Genome-wide two-locus epistasis scans in prostate cancer using two European populations

Approximately 40 single nucleotide polymorphisms (SNPs) that are associated with prostate cancer (PCa) risk have been identified through genome-wide association studies (GWAS). However, these GWAS-identified PCa risk-associated SNPs can explain only a small proportion of heritability (~13%) of PCa risk. Gene-gene interaction is speculated to be one of the major factors contributing to the so-called missing heritability. To evaluate the gene-gene interaction and PCa risk, we performed a two-stage genome-wide gene-gene interaction scan using a novel statistical approach named "Boolean Operation-based Screening and Testing". In the first stage, we exhaustively evaluated all pairs of SNP-SNP interactions for ~500,000 SNPs in 1,176 PCa cases and 1,101 control subjects from the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) study. No SNP-SNP interaction reached a genome-wide significant level of 4.4E-13. The second stage of the study involved evaluation of the top 1,325 pairs of SNP-SNP interactions (P(interaction) <1.0E-08) implicated in CGEMS in another GWAS population of 1,964 PCa cases from the Johns Hopkins Hospital (JHH) and 3,172 control subjects from the Illumina iControl database. Sixteen pairs of SNP-SNP interactions were significant in the JHH population at a P(interaction) cutoff of 0.01. However, none of the 16 pairs of SNP-SNP interactions were significant after adjusting for multiple tests. The current study represents one of the first attempts to explore the high-dimensional etiology of PCa on a genome-wide scale. Our results suggested a list of SNP-SNP interactions that can be followed in other replication studies.     

Characterizing associations and SNP-environment interactions for GWAS-identified prostate cancer risk markers--results from BPC3

Genome-wide association studies (GWAS) have identified multiple single nucleotide polymorphisms (SNPs) associated with prostate cancer risk. However, whether these associations can be consistently replicated, vary with disease aggressiveness (tumor stage and grade) and/or interact with non-genetic potential risk factors or other SNPs is unknown. We therefore genotyped 39 SNPs from regions identified by several prostate cancer GWAS in 10,501 prostate cancer cases and 10,831 controls from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). We replicated 36 out of 39 SNPs (P-values ranging from 0.01 to 10⁻²⁸). Two SNPs located near KLK3 associated with PSA levels showed differential association with Gleason grade (rs2735839, P = 0.0001 and rs266849, P = 0.0004; case-only test), where the alleles associated with decreasing PSA levels were inversely associated with low-grade (as defined by Gleason grade <8) tumors but positively associated with high-grade tumors. No other SNP showed differential associations according to disease stage or grade. We observed no effect modification by SNP for association with age at diagnosis, family history of prostate cancer, diabetes, BMI, height, smoking or alcohol intake. Moreover, we found no evidence of pair-wise SNP-SNP interactions. While these SNPs represent new independent risk factors for prostate cancer, we saw little evidence for effect modification by other SNPs or by the environmental factors examined.     

Polygenic Analysis of Late-Onset Alzheimer’s Disease from Mainland China

Recently, a number of single nucleotide polymorphisms (SNPs) were identified to be associated with late-onset Alzheimer disease (LOAD) through genome-wide association study data. Identification of SNP-SNP interaction played an important role in better understanding genetic basis of LOAD. In this study, fifty-eight SNPs were screened in a cohort of 229 LOAD cases and 318 controls from mainland China, and their interaction was evaluated by a series of analysis methods. Seven risk SNPs and six protective SNPs were identified to be associated with LOAD. Risk SNPs included rs9331888 (CLU), rs6691117 (CR1), rs4938933 (MS4A), rs9349407 (CD2AP), rs1160985 (TOMM40), rs4945261 (GAB2) and rs5984894 (PCDH11X); Protective SNPs consisted of rs744373 (BIN1), rs1562990 (MS4A), rs597668 (EXOC3L2), rs9271192 (HLA-DRB5/DRB1), rs157581 and rs11556505 (TOMM40). Among positive SNPs presented above, we found the interaction between rs4938933 (risk) and rs1562990 (protective) in MS4A weakened their each effect for LOAD; for three significant SNPs in TOMM40, their cumulative interaction induced the two protective SNPs effects lost and made the risk SNP effect aggravate for LOAD. Finally, we found rs6656401-rs3865444 (CR1-CD33) pairs were significantly associated with decreasing LOAD risk, while rs28834970-rs6656401 (PTK2B-CR1), and rs28834970-rs6656401 (PTK2B-CD33) were associated with increasing LOAD risk. In a word, our study indicates that SNP-SNP interaction existed in the same gene or cross different genes, which could weaken or aggravate their initial single effects for LOAD.     

