Combinational polymorphisms of seven CXCL12-related genes are protective against breast cancer in Taiwan

CXCL12/CXCR4 axis gene variants contribute to an increased vulnerability to HPV infection and cervical oncogenesis

PURPOSE

Every year, more than half a million women are diagnosed with cervical cancer (CC). Individual factors may contribute to the cervical cancer development, such as immunogenetic variation. CXCL12/CXCR4 axis is involved in tumor progression and aggressiveness. In the present study, we aimed to investigate a possible association between two single-nucleotide variants (CXCL12 rs1801157 and CXCR4 rs2228014) with HPV infection and cervical cancer development.

METHODS

PCR technique was used to test HPV positivity in 424 women, in which the allelic frequency of CXCL12 rs1801157 and CXCR4 rs2228014 was also assessed by PCR-restriction fragment length polymorphism.

RESULTS

CXCL12 rs1801157 was associated with HPV infection in the allelic distribution as well in the codominant, dominant and recessive genetic models; as well with squamous intraepithelial lesions (SIL) and CC in the codominant and dominant models. CXCR4 rs2228014 was associated to HPV infection in the codominant model and allelic distribution; as well with SIL/CC in the codominant, dominant and allelic models. Independent associations were found for CXCL12 AA genotype and HPV infection, SIL and CC development, as well as, CXCR4 allele T and HPV infection and CC. The variants interaction analysis demonstrated that the presence of both polymorphisms increases the susceptibility of HPV infection in 10.1 times, SIL (2 times) and CC development in 4.2 times.

CONCLUSIONS

This is the first study demonstrating that the interaction of CXCL12 and CXCR4 variants contributes to the increased susceptibility of HPV infection, squamous intraepithelial lesions and cervical cancer development.

Association of VEGF haplotypes with breast cancer risk in North-West Indians

BACKGROUND

Angiogenesis is a complex and coordinated process regulated by different growth factors and is one of the hallmark features of cancer. VEGF is one of the most important endothelial cell mitogen and has a critical role in normal physiological and tumor angiogenesis. The objective of this study was to investigate the potential association of haplotypes of six VEGF polymorphisms with breast cancer risk in North-West Indians.

METHODS

Samples of 250 breast cancer patients and 250 age and sex matched controls were genotyped for VEGF -2578C/A, -2549I/D, -460T/C, +405C/G, -7C/T and +936C/T polymorphisms. Haplotypes were generated to determine the better contribution of VEGF polymorphisms to breast cancer risk.

RESULTS

Haplotypes CDTCCC (OR = 0.56, 95%CI, 0.38-0.81; p = 0.003) and CDTGCC (OR = 0.63, 95%CI, 0.44-0.92; p = 0.018) of VEGF -2578C/A, -2549I/D, -460T/C, +405C/G, -7C/T and +936C/T polymorphisms were significantly associated with decreased risk of breast cancer. CDTCCC haplotype was also significantly associated with reduced risk of breast cancer in pre and post menopausal as well as both obese and non obese patients. Haplotype CDTGCC was marginally associated (p = 0.07) with reduced risk of breast cancer in non-obese patients as compared with non-obese controls where as haplotype AICGTC was marginally associated (p = 0.09) with reduced risk of breast cancer in obese patients when compared with non-obese patients. The CDTGCC haplotype was significantly associated with increased risk of breast cancer in premenopausal obese patients (OR = 1.98, 95%CI, 1.10-3.56; p = 0.02).

CONCLUSIONS

Our data indicated that CDTCCC and CDTGCC haplotypes of VEGF -2578C/A, -2549I/D, -460T/C, +405C/G, -7C/T and +936C/T polymorphisms were significantly associated with breast cancer risk in North-West Indians. Further studies on multiethnic groups with larger sample size are required to confirm our results.

Identification of key molecular targets that correlate with breast cancer through bioinformatic methods

BACKGROUND

The present study aimed to identify key molecular targets of breast cancer for targeted treatment and to improve the survival rate.

METHODS

Overlapped difference expression genes in three datasets were identified in a weighted gene co-expression network analysis (WGCNA) module and MetaDE.ES analysis. Combined with the prognosis information [time, death, status and relative survival (RS)] in GSE42568, single-factor Cox regression analysis was used to screen the genes that were significantly related to the prognosis in the target gene set.

RESULTS

In total, 13 optimal gene combinations with a significantly correlated prognosis were obtained, including SSPN, NELL2, AGTR1, NRIP3, IKZF2, NAT1, CXCL12, NPY1R, PRAME, PPP1R1B, CRISP3, NMU and GSTP1. In addition, there was a significant correlation between the samples given by the prognostic prediction system and the validation dataset (GSE20685 and TCGA), with p values of 0.0299 in GSE20685 and 1.461 × 10^-5 in TCGA, and an area under the receiver operating characteristic of 0.942 and 0.923, respectively. RS-related differentially expressed genes between high- and low-risk groups were significantly related to biological processes such as cell period and the hormone stimulation response, and were also significantly involved in KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways such as cell period, the peroxisome proliferator-activated receptor signaling pathway and the cancer pathway.

CONCLUSIONS

By predicting the survival risk of breast cancer patients based on the 13 optimal genes, high-risk patients would be detected early. Accordingly, this would help in the formulation of an appropriate treatment plan for patients.

Application of simulation-based CYP26 SNP-environment barcodes for evaluating the occurrence of oral malignant disorders by odds ratio-based binary particle swarm optimization: A case-control study in the Taiwanese population

Introduction

Genetic polymorphisms and social factors (alcohol consumption, betel quid (BQ) usage, and cigarette consumption), both separately or jointly, play a crucial role in the occurrence of oral malignant disorders such as oral and pharyngeal cancers and oral potentially malignant disorders (OPMD).

Material and methods

Simultaneous analyses of multiple single nucleotide polymorphisms (SNPs) and environmental effects on oral malignant disorders are essential to examine, albeit challenging. Thus, we conducted a case-control study (N = 576) to analyze the risk of occurrence of oral malignant disorders by using binary particle swarm optimization (BPSO) with an odds ratio (OR)-based method.

Results

We demonstrated that a combination of SNPs (CYP26B1 rs887844 and CYP26C1 rs12256889) and socio-demographic factors (age, ethnicity, and BQ chewing), referred to as the combined effects of SNP-environment, correlated with maximal risk diversity of occurrence observed between the oral malignant disorder group and the control group. The risks were more prominent in the oral and pharyngeal cancers group (OR = 10.30; 95% confidence interval (CI) = 4.58–23.15) than in the OPMD group (OR = 5.42; 95% CI = 1.94–15.12).

Conclusions

Simulation-based “SNP-environment barcodes” may be used to predict the risk of occurrence of oral malignant disorders. Applying simulation-based “SNP-environment barcodes” may provide insight into the importance of screening tests in preventing oral and pharyngeal cancers and OPMD.

