已发表论文

B 细胞受体信号通路突变通过生物信息学分析作为肺腺癌免疫检查点抑制剂的预后预测因子

 

Authors Lin A, Fang J, Cheng Q , Liu Z, Luo P , Zhang J

Received 17 June 2022

Accepted for publication 29 August 2022

Published 23 September 2022 Volume 2022:15 Pages 5541—5555

DOI https://doi.org/10.2147/JIR.S379016

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Ning Quan

Purpose: The advent of immune checkpoint inhibitors (ICIs) is a revolutionary breakthrough. However, without the selection of a specific target population, the response rate of ICI therapy in lung adenocarcinoma (LUAD) is low, so a clinical challenge has arisen in effectively using biomarkers to determine which patients can benefit from ICI therapy.
Methods: In this study, patients were divided according to whether or not nonsynonymous mutations were present in the BCR signaling pathway, and univariate and multivariate Cox regression models were established based on a LUAD cohort treated with ICIs (Miao-LUAD). Then the relationship between the mutation status of the BCR signaling pathway and the prognosis of immunotherapy was examined. Finally, data from The Cancer Genome Atlas (TCGA) LUAD cohort, the Rizvi-LUAD, the Samstein-LUAD, and the Zhujiang Hospital of Southern Medical University LUAD (Local-LUAD) cohort were combined, and the mutation panorama, immunogenicity, tumor microenvironment (TME) and pathway enrichment analysis between the BCR signaling pathway mutant group (BCR signaling MUT) and the BCR signaling pathway wild group (BCR signaling WT) were comprehensively compared.
Results: It was found that, compared with the BCR signaling WT, the BCR signaling MUT had a significantly improved progression-free survival (PFS) rate and overall survival (OS) rate, higher immunogenicity (tumor mutational burden, neoantigen load, and DNA damage response signaling mutations), and anti-tumor immune microenvironment.
Conclusion: These results revealed that the mutation state of the BCR signaling pathway has potential as a biomarker to predict the efficacy of ICIs in LUAD.
Keywords: non-small cell lung cancer, B cell receptor, immune checkpoint inhibitor, biomarker, microenvironment