Abstract 609: The predictive power of tertiary lymphoid structures in assessing response to trimodal therapy in muscle invasive bladder cancer
Bibliographic record
Abstract
Abstract Introduction: Radical cystectomy is the standard of care for muscle invasive bladder cancer (MIBC). Radiotherapy (RT) is a bladder preserving option that offers patients comparable survival rates. However, up to 30% of patients require salvage cystectomy. Emerging evidence points to an important yet poorly understood link between response to RT and the tumor microenvironment (TME). Notably, tertiary lymphoid structures (TLS) are being investigated as a potential local hub for mounting an immune response. These lymph-node-like structures are highly organized with a B cell zone surrounded by T cells. Mature TLS also have an active germinal center (GC) with follicular dendritic cells. A number of studies correlated TLS with improved outcomes in several types of solid cancers. Here, we explore the use of TLS and its associated immune TME as a predictive biomarker for response to RT in MIBC. Methods: Hematoxylin and Eosin (H&E) stained formalin-fixed-paraffin-embedded sections of pre-RT biopsy from 147 MIBC patients were examined to identify TLS presence with confirmation from a pathologist. Subsequent multiplex immunohistochemistry (mIHC) staining with CD21 and CD23 characterized TLS maturity. To investigate the interaction between TLS and TME, tissue microarrays (TMAs) were constructed, and gene expression profiles were obtained for 106 patients using NanoString’s Digital Spatial technology. Moreover, the TMAs were stained with CD20, Neutrophil Elastase, CD68, CD8, CD4, and FoxP3 by mIHC. Image analysis was performed on the Halo platform. TLS gene signature was correlated to the immune infiltration and the patient outcomes. Results: H&E revealed that 19.7% of patients (n=68) had TLS with a GC, 17.0% (n=25) had TLS without a GC, and 12.9% (n=19) had no TLS. In the remaining 50.3% of cases (n=74), confirmation of TLS presence required staining with CD3 and CD20. Gene expression of TLS marker CXCL13 was higher among complete responders to RT (p-value=0.0440). This trend was weakened when we examined a previously described 12-chemokine TLS signature (p= 0.1506). When segregating patients into TLS high/TLS low groups based on the gene signature, we observed significantly higher infiltration of CD8+ T cells (p<0.0001), neutrophils (p=0.005), regulatory T cells (p=0.0278), and B cells (p=0.0247) among the TLS high group. No difference in macrophage infiltration was observed between the two groups.Conclusion: Our results point to a nuanced role of TLS in the context of response to RT and in relation to the TME. Further histological analysis of TLS characteristics is necessary to paint a picture of the different immune profiles we observe in our cohort and their association with the outcomes of RT. Overall, our study could identify an immune signature that could serve as a selection criterion for patients who would benefit the most from bladder-sparing therapies. Citation Format: Nour Hassan, José Joao Mansure, Mina Farag, Ronald Kool, Eva Michaud, Mohanned Alessa, Luis Souhami, Fabio Cury, Fadi Brimo, Wassim Kassouf. The predictive power of tertiary lymphoid structures in assessing response to trimodal therapy in muscle invasive bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 609.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".