Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma

Yujin Hoshida, Sebastian M.B. Nijman, Masahiro Kobayashi, Jennifer A. Chan, Jean Philippe Brunet, Derek Y. Chiang, Augusto Villanueva, Philippa Newell, Kenji Ikeda, Masaji Hashimoto, Goro Watanabe, Stacey Gabriel, Scott L. Friedman, Hiromitsu Kumada, Josep M. Llovet, Todd R. Golub

Research output: Contribution to journalArticle

478 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)7385-7392
Number of pages8
JournalCancer Research
Volume69
Issue number18
DOIs
StatePublished - Oct 13 2009
Externally publishedYes

Fingerprint

Gene Expression Profiling
Hepatocellular Carcinoma
Transcriptome
Fetal Proteins
Catenins
Transforming Growth Factors
Hepatitis C
Hepatitis B
Paraffin
Formaldehyde
Meta-Analysis
Hepatocytes
Neoplasms
Anatomy
Mutation
Serum

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Hoshida, Y., Nijman, S. M. B., Kobayashi, M., Chan, J. A., Brunet, J. P., Chiang, D. Y., ... Golub, T. R. (2009). Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma. Cancer Research, 69(18), 7385-7392. https://doi.org/10.1158/0008-5472.CAN-09-1089

Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma. / Hoshida, Yujin; Nijman, Sebastian M.B.; Kobayashi, Masahiro; Chan, Jennifer A.; Brunet, Jean Philippe; Chiang, Derek Y.; Villanueva, Augusto; Newell, Philippa; Ikeda, Kenji; Hashimoto, Masaji; Watanabe, Goro; Gabriel, Stacey; Friedman, Scott L.; Kumada, Hiromitsu; Llovet, Josep M.; Golub, Todd R.

In: Cancer Research, Vol. 69, No. 18, 13.10.2009, p. 7385-7392.

Research output: Contribution to journalArticle

Hoshida, Y, Nijman, SMB, Kobayashi, M, Chan, JA, Brunet, JP, Chiang, DY, Villanueva, A, Newell, P, Ikeda, K, Hashimoto, M, Watanabe, G, Gabriel, S, Friedman, SL, Kumada, H, Llovet, JM & Golub, TR 2009, 'Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma', Cancer Research, vol. 69, no. 18, pp. 7385-7392. https://doi.org/10.1158/0008-5472.CAN-09-1089
Hoshida, Yujin ; Nijman, Sebastian M.B. ; Kobayashi, Masahiro ; Chan, Jennifer A. ; Brunet, Jean Philippe ; Chiang, Derek Y. ; Villanueva, Augusto ; Newell, Philippa ; Ikeda, Kenji ; Hashimoto, Masaji ; Watanabe, Goro ; Gabriel, Stacey ; Friedman, Scott L. ; Kumada, Hiromitsu ; Llovet, Josep M. ; Golub, Todd R. / Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma. In: Cancer Research. 2009 ; Vol. 69, No. 18. pp. 7385-7392.
@article{fa0b7eea6fef4b81910c7d271da9c386,
title = "Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma",
abstract = "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.",
author = "Yujin Hoshida and Nijman, {Sebastian M.B.} and Masahiro Kobayashi and Chan, {Jennifer A.} and Brunet, {Jean Philippe} and Chiang, {Derek Y.} and Augusto Villanueva and Philippa Newell and Kenji Ikeda and Masaji Hashimoto and Goro Watanabe and Stacey Gabriel and Friedman, {Scott L.} and Hiromitsu Kumada and Llovet, {Josep M.} and Golub, {Todd R.}",
year = "2009",
month = "10",
day = "13",
doi = "10.1158/0008-5472.CAN-09-1089",
language = "English (US)",
volume = "69",
pages = "7385--7392",
journal = "Cancer Research",
issn = "0008-5472",
number = "18",

}

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 - 2009/10/13

Y1 - 2009/10/13

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.

UR - http://www.scopus.com/inward/record.url?scp=70349739285&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70349739285&partnerID=8YFLogxK

U2 - 10.1158/0008-5472.CAN-09-1089

DO - 10.1158/0008-5472.CAN-09-1089

M3 - Article

C2 - 19723656

AN - SCOPUS:70349739285

VL - 69

SP - 7385

EP - 7392

JO - Cancer Research

JF - Cancer Research

SN - 0008-5472

IS - 18

ER -