Homo sapiens
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PROVIDER: PRJNA322831 | ENA |
REPOSITORIES: ENA
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Project description:Two microRNA Signatures for Malignancy and Immune Infiltration Predict Overall Survival in Advanced Epithelial Ovarian Cancer
| PRJNA322527 | ENA
Project description:The presence of tumor cells in effusions within serosal cavities is a clinical manifestation of advanced-stage cancer and is generally associated with poor survival. Identifying molecular targets may help to design efficient treatments to eradicate these aggressive cancer cells and improve patient survival. Using a state-of-the-art Taqman-based qRT-PCR assay, we investigated the multidrug resistance (MDR) transcriptome of 32 unpaired ovarian serous carcinoma effusion samples obtained at diagnosis or at disease recurrence following chemotherapy. MDR genes were selected a priori based on an extensive curation of the literature published during the last three decades. We found three gene signatures with a statistically significant correlation with overall survival (OS), response to treatment (complete response - CR vs. other), and progression free survival (PFS). The median log-rank p-values for the signatures were 0.023, 0.034, and 0.008, respectively. No correlation was found with residual tumor status after cytoreductive surgery, treatment (with or without chemotherapy) and stage defined according to the International Federation of Gynecology and Obstetrics. Further analyses demonstrated that gene expression alone can effectively predict the survival outcome of women with ovarian serous carcinoma (OS: log-rank p=0.0000 and PFS: log-rank p=0.002). Interestingly, the signature for overall survival is the same in patients at first presentation and those who had chemotherapy and relapsed. This pilot study highlights two new gene signatures that may help in optimizing the treatment for ovarian carcinoma patients with effusions. In the study presented here, effusion samples were obtained from 32 patients diagnosed with serous ovarian carcinoma (n=25), primary peritoneal serous carcinoma (n=6) or tubal serous carcinoma (n=1). They were accrued at the Division of Pathology in the Norwegian Radium Hospital from 2000-2006. RNA was used to study the expression profile of 381 multidrug resistant-related genes.
2011-11-17 | E-GEOD-29702 | biostudies-arrayexpress
Project description:MicroRNAs have been established as key regulators of tumor gene expression and as prime biomarker candidates for clinical phenotypes in epithelial ovarian cancer (EOC). We analyzed the coexpression and regulatory structure of microRNAs and their colocalized gene targets in primary tumor tissue of 20 advanced epithelial ovarian cancer patients in order to construct a regulatory signature for clinical prognosis. We performed an integrative analysis to identify two prognostic microRNA/mRNA coexpression modules, each enriched for consistent biological functions. One module, enriched for malignancy related functions, was found to be upregulated in malignant versus benign samples. The second module, enriched for immune related functions, was strongly correlated with intratumoral immune infiltrates of T cells, NK cells, Cytotoxic Lymphocytes, and Macrophages. We validated the prognostic relevance of the immunological module microRNAs in the publically available TCGA dataset. These findings provide novel functional roles for microRNAs in the progression of advanced EOC and possible prognostic signatures for survival.
2017-04-01 | GSE81778 | GEO
Project description:MicroRNAs have been established as key regulators of tumor gene expression and as prime biomarker candidates for clinical phenotypes in epithelial ovarian cancer (EOC). We analyzed the coexpression and regulatory structure of microRNAs and their colocalized gene targets in primary tumor tissue of 20 advanced epithelial ovarian cancer patients in order to construct a regulatory signature for clinical prognosis. We performed an integrative analysis to identify two prognostic microRNA/mRNA coexpression modules, each enriched for consistent biological functions. One module, enriched for malignancy related functions, was found to be upregulated in malignant versus benign samples. The second module, enriched for immune related functions, was strongly correlated with intratumoral immune infiltrates of T cells, NK cells, Cytotoxic Lymphocytes, and Macrophages. We validated the prognostic relevance of the immunological module microRNAs in the publically available TCGA dataset. These findings provide novel functional roles for microRNAs in the progression of advanced EOC and possible prognostic signatures for survival.
2017-04-01 | GSE81873 | GEO
Project description:The presence of tumor cells in effusions within serosal cavities is a clinical manifestation of advanced-stage cancer and is generally associated with poor survival. Identifying molecular targets may help to design efficient treatments to eradicate these aggressive cancer cells and improve patient survival. Using a state-of-the-art Taqman-based qRT-PCR assay, we investigated the multidrug resistance (MDR) transcriptome of 32 unpaired ovarian serous carcinoma effusion samples obtained at diagnosis or at disease recurrence following chemotherapy. MDR genes were selected a priori based on an extensive curation of the literature published during the last three decades. We found three gene signatures with a statistically significant correlation with overall survival (OS), response to treatment (complete response - CR vs. other), and progression free survival (PFS). The median log-rank p-values for the signatures were 0.023, 0.034, and 0.008, respectively. No correlation was found with residual tumor status after cytoreductive surgery, treatment (with or without chemotherapy) and stage defined according to the International Federation of Gynecology and Obstetrics. Further analyses demonstrated that gene expression alone can effectively predict the survival outcome of women with ovarian serous carcinoma (OS: log-rank p=0.0000 and PFS: log-rank p=0.002). Interestingly, the signature for overall survival is the same in patients at first presentation and those who had chemotherapy and relapsed. This pilot study highlights two new gene signatures that may help in optimizing the treatment for ovarian carcinoma patients with effusions.
