J Liver Cancer.  2019 Sep;19(2):97-107. 10.17998/jlc.19.2.97.

The Genomic Landscape and Its Clinical Implications in Hepatocellular Carcinoma

• Yim SY
• Lee JS

• KMID: 2463610
• DOI: http://doi.org/10.17998/jlc.19.2.97

Abstract

The pathogenesis of hepatocellular carcinoma (HCC) is a complex process. During the last decade, advances in genomic technologies enabled delineation of the genomic landscape of HCC, resulting in the identification of the common underlying molecular alterations. The tumor microenvironment, regulated by inflammatory cells, including cancer cells, stromal tissues, and the surrounding extracellular matrix, has been extensively studied using molecular data. The integration of molecular, immunological, histopathological, and clinical findings has provided clues to uncover predictive biomarkers to enhance responses to novel therapies. Herein, we provide an overview of the current HCC genomic landscape, previously identified gene signatures that are used routinely to predict prognosis, and an immune-specific class of HCC. Since biomarker-driven treatment is still an unmet need in HCC management, translation of these discoveries into clinical practice will lead to personalized therapies and improve patient care, especially in the era of targeted and immunotherapies.

Keyword

Advanced hepatocellular carcinoma; Sorafenib; Adverse event; Pancreatic pseudocyst; Pancreatitis

MeSH Terms

Biomarkers
Carcinoma, Hepatocellular*
Extracellular Matrix
Humans
Immunotherapy
Pancreatic Pseudocyst
Pancreatitis
Patient Care
Prognosis
Stromal Cells
Tumor Microenvironment
Biomarkers

Figure

• 

  Figure 1. The landscape of genomic alterations in hepatocellular carcinomas. The top panel shows individual tumor mutation counts, and the middle panel shows clinical parameters. The bottom panel shows genes with significant levels of mutations (MutSig suite, FDR, <0.1) and mutation types are shown as legends at the bottom. Adapted from reference [4]. FDR, false discovery rate.

• 

  Figure 2. Integration of molecular, pathological, clinical, and immune classifications. Proliferative classes (S1, S2, [Hoshida’s classification] and G1-3 [Boyault’s classification]) are associated with poor prognosis, and non-proliferative classes (S3, G4-6) are less aggressive subtypes. HBV, hepatitis B virus; AFP, alpha-fetoprotein; ATM, ataxia telangiectasia mutated; CK19, cytokeratin 19; CRP, C-reactive protein; CTNNB1, catenin beta 1; EpCAM, epithelial cell adhesion molecule; FGF19, fibroblast growth factor 19; p-S6, phospho-ribosomal protein S6; RPS6KA3, ribosomal protein S6 kinase A3; TSC1/2, tuberous sclerosis 1/2; TP53, tumor protein P53. Adapted from reference [54] with permission.

• 

  Figure 3. Classification of hepatocellular carcinomas based on immune classes. Immune classes are characterized by high immune tumor infiltration levels and are classified into two subgroups. The “active immune” subgroup has markers for adaptive T-cell responses and has molecular traits responsive to immunotherapies, while the “exhausted immune group” has stromal and TGF-β activation. HCC, hepatocellular carcinoma; CCL4, C-C motif chemokine ligand 4; CTNNB1, catenin beta 1; IFN-γ, interferon-gamma; GZMB, granzyme B; PD-1, programmed cell death 1; PD-L1, program cell death 1 ligand 1; PRF, perforin 1; PTK2, protein tyrosine kinase 2; TGF-β, transforming growth factor-beta 1; TLS, tertiary lymphoid structures. Adapted from reference [60] and reference [62] with permission.

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