Abstract
BackgroundHigh-grade serous ovarian cancer (HGSC), the most common ovarian carcinoma type, is associated with the highest mortality rate among all gynecological malignancies. As chemoresistance has been demonstrated as the major challenge in improving the prognosis of HGSC patients, we here aimed to identify microRNA (miRNA) biomarkers for predicting platinum resistance and further explore their functions in HGSC.ResultsWe developed and applied our network vulnerability-based and knowledge-guided bioinformatics model first time for the study of drug-resistance in cancer. Four miRNA biomarkers (miR-454-3p, miR-98-5p, miR-183-5p and miR-22-3p) were identified with potential in stratifying platinum-sensitive and platinum-resistant HGSC patients and predicting prognostic outcome. Among them, miR-454-3p and miR-183-5p were newly discovered to be closely implicated in platinum resistance in HGSC. Functional analyses highlighted crucial roles of the four miRNA biomarkers in platinum resistance through mediating transcriptional regulation, cell proliferation and apoptosis. Moreover, expression patterns of the miRNA biomarkers were validated in both platinum-sensitive and platinum-resistant ovarian cancer cells.ConclusionsWith bioinformatics modeling and analysis, we identified and confirmed four novel putative miRNA biomarkers, miR-454-3p, miR-98-5p, miR-183-5p and miR-22-3p that could serve as indicators of resistance to platinum-based chemotherapy, thereby contributing to the improvement of chemotherapeutic efficiency and optimization of personalized treatments in HGSC.
Highlights
High-grade serous ovarian cancer (HGSC), the most common ovarian carcinoma type, is associated with the highest mortality rate among all gynecological malignancies
Data collection To explore miRNA biomarkers associated with platinum-resistance in ovarian cancer, the mRNA and miRNA expression data and clinical data of 31 platinum-sensitive and 37 platinum-resistant HGSC patients were downloaded from the publicly available International Cancer Genome Consortium (ICGC) based on search term ‘OV-AU’, which has been published by Patch et al [17] in Nature (2015)
The miRNA raw data were deposited in the Gene Expression Omnibus (GEO) datasets with the accession number GSE65821, and the transcriptome sequencing raw data were deposited in the European Genome-phenome Archive (EGA) repository under the accession code EGAD00001000877
Summary
High-grade serous ovarian cancer (HGSC), the most common ovarian carcinoma type, is associated with the highest mortality rate among all gynecological malignancies. MicroRNAs (miRNAs) are approximately 22-nt noncoding RNAs that post-transcriptionally modulate gene expression in a sequence-specific manner via mRNA degradation or translational repression [6]. These molecules are extensively involved in regulation of cellular processes, including proliferation, differentiation, and apoptosis. Accumulating evidence has demonstrated that multiple miRNAs are aberrantly expressed in various cancer types and contribute to the initiation and progression of cancer as oncogenes or tumor suppressors [8]. These miRNAs can be effectively used as predictive biomarkers or therapeutic targets to optimize cancer diagnosis and treatment regimens [9, 10]
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