distinct effects. Through the genes identified in this study, glucocorticoids appear to influence intermediary metabolism, energy balance, inflammation, and local circadian rythmicity in subcutaneous fat. Our results may also explain in part the development of metabolic abnormality and obesity in subjects under stress or patients with melancholic/atypical depression who demonstrate elevated levels of PM serum cortisol. Copyright © 2013 The Obesity Society.

Gene expression and functional annotation of the human ciliary body epithelia.

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Sarah F Janssen

Full Text Available PURPOSE: The ciliary body (CB of the human eye consists of the non-pigmented (NPE and pigmented (PE neuro-epithelia. We investigated the gene expression of NPE and PE, to shed light on the molecular mechanisms underlying the most important functions of the CB. We also developed molecular signatures for the NPE and PE and studied possible new clues for glaucoma. METHODS: We isolated NPE and PE cells from seven healthy human donor eyes using laser dissection microscopy. Next, we performed RNA isolation, amplification, labeling and hybridization against 44×k Agilent microarrays. For microarray conformations, we used a literature study, RT-PCRs, and immunohistochemical stainings. We analyzed the gene expression data with R and with the knowledge database Ingenuity. RESULTS: The gene expression profiles and functional annotations of the NPE and PE were highly similar. We found that the most important functionalities of the NPE and PE were related to developmental processes, neural nature of the tissue, endocrine and metabolic signaling, and immunological functions. In total 1576 genes differed statistically significantly between NPE and PE. From these genes, at least 3 were cell-specific for the NPE and 143 for the PE. Finally, we observed high expression in the (NPE of 35 genes previously implicated in molecular mechanisms related to glaucoma. CONCLUSION: Our gene expression analysis suggested that the NPE and PE of the CB were quite similar. Nonetheless, cell-type specific differences were found. The molecular machineries of the human NPE and PE are involved in a range of neuro-endocrinological, developmental and immunological functions, and perhaps glaucoma.

Meta-analysis of crowdsourced data compendia suggests pan-disease transcriptional signatures of autoimmunity [version 1; referees: 2 approved

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William W. Lau

2016-12-01

Full Text Available Background: The proliferation of publicly accessible large-scale biological data together with increasing availability of bioinformatics tools have the potential to transform biomedical research. Here we report a crowdsourcing Jamboree that explored whether a team of volunteer biologists without formal bioinformatics training could use OMiCC, a crowdsourcing web platform that facilitates the reuse and (meta- analysis of public gene expression data, to compile and annotate gene expression data, and design comparisons between disease and control sample groups. Methods: The Jamboree focused on several common human autoimmune diseases, including systemic lupus erythematosus (SLE, multiple sclerosis (MS, type I diabetes (DM1, and rheumatoid arthritis (RA, and the corresponding mouse models. Meta-analyses were performed in OMiCC using comparisons constructed by the participants to identify 1 gene expression signatures for each disease (disease versus healthy controls at the gene expression and biological pathway levels, 2 conserved signatures across all diseases within each species (pan-disease signatures, and 3 conserved signatures between species for each disease and across all diseases (cross-species signatures. Results: A large number of differentially expressed genes were identified for each disease based on meta-analysis, with observed overlap among diseases both within and across species. Gene set/pathway enrichment of upregulated genes suggested conserved signatures (e.g., interferon across all human and mouse conditions. Conclusions: Our Jamboree exercise provides evidence that when enabled by appropriate tools, a "crowd" of biologists can work together to accelerate the pace by which the increasingly large amounts of public data can be reused and meta-analyzed for generating and testing hypotheses. Our encouraging experience suggests that a similar crowdsourcing approach can be used to explore other biological questions.

Identifying molecular subtypes in human colon cancer using gene expression and DNA methylation microarray data.

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Ren, Zhonglu; Wang, Wenhui; Li, Jinming

2016-02-01

Identifying colon cancer subtypes based on molecular signatures may allow for a more rational, patient-specific approach to therapy in the future. Classifications using gene expression data have been attempted before with little concordance between the different studies carried out. In this study we aimed to uncover subtypes of colon cancer that have distinct biological characteristics and identify a set of novel biomarkers which could best reflect the clinical and/or biological characteristics of each subtype. Clustering analysis and discriminant analysis were utilized to discover the subtypes in two different molecular levels on 153 colon cancer samples from The Cancer Genome Atlas (TCGA) Data Portal. At gene expression level, we identified two major subtypes, ECL1 (expression cluster 1) and ECL2 (expression cluster 2) and a list of signature genes. Due to the heterogeneity of colon cancer, the subtype ECL1 can be further subdivided into three nested subclasses, and HOTAIR were found upregulated in subclass 2. At DNA methylation level, we uncovered three major subtypes, MCL1 (methylation cluster 1), MCL2 (methylation cluster 2) and MCL3 (methylation cluster 3). We found only three subtypes of CpG island methylator phenotype (CIMP) in colon cancer instead of the four subtypes in the previous reports, and we found no sufficient evidence to subdivide MCL3 into two distinct subgroups.

Differential gene expression in patients with subsyndromal symptomatic depression and major depressive disorder.

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Yang, Chengqing; Hu, Guoqin; Li, Zezhi; Wang, Qingzhong; Wang, Xuemei; Yuan, Chengmei; Wang, Zuowei; Hong, Wu; Lu, Weihong; Cao, Lan; Chen, Jun; Wang, Yong; Yu, Shunying; Zhou, Yimin; Yi, Zhenghui; Fang, Yiru

2017-01-01

Subsyndromal symptomatic depression (SSD) is a subtype of subthreshold depressive and can lead to significant psychosocial functional impairment. Although the pathogenesis of major depressive disorder (MDD) and SSD still remains poorly understood, a set of studies have found that many same genetic factors play important roles in the etiology of these two disorders. Nowadays, the differential gene expression between MDD and SSD is still unknown. In our previous study, we compared the expression profile and made the classification with the leukocytes by using whole-genome cRNA microarrays among drug-free first-episode subjects with SSD, MDD and matched healthy controls (8 subjects in each group), and finally determined 48 gene expression signatures. Based on these findings, we further clarify whether these genes mRNA was different expressed in peripheral blood in patients with SSD, MDD and healthy controls (60 subjects respectively). With the help of the quantitative real-time reverse transcription-polymerase chain reaction (RT-qPCR), we gained gene relative expression levels among the three groups. We found that there are three of the forty eight co-regulated genes had differential expression in peripheral blood among the three groups, which are CD84, STRN, CTNS gene (F = 3.528, p = 0.034; F = 3.382, p = 0.039; F = 3.801, p = 0.026, respectively) while there were no significant differences for other genes. CD84, STRN, CTNS gene may have significant value for performing diagnostic functions and classifying SSD, MDD and healthy controls.

Identifying the Gene Signatures from Gene-Pathway Bipartite Network Guarantees the Robust Model Performance on Predicting the Cancer Prognosis

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Li He

2014-01-01

Full Text Available For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.

Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

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Watanabe, Kazuhide; Biesinger, Jacob; Salmans, Michael L; Roberts, Brian S; Arthur, William T; Cleary, Michele; Andersen, Bogi; Xie, Xiaohui; Dai, Xing

2014-01-01

Deregulation of canonical Wnt/CTNNB1 (beta-catenin) pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells. We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis. Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

Comparing cancer vs normal gene expression profiles identifies new disease entities and common transcriptional programs in AML patients

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Rapin, Nicolas; Bagger, Frederik Otzen; Jendholm, Johan

2014-01-01

Gene expression profiling has been used extensively to characterize cancer, identify novel subtypes, and improve patient stratification. However, it has largely failed to identify transcriptional programs that differ between cancer and corresponding normal cells and has not been efficient in iden......-karyotype AML, which allowed for the generation of a highly prognostic survival signature. Collectively, our CvN method holds great potential as a tool for the analysis of gene expression profiles of cancer patients....

Specific extracellular matrix remodeling signature of colon hepatic metastases.

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Maguy Del Rio

Full Text Available To identify genes implicated in metastatic colonization of the liver in colorectal cancer, we collected pairs of primary tumors and hepatic metastases before chemotherapy in 13 patients. We compared mRNA expression in the pairs of patients to identify genes deregulated during metastatic evolution. We then validated the identified genes using data obtained by different groups. The 33-gene signature was able to classify 87% of hepatic metastases, 98% of primary tumors, 97% of normal colon mucosa, and 95% of normal liver tissues in six datasets obtained using five different microarray platforms. The identified genes are specific to colon cancer and hepatic metastases since other metastatic locations and hepatic metastases originating from breast cancer were not classified by the signature. Gene Ontology term analysis showed that 50% of the genes are implicated in extracellular matrix remodeling, and more precisely in cell adhesion, extracellular matrix organization and angiogenesis. Because of the high efficiency of the signature to classify colon hepatic metastases, the identified genes represent promising targets to develop new therapies that will specifically affect hepatic metastasis microenvironment.

