Improving detection and risk assessment for prostate cancer in men
Official title: Computational Feature Profiling and Modeling for Prostate Cancer Detection and Risk Stratification
Funded at University of California Los Angeles · NIH-10994658 · Data updated 2026-11-12
This study is looking to improve how we find and understand prostate cancer in men by using new technology to spot important signs that can help tell the difference between serious and less serious cases, which could lead to better treatment and fewer unnecessary procedures.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Los Angeles NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project start | December 5, 2023 |
| Project end | November 30, 2028 |
| Funding year | 2025 |
| Award (this year) | $619,960 |
| NIH project number | 5R01CA279666-02 |
| Project ID | NIH-10994658 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are American men who are at risk for prostate cancer or have been diagnosed with the disease.
✕Less likely to help
Patients with non-prostate cancer-related conditions or those who are not male may not receive any benefit from this research.
What this research studies
This research focuses on enhancing the detection and risk assessment of prostate cancer, which is a significant health concern for American men. By analyzing a large group of patients, the study aims to identify new biological markers and develop advanced computational models that can better differentiate between aggressive and indolent forms of cancer. The approach involves using innovative technologies like graph convolutional networks and convolutional neural networks to analyze various patient data, potentially leading to more accurate diagnoses and treatment plans. This could help reduce unnecessary treatments and improve patient outcomes.
Why it matters
Potential benefit: If successful, this research could lead to more precise detection of aggressive prostate cancer, minimizing unnecessary treatments for patients with less severe forms of the disease.
How similar studies have gone: Previous research has shown promise in using advanced computational methods for cancer detection, indicating that this approach could yield significant advancements in prostate cancer management.
Where this research is happening
-
University of California Los Angeles
Los Angeles, United States Active
Researchers
- Principal investigator: Arnold, Corey Wells — University of California Los Angeles
- Study coordinator: Arnold, Corey Wells
Related research
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-
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Effects of ADT on motivation and emotion in prostate cancer patients
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-
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-
Characterizing epigenetic targets in prostate cancer to help AR-driven cancer
A research project at MD Anderson aims to understand how epigenetic factors shape androgen receptor signaling in prostate cancer to find new ways to treat resistant forms of the disease.
-
AR and RNA-binding in prostate cancer resistance
A cancer research grant exploring how the androgen receptor’s interaction with RNA may drive treatment resistance in prostate cancer, with potential to guide new therapies.
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.