Genetic Polymorphisms at TIMP3 Are Associated with Survival of Adenocarcinoma of the Gastroesophageal Junction

The poor survival of adenocarcinomas of the gastroesophageal junction (GEJ) makes them clinically important. Discovery of host genetic factors that affect outcome may guide more individualized treatment. This study tests whether constitutional genetic variants in matrix metalloproteinases (MMP) and tissue inhibitors of metalloproteinases (TIMP) genes are associated with outcome of GEJ adenocarcinoma. Single nucleotide polymorphisms (SNPs) at four TIMP (TIMP1-4) and three MMP genes (MMP2, MMP7 and MMP9) were genotyped in DNA samples from a prospective cohort of patients with primary adenocarcinoma of the GEJ admitted to the British Columbia Cancer Agency. Cox proportional hazards regression, with adjustment for patient, disease and treatment variables, was used to estimate the association of SNPs with survival. Genotypes for 85 samples and 48 SNPs were analyzed. Four SNPs across TIMP3, (rs130274, rs715572, rs1962223 and rs5754312) were associated with survival. Interaction analyses revealed that the survival associations with rs715572 and rs5754312 are specific and significant for 5FU+cisplatin treated patients. Sanger sequencing of the TIMP3 coding and promoter regions revealed an additional SNP, rs9862, also associated with survival. TIMP3 genetic variants are associated with survival and may be potentially useful in optimizing treatment strategies for individual patients.     

Assessing SNP-SNP Interactions among DNA Repair,Modification and Metabolism Related Pathway Genes in Breast Cancer Susceptibility

Genome-wide association studies (GWASs) have identified low-penetrance common variants (i.e., single nucleotide polymorphisms, SNPs) associated with breast cancer susceptibility. Although GWASs are primarily focused on single-locus effects, gene-gene interactions (i.e., epistasis) are also assumed to contribute to the genetic risks for complex diseases including breast cancer. While it has been hypothesized that moderately ranked (P value based) weak single-locus effects in GWASs could potentially harbor valuable information for evaluating epistasis, we lack systematic efforts to investigate SNPs showing consistent associations with weak statistical significance across independent discovery and replication stages. The objectives of this study were i) to select SNPs showing single-locus effects with weak statistical significance for breast cancer in a GWAS and/or candidate-gene studies; ii) to replicate these SNPs in an independent set of breast cancer cases and controls; and iii) to explore their potential SNP-SNP interactions contributing to breast cancer susceptibility. A total of 17 SNPs related to DNA repair, modification and metabolism pathway genes were selected since these pathways offer a priori knowledge for potential epistatic interactions and an overall role in breast carcinogenesis. The study design included predominantly Caucasian women (2,795 cases and 4,505 controls) from Alberta, Canada. We observed two two-way SNP-SNP interactions (APEX1-rs1130409 and RPAP1-rs2297381; MLH1-rs1799977 and MDM2-rs769412) in logistic regression that conferred elevated risks for breast cancer (P _interaction<7.3×10⁻³). Logic regression identified an interaction involving four SNPs (MBD2-rs4041245, MLH1-rs1799977, MDM2-rs769412, BRCA2-rs1799943) (P _permutation = 2.4×10⁻³). SNPs involved in SNP-SNP interactions also showed single-locus effects with weak statistical significance, while BRCA2-rs1799943 showed stronger statistical significance (P _{correlation/trend} = 3.2×10⁻⁴) than the others. These single-locus effects were independent of body mass index. Our results provide a framework for evaluating SNPs showing statistically weak but reproducible single-locus effects for epistatic effects contributing to disease susceptibility.     

