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A comparative analysis of gene-expression data of multiple cancer types.

ABSTRACT: A comparative study of public gene-expression data of seven types of cancers (breast, colon, kidney, lung, pancreatic, prostate and stomach cancers) was conducted with the aim of deriving marker genes, along with associated pathways, that are either common to multiple types of cancers or specific to individual cancers. The analysis results indicate that (a) each of the seven cancer types can be distinguished from its corresponding control tissue based on the expression patterns of a small number of genes, e.g., 2, 3 or 4; (b) the expression patterns of some genes can distinguish multiple cancer types from their corresponding control tissues, potentially serving as general markers for all or some groups of cancers; (c) the proteins encoded by some of these genes are predicted to be blood secretory, thus providing potential cancer markers in blood; (d) the numbers of differentially expressed genes across different cancer types in comparison with their control tissues correlate well with the five-year survival rates associated with the individual cancers; and (e) some metabolic and signaling pathways are abnormally activated or deactivated across all cancer types, while other pathways are more specific to certain cancers or groups of cancers. The novel findings of this study offer considerable insight into these seven cancer types and have the potential to provide exciting new directions for diagnostic and therapeutic development.

SUBMITTER: Xu K

PROVIDER: S-EPMC2965162 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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A comparative analysis of gene-expression data of multiple cancer types.

Xu Kun K Cui Juan J Olman Victor V Yang Qing Q Puett David D Xu Ying Y

PloS one 20101027 10

A comparative study of public gene-expression data of seven types of cancers (breast, colon, kidney, lung, pancreatic, prostate and stomach cancers) was conducted with the aim of deriving marker genes, along with associated pathways, that are either common to multiple types of cancers or specific to individual cancers. The analysis results indicate that (a) each of the seven cancer types can be distinguished from its corresponding control tissue based on the expression patterns of a small number ...[more]

PMID: 21060876

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Project description:Cell migration is an instrumental process that ensures cells are properly positioned to support the specification of distinct tissue types during development. To provide insight, we used fluorescence activated cell sorting (FACS) to isolate two migrating cell types from the Drosophila embryo: caudal visceral mesoderm (CVM) cells, precursors of longitudinal muscles of the gut, and hemocytes (HCs), the Drosophila equivalent of blood cells. ~350 genes were identified from each of the sorted samples using RNA-seq, and in situ hybridization was used to confirm expression within each cell type or, alternatively, within other interacting, co-sorted cell types. To start, the two gene expression profiling datasets were compared to identify cell migration regulators that are potentially generally-acting. 73 genes were present in both CVM cell and HC gene expression profiles, including the transcription factor zinc finger homeodomain-1 (zfh1). Comparisons with gene expression profiles of Drosophila border cells that migrate during oogenesis had a more limited overlap, with only the genes neyo (neo) and singed (sn) found to be expressed in border cells as well as CVM cells and HCs, respectively. Neo encodes a protein with Zona pellucida domain linked to cell polarity, while sn encodes an actin binding protein. Tissue specific RNAi expression coupled with live in vivo imaging was used to confirm cell-autonomous roles for zfh1 and neo in supporting CVM cell migration, whereas previous studies had demonstrated a role for Sn in supporting HC migration. In addition, comparisons were made to migrating cells from vertebrates. Seven genes were found expressed by chick neural crest cells, CVM cells, and HCs including extracellular matrix (ECM) proteins and proteases. In summary, we show that genes shared in common between CVM cells, HCs, and other migrating cell types can help identify regulators of cell migration. Our analyses show that neo in addition to zfh1 and sn studied previously impact cell migration. This study also suggests that modification of the extracellular milieu may be a fundamental requirement for cells that undergo cell streaming migratory behaviors.

Dataset Information

A comparative analysis of gene-expression data of multiple cancer types.

Publications

A comparative analysis of gene-expression data of multiple cancer types.

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