Cross-Study Projections of Genomic Biomarkers: An Evaluation in Cancer Genomics Export

@article{citeulike:5253128, abstract = {Human disease studies using DNA microarrays in both clinical/observational and experimental/controlled studies are having increasing impact on our understanding of the complexity of human diseases. A fundamental concept is the use of gene expression as a \^{a}€{\oe}common currency\^{a}€� that links the results of in vitro controlled experiments to in vivo observational human studies. Many studies \^{a}€ ” in cancer and other diseases \^{a}€ ” have shown promise in using in vitro cell manipulations to improve understanding of in vivo biology, but experiments often simply fail to reflect the enormous phenotypic variation seen in human diseases. We address this with a framework and methods to dissect, enhance and extend the in vivo utility of in vitro derived gene expression signatures. From an experimentally defined gene expression signature we use statistical factor analysis to generate multiple quantitative factors in human cancer gene expression data. These factors retain their relationship to the original, one-dimensional in vitro signature but better describe the diversity of in vivo biology. In a breast cancer analysis, we show that factors can reflect fundamentally different biological processes linked to molecular and clinical features of human cancers, and that in combination they can improve prediction of clinical outcomes.}, author = {Lucas, Joseph E. and Carvalho, Carlos M. and Chen, Julia L. and Chi, Jen-Tsan and West, Mike}, citeulike-article-id = {5253128}, citeulike-linkout-0 = {http://dx.doi.org/10.1371/journal.pone.0004523}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/19225561}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=19225561}, day = {19}, doi = {10.1371/journal.pone.0004523}, issn = {1932-6203}, journal = {PLoS ONE}, keywords = {cross-platform, cross-study, gene\_lists, projection}, month = {February}, number = {2}, pages = {e4523+}, posted-at = {2009-09-30 10:11:25}, priority = {0}, publisher = {Public Library of Science}, title = {Cross-Study Projections of Genomic Biomarkers: An Evaluation in Cancer Genomics}, url = {http://dx.doi.org/10.1371/journal.pone.0004523}, volume = {4}, year = {2009} }

TY - JOUR ID - citeulike:5253128 L3 - citeulike-article-id:5253128 N2 - Human disease studies using DNA microarrays in both clinical/observational and experimental/controlled studies are having increasing impact on our understanding of the complexity of human diseases. A fundamental concept is the use of gene expression as a “common currency� that links the results of in vitro controlled experiments to in vivo observational human studies. Many studies – in cancer and other diseases – have shown promise in using in vitro cell manipulations to improve understanding of in vivo biology, but experiments often simply fail to reflect the enormous phenotypic variation seen in human diseases. We address this with a framework and methods to dissect, enhance and extend the in vivo utility of in vitro derived gene expression signatures. From an experimentally defined gene expression signature we use statistical factor analysis to generate multiple quantitative factors in human cancer gene expression data. These factors retain their relationship to the original, one-dimensional in vitro signature but better describe the diversity of in vivo biology. In a breast cancer analysis, we show that factors can reflect fundamentally different biological processes linked to molecular and clinical features of human cancers, and that in combination they can improve prediction of clinical outcomes. IS - 2 JF - PLoS ONE SN - 1932-6203 TI - Cross-Study Projections of Genomic Biomarkers: An Evaluation in Cancer Genomics PB - Public Library of Science VL - 4 SP - e4523 KW - cross-platform KW - cross-study KW - gene_lists KW - projection AU - Lucas, Joseph AU - Carvalho, Carlos AU - Chen, Julia AU - Chi, Jen-Tsan AU - West, Mike PY - 2009/02/19/ UR - http://dx.doi.org/10.1371/journal.pone.0004523 ER -