2011-11-17 | GSE29702 | GEO
Project description:To demonstrate the use of a whole-genome oligonucleotide array to perform expression profiling on a series of microdissected late-stage, high-grade papillary serous ovarian adenocarcinomas to establish a prognostic gene signature correlating with survival and to identify novel survival factors in ovarian cancer. Advanced stage papillary serous tumors of the ovary are responsible for the majority of ovarian cancer deaths, yet the molecular determinants modulating patient survival are poorly characterized. We identify and validate a prognostic gene expression signature correlating with survival in a series of microdissected serous ovarian tumors. Experiment Overall Design: We identified 53 advanced stage, high-grade primary tumor specimens and 10 normal ovarian surface epithelium (OSE) brushings.
2009-10-23 | E-GEOD-18520 | biostudies-arrayexpress
Project description:To date, a variety of studies have employed gene expression profiling to classify ovarian carcinomas in clinically relevant subtypes. These studies provided valuable first clues to molecular changes in ovarian cancer that might be exploited in new treatment strategies. However, most studies were of relatively limited size and the number of overlapping genes in the identified profiles was minimal. Although identification of gene expression profiles associated with clinically relevant subtypes in ovarian cancer is important, knowledge is now emerging rapidly on how genes interact in pathways, networks and complexes; this allows us to unravel those cellular pathways determining the biological behavior of ovarian cancer, that might be successfully targeted with drugs. The aim of our study was: 1) To develop a gene expression profile associated with overall survival in advanced stage serous ovarian cancer, 2) to assess the association of pathways and transcription factors with overall survival, and 3) to validate our identified profile and pathways/transcription factors in an independent set of ovarian cancers. According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ~35K 70-mer oligonucleotide microarrays. A continuous predictor of overall survival was built taking into account well-known issues in microarray analysis, such as multiple testing and overfitting. A functional class scoring analysis was utilized to assess pathways/transcription factors for their association with overall survival. The prognostic value of genes that constitute our overall survival profile was validated on a fully independent, publicly available data set of 118 well-defined primary serous ovarian cancers. Furthermore, functional class scoring analysis was also performed on this independent data set to assess the similarities with results from our own data set. An 86-gene overall survival profile discriminated between patients with unfavorable and favorable prognosis (median survival, 19 vs. 41 months, respectively; permutation p-value of log-rank statistic = 0.015) and maintained its independent prognostic value in multivariate analysis. Genes that comprised the overall survival profile were also able to discriminate between the two risk groups in the independent data set. In our dataset 17/167 pathways and 13/111 transcription factors were associated with overall survival of which 16 and 12 respectively were confirmed in the independent dataset. Our study provides new clues to genes, pathways and transcription factors which contribute to the clinical outcome of serous ovarian cancer and might be exploited in designing new treatment strategies. Keywords: Oncology/Gynecological Cancers, Genetics and Genomics/Cancer Genetics, Genetics and Genomics/Gene Expression, Genetics and Genomics/Genomics According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ~35K 70-mer oligonucleotide microarrays. Two randomly selected samples were hybridized together on the arrays for intensity-based instead of ratio-based analysis of the microarray data.
2008-12-10 | E-GEOD-13876 | biostudies-arrayexpress
Project description:Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I, II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.
2018-10-04 | GSE101108 | GEO
Project description:Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I, II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.
2018-10-04 | GSE101107 | GEO
Project description:The purpose of our study was to identify expression signatures and molecular markers associated with tumor recurrence and survival in patients with locally advanced head and neck squamous cell carcinoma (HNSCC). We studied the expression profile of 63 pre-treatment tumor biopsies obtained from locally advanced HNSCCs treated with standard treatments. Cluster analysis identified three tumor subtypes associated with significant differences in local recurrence-free survival (LRFS), progression free-survival (PFS) and overall survival (OS). Tumor subtype 1, associated with short LRFS, PFS and OS, showed features of epithelial-mesenchymal transition and undifferentiation. It also overexpressed genes involved in cell adhesion, NF-κB and integrin signalling. Tumor subtype 3, associated with longer LRFS, PFS and OS, showed a high degree of differentiation and overexpressed genes located in chromosomal regions 19q13 and 1q21. Tumor subtype 2, which had a clinical outcome intermediate between subtype 1 and subtype 3, overexpressed genes involved in branching morphogenesis. Receiver Operating Characteristic (ROC) analysis identified a subset of genes associated with local recurrence and survival. We validated the association between gene cluster classification and patient survival using two HNSCC data sets obtained from two independent patient cohorts. Finally, using the gene expression profile of the pre-treatment tumor biopsy, we generated a gene expression signature that could predict survival in locally advanced patients.
2011-05-31 | GSE23036 | GEO