Joint effect of peroxisome proliferator-activated receptor γ genetic polymorphisms and estrogen-related risk factors on breast cancer risk: results from a case-control study in Taiwan

Contribution of gene polymorphisms on 3p25 to salivary gland carcinoma, ameloblastoma, and odontogenic keratocyst in the Chinese Han population

OBJECTIVE

This study aimed to investigate the contribution of gene polymorphisms in 3p25 to salivary gland carcinoma (SGC), ameloblastoma (AM), and odontogenic keratocyst (OKC) in the Chinese Han population.

STUDY DESIGN

Sixteen tag-single nucleotide polymorphisms (SNPs) within 5 genes (SYN2, TIMP4, PPARG, RAF1, and IQSEC1) in 3p25 were genotyped in 411 individuals with or without SGC, AM, and OKC. Genotype, clinical phenotype, and bioinformatics analyses were performed to evaluate the function of candidate SNPs.

RESULTS

SYN2-rs3773364, TIMP4-rs3755724, PPARG-rs10865710, and PPARG-rs1175544 were related to decreased SGC susceptibility, whereas IQSEC1-rs2600322 and IQSEC1-rs2686742 decreased and increased AM risk, respectively. Stratification analysis revealed that the significance of the identified SNPs was stronger in females or individuals younger than 46 years in SGC. PPARG-rs10865710 and PPARG-rs1175544 were associated with lower lymph node metastasis. SYN2-rs3773364 and PPARG-rs1175544 were associated with favorable SGC patient survival. Functional assessments linked PPARG-rs1175544 to PPARG expression regulation. Linkage disequilibrium analysis revealed a haplotype (SYN2-rs3773364-A, TIMP4-rs3817004-A, and TIMP4-rs3755724-C) associated with decreased susceptibility to SGC. Generalized multifactor dimensionality reduction analysis indicated the gene-gene interactions among IQSEC1, TIMP4, and PPARG in SGC, AM, and OKC progression.

CONCLUSIONS

These variants play important roles in the progression of SGC, AM, and OKC in the Chinese Han population and may be considered biomarkers for early diagnosis and prognosis prediction.

Association between PPARγ, PPARGC1A, and PPARGC1B genetic variants and susceptibility of gastric cancer in an Eastern Chinese population

PURPOSE

Previous studies showed that peroxisome proliferator-activated receptor gamma (PPARγ) and PPARγ coactivator1 family (PPARGC1A and PPARGC1B) gene single nucleotide variants (SNVs)were strongly associated with cancer susceptibility. The purpose of this study was to investigate the association of PPARγ, PPARGC1A, and PPARGC1B variants with the risk of gastric cancer (GC).

PATIENTS AND METHODS

We performed a case-control study of 490 GC cases and 1,476 healthy controls from eastern China. PPARγ rs1801282 C > G, rs3856806 C > T, PPARGC1A rs2970847 C > T, rs8192678 C > T and PPARGC1B rs7732671 G > C, rs17572019 G > A SNVs were selected to investigate the association between these SNVs and GC susceptibility. Genotypes of the SNVs were assessed by multiplex fluorescent PCR using a custom-by-design 48-Plex SNPscan^tm Kit.

RESULTS

The PPARγ rs1801282 SNV was associated with a decreased risk for GC (GC vs. CC: odds ratio (OR) = 0.62, 95% confidence interval (95%CI) = 0.42-0.93, adjusted P = 0.019; GC + GG vs. GG: OR = 0.63 95%CI = 0.42-0.93, adjusted P = 0.019; respectively). In addition, stratified analysis revealed that the PPARγ rs1801282 SNV was correlated with the risk of GC in subgroups of age ≥ 61, no smoking, and no alcohol consuming. We also confirmed that the PPARγ rs3856806 C > T SNV promoted the risk of GC in women. The PPARGC1A rs8192678 TT genotype decreased the susceptibility of GC in men. The PPARGC1A rs2970847 C > T SNV decreased the susceptibility of GC in the subgroup of BMI ≥ 24 kg/m². The PPARGC1B rs7732671 G > C and rs17572019 G > A SNVs promoted the risk of GC in the subgroup of BMI ≥ 24 kg/m².