CXCL12 chemokine and CXCR4 receptor: association with susceptibility and prognostic markers in triple negative breast cancer

CXCL12/CXCR4 signaling has been implicated in breast carcinogenesis, and genetic polymorphisms in these molecules have been associated with different types of cancer. The present study analyzed genetic polymorphisms in CXCL12 (rs1801157, G > A) and CXCR4 (rs2228014, C > T) and CXCR4 immunostaining in tumor tissues from patients with triple negative breast cancer (TNBC) aiming to evaluate their possible role in its' susceptibility and prognosis. Genetic polymorphisms were analyzed in 59 TNBC patients and 150 control women; age-adjusted logistic regression showed no association when variants were considered in isolation; however, a statistically significant interaction was noted for heterozygosis for both allelic variants increasing the odds for TNBC (CXCL12-GA by CXCR4-CT: OR 7.23; 95% CI 1.15-45.41; p = 0.035). CXCL12 polymorphism was correlated negatively with proliferation index (Ki67) (Tau-b = - 0.406; p = 0.006). CXCR4 immunostaining was evaluated in 37 TNBC patients (22 with paired tumor-normal adjacent tissue). CXCR4 was detected more intensely in cell cytoplasm than in membrane, and was more expressed in tumor than in normal adjacent tissues, although not statistically significant. CXCR4 expression on the membrane of tumor cells was correlated positively with histopathological grade (Tau-b = 0.271; p = 0.036) and negatively with lymph node metastasis (Tau-b = - 0.478; p = 0.036). The present study indicates that CXCL12 and CXCR4 polymorphisms and CXCR4 immunostaining might have susceptibility and prognostic roles in TNBC pathogenesis.

A meta-analytic review of the association between two common SNPs in miRNAs and lung cancer susceptibility

Background

MicroRNAs (miRNAs) are involved in many biological processes, including tumor suppression. Multiple studies have shown an association between the miRNA-196a2 rs11614913 and miRNA-146a rs2910164 polymorphisms and cancer risk. However, the implications of the reported data are debatable and inconclusive.

Materials and methods

Relevant articles were retrieved from the PubMed, EMBASE, China National Knowledge Infrastructure, and WanFang databases from January 1, 2007, to April 30, 2017. Studies were assessed based on designated inclusion and exclusion criteria, and data were manually extracted from relevant studies by two investigators. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to explore the association between two single-nucleotide polymorphisms (SNPs) in miRNAs and lung cancer susceptibility.

Results

Nine eligible articles were included, consisting of 3,101 cancer cases and 3,234 controls for miRNA-196a2 rs11614913, and 3,483 cases and 3,578 controls for miRNA-146a rs2910164. For studies evaluating miRNA-196a2 rs11614913, significant associations with lung cancer risk were discovered. Overall, the pooled analysis showed that miRNA-196a2 rs11614913 was associated with a decreased cancer risk (CC vs TT: OR = 1.25, 95% CI: 1.09–1.44; CT vs TT: OR = 1.26, 95% CI: 1.03–1.53). For miRNA-146a rs2910164, only the CC genotype was found to be associated with high lung cancer risk (OR = 1.30, 95% CI: 1.13–1.49). Subgroup analyses based on ethnicity, source of control group, and country indicated that there were strong associations between miRNA-146a rs2910164 and cancer risk.

Conclusion

The results indicated that lung cancer risk was significantly associated with miRNA-196a2 rs11614913 and miRNA-146a rs2910164. These two common SNPs in miRNAs may be potential biomarkers of lung cancer.

Genetic variation of CXCR4 and risk of coronary artery disease: epidemiological study and functional validation of CRISPR/Cas9 system

Cardiovascular diseases (CVDs) remain the leading cause of death worldwide, while coronary artery disease (CAD) account for a large part of CVDs. Vascular CXCR4 could limit atherosclerosis by maintaining arterial integrity. Here, we conducted a population-based, case-control study to evaluate the associations of common genetic variation within the CXCR4 gene (rs2228014, rs117600832, rs2471859, and rs2322864) with CAD risk in a Chinese population. We found that CXCR4 rs2228014 was significantly associated with 1.29-fold increased risk of CAD (A vs G: OR = 1.29; 95% CI = 1.07–1.55; P = 0.007). The subjects with genotype AA (OR = 1.98; 95% CI = 1.03–3.81; P = 0.041) and AG (OR = 1.27; 95% CI = 1.02–1.58; P = 0.030) have higher risk of CAD, compared with those with genotype GG. Furthermore, both in the CAD patients with diabetes and those without diabetes, rs2228014 was significantly associated with increased risk of CAD (P < 0.05). Additionally, we also validated the significant association for rs2322864 (C vs T: OR = 1.20; 95% CI = 1.00–1.44; P = 0.046). Knockout of CXCR4 gene could significantly impair the capacity of cholesterol efflux (P < 0.01). These findings strongly suggest that CXCR4 polymorphisms might contribute to CAD susceptibility, and the exact biological mechanism awaits further research.

Joint Analysis of SNP-SNP-Environment Interactions for Chronic Dialysis by an Improved Branch and Bound Algorithm

In previous studies, both single-nucleotide polymorphism (SNP)-SNP or gene-gene (G × G) interactions and SNP-environmental factor (G × E) interactions were reported to partially account for "missing" heritability. However, (G × G) × E interactions were less commonly addressed. The purpose of this study was to develop a novel strategy to evaluate possible (G × G) × E interactions in D-loop-based chronic dialysis association. Using values from our previously published data set (704 controls and 193 cases) of 77 D-loop SNPs and 7 environmental factors (coronary heart disease, hypertension, diabetes mellitus, triglyceride, cholesterol, blood thiol, and TBARS levels), we compared the performances of G, G × G, G × E, and (G × G) × E. We found that the interactions of four individual SNPs previously associated with a significantly high risk of chronic dialysis [odds ratio (OR) = 1.56-4.93] with environmental factors (G × E) increased the risk of chronic dialysis (maximum OR = 35.43). We then used an improved branch and bound algorithm to identify combinations of two to four SNPs that were most highly associated with chronic dialysis (OR = 9.27-34.39). When the interactions of the two- and three-SNP combinations with environmental factors were evaluated, we found that the (G × G) × E effects increased the risk of chronic dialysis (maximum OR = 8.32-57.54 and OR = 12.52-57.81, respectively; adjusted OR = 8.67-81.81 and OR = 12.29-81.95, respectively). Taken together, the (G × G) × E interactions identified chronic dialysis-associated SNPs that would not have been found using G × G or G × E interactions, suggesting that (G × G) × E interactions may be helpful to solve the problems of missing heritability in association studies.

SNPs, linkage disequilibrium, and chronic mountain sickness in Tibetan Chinese

Chronic mountain sickness (CMS) is estimated at 1.2% in Tibetans living at the Qinghai-Tibetan Plateau. Eighteen single-nucleotide polymorphisms (SNPs) from nine nuclear genes that have an association with CMS in Tibetans have been analyzed by using pairwise linkage disequilibrium (LD). The SNPs included are the angiotensin-converting enzyme (rs4340), the angiotensinogen (rs699), and the angiotensin II type 1 receptor (AGTR1) (rs5186) from the renin-angiotensin system. A low-density lipoprotein apolipoprotein B (rs693) SNP was also included. From the hypoxia-inducible factor oxygen signaling pathway, the endothetal Per-Arnt-Sim domain protein 1 (EPAS1) and the egl nine homolog 1 (ENGL1) (rs480902) SNPs were included in the study. SNPs from the vascular endothelial growth factor (VEGF) signaling pathway included are the v-akt murine thymoma viral oncogene homolog 3 (rs4590656 and rs2291409), the endothelial cell nitric oxide synthase 3 (rs1007311 and rs1799983), and the (VEGFA) (rs699947, rs34357231, rs79469752, rs13207351, rs28357093, rs1570360, rs2010963, and rs3025039). An increase in LD occurred in 40 pairwise comparisons, whereas a decrease in LD was found in 55 pairwise comparisons between the controls and CMS patients. These changes were found to occur within and between signaling pathways, which suggests that there is an interaction between SNP alleles from different areas of the genome that affect CMS.

