Prediction and validation of GUCA2B as the hub-gene in colorectal cancer based on co-expression network analysis: In-silico and in-vivo study

Biomedicine & Pharmacotherapy

Hossein Safarpour¹  Tahmine Tavakoli²  Zohreh Rezaei³  Reyhane Hoshyar⁴  Samira Nomiri⁴  Elham Chamani⁴  Fatemeh Salmani⁵  Pegah Larki⁶  Faranak gholipour⁷  Neda Jalili Tabrizi⁷  Afshin Derakhshani⁸  Mariacarmela Santarpia⁹  Tindara Franchina⁹  Oronzo Brunetti^1,10  Nicola Silvestris^1,10 

[1] Department of Biomedical Sciences and Human Oncology (DIMO), University of Bari, Bari, Italy;Cardiovascular Research Center, Birjand University of Medical Sciences, Birjand, Iran;Department of Biology, Faculty of Sciences, University of Sistan and Balouchestan, Zahedan, Iran;Department of Clinical Biochemistry, Faculty of Medicine, Birjand University of Medical Sciences, Birjand, Iran;Department of Epidemiology and Biostatistics, Social Determinants of Health Research Center, Faculty of Health, Birjand University of Medical Sciences, Birjand, Iran;Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran;Immunology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran;Laboratory of Experimental Pharmacology, IRCCS Istituto Tumori Giovanni Paolo II, Bari, Italy;Medical Oncology Unit, Department of Human Pathology “G. Barresi”, University of Messina, Messina, Italy;Medical Oncology Unit, IRCCS Istituto Tumori “Giovanni Paolo II” of Bari, Bari, Italy;

关键词: Colorectal cancer;    Molecular pathogenicity;    Transcriptome analysis;    WGCNA;    GUCA2B;   

DOI  :  

来源: DOAJ

【 摘 要 】

Background: Several serious attempts to treat colorectal cancer have been made in recent decades. However, no effective treatment has yet been discovered due to the complexities of its etiology. Methods: we used Weighted Gene Co-expression Network Analysis (WGCNA) to identify key modules, hub-genes, and mRNA-miRNA regulatory networks associated with CRC. Next, enrichment analysis of modules has been performed using Cluepedia. Next, quantitative real-time PCR (RT-qPCR) was used to validate the expression of selected hub-genes in CRC tissues. Results: Based on the WGCNA results, the brown module had a significant positive correlation (r = 0.98, p-value=9e-07) with CRC. Using the survival and DEGs analyses, 22 genes were identified as hub-genes. Next, three candidate hub-genes were selected for RT-qPCR validation, and 22 pairs of cancerous and non-cancerous tissues were collected from CRC patients referred to the Gastroenterology and Liver Clinic. The RT-qPCR results revealed that the expression of GUCA2B was significantly reduced in CRC tissues, which is consistent with the results of differential expression analysis. Finally, top miRNAs correlated with GUCA2B were identified, and ROC analyses revealed that GUCA2B has a high diagnostic performance for CRC. Conclusions: The current study discovered key modules and GUCA2B as a hub-gene associated with CRC, providing references to understand the pathogenesis and be considered a novel candidate to CRC target therapy.

【 授权许可】

Unknown