Literature DB >> 26662407

Identification of hub genes and pathways associated with retinoblastoma based on co-expression network analysis.

Q L Wang1, X Chen2, M H Zhang3, Q H Shen4, Z M Qin5.   

Abstract

The objective of this paper was to identify hub genes and pathways associated with retinoblastoma using centrality analysis of the co-expression network and pathway-enrichment analysis. The co-expression network of retinoblastoma was constructed by weighted gene co-expression network analysis (WGCNA) based on differentially expressed (DE) genes, and clusters were obtained through the molecular complex detection (MCODE) algorithm. Degree centrality analysis of the co-expression network was performed to explore hub genes present in retinoblastoma. Pathway-enrichment analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Validation of hub gene expression in retinoblastoma was performed by reverse transcription-polymerase chain reaction (RT-PCR) analysis. The co-expression network based on 221 DE genes between retinoblastoma and normal controls consisted of 210 nodes and 3965 edges, and 5 clusters of the network were evaluated. By assessing the centrality analysis of the co-expression network, 21 hub genes were identified, such as SNORD115-41, RASSF2, and SNORD115-44. According to RT-PCR analysis, 16 of the 21 hub genes were differently expressed, including RASSF2 and CDCA7, and 5 were not differently expressed in retinoblastoma compared to normal controls. Pathway analysis showed that genes in 2 clusters were enriched in 3 pathways: purine metabolism, p53 signaling pathway, and melanogenesis. In this study, we successfully identified 16 hub genes and 3 pathways associated with retinoblastoma, which may be potential biomarkers for early detection and therapy for retinoblastoma.

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Year:  2015        PMID: 26662407     DOI: 10.4238/2015.December.8.4

Source DB:  PubMed          Journal:  Genet Mol Res        ISSN: 1676-5680


  7 in total

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5.  Comprehensive Analysis of Serum Small Extracellular Vesicles-Derived Coding and Non-Coding RNAs from Retinoblastoma Patients for Identifying Regulatory Interactions.

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Journal:  Cancers (Basel)       Date:  2022-08-29       Impact factor: 6.575

6.  Identification of two novel biomarkers of rectal carcinoma progression and prognosis via co-expression network analysis.

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  7 in total

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