Blood test to track treatment resistance in advanced prostate cancer
Cell-free DNA fragmentomics as prognostic and treatment resistance biomarkers in metastatic castration-resistant prostate cancer
['FUNDING_R01'] · UNIVERSITY OF WISCONSIN-MADISON · NIH-11249567
This project uses a blood-based DNA fragment test plus AI to spot molecular changes that signal treatment resistance in men with metastatic castration-resistant prostate cancer.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF WISCONSIN-MADISON (nih funded) |
| Locations | 1 site (MADISON, UNITED STATES) |
| Trial ID | NIH-11249567 on ClinicalTrials.gov |
What this research studies
If you have metastatic castration‑resistant prostate cancer, this project uses routine blood draws to look at tiny fragments of tumor DNA floating in your bloodstream. Researchers analyze patterns of those DNA fragments on standard cancer gene panels and apply machine learning to detect molecular shifts—like changes in the androgen receptor or a switch to neuroendocrine behavior—that can make therapies stop working. The approach is repeated over time in patients enrolled in prospective trials so clinicians can spot resistance earlier than with PSA or imaging alone. The goal is a low-cost, widely available liquid biopsy that could help guide which therapy to try next.
Who could benefit from this research
Good fit: Ideal candidates are men with metastatic castration‑resistant prostate cancer who are receiving or changing androgen-signaling inhibitor therapy and can provide regular blood samples and follow-up.
Not a fit: Men with localized prostate cancer or those whose tumors do not release detectable circulating tumor DNA are unlikely to benefit directly from this approach.
Why it matters
Potential benefit: It could detect treatment resistance earlier and help doctors choose more effective next treatments.
How similar studies have performed: Prior studies using circulating tumor DNA and fragment patterns with machine learning have shown promise for cancer monitoring, but applying fragmentomics specifically to predict ARSI resistance and neuroendocrine shifts in mCRPC is a relatively new approach.
Where this research is happening
MADISON, UNITED STATES
- UNIVERSITY OF WISCONSIN-MADISON — MADISON, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: ZHAO, SHUANG — UNIVERSITY OF WISCONSIN-MADISON
- Study coordinator: ZHAO, SHUANG
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.