Review highlights theranostic strategies using PSMA PET imaging and targeted therapies to improve outcomes in prostate cancer.
Prostate cancer is the most common solid tumor in males, and it remains a leading cause of cancer-related mortality. Clinicians still struggle to detect early metastatic spread and treat patients whose disease no longer responds to conventional therapy, despite advancements in diagnostics and treatment. Theranostic strategies that target prostate-specific membrane antigen (PSMA) have emerged as a promising strategy to resolve these gaps. PSMA-targeted positron emission tomography (PET) provides superior sensitivity and specificity in comparison to conventional modalities, enabling the detection of recurrent or small-volume disease at low prostate-specific antigen (PSA) levels. Simultaneously, PSMA-directed radioligand therapies, including 177Lu-PSMA-617, have demonstrated advances in progression-free survival (PFS) and overall survival (OS) in metastatic castration-resistant prostate cancer (mCRPC), with a manageable toxicity profile. This review emphasizes the significance of PSMA-based imaging and treatment, utilizing evidence from landmark trials. It also looks at changing approaches including early in the disease course through use of theranostics and dual-tracer PET imaging. Strategies using the immunomodulatory effects of radioligand therapy and combination treatments including androgen receptor (AR) pathway inhibitors, chemotherapy, or immunotherapy are under research and may improve outcomes. Furthermore, increasing the range of use of theranostics is the development of next-generation radiotracers and techniques to handle PSMA-negative or neuroendocrine variations. Lastly, we address worldwide differences in access to PSMA-targeted devices defined by manufacturing infrastructure, regulatory diversity, and financing that still hinder use. Fully achieving the potential of theranostics in prostate cancer will depend on improvements in patient selection, treatment sequencing, and equitable implementation.
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Al-Assil et al. (2026) studied this question.
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