The impact of biological features for a better prediction of posttransplant hepatocellular cancer recurrence

Curr Opin Organ Transplant. 2022 Aug 1;27(4):305-311. doi: 10.1097/MOT.0000000000000955. Epub 2022 Jan 19.

Abstract

Purpose of review: Morphological criteria (i.e., Milan Criteria) have been considered for a long time to be the best tool for selecting patients with hepatocellular cancer (HCC) waiting for liver transplantation (LT). In the last ten years, a refinement of the selection criteria has been observed, with the introduction of biological tumor characteristics enabling to enlarge the number of potential transplant candidates and to select LT candidates with a lower risk of posttransplant recurrence.

Recent findings: Several biological tumor aspects have been explored and validated in international cohorts to expand the ability to predict patients at high risk for recurrence. Alpha-fetoprotein, radiological response to locoregional treatments, and other more recently proposed markers have been principally explored. Moreover, more complex statistical approaches (i.e., deep learning) have been advocated to explore the nonlinear intercorrelations between the investigated features.

Summary: The addition of biological aspects to morphology has improved the ability to discriminate among high- and low-risk patients for recurrence. New prognostic algorithms based on the more sophisticated artificial intelligence approach are further improving the capability to select LT candidates with HCC.

Publication types

  • Review

MeSH terms

  • Artificial Intelligence
  • Carcinoma, Hepatocellular* / pathology
  • Carcinoma, Hepatocellular* / surgery
  • Humans
  • Liver Neoplasms* / pathology
  • Liver Neoplasms* / surgery
  • Liver Transplantation* / adverse effects
  • Neoplasm Recurrence, Local
  • Patient Selection
  • Retrospective Studies
  • alpha-Fetoproteins

Substances

  • alpha-Fetoproteins