Polygenic risk score for genetic evaluation of prostate cancer risk in Asian populations: A narrative review

Predictive value of polygenic risk score for prostate cancer incidence and prognosis in the Han Chinese

Although prostate cancer is a common occurrence among males, the relationship between existing risk prediction models remains unclear. The objective of this hospital-based retrospective study is to investigate the impact of polygenic risk scores (PRSs) on the incidence and prognosis of prostate cancer in the Han Chinese population. A total of 24,778 male participants including 903 patients with prostate cancer at Taichung Veterans General Hospital were enrolled in the study. PRS was calculated using 269 single nucleotide polymorphisms and their corresponding effect sizes from the polygenic score catalog. The association between PRS and the risk prostate cancer was evaluated using Cox proportional hazards regression model. Among the 24,778 participants, 903 were diagnosed with prostate cancer. The risk of prostate cancer was significantly higher in the highest quartile of PRS distribution compared to the lowest (hazard ratio = 4.770, 95% CI = 3.999-5.689, p < 0.0001), with statistical significance across all age groups. Patients in the highest quartile were diagnosed with prostate cancer at a younger age (66.8 ± 8.3 vs. 69.5 ± 8.8, p = 0.002). Subgroup analysis of patients with localized or stage 4 prostate cancer showed no significant differences in biochemical failure or overall survival. This hospital-based cohort study observed that a higher PRS was associated with increased susceptibility to prostate cancer and younger age of diagnosis. However, PRS was not found to be a significant predictor of disease stage and prognosis. These findings suggest that PRS could serve as a useful tool in prostate cancer risk assessment.

Utility of polygenic scores across diverse diseases in a hospital cohort for predictive modeling

Polygenic scores estimate genetic susceptibility to diseases. We systematically calculated polygenic scores across 457 phenotypes using genotyping array data from China Medical University Hospital. Logistic regression models assessed polygenic scores' ability to predict disease traits. The polygenic score model with the highest accuracy, based on maximal area under the receiver operating characteristic curve (AUC), is provided on the GeneAnaBase website of the hospital. Our findings indicate 49 phenotypes with AUC greater than 0.6, predominantly linked to endocrine and metabolic diseases. Notably, hyperplasia of the prostate exhibited the highest disease prediction ability (P value = 1.01 × 10-19, AUC = 0.874), highlighting the potential of these polygenic scores in preventive medicine and diagnosis. This study offers a comprehensive evaluation of polygenic scores performance across diverse human traits, identifying promising applications for precision medicine and personalized healthcare, thereby inspiring further research and development in this field.

Association of Androgen Deprivation Therapy with Osteoporotic Fracture in Patients with Prostate Cancer with Low Tumor Burden Using a Retrospective Population-Based Propensity-Score-Matched Cohort

This study evaluated the effect of androgen deprivation therapy (ADT) on osteoporotic fractures (OF) and its prognostic effect on overall survival in patients with localized or regional prostate cancer (PC) using the Korean National Insurance Dataset. A total of 8883 pairs of 1:1 propensity-score-matched patients with localized or regional PC were retrospectively enrolled between 2007 and 2016. All patients underwent at least 1 year of follow-up to evaluate therapeutic outcomes. Multivariate analysis was performed to determine the prognostic effect of ADT on OF. During a mean follow-up of 47.7 months, 977 (3.43%) patients developed OF, and the incidences of hip, spine, and wrist fractures were significantly different between ADT and non-ADT groups (p < 0.05). The ADT group had a significantly higher incidence of OF (hazard ratio 2.055, 95% confidence interval 1.747-2.417) than the non-ADT group (p < 0.05), and the incidence of spine/hip/wrist OF was significantly higher in the ADT group regardless of the PC stage (p < 0.05). Multivariate analysis failed to show any significant difference in overall survival between the two groups (p > 0.05). ADT resulted in a significantly higher incidence of OF among patients with localized and regional PC, but the overall survival did not differ between ADT and non-ADT groups.

The Combined Effect of Polygenic Risk Score and Prostate Health Index in Chinese Men Undergoing Prostate Biopsy

To date, the combined effect of polygenic risk score (PRS) and prostate health index (phi) on PCa diagnosis in men undergoing prostate biopsy has never been investigated. A total of 3166 patients who underwent initial prostate biopsy in three tertiary medical centers from August 2013 to March 2019 were included. PRS was calculated on the basis of the genotype of 102 reported East-Asian-specific risk variants. It was then evaluated in the univariable or multivariable logistic regression models that were internally validated using repeated 10-fold cross-validation. Discriminative performance was assessed by area under the receiver operating curve (AUC) and net reclassification improvement (NRI) index. Compared with men in the first quintile of age and family history adjusted PRS, those in the second, third, fourth, and fifth quintiles were 1.86 (odds ratio, 95% confidence interval (CI): 1.34-2.56), 2.07 (95%CI: 1.50-2.84), 3.26 (95%CI: 2.36-4.48), and 5.06 (95%CI: 3.68-6.97) times as likely to develop PCa (all p < 0.001). Adjustment for other clinical parameters yielded similar results. Among patients with prostate-specific antigen (PSA) at 2-10 ng/mL or 2-20 ng/mL, PRS still had an observable ability to differentiate PCa in the group of prostate health index (phi) at 27-36 (P_trend < 0.05) or >36 (P_trend ≤ 0.001). Notably, men with moderate phi (27-36) but highest PRS (top 20% percentile) would have a comparable risk of PCa (positive rate: 26.7% or 31.3%) than men with high phi (>36) but lowest PRS (bottom 20% percentile positive rate: 27.4% or 34.2%). The combined model of PRS, phi, and other clinical risk factors provided significantly better performance (AUC: 0.904, 95%CI: 0.887-0.921) than models without PRS. Adding PRS to clinical risk models could provide significant net benefit (NRI, from 8.6% to 27.6%), especially in those early onset patients (NRI, from 29.2% to 44.9%). PRS may provide additional predictive value over phi for PCa. The combination of PRS and phi that effectively captured both clinical and genetic PCa risk is clinically practical, even in patients with gray-zone PSA.