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

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Hettne Kristina M

2013-01-01

Full Text Available Abstract Background Availability of chemical response-specific lists of genes (gene sets for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM, and that these can be used with gene set analysis (GSA methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles. Methods We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human and 588 (mouse gene sets from the Comparative Toxicogenomics Database (CTD. We tested for significant differential expression (SDE (false discovery rate -corrected p-values Results Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants had a similar toxicity pattern as the triazoles. We confirmed embryotoxic effects, and discriminated triazoles from other chemicals. Conclusions Gene set analysis with next-gen TM-derived chemical response-specific gene sets is a scalable method for identifying similarities in gene responses to other chemicals, from which one may infer potential mode of action and/or toxic effect.

Neighboring Genes Show Correlated Evolution in Gene Expression

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Ghanbarian, Avazeh T.; Hurst, Laurence D.

2015-01-01

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

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2013-01-01

Background Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set analysis (GSA) methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles. Methods We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human) and 588 (mouse) gene sets from the Comparative Toxicogenomics Database (CTD). We tested for significant differential expression (SDE) (false discovery rate -corrected p-values sets and the CTD-derived gene sets in gene expression (GE) data sets of five chemicals (from experimental models). We tested for SDE of gene sets for six fibrates in a peroxisome proliferator-activated receptor alpha (PPARA) knock-out GE dataset and compared to results from the Connectivity Map. We tested for SDE of 319 next-gen TM-derived gene sets for environmental toxicants in three GE data sets of triazoles, and tested for SDE of 442 gene sets associated with embryonic structures. We compared the gene sets to triazole effects seen in the Whole Embryo Culture (WEC), and used principal component analysis (PCA) to discriminate triazoles from other chemicals. Results Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants had a similar toxicity pattern as the

Gene expression profiles of primary colorectal carcinomas, liver metastases, and carcinomatoses

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Myklebost Ola

2007-01-01

Full Text Available Abstract Background Despite the fact that metastases are the leading cause of colorectal cancer deaths, little is known about the underlying molecular changes in these advanced disease stages. Few have studied the overall gene expression levels in metastases from colorectal carcinomas, and so far, none has investigated the peritoneal carcinomatoses by use of DNA microarrays. Therefore, the aim of the present study is to investigate and compare the gene expression patterns of primary carcinomas (n = 18, liver metastases (n = 4, and carcinomatoses (n = 4, relative to normal samples from the large bowel. Results Transcriptome profiles of colorectal cancer metastases independent of tumor site, as well as separate profiles associated with primary carcinomas, liver metastases, or peritoneal carcinomatoses, were assessed by use of Bayesian statistics. Gains of chromosome arm 5p are common in peritoneal carcinomatoses and several candidate genes (including PTGER4, SKP2, and ZNF622 mapping to this region were overexpressed in the tumors. Expression signatures stratified on TP53 mutation status were identified across all tumors regardless of stage. Furthermore, the gene expression levels for the in vivo tumors were compared with an in vitro model consisting of cell lines representing all three tumor stages established from one patient. Conclusion By statistical analysis of gene expression data from primary colorectal carcinomas, liver metastases, and carcinomatoses, we are able to identify genetic patterns associated with the different stages of tumorigenesis.

Gene Expression Commons: an open platform for absolute gene expression profiling.

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Jun Seita

Full Text Available Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000 of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/ which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.

Molecular Biology In Young Women With Breast Cancer: From Tumor Gene Expression To DNA Mutations.

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Gómez-Flores-Ramos, Liliana; Castro-Sánchez, Andrea; Peña-Curiel, Omar; Mohar-Betancourt, Alejandro

2017-01-01

Young women with breast cancer (YWBC) represent roughly 15% of breast cancer (BC) cases in Latin America and other developing regions. Breast tumors occurring at an early age are more aggressive and have an overall worse prognosis compared to breast tumors in postmenopausal women. The expression of relevant proliferation biomarkers such as endocrine receptors and human epidermal growth factor receptor 2 appears to be unique in YWBC. Moreover, histopathological, molecular, genetic, and genomic studies have shown that YWBC exhibit a higher frequency of aggressive subtypes, differential tumor gene expression, increased genetic susceptibility, and specific genomic signatures, compared to older women with BC. This article reviews the current knowledge on tumor biology and genomic signatures in YWBC.

On reliable discovery of molecular signatures

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Björkegren Johan

2009-01-01

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.

Autism-associated gene expression in peripheral leucocytes commonly observed between subjects with autism and healthy women having autistic children.

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Yuki Kuwano

Full Text Available Autism spectrum disorder (ASD is a severe neuropsychiatric disorder which has complex pathobiology with profound influences of genetic factors in its development. Although the numerous autism susceptible genes were identified, the etiology of autism is not fully explained. Using DNA microarray, we examined gene expression profiling in peripheral blood from 21 individuals in each of the four groups; young adults with ASD, age- and gender-matched healthy subjects (ASD control, healthy mothers having children with ASD (asdMO, and asdMO control. There was no blood relationship between ASD and asdMO. Comparing the ASD group with control, 19 genes were found to be significantly changed. These genes were mainly involved in cell morphology, cellular assembly and organization, and nerve system development and function. In addition, the asdMO group possessed a unique gene expression signature shown as significant alterations of protein synthesis despite of their nonautistic diagnostic status. Moreover, an ASD-associated gene expression signature was commonly observed in both individuals with ASD and asdMO. This unique gene expression profiling detected in peripheral leukocytes from affected subjects with ASD and unaffected mothers having ASD children suggest that a genetic predisposition to ASD may be detectable even in peripheral cells. Altered expression of several autism candidate genes such as FMR-1 and MECP2, could be detected in leukocytes. Taken together, these findings suggest that the ASD-associated genes identified in leukocytes are informative to explore the genetic, epigenetic, and environmental background of ASD and might become potential tools to assess the crucial factors related to the clinical onset of the disorder.

A signature of epithelial-mesenchymal plasticity and stromal activation in primary tumor modulates late recurrence in breast cancer independent of disease subtype.

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Cheng, Qing; Chang, Jeffrey T; Gwin, William R; Zhu, Jun; Ambs, Stefan; Geradts, Joseph; Lyerly, H Kim

2014-07-25

Despite improvements in adjuvant therapy, late systemic recurrences remain a lethal consequence of both early- and late-stage breast cancer. A delayed recurrence is thought to arise from a state of tumor dormancy, but the mechanisms that govern tumor dormancy remain poorly understood. To address the features of breast tumors associated with late recurrence, but not confounded by variations in systemic treatment, we compiled breast tumor gene expression data from 4,767 patients and established a discovery cohort consisting of 743 lymph node-negative patients who did not receive systemic neoadjuvant or adjuvant therapy. We interrogated the gene expression profiles of the 743 tumors and identified gene expression patterns that were associated with early and late disease recurrence among these patients. We applied this classification to a subset of 46 patients for whom expression data from microdissected tumor epithelium and stroma was available, and identified a distinct gene signature in the stroma and also a corresponding tumor epithelium signature that predicted disease recurrence in the discovery cohort. This tumor epithelium signature was then validated as a predictor for late disease recurrence in the entire cohort of 4,767 patients. We identified a novel 51-gene signature from microdissected tumor epithelium associated with late disease recurrence in breast cancer independent of the molecular disease subtype. This signature correlated with gene expression alterations in the adjacent tumor stroma and describes a process of epithelial to mesenchymal transition (EMT) and tumor-stroma interactions. Our findings suggest that an EMT-related gene signature in the tumor epithelium is related to both stromal activation and escape from disease dormancy in breast cancer. The presence of a late recurrence gene signature in the primary tumor also suggests that intrinsic features of this tumor regulate the transition of disseminated tumor cells into a dormant phenotype with

FOXP1 suppresses immune response signatures and MHC class II expression in activated B-cell-like diffuse large B-cell lymphomas

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Brown, P J; Wong, K K; Felce, S L

2016-01-01

The FOXP1 (forkhead box P1) transcription factor is a marker of poor prognosis in diffuse large B-cell lymphoma (DLBCL). Here microarray analysis of FOXP1-silenced DLBCL cell lines identified differential regulation of immune response signatures and major histocompatibility complex class II (MHC II......) genes as some of the most significant differences between germinal center B-cell (GCB)-like DLBCL with full-length FOXP1 protein expression versus activated B-cell (ABC)-like DLBCL expressing predominantly short FOXP1 isoforms. In an independent primary DLBCL microarray data set, multiple MHC II genes......, including human leukocyte antigen DR alpha chain (HLA-DRA), were inversely correlated with FOXP1 transcript expression (PABC-DLBCL cells led to increased cell-surface expression of HLA-DRA and CD74. In R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone...

