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

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.

A PPARG Splice Variant in Granulosa Cells Is Associated with Polycystic Ovary Syndrome

BACKGROUND

We explored whether there are splice variants (SVs) of peroxisome proliferator-activated receptor-gamma (PPARG) in polycystic ovary syndrome (PCOS) patients and its relationship with clinical features and KGN cell functions.

METHODS

We performed a study involving 153 women with PCOS and 153 age-matched controls. One type of PPARG SV was detected by SMARTer RACE. The correlations between PPARG SV expression levels, clinical features, and KGN cell functions were analyzed. The effect of the PPARG SV on the expression of important genes in metabolism-related pathways was explored by PCR array.

RESULTS

The expression of the PPARG SV in PCOS patients was significantly higher than that in the controls. Clinical features were more significant in the PCOS group with the SV. Compared with overexpression of PPARG, the overexpression of the PPARG SV inhibited the proliferation, migration, and apoptosis of KGN cells in vitro. The genes related to the PPARG SV were mainly involved in lipid metabolism.

CONCLUSION

While granulosa cells contribute greatly to the development of follicles, our results suggest that the identified PPARG SV may regulate cell proliferation, migration, and apoptosis in granulosa cells, which could partially explain the mechanisms of ovulation dysfunction in PCOS. Further investigation of the utility of this PPARG SV as a biomarker for PCOS is warranted.

Differential Oral Microbial Input Determines Two Microbiota Pneumo-Types Associated with Health Status

The oral and upper respiratory tracts are closely linked anatomically and physiologically with the lower respiratory tract and lungs, and the influence of oral and upper respiratory microbes on the lung microbiota is increasingly being recognized. However, the ecological process and individual heterogeneity of the oral and upper respiratory tract microbes shaping the lung microbiota remain unclear owing to the lack of controlled analyses with sufficient sample sizes. Here, the microbiomes of saliva, nasal cavity, oropharyngeal area, and bronchoalveolar lavage samples are profiled and the shaping process of multisource microbes on the lung microbiota is measured. It is found that oral and nasal microbial inputs jointly shape the lung microbiota by occupying different ecological niches. It is also observed that the spread of oral microbes to the lungs is heterogeneous, with more oral microbes entering the lungs being associated with decreased lung function and increased lung proinflammatory cytokines. These results depict the external shaping process of lung microbiota and indicate the great value of oral samples, such as saliva, in monitoring and assessing lung microbiota status in clinical settings.

The Role of PPAR-gamma C161T Polymorphism in Colorectal Cancer Susceptibility

BACKGROUND/AIM

This study aimed to determine the role of the peroxisome proliferator-activated receptor-gamma (PPARg) C161T genotype and allele frequencies in predisposition to colorectal cancer (CRC).

PATIENTS AND METHODS

PPARg C161T (His447His; rs3856806) gene polymorphisms were determined by polymerase chain reaction-restriction fragment length polymorphism analysis in patients with CRC (n=101) and controls (n=238).

RESULTS

The T161 allele (CT+TT genotypes) of PPARg C161T polymorphism was associated with CRC development (p<0.001; OR=3.239, 95%CI=1.997-5.252). Subgroup analysis showed that the T161 allele was associated with a 3.056-fold increased risk for colon cancer (CC) (p<0.001; 95%CI=1.709-5.464) and 3.529-fold increased risk for rectal cancer (RC) (p<0.001; 95%C=1.784-6.981). Frequencies of the T161 allele were also higher in total CRC and CC patients with poorly differentiated tumors (p<0.001, c²=30,601, OR=3.109; 95%CI=1.970-4.906 and p<0.001, Fisher exact test, respectively).

CONCLUSION

PPARg T161 allele carriers have increased risk for developing CRC.

