Method development for identification of targetable genes in ADT-induced prostate cancer dormancy : the case of Interleukin-33
Bibliographic record
Abstract
Background: Prostate cancer is the most common cancer in Canadian men. Androgen receptor drives PCa, and androgen deprivation therapy is the standard of care for advanced PCa, initially ADT elicits a response but often leads to ADT-induced dormancy that precedes relapse to castration-resistant PCa, which is incurable. This underscores the need to better understand tumor dormancy, identify critical genes for dormant cell survival, and develop therapies to target cancer in the earlier disease state when it is more easily treated. We hypothesize that dormancy PDX models provide accurate tumor recapitulation for study of actionable disease targets through wet lab and computational methodology. We will use IL33 as an example for this study. Materials and Methods: A panel of hormone-naïve PCa PDX models were used to establish ADT-induced dormancy. Bulk RNA sequencing of PDX models were analysed to assess IL33 RNA expression. IL33 protein was examined by IHC on sections taken pre-castration and during dormancy. The same methods were applied to FVB Myc-CaP models to recapitulate the immunocompetent TME at chronological timepoints following ADT. We carried out sequencing analysis on clinical cohorts and IHC staining on ADT-treated tissue microarrays. Functional analysis was carried out using single cell sequencing of the LTL331 model in the dormant stage and clinical cohorts for correlation analysis. Results: We confirmed a significant upregulation of IL33 in PDX models at both RNA and protein levels in the dormant stage. Importantly we also found upregulation of IL33 in Myc-CaP immunocompetent mouse models after host-castration. This was also observed in several cohorts of ADT-treated clinical PCa samples, suggesting IL33 is clinically relevant. Using a single cell sequencing dataset of LTL331 model, we also discovered the enrichment of IL33 in a dormant cluster and predicted function roles of IL33 in PCa dormancy. Conclusion: Our results establish a enrichment of IL33 in ADT-induced dormancy in PCa. We confirmed IL33 upregulation across multiple PDX and immunocompetent mouse models, and established clinical relevance of IL33 upregulation following ADT. We also predicted functional roles for IL33 in dormancy by computational methods. This study has successfully established a reproducible methodology for analysis of target genes in ADT-induced dormancy.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".