Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer Patients
Objective: This study was conducted in order to construct a competitive endogenous RNA (ceRNA) network to screen RNA that plays an important role in colon cancer and to construct a model to predict the prognosis of patients.Methods: The gene expression data of colon cancer were downloaded from the T...
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2021-10-01
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doaj-5a0211d0225c4edeaf1f54db8d26d2542021-10-07T04:56:00ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2021-10-01910.3389/fcell.2021.686844686844Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer PatientsJiasheng Xu0Jiasheng Xu1Tianyi Ling2Tianyi Ling3Siqi Dai4Siqi Dai5Shuwen Han6Shuwen Han7Kefeng Ding8Kefeng Ding9Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaCancer Center, Zhejiang University, Hangzhou, ChinaDepartment of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaCancer Center, Zhejiang University, Hangzhou, ChinaDepartment of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaCancer Center, Zhejiang University, Hangzhou, ChinaDepartment of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaCancer Center, Zhejiang University, Hangzhou, ChinaDepartment of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, ChinaCancer Center, Zhejiang University, Hangzhou, ChinaObjective: This study was conducted in order to construct a competitive endogenous RNA (ceRNA) network to screen RNA that plays an important role in colon cancer and to construct a model to predict the prognosis of patients.Methods: The gene expression data of colon cancer were downloaded from the TCGA database. The difference was analyzed by the R software and the ceRNA network was constructed. The survival-related RNA was screened out by combining with clinical information, and the prognosis model was established by lasso regression. CIBERSORT was used to analyze the infiltration of immune cells in colon cancer, and the differential expression of immune cells related to survival was screened out by combining clinical information. The correlation between RNA and immune cells was analyzed by lasso regression. PCR was used to verify the expression of seven RNAs in colon cancer patients with different prognoses.Results: Two hundred and fifteen lncRNAs, 357 miRNAs, and 2,955 mRNAs were differentially expressed in colon cancer. The constructed ceRNA network contains 18 lncRNAs, 42 miRNAs, and 168 mRNAs, of which 18 RNAs are significantly related to survival. Through lasso analysis, we selected seven optimal RNA construction models. The AUC value of the model was greater than 0.7, and there was a significant difference in the survival rate between the high- and low-risk groups. Two kinds of immune cells related to the prognosis of patients were screened out. The results showed that the expression of seven RNA markers in colon cancer patients with different prognoses was basically consistent with the model analysis.Conclusion: We have established the regulatory network of ceRNA in colon cancer, screened out seven core RNAs and two kinds of immune cells, and constructed a comprehensive prognosis model of colon cancer patients.https://www.frontiersin.org/articles/10.3389/fcell.2021.686844/fullceRNA regulatory networkimmune cellsprognosisevaluation modelcolon cancer |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jiasheng Xu Jiasheng Xu Tianyi Ling Tianyi Ling Siqi Dai Siqi Dai Shuwen Han Shuwen Han Kefeng Ding Kefeng Ding |
spellingShingle |
Jiasheng Xu Jiasheng Xu Tianyi Ling Tianyi Ling Siqi Dai Siqi Dai Shuwen Han Shuwen Han Kefeng Ding Kefeng Ding Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer Patients Frontiers in Cell and Developmental Biology ceRNA regulatory network immune cells prognosis evaluation model colon cancer |
author_facet |
Jiasheng Xu Jiasheng Xu Tianyi Ling Tianyi Ling Siqi Dai Siqi Dai Shuwen Han Shuwen Han Kefeng Ding Kefeng Ding |
author_sort |
Jiasheng Xu |
title |
Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer Patients |
title_short |
Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer Patients |
title_full |
Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer Patients |
title_fullStr |
Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer Patients |
title_full_unstemmed |
Constructing the ceRNA Regulatory Network and Combining Immune Cells to Evaluate Prognosis of Colon Cancer Patients |
title_sort |
constructing the cerna regulatory network and combining immune cells to evaluate prognosis of colon cancer patients |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Cell and Developmental Biology |
issn |
2296-634X |
publishDate |
2021-10-01 |
description |
Objective: This study was conducted in order to construct a competitive endogenous RNA (ceRNA) network to screen RNA that plays an important role in colon cancer and to construct a model to predict the prognosis of patients.Methods: The gene expression data of colon cancer were downloaded from the TCGA database. The difference was analyzed by the R software and the ceRNA network was constructed. The survival-related RNA was screened out by combining with clinical information, and the prognosis model was established by lasso regression. CIBERSORT was used to analyze the infiltration of immune cells in colon cancer, and the differential expression of immune cells related to survival was screened out by combining clinical information. The correlation between RNA and immune cells was analyzed by lasso regression. PCR was used to verify the expression of seven RNAs in colon cancer patients with different prognoses.Results: Two hundred and fifteen lncRNAs, 357 miRNAs, and 2,955 mRNAs were differentially expressed in colon cancer. The constructed ceRNA network contains 18 lncRNAs, 42 miRNAs, and 168 mRNAs, of which 18 RNAs are significantly related to survival. Through lasso analysis, we selected seven optimal RNA construction models. The AUC value of the model was greater than 0.7, and there was a significant difference in the survival rate between the high- and low-risk groups. Two kinds of immune cells related to the prognosis of patients were screened out. The results showed that the expression of seven RNA markers in colon cancer patients with different prognoses was basically consistent with the model analysis.Conclusion: We have established the regulatory network of ceRNA in colon cancer, screened out seven core RNAs and two kinds of immune cells, and constructed a comprehensive prognosis model of colon cancer patients. |
topic |
ceRNA regulatory network immune cells prognosis evaluation model colon cancer |
url |
https://www.frontiersin.org/articles/10.3389/fcell.2021.686844/full |
work_keys_str_mv |
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