The Role of Peroxisome Proliferator-Activated Receptors (PPARs) in Pan-Cancer

RNA-Seq explores the functional role of the fibroblast growth factor 10 gene in bovine adipocytes differentiation

OBJECTIVE

The present study was executed to explore the molecular mechanism of fibroblast growth factor 10 (FGF10) gene in bovine adipogenesis.

METHODS

The bovine FGF10 gene was overexpressed through Ad-FGF10 or inhibited through siFGF10 and their negative control (NC) in bovine adipocytes, and the multiplicity of infection, transfection efficiency, interference efficiency were evaluated through quantitative real-time polymerase chain reaction, western blotting and fluorescence microscopy. The lipid droplets, triglycerides (TG) content and the expression levels of adipogenic marker genes were measured during preadipocytes differentiation. The differentially expressed genes were explored through deep RNA sequencing.

RESULTS

The highest mRNA level was found in omasum, subcutaneous fat, and intramuscular fat. Moreover, the highest mRNA level was found in adipocytes at day 4 of differentiation. The results of red-oil o staining showed that overexpression (Ad-FGF10) of the FGF10 gene significantly (p<0.05) reduced the lipid droplets and TG content, and their downregulation (siFGF10) increased the measurement of lipid droplets and TG in differentiated bovine adipocytes. Furthermore, the overexpression of the FGF10 gene down regulated the mRNA levels of adipogenic marker genes such as CCAAT enhancer binding protein alpha (C/EBPα), fatty acid binding protein (FABP4), peroxisome proliferator-activated receptor-γ (PPARγ), lipoprotein lipase (LPL), and Fas cell surface death receptor (FAS), similarly, down-regulation of the FGF10 gene enriched the mRNA levels of C/EBPα, PPARγ, FABP4, and LPL genes (p<0.01). Additionally, the protein levels of PPARγ and FABP4 were reduced (p<0.05) in adipocytes infected with Ad-FGF10 gene and enriched in adipocytes transfected with siFGF10. Moreover, a total of 1,774 differentially expressed genes (DEGs) including 157 up regulated and 1,617 down regulated genes were explored in adipocytes infected with Ad-FGF10 or Ad-NC through deep RNA-sequencing. The top Kyoto encyclopedia of genes and genomes pathways regulated through DEGs were the PPAR signaling pathway, cell cycle, base excision repair, DNA replication, apoptosis, and regulation of lipolysis in adipocytes.

CONCLUSION

Therefore, we can conclude that the FGF10 gene is a negative regulator of bovine adipogenesis and could be used as a candidate gene in marker-assisted selection.

Comprehensive analysis of peroxisome proliferator-activated receptors to predict the drug resistance, immune microenvironment, and prognosis in stomach adenocarcinomas

Background

Peroxisome proliferator-activated receptors (PPARs) exert multiple functions in the initiation and progression of stomach adenocarcinomas (STAD). This study analyzed the relationship between PPARs and the immune status, molecular mutations, and drug therapy in STAD.

Methods

The expression profiles of three PPAR genes (PPARA, PPARD and PPARG) were downloaded from The Cancer Genome Atlas (TCGA) dataset to analyze their expression patterns across pan-cancer. The associations between PPARs and clinicopathologic features, prognosis, tumor microenvironment, genome mutation and drug sensitivity were also explored. Co-expression between two PPAR genes was calculated using Pearson analysis. Regulatory pathways of PPARs were scored using gene set variation analysis (GSVA) package. Quantitative real-time polymerase chain reaction (qRT-PCR), Western blot, Cell Counting Kit-8 (CCK-8) assay and transwell assay were conducted to analyze the expression and function of the PPAR genes in STAD cell lines (AGS and SGC7901 cells).

Results

PPARA, PPARD and PPARG were more abnormally expressed in STAD samples and cell lines when compared to most of 32 type cancers in TCGA. In STAD, the expression of PPARD was higher in Grade 3+4 and male patients, while that of PPARG was higher in patient with Grade 3+4 and age > 60. Patients in high-PPARA expression group tended to have longer survival time. Co-expression analysis revealed 6 genes significantly correlated with the three PPAR genes in STAD. Single-sample GSEA (ssGSEA) showed that the three PPAR genes were enriched in 23 pathways, including MITOTIC_SPINDLE, MYC_TARGETS_V1, E2F_TARGETS and were closely correlated with immune cells, including NK_cells_resting, T_cells_CD4_memory_resting, and macrophages_M0. Immune checkpoint genes (CD274, SIGLEC15) were abnormally expressed between high-PPAR expression and low-PPAR expression groups. TTN, MUC16, FAT2 and ANK3 genes had a high mutation frequency in both high-PPARA/PPARG and low-PPARA/PPARG expression group. Fourteen and two PPARA/PPARD drugs were identified to be able to effectively treat patients in high-PPARA/PPARG and low-PPARA/PPARG expression groups, respectively. We also found that the chemotherapy drug Vinorelbine was positively correlated with the three PPAR genes, showing the potential of Vinorelbine to serve as a treatment drug for STAD. Furthermore, cell experiments demonstrated that PPARG had higher expression in AGS and SGC7901 cells, and that inhibiting PPARG suppressed the viability, migration and invasion of AGS and SGC7901 cells.

