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Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer

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 s...

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Detalles Bibliográficos
Autores principales: 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, Sun Young, Chung, Hyun Cheol, 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
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2748685/
https://www.ncbi.nlm.nih.gov/pubmed/19798449
http://dx.doi.org/10.1371/journal.pgen.1000676
Descripción
Sumario: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.