Genome-Wide Testing of Putative Functional Exonic Variants in Relationship with Breast and Prostate Cancer Risk in a Multiethnic Population

Rare variation in protein coding sequence is poorly captured by GWAS arrays and has been hypothesized to contribute to disease heritability. Using the Illumina HumanExome SNP array, we successfully genotyped 191,032 common and rare non-synonymous, splice site, or nonsense variants in a multiethnic sample of 2,984 breast cancer cases, 4,376 prostate cancer cases, and 7,545 controls. In breast cancer, the strongest associations included either SNPs in or gene burden scores for genes LDLRAD1, SLC19A1, FGFBP3, CASP5, MMAB, SLC16A6, and INS-IGF2. In prostate cancer, one of the most associated SNPs was in the gene GPRC6A (rs2274911, Pro91Ser, OR = 0.88, P = 1.3×10⁻⁵) near to a known risk locus for prostate cancer; other suggestive associations were noted in genes such as F13A1, ANXA4, MANSC1, and GP6. For both breast and prostate cancer, several of the most significant associations involving SNPs or gene burden scores (sum of minor alleles) were noted in genes previously reported to be associated with a cancer-related phenotype. However, only one of the associations (rs145889899 in LDLRAD1, p = 2.5×10⁻⁷ only seen in African Americans) for overall breast or prostate cancer risk was statistically significant after correcting for multiple comparisons. In addition to breast and prostate cancer, other cancer-related traits were examined (body mass index, PSA level, and alcohol drinking) with a number of known and potentially novel associations described. In general, these findings do not support there being many protein coding variants of moderate to high risk for breast and prostate cancer with odds ratios over a range that is probably required for protein coding variation to play a truly outstanding role in risk heritability. Very large sample sizes will be required to better define the role of rare and less penetrant coding variation in prostate and breast cancer disease genetics.     

Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer

Background

Molecular and epidemiological evidence demonstrate that altered gene expression and single nucleotide polymorphisms in the apoptotic pathway are linked to many cancers. Yet, few studies emphasize the interaction of variant apoptotic genes and their joint modifying effects on prostate cancer (PCA) outcomes. An exhaustive assessment of all the possible two-, three- and four-way gene-gene interactions is computationally burdensome. This statistical conundrum stems from the prohibitive amount of data needed to account for multiple hypothesis testing.

Methods

To address this issue, we systematically prioritized and evaluated individual effects and complex interactions among 172 apoptotic SNPs in relation to PCA risk and aggressive disease (i.e., Gleason score ≥ 7 and tumor stages III/IV). Single and joint modifying effects on PCA outcomes among European-American men were analyzed using statistical epistasis networks coupled with multi-factor dimensionality reduction (SEN-guided MDR). The case-control study design included 1,175 incident PCA cases and 1,111 controls from the prostate, lung, colo-rectal, and ovarian (PLCO) cancer screening trial. Moreover, a subset analysis of PCA cases consisted of 688 aggressive and 488 non-aggressive PCA cases. SNP profiles were obtained using the NCI Cancer Genetic Markers of Susceptibility (CGEMS) data portal. Main effects were assessed using logistic regression (LR) models. Prior to modeling interactions, SEN was used to pre-process our genetic data. SEN used network science to reduce our analysis from > 36 million to < 13,000 SNP interactions. Interactions were visualized, evaluated, and validated using entropy-based MDR. All parametric and non-parametric models were adjusted for age, family history of PCA, and multiple hypothesis testing.

Results

Following LR modeling, eleven and thirteen sequence variants were associated with PCA risk and aggressive disease, respectively. However, none of these markers remained significant after we adjusted for multiple comparisons. Nevertheless, we detected a modest synergistic interaction between AKT3 rs2125230-PRKCQ rs571715 and disease aggressiveness using SEN-guided MDR (p = 0.011).

Conclusions

In summary, entropy-based SEN-guided MDR facilitated the logical prioritization and evaluation of apoptotic SNPs in relation to aggressive PCA. The suggestive interaction between AKT3-PRKCQ and aggressive PCA requires further validation using independent observational studies.     