CXC motif chemokine receptor 4 gene polymorphism and cancer risk

BACKGROUND

Previous epidemiological studies have reported the relationship between CXC motif chemokine receptor 4 (CXCR4) synonymous polymorphism (rs2228014), and risk of cancer, but the results remained conflicting and controversial. Therefore, this study was devised to evaluate the genetic effects of the rs2228014 polymorphism on cancer risk in a large meta-analysis.

METHODS

The computer-based databases (EMBASE, Web of Science, and PubMed) were searched for all relevant studies evaluating rs2228014 and susceptibility to cancer. In the analysis, pooled odds ratios (ORs) with its corresponding 95% confidence intervals (CIs) were calculated in 5 genetic models to assess the genetic risk. Egger regression and Begg funnel plots test were conducted to appraise the publication bias.

RESULTS

Data on rs2228014 polymorphism and overall cancer risk were available for 3684 cancer patients and 5114 healthy controls participating in 11 studies. Overall, a significantly increased risk of cancer was associated with rs2228014 polymorphism in homozygote model (OR = 2.01, 95% CI: 1.22-3.33) and in recessive model (OR = 1.97, 95% CI: 1.23-3.16). When stratified by ethnicity, the results were positive only in Asian populations (heterozygote model: OR = 1.36, 95% CI: 1.13-1.65; homozygote model: OR = 2.43, 95% CI: 1.21-4.91; dominant model: OR = 1.47, 95% CI: 1.13-1.90; recessive model: OR = 2.25, 95% CI: 1.13-4.48; and allele model: OR = 1.48, 95% CI: 1.10-1.99). Besides, in the subgroup analysis by source of control, the result was significant only in population-based control (homozygote model: OR = 2.39, 95% CI: 1.06-5.40; recessive model: pooled OR = 2.24, 95% CI: 1.02-4.96).

CONCLUSION

In general, our results first indicated that the rs2228014 polymorphism in CXCR4 gene is correlated with an increased risk of cancer, especially among Asian ethnicity. Large, well-designed epidemiological studies are required to verify the current findings.

Association between BHMT gene rs3733890 polymorphism and cancer risk: evidence from a meta-analysis

BACKGROUND AND OBJECTIVE

The gene betaine-homocysteine methyltransferase (BHMT) has drawn much attention during the past decades. An increasing number of clinical and genetic investigations have supposed that BHMT rs3733890 polymorphism might be associated with risk of breast cancer and ovarian cancer. As no consistent conclusion has been achieved, we conducted an up-to-date summary of BHMT rs3733890 polymorphism and cancer risk through a meta-analysis.

MATERIALS AND METHODS

The articles were collected from PubMed, Google Scholar, and CNKI (Chinese) databases up to December 2015. Then, the correlations were determined by reading the titles and abstracts and by further reading the full text to filter the unqualified articles. Odds ratio (OR) and the corresponding 95% confidence intervals (CI) were used to assess the results.

RESULTS

Among 187 articles collected in the analysis, seven studies with a total of 2,832 cases and 3,958 controls were included for evaluation of the association between BHMT rs3733890 polymorphism and susceptibility of cancer risk. The heterogeneity test showed no significant differences. Furthermore, we found that BHMT -742G>A polymorphism in case and control groups showed no statistically significant association with susceptibility in various cancer types except for uterine cervical cancer (A vs G: OR =0.641, 95% CI =0.445-0.923, P=0.017; AA+AG vs GG: OR =0.579, 95% CI =0.362-0.924, P=0.022). In addition, no statistically significant association was uncovered when stratification analyses were conducted by ethnicity and genotyping methods.

CONCLUSION

Our results have shown no obvious evidence that rs3733890 polymorphism in BHMT gene affected the susceptibility of head and neck squamous cell carcinoma, breast cancer, ovarian cancer, colorectal adenoma, and liver cancer. In contrast, we found the protective role of BHMT -742G>A polymorphism in uterine cervical cancer incidence. Future well-designed studies comprising larger sample size are warranted to verify our findings.

Breast cancer-associated high-order SNP-SNP interaction of CXCL12/CXCR4-related genes by an improved multifactor dimensionality reduction (MDR-ER)

In association studies, the combined effects of single nucleotide polymorphism (SNP)-SNP interactions and the problem of imbalanced data between cases and controls are frequently ignored. In the present study, we used an improved multifactor dimensionality reduction (MDR) approach namely MDR-ER to detect the high order SNP‑SNP interaction in an imbalanced breast cancer data set containing seven SNPs of chemokine CXCL12/CXCR4 pathway genes. Most individual SNPs were not significantly associated with breast cancer. After MDR‑ER analysis, six significant SNP‑SNP interaction models with seven genes (highest cross‑validation consistency, 10; classification error rates, 41.3‑21.0; and prediction error rates, 47.4‑55.3) were identified. CD4 and VEGFA genes were associated in a 2‑loci interaction model (classification error rate, 41.3; prediction error rate, 47.5; odds ratio (OR), 2.069; 95% bootstrap CI, 1.40‑2.90; P=1.71E‑04) and it also appeared in all the best 2‑7‑loci models. When the loci number increased, the classification error rates and P‑values decreased. The powers in 2‑7‑loci in all models were >0.9. The minimum classification error rate of the MDR‑ER‑generated model was shown with the 7‑loci interaction model (classification error rate, 21.0; OR=15.282; 95% bootstrap CI, 9.54‑23.87; P=4.03E‑31). In the epistasis network analysis, the overall effect with breast cancer susceptibility was identified and the SNP order of impact on breast cancer was identified as follows: CD4 = VEGFA > KITLG > CXCL12 > CCR7 = MMP2 > CXCR4. In conclusion, the MDR‑ER can effectively and correctly identify the best SNP‑SNP interaction models in an imbalanced data set for breast cancer cases.

The SDF-1 rs1801157 Polymorphism is Associated with Cancer Risk: An Update Pooled Analysis and FPRP Test of 17,876 Participants

The stromal cell derived factor-1 (SDF-1) rs1801157 gene polymorphism has been implicated in susceptibility to cancer, but the results were inconclusive. The current study was to precisely investigate the association between SDF-1 rs1801157 polymorphism and cancer risk using meta-analysis and the false positive report probability (FPRP) test. All 17,876 participants were included in the study. The meta-analysis results indicated a significant association between the SDF-1 rs1801157 polymorphism and cancer risk. By subgroup analyses, the results detected that the SDF-1 rs1801157 polymorphism was associated with cancer susceptibility among Asians and Caucasians. Additionally, we also found significant associations between the SDF-1 rs1801157 polymorphism and susceptibility to different types of cancer. However, to avoid a "false positive report", we further investigated the significant associations observed in the present meta-analysis using the FPRP test. Interestingly, the results of the FPRP test indicated that only 4 gene models were truly associated with cancer risk, especially in Asians. Moreover, we confirmed that the SDF-1 rs1801157 gene polymorphism was only associated with lung and urologic cancer risk. In summary, this study suggested that the SDF-1 rs1801157 polymorphism may serve as a risk factor for cancer development among Asians, especially an increased risk of urologic and lung cancers.

