Weighted gene coexpression network analysis of DEGs detected in breast cancer cell response to soy isoflavones

Soy foods are rich in isoflavones, which belong to the phytoestrogen family that could reduce breast cancerrisk. To define the biological networks affected by isoflavones in breast cancer cells, a WGCNA wasperformed to identify modules by analyzing ۲۸۳ microarray samples from ۷ different experiments. Theresults showed, genes were grouped into five discrete modules, each of which was coded by a unique color.The size of these modules ranged from ۱۰۱ to ۲,۲۵۷ genes. The two major modules were named turquoise(۲,۲۵۷ genes), and blue (۱,۰۱۳genes). We performed an enrichment of GO to gain insight into the biologicalfunctions of the genes within these modules. The turquoise module was highly enriched for cell division andmitotic nuclear division. The blue module was associated with DNA replication. The majority of genes inblue module were up-regulated by isoflavones. The blue module also included ۳۹ genes that were related topathways in cancer (e.g., BAD, HSP۹۰B۱, and E۲F۳). BAD regulates cell growth. Role of Hsp۹۰B۱ inovarian cell survival and cell apoptosis has been highlighted. E۲F۳ controls cell cycle progression. The brownmodule was highly enriched for genes involved in embryonic digit morphogenesis. Moreover, we observedthis module was annotated in response to estrogen. This module was enriched for hippo signaling pathway.Hippo pathway plays an important role in cell proliferation and breast cancer metastasis. The GATA۳ genewas found in the brown module. GATA۳ requires normal development of the mammary gland and shows arelatively high sensitivity to breast carcinomas. The yellow module was observed to be enriched with termssuch as cell-cell adhesion, translation, and protein folding. Finally, the green module was not enriched forany significant biological process term. In the blue module, DEGs were significantly enriched in the cellcycle and cancer pathways.

کلیدواژه ها:

Breast cancer ، Isoflavones ، Weighted gene coexpression network analysis ، Meta-analysis