Genetic variability of the mTOR pathway and prostate cancer risk in the European Prospective Investigation on Cancer (EPIC)

The mTOR (mammalian target of rapamycin) signal transduction pathway integrates various signals, regulating ribosome biogenesis and protein synthesis as a function of available energy and amino acids, and assuring an appropriate coupling of cellular proliferation with increases in cell size. In addition, recent evidence has pointed to an interplay between the mTOR and p53 pathways. We investigated the genetic variability of 67 key genes in the mTOR pathway and in genes of the p53 pathway which interact with mTOR. We tested the association of 1,084 tagging SNPs with prostate cancer risk in a study of 815 prostate cancer cases and 1,266 controls nested within the European Prospective Investigation into Cancer and Nutrition (EPIC). We chose the SNPs (n = 11) with the strongest association with risk (p<0.01) and sought to replicate their association in an additional series of 838 prostate cancer cases and 943 controls from EPIC. In the joint analysis of first and second phase two SNPs of the PRKCI gene showed an association with risk of prostate cancer (OR_allele = 0.85, 95% CI 0.78–0.94, p = 1.3×10⁻³ for rs546950 and OR_allele = 0.84, 95% CI 0.76–0.93, p = 5.6×10⁻⁴ for rs4955720). We confirmed this in a meta-analysis using as replication set the data from the second phase of our study jointly with the first phase of the Cancer Genetic Markers of Susceptibility (CGEMS) project. In conclusion, we found an association with prostate cancer risk for two SNPs belonging to PRKCI, a gene which is frequently overexpressed in various neoplasms, including prostate cancer.     

Genetic Association of the KLK4 Locus with Risk of Prostate Cancer

The Kallikrein-related peptidase, KLK4, has been shown to be significantly overexpressed in prostate tumours in numerous studies and is suggested to be a potential biomarker for prostate cancer. KLK4 may also play a role in prostate cancer progression through its involvement in epithelial-mesenchymal transition, a more aggressive phenotype, and metastases to bone. It is well known that genetic variation has the potential to affect gene expression and/or various protein characteristics and hence we sought to investigate the possible role of single nucleotide polymorphisms (SNPs) in the KLK4 gene in prostate cancer. Assessment of 61 SNPs in the KLK4 locus (±10 kb) in approximately 1300 prostate cancer cases and 1300 male controls for associations with prostate cancer risk and/or prostate tumour aggressiveness (Gleason score <7 versus ≥7) revealed 7 SNPs to be associated with a decreased risk of prostate cancer at the P(trend)<0.05 significance level. Three of these SNPs, rs268923, rs56112930 and the HapMap tagSNP rs7248321, are located several kb upstream of KLK4; rs1654551 encodes a non-synonymous serine to alanine substitution at position 22 of the long isoform of the KLK4 protein, and the remaining 3 risk-associated SNPs, rs1701927, rs1090649 and rs806019, are located downstream of KLK4 and are in high linkage disequilibrium with each other (r(2)≥0.98). Our findings provide suggestive evidence of a role for genetic variation in the KLK4 locus in prostate cancer predisposition.     

Genetic Variations in the Transforming Growth Factor Beta Pathway as Predictors of Bladder Cancer Risk

Bladder cancer is the fifth most common cancer in the United States, and identifying genetic markers that may predict susceptibility in high-risk population is always needed. The purpose of our study is to determine whether genetic variations in the transforming growth factor-beta (TGF-β) pathway are associated with bladder cancer risk. We identified 356 single-nucleotide polymorphisms (SNPs) in 37 key genes from this pathway and evaluated their association with cancer risk in 801 cases and 801 controls. Forty-one SNPs were significantly associated with cancer risk, and after adjusting for multiple comparisons, 9 remained significant (Q-value ≤0.1). Haplotype analysis further revealed three haplotypes within VEGFC and two haplotypes in EGFR were significantly associated with increased bladder cancer risk compared to the most common haplotype. Classification and regression tree analysis further revealed potential high-order gene-gene interactions, with VEGFC: rs3775194 being the initial split, which suggests that this variant is responsible for the most variation in risk. Individuals carrying the common genotype for VEGFC: rs3775194 and EGFR: rs7799627 and the variant genotype for VEGFR: rs4557213 had a 4.22-fold increase in risk, a much larger effect magnitude than that conferred by common genotype for VEGFR: rs4557213. Our study provides the first epidemiological evidence supporting a connection between TGF-β pathway variants and bladder cancer risk.     

