Assessing the clinical utility of genetic risk scores for targeted cancer screening.

BACKGROUND: Genome-wide association studies have identified thousands of disease-associated single nucleotide polymorphisms (SNPs). A subset of these SNPs may be additively combined to generate genetic risk scores (GRSs) that confer risk for a specific disease. Although the clinical validity of GRSs to predict risk of specific diseases has been well established, there is still a great need to determine their clinical utility by applying GRSs in primary care for cancer risk assessment and targeted intervention. METHODS: This clinical study involved 281 primary care patients without a personal history of breast, prostate or colorectal cancer who were 40-70 years old. DNA was obtained from a pre-existing biobank at NorthShore University HealthSystem. GRSs for colorectal cancer and breast or prostate cancer were calculated and shared with participants through their primary care provider. Additional data was gathered using questionnaires as well as electronic medical record information. A t-test or Chi-square test was applied for comparison of demographic and key clinical variables among different groups. RESULTS: The median age of the 281 participants was 58 years and the majority were female (66.6%). One hundred one (36.9%) participants received 2 low risk scores, 99 (35.2%) received 1 low risk and 1 average risk score, 37 (13.2%) received 1 low risk and 1 high risk score, 23 (8.2%) received 2 average risk scores, 21 (7.5%) received 1 average risk and 1 high risk score, and no one received 2 high risk scores. Before receiving GRSs, younger patients and women reported significantly more worry about risk of developing cancer. After receiving GRSs, those who received at least one high GRS reported significantly more worry about developing cancer. There were no significant differences found between gender, age, or GRS with regards to participants' reported optimism about their future health neither before nor after receiving GRS results. CONCLUSIONS: Genetic risk scores that quantify an individual's risk of developing breast, prostate and colorectal cancers as compared with a race-defined population average risk have potential clinical utility as a tool for risk stratification and to guide cancer screening in a primary care setting.

Differences in inherited risk among relatives of hereditary prostate cancer patients using genetic risk score.

PURPOSE: Family history assigns equivalent risk to all relatives based upon the degree of relationship. Recent genetic studies have identified single nucleotide polymorphisms (SNPs) that can be used to calculate a genetic risk score (GRS) to determine prostate cancer (PCa) risk. We sought to determine whether GRS can stratify PCa risk among individuals in families considered to be at higher risk due their family history of PCa. MATERIALS AND METHODS: Family members with hereditary PCa were recruited and genotyped for 17 SNPs associated with PCa. A GRS was calculated for all subjects. Analyses compared the distribution of GRS values among affected and unaffected family members of varying relationship degrees. RESULTS: Data was available for 789 family members of probands including 552 affected and 237 unaffected relatives. Median GRSs were higher among first-degree relatives compared to second- and third-degree relatives. In addition, GRS values among affected first- and second-degree relatives were significantly higher than unaffected relatives (P = 0.042 and P = 0.016, respectively). Multivariate analysis including GRS and degree of relationship demonstrated that GRS was a significant and independent predictor of PCa (OR 1.52, 95%CI 1.15-2.01). CONCLUSION: GRS is an easy-to-interpret, objective measure that can be used to assess differences in PCa risk among family members of affected men. GRS allows for further differentiation among family members, providing better risk assessment. While prospective validation studies are required, this information can help guide relatives in regards to the time of initiation and frequency of PCa screening.

Germline mutations in DNA repair genes are associated with bladder cancer risk and unfavourable prognosis.

OBJECTIVES: To perform a systematic evaluation of whether germline DNA repair gene mutations in bladder cancer (BCa) are associated with increased risk of BCa and aggressive disease. MATERIALS AND METHODS: Germline DNA from 98 patients with BCa was analysed for 54 DNA repair genes using a customized targeted sequencing panel. Population control data were obtained from the public databases the Exome Aggregation Consortium database and the Genome Aggregation Database. Mutation pathogenicity was annotated based on American College of Medical Genetics criteria, mutation frequencies in the general population and the ClinVar database. Mutation frequencies were compared based on case-control and case-case designs for disease risks, disease aggressiveness and outcomes. RESULTS: The frequency of pathogenic/likely pathogenic germline DNA repair gene mutations was 10.2% among patients with BCa. Within the subset of patients with carcinoma invading the bladder muscle, the frequency was 15.8%, ~2.4-fold higher than in patients with non-muscle invasive BCa (6.67%). The mutation frequency among patients with early-onset disease (at age <45 years) was ~3-fold higher than among those diagnosed after age 45 years (28.57% vs 8.79%). Mutation carriers had a significantly higher frequency of unfavourable clinical outcomes (disease recurrence or progression to metastatic BCa) than non-carriers (50.0% vs 13.64%; P = 0.013). CONCLUSION: Pathogenic and likely pathogenic mutations in DNA repair genes were associated with unfavourable prognosis of BCa.

A genetic variant near GATA3 implicated in inherited susceptibility and etiology of benign prostatic hyperplasia (BPH) and lower urinary tract symptoms (LUTS).