Common patterns and disease-related signatures in tuberculosis and sarcoidosis.

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Maertzdorf, Jeroen; Weiner, January; Mollenkopf, Hans-Joachim; Bauer, Torsten; Prasse, Antje; Müller-Quernheim, Joachim; Kaufmann, Stefan H E

2012-05-15

In light of the marked global health impact of tuberculosis (TB), strong focus has been on identifying biosignatures. Gene expression profiles in blood cells identified so far are indicative of a persistent activation of the immune system and chronic inflammatory pathology in active TB. Definition of a biosignature with unique specificity for TB demands that identified profiles can differentiate diseases with similar pathology, like sarcoidosis (SARC). Here, we present a detailed comparison between pulmonary TB and SARC, including whole-blood gene expression profiling, microRNA expression, and multiplex serum analytes. Our analysis reveals that previously disclosed gene expression signatures in TB show highly similar patterns in SARC, with a common up-regulation of proinflammatory pathways and IFN signaling and close similarity to TB-related signatures. microRNA expression also presented a highly similar pattern in both diseases, whereas cytokines in the serum of TB patients revealed a slightly elevated proinflammatory pattern compared with SARC and controls. Our results indicate several differences in expression between the two diseases, with increased metabolic activity and significantly higher antimicrobial defense responses in TB. However, matrix metallopeptidase 14 was identified as the most distinctive marker of SARC. Described communalities as well as unique signatures in blood profiles of two distinct inflammatory pulmonary diseases not only have considerable implications for the design of TB biosignatures and future diagnosis, but they also provide insights into biological processes underlying chronic inflammatory disease entities of different etiology.

Differential gene expression profiles of peripheral blood mononuclear cells in childhood asthma.

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Kong, Qian; Li, Wen-Jing; Huang, Hua-Rong; Zhong, Ying-Qiang; Fang, Jian-Pei

2015-05-01

Asthma is a common childhood disease with strong genetic components. This study compared whole-genome expression differences between asthmatic young children and healthy controls to identify gene signatures of childhood asthma. Total RNA extracted from peripheral blood mononuclear cells (PBMC) was subjected to microarray analysis. QRT-PCR was performed to verify the microarray results. Classification and functional characterization of differential genes were illustrated by hierarchical clustering and gene ontology analysis. Multiple logistic regression (MLR) analysis, receiver operating characteristic (ROC) curve analysis, and discriminate power were used to scan asthma-specific diagnostic markers. For fold-change>2 and p childhood asthma model for prediction and diagnosis.

Epipodial Tentacle Gene Expression and Predetermined Resilience to Summer Mortality in the Commercially Important Greenlip Abalone, Haliotis laevigata.

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Shiel, Brett P; Hall, Nathan E; Cooke, Ira R; Robinson, Nicholas A; Strugnell, Jan M

2017-04-01

"Summer mortality" is a phenomenon that occurs during warm water temperature spikes that results in the mass mortality of many ecologically and economically important mollusks such as abalone. This study aimed to determine whether the baseline gene expression of abalone before a laboratory-induced summer mortality event was associated with resilience to summer mortality. Tentacle transcriptomes of 35 greenlip abalone (Haliotis laevigata) were sequenced prior to the animals being exposed to an increase in water temperature-simulating conditions which have previously resulted in summer mortality. Abalone derived from three source locations with different environmental conditions were categorized as susceptible or resistant to summer mortality depending on whether they died or survived after the water temperature was increased. We detected two genes showing significantly higher expression in resilient abalone relative to susceptible abalone prior to the laboratory-induced summer mortality event. One of these genes was annotated through the NCBI non-redundant protein database using BLASTX to an anemone (Exaiptasia pallida) Transposon Ty3-G Gag Pol polyprotein. Distinct gene expression signatures were also found between resilient and susceptible abalone depending on the population origin, which may suggest divergence in local adaptation mechanisms for resilience. Many of these genes have been suggested to be involved in antioxidant and immune-related functions. The identification of these genes and their functional roles have enhanced our understanding of processes that may contribute to summer mortality in abalone. Our study supports the hypothesis that prestress gene expression signatures are indicative of the likelihood of summer mortality.

Circulating neutrophil transcriptome may reveal intracranial aneurysm signature.

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Vincent M Tutino

Full Text Available Unruptured intracranial aneurysms (IAs are typically asymptomatic and undetected except for incidental discovery on imaging. Blood-based diagnostic biomarkers could lead to improvements in IA management. This exploratory study examined circulating neutrophils to determine whether they carry RNA expression signatures of IAs.Blood samples were collected from patients receiving cerebral angiography. Eleven samples were collected from patients with IAs and 11 from patients without IAs as controls. Samples from the two groups were paired based on demographics and comorbidities. RNA was extracted from isolated neutrophils and subjected to next-generation RNA sequencing to obtain differential expressions for identification of an IA-associated signature. Bioinformatics analyses, including gene set enrichment analysis and Ingenuity Pathway Analysis, were used to investigate the biological function of all differentially expressed transcripts.Transcriptome profiling identified 258 differentially expressed transcripts in patients with and without IAs. Expression differences were consistent with peripheral neutrophil activation. An IA-associated RNA expression signature was identified in 82 transcripts (p<0.05, fold-change ≥2. This signature was able to separate patients with and without IAs on hierarchical clustering. Furthermore, in an independent, unpaired, replication cohort of patients with IAs (n = 5 and controls (n = 5, the 82 transcripts separated 9 of 10 patients into their respective groups.Preliminary findings show that RNA expression from circulating neutrophils carries an IA-associated signature. These findings highlight a potential to use predictive biomarkers from peripheral blood samples to identify patients with IAs.

Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data.

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Lee, Hyeonjeong; Shin, Miyoung

2017-01-01

The problem of discovering genetic markers as disease signatures is of great significance for the successful diagnosis, treatment, and prognosis of complex diseases. Even if many earlier studies worked on identifying disease markers from a variety of biological resources, they mostly focused on the markers of genes or gene-sets (i.e., pathways). However, these markers may not be enough to explain biological interactions between genetic variables that are related to diseases. Thus, in this study, our aim is to investigate distinctive associations among active pathways (i.e., pathway-sets) shown each in case and control samples which can be observed from gene expression and/or methylation data. The pathway-sets are obtained by identifying a set of associated pathways that are often active together over a significant number of class samples. For this purpose, gene expression or methylation profiles are first analyzed to identify significant (active) pathways via gene-set enrichment analysis. Then, regarding these active pathways, an association rule mining approach is applied to examine interesting pathway-sets in each class of samples (case or control). By doing so, the sets of associated pathways often working together in activity profiles are finally chosen as our distinctive signature of each class. The identified pathway-sets are aggregated into a pathway activity network (PAN), which facilitates the visualization of differential pathway associations between case and control samples. From our experiments with two publicly available datasets, we could find interesting PAN structures as the distinctive signatures of breast cancer and uterine leiomyoma cancer, respectively. Our pathway-set markers were shown to be superior or very comparable to other genetic markers (such as genes or gene-sets) in disease classification. Furthermore, the PAN structure, which can be constructed from the identified markers of pathway-sets, could provide deeper insights into

Molecular signatures define alopecia areata subtypes and transcriptional biomarkers

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Ali Jabbari

2016-05-01

Full Text Available Alopecia areata (AA is an autoimmune disease typified by nonscarring hair loss with a variable clinical course. In this study, we conducted whole genome gene expression analysis of 96 human scalp skin biopsy specimens from AA or normal control subjects. Based on gene expression profiling, samples formed distinct clusters based on the presence or absence of disease as well as disease phenotype (patchy disease compared with alopecia totalis or universalis. Differential gene expression analysis allowed us to robustly demonstrate graded immune activity in samples of increasing phenotypic severity and generate a quantitative gene expression scoring system that classified samples based on interferon and cytotoxic T lymphocyte immune signatures critical for disease pathogenesis.

