Assessing interactions of two loci (rs4242382 and rs10486567) in familial prostate cancer: statistical evaluation of epistasis

The Role of HOX Transcription Factors in Cancer Predisposition and Progression

Homeobox (HOX) transcription factors, encoded by a subset of homeodomain superfamily genes, play pivotal roles in many aspects of cellular physiology, embryonic development, and tissue homeostasis. Findings over the past decade have revealed that mutations in HOX genes can lead to increased cancer predisposition, and HOX genes might mediate the effect of many other cancer susceptibility factors by recognizing or executing altered genetic information. Remarkably, several lines of evidence highlight the interplays between HOX transcription factors and cancer risk loci discovered by genome-wide association studies, thereby gaining molecular and biological insight into cancer etiology. In addition, deregulated HOX gene expression impacts various aspects of cancer progression, including tumor angiogenesis, cell autophagy, proliferation, apoptosis, tumor cell migration, and metabolism. In this review, we will discuss the fundamental roles of HOX genes in cancer susceptibility and progression, highlighting multiple molecular mechanisms of HOX involved gene misregulation, as well as their potential implications in clinical practice.

SNP-SNP interactions of three new pri-miRNAs with the target gene PGC and multidimensional analysis of H. pylori in the gastric cancer/atrophic gastritis risk in a Chinese population

Gastric cancer (GC) is a multistep complex disease involving multiple genes, and gene–gene interactions have a greater effect than a single gene in determining cancer susceptibility. This study aimed to explore the interaction of the let-7e rs8111742, miR-365b rs121224, and miR-4795 rs1002765 single nucleotide polymorphisms (SNPs) with SNPs of the predicted target gene PGC and Helicobacter pylori status in GC and atrophic gastritis (AG) risk. Three miRNA SNPs and seven PGC SNPs were detected in 2448 cases using the Sequenom MassArray platform. Two pairwise combinations of miRNA and PGC SNPs were associated with increased AG risk (let-7e rs8111742 – PGC rs6458238 and miR-4795 rs1002765 – PGC rs9471643). Singly, miR-365b rs121224 and PGC rs6912200 had no effect individually but in combination they demonstrated an epistatic interaction associated with AG risk. Similarly, let-7e rs8111742 and miR-4795 rs1002765 SNPs interacted with H. pylori infection to increase GC risk (rs8111742: P_interaction = 0.024; rs1002765: P_interaction = 0.031, respectively). A three-dimensional interaction analysis found miR-4795 rs1002765, PGC rs9471643, and H. pylori infection positively interacted to increase AG risk (P_{interaction =} 0.027). Also, let-7e rs8111742, PGC rs6458238, and H. pylori infection positively interacted to increase GC risk (P_{interaction =} 0.036). Furthermore, both of these three-dimensional interactions had a dosage–effect correspondence (P_trend < 0.001) and were verified by MDR. In conclusion, the miRNAs SNPs (let-7e rs8111742 and miR-4795 rs1002765) might have more superior efficiency when combined with PGC SNPs and/or H. pylori for GC or AG risk than a single SNP on its own.

Association between polymorphisms in TP53 and MDM2 genes and susceptibility to prostate cancer

Tumor protein 53 (TP53), a tumor suppressor gene, is a vital cellular cancer suppressor in multicellular organisms. Murine double minute-2 (MDM2) is an oncoprotein that inhibits TP53 activity. A number of studies have examined the association of TP53 and MDM2 polymorphisms with the risk of common forms of cancer, but the findings remain inconclusive. The present study aimed to evaluate the impact of the 40-bp insertion/deletion (I/D) polymorphism (rs3730485) in the MDM2 promoter region and the 16-bp I/D polymorphism (rs17878362) in TP53 on the susceptibility of prostate cancer (PCa) in a sample of the Iranian population. This case-control study included 103 patients with pathologically confirmed PCa and 142 patients with benign prostatic hyperplasia. The MDM2 40-bp I/D and TP53 16-bp I/D polymorphism was determined using polymerase chain reaction analysis. The results demonstrated that the MDM2 40-bp I/D polymorphism increased the risk of PCa in a co-dominant inheritance model [odds ratio (OR)=1.88; 95% confidence interval (CI)=1.11-3.19; P=0.023, D/D vs. I/I], while this variant marginally increased the risk of PCa in a dominant model (OR=1.69; 95% CI=1.00-2.83; P=0.051, I/D+D/D vs. I/I). No significant association was observed between the TP53 16-bp I/D polymorphism and PCa. In conclusion, the present study demonstrated that the 40-bp I/D polymorphism in the MDM2 promoter increased the risk of PCa in an Iranian population. Further investigations with diverse ethnicities and larger sample sizes are required to verify these results.

The Cumulative Effect of Gene-Gene and Gene-Environment Interactions on the Risk of Prostate Cancer in Chinese Men

Prostate cancer (PCa) is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI), smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR) and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs) = 1.79–4.41). GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032) and 5.33 (p = 0.046), respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007) and 3.11 (p = 0.024), respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041). These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa.

Prostate cancer screening using risk stratification based on a multi-state model of genetic variants

BACKGROUND

Risk-stratified screening for prostate cancer (PCa) with prostate-specific antigen (PSA) testing incorporating genetic variants has received some attention but has been scarcely investigated. We developed a model to stratify the Finnish population by different risk profiles related to genetic variants to optimize the screening policy.

METHODS

Data from the Finnish randomized controlled trial on screening for PCa with PSA testing were used to estimate a six-state Markov model of disease progression. Blood samples from Finnish men were used to assess the risk of PCa related to three genetic variants (rs4242382, rs138213197, and rs200331695). A risk score-based approach combined with a series of computer simulation models was applied to optimize individual screening policies.

RESULTS

The 10-year risk of having progressive prostate cancer detected ranged from 43% in the top 5% risk group to approximately 11% in the bottom half of the population. Using the median group, with screening every four years beginning at 55 years-old, as the reference group, the recommended age beginning screening was approximately 47 years-old for the top 5% risk group and 55 years-old for those in the lower 60% risk group. The recommended interscreening interval has been shortened for individuals in the high risk group. The increased availability of genomic information allows the proposed multistate model to be more discriminating with respect to risk stratification and the suggested screening policy, particularly for the lowest risk groups-. --

CONCLUSIONS

A multi-state genetic variant-based model was developed for further application to population risk stratification to optimize the interscreening interval and the age at which to begin screening for PSA. A small sub-group of the population is likely to benefit from more intensive screening with early start and short interval, while half of the population is unlikely to benefit from such protocol (compared with four-year interval after age 55 years).