Evasion of immunosurveillance by genomic alterations of PPARγ/RXRα in bladder cancer
Bibliographic record
Abstract
Abstract Muscle-invasive bladder cancer (MIBC) is an aggressive disease with limited therapeutic options. Although immunotherapies are approved for MIBC, the majority of patients fail to respond, suggesting existence of complementary immune evasion mechanisms. Here, we report that the PPARγ/RXRα pathway constitutes a tumor-intrinsic mechanism underlying immune evasion in MIBC. Recurrent mutations in RXRα at serine 427 (S427F/Y), through conformational activation of the PPARγ/RXRα heterodimer, and focal amplification/overexpression of PPARγ converge to modulate PPARγ/RXRα-dependent transcription programs. Immune cell-infiltration is controlled by activated PPARγ/RXRα that inhibits expression/secretion of inflammatory cytokines. Clinical data sets and an in vivo tumor model indicate that PPARγHigh/RXRαS427F/Y impairs CD8+ T-cell infiltration and confers partial resistance to immunotherapies. Knockdown of PPARγ or RXRα and pharmacological inhibition of PPARγ significantly increase cytokine expression suggesting therapeutic approaches to reviving immunosurveillance and sensitivity to immunotherapies. Our study reveals a class of tumor cell-intrinsic “immuno-oncogenes” that modulate the immune microenvironment of cancer.
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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 | 0.000 | 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".