The Transcriptional Signature of Active Tuberculosis Reflects Symptom Status in Extra-Pulmonary and Pulmonary Tuberculosis.

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Simon Blankley

Full Text Available Mycobacterium tuberculosis infection is a leading cause of infectious death worldwide. Gene-expression microarray studies profiling the blood transcriptional response of tuberculosis (TB patients have been undertaken in order to better understand the host immune response as well as to identify potential biomarkers of disease. To date most of these studies have focused on pulmonary TB patients with gene-expression profiles of extra-pulmonary TB patients yet to be compared to those of patients with pulmonary TB or sarcoidosis.A novel cohort of patients with extra-pulmonary TB and sarcoidosis was recruited and the transcriptional response of these patients compared to those with pulmonary TB using a variety of transcriptomic approaches including testing a previously defined 380 gene meta-signature of active TB.The 380 meta-signature broadly differentiated active TB from healthy controls in this new dataset consisting of pulmonary and extra-pulmonary TB. The top 15 genes from this meta-signature had a lower sensitivity for differentiating extra-pulmonary TB from healthy controls as compared to pulmonary TB. We found the blood transcriptional responses in pulmonary and extra-pulmonary TB to be heterogeneous and to reflect the extent of symptoms of disease.The transcriptional signature in extra-pulmonary TB demonstrated heterogeneity of gene expression reflective of symptom status, while the signature of pulmonary TB was distinct, based on a higher proportion of symptomatic individuals. These findings are of importance for the rational design and implementation of mRNA based TB diagnostics.

Expressiveness considerations of XML signatures

DEFF Research Database (Denmark)

Jensen, Meiko; Meyer, Christopher

2011-01-01

XML Signatures are used to protect XML-based Web Service communication against a broad range of attacks related to man-in-the-middle scenarios. However, due to the complexity of the Web Services specification landscape, the task of applying XML Signatures in a robust and reliable manner becomes...... more and more challenging. In this paper, we investigate this issue, describing how an attacker can still interfere with Web Services communication even in the presence of XML Signatures. Additionally, we discuss the interrelation of XML Signatures and XML Encryption, focussing on their security...

Integrative ChIP-seq/microarray analysis identifies a CTNNB1 target signature enriched in intestinal stem cells and colon cancer.

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Kazuhide Watanabe

Full Text Available Deregulation of canonical Wnt/CTNNB1 (beta-catenin pathway is one of the earliest events in the pathogenesis of colon cancer. Mutations in APC or CTNNB1 are highly frequent in colon cancer and cause aberrant stabilization of CTNNB1, which activates the transcription of Wnt target genes by binding to chromatin via the TCF/LEF transcription factors. Here we report an integrative analysis of genome-wide chromatin occupancy of CTNNB1 by chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq and gene expression profiling by microarray analysis upon RNAi-mediated knockdown of CTNNB1 in colon cancer cells.We observed 3629 CTNNB1 binding peaks across the genome and a significant correlation between CTNNB1 binding and knockdown-induced gene expression change. Our integrative analysis led to the discovery of a direct Wnt target signature composed of 162 genes. Gene ontology analysis of this signature revealed a significant enrichment of Wnt pathway genes, suggesting multiple feedback regulations of the pathway. We provide evidence that this gene signature partially overlaps with the Lgr5+ intestinal stem cell signature, and is significantly enriched in normal intestinal stem cells as well as in clinical colorectal cancer samples. Interestingly, while the expression of the CTNNB1 target gene set does not correlate with survival, elevated expression of negative feedback regulators within the signature predicts better prognosis.Our data provide a genome-wide view of chromatin occupancy and gene regulation of Wnt/CTNNB1 signaling in colon cancer cells.

Gene expression markers in circulating tumor cells may predict bone metastasis and response to hormonal treatment in breast cancer.

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Wang, Haiying; Molina, Julian; Jiang, John; Ferber, Matthew; Pruthi, Sandhya; Jatkoe, Timothy; Derecho, Carlo; Rajpurohit, Yashoda; Zheng, Jian; Wang, Yixin

2013-11-01

Circulating tumor cells (CTCs) have recently attracted attention due to their potential as prognostic and predictive markers for the clinical management of metastatic breast cancer patients. The isolation of CTCs from patients may enable the molecular characterization of these cells, which may help establish a minimally invasive assay for the prediction of metastasis and further optimization of treatment. Molecular markers of proven clinical value may therefore be useful in predicting disease aggressiveness and response to treatment. In our earlier study, we identified a gene signature in breast cancer that appears to be significantly associated with bone metastasis. Among the genes that constitute this signature, trefoil factor 1 (TFF1) was identified as the most differentially expressed gene associated with bone metastasis. In this study, we investigated 25 candidate gene markers in the CTCs of metastatic breast cancer patients with different metastatic sites. The panel of the 25 markers was investigated in 80 baseline samples (first blood draw of CTCs) and 30 follow-up samples. In addition, 40 healthy blood donors (HBDs) were analyzed as controls. The assay was performed using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) with RNA extracted from CTCs captured by the CellSearch system. Our study indicated that 12 of the genes were uniquely expressed in CTCs and 10 were highly expressed in the CTCs obtained from patients compared to those obtained from HBDs. Among these genes, the expression of keratin 19 was highly correlated with the CTC count. The TFF1 expression in CTCs was a strong predictor of bone metastasis and the patients with a high expression of estrogen receptor β in CTCs exhibited a better response to hormonal treatment. Molecular characterization of these genes in CTCs may provide a better understanding of the mechanism underlying tumor metastasis and identify gene markers in CTCs for predicting disease progression and

Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data

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Ghosh Debashis

2004-12-01

Full Text Available Abstract Background An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. Results By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies (n = 305 samples on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. Conclusion The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta

An evolutionarily conserved sexual signature in the primate brain.

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Björn Reinius

2008-06-01

Full Text Available The question of a potential biological sexual signature in the human brain is a heavily disputed subject. In order to provide further insight into this issue, we used an evolutionary approach to identify genes with sex differences in brain expression level among primates. We reasoned that expression patterns important to uphold key male and female characteristics may be conserved during evolution. We selected cortex for our studies because this specific brain region is responsible for many higher behavioral functions. We compared gene expression profiles in the occipital cortex of male and female humans (Homo sapiens, a great ape and cynomolgus macaques (Macaca fascicularis, an old world monkey, two catarrhine species that show abundant morphological sexual dimorphism, as well as in common marmosets (Callithrix Jacchus, a new world monkey which are relatively sexually monomorphic. We identified hundreds of genes with sex-biased expression patterns in humans and macaques, while fewer than ten were differentially expressed between the sexes in marmosets. In primates, a general rule is that many of the morphological and behavioral sexual dimorphisms seen in polygamous species, such as macaques, are typically less pronounced in monogamous species such as the marmosets. Our observations suggest that this correlation may also be reflected in the extent of sex-biased gene expression in the brain. We identified 85 genes with common sex-biased expression, in both human and macaque and 2 genes, X inactivation-specific transcript (XIST and Heat shock factor binding protein 1 (HSBP1, that were consistently sex-biased in the female direction in human, macaque, and marmoset. These observations imply a conserved signature of sexual gene expression dimorphism in cortex of primates. Further, we found that the coding region of female-biased genes is more evolutionarily constrained compared to the coding region of both male-biased and non sex-biased brain

Gene expression signature is shared by patients with Alzheimer's disease and schizophrenia at the superior temporal gyrus.

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Horesh, Y; Katsel, P; Haroutunian, V; Domany, E

2011-03-01

Alzheimer's disease and Schizophrenia are two common diseases of the brain with significant differences in neuropathology, etiology and symptoms. This dissimilarity in the two diseases makes a comparison of the two ideal for detecting molecular substrates that are common to brain disorders in general. In this study, we compared gene expression profiles across multiple brain areas, taken postmortem from patients with well-characterized Alzheimer's disease and Schizophrenia, and from cognitively normal control group with no neuro- or psychopathology. Although the totality of gene expression changes in the two diseases is dissimilar, a subset of genes appears to play a role in both diseases in specific brain regions. We find at Brodmann area 22, the superior temporal gyrus, a statistically significant number of genes with apparently disregulated expression in both diseases. Furthermore, we found genes that differentiate the two diseases from the control across multiple brain regions, and note that these genes were usually down-regulated. Brodmann area 8, part of the superior frontal cortex, is relatively abundant with them. We show overwhelming statistical evidence for Alzheimer's and Schizophrenia sharing a specific molecular background at the superior temporal gyrus. We suggest that impairment of the regulation of autophagy pathway is shared, in BA 22, by the two diseases. © 2010 The Author(s). European Journal of Neurology © 2010 EFNS.