DNMT1, DNMT3A and DNMT3B gene variants in relation to ovarian cancer risk in the Polish population

Studies have demonstrated that changes in DNA methylation of cancer related genes can be an elementary process accounting for ovarian tumorigenesis. Therefore, we evaluated the possible association of single nucleotide polymorphisms (SNPs) of DNA methyltransferases (DNMTs) genes, including DNMT1, DNMT3B, and DNMT3A, with ovarian cancer development in the Polish population. Using PCR–RFLP and HRM analyses, we studied the prevalence of the DNMT1 rs8101626, rs2228611 and rs759920, DNMT3A rs2289195, 7590760, rs13401241, rs749131 and rs1550117, and DNMT3B rs1569686, rs2424913 and rs2424932 SNPs in patients with ovarian cancer (n = 159) and controls (n = 180). The lowest p values of the trend test were observed for the DNMT1 rs2228611 and rs759920 SNPs in patients with ovarian cancer (p _trend = 0.0118 and p _trend = 0.0173, respectively). Moreover, we observed, in the recessive inheritance model, that the DNMT1 rs2228611 and rs759920 SNPs are associated with an increased risk of ovarian cancer development [OR 1.836 (1.143–2.949), p = 0.0114, p _corr = 0.0342, and OR 1.932 (1.185–3.152), p = 0.0078, p _cor=0.0234, respectively]. However, none of other nine studied SNPs displayed significant contribution to the development of ovarian cancer. Furthermore, haplotype and multifactor dimensionality reduction analysis of the studied DNMT1, DNMT3B, and DNMT3A polymorphisms did not reveal either SNP combinations or gene interactions to be associated with the risk of ovarian cancer development. Our results may suggest that DNMT1 variants may be risk factors of ovarian cancer.     

Genetic variations in VDR associated with prostate cancer risk and progression in a Korean population

Low levels of vitamin D are implicated as a potential risk factor for prostate cancer, and the vitamin D receptor (VDR) gene may be important in the onset and progression of prostate cancer. In this study, sequence variants in the VDR gene were investigated in a Korean study cohort to determine whether they are associated with prostate cancer risk. We evaluated the association between 47 single nucleotide polymorphisms (SNPs) in the VDR gene and prostate cancer risk as well as clinical characteristics (prostate-specific antigen level, clinical stage, pathological stage and Gleason score) in Korean men (272 prostate cancer patients and 173 benign prostatic hyperplasia patient who underwent a prostate biopsy, which was negative for malignancy) using unconditional logistic regression. The statistical analysis suggested that two VDR sequence variants (rs2408876 and rs2239182) had a significant association with prostate cancer risk (odds ratio [OR]. 1.41; p = 0.03; OR, 0.73; p = 0.05, respectively). Logistic analyses of the VDR polymorphisms with several prostate cancer related factors showed that several SNPs were significant; nine SNPs to PSA level, three to clinical stage, two to pathological stage, and three SNPs to the Gleason score. The results suggest that some VDR gene polymorphisms in Korean men might not only be associated with prostate cancer risk but also significantly related to prostate cancer-related risk factors such as PSA level, tumor stage, and Gleason score. However, current limitation for small cohort with not-healthy control group might have false positive effects; therefore it should be overcome via further large-scale validating studies.     

Midkine is a NF-κB-inducible gene that supports prostate cancer cell survival

Background

Atherosclerotic peripheral arterial disease (PAD) affects 8–10 million people in the United States and is associated with a marked impairment in quality of life and an increased risk of cardiovascular events. Noninvasive assessment of PAD is performed by measuring the ankle-brachial index (ABI). Complex traits, such as ABI, are influenced by a large array of genetic and environmental factors and their interactions. We attempted to characterize the genetic architecture of ABI by examining the main and interactive effects of individual single nucleotide polymorphisms (SNPs) and conventional risk factors.

Methods

We applied linear regression analysis to investigate the association of 435 SNPs in 112 positional and biological candidate genes with ABI and related physiological and biochemical traits in 1046 non-Hispanic white, hypertensive participants from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. The main effects of each SNP, as well as SNP-covariate and SNP-SNP interactions, were assessed to investigate how they contribute to the inter-individual variation in ABI. Multivariable linear regression models were then used to assess the joint contributions of the top SNP associations and interactions to ABI after adjustment for covariates. We reduced the chance of false positives by 1) correcting for multiple testing using the false discovery rate, 2) internal replication, and 3) four-fold cross-validation.

