Clinical and Morpho-Molecular Classifiers for Prediction of Hepatocellular Carcinoma Prognosis and Recurrence After Surgical Resection

Abstract

Background: Approximately 50% hepatocellular carcinoma (HCC) patients die within 5-year after surgical resection. The present staging systems do not fully allow to accurately predict the HCC prognosis and recurrence. This study aimed to identify clinicopathological characteristics and molecular markers to establish classifiers to predict the 5-year overall survival (OS) and the 3-year recurrence in HCC patients post-operatively. Methods: In this retrospective multicenter study, we enrolled 647 patients, underwent surgical resection for HCC and divided the patients into one training (406 patients from the Institution I) and two validation cohorts (136 and 105 patients from Institutions I and II). Clinicopathologic characteristics and tumor protein expression of 29 biomarkers on tumorigenesis, development and invasiveness by immunohistochemical (IHC) analysis were used to develop and validate a prognostic and a recurrent classifier after a five-year follow-up. The classifiers were developed using the maximum relevance minimum redundancy algorithm jointly with the multivariable regression method. The classifiers were further validated by an internal validation from the Institution I, and an independent validation from the Institution II. Findings: The prognostic classifier integrated three clinicopathologic characteristics of age, tumor number, tumor diameter; and seven immunomarkers, including BAX, CD34, CEA, E-cadherin, MMP-9, S100A9, and TYSY, while the recurrent classifier was composed of five clinicopathologic characteristics of age, tumor location, tumor number, tumor diameter, AFP levels; and six immunomarkers, CD34, E-Cadherin, HRas, PCNA, p53 and S100A9. The prognostic classifier distinguished HCC patients into high- and low-probability survival groups with significant differences in 5-year OS rate in all three cohorts (training cohort: 57.36% vs. 22.97%; P<0.0001; internal validation cohort: 61.90% vs. 28.85%; P<0.0001; independent validation cohort: 64.28% vs. 22.45%; P<0.0001). The recurrent classifier also demonstrated a good discrimination in all three cohorts. Interpretation: This study presented a prognostic classifier and a recurrent classifier using clinicopathologic and IHC characteristics. The developed classifiers stratified HCC patients into high- and low-probability survival or recurrent groups, which would further enhance individualized patient therapy. Funding Statement: This work was supported by the National S&T Major Project (No. 2017ZX10203205), National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917), National Key Research Plan by the Ministry of Science and Technology of China (Grant No. 2016YFC0104507), Natural Science Foundation of China (NSFC Grant No. 81871351), Zhejiang Medical and Health Science and Technology Project (No. 2018KY389). Declaration of Interests: The authors declare no conflicts of interest. Ethics Approval Statement: This retrospective multicenter study was approved by the research ethics committees at the First Affiliated Hospital, Zhejiang University School of Medicine (Institution I) and the Second Affiliated Hospital, Zhejiang University School of Medicine (Institution II).