Single-cell and bulk transcriptome analysis identifies B-cell subpopulations and associated cancer subtypes with distinct clinical and molecular characteristics
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View abstract on PubMed
Summary
This summary is machine-generated.This study identifies eight distinct B cell subpopulations and their prognostic relevance in pan-cancer. These findings advance understanding of B cell heterogeneity and its impact on cancer outcomes and immunotherapy response.
Area Of Science
- Immunology
- Oncology
- Bioinformatics
Background
- B cell subpopulations exhibit pro- and anti-tumoral activities.
- Clinical relevance of B cell markers in pan-cancer is understudied.
Purpose Of The Study
- Identify and characterize B cell subpopulations in pan-cancer.
- Determine their prognostic and predictive value for cancer outcomes and immunotherapy response.
Main Methods
- Integrated 14 scRNA-seq datasets (102,504 cells, 424 patients, 15 cancer types) for unsupervised clustering.
- Analyzed functional dynamics, prognostic relevance, and spatial transcriptomic data.
- Developed predictive models using B cell subpopulation-specific gene signatures.
Main Results
- Identified eight B cell subpopulations (naive, plasma, memory, germinal center, cycling).
- Correlated specific subpopulations (b07-cycling, b04-GC) with negative prognosis and others (b02-naive) with positive prognosis.
- Developed models accurately predicting cancer survival and immunotherapy response using 13 gene signatures.
Conclusions
- Delineated eight B cell subpopulations with distinct prognostic relevance in pan-cancer.
- Signature-based stratification and models highlight clinical significance in cancer outcomes and therapy response.
- Advanced understanding of B cell heterogeneity in the tumor microenvironment.
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