5mC-Related lncRNAs as Potential Prognostic Biomarkers in Colon Adenocarcinoma

Globally, colon adenocarcinoma (COAD) is one of the most frequent types of malignant tumors. About 40~50% of patients with advanced colon adenocarcinoma die from recurrence and metastasis. Long non-coding RNAs (lncRNAs) and 5-methylcytosine (5mC) regulatory genes have been demonstrated to involve in...

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Main Authors: Yinghui Huang, Huiqian Huang, Yong Wang, Hui Liu, Yingdan Huang
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Biology
Subjects:
Online Access:https://www.mdpi.com/2079-7737/11/2/231
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author Yinghui Huang
Huiqian Huang
Yong Wang
Hui Liu
Yingdan Huang
author_facet Yinghui Huang
Huiqian Huang
Yong Wang
Hui Liu
Yingdan Huang
author_sort Yinghui Huang
collection DOAJ
description Globally, colon adenocarcinoma (COAD) is one of the most frequent types of malignant tumors. About 40~50% of patients with advanced colon adenocarcinoma die from recurrence and metastasis. Long non-coding RNAs (lncRNAs) and 5-methylcytosine (5mC) regulatory genes have been demonstrated to involve in the progression and prognosis of COAD. The goal of this study was to explore the biological characteristics and potential predictive value of 5mC-related lncRNA signature in COAD. In this research, The Cancer Genome Atlas (TCGA) was utilized to obtain the expression of genes and somatic mutations in COAD, and Pearson correlation analysis was used to select lncRNAs involved in 5mC-regulated genes. Furthermore, we applied univariate Cox regression and Lasso Cox regression to construct 5mC-related lncRNA signature. Then Kaplan–Meier survival analysis, principal components analysis (PCA), receiver operating characteristic (ROC) curve, and a nomogram were performed to estimate the prognostic effect of the risk signature. GSEA was utilized to predict downstream access of the risk signature. Finally, the immune characteristics and immunotherapeutic signatures targeting this risk signature were analyzed. In the results, we obtained 1652 5mC-related lncRNAs by Pearson correlation analysis in the TCGA database. Next, we selected a risk signature that comprised 4 5mC-related lncRNAs by univariate and Lasso Cox regression. The prognostic value of the risk signature was proven. Finally, the biological mechanism and potential immunotherapeutic response of the risk signature were identified. Collectively, we constructed the 5mC-related lncRNA risk signature, which could provide a novel prognostic prediction of COAD patients.
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spelling doaj.art-683990b38db34bdcb900cf14223704f02023-11-23T18:50:04ZengMDPI AGBiology2079-77372022-02-0111223110.3390/biology110202315mC-Related lncRNAs as Potential Prognostic Biomarkers in Colon AdenocarcinomaYinghui Huang0Huiqian Huang1Yong Wang2Hui Liu3Yingdan Huang4Key Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan 430056, ChinaNational Research Center of Cultural Industries, Central China Normal University, Wuhan 430056, ChinaDepartment of Medical Oncology, The First Affiliated Hospital of Nanchang University, 17 YongwaiZhengRoad, Nanchang 330209, ChinaKey Laboratory of Adolescent Cyberpsychology and Behavior, Ministry of Education, Wuhan 430056, ChinaDepartment of Lymphoma Medicine, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430079, ChinaGlobally, colon adenocarcinoma (COAD) is one of the most frequent types of malignant tumors. About 40~50% of patients with advanced colon adenocarcinoma die from recurrence and metastasis. Long non-coding RNAs (lncRNAs) and 5-methylcytosine (5mC) regulatory genes have been demonstrated to involve in the progression and prognosis of COAD. The goal of this study was to explore the biological characteristics and potential predictive value of 5mC-related lncRNA signature in COAD. In this research, The Cancer Genome Atlas (TCGA) was utilized to obtain the expression of genes and somatic mutations in COAD, and Pearson correlation analysis was used to select lncRNAs involved in 5mC-regulated genes. Furthermore, we applied univariate Cox regression and Lasso Cox regression to construct 5mC-related lncRNA signature. Then Kaplan–Meier survival analysis, principal components analysis (PCA), receiver operating characteristic (ROC) curve, and a nomogram were performed to estimate the prognostic effect of the risk signature. GSEA was utilized to predict downstream access of the risk signature. Finally, the immune characteristics and immunotherapeutic signatures targeting this risk signature were analyzed. In the results, we obtained 1652 5mC-related lncRNAs by Pearson correlation analysis in the TCGA database. Next, we selected a risk signature that comprised 4 5mC-related lncRNAs by univariate and Lasso Cox regression. The prognostic value of the risk signature was proven. Finally, the biological mechanism and potential immunotherapeutic response of the risk signature were identified. Collectively, we constructed the 5mC-related lncRNA risk signature, which could provide a novel prognostic prediction of COAD patients.https://www.mdpi.com/2079-7737/11/2/2315-methylcytosinecolon adenocarcinomalncRNA signatureprognosisimmunotherapy
spellingShingle Yinghui Huang
Huiqian Huang
Yong Wang
Hui Liu
Yingdan Huang
5mC-Related lncRNAs as Potential Prognostic Biomarkers in Colon Adenocarcinoma
Biology
5-methylcytosine
colon adenocarcinoma
lncRNA signature
prognosis
immunotherapy
title 5mC-Related lncRNAs as Potential Prognostic Biomarkers in Colon Adenocarcinoma
title_full 5mC-Related lncRNAs as Potential Prognostic Biomarkers in Colon Adenocarcinoma
title_fullStr 5mC-Related lncRNAs as Potential Prognostic Biomarkers in Colon Adenocarcinoma
title_full_unstemmed 5mC-Related lncRNAs as Potential Prognostic Biomarkers in Colon Adenocarcinoma
title_short 5mC-Related lncRNAs as Potential Prognostic Biomarkers in Colon Adenocarcinoma
title_sort 5mc related lncrnas as potential prognostic biomarkers in colon adenocarcinoma
topic 5-methylcytosine
colon adenocarcinoma
lncRNA signature
prognosis
immunotherapy
url https://www.mdpi.com/2079-7737/11/2/231
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AT huiqianhuang 5mcrelatedlncrnasaspotentialprognosticbiomarkersincolonadenocarcinoma
AT yongwang 5mcrelatedlncrnasaspotentialprognosticbiomarkersincolonadenocarcinoma
AT huiliu 5mcrelatedlncrnasaspotentialprognosticbiomarkersincolonadenocarcinoma
AT yingdanhuang 5mcrelatedlncrnasaspotentialprognosticbiomarkersincolonadenocarcinoma