Atypical B cells mediate poor response to Bacillus Calmette Guérin immunotherapy in non-muscle invasive bladder cancer
Bibliographic record
Abstract
Abstract Poor response to Bacillus Calmette-Guérin (BCG) immunotherapy remains a major barrier in the management of patients with non-muscle-invasive bladder cancer (NMIBC). Among the multiple factors contributing to poor outcomes, a B cell infiltrated pre-treatment immune microenvironment of NMIBC tumors has emerged as a key determinant of response to BCG. The mechanisms underlying the paradoxical roles of B cells in NMIBC are poorly understood. Here, we show that B cell dominant tertiary lymphoid structures (TLSs), a hallmark feature of chronic mucosal immune response, are abundant and located close to the epithelial compartment in pre-treatment tumors from BCG non-responders. Digital spatial proteomic profiling of whole tumor sections revealed higher expression of immune exhaustion-associated proteins within the TLSs from both responders and non-responders. Chronic local inflammation, induced by the N-butyl- N-(4-hydroxybutyl) nitrosamine (BBN) carcinogen, led to TLS formation with recruitment and differentiation of the immunosuppressive atypical B cell (ABCs) subset within the bladder microenvironment, predominantly in aging female mice compared to their male counterparts. Depletion of ABCs simultaneous to BCG treatment delayed cancer progression in female mice. Our findings provide the first evidence indicating the role of ABCs in BCG response and will inform future development of therapies targeting the B cell exhaustion axis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".