Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer Export

@article{citeulike:5879400, abstract = {Author Summary Gastric cancer is the second leading cause of global cancer mortality. With current treatments, less than a quarter of patients survive longer than five years after surgery. Individual gastric cancers are highly disparate in their cellular characteristics and responses to standard chemotherapeutic drugs, making gastric cancer a complex disease. Pathway based approaches, rather than single gene studies, may help to unravel this complexity. Here, we make use of a computational approach to identify connections between molecular pathways and cancer profiles. In a large scale study of more than 300 patients, we identified subgroups of gastric cancers distinguishable by their patterns of driving molecular pathways. We show that these identified subgroups are clinically relevant in predicting survival duration and may prove useful in guiding the choice of targeted therapies designed to interfere with these molecular pathways. We also identified specific gastric cancer cell lines mirroring these pathway subgroups, which should facilitate the pre-clinical assessment of responses to targeted therapies in each subgroup.}, author = {Ooi, Chia H. and Ivanova, Tatiana and Wu, Jeanie and Lee, Minghui and Tan, Iain B. and Tao, Jiong and Ward, Lindsay and Koo, Jun H. and Gopalakrishnan, Veena and Zhu, Yansong and Cheng, Lai L. and Lee, Julian and Rha, Sun Y. and Chung, Hyun C. and Ganesan, Kumaresan and So, Jimmy and Soo, Khee C. and Lim, Dennis and Chan, Weng H. and Wong, Wai K. and Bowtell, David and Yeoh, Khay G. and Grabsch, Heike and Boussioutas, Alex and Tan, Patrick}, citeulike-article-id = {5879400}, citeulike-linkout-0 = {http://dx.doi.org/10.1371/journal.pgen.1000676}, day = {2}, doi = {10.1371/journal.pgen.1000676}, journal = {PLoS Genet}, keywords = {cancer, diganostic, expression, gene, network}, month = {October}, number = {10}, pages = {e1000676+}, posted-at = {2009-10-07 15:40:18}, priority = {2}, publisher = {Public Library of Science}, title = {Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer}, url = {http://dx.doi.org/10.1371/journal.pgen.1000676}, volume = {5}, year = {2009} }

TY - JOUR ID - citeulike:5879400 L3 - citeulike-article-id:5879400 N2 - Author Summary Gastric cancer is the second leading cause of global cancer mortality. With current treatments, less than a quarter of patients survive longer than five years after surgery. Individual gastric cancers are highly disparate in their cellular characteristics and responses to standard chemotherapeutic drugs, making gastric cancer a complex disease. Pathway based approaches, rather than single gene studies, may help to unravel this complexity. Here, we make use of a computational approach to identify connections between molecular pathways and cancer profiles. In a large scale study of more than 300 patients, we identified subgroups of gastric cancers distinguishable by their patterns of driving molecular pathways. We show that these identified subgroups are clinically relevant in predicting survival duration and may prove useful in guiding the choice of targeted therapies designed to interfere with these molecular pathways. We also identified specific gastric cancer cell lines mirroring these pathway subgroups, which should facilitate the pre-clinical assessment of responses to targeted therapies in each subgroup. IS - 10 JF - PLoS Genet TI - Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer PB - Public Library of Science VL - 5 SP - e1000676 KW - cancer KW - diganostic KW - expression KW - gene KW - network AU - Ooi, Chia AU - Ivanova, Tatiana AU - Wu, Jeanie AU - Lee, Minghui AU - Tan, Iain AU - Tao, Jiong AU - Ward, Lindsay AU - Koo, Jun AU - Gopalakrishnan, Veena AU - Zhu, Yansong AU - Cheng, Lai AU - Lee, Julian AU - Rha, Sun AU - Chung, Hyun AU - Ganesan, Kumaresan AU - So, Jimmy AU - Soo, Khee AU - Lim, Dennis AU - Chan, Weng AU - Wong, Wai AU - Bowtell, David AU - Yeoh, Khay AU - Grabsch, Heike AU - Boussioutas, Alex AU - Tan, Patrick PY - 2009/10/02/ UR - http://dx.doi.org/10.1371/journal.pgen.1000676 ER -