Clinical and morpho-molecular classifiers for prediction of hepatocellular carcinoma prognosis and recurrence after surgical resection Journal Articles uri icon

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  • 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: We enrolled 647 HCC patients from two institutions, underwent surgical resection and divided the patients into one training and two validation cohorts. Clinicopathologic characteristics and tumor protein expression of 29 biomarkers by immunohistochemical (IHC) analysis were used to develop and validate a prognostic and a recurrent classifier, using the maximum relevance minimum redundancy algorithm jointly with the multivariable regression method. RESULTS: 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 good discrimination in all three cohorts. CONCLUSION: 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 can help clinicians judge whether adjuvant therapy is beneficial post-operatively.


  • Zhang, Xiuming
  • Bai, Yanfeng
  • Xu, Lei
  • Zhang, Buyi
  • Feng, Shi
  • Xu, Liming
  • Zhang, Han
  • Xu, Linjie
  • Yang, Pengfei
  • Niu, Tianye
  • Zheng, Shusen
  • Liu, Jimin (Nancy)

publication date

  • November 2019

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