# Integrative Meta-Analysis Identifies Epithelial–Mesenchymal Transition Gene Signatures as Key Determinants of Ovarian Cancer Progression and Treatment Outcome

## TL;DR

This study finds that genes involved in epithelial-mesenchymal transition (EMT) are linked to ovarian cancer progression and treatment response, suggesting potential biomarkers for personalized therapy.

## Contribution

The study identifies a novel four-gene EMT signature associated with drug sensitivity in ovarian cancer.

## Key findings

- Recurrent genomic and transcriptomic alterations were found in EMT-associated genes in ovarian cancer.
- A four-EMT gene signature (EFNA1, OVOL2, GATA3, DSG2) correlates with differential sensitivity to VEGFR and EGFR inhibitors.
- EMT-driven molecular changes contribute to ovarian cancer progression and chemoresistance.

## 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 EGFR inhibitors in OC cell lines. Overall, these results suggest that EMT-driven molecular changes contribute to the onset and progression of OC and highlight a subset of EMT genes as promising predictive biomarkers for targeted therapy responses.