Cargando…
A Novel Prognostic Model of Early-Stage Lung Adenocarcinoma Integrating Methylation and Immune Biomarkers
Lung adenocarcinoma (LUAD) is caused by multiple biological factors. Therefore, it will be more meaningful to study the prognosis from the perspective of omics integration. Given the significance of epigenetic modification and immunity in tumorigenesis and development, we tried to combine aberrant m...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7859522/ https://www.ncbi.nlm.nih.gov/pubmed/33552145 http://dx.doi.org/10.3389/fgene.2020.634634 |
_version_ | 1783646753224916992 |
---|---|
author | Ren, Jin Yang, Yun Li, Chuanyin Xie, Lu Hu, Ronggui Qin, Xiong Zhang, Menghuan |
author_facet | Ren, Jin Yang, Yun Li, Chuanyin Xie, Lu Hu, Ronggui Qin, Xiong Zhang, Menghuan |
author_sort | Ren, Jin |
collection | PubMed |
description | Lung adenocarcinoma (LUAD) is caused by multiple biological factors. Therefore, it will be more meaningful to study the prognosis from the perspective of omics integration. Given the significance of epigenetic modification and immunity in tumorigenesis and development, we tried to combine aberrant methylation and tumor infiltration CD8 T cell-related genes to build a prognostic model, to explore the key biomarkers of early-stage LUAD. On the basis of RNA-seq and methylation microarray data downloaded from The Cancer Genome Atlas (TCGA), differentially expressed genes and aberrant methylated genes were calculated with “DEseq2” and “ChAMP” packages, respectively. A Chi-square test was performed to obtain methylation driver genes. Weighted correlation network analysis (WGCNA) was utilized to mine cancer biomarkers related to CD8 T cells. With the consequences of univariate Cox proportional hazards analysis and least absolute shrinkage and selection operator (LASSO) COX regression analysis, the prognostic index based on 17 methylation driver genes (ZNF677, FAM83A, TRIM58, CLDN6, NKD1, NFE2L3, FKBP5, ITGA5, ASCL2, SLC24A4, WNT3A, TMEM171, PTPRH, ITPKB, ITGA2, SLC6A17, and CCDC81) and four CD8 T cell-related genes (SPDL1, E2F7, TK1, and TYMS) was successfully established, which could make valuable predictions for the survival risk of patients with early-stage LUAD. |
format | Online Article Text |
id | pubmed-7859522 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78595222021-02-05 A Novel Prognostic Model of Early-Stage Lung Adenocarcinoma Integrating Methylation and Immune Biomarkers Ren, Jin Yang, Yun Li, Chuanyin Xie, Lu Hu, Ronggui Qin, Xiong Zhang, Menghuan Front Genet Genetics Lung adenocarcinoma (LUAD) is caused by multiple biological factors. Therefore, it will be more meaningful to study the prognosis from the perspective of omics integration. Given the significance of epigenetic modification and immunity in tumorigenesis and development, we tried to combine aberrant methylation and tumor infiltration CD8 T cell-related genes to build a prognostic model, to explore the key biomarkers of early-stage LUAD. On the basis of RNA-seq and methylation microarray data downloaded from The Cancer Genome Atlas (TCGA), differentially expressed genes and aberrant methylated genes were calculated with “DEseq2” and “ChAMP” packages, respectively. A Chi-square test was performed to obtain methylation driver genes. Weighted correlation network analysis (WGCNA) was utilized to mine cancer biomarkers related to CD8 T cells. With the consequences of univariate Cox proportional hazards analysis and least absolute shrinkage and selection operator (LASSO) COX regression analysis, the prognostic index based on 17 methylation driver genes (ZNF677, FAM83A, TRIM58, CLDN6, NKD1, NFE2L3, FKBP5, ITGA5, ASCL2, SLC24A4, WNT3A, TMEM171, PTPRH, ITPKB, ITGA2, SLC6A17, and CCDC81) and four CD8 T cell-related genes (SPDL1, E2F7, TK1, and TYMS) was successfully established, which could make valuable predictions for the survival risk of patients with early-stage LUAD. Frontiers Media S.A. 2021-01-21 /pmc/articles/PMC7859522/ /pubmed/33552145 http://dx.doi.org/10.3389/fgene.2020.634634 Text en Copyright © 2021 Ren, Yang, Li, Xie, Hu, Qin and Zhang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Ren, Jin Yang, Yun Li, Chuanyin Xie, Lu Hu, Ronggui Qin, Xiong Zhang, Menghuan A Novel Prognostic Model of Early-Stage Lung Adenocarcinoma Integrating Methylation and Immune Biomarkers |
title | A Novel Prognostic Model of Early-Stage Lung Adenocarcinoma Integrating Methylation and Immune Biomarkers |
title_full | A Novel Prognostic Model of Early-Stage Lung Adenocarcinoma Integrating Methylation and Immune Biomarkers |
title_fullStr | A Novel Prognostic Model of Early-Stage Lung Adenocarcinoma Integrating Methylation and Immune Biomarkers |
title_full_unstemmed | A Novel Prognostic Model of Early-Stage Lung Adenocarcinoma Integrating Methylation and Immune Biomarkers |
title_short | A Novel Prognostic Model of Early-Stage Lung Adenocarcinoma Integrating Methylation and Immune Biomarkers |
title_sort | novel prognostic model of early-stage lung adenocarcinoma integrating methylation and immune biomarkers |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7859522/ https://www.ncbi.nlm.nih.gov/pubmed/33552145 http://dx.doi.org/10.3389/fgene.2020.634634 |
work_keys_str_mv | AT renjin anovelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT yangyun anovelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT lichuanyin anovelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT xielu anovelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT huronggui anovelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT qinxiong anovelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT zhangmenghuan anovelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT renjin novelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT yangyun novelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT lichuanyin novelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT xielu novelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT huronggui novelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT qinxiong novelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers AT zhangmenghuan novelprognosticmodelofearlystagelungadenocarcinomaintegratingmethylationandimmunebiomarkers |