An analysis of the association between prostate cancer risk loci, PSA levels, disease aggressiveness and disease-specific mortality

Analysis of genetic biomarkers, polymorphisms in ADME-related genes and their impact on pharmacotherapy for prostate cancer

Prostate cancer (PCa) is a non-cutaneous malignancy in males with wide variation in incidence rates across the globe. It is the second most reported cause of cancer death. Its etiology may have been linked to genetic polymorphisms, which are not only dominating cause of malignancy casualties but also exerts significant effects on pharmacotherapy outcomes. Although many therapeutic options are available, but suitable candidates identified by useful biomarkers can exhibit maximum therapeutic efficacy. The single-nucleotide polymorphisms (SNPs) reported in androgen receptor signaling genes influence the effectiveness of androgen receptor pathway inhibitors and androgen deprivation therapy. Furthermore, SNPs located in genes involved in transport, drug metabolism, and efflux pumps also influence the efficacy of pharmacotherapy. Hence, SNPs biomarkers provide the basis for individualized pharmacotherapy. The pharmacotherapeutic options for PCa include hormonal therapy, chemotherapy (Docetaxel, Mitoxantrone, Cabazitaxel, and Estramustine, etc.), and radiotherapy. Here, we overview the impact of SNPs reported in various genes on the pharmacotherapy for PCa and evaluate current genetic biomarkers with an emphasis on early diagnosis and individualized treatment strategy in PCa.

Biochemical activity induced by a germline variation in KLK3 (PSA) associates with cellular function and clinical outcome in prostate cancer

Genetic variation at the 19q13.3 KLK locus is linked with prostate cancer susceptibility. The non-synonymous KLK3 SNP, rs17632542 (c.536T>C; Ile163Thr-substitution in PSA) is associated with reduced prostate cancer risk, however, the functional relevance is unknown. Here, we identify that the SNP variant-induced change in PSA biochemical activity as a previously undescribed function mediating prostate cancer pathogenesis. The 'Thr' PSA variant led to small subcutaneous tumours, supporting reduced prostate cancer risk. However, 'Thr' PSA also displayed higher metastatic potential with pronounced osteolytic activity in an experimental metastasis in-vivo model. Biochemical characterization of this PSA variant demonstrated markedly reduced proteolytic activity that correlated with differences in in-vivo tumour burden. The SNP is associated with increased risk for aggressive disease and prostate cancer-specific mortality in three independent cohorts, highlighting its critical function in mediating metastasis. Carriers of this SNP allele had reduced serum total PSA and a higher free/total PSA ratio that could contribute to late biopsy decisions and delay in diagnosis. Our results provide a molecular explanation for the prominent 19q13.3 KLK locus, rs17632542 SNP, association with a spectrum of prostate cancer clinical outcomes.

SNPs at SMG7 Associated with Time from Biochemical Recurrence to Prostate Cancer Death

BACKGROUND

A previous genome-wide association study identified several loci with genetic variants associated with prostate cancer survival time in two cohorts from Sweden. Whether these variants have an effect in other populations or if their effect is homogenous across the course of disease is unknown.

METHODS

These variants were genotyped in a cohort of 1,298 patients. Samples were linked with age, PSA level, Gleason score, cancer stage at surgery, and times from surgery to biochemical recurrence to death from prostate cancer. SNPs rs2702185 and rs73055188 were tested for association with prostate cancer-specific survival time using a multivariate Cox proportional hazard model. SNP rs2702185 was further tested for association with time to biochemical recurrence and time from biochemical recurrence to death with a multi-state model.

RESULTS

SNP rs2702185 at SMG7 was associated with prostate cancer-specific survival time, specifically the time from biochemical recurrence to prostate cancer death (HR, 2.5; 95% confidence interval, 1.4-4.5; P = 0.0014). Nine variants were in linkage disequilibrium (LD) with rs2702185; one, rs10737246, was found to be most likely to be functional based on LD patterns and overlap with open chromatin. Patterns of open chromatin and correlation with gene expression suggest that this SNP may affect expression of SMG7 in T cells.

CONCLUSIONS

The SNP rs2702185 at the SMG7 locus is associated with time from biochemical recurrence to prostate cancer death, and its LD partner rs10737246 is predicted to be functional.

IMPACT

These results suggest that future association studies of prostate cancer survival should consider various intervals over the course of disease.

KLK3 germline mutation I179T complements DNA repair genes for predicting prostate cancer progression

BACKGROUND

Germline mutations in DNA repair genes and KLK3 have been associated with adverse prostate cancer (PCa) outcomes in separate studies but never jointly. The objective of this study is to simultaneously assess these two types of germline mutations.