Imaging gene expression in gene therapy

International Nuclear Information System (INIS)

Wiebe, Leonard I.

1997-01-01

Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on 'suicide gene therapy' of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k + ) has been use for 'suicide' in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k + gene expression where the H S V-1 t k + gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([ 18 F]F H P G; [ 18 F]-A C V), and pyrimidine- ([ 123 / 131 I]I V R F U; [ 124 / 131I ]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [ 123 / 131I ]I V R F U imaging with the H S V-1 t k + reporter gene will be presented

Adipose Gene Expression Prior to Weight Loss Can Differentiate and Weakly Predict Dietary Responders

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Mutch, David M.; Temanni, M. Ramzi; Henegar, Corneliu; Combes, Florence; Pelloux, Véronique; Holst, Claus; Sørensen, Thorkild I. A.; Astrup, Arne; Martinez, J. Alfredo; Saris, Wim H. M.; Viguerie, Nathalie; Langin, Dominique; Zucker, Jean-Daniel; Clément, Karine

2007-01-01

Background The ability to identify obese individuals who will successfully lose weight in response to dietary intervention will revolutionize disease management. Therefore, we asked whether it is possible to identify subjects who will lose weight during dietary intervention using only a single gene expression snapshot. Methodology/Principal Findings The present study involved 54 female subjects from the Nutrient-Gene Interactions in Human Obesity-Implications for Dietary Guidelines (NUGENOB) trial to determine whether subcutaneous adipose tissue gene expression could be used to predict weight loss prior to the 10-week consumption of a low-fat hypocaloric diet. Using several statistical tests revealed that the gene expression profiles of responders (8–12 kgs weight loss) could always be differentiated from non-responders (diet is able to differentiate responders from non-responders as well as serve as a weak predictor of subjects destined to lose weight. While the degree of prediction accuracy currently achieved with a gene expression snapshot is perhaps insufficient for clinical use, this work reveals that the comprehensive molecular signature of adipose tissue paves the way for the future of personalized nutrition. PMID:18094752

The gene expression profile of non-cultured, highly purified human adipose tissue pericytes: Transcriptomic evidence that pericytes are stem cells in human adipose tissue

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Silva Meirelles, Lindolfo da, E-mail: lindolfomeirelles@gmail.com [Center for Cell-Based Therapy (CEPID/FAPESP), Regional Center for Hemotherapy of Ribeirão Preto, University of São Paulo, Rua Tenente Catão Roxo 2501, 14051-140 Ribeirão Preto, SP (Brazil); Laboratory for Stem Cells and Tissue Engineering, PPGBioSaúde, Lutheran University of Brazil, Av. Farroupilha 8001, 92425-900 Canoas, RS (Brazil); Deus Wagatsuma, Virgínia Mara de; Malta, Tathiane Maistro; Bonini Palma, Patrícia Viana [Center for Cell-Based Therapy (CEPID/FAPESP), Regional Center for Hemotherapy of Ribeirão Preto, University of São Paulo, Rua Tenente Catão Roxo 2501, 14051-140 Ribeirão Preto, SP (Brazil); Araújo, Amélia Goes; Panepucci, Rodrigo Alexandre [Laboratory of Large-Scale Functional Biology (LLSFBio), Regional Center for Hemotherapy of Ribeirão Preto, University of São Paulo, Rua Tenente Catão Roxo 2501, 14051-140 Ribeirão Preto, SP (Brazil); and others

2016-12-10

Pericytes (PCs) are a subset of perivascular cells that can give rise to mesenchymal stromal cells (MSCs) when culture-expanded, and are postulated to give rise to MSC-like cells during tissue repair in vivo. PCs have been suggested to behave as stem cells (SCs) in situ in animal models, although evidence for this role in humans is lacking. Here, we analyzed the transcriptomes of highly purified, non-cultured adipose tissue (AT)-derived PCs (ATPCs) to detect gene expression changes that occur as they acquire MSC characteristics in vitro, and evaluated the hypothesis that human ATPCs exhibit a gene expression profile compatible with an AT SC phenotype. The results showed ATPCs are non-proliferative and express genes characteristic not only of PCs, but also of AT stem/progenitor cells. Additional analyses defined a gene expression signature for ATPCs, and revealed putative novel ATPC markers. Almost all AT stem/progenitor cell genes differentially expressed by ATPCs were not expressed by ATMSCs or culture-expanded ATPCs. Genes expressed by ATMSCs but not by ATPCs were also identified. These findings strengthen the hypothesis that PCs are SCs in vascularized tissues, highlight gene expression changes they undergo as they assume an MSC phenotype, and provide new insights into PC biology. - Highlights: • Non-cultured adipose tissue-derived human pericytes (ncATPCs) exhibit a distinctive gene expression signature. • ncATPCs express key adipose tissue stem cell genes previously described in vivo in mice. • ncATPCs express message for anti-proliferative and antiangiogenic molecules. • Most ncATPC-specific transcripts are absent in culture-expanded pericytes or ATMSCs • Gene expression changes ncATPCs undergo as they acquire a cultured ATMSC phenotype are pointed out.

The gene expression profile of non-cultured, highly purified human adipose tissue pericytes: Transcriptomic evidence that pericytes are stem cells in human adipose tissue

International Nuclear Information System (INIS)

Silva Meirelles, Lindolfo da; Deus Wagatsuma, Virgínia Mara de; Malta, Tathiane Maistro; Bonini Palma, Patrícia Viana; Araújo, Amélia Goes; Panepucci, Rodrigo Alexandre

2016-01-01

Pericytes (PCs) are a subset of perivascular cells that can give rise to mesenchymal stromal cells (MSCs) when culture-expanded, and are postulated to give rise to MSC-like cells during tissue repair in vivo. PCs have been suggested to behave as stem cells (SCs) in situ in animal models, although evidence for this role in humans is lacking. Here, we analyzed the transcriptomes of highly purified, non-cultured adipose tissue (AT)-derived PCs (ATPCs) to detect gene expression changes that occur as they acquire MSC characteristics in vitro, and evaluated the hypothesis that human ATPCs exhibit a gene expression profile compatible with an AT SC phenotype. The results showed ATPCs are non-proliferative and express genes characteristic not only of PCs, but also of AT stem/progenitor cells. Additional analyses defined a gene expression signature for ATPCs, and revealed putative novel ATPC markers. Almost all AT stem/progenitor cell genes differentially expressed by ATPCs were not expressed by ATMSCs or culture-expanded ATPCs. Genes expressed by ATMSCs but not by ATPCs were also identified. These findings strengthen the hypothesis that PCs are SCs in vascularized tissues, highlight gene expression changes they undergo as they assume an MSC phenotype, and provide new insights into PC biology. - Highlights: • Non-cultured adipose tissue-derived human pericytes (ncATPCs) exhibit a distinctive gene expression signature. • ncATPCs express key adipose tissue stem cell genes previously described in vivo in mice. • ncATPCs express message for anti-proliferative and antiangiogenic molecules. • Most ncATPC-specific transcripts are absent in culture-expanded pericytes or ATMSCs • Gene expression changes ncATPCs undergo as they acquire a cultured ATMSC phenotype are pointed out.

Comparison of transcriptomic signature of post-Chernobyl and postradiotherapy thyroid tumors.

