1. Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer.
- Author
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Fonseca NM, Maurice-Dror C, Herberts C, Tu W, Fan W, Murtha AJ, Kollmannsberger C, Kwan EM, Parekh K, Schönlau E, Bernales CQ, Donnellan G, Ng SWS, Sumiyoshi T, Vergidis J, Noonan K, Finch DL, Zulfiqar M, Miller S, Parimi S, Lavoie JM, Hardy E, Soleimani M, Nappi L, Eigl BJ, Kollmannsberger C, Taavitsainen S, Nykter M, Tolmeijer SH, Boerrigter E, Mehra N, van Erp NP, De Laere B, Lindberg J, Grönberg H, Khalaf DJ, Annala M, Chi KN, and Wyatt AW
- Subjects
- Humans, Male, Prognosis, Prospective Studies, Biological Specimen Banks, Biomarkers, Tumor genetics, Liquid Biopsy, Mutation, Prostatic Neoplasms, Castration-Resistant diagnosis, Prostatic Neoplasms, Castration-Resistant genetics, Prostatic Neoplasms, Castration-Resistant drug therapy
- Abstract
No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine-learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org ). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing., (© 2024. The Author(s).)
- Published
- 2024
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