Results

When the results from these three procedures were combined, only two SNP main effects in NOS3, three SNP-covariate interactions (ADRB2 Gly 16 – lipoprotein(a) and SLC4A5 – diabetes interactions), and 25 SNP-SNP interactions (involving SNPs from 29 different genes) were significant, replicated, and cross-validated. Combining the top SNPs, risk factors, and their interactions into a model explained nearly 18% of variation in ABI in the sample. SNPs in six genes (ADD2, ATP6V1B1, PRKAR2B, SLC17A2, SLC22A3, and TGFB3) were also influencing triglycerides, C-reactive protein, homocysteine, and lipoprotein(a) levels.

Conclusion

We found that candidate gene SNP main effects, SNP-covariate and SNP-SNP interactions contribute to the inter-individual variation in ABI, a marker of PAD. Our findings underscore the importance of conducting systematic investigations that consider context-dependent frameworks for developing a deeper understanding of the multidimensional genetic and environmental factors that contribute to complex diseases.     

MicroRNA Polymorphisms and Environmental Smoke Exposure as Risk Factors for Oesophageal Squamous Cell Carcinoma

MicroRNAs (miRNAs) and related polymorphisms have been implicated in the susceptibility to oesophageal squamous cell carcinoma (OSCC). In our study, three miRNA-related SNPs: rs6505162 A>C (pre-miRNA of miR-423), rs213210 A>G (3’UTR of miR-219-1) and rs7372209 C>T (5’UTR of miR-26a-1) were investigated in the Black and Mixed Ancestry population groups in South Africa. The potential cumulative effects of these SNPs, as well as gene-environment interactions were also analysed. In Blacks, rs6505162 A>C was associated with OSCC under dominant, additive and recessive models with odds ratios (ORs) 1.353, 1.404, and 2.858, respectively. This locus showed very strong interactions with smoke inhalation from burning wood or charcoal used for heating and cooking in very poorly ventilated areas (OR_(GE)=7.855, P_(GE)=9.17*10^-10 in the Black group). Furthermore, the miR-423-3p level was 1.39 fold up-regulated in tumour tissues compared to the adjacent normal tissue (paired t-test P value 0.0087). SNP-SNP interaction between rs2132210 and rs7372209 was found in both Black and Mixed Ancestry subjects. The AA_rs213210-CT_rs7372209 genotype had a protective effect on OSCC risk (in the Black, OR=0.229, P=0.012; and the Mixed Ancestry groups, OR=0.230, P=0.00014). This study is the first to link SNPs in miR-423 together with environmental smoke exposure to risk for developing OSCC.     

Fine mapping the KLK3 locus on chromosome 19q13.33 associated with prostate cancer susceptibility and PSA levels

Measurements of serum prostate-specific antigen (PSA) protein levels form the basis for a widely used test to screen men for prostate cancer. Germline variants in the gene that encodes the PSA protein (KLK3) have been shown to be associated with both serum PSA levels and prostate cancer. Based on a resequencing analysis of a 56?kb region on chromosome 19q13.33, centered on the KLK3 gene, we fine mapped this locus by genotyping tag SNPs in 3,522 prostate cancer cases and 3,338 controls from five case?Ccontrol studies. We did not observe a strong association with the KLK3 variant, reported in previous studies to confer risk for prostate cancer (rs2735839; P?=?0.20) but did observe three highly correlated SNPs (rs17632542, rs62113212 and rs62113214) associated with prostate cancer [P?=?3.41?×?10^?4, per-allele trend odds ratio (OR)?=?0.77, 95% CI?=?0.67?C0.89]. The signal was apparent only for nonaggressive prostate cancer cases with Gleason score <7 and disease stage <III (P?=?4.72?×?10^?5, per-allele trend OR?=?0.68, 95% CI?=?0.57?C0.82) and not for advanced cases with Gleason score >8 or stage ??III (P?=?0.31, per-allele trend OR?=?1.12, 95% CI?=?0.90?C1.40). One of the three highly correlated SNPs, rs17632542, introduces a non-synonymous amino acid change in the KLK3 protein with a predicted benign or neutral functional impact. Baseline PSA levels were 43.7% higher in control subjects with no minor alleles (1.61?ng/ml, 95% CI?=?1.49?C1.72) than in those with one or more minor alleles at any one of the three SNPs (1.12?ng/ml, 95% CI?=?0.96?C1.28) (P?=?9.70?×?10^?5). Together our results suggest that germline KLK3 variants could influence the diagnosis of nonaggressive prostate cancer by influencing the likelihood of biopsy.     

