Determinants of outcome following PSMA-based radioligand therapy and mechanisms of resistance in patients with metastatic castration-resistant prostate cancer

Autor: Louise Kostos, James P. Buteau, Michael S. Hofman, Arun A. Azad
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Therapeutic Advances in Medical Oncology, Vol 15 (2023)
Druh dokumentu: article
ISSN: 1758-8359
17588359
DOI: 10.1177/17588359231179309
Popis: [ 177 Lu]Lu-PSMA has recently been approved for use in the post-taxane, post-novel hormonal-agent setting in patients with metastatic castration-resistant prostate cancer. As a beta-emitting radioligand targeting prostate-specific membrane antigen (PSMA), it delivers radiation to cells expressing PSMA on their surface. In pivotal clinical trials, patients were selected for this treatment based on positron emission tomography (PET)/CT imaging, requiring PSMA-avid disease with no evidence of discordant disease on 2-[ 18 F]fluoro-2-deoxy-D-glucose PET/CT or contrast CT scan. Despite exhibiting an optimal imaging phenotype, the response for many patients is not durable, and a minority do not respond to [ 177 Lu]Lu-PSMA at all. Disease progression is inevitable even for those who achieve an exceptional initial response. Reasons for both primary and acquired resistance are largely unknown; however, they are likely due to the presence of underlying PSMA-negative disease not identified on imaging, molecular factors conferring radioresistance, and inadequate delivery of lethal radiation, particularly to sites of micrometastatic disease. Biomarkers are urgently needed to optimize patient selection for treatment with [ 177 Lu]Lu-PSMA by identifying those who are most and least likely to respond. Retrospective data support using several prognostic and predictive baseline patient- and disease-related parameters; however, robust prospective data is required before these can be translated into widespread use. Further, early on-treatment clinical parameters (in addition to serial prostate-specific antigen [PSA] levels and conventional restaging imaging) may serve as surrogates for predicting treatment response. With little known about the efficacy of treatments given after [ 177 Lu]Lu-PSMA, optimal treatment sequencing is paramount, and biomarker-driven patient selection will hopefully improve treatment and survival outcomes.
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