CONCLUSION

This study indicates that the PPARγ, PPARGC1A, and PPARGC1B SNVs may be associated with the susceptibility of GC in eastern Chinese population. Future studies with larger populations, detailed H. pylori infection status for subgroup analysis, and functional study are needed to further clarify the relationship between these SNVs and GC risk.

Peroxisome Proliferator-Activated Receptor Gamma Pro12Ala/C161T Genotypes and Risky Haplotype Altering Risk of Breast Cancer: A Turkish Case-Control Study

Breast cancer (BC) has a high incidence rate among women worldwide, and the mechanisms and etiology of this disease are not yet fully understood. The peroxisome proliferator-activated receptor gamma (PPARgamma), a nuclear hormone receptor that plays important roles in energy metabolism and cellular differentiation, is also suggested to be effective in cancer development. However, the results of studies investigating the cancer association with PPARgamma are inconsistent, creating a need for further investigation of the effects of this transcription factor on BC risk. We have examined the Pro12Ala-(rs1801282) and C161T-(rs3856806) polymorphisms of the PPARgamma gene in Turkish patients with BC in this case-control study. A total of 95 women diagnosed with BC as cases and 119 controls were genotyped for PPARgamma polymorphisms by polymerase chain reaction and restriction fragment length polymorphism techniques. The ProPro genotype and T161 allele were associated with an increased risk of BC comparing with the Ala12 allele and CC161 genotype, respectively (p < 0.001). The multivariate regression analysis confirmed that the ProPro genotype (p < 0.011), T161 allele (p < 0.001), smoking (p = 0.019), and advanced age (> 60 years) (p = 0.007) are risk factors for breast cancer. We also found that the PPARgamma Pro12Ala and C161T polymorphisms were in linkage disequilibrium (D':0.511, r²:0.099). It was determined that carrying ProPro-T161 risky PPARgamma haplotype was associated with a higher risk of BC compared to protective Ala12-CC161 haplotype (p < 0.01, OR:7.797, 95% CI:3.521-17.263). We concluded that PPARgamma Pro12Ala and C161T polymorphisms are associated with increased BC risk, and ProPro-T161 risky haplotype, which is in linkage disequilibrium, increases this effect.

Analysis of key genes and pathways in breast ductal carcinoma in situ

Breast cancer (BC) remains the most common cancer in females. Therefore, the present study aimed to identify key genes involved in the carcinogenesis of BC and to explore their prognostic values by integrating bioinformatics tools. The gene expression profiles of 46 ductal carcinoma in situ (DCIS) and three normal breast tissues from the GSE59248 dataset were downloaded. Differentially expressed genes (DEGs) were subsequently identified using the online tool GEO2R and a functional enrichment analysis was performed. In addition, a protein-protein interaction (PPI) network was constructed and the top eight hub genes were identified. The prognostic values of the hub genes were further investigated. A total of 316 DEGs, including 32 upregulated and 284 downregulated genes, were identified. Furthermore, eight hub genes, including lipase E hormone sensitive type, patatin like phospholipase domain containing 2, adiponectin C1Q and collagen domain containing (ADIPOQ), peroxisome proliferator activated receptor γ (PPARG), fatty acid binding protein 4 (FABP4), diacylglycerol O-acyltransferase 2, lipoprotein lipase (LPL) and leptin (LEP), were identified from the PPI network. The downregulated expression of ADIPOQ, PPARG, FABP4, LPL and LEP was significantly associated with poor overall survival in patients with DCIS. Therefore, these genes may serve as potential biomarkers for prognosis prediction. However, further investigation is required to validate the results obtained in the present study.

Genetic polymorphisms of PPAR genes and human cancers: evidence for gene-environment interactions

Peroxisome proliferator-activated receptors (PPARs) are nuclear transcription factors that play a role in lipid metabolism, cell proliferation, terminal differentiation, apoptosis, and inflammation. Although several cancer models have been suggested to explain PPARs' involvement in tumorigenesis, however, their role is still unclear. In this review, we examined associations of the different PPARs, polymorphisms and various types of cancer with a focus on gene-environment interactions. Reviewed evidence suggests that functional genetic variants of the different PPARs may modulate the relationship between environmental exposure and cancer risk. In addition, this report unveils the scarcity of reliable quantitative environmental exposure data when examining these interactions, and the current gaps in studying gene-environment interactions in many types of cancer, particularly colorectal, prostate, and bladder cancers.

