Abstract
The vast amount of gene expression profiling data of bulk tumors and cell lines available in the public domain represents a tremendous resource. For any major cancer type, expression data can identify molecular subtypes, predict patient outcome, identify markers of therapeutic response, determine the functional consequences of somatic mutation, and elucidate the biology of metastatic and advanced cancers. This review provides a broad overview of gene expression profiling in cancer (which may include transcriptome and proteome levels) and the types of findings made using these data. This review also provides specific examples of accessing public cancer gene expression data sets and generating unique views of the data and the resulting genes of interest. These examples involve pan-cancer molecular subtyping, metabolism-associated expression correlates of patient survival involving multiple cancer types, and gene expression correlates of chemotherapy response in breast tumors.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
