MétaCan
Menu
Back to cohort
Record W4409995180 · doi:10.1016/j.xcrm.2025.102101

Low T cell diversity associates with poor outcome in bladder cancer: A comprehensive longitudinal analysis of the T cell receptor repertoire

2025· article· en· W4409995180 on OpenAlexaff
Asbjørn Kjær, Nanna Kristjánsdóttir, Randi Istrup Juul, Iver Nordentoft, Karin Birkenkamp‐Demtröder, Johanne Ahrenfeldt, Trine Strandgaard, Deema Radif, Darren Hodgson, Christopher Abbosh, Hugo J.W.L. Aerts, Mads Agerbæk, Jørgen Bjerggaard Jensen, Nicolai J. Birkbak, Lars Dyrskjøt

Bibliographic record

VenueCell Reports Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersLundbeckfondenAarhus Universitets ForskningsfondNovo Nordisk FondenKræftens BekæmpelseAarhus UniversitetAstraZeneca
KeywordsT-cell receptorImmunotherapyBiologyRepertoireImmune systemCytotoxic T cellImmunologyT cellBladder cancerCancer immunotherapyCancerCancer researchGenetics

Abstract

fetched live from OpenAlex

T cells are crucial effector cells in the endogenous defense against cancer, yet the clinical impact of their quantity, diversity, and dynamics remains underexplored. Here, we investigate the clinical relevance of the T cell receptor (TCR) repertoire in patients with bladder cancer. In advanced-stage disease, low pre-treatment peripheral TCR diversity is associated with worse overall survival (p = 0.024), particularly when coupled with low circulating T cell fractions (p = 0.00049). These low-diversity repertoires are dominated by hyper-expanded clones that persist throughout treatment. Further longitudinal analysis reveals reductions in TCR diversity after treatment, indicating adverse effects on the immune system. In early-stage disease, immunotherapy increases TCR diversity in patients with good outcomes. Furthermore, single-cell sequencing identifies most hyper-expanded clones as cytotoxic T cells, while non-expanded clones are predominantly naive T cells. Overall, this highlights TCR diversity as a promising biomarker, offering opportunities for tailored oncological treatments to enhance clinical outcomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.017
GPT teacher head0.273
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCell Reports MedicineSame topicCancer Immunotherapy and BiomarkersFrench-language works237,207