Identification and Validation of an Immune and Ferroptosis-Combined Index for Non-Small Cell Lung Cancer

Background: Non-small cell lung cancer (NSCLC) is among the major health problems around the world. Reliable biomarkers for NSCLC are still needed in clinical practice. We aimed to develop a novel ferroptosis- and immune-based index for NSCLC. Methods: The training and testing datasets were obtained from TCGA and GEO databases, respectively. Immune- and ferroptosis-related genes were identified and used to establish a prognostic model. Then, the prognostic and therapeutic potential of the established index was evaluated. Results: Intimate interaction of immune genes with ferroptosis genes was observed. A total of 32 prognosis-related signatures were selected to develop a predictive model for NSCLC using LASSO Cox regression. Patients were classified into the high- and low-risk group based on the risk score. Patients in the low-risk group have better OS in contrast with that in the high-risk group in independent verification datasets. Besides, patients with a high risk score have shorter OS in all subgroups (T, N, and M0 subgroups) and pathological stages (stage I, II, and III). The risk score was positively associated with Immune Score, Stromal Score, and Ferroptosis Score in TCGA and GEO cohorts. A differential immune cell infiltration between the high-risk and the low-risk groups was also observed. Finally, we explored the significance of our model in tumor-related pathways, and different enrichment levels in the therapeutic pathway were observed between the high- and low-risk groups. Conclusion: The present study developed an immune and ferroptosis-combined index for the prognosis of NSCLC.

A System Bioinformatics Approach Predicts the Molecular Mechanism Underlying the Course of Action of Radix Salviae Reverses GBM Effects

Objective

This study used in vitro techniques to investigate the therapeutic effect of Radix Salviae on human glioblastoma and decode its underlying molecular mechanism.

Methods

The active components and targets of the Radix Salviae were identified from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). The targets of human glioblastoma were obtained from the GeneCards Database. The Radix Salviae-mediated antiglioblastoma was evaluated by Gene Ontology (GO) analyses and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Finally, mechanism of action of Radix Salviae against human glioblastoma was deduced by molecular docking and experiments.

Results

We screened 66 active ingredients and 45 targets of the Radix Salviae. The enrichment analysis based on the targets mentioned above suggested a possible role in protein phosphorylation, cell transcription, apoptosis, and inflammatory factor signaling pathways. Further study demonstrated that cryptotanshinone, an essential component of Radix Salviae, played a significant role in killing human glioblastoma cells and protecting the body by inhibiting the AKT, IKB, and STAT3 signaling pathways.

Conclusions

Radix Salviae could inhibit the proliferation and invasion of human glioblastoma by regulating STAT3, Akt, and IKB signaling pathways. Radix Salviae has potential therapeutic value in the future for human glioblastoma.

Transitioning pre-clinical glioblastoma models to clinical settings with biomarkers identified in 3D cell-based models: A systematic scoping review

Glioblastoma (GBM) remains incurable despite the overwhelming discovery of 2-dimensional (2D) cell-based potential therapeutics since the majority of them have met unsatisfactory results in animal and clinical settings. Incremental empirical evidence has laid the widespread need of transitioning 2D to 3-dimensional (3D) cultures that better mimic GBM's complex and heterogenic nature to allow better translation of pre-clinical results. This systematic scoping review analyses the transcriptomic data involving 3D models of GBM against 2D models from 22 studies identified from four databases (PubMed, ScienceDirect, Medline, and Embase). From a total of 499 genes reported in these studies, 313 (63%) genes were upregulated across 3D models cultured using different scaffolds. Our analysis showed that 4 of the replicable upregulated genes are associated with GBM stemness, epithelial to mesenchymal transition (EMT), hypoxia, and migration-related genes regardless of the type of scaffolds, displaying close resemblances to primitive undifferentiated tumour phenotypes that are associated with decreased overall survival and increased hazard ratio in GBM patients. The upregulation of drug response and drug efflux genes (e.g. cytochrome P450s and ABC transporters) mirrors the GBM genetic landscape that contributes to in vivo and clinical treatment resistance. These upregulated genes displayed strong protein-protein interactions when analysed using an online bioinformatics software (STRING). These findings reinforce the need for widespread transition to 3D GBM models as a relatively inexpensive humanised pre-clinical tool with suitable genetic biomarkers to bridge clinical gaps in potential therapeutic evaluations.

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.

