Integrative Transcriptome Analysis Reveals Common Molecular Subclasses of Human Hepatocellular Carcinoma

By Yujin Hoshida, Sebastian M. B. Nijman, M. Kobayashi, J. Chan, Jean-Philippe Brunet, Derek Y. Chiang, A. Villanueva, P. Newell, K. Ikeda, M. Hashimoto and 6 more. Cancer Research, 2009

1,102 citations recorded by the source corpus.

Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, and prior attempts to develop genomics-based classification for HCC have yielded highly divergent results, indicating difficulty to identify unified molecular anatomy. We performed a meta-analysis of gene expression profiles in datasets from 8 independent patient cohorts across the world. In addition, aiming to establish the real world applicability of a classification system, we profiled 118 formalin-fixed, paraffin-embedded tissues from an additional patient cohort. A total of 603 patients were analyzed, representing the major etiologies of HCC (hepatitis B and C) collected from Western and Eastern countries. We observed 3 robust HCC subclasses (termed S1, S2, and S3), each correlated with clinical parameters such as tumor size, extent of cellular differentiation, and serum alpha-fetoprotein levels. An analysis of the components of the signatures indicated that S1 reflected aberrant activation of the WNT signaling pathway, S2 was characterized by proliferation as well as MYC and AKT activation, and S3 was associated with hepatocyte differentiation. Functional studies indicated that the WNT pathway activation signature characteristic of S1 tumors was not simply the result of beta-catenin mutation, but rather was the result of TGF-beta activation, thus representing a new mechanism of WNT pathway activation in HCC. These experiments establish the first consensus classification framework for HCC based on gene-expression profiles, and highlight the power of integrating of multiple datasets to define a robust molecular taxonomy of the disease.

Subfields: Epidemiology, Hepatology, Pulmonary and Respiratory Medicine

View Paper: https://www.semanticscholar.org/paper/395e8445c15dbecd0d936ea2f3e41a01bc34d0a0

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Citations in the corpus

Hepatocellular carcinoma (HCC): Epidemiology, etiology and molecular classification (2020, methodology): “Immune-high group was associated with Hoshida’s S1 and Boyault’s G2 and Immune-low subtype with Hoshida’s S3 and Boyault’s G6 subclasses (Boyault et al., 2007; Hoshida et al., 2009).”
Current Strategy for Staging and Treatment: The BCLC Update and Future Prospects (2010, methodology): “The approach should be considered a work in progress as reflected by a recent meta-analysis where all the proposed molecular classifications have been merged and resulted in a system with just three strata.(71) Clearly, the future is in this direction, but we are not there yet.”
Asia–Pacific clinical practice guidelines on the management of hepatocellular carcinoma: a 2017 update (2017, background): “Abnormal serum AFP levels can be detected in only a meager proportion of early-stage HCC tumors (10–20%), which has been correlated now with a particular subtype of HCC depicting an aggressive behavior (S2 class, EpCAM positive) [383].”
Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma (2017, neutral): “, 2016), Hoshida signature (Hoshida et al., 2009), and 65-gene risk scores for recurrence (RS65) (Kim et al.”
Deep Learning based multi-omics integration robustly predicts survival in liver cancer (2017, background): “To understand the HCC heterogeneity among patients, a considerable amount of work has been done to identify the HCC molecular subtypes (13-19).”