Preprint Article Version 2 This version is not peer-reviewed

Identification of Prognostic Biomarker Signatures and Candidate Drugs in Colorectal Cancer: Insights from Systems Biology Analysis

Version 1 : Received: 30 November 2018 / Approved: 3 December 2018 / Online: 3 December 2018 (09:33:34 CET)
Version 2 : Received: 28 December 2018 / Approved: 29 December 2018 / Online: 29 December 2018 (07:05:05 CET)

A peer-reviewed article of this Preprint also exists.

Rahman, M.R.; Islam, T.; Gov, E.; Turanli, B.; Gulfidan, G.; Shahjaman, M.; Banu, N.A.; Mollah, M.N.H.; Arga, K.Y.; Moni, M.A. Identification of Prognostic Biomarker Signatures and Candidate Drugs in Colorectal Cancer: Insights from Systems Biology Analysis. Medicina 2019, 55, 20. Rahman, M.R.; Islam, T.; Gov, E.; Turanli, B.; Gulfidan, G.; Shahjaman, M.; Banu, N.A.; Mollah, M.N.H.; Arga, K.Y.; Moni, M.A. Identification of Prognostic Biomarker Signatures and Candidate Drugs in Colorectal Cancer: Insights from Systems Biology Analysis. Medicina 2019, 55, 20.

Journal reference: Medicina 2019, 55, 20
DOI: 10.3390/medicina55010020

Abstract

Background and objectives: Colorectal cancer (CRC) is the second most common cause of cancer-related death in the world, but early diagnosis ameliorates the survival of CRC. This report directed to identify molecular biomarker signatures in CRC. Materials and Methods: We analyzed two microarray datasets (GSE35279 and GSE21815) from Gene Expression Omnibus (GEO) to identify mutual differentially expressed genes (DEGs). We integrated DEGs with protein-protein interaction and transcriptional/post-transcriptional regulatory networks to identify reporter signaling and regulatory molecules; utilized functional overrepresentation and pathway enrichment analyses to elucidate their roles in biological processes and molecular pathways; performed survival analyses to evaluate their prognostic performance; and applied drug repositioning analyses through Connectivity map (CMap) and geneXpharma tools to hypothesize possible drug candidates targeting reporter molecules. Results: A total of 727 up-regulated and 99 down-regulated DEGs were detected. The PI3K-Akt signaling, Wnt signaling, ECM-interaction, and cell cycle were identified as significantly enriched pathways. Ten hub proteins (ADNP, CCND1, CD44, CDK4, CEBPB, CENPA, CENPH, CENPN, MYC, and RFC2), 10 transcription factors (ETS1, ESR1, GATA1, GATA2, GATA3, AR, YBX1, FOXP3, E2F4, and PRDM14) and 2 miRNAs (miR-193b-3p and miR-615-3p) were detected as reporter molecules. The survival analyses through Kaplan Meier curves indicated remarkable performance of reporter molecules in estimation of survival probability in CRC patients. In addition, several drug candidates including anti-neoplastic and immunomodulating agents were repositioned. Conclusions: This study presents biomarker signatures at protein and RNA levels with prognostic capability in CRC. We think that the molecular signatures and candidate drugs presented in this study might be useful in future studies indenting development of accurate diagnostic and/or prognostic biomarker screens and efficient therapeutic strategies in CRC.

Subject Areas

colorectal cancer; differentially expressed genes; biomarkers; protein-protein interaction; reporter biomolecules; candidate drugs; systems biology; drug repositioning

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