Frontiers in ImmunologyImmunologyPeer-reviewed journal article
FCRLs and atypical transcriptional pattern in tumor infiltrating B cells from lung and renal cancer
Ekaterina A. BryushkovaiD, Evgenii V. Shchoka, Daniil K. LukyanoviD, Marina Gikalo, Nataliya V. MushenkovaiD, Константин Константинович ЛактионовiD, Aleksey M. KazakoviD, Oybek KhalmurzaeviD, Vsevolod Borisovich MatveeviD, Dmitriy M. ChudakoviD, Ekaterina O. SerebrovskayaiD
Abstract
Advances in high-dimensional flow cytometry and single-cell RNA sequencing (scRNA-seq) have enhanced our understanding of the heterogeneity of tumor-infiltrating B cells (TIBs). Subpopulations of TIBs exhibit diverse, sometimes opposing roles in tumor control, influenced by surface molecule, cytokine, and transcription factor expression. IgA and IgG expression in tumors have shown predictive value in melanoma and KRAS-mutated, but not KRAS wild-type, lung adenocarcinoma (LUAD). To investigate the functional differences between B cells producing these isotypes, we performed bulk transcriptome analysis of tumor-infiltrating surface-IgA+ (sIgA+) and sIgG+ memory B cells in LUAD. In LUAD, sIgA+ B cells overexpressed FCRL4, PDCD1, and RUNX2, suggesting an atypical chronically antigen-stimulated phenotype with features of exhaustion. Public scRNA-seq data revealed FCRL4-expressing TIBs as a distinct cluster with upregulation of genes involved in IFN{gamma} and IFN responses. sIgG+ B cells from LUAD overexpressed IL5RA, indicating a role for IL-5 in class-switch recombination to IgG. TCGA LUAD cohort analysis showed that the FCRL4/CD20 expression ratio correlates with lower survival, reinforcing FCRL4 as a marker of dysfunctional TIBs. Additionally, in renal cancer, high IGHA1/IGHG1 ratios were linked to worse survival. These findings suggest that the IgA/IgG ratio in tumors reflects not only the TME cytokine environment, but also functional differences in B cell populations, providing insights into their diverse roles in tumor progression.
- organism: human
- assay: bulk RNA-seq
- assay: scRNA-seq
- research focus: differential expression
- research focus: cell type annotation
- approach: statistical model
- Citations
- 1
- FWCI
- 0.37
- Field percentile
- top 42%
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