A systematic gene-gene and gene-environment interaction analysis of DNA repair genes XRCC1, XRCC2, XRCC3, XRCC4, and oral cancer risk

Oral cancer is the sixth most common cancer worldwide with a high mortality rate. Biomarkers that anticipate susceptibility, prognosis, or response to treatments are much needed. Oral cancer is a polygenic disease involving complex interactions among genetic and environmental factors, which require multifaceted analyses. Here, we examined in a dataset of 103 oral cancer cases and 98 controls from Taiwan the association between oral cancer risk and the DNA repair genes X-ray repair cross-complementing group (XRCCs) 1-4, and the environmental factors of smoking, alcohol drinking, and betel quid (BQ) chewing. We employed logistic regression, multifactor dimensionality reduction (MDR), and hierarchical interaction graphs for analyzing gene-gene (G×G) and gene-environment (G×E) interactions. We identified a significantly elevated risk of the XRCC2 rs2040639 heterozygous variant among smokers [adjusted odds ratio (OR) 3.7, 95% confidence interval (CI)=1.1-12.1] and alcohol drinkers [adjusted OR=5.7, 95% CI=1.4-23.2]. The best two-factor based G×G interaction of oral cancer included the XRCC1 rs1799782 and XRCC2 rs2040639 [OR=3.13, 95% CI=1.66-6.13]. For the G×E interaction, the estimated OR of oral cancer for two (drinking-BQ chewing), three (XRCC1-XRCC2-BQ chewing), four (XRCC1-XRCC2-age-BQ chewing), and five factors (XRCC1-XRCC2-age-drinking-BQ chewing) were 32.9 [95% CI=14.1-76.9], 31.0 [95% CI=14.0-64.7], 49.8 [95% CI=21.0-117.7] and 82.9 [95% CI=31.0-221.5], respectively. Taken together, the genotypes of XRCC1 rs1799782 and XRCC2 rs2040639 DNA repair genes appear to be significantly associated with oral cancer. These were enhanced by exposure to certain environmental factors. The observations presented here warrant further research in larger study samples to examine their relevance for routine clinical care in oncology.

PCR-CTPP design for enzyme-free SNP genotyping using memetic algorithm

In recent years, many single nucleotide polymorphisms (SNPs) have been successfully genotyped by polymerase chain reaction with confronting two-pair primers (PCR-CTPP). However, computation experiments of feasible CTPP primers are still challenging. The melting temperatures between four primers must be within a very narrow range, and many primer constraints need to be conformed to. PCR-CTPP is a simple, time- and cost-effective SNP genotyping method applied in molecular biology and biomedical fields. In this study, an MA (memetic algorithm)-based method is proposed to enable the design of feasible CTPP primer sets. Overall, 288 SNPs which exclude the deletion/insertion polymorphisms (DIPs) and multi-nucleotide polymorphisms (MNPs) in the SLC6A4 gene were tested in silico. The results were compared with a GA (genetic algorithm)-based method and indicate that the proposed method provides more feasible CTPP primers than the GA-based method. The MA-based CTPP primer design method provides critical melting temperatures and all kinds of evaluation of the common primer constraints. It could conceivably assist biologists and other researchers in obtaining feasible CTTP primer sets. The MA-CTPP algorithm is implemented in JAVA and a user-friendly input interface is freely available at http://bio.kuas.edu.tw/ma-ctpp/.

The Combinational Polymorphisms of ORAI1 Gene Are Associated with Preventive Models of Breast Cancer in the Taiwanese

The ORAI calcium release-activated calcium modulator 1 (ORAI1) has been proven to be an important gene for breast cancer progression and metastasis. However, the protective association model between the single nucleotide polymorphisms (SNPs) of ORAI1 gene was not investigated. Based on a published data set of 345 female breast cancer patients and 290 female controls, we used a particle swarm optimization (PSO) algorithm to identify the possible protective models of breast cancer association in terms of the SNPs of ORAI1 gene. Results showed that the PSO-generated models of 2-SNP (rs12320939-TT/rs12313273-CC), 3-SNP (rs12320939-TT/rs12313273-CC/rs712853-(TT/TC)), 4-SNP (rs12320939-TT/rs12313273-CC/rs7135617-(GG/GT)/rs712853-(TT/TC)), and 5-SNP (rs12320939-TT/rs12313273-CC/rs7135617-(GG/GT)/rs6486795-CC/rs712853-(TT/TC)) displayed low values of odds ratios (0.409–0.425) for breast cancer association. Taken together, these results suggested that our proposed PSO strategy is powerful to identify the combinational SNPs of rs12320939, rs12313273, rs7135617, rs6486795, and rs712853 of ORAI1 gene with a strongly protective association in breast cancer.

Identification of a shared protective genetic susceptibility locus for colorectal cancer and gastric cancer

Risk of both colorectal cancer (CRC) and gastric cancer (GC) is considered to be heritable with mounting evidence for their genetic susceptibility. However, it remains unknown whether a shared genetic background is underlying these two cancers. A total of ten single nucleotide polymorphisms (SNPs) associated with digestive system cancers risk were selected from previous genome-wide association studies. All SNPs were genotyped in 449 CRC cases, 588 GC cases, and 703 controls using Sequenom Mass-ARRAY technology. Odds ratios (ORs) and 95 % confidence intervals (95 % CIs) were estimated using unconditional logistic regression analysis with adjustment for age and gender, and evaluated their association with both cancers in a Han Chinese population using chi-squared (χ (2)) test and genetic model analysis. By χ (2) test, we found that rs2057314 (p = 0.028; OR = 1.21) was significantly associated with an increased risk of CRC, rs7758229 (p = 0.005; OR = 0.77) was significantly associated with a decreased risk of GC. Furthermore, a shared susceptibility locus rs9502893 was found to have significant protective effect against CRC (p = 0.010; OR = 0.80) and GC (p = 0.0003; OR = 0.74). Our findings could provide insight into the underlying shared a partly overlapping genetic aspect of CRC and GC in a Chinese population. Additional studies are required to verify and discover more common genetic variants associated with risk for digestive system cancers.

The Effect of C-X-C Motif Chemokine 13 on Hepatocellular Carcinoma Associates with Wnt Signaling

Objects. To investigate the effect of CXCL13 (C-X-C motif chemokine 13) on hepatocellular carcinoma and clarify the potential mechanisms. Methods. 32 patients with hepatocellular carcinoma and 12 healthy controls were recruited for analyzing the expression of CXCL13 by RT-PCR (reverse transcription-polymerase chain reaction). ELISA (enzyme-linked immune-sorbent assay) was used to test the concentration of serum CXCL13. The interaction between CXCL13 and Wnt signaling was analyzed by western blot. In vitro PBMCs cultured with HepG2 supernatant, the levels of IL-12, IL4, IL-6, and IL-17, and four IgG subclasses were detected by ELISA. Results. The rate of high expression CXCL13 was 63.4% in advanced HCC patients, and the serum CXCL13 was also at a high level in stage IV HCC patients. Meanwhile CXCL13 level was positively correlated with serum ALT (Alanine Transaminase) and AST (Aspartate Aminotransferase). CXCL13 and Wnt/β-catenin signaling shared a positive feedback loop. Furthermore, CXCL13 could obviously promote the expressions of IL-12 and IL-17, and induce IgG4 secreted by B cells. Conclusions. The effect of CXCL13 on promoting liver cancer is related to the activation of Wnt/β-catenin pathway and the facilitation of IL-12, IL-17 and IgG4. CXCL13 plays an important role in the progression of HCC, and it may act as a potential target for the diagnosis and treatment of HCC.

