Abstract A015: The emerging role of basophils in non-muscle-invasive bladder cancer
Bibliographic record
Abstract
Abstract Non-muscle-invasive bladder cancer (NMIBC) is characterized by a high recurrence rate (>40 %) despite transurethral resection and intravesical BCG immunotherapy, underscoring the urgent need for novel prognostic biomarkers. In our retrospective multicentre study, we identified circulating basophils as independent predictive factors for both recurrence (HR = 1.9; p = 0.010) and tumor progression (HR = 2.3; p = 0.020). Beyond their established role in inflammation, increased circulating basophil counts may reflect an immunosuppressive state, potentially associated with a less effective response to BCG treatment. We hypothesize that basophil expansion signals systemic immune dysregulation, ultimately facilitating tumor recurrence. To test this, our project combines: (1) detailed characterization of activation profiles in both circulating and tumor-associated basophils, and (2) investigation of their interactions with tumor cells to clarify their impact on the tumor microenvironment (TME). Flow cytometry analysis of 60 NMIBC patients revealed significantly increased granzyme B expression in circulating basophils compared to healthy controls (p = 0.0008), as well as a trend toward higher levels of interleukin (IL)-4 and IL-13. These findings suggest a paradox where granzyme B, typically associated with antitumoral responses, may instead promote immune evasion and tissue invasion in this context. To further explore recruitment to the tumor site, urine-based immune profiling showed that basophils, although typically rare, represented an average of 8 % of urinary immune cells in NMIBC patients, with an increasing trend in newly diagnosed patients who subsequently experienced recurrence. In parallel, in vitro co-culture models demonstrated that tumor cell-activated basophils selectively inhibited helper T cell proliferation (-30 %; p = 0.004) without affecting cytotoxic T cells, highlighting their potential immunosuppressive role within the TME. Our findings position basophils as key mediators of BCG resistance and accessible blood-based biomarkers for stratifying risk in high-risk NMIBC patients. These results open avenues for personalized risk assessment and optimized therapeutic strategies. Citation Format: Geneviève Trépanire, Typhaine Gris, Paul Toren. The emerging role of basophils in non-muscle-invasive bladder cancer [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 A015.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".