Wu, A;
Attard, G;
(2019)
Plasma DNA Analysis in Prostate Cancer: Opportunities for Improving Clinical Management.
Clinical Chemistry
, 65
(1)
10.1373/clinchem.2018.287250.
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Abstract
BACKGROUND: Molecular characterization of tumors could be important for clinical management. Plasma DNA obtained noninvasively as a liquid biopsy could be widely applicable for clinical implementation in biomarker-based treatment strategies. CONTENT: Prostate cancer is a disease with variable clinical outcomes and molecular features and therefore presents multiple opportunities for biomarker-based treatment optimization. Tissue analysis may not be representative of the lethal clone in localized disease or of intrapatient, intermetastases heterogeneity; fresh tissue is often challenging to obtain by biopsy of metastasis, whereas archival samples may not represent current disease and may be of insufficient quality. Plasma DNA is of variable tumor-to-normal fraction that requires accurate estimation using sensitively measured genomic events. In plasma with sufficient tumor content, the spectrum of genomic aberrations closely resembles tissue and could be used to molecularly characterize patients in real time. In this review we discuss the opportunities for improving clinical management by using plasma DNA analysis in different clinical scenarios across the disease spectrum, from detection of prostate cancer and disease relapse to treatment response prediction, response assessment, and interrogation of treatment resistance in metastatic prostate cancer. Combinational strategies may incorporate other modalities, including circulating tumor cells, circulating microRNA, and extracellular vesicles analysis, which could help to achieve more accurate characterization. SUMMARY: There are many opportunities for plasma DNA analyses to change clinical management. However, there are challenges that need to be addressed to clinically implement a test, including the development of accurate, fit for purpose, and technically reproducible assay, followed by prospective validation in a large cohort of patients.
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