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Analysis of Pathway Activity in Primary Tumors and NCI60 Cell Lines Using Gene Expression Profiling Data
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作者 Xing-Dong Feng Shu-Guang Huang +8 位作者 Jian-Yong Shou Bi-Rong Liao Jonathan M. Yingling Xiang Ye Xi Lin Lawrence M. Gelbert Eric W. Su Jude E. Onyia Shu-Yu Li 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2007年第1期15-24,共10页
To determine cancer pathway activities in nine types of primary tumors and NCI60 cell lines, we applied an in silico approach by examining gene signatures reflective of consequent pathway activation using gene express... To determine cancer pathway activities in nine types of primary tumors and NCI60 cell lines, we applied an in silico approach by examining gene signatures reflective of consequent pathway activation using gene expression data. Supervised learning approaches predicted that the Ras pathway is active in -70% of lung adenocarcinomas but inactive in most squamous cell carcinomas, pulmonary carcinoids, and small cell lung carcinomas. In contrast, the TGF-β, TNF-α, Src, Myc, E2F3, and β-catenin pathways are inactive in lung adenocarcinomas. We predicted an active Ras, Myc, Src, and/or E2F3 pathway in significant percentages of breast cancer, colorectal carcinoma, and gliomas. Our results also suggest that Ras may be the most prevailing oncogenic pathway. Additionally, many NCI60 cell lines exhibited a gene signature indicative of an active Ras, Myc, and/or Src, but not E2F3, β-catenin, TNF-α, or TGF-β pathway. To our knowledge, this is the first comprehensive survey of cancer pathway activities in nine major tumor types and the most widely used NCI60 cell lines. The "gene expression pathway signatures" we have defined could facilitate the understanding of molecular mechanisms in cancer development and provide guidance to the selection of appropriate cell lines for cancer research and pharmaceutical compound screening. 展开更多
关键词 cancer pathways gene expression profiling supervised learning CLASSIFICATION
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