Navegando el sinuoso camino hacia la atención de precisión del cáncer de próstata

Prostate cancer (PCa) remains the second leading cause of cancer-related mortality among U.S. men, driven in large part by metastatic castration-resistant prostate cancer (mCRPC) despite initial responses to androgen-receptor (AR)-targeted therapies. Over the last two decades, treatment options for mCRPC have significantly expanded to include novel therapeutic modalities that integrate biomarker-guided patient selection. These biomarker-driven therapies have ushered us into the era of "precision oncology" in prostate cancer care, and we highlight key developments. In light of these promising early results, we also review key opportunities and challenges ahead. Additionally, we share a conceptual roadmap to leverage multi-omics molecular data in the era of artificial intelligence/machine learning (AI/ML) to accelerate progress in prostate cancer precision medicine. Specifically, we discuss how these tools may help better facilitate the development of near-patient preclinical models for prostate cancer towards capturing key aspects of prostate cancer tumor biology, and a potential path toward accelerating translation of laboratory discoveries into clinical practice for mCPRC patients.