The G801A polymorphism in the CXCL12 gene and risk of breast carcinoma: evidence from a meta-analysis including 2,931 subjects

More and more evidence indicates that the G801A polymorphism in the CXCL12 gene might be associated with susceptibility to breast carcinoma in humans being. However, individually published results have been inconsistent. The purpose of this meta-analysis was to investigate the association between the G801A polymorphism in the CXCL12 gene and breast carcinoma risk. A complete search strategy was done by the electronic databases including PubMed and Chinese Biomedical Literature Database. A meta-analysis including seven individual studies was carried out in order to explore the association between the G801A polymorphism in the CXCL12 gene polymorphisms and breast carcinoma. The pooled odds ratios (ORs) and their corresponding 95% confidence intervals (95%CIs) between the G801A polymorphism in the CXCL12 gene and breast carcinoma risk were assessed by the random-effects model. A significant relationship between the G801A polymorphism in the CXCL12 gene and breast carcinoma was discovered in an allelic genetic model (OR: 1.214, 95%CI: 1.085- 1.358, p=0.001), a homozygote model (OR: 1.663, 95%CI: 1.240-2.232, p=0.001), a heterozygote model (OR: 1.392, 95%CI: 1.190-1.629, p=0.000), a recessive genetic model (OR: 1.407, 95%CI: 1.060-1.868, p=0.018) and a dominant genetic model (OR: 1.427, 95%CI: 1.228-1.659, p=0.000). On sub-group analysis based on ethnicity, significance was observed between the European group and the mixed group. A significant relationship was found between the G801A polymorphism in the CXCL12 gene and breast carcinoma risk. Individuals with the A allele of the G801A polymorphism in the CXCL12 gene are under a higher risk for breast carcinoma.

The CXCL12 G801A polymorphism is associated with cancer risk: a meta-analysis

Background

CXCL12 is a small chemotactic cytokine belonging to the CXC chemokine family expressed in various organs. It contributes to the migration, invasion and angiogenesis of cancer cells. Recently, the CXCL12 G801A polymorphism was shown to be associated with an increased risk of various kinds of cancers, but the results were too inconsistent to be conclusive.

Methods

To solve the problem of inadequate statistical power and conflicting results, a meta-analysis of published case-control studies was performed, including 4,435 cancer cases and 6,898 controls. Odds ratios (ORs) and their 95% confidence intervals (CIs) were used to determine the strength of association between CXCL12 G801A polymorphism and cancer risk.

Results

A significant association between CXCL12 G801A polymorphism and cancer risk was found under all genetic models. Further, subgroup analysis stratified by ethnicity suggested a significant association between CXCL12 G801A polymorphism and cancer risk in the Asian subgroup under all genetic models. However, in the Caucasian subgroup, a significant association was only found under an additive genetic model and a dominant genetic model. The analysis stratified by cancer type found that CXCL12 G801A polymorphism may increase the risk of breast cancer, lung cancer, and “other” cancers. Based on subgroup stratified by source of controls, a significant association was observed in hospital-based studies under all genetic models.

Conclusions

The CXCL12 G801A polymorphism is associated with an increased risk of cancer based on current published data. In the future, large-scale well-designed studies with more information are needed to better estimate possible gene-gene or gene-environment interactions.

SNP 1772 C > T of HIF-1α gene associates with breast cancer risk in a Taiwanese population

Background

Hypoxia inducible factor 1α (HIF-1α) is a stress-responsive transcription factor to hypoxia and its expression is correlated to tumor progression and angiogenesis. Several single nucleotide polymorphisms (SNPs) of HIF-1α gene in the oxygen-dependent degradation (ODD) domain was reportedly associated with increased HIF-1α activity.

Results

In this study, we focused on the relationship between SNP 1772 C > T (rs11549465) of HIF-1α gene and its breast cancer risk, as well as its correlation with HIF-1α expression and tumor angiogenesis. Ninety six breast cancer patients and 120 age-matched controls were enrolled. We found that 1772 T allele of HIF-1α gene was associated with increased breast cancer risk (adjusted OR = 14.51; 95% CI: 6.74-31.24). This SNP was not associated with clinicopathologic features of angiogenesis such as VEGF activity and the micro-vessel density and survival of breast cancer patients.

Conclusion

Taken together, the 1772 C > T of HIF-1α gene is a potential biomarker for breast cancer susceptibility.

Vascular endothelial growth factor (VEGF) polymorphism and increased risk of epithelial ovarian cancer

INTRODUCTION

Angiogenesis (AG) is essential for epithelial ovarian cancer (EOC) development. Vascular endothelial growth factor (VEGF), encoded by the VEGF gene, and endostatin, the product of the COL18A1 gene, act as a potent promoter and an inhibitor of AG, respectively. In the present study, we tested whether VEGF C936T and COL18A1 D104N polymorphisms alter the risk of EOC.

METHODS

Genomic DNA from 131 EOC patients and 137 controls were analyzed by polymerase chain reaction and restriction fragment length polymorphism methods. The differences between groups were analyzed by χ (2) or Fisher's exact test and logistic regression analysis.

RESULTS

The frequency of the VEGF 936CC genotype was higher in patients than in controls (84.8% vs. 75.3%, P = 0.03). Individuals with respective genotypes had a 1.98 (95% CI 1.04-3.78)-fold increased risk of EOC than those with the remaining genotypes. An excess of VEGF 936CC plus COL18A1 DN genotype was seen in patients when compared to controls (48.6% vs. 30.5%); however, only a tendency toward a statistically significant difference in genotype frequencies was found in the study (P = 0.06), reflecting a trend toward an increased risk of 2.44 for EOC in carriers of the combined genotype.

CONCLUSION

Our data present, for the first time, preliminary evidence that VEGF C936T alone or combined with the COL18A1 D104N polymorphism of AG constitutes an important inherited EOC determinant.

Restoring TRAIL mediated signaling in ovarian cancer cells

Ovarian cancer has emerged as a multifaceted and genomically complex disease. Genetic/epigenetic mutations, suppression of tumor suppressors, overexpression of oncogenes, rewiring of intracellular signaling cascades and loss of apoptosis are some of the deeply studied mechanisms. In vitro and in vivo studies have highlighted different molecular mechanisms that regulate tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) mediated apoptosis in ovarian cancer. In this review, we bring to limelight, expansion in understanding systematical characterization of ovarian cancer cells has led to the rapid development of new drugs and treatments to target negative regulators of TRAIL mediated signaling pathway. Wide ranging synthetic and natural agents have been shown to stimulate mRNA and protein expression of death receptors. This review is compartmentalized into programmed cell death protein 4, platelet-derived growth factor signaling and miRNA control of TRAIL mediated signaling to ovarian cancer. Mapatumumab and PRO95780 have been tested for efficacy against ovarian cancer. Use of high-throughput screening assays will aid in dissecting the heterogeneity of this disease and increasing a long-term survival which might be achieved by translating rapidly accumulating information obtained from molecular and cellular studies to clinic researches.

