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Comprehensive analysis of ceRNA network of ERCC4 in colorectal cancer

OBJECTIVE: ERCC4 is one of the most significant molecules of Nucleotide Excision Repair (NER), which has been researched due to its high expression in colorectal cancer (CRC). This study aimed to find out the ceRNA (competitive endogenous RNA) network of ERCC4 in CRC. METHODS AND MATERIALS: Pan canc...

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Autores principales: Hu, Huixin, Liu, Songyi, Chu, Aining, Chen, Jing, Xing, Chengzhong, Jing, Jingjing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8679902/
https://www.ncbi.nlm.nih.gov/pubmed/34993023
http://dx.doi.org/10.7717/peerj.12647
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author Hu, Huixin
Liu, Songyi
Chu, Aining
Chen, Jing
Xing, Chengzhong
Jing, Jingjing
author_facet Hu, Huixin
Liu, Songyi
Chu, Aining
Chen, Jing
Xing, Chengzhong
Jing, Jingjing
author_sort Hu, Huixin
collection PubMed
description OBJECTIVE: ERCC4 is one of the most significant molecules of Nucleotide Excision Repair (NER), which has been researched due to its high expression in colorectal cancer (CRC). This study aimed to find out the ceRNA (competitive endogenous RNA) network of ERCC4 in CRC. METHODS AND MATERIALS: Pan cancer mRNA expression of ERCC4 was evaluated using TCGA database. The protein expression of ERCC4 was evaluated based on the Human Protein Atlas (HPA). We screened DElncRNAs and DEmiRNAs in two groups of ERCC4(high) and ERCC4(low) expression in CRC. Then a lncRNA-miRNA-ERCC4 regulatory network was constructed based on DElncRNAs and DEmiRNAs using Starbase database and visualized by Cytoscape software. Kaplan-Meier analysis was performed to evaluate the prognostic value of the ceRNA network. Further, RT-PCR was performed to validate the expression of the representative molecules in the ceRNA network in CRC and normal tissues. The relationship between drug sensitivity and these molecules were also evaluated using RNAactDrug database. RESULTS: ERCC4 was overexpressed in a variety of tumors at mRNA levels, including CRC. High expression of ERCC4 was also observed on protein level in CRC. A total of 1,885 DElncRNAs and 68 DEmiRNAs were identified from CRC samples in ERCC4(high) and ERCC4(low) expression groups. Predicted by the Starbase database, we got interacting miRNAs and lncRNAs of ERCC4 from the DEmiRNAs and DElncRNAs, and a lncRNA-miRNA-ERCC4 regulatory network was constructed. Kaplan-Meier survival curves results showed that miR-200c-3p (hazard ratio [HR] = 0.62, P = 0.032), MALAT1 (HR = 1.54, P = 0.016), and AC005520.2 (hazard ratio [HR] = 1.75, P = 0.002) were significantly associated with the prognosis of CRC. After validation by RT-PCR, we found that ERCC4 and MALAT1 were up-regulated in CRC compared with normal tissues, while miR-200c-3p was down-regulated. A strong negative correlation was observed between MALAT1 and miR-200c-3p. Drug sensitivity analysis showed that ERCC4, miR-200c and MALAT1 were all associated with Cisplatin. CONCLUSION: We constructed a ceRNA network of ERCC4 in CRC, of which the MALAT1-miR-200c-3p-ERCC4 axis may be involved in the development, prognosis and chemotherapy sensitivity of CRC. These findings might provide novel clues and insights on the molecular mechanisms of ERCC4 and NER pathway in CRC.
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spelling pubmed-86799022022-01-05 Comprehensive analysis of ceRNA network of ERCC4 in colorectal cancer Hu, Huixin Liu, Songyi Chu, Aining Chen, Jing Xing, Chengzhong Jing, Jingjing PeerJ Bioinformatics OBJECTIVE: ERCC4 is one of the most significant molecules of Nucleotide Excision Repair (NER), which has been researched due to its high expression in colorectal cancer (CRC). This study aimed to find out the ceRNA (competitive endogenous RNA) network of ERCC4 in CRC. METHODS AND MATERIALS: Pan cancer mRNA expression of ERCC4 was evaluated using TCGA database. The protein expression of ERCC4 was evaluated based on the Human Protein Atlas (HPA). We screened DElncRNAs and DEmiRNAs in two groups of ERCC4(high) and ERCC4(low) expression in CRC. Then a lncRNA-miRNA-ERCC4 regulatory network was constructed based on DElncRNAs and DEmiRNAs using Starbase database and visualized by Cytoscape software. Kaplan-Meier analysis was performed to evaluate the prognostic value of the ceRNA network. Further, RT-PCR was performed to validate the expression of the representative molecules in the ceRNA network in CRC and normal tissues. The relationship between drug sensitivity and these molecules were also evaluated using RNAactDrug database. RESULTS: ERCC4 was overexpressed in a variety of tumors at mRNA levels, including CRC. High expression of ERCC4 was also observed on protein level in CRC. A total of 1,885 DElncRNAs and 68 DEmiRNAs were identified from CRC samples in ERCC4(high) and ERCC4(low) expression groups. Predicted by the Starbase database, we got interacting miRNAs and lncRNAs of ERCC4 from the DEmiRNAs and DElncRNAs, and a lncRNA-miRNA-ERCC4 regulatory network was constructed. Kaplan-Meier survival curves results showed that miR-200c-3p (hazard ratio [HR] = 0.62, P = 0.032), MALAT1 (HR = 1.54, P = 0.016), and AC005520.2 (hazard ratio [HR] = 1.75, P = 0.002) were significantly associated with the prognosis of CRC. After validation by RT-PCR, we found that ERCC4 and MALAT1 were up-regulated in CRC compared with normal tissues, while miR-200c-3p was down-regulated. A strong negative correlation was observed between MALAT1 and miR-200c-3p. Drug sensitivity analysis showed that ERCC4, miR-200c and MALAT1 were all associated with Cisplatin. CONCLUSION: We constructed a ceRNA network of ERCC4 in CRC, of which the MALAT1-miR-200c-3p-ERCC4 axis may be involved in the development, prognosis and chemotherapy sensitivity of CRC. These findings might provide novel clues and insights on the molecular mechanisms of ERCC4 and NER pathway in CRC. PeerJ Inc. 2021-12-14 /pmc/articles/PMC8679902/ /pubmed/34993023 http://dx.doi.org/10.7717/peerj.12647 Text en © 2021 Hu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Hu, Huixin
Liu, Songyi
Chu, Aining
Chen, Jing
Xing, Chengzhong
Jing, Jingjing
Comprehensive analysis of ceRNA network of ERCC4 in colorectal cancer
title Comprehensive analysis of ceRNA network of ERCC4 in colorectal cancer
title_full Comprehensive analysis of ceRNA network of ERCC4 in colorectal cancer
title_fullStr Comprehensive analysis of ceRNA network of ERCC4 in colorectal cancer
title_full_unstemmed Comprehensive analysis of ceRNA network of ERCC4 in colorectal cancer
title_short Comprehensive analysis of ceRNA network of ERCC4 in colorectal cancer
title_sort comprehensive analysis of cerna network of ercc4 in colorectal cancer
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8679902/
https://www.ncbi.nlm.nih.gov/pubmed/34993023
http://dx.doi.org/10.7717/peerj.12647
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