Molecular Oncology (Jan 2022)

Combining liquid biopsy and functional imaging analysis in metastatic castration‐resistant prostate cancer helps predict treatment outcome

  • Vincenza Conteduca,
  • Emanuela Scarpi,
  • Paola Caroli,
  • Cristian Lolli,
  • Giorgia Gurioli,
  • Nicole Brighi,
  • Giulia Poti,
  • Alberto Farolfi,
  • Amelia Altavilla,
  • Giuseppe Schepisi,
  • Federica Matteucci,
  • Giovanni Paganelli,
  • Ugo De Giorgi

DOI
https://doi.org/10.1002/1878-0261.13120
Journal volume & issue
Vol. 16, no. 2
pp. 538 – 548

Abstract

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Plasma tumour DNA (ptDNA) is a potential early noninvasive biomarker of treatment outcome in metastatic castration‐resistant prostate cancer (mCRPC). Herein, we investigated whether pretreatment ptDNA levels reflect metabolic tumour burden in mCRPC and better predict treatment outcome in combination with functional imaging. Targeted next‐generation sequencing was performed to estimate the ptDNA fraction from 102 mCRPC patients receiving abiraterone or enzalutamide. The maximum standardized uptake value (SUVmax), total lesion activity (TLA) and metabolic tumour volume (MTV) were evaluated on 18F‐fluorocholine positron emission tomography/computed tomography. We assessed a Weibull multiple regression model to determine the combined impact of clinical, molecular and imaging characteristics on overall survival (OS) and progression‐free survival (PFS), and to obtain prognostic scores. A significant association was seen between ptDNA and SUVmax, MTV and TLA. For survival analysis, patients were randomly allocated into a training (n = 68) and a validation (n = 34) set. In the training set, multivariable analyses showed that ptDNA, MTV and serum lactate dehydrogenase together with visceral metastasis were independent predictors of both OS and PFS. Prognostic scores were generated, with the identification of three groups of patients with significantly different median OS (29.2, 15.9 and 8.7 months) and PFS (13.3, 7.7 and 3.2 months) probabilities. The differences in median survival between risk groups were confirmed in the validation cohort for both OS and PFS. In our study, we showed that integrating plasma DNA analysis with functional imaging may improve prognostic risk stratification and treatment selection in mCRPC.

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