Double-bottom chaotic map particle swarm optimization based on chi-square test to determine gene-gene interactions

Gene-gene interaction studies focus on the investigation of the association between the single nucleotide polymorphisms (SNPs) of genes for disease susceptibility. Statistical methods are widely used to search for a good model of gene-gene interaction for disease analysis, and the previously determined models have successfully explained the effects between SNPs and diseases. However, the huge numbers of potential combinations of SNP genotypes limit the use of statistical methods for analysing high-order interaction, and finding an available high-order model of gene-gene interaction remains a challenge. In this study, an improved particle swarm optimization with double-bottom chaotic maps (DBM-PSO) was applied to assist statistical methods in the analysis of associated variations to disease susceptibility. A big data set was simulated using the published genotype frequencies of 26 SNPs amongst eight genes for breast cancer. Results showed that the proposed DBM-PSO successfully determined two- to six-order models of gene-gene interaction for the risk association with breast cancer (odds ratio > 1.0; P value <0.05). Analysis results supported that the proposed DBM-PSO can identify good models and provide higher chi-square values than conventional PSO. This study indicates that DBM-PSO is a robust and precise algorithm for determination of gene-gene interaction models for breast cancer.

Identifying association model for single-nucleotide polymorphisms of ORAI1 gene for breast cancer

Background

ORAI1 channels play an important role for breast cancer progression and metastasis. Previous studies indicated the strong correlation between breast cancer and individual single nucleotide polymorphisms (SNPs) of ORAI1 gene. However, the possible SNP-SNP interaction of ORAI1 gene was not investigated.

Results

To develop the complex analyses of SNP-SNP interaction, we propose a genetic algorithm (GA) to detect the model of breast cancer association between five SNPs (rs12320939, rs12313273, rs7135617, rs6486795 and rs712853) of ORAI1 gene. For individual SNPs, the differences between case and control groups in five SNPs of ORAI1 gene were not significant. In contrast, GA-generated SNP models show that 2-SNP (rs12320939-GT/rs6486795-CT), 3-SNP (rs12320939-GT/rs12313273-TT/rs6486795-TC), 5-SNP (rs12320939-GG/rs12313273-TC/rs7135617-TT/rs6486795-TT/rs712853-TT) have higher risks for breast cancer in terms of odds ratio analysis (1.357, 1.689, and 13.148, respectively).

Conclusion

Taken together, the cumulative effects of SNPs of ORAI1 gene in breast cancer association study were well demonstrated in terms of GA-generated SNP models.

Vascular endothelial growth factor +936C/T polymorphism and breast cancer risk: a meta-analysis of 13 case-control studies

The association between vascular endothelial growth factor (VEGF) +936C/T polymorphism and breast cancer risk has been widely reported, but results were inconsistent. In order to derive a more precise estimation of the relationship, a meta-analysis was performed. Eligible articles were identified through search of databases including PubMed, Embase, and Chinese Biomedical Literature Database (CBM). The association between the VEGF +936C/T polymorphism and breast cancer risk was conducted by odds ratios (ORs) and 95 % confidence intervals (95 % CIs). Finally, a total of 13 studies with 6,879 cases and 7,219 controls were included in our meta-analysis. Overall, a significant association was found between VEGF +936C/T polymorphisms and the risk of breast cancer in overall populations under five models (T vs. C: OR = 0.83, 95 % CI = 0.73–0.94, P = 0.002; TT vs. CC: OR = 0.74, 95 % CI = 0.61–0.91, P = 0.004, Fig. 1a; TC vs. CC: OR = 0.83, 95 % CI = 0.71–0.96, P = 0.014; TT vs. CC/CT: OR = 0.77, 95 % CI = 0.62–0.94, P = 0.010; TT/TC vs. CC: OR = 0.82, 95 % CI = 0.72–0.95, P = 0.006). In the subgroup analysis by ethnicity, there were also significant associations found between VEGF +936C/T polymorphism and breast cancer risk in Asians and Caucasians. In conclusion, the results of our meta-analysis suggest that the VEGF +936C/T polymorphism is significantly associated with breast cancer development and the VEGF 936T allele carriers may be associated with decreased breast cancer risk.

Identification of SNP barcode biomarkers for genes associated with facial emotion perception using particle swarm optimization algorithm

BACKGROUND

Facial emotion perception (FEP) can affect social function. We previously reported that parts of five tested single-nucleotide polymorphisms (SNPs) in the MET and AKT1 genes may individually affect FEP performance. However, the effects of SNP-SNP interactions on FEP performance remain unclear.

METHODS

This study compared patients with high and low FEP performances (n = 89 and 93, respectively). A particle swarm optimization (PSO) algorithm was used to identify the best SNP barcodes (i.e., the SNP combinations and genotypes that revealed the largest differences between the high and low FEP groups).

RESULTS

The analyses of individual SNPs showed no significant differences between the high and low FEP groups. However, comparisons of multiple SNP-SNP interactions involving different combinations of two to five SNPs showed that the best PSO-generated SNP barcodes were significantly associated with high FEP score. The analyses of the joint effects of the best SNP barcodes for two to five interacting SNPs also showed that the best SNP barcodes had significantly higher odds ratios (2.119 to 3.138; P < 0.05) compared to other SNP barcodes. In conclusion, the proposed PSO algorithm effectively identifies the best SNP barcodes that have the strongest associations with FEP performance.

CONCLUSIONS

This study also proposes a computational methodology for analyzing complex SNP-SNP interactions in social cognition domains such as recognition of facial emotion.

Particle swarm optimization algorithm for analyzing SNP-SNP interaction of renin-angiotensin system genes against hypertension

Most non-significant individual single nucleotide polymorphisms (SNPs) were undiscovered in hypertension association studies. Their possible SNP-SNP interactions were usually ignored and leaded to missing heritability. In present study, we proposed a particle swarm optimization (PSO) algorithm to analyze the SNP-SNP interaction associated with hypertension. Genotype dataset of eight SNPs of renin-angiotensin system genes for 130 non-hypertension and 313 hypertension subjects were included. Without SNP-SNP interaction, most individual SNPs were non-significant difference between the hypertension and non-hypertension groups. For SNP-SNP interaction, PSO can select the SNP combinations involving different SNP numbers, namely the best SNP barcodes, to show the maximum frequency difference between non-hypertension and hypertension groups. After computation, the best PSO-generated SNP barcodes were dominant in non-hypertension in terms of the occurrences of frequency differences between non-hypertension and hypertension groups. The OR values of the best SNP barcodes involving 2-8 SNPs were 0.705-0.334, suggesting that these SNP barcodes were protective against hypertension. In conclusion, this study demonstrated that non-significant SNPs may generate the joint effect in association study. Our proposed PSO algorithm is effective to identify the best protective SNP barcodes against hypertension.

Evaluation of breast cancer susceptibility using improved genetic algorithms to generate genotype SNP barcodes

Genetic association is a challenging task for the identification and characterization of genes that increase the susceptibility to common complex multifactorial diseases. To fully execute genetic studies of complex diseases, modern geneticists face the challenge of detecting interactions between loci. A genetic algorithm (GA) is developed to detect the association of genotype frequencies of cancer cases and noncancer cases based on statistical analysis. An improved genetic algorithm (IGA) is proposed to improve the reliability of the GA method for high-dimensional SNP-SNP interactions. The strategy offers the top five results to the random population process, in which they guide the GA toward a significant search course. The IGA increases the likelihood of quickly detecting the maximum ratio difference between cancer cases and noncancer cases. The study systematically evaluates the joint effect of 23 SNP combinations of six steroid hormone metabolisms, and signaling-related genes involved in breast carcinogenesis pathways were systematically evaluated, with IGA successfully detecting significant ratio differences between breast cancer cases and noncancer cases. The possible breast cancer risks were subsequently analyzed by odds-ratio (OR) and risk-ratio analysis. The estimated OR of the best SNP barcode is significantly higher than 1 (between 1.15 and 7.01) for specific combinations of two to 13 SNPs. Analysis results support that the IGA provides higher ratio difference values than the GA between breast cancer cases and noncancer cases over 3-SNP to 13-SNP interactions. A more specific SNP-SNP interaction profile for the risk of breast cancer is also provided.

