Abstract PR003: T cell receptor repertoire and diversity are prognostic markers in bladder cancer
Bibliographic record
Abstract
Abstract T cells represent essential effector cells in the intrinsic antitumor immune response. Cancer-specific T cells can recognize cancer neoantigens through their T cell receptors (TCRs). The expansion of these clones is believed to be an early response to malignancy. We hypothesized that the T cell landscape offers insights into immune competency. We aimed to characterize the TCR repertoire in patients with bladder cancer and explore correlations with disease outcomes. We analyzed the TCR landscape in a cohort of 119 patients with muscle-invasive bladder cancer (MIBC) treated with chemotherapy followed by radical cystectomy. Peripheral and tumor TCR repertoires were produced using ultradeep amplicon-based sequencing of the TCR beta chain. T cell fractions were inferred from whole exome sequencing data of blood DNA using TcellExTRECT. Latent viral DNA was investigated in plasma whole genome sequencing data using Kraken2. Antigen targets were estimated using GLIPH2. The T cell subtype compositions in tumor and blood were investigated in four patients with bladder cancer using the Chromium Single Cell Immune profiling kit from 10X Genomics. Low pre-treatment peripheral TCR diversity was associated with worse overall survival (HR = 2.3, p = 0.024, n = 119) in patients with MIBC, particularly when combined with a low fraction of circulating T cells (HR= 4.7, p = 0.00049, n = 67). We validated these findings in two independent cohorts of patients with MIBC (p = 0.01, n = 107; p = 0.042, n = 79). The low-diversity TCR repertoires were characterized by large expanded T cell clones that persisted over time. Longitudinal analysis indicated a potential adverse impact of treatment, evidenced by a reduction in TCR diversity and circulating T cells over time in patients with initially high-diversity repertoires. TCR target annotation revealed that expanded T cell clones disproportionately targeted latent viral infections and cytomegalovirus DNA detection was strongly associated with low TCR diversity (p = 5.3 × 10−5). We observed a notable disparity between tumor and peripheral blood TCR repertoires. Single-cell sequencing revealed that regulatory T cells were prevalent in the tumor, whereas a combination of cytotoxic and naïve T cells dominated the blood. More explicitly, expanded clones in the blood were commonly annotated as terminally differentiated effector memory T cells expressing high levels of cytotoxic and exhausted genes. Our results suggest that high peripheral TCR diversity and high T cell fraction are markers of general immune competence, reflecting the ability to eradicate cancer and other diseases. In contrast, the expanded persistent clones predominating the low peripheral TCR diversity repertoires are likely exhausted and less likely to exhibit tumor specificity or effective disease-fighting capabilities. Our findings underline the crucial role of the immune system in determining disease outcomes and highlight the potential for improving immune health as a promising approach for future treatment and prevention. Citation Format: Nanna Kristjánsdóttir, Asbjørn Kjær, Iver Nordentoft, Randi I Juul, Karin Birkenkamp-Demtröder, Johanne Ahrenfeldt, Trine Strandgaard, Deema Radif, Darren Hodgson, Christopher Abbosh, Hugo JWL Aerts, Mads Agerbæk, Jørgen B Jensen, Nicolai J. Birkbak, Lars Dyrskjøt. T cell receptor repertoire and diversity are prognostic markers in bladder cancer [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr PR003.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".