PPARG c.1347C>T polymorphism is associated with cancer susceptibility: from a case-control study to a meta-analysis

Recently, several studies suggested that PPARG c.1347C>T polymorphism was correlated with cancer risk. However, past results remained controversial. In this study, we performed a case-control study on the relationship of PPARG c.1347C>T polymorphism with risk of non-small cell lung cancer (NSCLC) and subsequently carried out a meta-analysis to further assess the association between PPARG c.1347C>T and overall cancer. In our case-control study, after adjusting by age, sex, body mass index (BMI), smoking and drinking, a tendency to increased NSCLC risk was noted (CT/TT vs. CC: adjusted OR, 1.21; 95% CI, 0.97–1.51; P = 0.097). In the meta-analysis, we found a significant association between PPARG c.1347C>T polymorphism and overall cancer risk (T vs. C: OR, 1.13; 95% CI, 1.03–1.23; P = 0.006; TT vs. CC: OR, 1.29; 95% CI, 1.07–1.56; P = 0.008, CT/TT vs. CC: OR, 1.11; 95% CI, 1.02–1.21; P = 0.014 and TT vs. CT/CC: OR, 1.26; 95% CI, 1.04–1.52; P = 0.016). In a subgroup analysis by ethnicity, evidence of significant association between PPARG c.1347C>T polymorphism and cancer risk was found among Asians and mixed populations. In a subgroup analysis by cancer type, PPARG c.1347C>T polymorphism was associated with risk of esophageal cancer and glioblastoma. In addition, in a subgroup analysis by origin of cancer cell, evidence of significant association between PPARG c.1347C>T polymorphism and cancer risk was also found among epithelial tumor. In conclusion, the findings indicate PPARG c.1347C>T polymorphism may increase the susceptibility of cancer.

Lack of effects of peroxisome proliferator-activated receptor gamma genetic polymorphisms on breast cancer risk: a case-control study and pooled analysis

A growing body of evidence suggests that the peroxisome proliferator-activated receptor-gamma (PPARγ) gene may harbor targets for the chemoprevention of breast cancer. However, it is unclear whether polymorphisms in the PPARγ gene are associated with the susceptibility of breast cancer. We performed a candidate gene association study between PPARγ polymorphisms and breast cancer and a meta-analysis on the association of breast cancer with selected PPARγ variants. Six single nucleotide polymorphisms (SNPs) in the PPARγ gene were analyzed among 456 breast cancer patients and 461 controls from the National Cancer Center in Korea. Association between the polymorphisms and breast cancer risk were assessed using the Cochrane-Armitage test for trend and a multivariate logistic regression model. Two SNPs, rs3856806 and rs1801282, had been previously analyzed, thus enabling us to perform pooled analyses on their associations with breast cancer susceptibility. Our findings from the candidate gene association study showed no association between the PPARγ gene polymorphisms and breast cancer risk. A meta-analysis combining existing studies and our current study also refuted an association of the PPARγ gene with breast cancer. Our findings suggest that the PPARγ gene may not harbor variants that alter breast cancer susceptibility, although a moderate sample size might have precluded a decisive conclusion.

Association between genetic polymorphisms of inflammatory response genes and the risk of ovarian cancer

BACKGROUND/PURPOSE

Inflammation plays an important role in promoting ovarian tumorigenesis and cancer progression. However, the relationship between polymorphisms in inflammatory response genes and risk of ovarian cancer remains poorly understood. In this study, we investigated the association of PPARG Pro12Ala, IL6-174G/C, E-selectin S128R, NFKB1-94 ins/del, NFKBIA-826C/T, and ICAM-1 K469E polymorphisms with ovarian cancer risk in a Chinese population.

METHODS

Genotyping of the polymorphisms was performed on 687 cases and 687 controls employing the PCR-RFLP technique, and the logistic regression model was used to measure the risk association.