The screening of immune-related biomarkers for prognosis of lung adenocarcinoma

Lung adenocarcinoma (LUAD) accounts for a frequently seen non-small cell lung cancer (NSCLC) histological subtype, and it is associated with dismal prognostic outcome. However, the benefits of traditional treatment are still limited, and the efficacies of immunotherapy are quite different. Therefore, it is of great significance to identify novel immune-related therapeutic targets in lung adenocarcinoma. In this study, we identified a set of immune-related biomarkers for prognosis of lung adenocarcinoma, which could provide new ideas for immunotherapy of lung adenocarcinoma. Datasets related to LUAD were filtered from the GEO database. The appropriate packages were used to identify differentially expressed genes (DEGs) and to carry out enrichment analysis, followed by the construction of prognostic biomarkers. The Kaplan-Meier (K-M) curves were plotted to analyze patient survival based on hub genes. Associations between the expression of selected biomarkers and six types of tumor-infiltrating immune cells were evaluated based on the online tool TIMER. After analyzing five GEO datasets(GSE32867, GSE46539, GSE63459, GSE75037 and GSE116959), we discovered altogether 67 DEGs, among which, 15 showed up-regulation while 52 showed down-regulation. Enrichments of integrated DEGs were identified in the ontology categories. CAV1, CFD, FMO2 and CLEC3B were eventually selected as independent prognostic biomarkers, they were correlated with clinical outcomes of LUAD patients. Moreover, a positive correlation was observed between biomarker expression and all different types of immune infiltration, and the expression level of the four biomarkers was all positively related to macrophage.

Profiles of immune cell infiltration and immune-related genes in the tumor microenvironment of osteosarcoma

This work aimed to investigate tumor-infiltrating immune cells (TIICs) and immune-associated genes in the tumor microenvironment of osteosarcoma. An algorithm known as ESTIMATE was applied for immune score assessment, and osteosarcoma cases were assigned to the high and low immune score groups. Immune-associated genes between these groups were compared, and an optimal immune-related risk model was built by Cox regression analyses. The deconvolution algorithm (referred to as CIBERSORT) was applied to assess 22 TIICs for their amounts in the osteosarcoma microenvironment. Osteosarcoma cases with high immune score had significantly improved outcome (P<0.01). The proportions of naive B cells and M0 macrophages were significantly lower in high immune score tissues compared with the low immune score group (P<0.05), while the amounts of M1 macrophages, M2 macrophages, and resting dendritic cells were significantly higher (P<0.05). Important immune-associated genes were determined to generate a prognostic model by Cox regression analysis. Interestingly, cases with high risk score had poor outcome (P<0.01). The areas under the curve (AUC) for the risk model in predicting 1, 3 and 5-year survival were 0.634, 0.781, and 0.809, respectively. Gene set enrichment analysis suggested immunosuppression in high-risk osteosarcoma patients, in association with poor outcome.

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 rs3856806 C>T Polymorphism Increased the Risk of Colorectal Cancer: A Case-Control Study in Eastern Chinese Han Population

Purpose: Functional variants in the peroxisome proliferator-activated receptor gamma (PPARG) and PPARG co-activator 1 (PPARGC1) family (e.g., PPARGC1A and PPARGC1B) genes were predicted to confer susceptibility to colorectal cancer (CRC). The aim of the present study was to explore the relationship between PPARG, PPARGC1A, PPARGC1B polymorphism and the risk of CRC.

Patients and methods: We conducted a case-control study with 1,003 CRC cases and 1,303 controls. We selected the PPARG rs3856806 C>T, PPARGC1A rs2970847 C>T, rs8192678 C>T, rs3736265 G>A and PPARGC1B rs7732671 G>C and rs17572019 G>A SNPs to assess the relationship between PPARG, PPARGC1A, PPARGC1B their variants and risk of CRC.

Results: We found that the PPARG rs3856806 C>T polymorphism increased the risk of CRC (TT vs. CC: adjusted OR, 1.59, 95% CI 1.08–2.35, P = 0.020; TT/CT vs. CC: adjusted OR, 1.26; 95% CI 1.06–1.49; P = 0.009 and TT vs. CC/CT: adjusted OR, 1.54; 95% CI 1.05–2.26; P = 0.028), even after a Bonferroni correction test. The stratified analysis revealed that the PPARG rs3856806 C>T polymorphism also increased the risk of CRC, especially in male, ≥61 years old, never smoking, never drinking, BMI ≥ 24 kg/m², colon cancer and rectum cancer subgroups.

Conclusion: Our findings highlight that the PPARG rs3856806 C>T polymorphism may increase the risk of CRC. In the future larger sample size case-control studies with a detailed functional assessment are needed to further determine the relationship of the PPARG rs3856806 C>T polymorphism with CRC risk.