一种可预测乙型肝炎病毒相关性肝细胞癌早期复发的原位分子信号

State Key Laboratory of Oncology in South China, Cancer Center, Sun Yat-sen (Zhongshan) University, Guangzhou 510 060, China

Background & Aims: To develop an in situ molecular signature to predict postsurgical recurrence in hepatocellular carcinoma (HCC) patients. Methods: Immunohistochemistry was performed using tissue microarrays containing both tumoral and peri-tumoral regions of the advancing tumor edge from 336 HCC patients (289 were positive for hepatitis B virus) who underwent curative resection. Forty-nine variables were analyzed in the training set (n = 151) using support vector machine and stepwise algorithms to develop a classifier to predict recurrence within 1 year, which was mainly caused by invasion or metastasis from the primary tumors. The classifier was further validated in an independent cohort of 185 patients (71 internal and 114 external). Results: The final signature was composed of eight IHC features: CD80 T, B7-DC T, HLA-DR P, FasL P, Bcl-2 T, Ki-67 T, cyclin D1 T, and CK19 T. In the independent test set, this classifier reliably predicted recurrence within 1 year (sensitivity, 69.1%; specificity, 65.0%) with an odds ratio of 4.149 (95% CI, 2.189-7.864). Based on a multivariate logistic model, the in situ molecular signature provided significant predictive power independent of tumor number, tumor size, vascular invasion and BCLC classification (p = 0.001). The highest potential clinical impact of the classifier was observed in early-stage (BCLC classification 0-A) patients (p <0.0001), and the classifier was also predictive of the time-to-recurrence and overall survival (both p <0.0001). Conclusions: This in situ molecular classifier could provide a novel approach to identify patients who are at greatest risk for postsurgical recurrence of HCC and may benefit from intensive clinical follow-up or chemopreventive strategies. © 2012 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Zheng, L.; State Key Laboratory of Oncology in South China, Cancer Center, Sun Yat-sen (Zhongshan) University, Guangzhou 510 060, China; email: zhenglm@mail.sysu.edu.cn