Genomic Mutations, Treatment--Resistance & Prostate Cancer - The Deng Lab at Yale School of Medicine
Why It Matters
Understanding and targeting resistance mechanisms could extend the efficacy of existing therapies, reducing mortality and shaping personalized treatment pathways for prostate cancer patients.
Key Takeaways
- •Prostate cancer often develops resistance to hormone therapies
- •Deng Lab uses AI to identify resistance-driving genomic mutations
- •Patient-derived tissue cultures validate computational predictions in prostate cancer
- •Collaboration aims to create drugs targeting resistance proteins
- •Goal: predict and prevent resistance with combined therapeutic strategies
Summary
Therapy resistance remains a major hurdle in prostate cancer, especially after initial success with hormone‑based treatments. The Deng Lab at Yale School of Medicine is dedicated to uncovering the molecular mechanisms that enable cancer cells to evade therapy.
The team combines patient‑derived genomic data with artificial‑intelligence algorithms to pinpoint mutations that drive resistance. These computational hits are then tested in patient‑derived tissue cultures, providing a translational bridge from data to biology.
Lab leader Dr. Deng cites a personal motivation—watching a friend battle leukemia—as a driving force, emphasizing the lab’s patient‑centered mission to develop drugs that degrade resistance‑promoting proteins and to create predictive biomarkers.
If successful, these efforts could yield combination regimens that preempt resistance, offering clinicians tools to personalize treatment and improve long‑term survival for prostate cancer patients.
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