Center for Systems Biology, Soochow University, Jiangsu, Suzhou 215006, China.
Comput Math Methods Med. 2013;2013:909525. doi: 10.1155/2013/909525. Epub 2013 Jan 16.
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.
随着微阵列技术的最新进展，癌症的分子特征的基因组规模鉴定蓬勃发展。然而，不同实验室获得的差异表达基因高度不同。目前在基因水平上的差异表明需要一种新的策略来获得更稳健的癌症特征。在本文中，我们假设：（1）不同癌症微阵列数据集的表达特征在通路水平上比在基因水平上更相似；（2）不同个体的癌症分子机制的可比性与其遗传相似性有关。为了支持这些假设，我们总结了理论和实验证据，并对结直肠癌和前列腺癌微阵列数据集进行了案例研究。基于上述假设，我们提出可靠的癌症特征应该在遗传同质人群的生物途径背景下进行研究。希望这些假设能够指导癌症机制和特征发现的未来研究。
