TY - JOUR
T1 - Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma
AU - Hoshida, Yujin
AU - Nijman, Sebastian M.B.
AU - Kobayashi, Masahiro
AU - Chan, Jennifer A.
AU - Brunet, Jean Philippe
AU - Chiang, Derek Y.
AU - Villanueva, Augusto
AU - Newell, Philippa
AU - Ikeda, Kenji
AU - Hashimoto, Masaji
AU - Watanabe, Goro
AU - Gabriel, Stacey
AU - Friedman, Scott L.
AU - Kumada, Hiromitsu
AU - Llovet, Josep M.
AU - Golub, Todd R.
PY - 2009
Y1 - 2009
N2 - Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, and prior attempts to develop genomic-based classification for HCC have yielded highly divergent results, indicating difficulty in identifying unified molecular anatomy. We performed a meta-analysis of gene expression profiles in data sets from eight 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 three robust HCC subclasses (termed S1, S2, and S3), each correlated with clinical parameters such as tumor size, extent of cellular differentiation, and serum α-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 β-catenin mutation but rather was the result of transforming growth factor-β 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 multiple data sets to define a robust molecular taxonomy of the disease.
AB - Hepatocellular carcinoma (HCC) is a highly heterogeneous disease, and prior attempts to develop genomic-based classification for HCC have yielded highly divergent results, indicating difficulty in identifying unified molecular anatomy. We performed a meta-analysis of gene expression profiles in data sets from eight 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 three robust HCC subclasses (termed S1, S2, and S3), each correlated with clinical parameters such as tumor size, extent of cellular differentiation, and serum α-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 β-catenin mutation but rather was the result of transforming growth factor-β 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 multiple data sets to define a robust molecular taxonomy of the disease.
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U2 - 10.1158/0008-5472.CAN-09-1089
DO - 10.1158/0008-5472.CAN-09-1089
M3 - Article
C2 - 19723656
AN - SCOPUS:70349739285
SN - 0008-5472
VL - 69
SP - 7385
EP - 7392
JO - Cancer research
JF - Cancer research
IS - 18
ER -