Germline alterations among Hispanic men with prostate cancer

Germline Genetic Variants in Cancer Predisposition Genes in Patients From Latin America and the Caribbean

The importance of having region-specific data when planning health interventions has become evident in recent years. Nonetheless, several world regions, including Latin America and the Caribbean (LAC), still face significant challenges. These regions need to develop strategies specifically designed to consider the inherent characteristics of their population composite and sociodemographic characteristics. More than 20% of the global cancer incidence arises in LAC. Yet, treatment, prevention, and follow-up guidelines in the area are frequently based on studies that mainly include patients from North America, Europe, and Asia. As personalized approaches become ubiquitous in medical practice, the amount of information emerging from LAC has risen considerably. In this review, we seek to present a comprehensive summary of the frequency of germline genetic variants in hereditary cancer syndromes in patients from LAC. The data highlight relevant differences in variants associated with LAC patients, including founder and recurrent variants, while showcasing potential features that might be relevant in oncology practices.

Experience using conventional compared to ancestry-based population descriptors in clinical genomics laboratories

Various scientific and professional groups, including the American Medical Association (AMA), American Society of Human Genetics (ASHG), American College of Medical Genetics (ACMG), and the National Academies of Sciences, Engineering, and Medicine (NASEM), have appropriately clarified that certain population descriptors, such as race and ethnicity, are social and cultural constructs with no basis in genetics. Nevertheless, these conventional population descriptors are routinely collected during the course of clinical genetic testing and may be used to interpret test results. Experts who have examined the use of population descriptors, both conventional and ancestry based, in human genetics and genomics have offered guidance on using these descriptors in research but not in clinical laboratory settings. This perspective piece is based on a decade of experience in a clinical genomics laboratory and provides insight into the relevance of conventional and ancestry-based population descriptors for clinical genetic testing, reporting, and clinical research on aggregated data. As clinicians, laboratory geneticists, genetic counselors, and researchers, we describe real-world experiences collecting conventional population descriptors in the course of clinical genetic testing and expose challenges in ensuring clarity and consistency in the use of population descriptors. Current practices in clinical genomics laboratories that are influenced by population descriptors are identified and discussed through case examples. In relation to this, we describe specific types of clinical research projects in which population descriptors were used and helped derive useful insights related to practicing and improving genomic medicine.

Germline genetic testing for prostate cancer: Ordering trends in the era of expanded hereditary cancer screening recommendations

PURPOSE

The availability of targeted therapies for advanced prostate cancer led to the expansion of national guidelines recommending germline genetic testing. The aim of this study was to describe recent trends in germline test ordering patterns for patients with prostate cancer.

MATERIALS AND METHODS

A retrospective cohort analysis of patients with prostate cancer who underwent germline testing through a single commercial laboratory (Invitae Corporation) between 2015-2020 was performed. Ordering trends between provider medical specialties were compared. Our primary hypothesis was that the proportion of tests ordered by urologists would increase over time.

RESULTS

In total, 17,256 prostate cancer patients underwent germline genetic testing; 14,400 patients had an ordering provider with an associated medical specialty and were included in the final comparison cohort. Total prostate cancer patients undergoing germline testing increased quarterly from 21 in Q2 of 2015 to 1,509 in Q3 of 2020. The proportion of tests ordered by urologists increased from 0% in Q2 2015 to 8.3% in Q3 2020 (P < 0.001). Compared to medical genetics, medical oncology, and other specialties, urology ordered more tests for patients under 70 years old (66% vs 51%-55%, P <0.004) and for patients who reported negative family history (25% vs 12%-20%, P = 0.012).

CONCLUSIONS

As awareness and indications for germline testing continue to expand, aggregate ordering volume is increasing, and urologists are becoming more involved in facilitating testing. This highlights the continued importance of educating urologists on the indications for and implications of germline genetic testing, as well as providing tools to support implementation.

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.