Polygenic risk score for tumor aggressiveness and early-onset prostate cancer in Asians

We attempted to assess the performance of an ethnic-specific polygenic risk score (PRS) designed from a Korean population to predict aggressive prostate cancer (PCa) and early-onset (age < 60). A PRS score comprised of 22 SNPs was computed in 3695 patients gathered from one of 4 tertiary centers in Korea. Males with biopsy or radical prostatectomy-proven PCa were included for analysis, collecting additional clinical parameters such as age, BMI, PSA, Gleason Group (GG), and staging. Patients were divided into 4 groups of PRS quartiles. Intergroup differences were assessed, as well as risk ratio and predictive performance based on GG using logistic regression analysis and AUC. No significant intergroup differences were observed for BMI, PSA, and rate of ≥ T3a tumors on pathology. Rate of GG ≥ 2, GG ≥ 3, and GG ≥ 4 showed a significant pattern of increase by PRS quartile (p < 0.001, < 0.001, and 0.039, respectively). With the lowest PRS quartile as reference, higher PRS groups showed sequentially escalating risk for GG ≥ 2 and GG ≥ 3 pathology, with a 4.6-fold rise in GG ≥ 2 (p < 0.001) and 2.0-fold rise in GG ≥ 3 (p < 0.001) for the highest PRS quartiles. Combining PRS with PSA improved prediction of early onset csPCa (AUC 0.759) compared to PRS (AUC 0.627) and PSA alone (AUC 0.736). To conclude, an ethnic-specific PRS was found to predict susceptibility of aggressive PCa in addition to improving detection of csPCa when combined with PSA in early onset populations. PRS may have a role as a risk-stratification model in actual practice. Large scale, multi-ethnic trials are required to validate our results.

Race and prostate cancer: genomic landscape

In the past 20 years, new insights into the genomic pathogenesis of prostate cancer have been provided. Large-scale integrative genomics approaches enabled researchers to characterize the genetic and epigenetic landscape of prostate cancer and to define different molecular subclasses based on the combination of genetic alterations, gene expression patterns and methylation profiles. Several molecular drivers of prostate cancer have been identified, some of which are different in men of different races. However, the extent to which genomics can explain racial disparities in prostate cancer outcomes is unclear. Future collaborative genomic studies overcoming the underrepresentation of non-white patients and other minority populations are essential.

Polygenic risk score in prostate cancer

PURPOSE OF REVIEW

This study was conducted in order to review the outcomes regarding polygenic risk score (PRS) in prediction of prostate cancer (PCa). With the increasing proficiency of genetic analysis, assessment of PRS for prediction of PCa has been performed in numerous studies. Genetic risk prediction models for PCa that include hundreds to thousands of independent risk-associated variants are under development. For estimation of additive effect of multiple variants, the number of risk alleles carried by an individual is summed, and each variant is weighted according to its estimated effect size for generation of a PRS.

RECENT FINDINGS

Currently, regarding the accuracy of PRS alone, PCa detection rate ranged from 0.56 to 0.67. A higher rate of accuracy of 0.866-0.880 was observed for other models combining PRS with established clinical markers. The results of PRS from Asian populations showed a level of accuracy that is somewhat low compared with values from Western populations (0.63-0.67); however, recent results from Asian cohorts were similar to that of Western counterparts. Here, we review current PRS literature and examine the clinical utility of PRS for prediction of PCa.

SUMMARY

Emerging data from several studies regarding PRS in PCa could be the solution to adding predictive value to PCa risk estimation. Although commercial markers are available, development of a large-scale, well validated PRS model should be undertaken in the near future, in order to translate hypothetical scenarios to actual clinical practice.

Prediction of clinically significant prostate cancer using polygenic risk models in Asians

Purpose

To develop and evaluate the performance of a polygenic risk score (PRS) constructed in a Korean male population to predict clinically significant prostate cancer (csPCa).

Materials and Methods

Total 2,702 PCa samples and 7,485 controls were used to discover csPCa susceptible single nucleotide polymorphisms (SNPs). Males with biopsy-proven or post-radical prostatectomy Gleason score 7 or higher were included for analysis. After genotype imputation for quality control, logistic regression models were applied to test association and calculate effect size. Extracted candidate SNPs were further tested to compare predictive performance according to number of SNPs included in the PRS. The best-fit model was validated in an independent cohort of 311 cases and 822 controls.

Results

Of the 83 candidate SNPs with significant PCa association reported in previous literature, rs72725879 located in PRNCR1 showed the highest significance for PCa risk (odds ratio, 0.597; 95% confidence interval [CI], 0.555–0.641; p=4.3×10^-45). Thirty-two SNPs within 26 distinct loci were further selected for PRS construction. Best performance was found with the top 29 SNPs, with AUC found to be 0.700 (95% CI, 0.667–0.734). Males with very-high PRS (above the 95th percentile) had a 4.92-fold increased risk for csPCa.

Conclusions

Ethnic-specific PRS was developed and validated in Korean males to predict csPCa susceptibility using the largest csPCa sample size in Asia. PRS can be a potential biomarker to predict individual risk. Future multi-ethnic trials are required to further validate our results.