Jianfeng Xu

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.

Clinical validity and utility of genetic risk scores in prostate cancer.

Current issues related to prostate cancer (PCa) clinical care (e.g., over-screening, over-diagnosis, and over-treatment of nonaggressive PCa) call for risk assessment tools that can be combined with family history (FH) to stratify disease risk among men in the general population. Since 2007, genome-wide association studies (GWASs) have identified more than 100 SNPs associated with PCa susceptibility. In this review, we discuss (1) the validity of these PCa risk-associated SNPs, individually and collectively; (2) the various methods used for measuring the cumulative effect of multiple SNPs, including genetic risk score (GRS); (3) the adequate number of SNPs needed for risk assessment; (4) reclassification of risk based on evolving numbers of SNPs used to calculate genetic risk, (5) risk assessment for men from various racial groups, and (6) the clinical utility of genetic risk assessment. In conclusion, data available to date support the clinical validity of PCa risk-associated SNPs and GRS in risk assessment among men with or without FH. PCa risk-associated SNPs are not intended for diagnostic use; rather, they should be used the same way as FH. Combining GRS and FH can significantly improve the performance of risk assessment. Improved risk assessment may have important clinical utility in targeted PCa testing. However, clinical trials are urgently needed to evaluate this clinical utility as well as the acceptance of GRS by patients and physicians.

Clinically available RNA profiling tests of prostate tumors: utility and comparison

In the postscreening era, physicians are in need of methods to discriminate aggressive from nonaggressive prostate cancer (PCa) to reduce overdiagnosis and overtreatment. However, studies have shown that prognoses (e.g., progression and mortality) differ even among individuals with similar clinical and pathological characteristics. Existing risk classifiers (TMN grading system, Gleason score, etc.) are not accurately enough to represent the biological features of PCa. Using new genomic technologies, novel biomarkers and classifiers have been developed and shown to add value to clinical or pathological risk factors for predicting aggressive disease. Among them, RNA testing (gene expression analysis) is useful because it can not only reflect genetic variations but also reflect epigenetic regulations. Commercially available RNA profiling tests (Oncotype Dx, Prolaris, and Decipher) have demonstrated strong abilities to discriminate PCa with poor prognosis from less aggressive diseases. For instance, these RNA profiling tests can predict disease progression in active surveillance patients or early recurrence after radical treatments. These tests may offer more dependable methods for PCa prognosis prediction to make more accurate and personal medical decisions.

Genetic variants in 5p13.2 and 7q21.1 are associated with treatment for benign prostatic hyperplasia with the α-adrenergic receptor antagonist

Abstract Background: The etiology of benign prostatic hyperplasia (BPH) has not been well established. The preferred medical treatment for many men with symptomatic benign prostatic hyperplasia is either an α-adrenergic receptor antagonist (α-blocker), or a 5α-reductase inhibitor. Single nucleotide polymorphism (SNP) is a powerful tool for successful implementation of individualized treatment. Methods: Eighteen SNPs associated with drug efficacy in a Chinese population were genotyped in 790 BPH cases (330 aggressive and 460 non-aggressive BPH cases) and 1008 controls. All BPH patients were treated with α-adrenergic blockers for at least 9 months. We tested the associations between tagging single nucleotide polymorphism and BPH risk/aggressiveness, clinical characteristics at baseline, including the International Prostate Symptom Score (IPSS) and total prostate volume, and changes in clinical characteristics after treatment. Results: There were nine SNPs associated with BPH risk, clinical progression and therapeutic effect. (1) There were nine tSNPs been chosen in CYP3A4, CYP3A5 and RANBP3L genes. (2) The SNP, rs16902947 in RANBP3L at 5p13.2 (pu2009=u2009.01), was significantly associated with BPH. (3) We found two SNPs, rs16902947 in RANBP3L at 5p13.2 (pu2009=u2009.0388) and rs4646437 in CYP3A4 at 7q21.1 (pu2009=u2009.0325), associated with drug effect. (4) Allele “G” for rs16902947 was found to be risk alleles for BPH risk (OR=u20092.357, 95%CI 1.01–1.48). The “A” allele of rs4646437 was associated with lower IPSS at baseline (β=u2009−0.4232, p=u2009.03255). Conclusions: rs16902947, rs16902947 and rs4646437 single nucleotide polymorphisms are significantly associated with the clinical characteristics of benign prostatic hyperplasia and the efficacy of benign prostatic hyperplasia treatment.

