Evaluating a data-driven approach to biomarker discovery for tumor-targeted imaging in epithelial ovarian cancer

Résumé fourni par la source

In epithelial ovarian cancer (EOC), surgical outcome is the strongest prognostic factor for survival. However, estimating intra-abdominal tumor burden to plan optimal treatment strategies remains challenging. Moreover, metastases can remain undetected during surgery via visual and tactile inspection. Tumor-targeted molecular imaging has the potential to improve tumor cell identification pre- and intraoperatively. While targeting folate receptor-alpha (FRα) shows promise, other specific biomarkers are needed. This study evaluates a novel, data-driven approach using RNA expression data to identify new target proteins for tumor-targeted imaging in EOC. A knowledge platform was utilized to search omics-databases for membrane proteins expressed in EOC but absent or minimally expressed in surrounding tumor-negative and inflammatory cells. Differential gene expression analysis identified highly expressed genes, which were validated through immunohistochemistry. Two new genes were identified: VTCN1 and AQP5, encoding for proteins B7-H4 and AQP5, respectively. Immunohistochemical validation showed that B7-H4 expression aligned with RNA levels, indicating its potential as a new target. In contrast, there was a discrepancy in AQP5 expression at the protein level compared to its gene counterpart. While this approach was valuable in identifying novel targets for tumor targeted imaging of EOC, immunohistochemistry or cell studies remain imperative for validation of RNA expression results.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.