Targeting the chromatin effector Pygo2 promotes cytotoxic T cell responses and overcomes immunotherapy resistance in prostate cancer
Bibliographic record
Abstract
The noninflamed microenvironment in prostate cancer represents a barrier to immunotherapy. Genetic alterations underlying cancer cell–intrinsic oncogenic signaling are increasingly appreciated for their role in shaping the immune landscape. Recently, we identified Pygopus 2 ( PYGO2 ) as the driver oncogene for the amplicon at 1q21.3 in prostate cancer. Here, using transgenic mouse models of metastatic prostate adenocarcinoma, we found that Pygo2 deletion decelerated tumor progression, diminished metastases, and extended survival. Pygo2 loss augmented the activation and infiltration of cytotoxic T lymphocytes (CTLs) and sensitized tumor cells to T cell killing. Mechanistically, Pygo2 orchestrated a p53/Sp1/Kit/Ido1 signaling network to foster a microenvironment hostile to CTLs. Genetic or pharmacological inhibition of Pygo2 enhanced the antitumor efficacy of immunotherapies using immune checkpoint blockade (ICB), adoptive cell transfer, or agents inhibiting myeloid-derived suppressor cells. In human prostate cancer samples, Pygo2 expression was inversely correlated with the infiltration of CD8 + T cells. Analysis of the ICB clinical data showed association between high PYGO2 level and worse outcome. Together, our results highlight a potential path to improve immunotherapy using Pygo2-targeted therapy for advanced prostate cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".