Identification of a Prognostic Signature Based on Tumor-Infiltrating B Lymphocyte mRNA in Head and Neck Squamous Cell Carcinoma

基于肿瘤浸润B淋巴细胞mRNA的头颈部鳞状细胞癌预后特征的鉴定

阅读:1

Abstract

Introduction: Tumor-infiltrating B cells (TILBs) are an important part of the immune response during tumor regulation. However, the significance of B cells in immunotherapy has not been fully determined. Methods: In this study, highly expressed genes in B cells were obtained by comparing the gene expression in B cells with that in other immune cells and were named TILB-mRNAs. Among them, those genes expressed in patients with head and neck squamous cell carcinoma (HNSCC) identified in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) atlas were employed to screen for genes associated with HNSCC prognosis using univariate Cox analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and a TILB-related signature was constructed to predict patient prognostic risk using multivariate Cox regression analyses. Results: The constructed TILB-related signature, which comprised seven mRNAs (ZNF439, KMO, KDM5D, IFT57, HDAC9, GSAP, and CCR7), was verified to have a good ability to predict the prognosis of patients with HNSCC using three independent validation datasets from GEO, and the predictive ability was not affected by other factors. The signature reflected the state of immune cell infiltration in tumor tissue, especially B cells, patients with higher risk scores (RSs) had fewer infiltrating immune cells in their tumors, especially B cells. The gene expression of the TILB-related signature was also verified in TILBs from HNSCC using single-cell analysis, revealing that TILB-related marker genes were differentially expressed in different GB cell subsets. Discussion: This study provides risk assessment and outcome prediction for patients with HNSCC and provides potential targets for immunotherapy of HNSCC.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。