Transcription Factor-MicroRNA-Target Gene Networks Associated with Ovarian Cancer Survival and Recurrence

Abstract

The identification of reliable transcriptome biomarkers requires the simultaneous consideration of regulatory and target elements including microRNAs (miRNAs), transcription factors (TFs), and target genes. A novel approach that integrates multivariate survival analysis, feature selection, and regulatory network visualization was used to identify reliable biomarkers of ovarian cancer survival and recurrence. Expression profiles of 799 miRNAs, 17,814 TFs and target genes and cohort clinical records on 272 patients diagnosed with ovarian cancer were simultaneously considered and results were validated on an independent group of 146 patients. Three miRNAs (hsa-miR-16, hsa-miR-22*, and ebv-miR-BHRF1-2*) were associated with both ovarian cancer survival and recurrence and 27 miRNAs were associated with either one hazard. Two miRNAs (hsa-miR-521 and hsa-miR-497) were cohort-dependent, while 28 were cohort-independent. This study confirmed 19 miRNAs previously associated with ovarian cancer and identified two miRNAs that have previously been associated with other cancer types. In total, the expression of 838 and 734 target genes and 12 and eight TFs were associated (FDR-adjusted P-value <0.05) with ovarian cancer survival and recurrence, respectively. Functional analysis highlighted the association between cellular and nucleotide metabolic processes and ovarian cancer. The more direct connections and higher centrality of the miRNAs, TFs and target genes in the survival network studied suggest that network-based approaches to prognosticate or predict ovarian cancer survival may be more effective than those for ovarian cancer recurrence. This study demonstrated the feasibility to infer reliable miRNA-TF-target gene networks associated with survival and recurrence of ovarian cancer based on the simultaneous analysis of co-expression profiles and consideration of the clinical characteristics of the patients.

miR-335 Represents an Independent Prognostic Marker in Epithelial Ovarian Cancer

“…In fact, a recent study on breast cancer shows that miR-335 locus deletion is a frequent occurrence in ovarian cancer, and patients with miR-335 locus deletion have much worse survival. 23 However, in the recent profiling studies by Vecchione et al 24 and Delfino and Rodriguez-Zas, 25 miR-335 was not among the most significantly altered miRNAs in ovarian cancer, which may be due to differences in race and ethnicity and clinicopathologic features of enrolled patients. These two profiling studies were conducted in white patients, including those undergoing preadjuvant therapy, whereas our patients were Asian and had not received any chemotherapy or biotherapy before surgery.…”

A Regulatory miRNA–mRNA Network Is Associated with Tissue Repair Induced by Mesenchymal Stromal Cells in Acute Kidney Injury

“…Then, we searched for overlaps in the miRNA sets using GeneVenn, a web application for comparing set lists using Venn diagrams (19). The known and predicted relationships between miRNAs and target genes were obtained from the DIANA Tools and MIR@NT@N resource, according to the criteria in the default parameters (18–21). We only selected those genes targeted by at least two miRNAs to restrict our analysis to the most relevant pairs of connected miRNAs and mRNAs.…”

Analytical workflow profiling gene expression in murine macrophages

“…27 To avoid errors related to multiple tests, categories were only considered enriched if they were significant at FDR-adjusted EASE score based p -value < 0.1. 29 Cluster ES were re-calculated to reflect the remaining member categories (ES > 4). The GSEA methodology was implemented using the software package GSEA-P and enrichment was tested against the functional categories present in the Molecular Signature Database (MSigDB).…”