METHODS

Germline rare pathogenic mutations (RPMs) in 9 commonly tested DNA repair genes and KLK3 variants were tested for their associations with PCa progression in two PCa cohorts: (1) hospital-based PCa patients treated with radical surgery at the Johns Hopkins Hospital (JHH, N = 1943), and (2) population-based PCa patients in the UK Biobank (UKB, N = 10,224). Progression was defined as metastasis and/or PCa-specific death (JHH) and PCa-specific death (UKB). RPMs of DNA repair genes were annotated using the American College of Medical Genetics recommendations. Known KLK3 variants were genotyped. Associations were tested using a logistic regression model adjusting for genetic background (top ten principal components).

RESULTS

In the JHH, 3.2% (59/1,843) of patients had RPMs in 9 DNA repair genes; odds ratio (OR, 95% confidence interval) for progression was 2.99 (1.6-5.34), P < 0.001. In comparison, KLK3 I179T mutation was more common; 9.7% (189/1,943) carried the mutation, OR = 1.6 (1.05-2.37), P = 0.02. Similar results were found in the UKB. Both types of mutations remained statistically significant in multivariable analyses. In the combined cohort, compared to patients without any mutations (RPMs-/KLK3-), RPMs-/KLK3+ patients had modestly increased risk for progression [OR = 1.54 (1.15-2.02), P = 0.003], and RPMs+/KLK3+ patients had greatly increased risk for progression [OR = 5.41 (2.04-12.99), P < 0.001]. Importantly, associations of mutations with PCa progression were found in patients with clinically defined low- or intermediate risk for disease progression.

CONCLUSIONS

Two different cohorts consistently demonstrate that KLK3 I179T and RPMs of nine commonly tested DNA repair genes are complementary for predicting PCa progression. These results are highly relevant to PCa germline testing and provide critical information for KLK3 I179T to be considered in guidelines.

KLK3 SNP-SNP interactions for prediction of prostate cancer aggressiveness

Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP-SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10-9) and 3145 (P < 1 × 10-5) SNP-SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene-gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP-SNP interactions were supported by gene expression and protein-protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.

Prostate cancer risk SNP rs10993994 is a trans-eQTL for SNHG11 mediated through MSMB

How genome-wide association studies-identified single-nucleotide polymorphisms (SNPs) affect remote genes remains unknown. Expression quantitative trait locus (eQTL) association meta-analysis on 496 prostate tumor and 602 normal prostate samples with 117 SNPs revealed novel cis-eQTLs and trans-eQTLs. Mediation testing and colocalization analysis demonstrate that MSMB is a cis-acting mediator for SNHG11 (P < 0.01). Removing rs10993994 in LNCaP cell lines by CRISPR/Cas9 editing shows that the C-allele corresponds with an over 100-fold increase in MSMB expression and 5-fold increase in SNHG11 compared with the T-allele. Colocalization analysis confirmed that the same set of SNPs associated with MSMB expression is associated with SNHG11 expression (posterior probability of shared variants is 66.6% in tumor and 91.4% in benign). These analyses further demonstrate variants driving MSMB expression differ in tumor and normal, suggesting regulatory network rewiring during tumorigenesis.

Fumarate hydratase FH c.1431_1433dupAAA (p.Lys477dup) variant is not associated with cancer including renal cell carcinoma

Fumarate hydratase (FH) mutations underpin the autosomal recessive syndrome. FH deficiency and the autosomal dominant syndrome hereditary leiomyomatosis and renal cell carcinoma (HLRCC). The FH c.1431_1433dupAAA (p.Lys477dup) genomic alteration has been conclusively shown to contribute to FH deficiency when occurring with another FH germline alteration. However, a sufficiently large dataset has been lacking to conclusively determine its clinical significance to cancer predisposition in the heterozygous state. We reviewed a series of 7,571 patients with cancer who received germline results through MSK-IMPACT testing at the Memorial Sloan Kettering Cancer Center. The FH c.1431_1433dupAAA (p.Lys477dup) variant was detected in 24 individuals, none of whom was affected with renal cancer. Eleven of the 372 patients with renal cancer were identified to carried pathogenic FH variants associated with HLRCC. None of these 372 patients with renal cancer carried the FH c.1431_1433dupAAA variant. Our data indicate the FH c.1431_1433dupAAA is not associated with cancer including renal cell carcinoma.

Genome-wide Scan Identifies Role for AOX1 in Prostate Cancer Survival

BACKGROUND

Most men diagnosed with prostate cancer have low-risk cancers. How to predict prostate cancer progression at the time of diagnosis remains challenging.

OBJECTIVE

To identify single nucleotide polymorphisms (SNPs) associated with death from prostate cancer.

DESIGN, SETTING, AND PARTICIPANTS

Blood samples from 11 506 men in Sweden were collected during 1991-1996. Of these, 1053 men were diagnosed with prostate cancer and 245 died from the disease. Stage and grade at diagnosis and outcome information were obtained, and DNA from all cases was genotyped.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

A total of 6 126 633 SNPs were tested for association with prostate-cancer-specific survival time using a Cox proportional hazard model, adjusted for age, stage, and grade at diagnosis. A value of 1×10-6 was used as suggestive significance threshold. Positive candidate SNPs were tested for association with gene expression using expression quantitative trait locus analysis.

