RESUMO
BACKGROUND: Genomic studies have identified new subsets of aggressive prostate cancer (PCa) with poor prognosis (eg, neuroendocrine prostate cancer [NEPC], PCa with DNA damage response [DDR] alterations, or PCa resistant to androgen receptor pathway inhibitors [ARPIs]). Development of novel therapies relies on the availability of relevant preclinical models. OBJECTIVE: To develop new preclinical models (patient-derived xenograft [PDX], PDX-derived organoid [PDXO], and patient-derived organoid [PDO]) representative of the most aggressive variants of PCa and to develop a new drug evaluation strategy. DESIGN, SETTING, AND PARTICIPANTS: NEPC (n = 5), DDR (n = 7), and microsatellite instability (MSI)-high (n = 1) PDXs were established from 51 patients with metastatic PCa; PDXOs (n = 16) and PDOs (n = 6) were developed to perform drug screening. Histopathology and treatment response were characterized. Molecular profiling was performed by whole-exome sequencing (WES; n = 13), RNA sequencing (RNA-seq; n = 13), and single-cell RNA-seq (n = 14). WES and RNA-seq data from patient tumors were compared with the models. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Relationships with outcome were analyzed using the multivariable chi-square test and the tumor growth inhibition test. RESULTS AND LIMITATIONS: Our PDXs captured both common and rare molecular phenotypes and their molecular drivers, including alterations of BRCA2, CDK12, MSI-high status, and NEPC. RNA-seq profiling demonstrated broad representation of PCa subtypes. Single-cell RNA-seq indicates that PDXs reproduce cellular and molecular intratumor heterogeneity. WES of matched patient tumors showed preservation of most genetic driver alterations. PDXOs and PDOs preserve drug sensitivity of the matched tissue and can be used to determine drug sensitivity. CONCLUSIONS: Our models reproduce the phenotypic and genomic features of both common and aggressive PCa variants and capture their molecular heterogeneity. Successfully developed aggressive-variant PCa preclinical models provide an important tool for predicting tumor response to anticancer therapy and studying resistance mechanisms. PATIENT SUMMARY: In this report, we looked at the outcomes of preclinical models from patients with metastatic prostate cancer enrolled in the MATCH-R trial (NCT02517892).