Bioinformatic Analysis Identified Potentially Prognostic Long Noncoding RNAs and MicroRNAs for Gastric Cancer

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Gastric cancer (GC) is a leading global malignancy.
• Identifying novel diagnostic and therapeutic targets is crucial for improving patient outcomes.

Purpose of the Study:

• To identify potential diagnostic and therapeutic long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) for gastric cancer (GC).
• To investigate the prognostic value of differentially expressed lncRNAs (DElncRNAs) and miRNAs (DEmiRNAs) in GC.

Main Methods:

• Utilized The Cancer Genome Atlas (TCGA) database for GC data (187 tumor tissues, 32 non-tumor tissues).
• Employed RStudio/Bioconductor for univariate analysis, LASSO Cox, and multivariate Cox regression.
• Performed Kaplan-Meier survival analysis and pathway enrichment analysis.

Main Results:

• Identified five lncRNAs (AC007785.3, AC079385.3, LINC00392, LINC01729, U95743.1) and two miRNAs (hsa-miR-3174, hsa-miR-605) as independent prognostic indicators for GC.
• AC007785.3, AC079385.3, LINC01729, miR-3174, and miR-605 significantly correlated with overall survival (OS).
• Target genes clustered in MAPK and cGMP-PKG signaling pathways; AC007785.3 associated with metastasis, miR-3174 with primary tumor status.

Conclusions:

• Five lncRNAs and two miRNAs were identified as independent prognostic markers for GC.
• These identified molecules, alongside clinical factors, are related to GC pathogenesis and prognosis.
• The findings provide potential entry points for developing novel prognostic markers for GC.