Abstract 2853: Investigating DNAPK as a biomarker and a novel therapeutic target in aggressive prostate cancer
Bibliographic record
Abstract
Abstract Background/purpose: Despite recent advances in the development of androgen deprivation therapies (ADT), prostate cancer (PCa) remains the second leading cause of cancer death in American men. Thus, there is a critical need to improve treatment outcomes for men with aggressive PCa. The purpose of this study was to identify and functionally characterize kinases that can serve as both prognostic biomarkers and therapeutic targets in PCa. Methods: To identify kinases associated with metastatic progression of PCa, we utilized high-density oligonucleotide arrays to interrogate the expression of all kinases in 545 prostatectomy samples, obtained from high-risk patients with long-term clinical follow-up (>10 years). We ranked all kinases by their fold change in expression between PCas that subsequently metastasized versus those that did not. We then characterized the top ranked kinase in preclinical PCa models with in vitro mechanistic experiments and in vivo therapeutic studies. Results: We nominated DNA-dependent protein kinase (DNAPK) as the top kinase associated with metastatic PCa progression. Interrogation of pathways associated with DNAPK knockdown in PC3, DU145, VCaP and C4-2B, identified canonical Wnt signaling as the top DNAPK-activated pathway. In PCa cells (PC3, LNCaP C.S. {LNCaP grown under charcoal-stripped serum condition}, C4-2B and LNCaP-AR) DNAPK inhibition significantly abrogates Wnt signaling and abolishes cell proliferation, migration and invasion. Interestingly, we found that DNAPK directly modulates the Wnt signaling independent of the androgen receptor (AR), highlighting the therapeutic potential of DNAPK inhibition in cancers resistant to ADT. Indeed, in VCaP xenograft models, pharmacologic inhibition of DNAPK with NU7441 demonstrated 3.4 fold (p<0.01) reduction of tumor growth at non-toxic doses. Using an independent prostate cancer tissue cohort, we validate DNAPK expression as a biomarker for metastatic disease progression (p = 6.4 e−06, hazard ratio = 2). Conclusion: In summary, we nominate DNAPK as a potential biomarker of disease progression and as a novel therapeutic target in aggressive prostate cancer. Our data suggests that DNAPK mediates PCa progression by upregulating Wnt signaling, and demonstrates that DNAPK inhibition results in significant tumor responses in PCa xenografts. Citation Format: Vishal Kothari, Jonathan F. Goodwin, Shuang Zhao, Elai Davicioni, Jeffrey R. Karnes, Robert B. Den, Rohit Mehra, Karen E. Knudsen, Felix Y. Feng. Investigating DNAPK as a biomarker and a novel therapeutic target in aggressive prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2853. doi:10.1158/1538-7445.AM2015-2853
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".