Family history and pathogenic/likely pathogenic germline variants in prostate cancer patients

Performance of clinical risk scores and prediction models to identify pathogenic germline variants in patients with advanced prostate cancer

PURPOSE

Determining the frequency and distribution of pathogenic germline variants (PGVs) in Austrian prostate cancer (PCa) patients and to assess the accuracy of different clinical risk scores to correctly predict PGVs.

METHODS

This cross-sectional study included 313 men with advanced PCa. A comprehensive personal and family history was obtained based on predefined questionnaires. Germline DNA sequencing was performed between 2019 and 2021 irrespective of family history, metastatic or castration status or age at diagnosis. Clinical risk scores for hereditary cancer syndromes were evaluated and a PCa-specific score was developed to assess the presence of PGVs.

RESULTS

PGV presence was associated with metastasis (p = 0.047) and castration resistance (p = 0.011), but not with personal cancer history or with relatives with any type of cancer. Clinical risk scores (Manchester score, PREMM5 score, Amsterdam II criteria or Johns Hopkins criteria) showed low sensitivities (3.3-20%) for assessing the probability of PGV presence. A score specifically designed for PCa patients stratifying patients into low- or high-risk regarding PGV probability, correctly classified all PGV carriers as high-risk, whereas a third of PCa patients without PGVs was classified as low risk of the presence of PGVs.

CONCLUSION

Application of common clinical risk scores based on family history are not suitable to identify PCa patients with high PGV probabilities. A PCa-specific score stratified PCa patients into low- or high-risk of PGV presence with sufficient accuracy, and germline DNA sequencing may be omitted in patients with a low score. Further studies are needed to evaluate the score.

Family History of Prostate and Breast Cancer Integrated with a Polygenic Risk Score Identifies Men at Highest Risk of Dying from Prostate Cancer before Age 75 Years

PURPOSE

Family history of prostate cancer is one of the few universally accepted risk factors for prostate cancer. How much an assessment of inherited polygenic risk for prostate cancer adds to lifetime risk stratification beyond family history is unknown.

EXPERIMENTAL DESIGN

We followed 10,120 men in the Health Professionals Follow-up Study with existing genotype data for risk of prostate cancer and prostate cancer-specific death. We assessed to what extent family history of prostate or breast cancer, combined with a validated polygenic risk score (PRS) including 269 prostate cancer risk variants, identifies men at risk of prostate cancer and prostate cancer death across the age span.

RESULTS

During 20 years of follow-up, 1,915 prostate cancer and 166 fatal prostate cancer events were observed. Men in the top PRS quartile with a family history of prostate or breast cancer had the highest rate of both prostate cancer and prostate cancer-specific death. Compared with men at lowest genetic risk (bottom PRS quartile and no family history), the HR was 6.95 [95% confidence interval (CI), 5.57-8.66] for prostate cancer and 4.84 (95% CI, 2.59-9.03) for prostate cancer death. Men in the two upper PRS quartiles (50%-100%) or with a family history of prostate or breast cancer (61.8% of the population) accounted for 97.5% of prostate cancer deaths by age 75 years.

CONCLUSIONS

Our study shows that prostate cancer risk stratification on the basis of family history and inherited polygenic risk can identify men at highest risk of dying from prostate cancer before age 75 years.

Discovery of Lipid Metabolism-Related Genes for Predicting Tumor Immune Microenvironment Status and Prognosis in Prostate Cancer

Background. Reprogramming of lipid metabolism is closely associated with tumor development, serving as a common and critical metabolic feature that emerges during tumor evolution. Meanwhile, immune cells in the tumor microenvironment also undergo aberrant lipid metabolism, and altered lipid metabolism also has an impact on the function and status of immune cells, further promoting malignant biological behavior. Consequently, we focused on lipid metabolism-related genes for constructing a novel prognostic marker and evaluating immune status in prostate cancer. Methods. Information about prostate cancer patients was obtained from TCGA and GEO databases. The NMF algorithm was conducted to identify the molecular subtypes. The least absolute shrinkage and selection operator (Lasso) regression analysis was applied to establish a prognostic risk signature. CIBERSORT algorithm was used to calculate immune cell infiltration levels in prostate cancer. External clinical validation data were used to validate the results. Results. Prostate cancer samples were divided into two subtypes according to the NMF algorithm. A six-gene risk signature (PTGS2, SGPP2, ALB, PLA2G2A, SRD5A2, and SLC2A4) was independent of prognosis and showed good stability. There were significant differences between risk groups of patients with respect to the infiltration of immune cells and clinical variables. Response to immunotherapy also differed between different risk groups. Furthermore, the mRNA expression levels of the signature genes were verified in tissue samples by qRT-PCR. Conclusion. We constructed a six-gene signature with lipid metabolism in prostate cancer to effectively predict prognosis and reflect immune microenvironment status.

Disparities in germline testing among racial minorities with prostate cancer

Germline testing is becoming increasingly relevant in prostate cancer (PCa) screening, prognosis, and management. A subset of patients with PCa harbor pathogenic/likely pathogenic variants (P/LPVs) in genes mediating DNA-repair processes, and these P/LPVs have implications for cancer screening, treatment, and cascade testing. As a result, it is recommended that all men with high-risk localized and metastatic PCa undergo routine germline testing. As more PCa patients undergo germline testing, it is important that clinicians and genetics experts recognize current disparities in germline testing rates among racial/ethnic minorities in the United States. The reasons for these disparities are multiple and require similarly manifold consideration to close the germline testing gap and reduce inequities in PCa screening, management, and treatment.

The role of genetic testing in prostate cancer screening, diagnosis, and treatment

PURPOSE OF REVIEW

This review provides an overview of the current role of genetic testing in prostate cancer screening, diagnosis, and treatment.

RECENT FINDINGS

Recent studies have uncovered few but highly penetrant rare pathogenic mutations (RPMs), in genes, such as BRCA2, with strong prostate cancer risk and outcomes associations. Over 260 single nucleotide polymorphisms (SNPs) have also been identified, each associated with small incremental prostate cancer risk and when combined in a polygenic risk score (PRS), they provide strong prostate cancer risk prediction but do not seem to predict outcomes. Tumor tissue sequencing can also help identify actionable somatic mutations in many patients with advanced prostate cancer and inform on their risk of harboring a germline pathogenic mutation.

SUMMARY

RPM testing, PRS testing, and tumor sequencing all have current and/or potential future roles in personalized prostate cancer care.