Home LiteratureArticle Details
PMID: 33428592 Published · ppublish English

Identification of candidate genes encoding tumor-specific neoantigens in early- and late-stage colon adenocarcinoma.

Aging ·Vol. 13 ·No. 3 ·2021-00-10

Wang C, Xue W, Zhang H, Fu Y

Abstract

Colon adenocarcinoma (COAD) is one of the most common gastrointestinal malignant tumors and is characterized by a high mortality rate. Here, we integrated whole-exome and RNA sequencing data from The Cancer Genome Atlas and investigated the mutational spectra of COAD-overexpressed genes to define clinically relevant diagnostic/prognostic signatures and to unmask functional relationships with both tumor-infiltrating immune cells and regulatory miRNAs. We identified 24 recurrently mutated genes (frequency > 5%) encoding putative COAD-specific neoantigens. Five of them (NEB, DNAH2, ABCA12, CENPF and CELSR1) had not been previously reported as COAD biomarkers. Through machine learning-based feature selection, four early-stage-related (COL11A1, TG, SOX9, and DNAH2) and four late-stage-related (COL11A1, SOX9, TG and BRCA2) candidate neoantigen-encoding genes were selected as diagnostic signatures. They respectively showed 100% and 97% accuracy in predicting early- and late-stage patients, and an 8-gene signature had excellent prognostic performance predicting disease-free survival (DFS) in COAD patients. We also found significant correlations between the 24 candidate neoantigen genes and the abundance and/or activation status of 22 tumor-infiltrating immune cell types and 56 regulatory miRNAs. Our novel neoantigen-based signatures may improve diagnostic and prognostic accuracy and help design targeted immunotherapies for COAD treatment.

Keywords
colon adenocarcinoma machine learning neoantigens recurrent mutations sequencing
MeSH 主题词
Adenocarcinoma/diagnosis,genetics,immunology,pathology Antigens, Neoplasm/genetics,immunology Colonic Neoplasms/diagnosis,genetics,immunology,pathology Databases, Genetic Disease-Free Survival Female Humans Male Mutation Neoplasm Staging Prognosis Survival Rate
Article Info
Journal
Aging
Abbr.
Aging (Albany NY)
ISSN
1945-4589
Published
2021-00-10
Language
English
Country/Region
United States
NLM ID
101508617
Analysis Services
Analysis Services

Contact

No. 2 Wenbo Road, Zhangqiu District, Jinan, Shandong

Qilu Normal University · Genelibs Bioinformatics Lab

750 Shunhua Rd, Jinan

2F, Bldg F, University Science Park

Tel: 0531-88819269

WeChat Official Account

Follow our WeChat subscription account for real-time updates and the latest in medical and biological research.


Business Email

E-mail: product@genelibs.com