Dataset Information

Screening of potential biomarkers for chemoresistant ovarian carcinoma with miRNA expression profiling data by bioinformatics approach.

ABSTRACT: The aim of the present study was to screen out the biomarkers associated with chemoresistance in ovarian carcinomas and to investigate the molecular mechanisms. microRNA (miRNA) expression data was obtained from published microarray data of the GSE43867 dataset from Gene Expression Omnibus (GEO), including the data of 86 chemotherapy-treated patients with serous epithelial ovarian carcinomas (response group, 36 complete response cases and 12 partial response cases; non-response group, 10 stable cases and 28 progressive disease cases), and identification of differentially-expressed miRNAs were conducted with a GEO2R online tool based on R language. TargetScan 6.2 was used to predict the targets of differentially-expressed miRNAs. Protein-protein interaction network analysis was conducted by STRING 9.1, while functional enrichment [Gene Ontology (GO) biological process terms] and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted by GeneCodis3 for the target genes. A total of 6 differentially-expressed miRNAs were screened out, with 317 target genes obtained. It was found that 67 interactions existed among 76 genes/proteins through the PPI network analysis, and that 6 of these were potential key genes (PIK3R5, MAPK3, PTEN, S1PR3, BDKRB2 and NCBP2). The main biological processes involved in chemoresistant ovarian carcinoma were apoptosis, programmed cell death, cell migration, cell death and cell motility. The miRNA target genes were found to be associated with the ErbB signaling pathway, the gonadotropin-releasing hormone signaling pathway and other pathways in cancer. IK3R5, MAPK3 and PIK3R5 are involved in the majority of GO terms and KEGG pathways associated with chemoresistance in ovarian carcinoma.

SUBMITTER: Wei S

PROVIDER: S-EPMC4580032 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Screening of potential biomarkers for chemoresistant ovarian carcinoma with miRNA expression profiling data by bioinformatics approach.

Wei Shiyang S Wang Yafeng Y Xu Hong H Kuang Yan Y

Oncology letters 20150814 4

The aim of the present study was to screen out the biomarkers associated with chemoresistance in ovarian carcinomas and to investigate the molecular mechanisms. microRNA (miRNA) expression data was obtained from published microarray data of the GSE43867 dataset from Gene Expression Omnibus (GEO), including the data of 86 chemotherapy-treated patients with serous epithelial ovarian carcinomas (response group, 36 complete response cases and 12 partial response cases; non-response group, 10 stable ...[more]

PMID: 26622864

Similar Datasets

Project description:IntroductionOvarian clear cell carcinoma (OCCC) has distinct clinical and molecular features and heterogeneous prognosis. Insights into the somatic genomic abnormalities of OCCC provide the basis for deeper understanding and potential therapeutic avenues. Herein, we performed extensive genomic profiling in Chinese patients to illustrate the mutation landscape and genetic prognostic biomarkers of OCCC.Patients and methodsWe used targeted DNA sequencing on 61 OCCC cases with a panel of 520 cancer-related genes. Correlations between clinicopathological features and survival were evaluated. Nomogram-based models were constructed to predict progress-free survival (PFS).ResultsWe detected 763 somatic mutations spanning 286 genes. The most frequent genetic alterations, ARID1A (49%) and PIK3CA (48%), were concurrently mutated. Comprehensive copy number alterations (CNAs) were identified in chromosomes 20q13.2 and 8q. Most (73.7%) patients harboured potentially targetable driver mutations. The mean and median tumour mutational burden were 7.0 and 3.0 mutations/Mb, respectively. Microsatellite instability (high) was identified in 8.2% of patients. Mutation of the base-excision repair pathway was significantly higher in patients of stage II/III/IV. ATM mutation was associated with platinum sensitivity (p < .05). Survival analysis identified chr8q CNAs in all patients, PIK3CA mutations in stage I patients and SWI/SNF complex (ARID1A and SMARCA4) mutations in stage II/III/IV patients as potential prognosticators (p < .05). Integration of genetic alterations (SWI/SNF complex mutations, ATM mutations and chr8q CNAs) improved the performance of a nomogram based on tumour stage and residual disease (concordance index 0.75 vs. 0.70, p < .05).ConclusionsWe described somatic genomic alterations in Chinese OCCC patients and observed different genomic alterations between stage I and stage II/III/IV tumours. Genetic factors may supplement clinical factors in nomogram modelling for PFS prediction.Key MessagesWe performed extensive genomic profiling in a well-annotated cohort of 61 Chinese ovarian clear cell carcinoma (OCCC) patients.PIK3CA mutations were associated with worse overall survival (OS) in stage I OCCC, and SWI/SNF gene mutations were associated with improved OS in stage II/III/IV disease.We propose an easy-to-use nomogram using clinical factors (tumour stage and residual disease) and genetic alterations (SWI/SNF complex mutations, ATM mutations and chr8q CNAs) to predict the progress-free survival (PFS) of OCCC.

Project description:Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality, which makes the prognostic prediction challenging. Angiogenesis appears to be of critical importance in the progression and metastasis of HCC. Some of the angiogenesis-related genes promote this process, while other anti-angiogenesis genes suppress tumor growth and metastasis. Therefore, the comprehensive prognostic value of multiple angiogenesis-related genes in HCC needs to be further clarified. In this study, the mRNA expression profile of HCC patients and the corresponding clinical data were acquired from multiple public databases. Univariate Cox regression analysis was utilized to screen out differentially expressed angiogenesis-related genes with prognostic value. A multigene signature was established with the least absolute shrinkage and selection operator Cox regression in the Cancer Genome Atlas cohort, and validated through an independent cohort. The results suggested that a total of 16 differentially expressed genes (DEGs) were associated with overall survival (OS) and a 7-gene signature was constructed. The risk score of each patient was calculated using this signature, the median value of which was used to divide these patients into a high-risk group and a low-risk group. Compared with the low-risk group, the patients in the high-risk group had a poor prognosis. The risk score was an independent predictor for OS through multivariate Cox regression analysis. Then, unsupervised learning was used to verify the validity of this 7-gene signature. A nomogram by further integrating clinical information and the prognostic signature was utilized to predict prognostic risk and individual OS. Functional enrichment analyses demonstrated that these DEGs were enriched in the pathways of cell proliferation and mitosis, and the immune cell infiltration was significantly different between the two risk groups. In summary, a novel angiogenesis-related genes signature could be used to predict the prognosis of HCC and for targeted therapy.

Dataset Information

Screening of potential biomarkers for chemoresistant ovarian carcinoma with miRNA expression profiling data by bioinformatics approach.

Publications

Screening of potential biomarkers for chemoresistant ovarian carcinoma with miRNA expression profiling data by bioinformatics approach.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets