Abstract PR-08: Impact of gut microbiota on response to Bacillus Calmette-Guérin immunotherapy in bladder cancer: Towards a predictive molecular model
Bibliographic record
Abstract
Abstract Objectives: Bladder cancer is the fifth most frequently diagnosed cancer in Canada. Approximately 75% of cases are non-muscle invasive bladder cancer (NMIBC). Treatment of high-risk NMIBC involves transurethral tumor resection followed by intravesical immunotherapy with Bacillus Calmette-Guerin (BCG) instillations. Unfortunately, 40% of patients relapse within five years. Several studies showed that gut microbiota influence immunotherapy response and identified specific bacteria capable of improving systemic immunotherapy effectiveness in a variety of cancers. However, it is still unknown whether these bacteria also play a role in BCG response. Methods and Results: We performed metagenomic analyses on fecal DNA from 58 NMIBC patients collected before their BCG treatment to catalog gut microbiota composition. We first tested the TOPOSCORE, a gut microbiota-based predictive model for systemic immunotherapy response validated in various cancers (Derosa et al., Cell 2024). Although this predictive score identifies 100% of BCG non-responders (NR), it showed low specificity (57%) in predicting BCG response. Our preliminary data suggest that 50% of the NR bacteria are associated with antibiotic resistance. In parallel, we found a unique microbiota signature linked to BCG response using whole-genome sequencing. Several BCG response-associated bacterial species (RABS) were uniquely associated with improved recurrence-free survival of NMIBC patients. These RABS appear to harbor no antibiotic resistance genes, making them promising candidates as probiotic adjuvants to BCG therapy in bladder cancer. Conclusion: Our results suggest that gut microbiota associated with non-response to systemic immunotherapy is similar to that of BCG non-responders in NMIBC, while the bacteria linked to BCG response differ. Our current research aims to develop a unique predictive molecular test based on the microbiota signature of NMIBC patients, which will predict clinical response to BCG and optimize the patient care. Moreover, RABS identification supports the development of a BCG adjuvant treatment via a probiotic supplementation to improve BCG response. Citation Format: Marine Boireau, Jalal Laaraj, Gabriel Lachance, Roxane Tourigny, Sandra Isabel, Yves Fradet, Karine Robitaille, Vincent Fradet. Impact of gut microbiota on response to Bacillus Calmette-Guérin immunotherapy in bladder cancer: Towards a predictive molecular model [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Mechanisms of Cancer Immunity and Cancer-related Autoimmunity; 2025 Sep 24-27; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(9 Suppl):Abstract nr PR-08.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".