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Last Posted: Jun 02, 2023
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Genetically adjusted PSA levels for prostate cancer screening.
Linda Kachuri et al. Nat Med 2023 6

In this study, we discovered 128 genome-wide significant associations (P?<?5?×?10-8) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA) that explains 9.61% of constitutive PSA variation. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR)?=?3.44, P?=?6.2?×?10-14, area under the curve (AUC)?=?0.755) than unadjusted PSA (OR?=?3.31, P?=?1.1?×?10-12, AUC?=?0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC?=?0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC?=?0.786, P?=?7.2?×?10-4). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening.

Clinical utility of polygenic risk scores: a critical 2023 appraisal
S Koch et al, J Comm Genetics, May 3, 2023

We surveyed the current state of PRSs for various diseases, including breast cancer, diabetes, prostate cancer, coronary artery disease, and Parkinson disease, with an extra focus upon the potential improvement of clinical scores by their combination with PRSs. We observed that the diagnostic and prognostic performance of PRSs alone is consistently low, as expected. Moreover, combining a PRS with a clinical score at best led to moderate improvement of the power of either risk marker. Despite the large number of PRSs reported in the scientific literature, prospective studies of their clinical utility, particularly of the PRS-associated improvement of standard screening or therapeutic procedures, are still rare.

Predicting response to enzalutamide and abiraterone in metastatic prostate cancer using whole-omics machine learning.
Anouk C de Jong et al. Nature communications 2023 4 (1) 1968

Response to androgen receptor signaling inhibitors (ARSI) varies widely in metastatic castration resistant prostate cancer (mCRPC). To improve treatment guidance, biomarkers are needed. We use whole-genomics (WGS; n?=?155) with matching whole-transcriptomics (WTS; n?=?113) from biopsies of ARSI-treated mCRPC patients for unbiased discovery of biomarkers and development of machine learning-based prediction models. Tumor mutational burden (q?<?0.001), structural variants (q?<?0.05), tandem duplications (q?<?0.05) and deletions (q?<?0.05) are enriched in poor responders, coupled with distinct transcriptomic expression profiles.

A Polygenic Risk Score for Prostate Cancer Risk Prediction.
Kerry R Schaffer et al. JAMA internal medicine 2023 3

In this study, a prostate cancer polygenic risk score did not improve risk prediction of aggressive prostate cancer compared with a contemporary clinical risk predictor. Although the PRS269 improved model discrimination for all cancers, improvement was less than has been observed for other validated prostate cancer biomarker predictors such as the Prostate Health Index.

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Disclaimer: Articles listed in the Public Health Genomics and Precision Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.

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