ReviewBJC reports2025
B cells and tertiary lymphoid structures in cancer therapy response.
Review in BJC reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
27 citing papers in PubMed.
- Characterization of SPP1 + macrophages and their correlation with resistance to neoadjuvant chemotherapy in colorectal cancer liver metastasis.Molecular biomedicine · 2026Article
- IgM promotes antitumor immunity to a Tn-expressing solid tumor.Journal for immunotherapy of cancer · 2026Article
- B cells in cancer: functions, mechanisms and therapeutic advances.Signal transduction and targeted therapy · 2026Review
- STAID: A Self-Refining Deep Learning Framework for Spatial Cell-Type Deconvolution with Biologically Informed Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Beyond TLS Presence: A Functional Framework Integrating Maturity, Location, and Immune Context.Cancers · 2026Review
- Review
- ISPAT-3D: Spatially Varying Conditional Volumetric Network Estimation for 3D Tumor Imaging.Research square · 2026Article
- Regulatory B-cell states in NSCLC immunotherapy resistance: mechanisms, spatial context and translational implications.Cancer immunology, immunotherapy : CII · 2026Review
- ISPAT-3D: Spatially Varying Conditional Volumetric Network Estimation for 3D Tumor Imaging.bioRxiv : the preprint server for biology · 2026Article
- Precision oncology in the age of AI: lessons from AI-driven drug discovery and clinical translation.BJC reports · 2026Review
- From Immunobiology to Clinical Application: Tumor-Infiltrating Lymphocytes in Melanoma.Journal of personalized medicine · 2026Review
- Mesothelioma location influences the tumour microenvironment and immune checkpoint therapy response in preclinical models.Scientific reports · 2026Article
- Clinical and immunological significance of tertiary lymphoid structure maturation heterogeneity in brain metastases of lung adenocarcinoma.Journal of translational medicine · 2026Article
- Article
- The Role of B Cells in Tumorigenesis and Immunotherapy.Immune network · 2026Review
- The evolving role of the immune microenvironment of tumor draining lymph nodes in the development of biomarkers of non-small cell lung cancer.Frontiers in oncology · 2026Review
- Clinical impact and therapeutic potential of tertiary lymphoid structures in melanoma.Frontiers in immunology · 2026Review
- Metabolic Cross Talk in the Tumor Microenvironment.Cancer treatment and research · 2026Review
- Divergent CD45Frontiers in immunology · 2026Article
- The biological characteristics of tertiary lymphoid structures in head and neck cancer.Frontiers in immunology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent advances in immuno-oncology research have revolutionised our understanding of the interplay between immune cells and the tumour microenvironment (TME), profoundly impacting patient responses to therapy. The TME, comprising tumour cells, immune cells, extracellular matrix, stromal cells, and co-existing microbes, orchestrates the immune phenotype of cancers, shaping disease progression and treatment outcomes. Immune-cell infiltration serves as a significant prognostic marker in various cancers, with higher rates correlating with improved prognosis. Recent discoveries have paved the way for immune checkpoint blockade therapies, which exhibit remarkable efficacy across multiple cancer types. However, understanding the nuanced contributions of different immune-cell populations to therapeutic responses remains a challenge. The majority of research has focussed on the role of T cells in the immune response to cancer therapies, with the potential importance of B cells only recently being recognised. Here, we review the diverse phenotypes of B cells within the TME, their structural organisation within tertiary lymphoid structures (TLS), and the role of both B cells and TLS in cancer prognosis and response to different therapies for cancer treatment.
Identifiers
What OpenQuestion holds
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.