Improved branch and bound algorithm for detecting SNP-SNP interactions in breast cancer

BACKGROUND

Single nucleotide polymorphisms (SNPs) in genes derived from distinct pathways are associated with a breast cancer risk. Identifying possible SNP-SNP interactions in genome-wide case-control studies is an important task when investigating genetic factors that influence common complex traits; the effects of SNP-SNP interaction need to be characterized. Furthermore, observations of the complex interplay (interactions) between SNPs for high-dimensional combinations are still computationally and methodologically challenging. An improved branch and bound algorithm with feature selection (IBBFS) is introduced to identify SNP combinations with a maximal difference of allele frequencies between the case and control groups in breast cancer, i.e., the high/low risk combinations of SNPs.

RESULTS

A total of 220 real case and 334 real control breast cancer data are used to test IBBFS and identify significant SNP combinations. We used the odds ratio (OR) as a quantitative measure to estimate the associated cancer risk of multiple SNP combinations to identify the complex biological relationships underlying the progression of breast cancer, i.e., the most likely SNP combinations. Experimental results show the estimated odds ratio of the best SNP combination with genotypes is significantly smaller than 1 (between 0.165 and 0.657) for specific SNP combinations of the tested SNPs in the low risk groups. In the high risk groups, predicted SNP combinations with genotypes are significantly greater than 1 (between 2.384 and 6.167) for specific SNP combinations of the tested SNPs.

CONCLUSIONS

This study proposes an effective high-speed method to analyze SNP-SNP interactions in breast cancer association studies. A number of important SNPs are found to be significant for the high/low risk group. They can thus be considered a potential predictor for breast cancer association.

Improved branch and bound algorithm for detecting SNP-SNP interactions in breast cancer

Background

Single nucleotide polymorphisms (SNPs) in genes derived from distinct pathways are associated with a breast cancer risk. Identifying possible SNP-SNP interactions in genome-wide case–control studies is an important task when investigating genetic factors that influence common complex traits; the effects of SNP-SNP interaction need to be characterized. Furthermore, observations of the complex interplay (interactions) between SNPs for high-dimensional combinations are still computationally and methodologically challenging. An improved branch and bound algorithm with feature selection (IBBFS) is introduced to identify SNP combinations with a maximal difference of allele frequencies between the case and control groups in breast cancer, i.e., the high/low risk combinations of SNPs.

Results

A total of 220 real case and 334 real control breast cancer data are used to test IBBFS and identify significant SNP combinations. We used the odds ratio (OR) as a quantitative measure to estimate the associated cancer risk of multiple SNP combinations to identify the complex biological relationships underlying the progression of breast cancer, i.e., the most likely SNP combinations. Experimental results show the estimated odds ratio of the best SNP combination with genotypes is significantly smaller than 1 (between 0.165 and 0.657) for specific SNP combinations of the tested SNPs in the low risk groups. In the high risk groups, predicted SNP combinations with genotypes are significantly greater than 1 (between 2.384 and 6.167) for specific SNP combinations of the tested SNPs.

Conclusions

This study proposes an effective high-speed method to analyze SNP-SNP interactions in breast cancer association studies. A number of important SNPs are found to be significant for the high/low risk group. They can thus be considered a potential predictor for breast cancer association.

The single-nucleotide polymorphisms +936 C/T VEGF and -710 C/T VEGFR1 are associated with breast cancer protection in a Spanish population

Vascular endothelial growth factor (VEGF) is a potent regulator of angiogenesis and thereby involved in the development and progression of solid tumours. The association between polymorphisms of angiogenesis pathway genes and risk of breast cancer (BC) has been widely studied, but the results are not conclusive. This information is especially limited in Spanish women, so we decided to conduct a case-control study. Here, we selected four commonly studied polymorphisms in VEGF, rs3025039 (known as +936 C/T), rs1109324, rs154765 and rs833052, one polymorphism at the promoter of the VEGFR1 (-710 C/T) and another in the FGF2, rs1449683, gene to explore their association with BC susceptibility. Genotyping was performed by TaqMan SNP assays and polymerase chain reaction-restriction fragment length polymorphis (PCR-RFLP) on 453 patients and 461 controls in a population from Valencia (Spain). We observed that women carriers of +936 CT + TT VEGF genotypes have a protective effect concerning this disease (p = 0.014; OR 0.67, 95% CI 0.48-0.92) in the global group of patients. The haplotype TGAC of VEGF (rs3025039, rs1109324, rs154764 and rs833052) shows a reduction of the risk to develop BC (p = 3e-04; OR 0.48, 95% CI 0.32-0.72). Furthermore, we found that carriers of -710 CT + TT VEGFR1 genotypes have also a protective effect (p = 0.039; OR 0.55, 95% CI 0.31-0.98). When we stratified by groups of ages these associations were maintained. Our data report for the first time the association of the polymorphism -710 C/T VEGFR1 with BC. Additional experiments focused on VEGF-A, VEGFR1 and sVEGFR1 gene expression demonstrated that carriers of T allele at -710 C/T VEGFR1 genotype have higher levels of sVEGFR1/VEGF-A than the C/C genotype carriers. This was consistent with the hypothesis that this polymorphism may act as low penetrance risk factor. The data provided suggest that +936 C/T VEGF and -710 C/T VEGFR1 genotypes are likely important genetic markers of susceptibility to BC.

The CXCL12 G801A polymorphism and cancer risk: evidence from 17 case-control studies

CXCL12 has been implicated in human carcinogenesis, but the association between the most-studied G801A polymorphism (rs1801157) and the risk of various cancers was reported with inconclusive results. The aim of this study was to assess the association between the CXCL12 G801A polymorphism and cancer risk. A meta-analysis of 17 studies with 3048 cancer patients and 4522 controls was conducted to evaluate the strength of the association using odds ratio (OR) with its 95% confidence interval (CI). The overall results showed that the variant genotypes were associated with a significantly increased risk of all cancer types (OR=1.38, 95%CI=1.18-1.61 for GA versus GG, and OR=1.36, 95%CI=1.17-1.59 for GA/AA versus GG). In the stratified analyses, there was a significantly increased risk for the studies of breast cancer (OR=1.64, 95% CI=1.16-2.33 for AA versus GG, OR=1.42, 95%CI=1.18-1.71 for GA versus GG, and OR=1.44, 95%CI=1.21-1.72 for GA/AA versus GG) and lung cancer (OR=2.86, 95% CI=1.75-4.69 for AA versus GG, OR=1.62, 95% CI=1.20-2.18 for GA vs. GG, OR=1.80, 95% CI=1.36-2.39 for GA/AA versus GG, and OR=2.24, 95%CI=1.41-3.57 for AA versus GA/GG), which remained for the studies of Asian populations and hospital-based control sources. Although some modest bias could not be eliminated, this meta-analysis indicates that the CXCL12 G801A polymorphism is a low-penetrance risk factor for cancer development.

