Breast and ovarian cancers: toward a multi-cancer early detection test

Abstract

Introduction: Breast cancer (BC) and ovarian cancer (OC) are leading causes of cancer-related mortality among women worldwide. Despite their distinct clinical presentation these malignancies share genetic, hormonal, and micro-environmental characteristics, suggesting overlapping mechanisms of tumorigenesis and immune escape. Identifying common immune-related biomarkers could improve large scale early detection and guide the development of shared therapeutic strategies. Methods: We conducted a multiplex immunoassay profiling of 81 immune-related proteins including cytokines, chemokines, growth factors, and immune checkpoints in serum samples from 57 BC patients, 57 OC patients, and 49 healthy controls (HC). Results: Multivariate and univariate analyses were utilized to identify proteins exhibiting significant dysregulation. Receiver Operating Characteristic (ROC) curve analyses were conducted to evaluate the diagnostic performance of individual and combined protein panels. Protein-protein interaction networks were constructed using STRING and Cytoscape to elucidate shared functional modules. Multivariate analysis revealed a partial yet significant distinction between cancer patients and HC, with BC and OC exhibiting notable immunological similarities. Eighteen proteins were dysregulated in BC and OC as compared to HC, indicating shared oncogenic and immunological pathways. Furthermore, individual biomarkers exhibited moderate diagnostic performance, while combined panels achieved high accuracy. Network analysis revealed highly interconnected modules centered on the TNF/TNFR superfamily, co-stimulatory molecules, and chemokines, suggesting promising targets for combinatorial immunotherapy. Disscussion: our findings demonstrate a significant overlap in immune-related protein expression between BC and OC, supporting the feasibility of a common diagnostic biomarker panel for these female cancers. The identified proteins and their interaction networks offer valuable insights into the shared mechanisms of tumor progression and immune evasion, presenting promising avenues for early diagnosis and targeted therapy.