Oncotarget

Reviews:

Approaches to the discovery of non-invasive urinary biomarkers of prostate cancer

Andrej Jedinak, Kevin R. Loughlin and Marsha A. Moses _

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Oncotarget. 2018; 9:32534-32550. https://doi.org/10.18632/oncotarget.25946

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Abstract

Andrej Jedinak1,2, Kevin R. Loughlin2,3 and Marsha A. Moses1,2

1Vascular Biology Program and Department of Surgery, Boston Children’s Hospital, Boston, MA, USA

2Department of Surgery, Harvard Medical School, Boston, MA, USA

3Department of Urology, Brigham and Women’s Hospital, Boston, MA, USA

Correspondence to:

Marsha A. Moses, email: [email protected]

Keywords: prostate cancer; biomarkers; non-invasive; proteomics

Received: May 16, 2018    Accepted: July 23, 2018    Published: August 21, 2018

ABSTRACT

Prostate cancer (PCa) continues to be one of the most common cancers in men worldwide. Prostate specific antigen (PSA) measured in blood has been used for decades as an aid for physicians to detect the presence of prostate cancer. However, the PSA test has limited sensitivity and specificity, leading to unnecessary biopsies, overdiagnosis and overtreatment of patients. For these reasons, there is an urgent need for more accurate PCa biomarkers that can detect PCa with high sensitivity and specificity. Urine is a unique source of potential protein biomarkers that can be measured in a non-invasive way. This review comprehensively summarizes state of the art approaches used in the discovery and validation of urinary biomarkers for PCa. Numerous strategies are currently being used in the discovery of urinary biomarkers for prostate cancer including gel-based separation techniques, mass spectrometry, activity-based proteomic assays and software approaches. Antibody-based approaches remain preferred method for validation of candidate biomarkers with rapidly advancing multiplex immunoassays and MS-based targeted approaches. In the last decade, there has been a dramatic acceleration in the development of new techniques and approaches in the discovery of protein biomarkers for prostate cancer including computational, statistical and data mining methods. Many urinary-based protein biomarkers have been identified and have shown significant promise in initial studies. Examples of these potential biomarkers and the methods utilized in their discovery are also discussed in this review.


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