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Ory, Catherine; Ugolin, Nicolas; Hofman, Paul; Schlumberger, Martin; Likhtarev, Illya A; Chevillard, Sylvie

2013-11-01

We previously identified two highly discriminating and predictive radiation-induced transcriptomic signatures by comparing series of sporadic and postradiotherapy thyroid tumors (322-gene signature), and by reanalyzing a previously published data set of sporadic and post-Chernobyl thyroid tumors (106-gene signature). The aim of the present work was (i) to compare the two signatures in terms of gene expression deregulations and molecular features/pathways, and (ii) to test the capacity of the postradiotherapy signature in classifying the post-Chernobyl series of tumors and reciprocally of the post-Chernobyl signature in classifying the postradiotherapy-induced tumors. We now explored if postradiotherapy and post-Chernobyl papillary thyroid carcinomas (PTC) display common molecular features by comparing molecular pathways deregulated in the two tumor series, and tested the potential of gene subsets of the postradiotherapy signature to classify the post-Chernobyl series (14 sporadic and 12 post-Chernobyl PTC), and reciprocally of gene subsets of the post-Chernobyl signature to classify the postradiotherapy series (15 sporadic and 12 postradiotherapy PTC), by using conventional principal component analysis. We found that the five genes common to the two signatures classified the learning/training tumors (used to search these signatures) of both the postradiotherapy (seven PTC) and the post-Chernobyl (six PTC) thyroid tumor series as compared with the sporadic tumors (seven sporadic PTC in each series). Importantly, these five genes were also effective for classifying independent series of postradiotherapy (five PTC) and post-Chernobyl (six PTC) tumors compared to independent series of sporadic tumors (eight PTC and six PTC respectively; testing tumors). Moreover, part of each postradiotherapy (32 genes) and post-Chernobyl signature (16 genes) cross-classified the respective series of thyroid tumors. Finally, several molecular pathways deregulated in post

A gene expression signature of retinoblastoma loss-of-function is a predictive biomarker of resistance to palbociclib in breast cancer cell lines and is prognostic in patients with ER positive early breast cancer.

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Malorni, Luca; Piazza, Silvano; Ciani, Yari; Guarducci, Cristina; Bonechi, Martina; Biagioni, Chiara; Hart, Christopher D; Verardo, Roberto; Di Leo, Angelo; Migliaccio, Ilenia

2016-09-13

Palbociclib is a CDK4/6 inhibitor that received FDA approval for treatment of hormone receptor positive (HR+) HER2 negative (HER2neg) advanced breast cancer. To better personalize patients treatment it is critical to identify subgroups that would mostly benefit from it. We hypothesize that complex alterations of the Retinoblastoma (Rb) pathway might be implicated in resistance to CDK4/6 inhibitors and aim to investigate whether signatures of Rb loss-of-function would identify breast cancer cell lines resistant to palbociclib. We established a gene expression signature of Rb loss-of-function (RBsig) by identifying genes correlated with E2F1 and E2F2 expression in breast cancers within The Cancer Genome Atlas. We assessed the RBsig prognostic role in the METABRIC and in a comprehensive breast cancer meta-dataset. Finally, we analyzed whether RBsig would discriminate palbociclib-sensitive and -resistant breast cancer cells in a large RNA sequencing-based dataset. The RBsig was associated with RB1 genetic status in all tumors (p <7e-32) and in luminal or basal subtypes (p < 7e-11 and p < 0.002, respectively). The RBsig was prognostic in the METABRIC dataset (discovery: HR = 1.93 [1.5-2.4] p = 1.4e-08; validation: HR = 2.01 [1.6-2.5] p = 1.3e-09). Untreated and endocrine treated patients with estrogen receptor positive breast cancer expressing high RBsig had significantly worse recurrence free survival compared to those with low RBsig (HR = 2.37 [1.8 - 3.2] p = 1.87e-08 and HR = 2.62 [1.9- 3.5] p = 8.6e-11, respectively). The RBsig was able to identify palbociclib resistant and sensitive breast cancer cells (ROC AUC = 0,7778). Signatures of RB loss might be helpful in personalizing treatment of patients with HR+/HER2neg breast cancer. Further validation in patients receiving palbociclib is warranted.

Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data

OpenAIRE

Ezer, Daphne; Moignard, Victoria; G?ttgens, Berthold; Adryan, Boris

2016-01-01

Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete ...

Global gene expression in muscle from fasted/refed trout reveals up-regulation of genes promoting myofibre hypertrophy but not myofibre production.

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Rescan, Pierre-Yves; Le Cam, Aurelie; Rallière, Cécile; Montfort, Jérôme

2017-06-07

Compensatory growth is a phase of rapid growth, greater than the growth rate of control animals, that occurs after a period of growth-stunting conditions. Fish show a capacity for compensatory growth after alleviation of dietary restriction, but the underlying cellular mechanisms are unknown. To learn more about the contribution of genes regulating hypertrophy (an increase in muscle fibre size) and hyperplasia (the generation of new muscle fibres) in the compensatory muscle growth response in fish, we used high-density microarray analysis to investigate the global gene expression in muscle of trout during a fasting-refeeding schedule and in muscle of control-fed trout displaying normal growth. The compensatory muscle growth signature, as defined by genes up-regulated in muscles of refed trout compared with control-fed trout, showed enrichment in functional categories related to protein biosynthesis and maturation, such as RNA processing, ribonucleoprotein complex biogenesis, ribosome biogenesis, translation and protein folding. This signature was also enriched in chromatin-remodelling factors of the protein arginine N-methyl transferase family. Unexpectedly, functional categories related to cell division and DNA replication were not inferred from the molecular signature of compensatory muscle growth, and this signature contained virtually none of the genes previously reported to be up-regulated in hyperplastic growth zones of the late trout embryo myotome and to potentially be involved in production of new myofibres, notably genes encoding myogenic regulatory factors, transmembrane receptors essential for myoblast fusion or myofibrillar proteins predominant in nascent myofibres. Genes promoting myofibre growth, but not myofibre formation, were up-regulated in muscles of refed trout compared with continually fed trout. This suggests that a compensatory muscle growth response, resulting from the stimulation of hypertrophy but not the stimulation of hyperplasia

Minimising Immunohistochemical False Negative ER Classification Using a Complementary 23 Gene Expression Signature of ER Status

DEFF Research Database (Denmark)

Li, Qiyuan; Eklund, Aron Charles; Birkbak, Nicolai Juul

2010-01-01

with clinical outcome. METHODOLOGY/PRINCIPAL FINDINGS: Firstly, ER status was discriminated by fitting the bimodal expression of ESR1 to a mixed Gaussian model. The discriminative power of ESR1 suggested bimodal expression as an efficient way to stratify breast cancer; therefore we identified a set of genes...

Circulating neutrophil transcriptome may reveal intracranial aneurysm signature

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Tutino, Vincent M.; Poppenberg, Kerry E.; Jiang, Kaiyu; Jarvis, James N.; Sun, Yijun; Sonig, Ashish; Siddiqui, Adnan H.; Snyder, Kenneth V.; Levy, Elad I.; Kolega, John

2018-01-01

Background Unruptured intracranial aneurysms (IAs) are typically asymptomatic and undetected except for incidental discovery on imaging. Blood-based diagnostic biomarkers could lead to improvements in IA management. This exploratory study examined circulating neutrophils to determine whether they carry RNA expression signatures of IAs. Methods Blood samples were collected from patients receiving cerebral angiography. Eleven samples were collected from patients with IAs and 11 from patients without IAs as controls. Samples from the two groups were paired based on demographics and comorbidities. RNA was extracted from isolated neutrophils and subjected to next-generation RNA sequencing to obtain differential expressions for identification of an IA-associated signature. Bioinformatics analyses, including gene set enrichment analysis and Ingenuity Pathway Analysis, were used to investigate the biological function of all differentially expressed transcripts. Results Transcriptome profiling identified 258 differentially expressed transcripts in patients with and without IAs. Expression differences were consistent with peripheral neutrophil activation. An IA-associated RNA expression signature was identified in 82 transcripts (pIAs on hierarchical clustering. Furthermore, in an independent, unpaired, replication cohort of patients with IAs (n = 5) and controls (n = 5), the 82 transcripts separated 9 of 10 patients into their respective groups. Conclusion Preliminary findings show that RNA expression from circulating neutrophils carries an IA-associated signature. These findings highlight a potential to use predictive biomarkers from peripheral blood samples to identify patients with IAs. PMID:29342213

Both noncoding and protein-coding RNAs contribute to gene expression evolution in the primate brain.

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Babbitt, Courtney C; Fedrigo, Olivier; Pfefferle, Adam D; Boyle, Alan P; Horvath, Julie E; Furey, Terrence S; Wray, Gregory A

2010-01-18

Despite striking differences in cognition and behavior between humans and our closest primate relatives, several studies have found little evidence for adaptive change in protein-coding regions of genes expressed primarily in the brain. Instead, changes in gene expression may underlie many cognitive and behavioral differences. Here, we used digital gene expression: tag profiling (here called Tag-Seq, also called DGE:tag profiling) to assess changes in global transcript abundance in the frontal cortex of the brains of 3 humans, 3 chimpanzees, and 3 rhesus macaques. A substantial fraction of transcripts we identified as differentially transcribed among species were not assayed in previous studies based on microarrays. Differentially expressed tags within coding regions are enriched for gene functions involved in synaptic transmission, transport, oxidative phosphorylation, and lipid metabolism. Importantly, because Tag-Seq technology provides strand-specific information about all polyadenlyated transcripts, we were able to assay expression in noncoding intragenic regions, including both sense and antisense noncoding transcripts (relative to nearby genes). We find that many noncoding transcripts are conserved in both location and expression level between species, suggesting a possible functional role. Lastly, we examined the overlap between differential gene expression and signatures of positive selection within putative promoter regions, a sign that these differences represent adaptations during human evolution. Comparative approaches may provide important insights into genes responsible for differences in cognitive functions between humans and nonhuman primates, as well as highlighting new candidate genes for studies investigating neurological disorders.

