Integrative Meta-Analysis Identifies Epithelial-Mesenchymal Transition Gene Signatures as Key Determinants of Ovarian Cancer Progression and Treatment Outcome
Abstract
Ovarian cancer (OC) remains one of the most lethal gynecologic malignancies, with nearly 80% of patients diagnosed at advanced stages due to the absence of early symptoms and the nonspecific nature of later clinical manifestations. This highlights the urgent need for robust molecular biomarkers that can refine patient stratification and guide personalized therapeutic approaches. A major determinant of OC aggressiveness is the epithelial-to-mesenchymal transition (EMT), a transcriptionally driven program that represses epithelial identity while promoting mesenchymal traits, thereby enhancing invasion, dissemination, recurrence, and resistance to therapy. EMT dysregulation is widespread in OC and fuels tumor heterogeneity, metastatic spread, and chemoresistance. To investigate the contribution of EMT-related genes in OC biology, we analyzed whole-genome sequencing and RNA-seq data from 419 patients in The Cancer Genome Atlas (TCGA) Pan-Cancer Atlas, assessing their genomic and transcriptomic alterations. We integrated these findings with transcriptomic and drug-sensitivity data from the CTRPv2 portal, performing Pearson correlation analyses to identify therapeutic vulnerabilities associated with EMT gene expression. Our analysis identifies recurrent genomic and transcriptomic alterations across several EMT-associated genes. Notably, we identified a four-EMT gene signature (EFNA1, OVOL2, GATA3, and DSG2) whose expression correlates with differential sensitivity to VEGFR and…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 419 participants or records.
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