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.

Abstract 812: Association between variants in genes involved in the immune response and prostate cancer risk in men randomized to finasteride in the Prostate Cancer Prevention Trial

Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LAnnBackground: We reported that some, but not all single nucleotide polymorphisms (SNPs) in select immune response genes are associated with prostate cancer in the Prostate Cancer Prevention Trial* (PCPT) placebo arm. Here, we investigated whether these same SNPs are associated with risk in men randomized to finasteride, which is known to increase intraprostatic inflammation. Methods: 16 candidate SNPs in IL1, IL2, IL4, IL6, IL8, IL10, IL12(p40), IFNG, MSR1, RNASEL, TLR4, and TNFA and 7 tagSNPs in IL10 were genotyped in 625 prostate cancer cases, and 532 controls negative for cancer on an end-of-study biopsy nested in the PCPT finasteride arm. Cases and controls were non-Hispanic white men. We used logistic regression to estimate log-additive odds ratios (OR) and 95% confidence intervals (CI) adjusting for age and family history (matching factors). Results: Minor alleles of rs2243250 (T) in IL4 (OR = 1.46, 95% CI 1.03-2.08, P-trend = 0.03), rs1800896 (G) in IL10 (OR = 0.77, 95% CI 0.61-0.96, P-trend = 0.02), rs2430561 (A) in IFNG (OR = 1.33, 95% CI 1.02-1.74; P-trend = 0.04), rs3747531 (C) in MSR1 (OR = 0.55, 95% CI 0.32-0.95; P-trend = 0.03), and possibly rs4073 (A) in IL8 (OR = 0.81, 95% CI 0.64-1.01, P-trend = 0.06) were associated with higher- (Gleason 7-10; N = 222), but not lower- (Gleason 2-6; N = 380) grade prostate cancer. In men with low PSA (<2 ng/mL), these associations were attenuated and/or no longer significant, whereas inverse associations with higher-grade disease were apparent for minor alleles of rs1800795 (C: OR = 0.70, 95% CI 0.51-0.94, P-trend = 0.02) and rs1800797 (A: OR = 0.72, 95% CI 0.53-0.98, P-trend = 0.04) in IL6. While some IL10 tagSNPs were associated with lower- and higher-grade prostate cancer, distributions of IL10 haplotypes did not differ from controls, except possibly among those with low PSA (P = 0.07). Conclusion: In the PCPT finasteride arm, variation in genes involved in the immune response, including possibly IL8 and IL10 as in the placebo arm, may be associated with prostate cancer, especially higher-grade disease, but we cannot rule out PSA-associated detection bias or chance due to multiple testing.Funding: P01 CA108964, U10 CA37429, UM1 CA182883, T32 CA009314. *A SWOG-Coordinated Study S9217nnCitation Format: Danyelle A. Winchester, Cathee Till, Jianfeng Xu, Ian M. Thompson, Scott M. Lippmann, Howard L. Parnes, Angelo M. De Marzo, Charles G. Drake, Elizabeth A. Platz, The PCPT P01 Project 4 Research Team. Association between variants in genes involved in the immune response and prostate cancer risk in men randomized to finasteride in the Prostate Cancer Prevention Trial. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 812.

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

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.

Chapter 12 – Prostate Cancer

In personalized medicine (PM), the aim is to provide individual risk assessment for medical conditions, or to predict the efficacy of measures intended to monitor, prevent, or treat these conditions (http://www.personalizedmedicinecoalition.org). The approaches of PM could be important in addressing clinical and public health issues involved in a variety of diseases, including cancers that are detected via population-level screening. This is particularly relevant to prostate cancer (PCa), where concerns have been raised regarding prostate-specific antigen screening, subsequent overdiagnosis of low-grade diseases, and ultimately overtreatment of many indolent cancers. These interrelated issues have prompted a significant effort to identify markers that can effectively differentiate individuals who have different risks for PCa onset or progression. Improved risk estimation may help to address this major public health problem, as the prostate is the most common site of cancer diagnosis, accounting for approximately 26% of all new cancer diagnoses and 9% of cancer deaths in US men. This translates to an estimated 220,800 PCa diagnoses and 27,540 deaths in US men each year (Siegel et al., 2015. CA Cancer J Clin).