Bioinformatics analysis of the factors controlling type I IFN gene expression in autoimmune disease and virus-induced immunity

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Di eFeng

2013-09-01

Full Text Available Patients with systemic lupus erythematosus (SLE and Sjögren's syndrome (SS display increased levels of type I IFN-induced genes. Plasmacytoid dendritic cells (PDCs are natural interferon producing cells and considered to be a primary source of IFN-α in these two diseases. Differential expression patterns of type I IFN inducible transcripts can be found in different immune cell subsets and in patients with both active and inactive autoimmune disease. A type I IFN gene signature generally consists of three groups of IFN-induced genes - those regulated in response to virus-induced type I IFN, those regulated by the IFN-induced mitogen-activated protein kinase/extracellular-regulated kinase (MAPK/ERK pathway, and those by the IFN-induced phosphoinositide-3 kinase (PI-3K pathway. These three groups of type I IFN-regulated genes control important cellular processes such as apoptosis, survival, adhesion, and chemotaxis, that when dysregulated, contribute to autoimmunity. With the recent generation of large datasets in the public domain from next-generation sequencing and DNA microarray experiments, one can perform detailed analyses of cell type-specific gene signatures as well as identify distinct transcription factors that differentially regulate these gene signatures. We have performed bioinformatics analysis of data in the public domain and experimental data from our lab to gain insight into the regulation of type I IFN gene expression. We have found that the genetic landscape of the IFNA and IFNB genes are occupied by transcription factors, such as insulators CTCF and cohesin, that negatively regulate transcription, as well as IRF5 and IRF7, that positively and distinctly regulate IFNA subtypes. A detailed understanding of the factors controlling type I IFN gene transcription will significantly aid in the identification and development of new therapeutic strategies targeting the IFN pathway in autoimmune disease.

Imaging gene expression in gene therapy

Energy Technology Data Exchange (ETDEWEB)

Wiebe, Leonard I. [Alberta Univ., Edmonton (Canada). Noujaim Institute for Pharmaceutical Oncology Research

1997-12-31

Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on `suicide gene therapy` of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k{sup +}) has been use for `suicide` in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k{sup +} gene expression where the H S V-1 t k{sup +} gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([{sup 18} F]F H P G; [{sup 18} F]-A C V), and pyrimidine- ([{sup 123}/{sup 131} I]I V R F U; [{sup 124}/{sup 131I}]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [{sup 123}/{sup 131I}]I V R F U imaging with the H S V-1 t k{sup +} reporter gene will be presented

Common changes in global gene expression induced by RNA polymerase inhibitors in Shigella flexneri.

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Hua Fu

Full Text Available Characterization of expression profile of organisms in response to antimicrobials provides important information on the potential mechanism of action of the drugs. The special expression signature can be used to predict whether other drugs act on the same target. Here, the common response of Shigella flexneri to two inhibitors of RNA polymerase was examined using gene expression profiling. Consistent with similar effects of the two drugs, the gene expression profiles indicated that responses of the bacteria to these drugs were roughly the same, with 225 genes affected commonly. Of them, 88 were induced and 137 were repressed. Real-time PCR was performed for selected genes to verify the microarray results. Analysis of the expression data revealed that more than 30% of the plasmid-encoded genes on the array were up-regulated by the antibiotics including virF regulon, other virulence-related genes, and genes responsible for plasmid replication, maintenance, and transfer. In addition, some chromosome-encoded genes involved in virulence and genes acquired from horizontal transfer were also significantly up-regulated. However, the expression of genes encoding the beta-subunit of RNA polymerase was increased moderately. The repressed genes include those that code for products associated with the ribosome, citrate cycle, glycolysis, thiamine biosynthesis, purine metabolism, fructose metabolism, mannose metabolism, and cold shock proteins. This study demonstrates that the two antibiotics induce rapid cessation of RNA synthesis resulting in inhibition of translation components. It also indicates that the production of virulence factors involved in intercellular dissemination, tissue invasion and inflammatory destruction may be enhanced through derepressing horizontal transfer genes by the drugs.

A searchable cross-platform gene expression database reveals connections between drug treatments and disease

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Williams Gareth

2012-01-01

Full Text Available Abstract Background Transcriptional data covering multiple platforms and species is collected and processed into a searchable platform independent expression database (SPIED. SPIED consists of over 100,000 expression fold profiles defined independently of control/treatment assignment and mapped to non-redundant gene lists. The database is thus searchable with query profiles defined over genes alone. The motivation behind SPIED is that transcriptional profiles can be quantitatively compared and ranked and thus serve as effective surrogates for comparing the underlying biological states across multiple experiments. Results Drug perturbation, cancer and neurodegenerative disease derived transcriptional profiles are shown to be effective descriptors of the underlying biology as they return related drugs and pathologies from SPIED. In the case of Alzheimer's disease there is high transcriptional overlap with other neurodegenerative conditions and rodent models of neurodegeneration and nerve injury. Combining the query signature with correlating profiles allows for the definition of a tight neurodegeneration signature that successfully highlights many neuroprotective drugs in the Broad connectivity map. Conclusions Quantitative querying of expression data from across the totality of deposited experiments is an effective way of discovering connections between different biological systems and in particular that between drug action and biological disease state. Examples in cancer and neurodegenerative conditions validate the utility of SPIED.

Immature MEF2C-dysregulated T-cell leukemia patients have an early T-cell precursor acute lymphoblastic leukemia gene signature and typically have non-rearranged T-cell receptors

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Zuurbier, Linda; Gutierrez, Alejandro; Mullighan, Charles G.; Canté-Barrett, Kirsten; Gevaert, A. Olivier; de Rooi, Johan; Li, Yunlei; Smits, Willem K.; Buijs-Gladdines, Jessica G.C.A.M.; Sonneveld, Edwin; Look, A. Thomas; Horstmann, Martin; Pieters, Rob; Meijerink, Jules P.P.

2014-01-01

Three distinct immature T-cell acute lymphoblastic leukemia entities have been described including cases that express an early T-cell precursor immunophenotype or expression profile, immature MEF2C-dysregulated T-cell acute lymphoblastic leukemia cluster cases based on gene expression analysis (immature cluster) and cases that retain non-rearranged TRG@ loci. Early T-cell precursor acute lymphoblastic leukemia cases exclusively overlap with immature cluster samples based on the expression of early T-cell precursor acute lymphoblastic leukemia signature genes, indicating that both are featuring a single disease entity. Patients lacking TRG@ rearrangements represent only 40% of immature cluster cases, but no further evidence was found to suggest that cases with absence of bi-allelic TRG@ deletions reflect a distinct and even more immature disease entity. Immature cluster/early T-cell precursor acute lymphoblastic leukemia cases are strongly enriched for genes expressed in hematopoietic stem cells as well as genes expressed in normal early thymocyte progenitor or double negative-2A T-cell subsets. Identification of early T-cell precursor acute lymphoblastic leukemia cases solely by defined immunophenotypic criteria strongly underestimates the number of cases that have a corresponding gene signature. However, early T-cell precursor acute lymphoblastic leukemia samples correlate best with a CD1 negative, CD4 and CD8 double negative immunophenotype with expression of CD34 and/or myeloid markers CD13 or CD33. Unlike various other studies, immature cluster/early T-cell precursor acute lymphoblastic leukemia patients treated on the COALL-97 protocol did not have an overall inferior outcome, and demonstrated equal sensitivity levels to most conventional therapeutic drugs compared to other pediatric T-cell acute lymphoblastic leukemia patients. PMID:23975177

Changes in gene expression associated with reproductive maturation in wild female baboons.

