Journal
BMC GENOMICS
Volume 15, Issue -, Pages -Publisher
BMC
DOI: 10.1186/1471-2164-15-1015
Keywords
Prostate cancer; Co-expression; Gene Ontology; Module; Transcription factor; MicroRNA
Funding
- National Institutes of Health [R01LM011177, P50CA095103, P50CA098131, P30CA068485]
- Ingram Professorship Funds
- National Natural Science Foundation of China [31470821, 91230117, 31170795]
- China Scholarship Council [201206920018]
- NATIONAL CANCER INSTITUTE [P50CA095103, P30CA068485, P50CA098131] Funding Source: NIH RePORTER
- NATIONAL LIBRARY OF MEDICINE [R01LM011177] Funding Source: NIH RePORTER
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Background: Prostate cancer (PrCa) is the most commonly diagnosed cancer in men in the world. Despite the fact that a large number of its genes have been investigated, its etiology remains poorly understood. Furthermore, most PrCa candidate genes have not been rigorously replicated, and the methods by which they biologically function in PrCa remain largely unknown. Results: Aiming to identify key players in the complex prostate cancer system, we reconstructed PrCa co-expressed modules within functional gene sets defined by the Gene Ontology (GO) annotation (biological process, GO_BP). We primarily identified 118 GO_BP terms that were well-preserved between two independent gene expression datasets and a consequent 55 conserved co-expression modules within them. Five modules were then found to be significantly enriched with PrCa candidate genes collected from expression Quantitative Trait Loci (eQTL), somatic copy number alteration (SCNA), somatic mutation data, or prognostic analyses. Specifically, two transcription factors (TFs) (NFAT and SP1) and three microRNAs (hsa-miR-19a, hsa-miR-15a, and hsa-miR-200b) regulating these five candidate modules were found to be critical to the development of PrCa. Conclusions: Collectively, our results indicated that genes with similar functions may play important roles in disease through co-expression, and modules with different functions could be regulated by similar genetic components, such as TFs and microRNAs, in a synergistic manner.
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