WeChat Mini Program
Old Version Features

Development and Validation of a MUC16 Mutation-Associated Immune Prognostic Model for Lung Adenocarcinoma

Aging(2023)

Xi An Jiao Tong Univ | AF Mil Med Univ

Cited 0|Views17
Abstract
Mucin 16 (MUC16) mutation ranks third among all common mutations in lung adenocarcinoma (LUAD), and it has a certain effect on LUAD development and prognostic outcome. This research aimed to analyze the effects of MUC16 mutation on LUAD immunophenotype regulation and determine the prognostic outcome using an immune prognostic model (IPM) built with immune-related genes. The MUC16 mutation status and mRNA expression profiles were analyzed using diverse platforms and among several LUAD patients (n = 691). An IPM was then constructed using differentially expressed immune-related genes (DEIRGs) in MUC16MUT LUAD cases, and the data were compared with those of MUC16WT LUAD cases. The IPM's performance in distinguishing high-risk cases from low-risk ones among 691 LUAD cases was verified. Additionally, a nomogram was built and applied in the clinical setting. Furthermore, a comprehensive IPM-based analysis of how MUC16 mutation affected the tumor immune microenvironment (TIME) of LUAD was performed. MUC16 mutation decreased the immune response in LUAD. As revealed by functional annotation, the DEIRGs in the IPM were most significantly enriched in the humoral immune response function and the immune system disease pathway. Moreover, high-risk cases were associated with increased proportions of immature dendritic cells, neutrophils, and B-cells; enhanced type I interferon T-cell response; and increased expression of PD-1, CTLA-4, TIM-3, and LAG3 when compared with low-risk cases. MUC16 mutation shows potent association with TIME of LUAD. The as-constructed IPM displays high sensitivity to MUC16 mutation status and can be applied to discriminate high-risk LUAD cases from low-risk ones.
More
Translated text
Key words
MUC16,lung adenocarcinoma,immune prognostic model,prognosis,signature
PDF
Bibtex
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined