Unraveling Tumor Heterogeneity in Gynecological Cancer Using a Radiogenomics Approach

Ovarian cancer (OC) and endometrial cancer (EC) are highly heterogeneous gynecological malignancies with distinct molecular subtypes, therapeutic responses, and clinical outcomes. Traditional biopsy-based profiling often fails to capture the spatial and temporal complexity of these tumors. Radiogenomics, integrating imaging features with genomic and molecular data, has emerged as a promising approach to non-invasively analyze tumor heterogeneity. The purpose of this abstract is to critically examine and synthesize existing research on the application of radiogenomics in OC and EC, focusing on its ability to correlate imaging phenotypes with molecular biomarkers. This narrative review aims to demonstrate how radiogenomics can enhance tumor characterization, support biomarker prediction, and inform prognosis and therapeutic decision-making with non-invasive methods.This narrative review critically synthesizes current literature on radiogenomics applications in OC and EC. Studies using CT, MRI, and PET imaging were evaluated for their ability to correlate imaging phenotypes with molecular biomarkers, gene expression profiles, and clinical outcomes. The analysis emphasizes the role of radiogenomics in enhancing tumor characterization, predicting biomarker status, forecasting treatment response and prognosis.Radiogenomics has successfully identified associations between imaging features and key molecular alterations, such as BRCA mutations, homologous recombination deficiency (HRD), and immune-related biomarkers in OC, as well as POLE mutations, microsatellite instability (MSI), and tumor mutational burden (TMB) in EC. Predictive models incorporating radiomic features have demonstrated notable performance in estimating prognosis, treatment response, and recurrence risk across both cancer types.Radiogenomics has a strong potential to enhance personalized cancer care by analyzing tumor heterogeneity. However, clinical application requires methodological standardization, prospective validation, and integration into precision oncology workflows. · Radiogenomics enables non-invasive assessment of spatial and molecular heterogeneity in OC and EC.. · Integration of imaging and genomic data improves prediction of biomarkers, therapy response, and survival.. · Future clinical applications depend on methodological standardization, prospective validation, and integration into precision oncology workflows.. · Dolciami M, Celli V, Panico C et al. Unraveling Tumor Heterogeneity in Gynecological Cancer Using a Radiogenomics Approach Rofo 2025; DOI 10.1055/a-2698-8545.