Details

Autor(en) / Beteiligte

• Xu, Jing
• Ding, Tong
• He, Qi
• Yu, Xing-Juan
• Wu, Wen-Chao
• Jia, Wei-Hua
• Yun, Jing-Ping
• Zhang, Ying
• Shi, Ming
• Shao, Chun-Kui
• Pan, Wei-Dong
• Yin, Xiao-Yu
• Min, Jun
• Zhuang, Shi-Mei
• Zheng, Limin

Titel

An in situ molecular signature to predict early recurrence in hepatitis B virus-related hepatocellular carcinoma

Ist Teil von

• Journal of hepatology, 2012-08, Vol.57 (2), p.313-321

Ort / Verlag

Kidlington: Elsevier B.V

Erscheinungsjahr

2012

Quelle

MEDLINE

Beschreibungen/Notizen

• 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: CD80T , B7-DCT , HLA-DRP , FasLP , Bcl-2T , Ki-67T , cyclin D1T , and CK19T . 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.