ArticleFrontiers in immunology2023
Single-cell and bulk RNA sequencing analysis of B cell marker genes in TNBC TME landscape and immunotherapy.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- PD-1/PD-L1 immune checkpoint blockade in breast cancer: research insights and sensitization strategies.Molecular cancer · 2024Pooled it
- MIF-mediated intercellular crosstalk drives antigen-presenting-like cancer-associated fibroblast differentiation in triple-negative breast cancer via TGF-β signaling.Translational cancer research · 2026Article
- Dual Immunological Prognostic Models for Risk Stratification and Treatment Insights in Triple-Negative Breast Cancer.International journal of molecular sciences · 2026Article
- A Case-Driven Multi-Omics Analysis for Longitudinal Ibrutinib Response Evaluation of Patients With Chronic Lymphocytic Leukemia.European journal of haematology · 2025Article
- Tumor Microenvironment Dynamics of Triple-Negative Breast Cancer Under Radiation Therapy.International journal of molecular sciences · 2025Review
- Analysis of single-cell and spatial transcriptomics in TNBC cell-cell interactions.Frontiers in immunology · 2025Review
- Development of oxidative stress- and ferroptosis-related prognostic signature in gastric cancer and identification of CDH19 as a novel biomarker.Human genomics · 2024Article
- Hyper-N-glycosylated SEL1L3 as auto-antigenic B-cell receptor target of primary vitreoretinal lymphomas.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study amied to investigate the prognostic characteristics of triple negative breast cancer (TNBC) patients by analyzing B cell marker genes based on single-cell and bulk RNA sequencing. Methods: Utilizing single-cell sequencing data from TNBC patients, we examined tumor-associated B cell marker genes. Transcriptomic data from The Cancer Genome Atlas (TCGA) database were used as the foundation for predictive modeling. Independent validation set was conducted using the GSE58812 dataset. Immune cell infiltration into the tumor was assessed through various, including XCELL, TIMER, QUANTISEQ, CIBERSORT, CIBERSORT-ABS, and ssGSEA. The TIDE score was utilized to predict immunotherapy outcomes. Additional investigations were conducted on the immune checkpoint blockade gene, tumor mutational load, and the GSEA enrichment analysis. Results: Our analysis encompassed 22,106 cells and 20,556 genes in cancerous tissue samples from four TNBC patients, resulting in the identification of 116 B cell marker genes. A B cell marker gene score (BCMG score) involving nine B cell marker genes ( Conclusion: This study has established a robust model based on B-cell marker genes in TNBC, which holds significant potential for predicting prognosis and response to immunotherapy in TNBC patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.