Interleukin-10 Induces Expression of Neuroendocrine Markers and PDL1 in Prostate Cancer Cells
Bibliographic record
Abstract
Interleukin-10 (IL10) is best studied for its inhibitory action on immune cells and ability to suppress an antitumour immune response. But IL10 also exerts direct effects on nonimmune cells such as prostate cancer epithelial cells. Elevated serum levels of IL10 observed in prostate and other cancer patients are associated with poor prognosis. After first-line androgen-deprivation therapy, prostate cancer patients are treated with androgen receptor antagonists such as enzalutamide to inhibit androgen-dependent prostate cancer cell growth. However, development of resistance inevitably occurs and this is associated with tumour differentiation to more aggressive forms such as a neuroendocrine phenotype characterized by expression of neuron specific enolase and synaptophysin. We found that treatment of prostate cancer cell lines in vitro with IL10 or enzalutamide induced markers of neuroendocrine differentiation and inhibited androgen receptor reporter activity. Both also upregulated the levels of PDL1, which could promote tumour survival in vivo through its interaction with the immune cell inhibitory receptor PD1 to suppress antitumour immunity. These findings suggest that IL10’s direct action on prostate cancer cells could contribute to prostate cancer progression independent of IL10’s suppression of host immune cells.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".