LncMiM

LncMiM identifies lncRNA–miRNA–mRNA competing triplets and associated prognostic biomarkers in high-grade serous ovarian cancer using tumor expression data.

Key Features:

• Novel Methodology: Detects lncRNA–miRNA–mRNA competing triplets from tumor samples in the TCGA database using non-linear correlation analysis to address weak correlations between miRNA–target pairs and differences in expression levels.
• Comprehensive Analysis: Integrates lncRNA, miRNA, and mRNA expression relationships to consider the impact of lncRNAs and mRNAs on miRNA–target interactions.
• Extensive Network Mapping: Identified 847 lncRNA-associated competing triplets forming a regulatory network centered on miRNA–lncRNA pairs, with highly connected lncRNAs including ZFAS1, SNHG29, GAS5, AC112491.1, and AC099850.4.
• Biological Insights: Performs biological process and KEGG pathway enrichment analyses linking competing triplets to cell division, proliferation, cell cycle regulation, oocyte meiosis, oxidative phosphorylation, ribosome function, and the p53 signaling pathway.
• Prognostic Biomarker Identification: Performs survival analysis to nominate 107 potential prognostic biomarkers among competing triplets, including FGD5-AS1, HCP5, HMGN4, and TACC3.

Scientific Applications:

• Regulatory network mapping: Maps miRNA–lncRNA-centered regulatory networks in high-grade serous ovarian cancer and reports 847 competing triplets.
• Prognostic biomarker discovery: Identifies candidate prognostic biomarkers via survival analysis, nominating 107 candidates such as FGD5-AS1, HCP5, HMGN4, and TACC3.
• Pathway and mechanism inference: Associates competing triplets with biological processes and KEGG pathways (including oocyte meiosis, oxidative phosphorylation, ribosome, and the p53 signaling pathway) to inform mechanistic hypotheses.

Methodology:

Analysis uses tumor samples from the TCGA database, applies non-linear correlation analysis to detect lncRNA–miRNA–mRNA competing triplets, and employs biological process and KEGG pathway enrichment analysis and survival analysis.