Prognostic model based on B cell marker genes for NSCLC patients under neoadjuvant immunotherapy by integrated analysis of single-cell and bulk RNA-sequencing data

• DOI: 10.1007/s12094-024-03428-1
• Publication Date: 2024-04-02T08:01:47Z
• Authors: Yang Liu; Fenglong Bie; Guangyu Bai; Qilin Huai; Yuan Li; Xiaowei Chen; Bolun Zhou; Shugeng Gao
• Keywords: Male; B-Lymphocytes; Lung Neoplasms; Sequence Analysis, RNA; Middle Aged; Prognosis; Neoadjuvant Therapy; Carcinoma, Non-Small-Cell Lung; Tumor Microenvironment; Biomarkers, Tumor; Humans; Female; Immunotherapy; Single-Cell Analysis; Aged

Neoadjuvant immunotherapy has evolved as an effective option to treat non-small cell lung cancer (NSCLC). B cells play essential roles in the immune system as well as cancer progression. However, the repertoire of B cells and its association with clinical outcomes remains unclear in NSCLC patients receiving neoadjuvant immunotherapy.Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data for LUAD samples were accessed from the TCGA and GEO databases. LUAD-related B cell marker genes were confirmed based on comprehensive analysis of scRNA-seq data. We then constructed the B cell marker gene signature (BCMGS) and validated it. In addition, we evaluated the association of BCGMS with tumor immune microenvironment (TIME) characteristics. Furthermore, we validated the efficacy of BCGMS in a cohort of NSCLC patients receiving neoadjuvant immunotherapy.A BCMGS was constructed based on the TCGA cohort and further validated in three independent GSE cohorts. In addition, the BCMGS was proven to be significantly associated with TIME characteristics. Moreover, a relatively higher risk score indicated poor clinical outcomes and a worse immune response among NSCLC patients receiving neoadjuvant immunotherapy.We constructed an 18-gene prognostic signature derived from B cell marker genes based on scRNA-seq data, which had the potential to predict the prognosis and immune response of NSCLC patients receiving neoadjuvant immunotherapy.