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Get Free AccessBackground: For patients with mCRPC, PSMA-targeted radioligand treatment has significantly improved the clinical outcome. A blood-based liquid biopsy assay for recognizing PSMA protein expression on circulating tumor cells may be beneficial for better informing therapeutic decision-making and identifying the patients most likely to benefit from PSMA-targeted radioligand therapy. Methods: Using high-throughput imaging and digital AI pathology algorithms, a four-color immunofluorescence assay has been developed to find PSMA protein expression on CTCs on a glass slide. Cell line cells (LNCaP/PC3s/22Rv1) spiked into healthy donor blood were used to study the precision, specificity, sensitivity, limit of detection, and overall accuracy of the assay. Clinical validation and low-pass whole-genome sequencing were performed in PSMA-PET-positive patients with high-risk mCRPC (N = 24) utilizing 3 mL of blood. Results: The PSMA CTC IF assay achieved analytical specificity, sensitivity, and overall accuracy above 99% with high precision. In the clinical validation, 76% (16/21) of the cases were PSMA positive with CTC heterogeneity, and 88% (21/24) of the patients contained at least one conventional CTC per milliliter of blood. Thirty-six low-pass-sequenced CTCs from 11 individuals with mCRPC frequently exhibited copy number increases in AR and MYC and losses in RB1, PTEN, TP53, and BRCA2 locus. Conclusions: The analytical validation utilizing Epic Sciences’ liquid biopsy CTC platform demonstrated the potential to detect PSMA protein expression in CTCs from patients with mCRPC. This assay is positioned as an effective research tool to evaluate PSMA expression, heterogeneity, and therapeutic response in many ongoing clinical studies to target tumors that express PSMA.
Santosh Gupta, Luisa Fernandez, David Bourdon, Anis Hamid, Anupama Pasam, Ernest W.N. Lam, Rick Wenstrup, Shahneen Sandhu (2024). Detection of PSMA expression on circulating tumor cells by blood-based liquid biopsy in prostate cancer. , 13(1), DOI: https://doi.org/10.33393/jcb.2024.2636.
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Type
Article
Year
2024
Authors
8
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.33393/jcb.2024.2636
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