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

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Department of Biotechnology and Genetic Engineering, Islamic University, Kushtia-7003, Bangladesh
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Department of Biochemistry and Biotechnology, School of Biomedical Science, Khwaja Yunus Ali University, Sirajgonj-6751, Bangladesh
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Department of Bioengineering, Adana Science and Technology University, Adana-01250, Turkey
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Department of Bioengineering, Marmara University, Istanbul-34722, Turkey
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Department of Bioengineering, Istanbul Medeniyet University, Istanbul-34700, Turkey
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Department of Statistics, Begum Rokeya University, Rangpur-5400, Bangladesh
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Laboratory of Bioinformatics, Department of Statistics, University of Rajshahi, Rajshahi-6205, Bangladesh
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The University of Sydney, Faculty of Medicine and Health, Sydney Medical School, Discipline of Biomedical Science, Sydney, NSW 2006, Australia
*
Authors to whom correspondence should be addressed.
These two authors have made an equal contribution and hold joint first authorship for this work.
Medicina 2019, 55(1), 20; https://doi.org/10.3390/medicina55010020
Received: 30 November 2018 / Revised: 23 December 2018 / Accepted: 14 January 2019 / Published: 17 January 2019
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 aimed to identify molecular biomarker signatures in CRC. Materials and Methods: We analyzed two microarray datasets (GSE35279 and GSE21815) from the 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 upregulated and 99 downregulated DEGs were detected. The PI3K/Akt signaling, Wnt signaling, extracellular matrix (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 two microRNAs (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 the 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 the development of accurate diagnostic and/or prognostic biomarker screens and efficient therapeutic strategies in CRC. View Full-Text
Keywords: colorectal cancer; differentially expressed genes; biomarkers; protein–protein interaction; reporter biomolecules; candidate drugs; systems biology; drug repositioning colorectal cancer; differentially expressed genes; biomarkers; protein–protein interaction; reporter biomolecules; candidate drugs; systems biology; drug repositioning
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Rahman, M.R.; Islam, T.; Gov, E.; Turanli, B.; Gulfidan, G.; Shahjaman, M.; Akhter Banu, N.; 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.

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