YAP-based nomogram predicts poor prognosis in patients with hepatocellular carcinoma after curative surgery

基于YAP评分的列线图预测肝细胞癌患者根治性手术后的预后不良

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Abstract

BACKGROUND: Hepatocellular carcinoma (HCC) ranks prominently in cancer-related mortality globally. Surgery remains the main therapeutic option for the treatment of HCC, but high post-operative recurrence rate makes prognostic prediction challenging. The quest for a reliable model to predict HCC recurrence continues to enhance prognosis. We aim to develop a nomogram with multiple factors to accurately estimate the risk of post-operative recurrence in patients with HCC. METHODS: A single-center retrospective study on 262 patients who underwent partial hepatectomy for HCC at the Eastern Hepatobiliary Surgery Hospital from May 2010 to April 2013 was conducted where immunohistochemistry assessed Yes-associated protein (YAP) expression in HCC. In the training cohort, a nomogram that incorporated YAP expression and clinicopathological features was constructed to predict 2-, 3-, and 5-year recurrence-free survival (RFS). The performance of the nomogram was assessed with respect to discrimination calibration, and clinical usefulness with external validation. RESULTS: A total of 262 patients who underwent partial hepatectomy for HCC at the Eastern Hepatobiliary Surgery Hospital were included in our study. HCC patients with high YAP expression exhibited significantly higher recurrence and reduced overall survival (OS) rates compared to those with low YAP expression (P<0.001). YAP was significantly associated with alpha-fetoprotein (AFP) (P=0.03), microvascular invasion (MVI) (P<0.001), and tumor differentiation grade (P<0.001). In the training cohort, factors like YAP expression, hepatitis B surface antigen (HBsAg), hepatitis B virus deoxyribonucleic acid (HBV-DNA), Child-Pugh stage, tumor size, MVI, and tumor differentiation were identified as key elements for the predictive model. Two YAP-centric Nomograms were developed, with one focused on predicting postoperative OS and the other on RFS. The calibration curve further confirmed the model's accuracy in the training cohort. The validation cohort confirmed the model's predictive accuracy. CONCLUSIONS: The proposed nomogram combining the YAP, a predictor of HCC progression, and clinical features achieved more-accurate prognostic prediction for patients with HCC after partial hepatectomy, which may help clinicians implement more appropriate interventions.

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