High-grade serous ovarian cancer (HGSOC) is the most frequent subtype of ovarian cancer and is associated with high mortality rates. The surgical outcome is one of the most important prognostic variables. There are no valid biomarkers to identify which patients may benefit from a primary debulking technique. Researchers intended to find and evaluate a predictor panel for the surgical outcome of a residual tumor mass after first-line debulking surgery. Firstly, “in silico” examination of publicly available datasets found 200 genes as predictors for surgical outcomes. The top selected genes were then validated using the innovative Nanostring approach, which was employed for this research purpose for the first time. Around 225 primary ovarian cancer patients with fully annotated clinical data and a complete debulking rate of 60% were obtained for a clinical cohort. The 14 best-rated genes were subsequently validated through the cohort, employing immunohistochemical testing. Lastly, the researchers used this biomarker expression data to predict the presence of military carcinomatosis patterns. The nanostring analysis detected 37 genes differentially expressed between optimal and suboptimal debulked patients (P<0.05). The immunohistochemistry verified the top 14 genes, reaching an AUC Ø0.650. The analysis for the prediction of military carcinomatosis patterns produced an AUC of Ø0.797. The researchers’ investigation showed that tissue-based indicators were not able to accurately foretell the presence of a postoperative residual tumor. The surgical outcome of primary debulking for high-grade serous ovarian cancer patients is still largely determined by factors such as the expertise of the treating surgeon, the patient’s overall health, and the experience of the treating center.
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