RESULTS

A significantly increased risk association was observed for the heterozygous genotypes of PPARG [odds ratio (OR) = 1.52, 95% confidence interval (CI) = 1.01-2.29] and E-selectin (OR = 1.77, 95% CI = 1.07-2.93) polymorphisms, as well as the homozygous ins/ins genotype of NFKB1 polymorphism (OR = 1.39, 95% CI = 1.00-1.92). By contrast, ICAM-1 KE genotype was associated with a decreased ovarian cancer risk (OR = 0.77, 95% CI = 0.60-0.98). In addition, the NFKB1 del/del + NFKBIA TT combination was also found to be associated with a decreased ovarian cancer risk, with OR = 0.12 (95% CI = 0.01-0.95). The associations of the NFKB1 and ICAM-1 polymorphisms replicated the findings of previous reports, assuring the reliability of the results obtained.

CONCLUSION

NFKB1 and ICAM-1 polymorphisms could serve as useful ovarian cancer risk prediction biomarkers for the Chinese population, while the utility of PPARG and E-selectin polymorphisms as biomarkers requires further confirmation in independent ovarian cancer cohorts.

Peroxisome proliferator‑activated receptor γ polymorphisms as risk factors for dyslipidemia

Peroxisome proliferator‑activated receptor γ (PPARγ) may play an important role in lipid metabolism directly or by inducing the transcription of target genes. The aim of the present study was to investigate the association between common variants at the PPARγ locus (C1431T and Pro12Ala polymorphisms) and lipid serum levels. The studied population consisted of 820 subjects randomly selected from the Prevention of Multiple Metabolic Disorders and Metabolic Syndrome in Jiangsu Province cohort population. All subjects were interviewed and blood samples were obtained for laboratory analysis and DNA extraction. The TaqMan single nucleotide polymorphism genotyping assay was used for polymorphism genotyping. Individual polymorphisms and haplotype data were available for analysis. The 12Ala allele was found to be associated with significantly increased levels of triglyceride (TG) (P<0.01), whilst the 1431T allele was found to be associated with significantly increased levels of TG, total cholesterol (TC) and non‑high‑density lipoprotein (non‑HDL) (P<0.01). When P‑C, the most common haplotype, was used as the reference group, the P‑T, A‑C and A‑T haplotypes were found to be associated with significantly increased levels of TG (P<0.01). In addition, the A‑T haplotype was shown to be associated with significantly increased levels of TC and non‑HDL (P<0.01). In conclusion these results suggest that PPARγ gene variability may increase the risk of dyslipidemia.

PPAR α and PPAR γ polymorphisms as risk factors for dyslipidemia in a Chinese Han population

BACKGROUND

The PPAR α and PPAR γ are the key messengers responsible for the translation of nutritional stimuli into changes for the expression of genes, particularly genes involved in lipid metabolism. However, the associations between PPAR α/γ polymorphisms and lipid serum levels in the general population were rarely studied, and the conclusions were conflicting. The objective was to investigate the associations of the PPAR α and PPAR γ polymorphisms with dyslipidemia.

METHODS

820 subjects were randomly selected from the Prevention of Multiple Metabolic Disorders and MS in Jiangsu Province cohort populations. The logistic regression model was used to examine the association between these polymorphisms and dyslipidemia. SNPstats was used to explore the haplotype association analyses.

RESULTS

In the codominant and log-additive models, rs1800206, rs1805192 and rs3856806 were all associated with dyslipidemia (P < 0.005). When the most common haplotype L-G (established by rs1800206, rs4253778) was treated as the reference group, the V-G haplotype was associated with dyslipidemia (P < 0.001), higher TC and TG levels (P < 0.01). Moreover, when compared to Pro-C haplotype (established by rs1805192, rs3856806), the Pro-T, Ala-C, Ala-T haplotypes were associated with dyslipidemia (p < 0.001). A-T haplotype was associated with higher TC levels, (p < 0.01), and the P-T, A-C, A-T haplotypes were associated with higher TG levels (p < 0.01).