BACKGROUND: Benign prostatic hyperplasia (BPH) and associated lower urinary tract symptoms (LUTS) are common conditions. Little is known about their etiologies except that studies have suggested a substantial heritable component. Our objective is to provide a comprehensive, genome-wide evaluation of inherited risks and possible mechanisms of etiology in BPH. METHODS: We performed a three-stage, genome-wide association study (GWAS) of men from three independent populations, the REduction by DUtasteride of prostate Cancer Events (REDUCE) trial, the CLUE II cohort, and a Finnish hospital-based population. DNA samples were genotyped using the Illumina HumanOmniExpress BeadChip in REDUCE and CLUE II, and using the Sequenom iPLEX system for the confirmation stage in the Finnish population. A logistic regression model was used to evaluate the association between each SNP and BPH/LUTS. RESULTS: Fourteen SNPs reached P < 5.0 × 10-4 in the meta-analysis of the two GWASs (CLUE II and REDUCE). A total of 773 SNPs were chosen for the confirmation step in the Finish cohort. Only one SNP (rs17144046) located ∼489 kb downstream of GATA3 remained significant after correction for multiple testing (P < 6.5 × 10-5 ). This SNP marginally reached the GWAS significance level after performing a meta-analysis of the three stages (P-meta = 8.89 × 10-7 ). Expression quantitative trait loci (eQTL) analyses showed that the risk allele (G) of rs17144046 was significantly associated with increased expression of GATA3 (P = 0.017). Reported studies indicated a close correlation between GATA3 and BPH pathogenesis and progression. CONCLUSIONS: Rs17144046 located near GATA3 was significantly associated with BPH/LUTS in three independent populations, but did not reach a stringent GWAS significance level. Genetic variants of GATA3 may play a role in the inherited susceptibility and etiology of BPH/LUTS. Further research in this area is needed.

Reclassification of prostate cancer risk using sequentially identified SNPs: Results from the REDUCE trial.

BACKGROUND: Although the clinical validity of risk-associated single nucleotide polymorphisms (SNPs) for assessment of disease susceptibility has been consistently established, risk reclassification from increasing numbers of implicated risk-associated SNPs raises concern that it is premature for clinical use. Our objective is to assess the degree and impact of risk reclassification with the increasing number of SNPs. METHODS: A total of 3239 patients from the Reduction by Dutasteride of Prostate Cancer Events (REDUCE) trial were included. Four genetic risk scores (GRSs) were calculated based on sets of sequentially discovered prostate cancer (PCa) risk-associated SNPs (17, 34, 51, and 68 SNPs). RESULTS: Pair-wise correlation coefficients between sets of GRSs increased as more SNPs were included in the GRS: 0.80, 0.86, and 0.95 for 17 versus 34 SNPs, 34 versus 51 SNPs, and 51 versus 68 SNPs, respectively. Using a GRS of 1.5 as a cutoff for higher versus lower risk, reclassification rates of PCa risk decreased: 14.11%, 12.04%, and 8.15% for 17 versus 34 SNPs, 34 versus 51 SNPs, and 51 versus 68 SNPs, respectively. Evolving GRSs, nevertheless, provide a tool for further refining risk assessment. When all four sequential GRSs were considered, the detection rates of PCa for men whose GRSs were consistently <1.5, reclassified, and consistently ≥1.5 were 20.8%, 29.67%, and 39.26%, respectively (Ptrend = 1.12 × 10-8 ). In comparison, the detection rates of PCa in men with negative or positive family history were 23.75% and 31.78%, respectively. CONCLUSIONS: Risk assessment using currently available SNPs is justified. Multiple GRS values from evolving sets of SNPs provide a valuable tool for better refining risk.

Prostate health index significantly reduced unnecessary prostate biopsies in patients with PSA 2-10 ng/mL and PSA >10 ng/mL: Results from a Multicenter Study in China.

BACKGROUND: The performance of prostate health index (phi) in predicting prostate biopsy outcomes has been well established for patients with prostate-specific antigen (PSA) values between 2 and 10 ng/mL. However, the performance of phi remains unknown in patients with PSA >10 ng/mL, the vast majority in Chinese biopsy patients. We aimed to assess the ability of phi to predict prostate cancer (PCa) and high-grade disease (Gleason Score ≥7) on biopsy in a Chinese population. METHODS: This is a prospective, observational, multi-center study of consecutive patients who underwent a transrectal ultrasound guided prostate biopsy at four hospitals in Shanghai, China from August 2013 to December 2014. RESULTS: In the cohort of 1538 patients, the detection rate of PCa was 40.2%. phi had a significantly better predictive performance for PCa than total PSA (tPSA). The areas under the receiver operating characteristic curve (AUC) were 0.90 and 0.79 for phi and tPSA, respectively, P < 0.0001. A considerable proportion of patients in the cohort had PSAs >10 ng/mL (N = 838, 54.5%). The detection rates of PCa were 35.9% and 57.7% in patients with tPSA 10.1-20 and 20.1-50 ng/mL, respectively. The AUCs of phi (0.79 and 0.89, for these two groups, respectively) were also significantly higher than tPSA (0.57 and 0.63, respectively), both P < 0.0001. If a phi ≤35 was used as the cutoff, 599/1538 (39%) biopsies could have been avoided at a cost of missing small numbers of PCa patients: 49 (7.93%) PCa patients, including 18 (3.69%) high-grade tumors. CONCLUSIONS: Results from this study suggest that phi can be used to predict PCa and high-grade disease in Chinese men with high PSA levels (>10 ng/mL).