RESULTS AND LIMITATIONS

We found 12 SNPs at seven independent loci associated with prostate-cancer-specific survival time. One of 6 126 633 SNPs tested reached genome-wide significance (p<5×10-8) and replicated in an independent cohort: rs73055188 (p=5.27×10-9, per-allele hazard ratio [HR]=2.27, 95% confidence interval [CI] 1.72-2.98) in the AOX1 gene. A second SNP reached a suggestive level of significance (p<1×10-6) and replicated in an independent cohort: rs2702185 (p=7.1×10-7, per-allele HR=2.55, 95% CI=1.76-3.69) in the SMG7 gene. The SNP rs73055188 is correlated with AOX1 expression levels, which is associated with biochemical recurrence of prostate cancer in independent cohorts. This association is yet to be validated in other ethnic groups.

CONCLUSIONS

The SNP rs73055188 at the AOX1 locus is associated with prostate-cancer-specific survival time, and AOX1 gene expression level is correlated with biochemical recurrence of prostate cancer.

PATIENT SUMMARY

We identify two genetic markers that are associated with prostate-cancer-specific survival time.

Simple Methods and Rational Design for Enhancing Aptamer Sensitivity and Specificity

Aptamers are structured nucleic acid molecules that can bind to their targets with high affinity and specificity. However, conventional SELEX (Systematic Evolution of Ligands by EXponential enrichment) methods may not necessarily produce aptamers of desired affinity and specificity. Thus, to address these questions, this perspective is intended to suggest some approaches and tips along with novel selection methods to enhance evolution of aptamers. This perspective covers latest novel innovations as well as a broad range of well-established approaches to improve the individual binding parameters (aptamer affinity, avidity, specificity and/or selectivity) of aptamers during and/or post-SELEX. The advantages and limitations of individual aptamer selection methods and post-SELEX optimizations, along with rational approaches to overcome these limitations are elucidated in each case. Further the impact of chosen selection milieus, linker-systems, aptamer cocktails and detection modules utilized in conjunction with target-specific aptamers, on the overall assay performance are discussed in detail, each with its own advantages and limitations. The simple variations suggested are easily available for facile implementation during and/or post-SELEX to develop ultrasensitive and specific assays. Finally, success studies of established aptamer-based assays are discussed, highlighting how they utilized some of the suggested methodologies to develop commercially successful point-of-care diagnostic assays.

Environmental factors and risk of aggressive prostate cancer among a population of New Zealand men - a genotypic approach

Prostate cancer is one of the most significant health concerns for men worldwide. Numerous researchers carrying out molecular diagnostics have indicated that genetic interactions with biological and behavioral factors play an important role in the overall risk and prognosis of this disease. Single nucleotide polymorphisms (SNPs) are increasingly becoming strong biomarker candidates to identify susceptibility to prostate cancer. We carried out a gene × environment interaction analysis linked to aggressive and non-aggressive prostate cancer (PCa) with a number of SNPs. By using this method, we identified the susceptible alleles in a New Zealand population, and examined the interaction with environmental factors. We have identified a number of SNPs that have risk associations both with and without environmental interaction. The results indicate that certain SNPs are associated with disease vulnerability based on behavioral factors. The list of genes with SNPs identified as being associated with the risk of PCa in a New Zealand population is provided in the graphical abstract.

Identification of Novel Epigenetic Markers of Prostate Cancer by NotI-Microarray Analysis

A significant need for reliable and accurate cancer diagnostics and prognosis compels the search for novel biomarkers that would be able to discriminate between indolent and aggressive tumors at the early stages of disease. The aim of this work was identification of potential diagnostic biomarkers for characterization of different types of prostate tumors. NotI-microarrays with 180 clones associated with chromosome 3 genes/loci were applied to determine genetic and epigenetic alterations in 33 prostate tumors. For 88 clones, aberrations were detected in more than 10% of tumors. The major types of alterations were DNA methylation and/or deletions. Frequent methylation of the discovered loci was confirmed by bisulfite sequencing on selective sampling of genes: FGF12, GATA2, and LMCD1. Three genes (BHLHE40, BCL6, and ITGA9) were tested for expression level alterations using qPCR, and downregulation associated with hypermethylation was shown in the majority of tumors. Based on these data, we proposed the set of potential biomarkers for detection of prostate cancer and discrimination between prostate tumors with different malignancy and aggressiveness: BHLHE40, FOXP1, LOC285205, ITGA9, CTDSPL, FGF12, LOC440944/SETD5, VHL, CLCN2, OSBPL10/ZNF860, LMCD1, FAM19A4, CAND2, MAP4, KY, and LRRC58. Moreover, we probabilistically estimated putative functional relations between the genes within each set using the network enrichment analysis.