Distinct CD8 <sup>+</sup> T Cell Programming in the Tumor Microenvironment Contributes to Sex Bias in Bladder Cancer Outcome
Bibliographic record
Abstract
Abstract Men and women show striking yet unexplained discrepancies in incidence, clinical presentation, and therapeutic response across different types of infectious/autoimmune diseases and malignancies 1,2 . For instance, bladder cancer shows a 4-fold male-biased incidence that persists after adjustment for known risk factors 3,4 . Here, we utilize murine bladder cancer models to establish that male-biased tumor burden is driven by sex differences in endogenous T cell immunity. Notably, sex differences exist in early fate decisions by intratumoral CD8 + T cells following their activation. While female CD8 + T cells retain their effector function, male counterparts readily adopt a Tcf1 low Tim3 − progenitor state that becomes exhausted over tumor progression. Human cancers show an analogous male-biased frequency of exhausted CD8 + T cells. Mechanistically, we describe an opposing interplay between CD8 + T cell intrinsic androgen and type I interferon 5,6 signaling in Tcf1/ Tcf7 regulation and formation of the progenitor exhausted T cell subset. Consistent with female-biased interferon response 7 , testosterone-dependent stimulation of Tcf1/ Tcf7 and resistance to interferon occurs to a greater magnitude in male CD8 + T cells. Male-biased predisposition for CD8 + T cell exhaustion suggests that spontaneous rejection of early immunogenic bladder tumors is less common in males and carries implications for therapeutic efficacy of immune checkpoint inhibitors 8,9 .
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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 | 0.000 | 0.000 |
| 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) | 0.004 | 0.001 |
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".