A multiparametric approach to improve upon existing prostate cancer screening and biopsy recommendations.

PURPOSE OF REVIEW: To provide an overview of how genetic, serum, and urine biomarkers can help identify men at high risk for prostate cancer (PCa) and aggressive disease and men who would benefit from prostate biopsy. RECENT FINDINGS: Screening for PCa is controversial because of concerns about overdiagnosis and overtreatment of nonlife-threatening tumors. Therefore, an approach to screening that includes a detailed family history with genetic testing of risk single nucleotide polymorphisms and high-penetrance genetic variants should be considered. After an elevated serum prostate-specific antigen (PSA) level has been confirmed, obtaining additional information (family history, biomarkers, and imaging) should be considered before recommending a prostate biopsy. SUMMARY: There are now genetic tests that can help identify men who would benefit from PSA testing. Additional biomarker and imaging tests should be offered to those men who are confirmed to have elevated PSA values. These new biomarkers and imaging tests can improve the specificity of PSA testing while missing a small percentage of high-grade tumors. The path forward involves a multiparametric risk assessment based on clinical data and these new tests.

A review of biosimilars for rheumatoid arthritis.

Biologics are effective, though costly, medications for the treatment of rheumatoid arthritis (RA). Biosimilars are medications that have no clinically meaningful differences when compared with their corresponding reference biologics but cost significantly less. The U.S. Food and Drug Administration and the European Medication Agency have approved biosimilars for adalimumab, etanercept, infliximab, and rituximab for the treatment of RA. Streamlined approval processes are expected to expedite biosimilar development while maintaining strict safety and efficacy standards. Encouragingly, many analyses have demonstrated the potential for massive healthcare savings if biosimilars are used over biologics. Challenges to biosimilar uptake, including patient and provider hesitancy, can likely be overcome with the education of all stakeholders within healthcare systems.

Personalized prostate cancer care: from screening to treatment.

Unprecedented progress has been made in genomic personalized medicine in the last several years, allowing for more individualized healthcare assessments and recommendations than ever before. However, most of this progress in prostate cancer (PCa) care has focused on developing and selecting therapies for late-stage disease. To address this issue of limited focus, we propose a model for incorporating genomic-based personalized medicine into all levels of PCa care, from prevention and screening to diagnosis, and ultimately to the treatment of both early-stage and late-stage cancers. We have termed this strategy the "Pyramid Model" of personalized cancer care. In this perspective paper, our objective is to demonstrate the potential application of the Pyramid Model to PCa care. This proactive and comprehensive personalized cancer care approach has the potential to achieve three important medical goals: reducing mortality, improving quality of life and decreasing both individual and societal healthcare costs.

Population-standardized genetic risk score: the SNP-based method of choice for inherited risk assessment of prostate cancer.

Several different approaches are available to clinicians for determining prostate cancer (PCa) risk. The clinical validity of various PCa risk assessment methods utilizing single nucleotide polymorphisms (SNPs) has been established; however, these SNP-based methods have not been compared. The objective of this study was to compare the three most commonly used SNP-based methods for PCa risk assessment. Participants were men (n = 1654) enrolled in a prospective study of PCa development. Genotypes of 59 PCa risk-associated SNPs were available in this cohort. Three methods of calculating SNP-based genetic risk scores (GRSs) were used for the evaluation of individual disease risk such as risk allele count (GRS-RAC), weighted risk allele count (GRS-wRAC), and population-standardized genetic risk score (GRS-PS). Mean GRSs were calculated, and performances were compared using area under the receiver operating characteristic curve (AUC) and positive predictive value (PPV). All SNP-based methods were found to be independently associated with PCa (all P < 0.05; hence their clinical validity). The mean GRSs in men with or without PCa using GRS-RAC were 55.15 and 53.46, respectively, using GRS-wRAC were 7.42 and 6.97, respectively, and using GRS-PS were 1.12 and 0.84, respectively (all P < 0.05 for differences between patients with or without PCa). All three SNP-based methods performed similarly in discriminating PCa from non-PCa based on AUC and in predicting PCa risk based on PPV (all P > 0.05 for comparisons between the three methods), and all three SNP-based methods had a significantly higher AUC than family history (all P < 0.05). Results from this study suggest that while the three most commonly used SNP-based methods performed similarly in discriminating PCa from non-PCa at the population level, GRS-PS is the method of choice for risk assessment at the individual level because its value (where 1.0 represents average population risk) can be easily interpreted regardless of the number of risk-associated SNPs used in the calculation.