Translation of genomics and epigenomics in prostate cancer: progress and promising directions

During the last several years, exciting discoveries have been made in prostate cancer (PCa) as a result of significant advances in genomic technology and information. For example, using genome-wide association studies, more than 100 inherited genetic variants associated with PCa risk have been identified. Similarly, with the use of next-generation sequencing, various types of recurrent somatic DNA alterations in prostate tumors have been revealed. Some of these discoveries have potential clinical application to supplement existing tools for better decision-making regarding the need for screening, biopsy, and treatment of PCa. However, because of the complexity of these genomic findings and incomplete understanding of the genetics of this multifactorial disease, this potential has not yet been fully realized.

Abstract 4605: Variation in genes involved in the immune response and prostate cancer risk in the placebo arm of the Prostate Cancer Prevention Trial

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PAnnBackground: We previously found that inflammation in benign prostate tissue is associated with increased odds of prostate cancer especially higher-grade disease. To understand this link, we evaluated the association between single nucleotide polymorphisms (SNPs) in immune response genes and prostate cancer risk in the placebo arm of the Prostate Cancer Prevention Trial (PCPT).xa0Men were screened yearly and if not diagnosed with prostate cancer during the trial, underwent an end-of-study biopsy. Thus, in a subanalysis, we were able to study associations in men with low PSA; i.e., men in whom bias due to any link between inflammation and elevated PSA, an indication for biopsy, is reduced.nnMethods:nnWe genotyped 16 candidate SNPs in IL1b, IL2, IL4, IL6, IL8, IL10, IL12(p40), IFNG, MSR1, RNASEL, TLR4, and TNFA and 7 tagSNPs in IL10 in 881 prostate cancer cases and 848 controls negative for cancer on an end-of-study biopsy. Cases and controls were non-Hispanic white and frequency matched on age and family history. We classified cases as lower (Gleason sum <7; N = 674) and higher (7-10; N = 172) grade. We used logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusting for age and family history.xa0nnResults: The minor allele (C) of rs3212227 in IL12(p40) was associated with an increased risk of total (log additive: OR = 1.30, 95% CI 1.10-1.53; P-trend = 0.0017) and lower-grade (OR = 1.36, 95% CI 1.15-1.62; P-trend = 0.0004) prostate cancer. The minor allele (A) of rs4073 in IL8 was possibly associated with a decreased risk of higher-grade (OR = 0.81, 95% CI 0.64-1.02; P-trend = 0.07), but not total disease. None of the other candidates was associated with risk. The minor alleles of IL10 tagSNPs rs1800890 (A; OR = 0.87, 95% CI: 0.75-0.99; P-trend = 0.04) and rs3021094 (C; OR = 1.31, 95% CI 1.03-1.66, P-trend = 0.03) were associated with prostate cancer risk; the latter also with lower- (P-trend = 0.04) and possibly higher- (P-trend = 0.06) grade disease. These patterns were generally similar among men with prostate specific antigen (PSA)<2 ng/mL at biopsy. Conclusion: Our study suggests that variation in some immune response genes possibly may be associated with prostate cancer risk. These associations were not fully explained by PSA-associated detection bias as they remained in men with low PSA. Our findings provide some support to inflammations role in the etiology of prostate cancer.nnFunding: P01 CA108964, U10 CA37429, UM1 CA182883, T32 CA009314. *A SWOG-Coordinated Study S9217nnxa0nnxa0nnxa0nnCitation Format: Danyelle A. Winchester, Cathee Till, Phyllis J. Goodman, Catherine M. Tangen, Regina M. Santella, Teresa L. Johnson-Pais, Robin J. Leach, Jianfeng Xu, S. Lilly Zheng, Ian M. Thompson, M. Scott Lucia, Scott M. Lippmann, Howard L. Parnes, Paul J. Dluzniewski, William B. Isaacs, Angelo M. De Marzo, Charles G. Drake, Elizabeth A. Platz. Variation in genes involved in the immune response and prostate cancer risk in the placebo arm of the Prostate Cancer Prevention Trial. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4605. doi:10.1158/1538-7445.AM2015-4605