A new study published in iMetaMed introduces a systems-level approach to classifying endometrial cancer that could transform treatment decisions for patients with this disease.
Using network perturbation analysis—a method that examines how gene regulatory networks are disrupted in tumors compared to normal tissue—researchers analyzed transcriptomic data from 783 endometrial cancer patients across four independent cohorts. This approach identified three molecularly distinct subtypes with markedly different clinical outcomes.
The most aggressive subtype, designated C1, showed the poorest prognosis and was characterized by loss of hormone receptor signaling, an immune-excluded tumor microenvironment, and elevated TP53 mutations. Critically, drug sensitivity analysis revealed that C1 tumors are specifically sensitive to microtubule-targeting agents (such as paclitaxel) and proteasome inhibitors (such as bortezomib), while showing resistance to DNA-damaging agents.
"This classification system provides a practical framework for personalized treatment strategies," the researchers noted. "Molecular profiling at diagnosis could rapidly identify patients requiring intensified treatment with effective agents whilst avoiding resistant therapies."
The findings suggest that stratifying patients based on network-level molecular disruptions, rather than individual gene expression alone, may offer more clinically actionable insights for treatment selection in endometrial cancer.
Data/statistical analysis
Network perturbation analysis identifies three molecular subtypes with distinct clinical outcomes and therapeutic vulnerabilities in endometrial cancer
15-Dec-2025
The Authors declare no conflicts of interest regarding this study. All authors have agreed to publish this manuscript.