CONCLUSIONS

PPAR α and PPAR γ polymorphisms and haplotypes may be the genetic risk factors for dyslipidemia.

Peroxisome proliferator-activated receptor γ2 Pro12Ala (rs1801282) polymorphism and breast cancer susceptibility: a meta-analysis

Several studies have investigated the correlation between the peroxisome proliferator-activated receptor γ2 (PPAR‑γ2) Pro12Ala (rs1801282) polymorphism and the risk of breast cancer, with inconsistent results. For this reason, a meta-analysis was conducted to identify the potential correlation after pooling data from eligible case-control studies. Search strategies were conducted in PubMed, EMBASE and the COCHRANE Library in English and from VIP, CNKI and Sinomed in Chinese (all the papers were published before November 11, 2012) using appropriate terms. A total of 2,279 cases and 2,360 controls from four related case-control studies were included in this meta-analysis. According to the three eligible populations, the odds ratios (ORs) and 95% confidence intervals (CIs) on the risk of breast cancer for the CG versus CC and GG versus CC genotypes and the G versus C allele were 0.84 and 0.72-0.98, 0.92 and 0.32-2.61, and 0.98 and 0.84-1.13, respectively. The OR and 95% CI for CG+GG versus CC from the four study populations were 0.85 and 0.73-0.98, respectively. This meta-analysis supported the fact that the G allele of PPAR‑γ2 Pro12Ala (rs1801282) modestly affects the risk of breast cancer. Nevertheless, further studies are required to enrich the evidence of this correlation.

PPARγ and PPARGC1B polymorphisms modify the association between phthalate metabolites and breast cancer risk

CONTEXT

Breast cancer (BC) risk has been differentially associated with urinary levels of some phthalate metabolites.

OBJECTIVE

To investigate whether PPARγ and PPARGC1B polymorphisms modulate these associations.

MATERIALS AND METHODS

208 BC cases were age-matched with 220 population controls. Phthalate metabolites were determined by HPLC-MS. PPARγ Pro12Ala (rs1801281) and PPARGC1B Ala203Pro (rs7732671) and Val279Ile (rs17572019) were genotyped.

RESULTS

The association between mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) and BC risk was positively modified in PPARγ Pro12Ala C carriers. The association with mono-iso-butyl phthalate (MiBP) in PPARGC1B Ala203Pro G carriers was negatively modified.

CONCLUSION

PPARγ and PPARGC1B polymorphisms modulate the association between phthalate exposure and BC risk.

Genetic variation in peroxisome proliferator-activated receptor gamma, soy, and mammographic density in Singapore Chinese women

BACKGROUND

PPARγ is a transcription factor important for adipogenesis and adipocyte differentiation. Data from animal studies suggest that PPARγ may be involved in breast tumorigenesis, but results from epidemiologic studies on the association between PPARγ variation and breast cancer risk have been mixed. Recent data suggest that soy isoflavones can activate PPARγ. We investigated the interrelations of soy, PPARγ, and mammographic density, a biomarker of breast cancer risk in a cross-sectional study of 2,038 women who were members of the population-based Singapore Chinese Health Study Cohort.

METHODS

We assessed mammographic density using a computer-assisted method. We used linear regression to examine the association between 26 tagging single-nucleotide polymorphisms (SNP) of PPARγ and their interaction with soy intake and mammographic density. To correct for multiple testing, we calculated P values adjusted for multiple correlated tests (P(ACT)).

RESULTS

Out of the 26 tested SNPs in the PPARγ, seven SNPs were individually shown to be statistically significantly associated with mammographic density (P(ACT) = 0.008-0.049). A stepwise regression procedure identified that only rs880663 was independently associated with mammographic density which decreased by 1.89% per-minor allele (P(ACT) = 0.008). This association was significantly stronger in high-soy consumers as mammographic density decreased by 3.97% per-minor allele of rs880663 in high-soy consumers (P(ACT) = 0.006; P for interaction with lower soy intake = 0.017).

CONCLUSIONS

Our data support that PPARγ genetic variation may be important in determining mammographic density, particularly in high-soy consumers.

IMPACT

Our findings may help to identify molecular targets and lifestyle intervention for future prevention research.