Abstract 6475: Characterizing peri-tumoral tertiary lymphoid structures in non-muscle invasive bladder cancer using a spatial whole transcriptomics approach
Bibliographic record
Abstract
Abstract Background: Intravesical Bacillus Calmette-Guérin (BCG) immunotherapy is the gold standard for high-risk NMIBC, however over half of patients experience early recurrence or disease progression, highlighting the need for reliable predictive biomarkers. Our previous research identified that B cell dominant peri-tumoral tertiary lymphoid structures (TLSs) evolve during chronic carcinogenesis in a subset of patients who experience early recurrence or progression. TLSs generally correlate with favorable outcomes following treatment with immune checkpoint inhibitors, chemotherapy or oncolytic viruses. In contrast, their abundance in peri-tumoral regions in BCG-naïve NMIBC tumors associates with poor prognosis. This highlights the importance of their in-depth characterization and further exploring their biomarker potential in NMIBC. Methods: Peri-tumoral TLSs and tumor epithelial regions were profiled using the NanoString GeoMx Digital Spatial Profiler based whole transcriptome analysis. Multiplex Immunofluorescence was performed to infer spatial profiles of B, T and myeloid cell functional states as well as immune checkpoint proteins. Results: Spatial whole transcriptome analysis displayed increased expression of genes associated with antigen presentation, complement activation, B cell recruiting chemokines, and immunoglobulins in the TLSs regions. Tumor epithelial regions located adjacent to TLSs showed elevated expression of genes reflective of a luminal subtype. Increased PD-1+ cells in the peri-tumoral regions and enrichment of luminal subtype genes in the epithelial compartment indicated cancer cell intrinsic aggressive features associated with immune exclusion. Conclusion: The novel findings from this study will help establish peri-tumoral TLSs as biomarkers for predicting BCG therapy response, enabling early identification of patients who may benefit from alternative immunomodulatory treatments like oncolytic viruses, gemcitabine-docetaxel chemotherapy, or immune checkpoint inhibitors. Citation Format: Kartik Sachdeva. Characterizing peri-tumoral tertiary lymphoid structures in non-muscle invasive bladder cancer using a spatial whole transcriptomics approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6475.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".