A signal-based method for finding driver modules of breast cancer metastasis to the lung

Yan G, Chen V, Lu X, Lu S. A signal-based method for finding driver modules of breast cancer metastasis to the lung. Sci Rep. 2017 Aug 30; 7(1):10023. doi: 10.1038/s41598-09951-2. PMID: 28855549. PMC ID: PMC5577160.

Tumor metastasis is mainly caused by somatic genomic alterations (SGAs) that perturb pathways regulating metastasis-relevant activities and thus help the primary tumor to adapt to the new microenvironment. Identifying drivers of metastasis, i.e. SGAs, sheds light on the metastasis mechanism and provides guidance for targeted therapy. In this paper, we introduce a novel method to search for SGAs driving breast cancer metastasis to the lung. First, we search for transcriptomic modules with genes that are differentially expressed in breast cell lines with strong metastatic activities to the lung and co-expressed in a large number of breast tumors. Then, for each transcriptomic module, we search for a set of SGA genes (driver modules) such that genes in each driver module carry a common signal regulating the transcriptomic module. Evaluations indicate that many genes in driver modules are indeed related to metastasis, and our methods have identified many new driver candidates. We further choose two novel metastatic driver genes, BCL2L11 and CDH9, for in vitro verification. The wound healing assay reveals that inhibiting either BCL2L11 or CDH9 will enhance the migration of cell lines, which provides evidence that these two genes are suppressors of tumor metastasis.

Publication Year: 
2017
Publication Credits: 
Yan G, Chen V, Lu X, Lu S
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