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Babbitt, Courtney C; Tung, Jenny; Wray, Gregory A; Alberts, Susan C

2012-01-01

Changes in gene expression during development play an important role in shaping morphological and behavioral differences, including between humans and nonhuman primates. Although many of the most striking developmental changes occur during early development, reproductive maturation represents another critical window in primate life history. However, this process is difficult to study at the molecular level in natural primate populations. Here, we took advantage of ovarian samples made available through an unusual episode of human-wildlife conflict to identify genes that are important in this process. Specifically, we used RNA sequencing (RNA-Seq) to compare genome-wide gene expression patterns in the ovarian tissue of juvenile and adult female baboons from Amboseli National Park, Kenya. We combined this information with prior evidence of selection occurring on two primate lineages (human and chimpanzee). We found that in cases in which genes were both differentially expressed over the course of ovarian maturation and also linked to lineage-specific selection this selective signature was much more likely to occur in regulatory regions than in coding regions. These results suggest that adaptive change in the development of the primate ovary may be largely driven at the mechanistic level by selection on gene regulation, potentially in relationship to the physiology or timing of female reproductive maturation.

Exosomes from asbestos-exposed cells modulate gene expression in mesothelial cells.

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Munson, Phillip; Lam, Ying-Wai; Dragon, Julie; MacPherson, Maximilian; Shukla, Arti

2018-03-19

Asbestos exposure is a determinate cause of many diseases, such as mesothelioma, fibrosis, and lung cancer, and poses a major human health hazard. At this time, there are no identified biomarkers to demarcate asbestos exposure before the presentation of disease and symptoms, and there is only limited understanding of the underlying biology that governs asbestos-induced disease. In our study, we used exosomes, 30-140 nm extracellular vesicles, to gain insight into these knowledge gaps. As inhaled asbestos is first encountered by lung epithelial cells and macrophages, we hypothesize that asbestos-exposed cells secrete exosomes with signature proteomic cargo that can alter the gene expression of mesothelial cells, contributing to disease outcomes like mesothelioma. In the present study using lung epithelial cells (BEAS2B) and macrophages (THP-1), we first show that asbestos exposure causes changes in abundance of some proteins in the exosomes secreted from these cells. Furthermore, exposure of human mesothelial cells (HPM3) to these exosomes resulted in gene expression changes related to epithelial-to-mesenchymal transition and other cancer-related genes. This is the first report to indicate that asbestos-exposed cells secrete exosomes with differentially abundant proteins and that those exosomes have a gene-altering effect on mesothelial cells.-Munson, P., Lam, Y.-W., Dragon, J. MacPherson, M., Shukla, A. Exosomes from asbestos-exposed cells modulate gene expression in mesothelial cells.

An extended data mining method for identifying differentially expressed assay-specific signatures in functional genomic studies

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Rollins Derrick K

2010-12-01

Full Text Available Abstract Background Microarray data sets provide relative expression levels for thousands of genes for a small number, in comparison, of different experimental conditions called assays. Data mining techniques are used to extract specific information of genes as they relate to the assays. The multivariate statistical technique of principal component analysis (PCA has proven useful in providing effective data mining methods. This article extends the PCA approach of Rollins et al. to the development of ranking genes of microarray data sets that express most differently between two biologically different grouping of assays. This method is evaluated on real and simulated data and compared to a current approach on the basis of false discovery rate (FDR and statistical power (SP which is the ability to correctly identify important genes. Results This work developed and evaluated two new test statistics based on PCA and compared them to a popular method that is not PCA based. Both test statistics were found to be effective as evaluated in three case studies: (i exposing E. coli cells to two different ethanol levels; (ii application of myostatin to two groups of mice; and (iii a simulated data study derived from the properties of (ii. The proposed method (PM effectively identified critical genes in these studies based on comparison with the current method (CM. The simulation study supports higher identification accuracy for PM over CM for both proposed test statistics when the gene variance is constant and for one of the test statistics when the gene variance is non-constant. Conclusions PM compares quite favorably to CM in terms of lower FDR and much higher SP. Thus, PM can be quite effective in producing accurate signatures from large microarray data sets for differential expression between assays groups identified in a preliminary step of the PCA procedure and is, therefore, recommended for use in these applications.

High-throughput gene expression profiling of memory differentiation in primary human T cells

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Russell Kate

2008-08-01

Full Text Available Abstract Background The differentiation of naive T and B cells into memory lymphocytes is essential for immunity to pathogens. Therapeutic manipulation of this cellular differentiation program could improve vaccine efficacy and the in vitro expansion of memory cells. However, chemical screens to identify compounds that induce memory differentiation have been limited by 1 the lack of reporter-gene or functional assays that can distinguish naive and memory-phenotype T cells at high throughput and 2 a suitable cell-line representative of naive T cells. Results Here, we describe a method for gene-expression based screening that allows primary naive and memory-phenotype lymphocytes to be discriminated based on complex genes signatures corresponding to these differentiation states. We used ligation-mediated amplification and a fluorescent, bead-based detection system to quantify simultaneously 55 transcripts representing naive and memory-phenotype signatures in purified populations of human T cells. The use of a multi-gene panel allowed better resolution than any constituent single gene. The method was precise, correlated well with Affymetrix microarray data, and could be easily scaled up for high-throughput. Conclusion This method provides a generic solution for high-throughput differentiation screens in primary human T cells where no single-gene or functional assay is available. This screening platform will allow the identification of small molecules, genes or soluble factors that direct memory differentiation in naive human lymphocytes.

Integrated Analyses of Gene Expression Profiles Digs out Common Markers for Rheumatic Diseases

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Wang, Lan; Wu, Long-Fei; Lu, Xin; Mo, Xing-Bo; Tang, Zai-Xiang; Lei, Shu-Feng; Deng, Fei-Yan

2015-01-01

Objective Rheumatic diseases have some common symptoms. Extensive gene expression studies, accumulated thus far, have successfully identified signature molecules for each rheumatic disease, individually. However, whether there exist shared factors across rheumatic diseases has yet to be tested. Methods We collected and utilized 6 public microarray datasets covering 4 types of representative rheumatic diseases including rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis, and osteoarthritis. Then we detected overlaps of differentially expressed genes across datasets and performed a meta-analysis aiming at identifying common differentially expressed genes that discriminate between pathological cases and normal controls. To further gain insights into the functions of the identified common differentially expressed genes, we conducted gene ontology enrichment analysis and protein-protein interaction analysis. Results We identified a total of eight differentially expressed genes (TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, PRF1), each associated with at least 3 of the 4 studied rheumatic diseases. Meta-analysis warranted the significance of the eight genes and highlighted the general significance of four genes (CX3CR1, LY96, TLR5, and PRF1). Protein-protein interaction and gene ontology enrichment analyses indicated that the eight genes interact with each other to exert functions related to immune response and immune regulation. Conclusion The findings support that there exist common factors underlying rheumatic diseases. For rheumatoid arthritis, systemic lupus erythematosus, ankylosing spondylitis and osteoarthritis diseases, those common factors include TNFSF10, CX3CR1, LY96, TLR5, TXN, TIA1, PRKCH, and PRF1. In-depth studies on these common factors may provide keys to understanding the pathogenesis and developing intervention strategies for rheumatic diseases. PMID:26352601

Differential Effect of Active Smoking on Gene Expression in Male and Female Smokers

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Paul, Sunirmal; Amundson, Sally A

2015-01-01

Smoking is the second leading cause of preventable death in the United States. Cohort epidemiological studies have demonstrated that women are more vulnerable to cigarette-smoking induced diseases than their male counterparts, however, the molecular basis of these differences has remained unknown. In this study, we explored if there were differences in the gene expression patterns between male and female smokers, and how these patterns might reflect different sex-specific responses to the stress of smoking. Using whole genome microarray gene expression profiling, we found that a substantial number of oxidant related genes were expressed in both male and female smokers, however, smoking-responsive genes did indeed differ greatly between male and female smokers. Gene set enrichment analysis (GSEA) against reference oncogenic signature gene sets identified a large number of oncogenic pathway gene-sets that were significantly altered in female smokers compared to male smokers. In addition, functional annotation with Ingenuity Pathway Analysis (IPA) identified smoking-correlated genes associated with biological functions in male and female smokers that are directly relevant to well-known smoking related pathologies. However, these relevant biological functions were strikingly overrepresented in female smokers compared to male smokers. IPA network analysis with the functional categories of immune and inflammatory response gene products suggested potential interactions between smoking response and female hormones. Our results demonstrate a striking dichotomy between male and female gene expression responses to smoking. This is the first genome-wide expression study to compare the sex-specific impacts of smoking at a molecular level and suggests a novel potential connection between sex hormone signaling and smoking-induced diseases in female smokers. PMID:25621181