Sequence-based polymorphisms in the mitochondrial D-loop and potential SNP predictors for chronic dialysis

Background

The mitochondrial (mt) displacement loop (D-loop) is known to accumulate structural alterations and mutations. The aim of this study was to investigate the prevalence of single nucleotide polymorphisms (SNPs) within the D-loop among chronic dialysis patients and healthy controls.

Methodology and Principal Findings

We enrolled 193 chronic dialysis patients and 704 healthy controls. SNPs were identified by large scale D-loop sequencing and bioinformatic analysis. Chronic dialysis patients had lower body mass index, blood thiols, and cholesterol levels than controls. A total of 77 SNPs matched with the positions in reference of the Revised Cambridge Reference Sequence (CRS) were found in the study population. Chronic dialysis patients had a significantly higher incidence of 9 SNPs compared to controls. These include SNP5 (16108Y), SNP17 (16172Y), SNP21 (16223Y), SNP34 (16274R), SNP35 (16278Y), SNP55 (16463R), SNP56 (16519Y), SNP64 (185R), and SNP65 (189R) in D-loop of CRS. Among these SNPs with genotypes, SNP55-G, SNP56-C, and SNP64-A were 4.78, 1.47, and 5.15 times more frequent in dialysis patients compared to controls (P<0.05), respectively. When adjusting the covariates of demographics and comorbidities, SNP64-A was 5.13 times more frequent in dialysis patients compared to controls (P<0.01). Furthermore, SNP64-A was found to be 35.80, 3.48, 4.69, 5,55, and 4.67 times higher in female patients and in patients without diabetes, coronary artery disease, smoking, and hypertension in an independent significance manner (P<0.05), respectively. In patients older than 50 years or with hypertension, SNP34-A and SNP17-C were found to be 7.97 and 3.71 times more frequent (P<0.05) compared to patients younger than 50 years or those without hypertension, respectively.

Conclusions and Significance

The results of large-scale sequencing suggest that specific SNPs in the mtDNA D-loop are significantly associated with chronic dialysis. These SNPs can be considered as potential predictors for chronic dialysis.

An improved PSO algorithm for generating protective SNP barcodes in breast cancer

Background

Possible single nucleotide polymorphism (SNP) interactions in breast cancer are usually not investigated in genome-wide association studies. Previously, we proposed a particle swarm optimization (PSO) method to compute these kinds of SNP interactions. However, this PSO does not guarantee to find the best result in every implement, especially when high-dimensional data is investigated for SNP–SNP interactions.

Methodology/Principal Findings

In this study, we propose IPSO algorithm to improve the reliability of PSO for the identification of the best protective SNP barcodes (SNP combinations and genotypes with maximum difference between cases and controls) associated with breast cancer. SNP barcodes containing different numbers of SNPs were computed. The top five SNP barcode results are retained for computing the next SNP barcode with a one-SNP-increase for each processing step. Based on the simulated data for 23 SNPs of six steroid hormone metabolisms and signalling-related genes, the performance of our proposed IPSO algorithm is evaluated. Among 23 SNPs, 13 SNPs displayed significant odds ratio (OR) values (1.268 to 0.848; p<0.05) for breast cancer. Based on IPSO algorithm, the jointed effect in terms of SNP barcodes with two to seven SNPs show significantly decreasing OR values (0.84 to 0.57; p<0.05 to 0.001). Using PSO algorithm, two to four SNPs show significantly decreasing OR values (0.84 to 0.77; p<0.05 to 0.001). Based on the results of 20 simulations, medians of the maximum differences for each SNP barcode generated by IPSO are higher than by PSO. The interquartile ranges of the boxplot, as well as the upper and lower hinges for each n-SNP barcode (n = 3∼10) are more narrow in IPSO than in PSO, suggesting that IPSO is highly reliable for SNP barcode identification.

Conclusions/Significance

Overall, the proposed IPSO algorithm is robust to provide exact identification of the best protective SNP barcodes for breast cancer.

Association of genetic polymorphisms of CXCL12/SDF1 gene and its receptor, CXCR4, to the susceptibility and prognosis of non-small cell lung cancer

BACKGROUND

The aim of this study was to evaluate the relations of chemokine CXCL12, previously known as stromal cell-derived factor-1 (SDF1), and its receptor, CXCR4, gene variants on non-small cell lung cancer (NSCLC) risk and disease severity.

METHODS

Through a case-control study design, genomic DNA samples of 247 NSCLC patients and 328 age and sex-matched controls were subjected to polymerase chain reaction-restriction fragment length polymorphism analysis. The validity of this technique was proven by direct sequencing of amplified products. Statistical analyses were conducted to explore the contribution of polymorphism of the CXCL12/SDF1 gene and CXCR4, in the susceptibility to and prognosis of NSCLC.

RESULTS

Overall, the genotype frequencies of CXCL12/SDF1 gene and CXCR4, were significantly different between lung cancer patients and controls (p<0.0001), and also different between patients with lung cancers of various stages (p<0.0001). Logistic regression analysis revealed that higher odds ratios (ORs) for lung cancer were seen for individuals with CXCL12/SDF1 AA (an OR of 1.95, 95% CI 1.08-3.50, p=0.018), or CXCR4 TT (an OR of 4.71, 95% CI 1.99-11.2, p<0.0001), and for individuals with both CXCL12/SDF1 AA and CXCR4 TT genotypes (an OR of 12.4, 95% CI 1.56-98.3, p=0.002). The patients carrying a homologous AA genotype at CXCL12/SDF1, or a homologous TT genotype at CXCR4, had a tendency to advanced disease and toward poorer prognoses compared with other patients.

CONCLUSION

A significant association between the polymorphisms of CXCL12/SDF1 and CXCR4, and the susceptibility to and prognosis of NSCLC was demonstrated.

Current evidences on vascular endothelial growth factor polymorphisms and breast cancer susceptibility

Several polymorphisms of vascular endothelial growth factor (VEGF) such as 936 C/T, -2578 C/A, -406 C/T, and -1154 G/A polymorphism have been identified. Published data on the association between VEGF polymorphisms and breast cancer risk are inconclusive. To derive a more precise estimation of the relationship, a meta-analysis was performed. Crude OR with 95% CI was used to assess the strength of association between them. For VEGF 936C/T polymorphism, a total of 10 studies including 7,685 cases and 7,915 controls were involved in this meta-analysis. Overall, no significant associations were found between VEGF 936C/T polymorphism and breast cancer risk when all studies pooled into the meta-analysis (TC vs. CC: OR = 0.904, 95% CI = 0.797-1.024; TT vs. CC: OR = 0.974, 95% CI = 0.786-1.205; dominant model: OR = 0.911, 95% CI = 0.811-1.024; and recessive model: OR = 0.991, 95% CI = 0.801-1.226). In the subgroup analysis by ethnicity, still no significant associations were found for all comparison models. For -2578 C/A, -406 C/T, and -1154 G/A polymorphism, there were too limited data to perform a meta-analysis. In conclusion, this meta-analysis suggests that the VEGF 936C/T polymorphism may be not associated with breast cancer development. However, large sample and representative population-based studies with homogeneous breast cancer patients and well matched controls are warranted to confirm this finding.