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Clinical Research

Inherited risk assessment and its clinical utility for predicting prostate cancer from diagnostic prostate biopsies

Prostate Cancer and Prostatic Diseases volume 25, pages 422–430 (2022)Cite this article

Subjects

Abstract

Background

Many studies on prostate cancer (PCa) germline variants have been published in the last 15 years. This review critically assesses their clinical validity and explores their utility in prediction of PCa detection rates from prostate biopsy.

Methods

An integrative review was performed to (1) critically synthesize findings on PCa germline studies from published papers since 2016, including risk-associated single nucleotide polymorphisms (SNPs), polygenic risk score methods such as genetic risk score (GRS), and rare pathogenic mutations (RPMs); (2) exemplify the findings in a large population-based cohort from the UK Biobank (UKB); (3) identify gaps for implementing inherited risk assessment in clinic based on experience from a healthcare system; (4) evaluate available GRS data on their clinical utility in predicting PCa detection rates from prostate biopsies; and (5) describe a prospective germline-based biopsy trial to address existing gaps.

Results

SNP-based GRS and RPMs in four genes (HOXB13, BRCA2, ATM, and CHEK2) were significantly and consistently associated with PCa risk in large well-designed studies. In the UKB, positive family history, RPMs in the four implicated genes, and a high GRS (>1.5) identified 8.12%, 1.61%, and 17.38% of men to be at elevated PCa risk, respectively, with hazard ratios of 1.84, 2.74, and 2.39, respectively. Additionally, the performance of GRS for predicting PCa detection rate on prostate biopsy was consistently supported in several retrospective analyses of transrectal ultrasound (TRUS)-biopsy cohorts. Prospective studies evaluating the performance of all three inherited measures in predicting PCa detection rate from contemporary multiparametric MRI (mpMRI)-based biopsy are lacking. A multicenter germline-based biopsy trial to address these gaps is warranted.

Conclusions

The complementary performance of three inherited risk measures in PCa risk stratification is consistently supported. Their clinical utility in predicting PCa detection rate, if confirmed in prospective clinical trials, may improve current decision-making for prostate biopsy.

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Fig. 1: Risk allele frequency (RAF) and odds ratio of 261 prostate cancer risk-associated SNPs implicated in the European population.
Fig. 2: Scatter plot of two GRSs based on 130 and 239 PCa risk-associated SNPs discovered before and after 2020 in subjects of European descent from the UKB.
Fig. 3: Observed rate ratio (RR) for prostate cancer incidence.
Fig. 4: Observed prostate cancer risk (hazard ratio, HR) and 95% confidence interval of three inherited risk measures for prostate cancer in a prostate cancer incidence cohort from the UK Biobank (European descent, N = 224 613).
Fig. 5: Detection rate of prostate cancer (PCa) based on GRS groups.

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Acknowledgements

We are grateful to the Ellrodt-Schweighauser, Chez, and Melman families for establishing Endowed Chairs of Cancer Genomic Research and Personalized Prostate Cancer Care at NorthShore University HealthSystem in support of Dr. Xu and Dr. Helfand. Likewise, the support of W.T. Gerrard, Mario Duhon, Jennifer, and John Chalsty is gratefully acknowledged by Dr. Isaacs as is the support from Bernard L. Schwartz by Dr. Pavlovich. The authors gratefully acknowledge the generous support from donors to The Patrick C. Walsh Hereditary Prostate Cancer Research Program at The Brady Urological Institute.

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Authors and Affiliations

  1. Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA

    Jianfeng Xu, W. Kyle Resurreccion, Zhuqing Shi, Jun Wei, Chi-Hsiung Wang, S. Lilly Zheng & Brian T. Helfand

  2. Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA

    Jianfeng Xu, S. Lilly Zheng & Brian T. Helfand

  3. Department of Medicine, NorthShore University HealthSystem, Evanston, IL, USA

    Peter J. Hulick

  4. Department of Urology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

    Ashley E. Ross

  5. The Brady Urological Institute, The Johns Hopkins School of Medicine, Baltimore, MD, USA

    Christian P. Pavlovich & William B. Isaacs

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Contributions

XJ was responsible for designating the review protocol, conducting the integrative review, guiding the analysis, interpreting results, and drafting the review. WBI was responsible for designating the review protocol, conducting the integrative review, guiding the analysis, interpreting results, and revising the review. WKR was responsible for conducting the integrative review, performing the analysis, interpreting results, revising the review, and submitting the review. ZS was responsible for conducting the integrative review, performing the analysis, interpreting results, and revising the review. JW was responsible for conducting the integrative review, performing the analysis, interpreting results, and revising the review. CHW was responsible for conducting the integrative review, performing the analysis, interpreting results, and revising the review. SLZ was responsible for conducting the integrative review, interpreting results, and revising the review. PJH was responsible for conducting the integrative review, interpreting results, and revising the review. AER was responsible for conducting the integrative review, interpreting results, and revising the review. CPP was responsible for conducting the integrative review, interpreting results, and revising the review. BTH was responsible for conducting the integrative review, interpreting results, and revising the review.

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Correspondence to Jianfeng Xu.

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Competing interests

Authors Jianfeng Xu, W. Kyle Resurreccion, Zhuqing Shi, Jun Wei, S. Lilly Zheng, and Brian T. Helfand are employees of NorthShore University HealthSystem which has an agreement with GoPath Labs for genetic tests of polygenic risk score.

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Xu, J., Resurreccion, W.K., Shi, Z. et al. Inherited risk assessment and its clinical utility for predicting prostate cancer from diagnostic prostate biopsies. Prostate Cancer Prostatic Dis 25, 422–430 (2022). https://doi.org/10.1038/s41391-021-00458-6

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