How Genome-Wide SNP-SNP Interactions Relate to Nasopharyngeal Carcinoma Susceptibility

This study is the first to use genome-wide association study (GWAS) data to evaluate the multidimensional genetic architecture underlying nasopharyngeal cancer. Since analysis of data from GWAS confirms a close and consistent association between elevated risk for nasopharyngeal carcinoma (NPC) and major histocompatibility complex class 1 genes, our goal here was to explore lesser effects of gene-gene interactions. We conducted an exhaustive genome-wide analysis of GWAS data of NPC, revealing two-locus interactions occurring between single nucleotide polymorphisms (SNPs), and identified a number of suggestive interaction loci which were missed by traditional GWAS analyses. Although none of the interaction pairs we identified passed the genome-wide Bonferroni-adjusted threshold for significance, using independent GWAS data from the same population (Stage 2), we selected 66 SNP pairs in 39 clusters with P<0.01. We identified that in several chromosome regions, multiple suggestive interactions group to form a block-like signal, effectively reducing the rate of false discovery. The strongest cluster of interactions involved the CREB5 gene and a SNP rs1607979 on chromosome 17q22 (P = 9.86×10⁻¹¹) which also show trans-expression quantitative loci (eQTL) association in Chinese population. We then detected a complicated cis-interaction pattern around the NPC-associated HLA-B locus, which is immediately adjacent to copy-number variations implicated in male susceptibility for NPC. While it remains to be seen exactly how and to what degree SNP-SNP interactions such as these affect susceptibility for nasopharyngeal cancer, future research on these questions holds great promise for increasing our understanding of this disease’s genetic etiology, and possibly also that of other gene-related cancers.     

Common variants of xeroderma pigmentosum genes and prostate cancer risk

The genetic basis of prostate cancer (PC) is complex and appears to involve multiple susceptibility genes. A number of studies have evaluated a possible correlation between several NER gene polymorphisms and PC risk, but most of them evaluated only single SNPs among XP genes and the results remain inconsistent. Out of 94 SNPs located in seven XP genes (XPA–XPG) a total of 15 SNPs were assayed in 720 unselected patients with PC and compared to 1121 healthy adults. An increased risk of disease was associated with the XPD SNP, rs1799793 (Asp312Asn) AG genotype (OR = 2.60; p < 0.001) and with the AA genotype (OR = 531; p < 0.0001) compared to the control population. Haplotype analysis of XPD revealed one protective haplotype and four associated with an increased disease risk, which showed that the A allele (XPD rs1799793) appeared to drive the main effect on promoting prostate cancer risk. Polymorphism in XPD gene appears to be associated with the risk of prostate cancer.     

A common regulatory variant in SLC35B4 influences the recurrence and survival of prostate cancer

Single nucleotide polymorphisms (SNPs) within the regulatory elements of a gene can alter gene expression, making these SNPs of prime importance for candidate gene association studies. We aimed to determine whether such regulatory variants are associated with clinical outcomes in three cohorts of patients with prostate cancer. We used RegulomeDB to identify potential regulatory variants based on in silico predictions and reviewed genome‐wide experimental findings. Overall, 131 putative regulatory SNPs with the highest confidence score on predicted functionality were investigated in two independent localized prostate cancer cohorts totalling 458 patients who underwent radical prostatectomy. The statistically significant SNPs identified in these two cohorts were then tested in an additional cohort of 504 patients with advanced prostate cancer. We identified one regulatory SNPs, rs1646724, that are consistently associated with increased risk of recurrence in localized disease (P = .003) and mortality in patients with advanced prostate cancer (P = .032) after adjusting for known clinicopathological factors. Further investigation revealed that rs1646724 may affect expression of SLC35B4, which encodes a glycosyltransferase, and that down‐regulation of SLC35B4 by transfecting short hairpin RNA in DU145 human prostate cancer cell suppressed proliferation, migration and invasion. Furthermore, we found increased SLC35B4 expression correlated with more aggressive forms of prostate cancer and poor patient prognosis. Our study provides robust evidence that regulatory genetic variants can affect clinical outcomes.