Oncogenic pathway combinations predict clinical prognosis in gastric cancer

Chia Huey Ooi, Tatiana Ivanova, Jeanie Wu, Minghui Lee, Iain Beehuat Tan, Jiong Tao, Lindsay Ward, Jun Hao Koo, Veena Gopalakrishnan, Yansong Zhu, Lai Ling Cheng, Julian Lee, SunYoung Rha, Hyuncheol Chung, Kumaresan Ganesan, Jimmy So, Khee Chee Soo, Dennis Lim, Weng Hoong Chan, Wai Keong Wong & 5 others David Bowtell, Khay Guan Yeoh, Heike Grabsch, Alex Boussioutas, Patrick Tan

Research output: Contribution to journalArticle

195 Citations (Scopus)

Abstract

Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-κB, and Wnt/β-catenin) deregulated in the majority (>70%) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms.

Original languageEnglish
Article numbere1000676
JournalPLoS Genetics
Volume5
Issue number10
DOIs
Publication statusPublished - 2009 Oct 1

Fingerprint

stomach neoplasms
prognosis
Stomach Neoplasms
cancer
neoplasms
Neoplasms
Catenins
Survival
Second Primary Neoplasms
Transcriptome
Computer Simulation
stem cells
Stem Cells
cell lines
Cell Line
gene expression
prediction
Mortality
deregulation
stratification

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Genetics
  • Genetics(clinical)
  • Cancer Research

Cite this

Ooi, C. H., Ivanova, T., Wu, J., Lee, M., Tan, I. B., Tao, J., ... Tan, P. (2009). Oncogenic pathway combinations predict clinical prognosis in gastric cancer. PLoS Genetics, 5(10), [e1000676]. https://doi.org/10.1371/journal.pgen.1000676
Ooi, Chia Huey ; Ivanova, Tatiana ; Wu, Jeanie ; Lee, Minghui ; Tan, Iain Beehuat ; Tao, Jiong ; Ward, Lindsay ; Koo, Jun Hao ; Gopalakrishnan, Veena ; Zhu, Yansong ; Cheng, Lai Ling ; Lee, Julian ; Rha, SunYoung ; Chung, Hyuncheol ; Ganesan, Kumaresan ; So, Jimmy ; Soo, Khee Chee ; Lim, Dennis ; Chan, Weng Hoong ; Wong, Wai Keong ; Bowtell, David ; Yeoh, Khay Guan ; Grabsch, Heike ; Boussioutas, Alex ; Tan, Patrick. / Oncogenic pathway combinations predict clinical prognosis in gastric cancer. In: PLoS Genetics. 2009 ; Vol. 5, No. 10.
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abstract = "Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-κB, and Wnt/β-catenin) deregulated in the majority (>70{\%}) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms.",
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Ooi, CH, Ivanova, T, Wu, J, Lee, M, Tan, IB, Tao, J, Ward, L, Koo, JH, Gopalakrishnan, V, Zhu, Y, Cheng, LL, Lee, J, Rha, S, Chung, H, Ganesan, K, So, J, Soo, KC, Lim, D, Chan, WH, Wong, WK, Bowtell, D, Yeoh, KG, Grabsch, H, Boussioutas, A & Tan, P 2009, 'Oncogenic pathway combinations predict clinical prognosis in gastric cancer', PLoS Genetics, vol. 5, no. 10, e1000676. https://doi.org/10.1371/journal.pgen.1000676

Oncogenic pathway combinations predict clinical prognosis in gastric cancer. / Ooi, Chia Huey; Ivanova, Tatiana; Wu, Jeanie; Lee, Minghui; Tan, Iain Beehuat; Tao, Jiong; Ward, Lindsay; Koo, Jun Hao; Gopalakrishnan, Veena; Zhu, Yansong; Cheng, Lai Ling; Lee, Julian; Rha, SunYoung; Chung, Hyuncheol; Ganesan, Kumaresan; So, Jimmy; Soo, Khee Chee; Lim, Dennis; Chan, Weng Hoong; Wong, Wai Keong; Bowtell, David; Yeoh, Khay Guan; Grabsch, Heike; Boussioutas, Alex; Tan, Patrick.

In: PLoS Genetics, Vol. 5, No. 10, e1000676, 01.10.2009.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Oncogenic pathway combinations predict clinical prognosis in gastric cancer

AU - Ooi, Chia Huey

AU - Ivanova, Tatiana

AU - Wu, Jeanie

AU - Lee, Minghui

AU - Tan, Iain Beehuat

AU - Tao, Jiong

AU - Ward, Lindsay

AU - Koo, Jun Hao

AU - Gopalakrishnan, Veena

AU - Zhu, Yansong

AU - Cheng, Lai Ling

AU - Lee, Julian

AU - Rha, SunYoung

AU - Chung, Hyuncheol

AU - Ganesan, Kumaresan

AU - So, Jimmy

AU - Soo, Khee Chee

AU - Lim, Dennis

AU - Chan, Weng Hoong

AU - Wong, Wai Keong

AU - Bowtell, David

AU - Yeoh, Khay Guan

AU - Grabsch, Heike

AU - Boussioutas, Alex

AU - Tan, Patrick

PY - 2009/10/1

Y1 - 2009/10/1

N2 - Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-κB, and Wnt/β-catenin) deregulated in the majority (>70%) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms.

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