Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis

Preoperative radiochemotherapy is a promising therapeutic method for locally advanced rectal cancer patients. However, the response of colorectal cancer (CRC) patients to preoperative radiotherapy varies widely. In this study, we aimed to identify novel biomarkers that could predict the response of...

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Main Authors: Saeid Afshar, Tapak Leili, Payam Amini, Irina Dinu
Format: Article
Language:English
Published: Elsevier 2023-08-01
Series:Heliyon
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844023060772
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author Saeid Afshar
Tapak Leili
Payam Amini
Irina Dinu
author_facet Saeid Afshar
Tapak Leili
Payam Amini
Irina Dinu
author_sort Saeid Afshar
collection DOAJ
description Preoperative radiochemotherapy is a promising therapeutic method for locally advanced rectal cancer patients. However, the response of colorectal cancer (CRC) patients to preoperative radiotherapy varies widely. In this study, we aimed to identify novel biomarkers that could predict the response of colorectal tumors to treatment using a systems biology approach. We applied the Weighted Gene Co-Expression Network Analysis to construct co-expression networks and evaluated the correlation of these networks with radiation using the module-trait relationship. We then identified hub genes and related transcription factors in the selected co-expression module.Our analysis of seven constructed modules revealed that one module, which contained 113 nodes and 6066 edges, had the strongest correlation with radiation effects on CRC (correlation = 0.85; p-value = 6e-7). By analyzing the selected module with the CytoHubba plugin, we identified four hub genes, including ZEB2, JAM2, NDN, and PPAP2A. We also identified seven important transcription factors, including KLF4, SUZ12, TCF4, NANOG, POU5F1, SOX2, and SMARCA4, which may play essential roles in regulating the four hub genes.In summary, our findings suggest that ZEB2, JAM2, NDN, and PPAP2A, along with the seven transcription factors related to these hub genes, may be associated with the response of colorectal tumors to chemoradiotherapy.
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spelling doaj.art-e39145d90abf4d5f8d020d96a9da62d22023-08-30T05:52:55ZengElsevierHeliyon2405-84402023-08-0198e18869Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysisSaeid Afshar0Tapak Leili1Payam Amini2Irina Dinu3Cancer Research Center, Hamadan University of Medical Sciences, Hamadan, IranDepartment of Biostatistics, School of Public Health and Modeling of Noncommunicable Diseases Research Center, Hamadan University of Medical Sciences, Hamadan, Iran; Corresponding author. Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.School of Medicine, Keele University, Keele, Staffordshire, ST5 5BG, UKSchool of Public Health, University of Alberta, Edmonton, AB, CanadaPreoperative radiochemotherapy is a promising therapeutic method for locally advanced rectal cancer patients. However, the response of colorectal cancer (CRC) patients to preoperative radiotherapy varies widely. In this study, we aimed to identify novel biomarkers that could predict the response of colorectal tumors to treatment using a systems biology approach. We applied the Weighted Gene Co-Expression Network Analysis to construct co-expression networks and evaluated the correlation of these networks with radiation using the module-trait relationship. We then identified hub genes and related transcription factors in the selected co-expression module.Our analysis of seven constructed modules revealed that one module, which contained 113 nodes and 6066 edges, had the strongest correlation with radiation effects on CRC (correlation = 0.85; p-value = 6e-7). By analyzing the selected module with the CytoHubba plugin, we identified four hub genes, including ZEB2, JAM2, NDN, and PPAP2A. We also identified seven important transcription factors, including KLF4, SUZ12, TCF4, NANOG, POU5F1, SOX2, and SMARCA4, which may play essential roles in regulating the four hub genes.In summary, our findings suggest that ZEB2, JAM2, NDN, and PPAP2A, along with the seven transcription factors related to these hub genes, may be associated with the response of colorectal tumors to chemoradiotherapy.http://www.sciencedirect.com/science/article/pii/S2405844023060772WGCNAColorectal neoplasmChemoradiotherapyTranscription factors
spellingShingle Saeid Afshar
Tapak Leili
Payam Amini
Irina Dinu
Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis
Heliyon
WGCNA
Colorectal neoplasm
Chemoradiotherapy
Transcription factors
title Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis
title_full Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis
title_fullStr Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis
title_full_unstemmed Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis
title_short Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis
title_sort introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co expression network analysis
topic WGCNA
Colorectal neoplasm
Chemoradiotherapy
Transcription factors
url http://www.sciencedirect.com/science/article/pii/S2405844023060772
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AT payamamini introducingnovelkeygenesandtranscriptionfactorsassociatedwithrectalcancerresponsetochemoradiationthroughcoexpressionnetworkanalysis
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