Molecular profiling of liver tumors: classification and clinical translation for decision making

Semin Liver Dis. 2014 Nov;34(4):363-75. doi: 10.1055/s-0034-1394137. Epub 2014 Nov 4.

Abstract

Hepatocellular carcinoma (HCC) is a complex disease with a dismal prognosis. Consequently, a translational approach is required to personalized clinical decision making to improve survival of HCC patients. Molecular signatures from cirrhotic livers and single nucleotide polymorphism have been linked with HCC occurrence. Identification of high-risk populations will be useful to design chemopreventive trials. In addition, molecular signatures derived from tumor and nontumor samples are associated with early tumor recurrence due to metastasis and late tumor recurrence due to de novo carcinogenesis after curative treatment, respectively. Identification of patients with a high risk of relapse will guide adjuvant randomized trials. The genetic landscape drawn by next-generation sequencing has highlighted the genomic diversity of HCC. Genetic drivers recurrently mutated belong to different signaling pathways including telomere maintenance, cell-cycle regulators, chromatin remodeling, Wnt/b-catenin, RAS/RAF/MAPK kinase, and AKT/mTOR pathway. These cancer genes will be ideally targeted by biotherapies as a paradigm of stratified medicine adapted to tumor biology.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Animals
  • Biomarkers, Tumor / genetics*
  • Carcinoma, Hepatocellular / genetics*
  • Carcinoma, Hepatocellular / pathology
  • Carcinoma, Hepatocellular / therapy
  • Decision Support Techniques
  • Gene Expression Profiling*
  • Genetic Predisposition to Disease
  • Humans
  • Liver Neoplasms / genetics*
  • Liver Neoplasms / pathology
  • Liver Neoplasms / therapy
  • Molecular Targeted Therapy
  • Mutation
  • Phenotype
  • Polymorphism, Single Nucleotide
  • Precision Medicine
  • Predictive Value of Tests
  • Prognosis
  • Risk Assessment
  • Risk Factors

Substances

  • Biomarkers, Tumor