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Molecular signature of cancer at gene level or pathway level? Case studies of colorectal cancer and prostate cancer microarray data.


ABSTRACT: With recent advances in microarray technology, there has been a flourish in genome-scale identification of molecular signatures for cancer. However, the differentially expressed genes obtained by different laboratories are highly divergent. The present discrepancy at gene level indicates a need for a novel strategy to obtain more robust signatures for cancer. In this paper we hypothesize that (1) the expression signatures of different cancer microarray datasets are more similar at pathway level than at gene level; (2) the comparability of the cancer molecular mechanisms of different individuals is related to their genetic similarities. In support of the hypotheses, we summarized theoretical and experimental evidences, and conducted case studies on colorectal and prostate cancer microarray datasets. Based on the above assumption, we propose that reliable cancer signatures should be investigated in the context of biological pathways, within a cohort of genetically homogeneous population. It is hoped that the hypotheses can guide future research in cancer mechanism and signature discovery.

SUBMITTER: Chen J 

PROVIDER: S-EPMC3562646 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Molecular signature of cancer at gene level or pathway level? Case studies of colorectal cancer and prostate cancer microarray data.

Chen Jiajia J   Wang Ying Y   Shen Bairong B   Zhang Daqing D  

Computational and mathematical methods in medicine 20130116


With recent advances in microarray technology, there has been a flourish in genome-scale identification of molecular signatures for cancer. However, the differentially expressed genes obtained by different laboratories are highly divergent. The present discrepancy at gene level indicates a need for a novel strategy to obtain more robust signatures for cancer. In this paper we hypothesize that (1) the expression signatures of different cancer microarray datasets are more similar at pathway level  ...[more]

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