Conclusions

The current results confirmed that the three PPAR genes (PPARA, PPARD and PPARG) affected STAD development through mediating immune microenvironment and genome mutation.

Roles of PPAR activation in cancer therapeutic resistance: Implications for combination therapy and drug development

Therapeutic resistance is a major obstacle to successful treatment or effective containment of cancer. Peroxisome proliferator-activated receptors (PPARs) play an essential role in regulating energy homeostasis and determining cell fate. Despite of the pleiotropic roles of PPARs in cancer, numerous studies have suggested their intricate relationship with therapeutic resistance in cancer. In this review, we provided an overview of the roles of excessively activated PPARs in promoting resistance to modern anti-cancer treatments, including chemotherapy, radiotherapy, targeted therapy, and immunotherapy. The mechanisms through which activated PPARs contribute to therapeutic resistance in most cases include metabolic reprogramming, anti-oxidant defense, anti-apoptosis signaling, proliferation-promoting pathways, and induction of an immunosuppressive tumor microenvironment. In addition, we discussed the mechanisms through which activated PPARs lead to multidrug resistance in cancer, including drug efflux, epithelial-to-mesenchymal transition, and acquisition and maintenance of the cancer stem cell phenotype. Preliminary studies investigating the effect of combination therapies with PPAR antagonists have suggested the potential of these antagonists in reversing resistance and facilitating sustained cancer management. These findings will provide a valuable reference for further research on and clinical translation of PPAR-targeting treatment strategies.

miR136 regulates proliferation and differentiation of small tail han sheep preadipocytes

Low meat performance is the defect of Small Tail Han sheep. Intramuscular fat affects meat quality and largely determined by adipogenesis. In previous study, miR136 was showed one of differentially expressed microRNAs between preadipocytes and mature adipocytes of Small Tail Han sheep but its role in adipogenesis is still not elucidated. Here, we investigated the effect of miR136 on adipogenesis and the underlying mechanism. qPCR data showed that miR136 level increased with preadipocytes proliferation while declined with preadipocytes differentiation. Moreover, miR136 mimics blocked lipid droplet formation, reduced lipid content and triglyceride accumulation while miR136 inhibitor showed the opposite effects, revealing that miR136 promoted preadipocytes proliferation but inhibited preadipocytes differentiation. Bioinformatics and biochemical validation manifested that PPARGC1B was a target of miR136. Furthermore, miR136 mimics decreased PPARγ and C/EBPα expression accompanied by PPARGC1B expression descending. Reverse effects were observed with miR136 inhibitor. Besides, overexpression of miR136 elevated IGF1 expression. Collectively, our data first exhibited a regulatory role of miR136 in adipogenesis, which is promoting preadipocytes proliferation through elevating IGF1 expression while inhibiting preadipocytes differentiation through targeting PPARGC1B and further declined PPARγ and C/EBPα expression. The modulation of PPARGC1B by miR136 may provide a new potential target for increasing intramuscular fat.

Quercetin Alleviates Inflammation and Energy Deficiency Induced by Lipopolysaccharide in Chicken Embryos

Energy deficiency causes multiple organ dysfunctions after LPS induction. Quercetin is a phenolic compound found in herbal medicines. However, the effects of quercetin in alleviating LPS-induced energy deficiency remain unclear. In the present study, an in vivo LPS-induced inflammation model was established in chicken embryos. Specific pathogen-free chicken embryos (n = 120) were allocated to control, PBS with or without ethanol, quercetin (10, 20, or 40 nmol, respectively), and LPS (125 ng/egg) with or without quercetin groups. Fifteen day old embryonated eggs were injected with the abovementioned solutions via the allantoic cavity. On embryonic day 19, the tissues of the embryos were collected for histopathological examination using frozen oil red O staining, RNA extraction, real-time quantitative polymerase chain reaction, and immunohistochemical investigations. The glycogen and lipid contents in the liver increased after LPS stimulation as compared with the PBS group, whereas quercetin decreased the accumulation as compared with the LPS group. The mRNA expressions of AMPKα1 and AMPKα2 in the duodena, ceca, and livers were upregulated after LPS induction as compared with the PBS group, while quercetin could downregulate these expressions as compared with the LPS group. The immunopositivity of AMPKα2 in the villus, crypt, lamina propria, tunica muscularis, and myenteric plexus in the duodena and in the cytoplasms of hepatocytes significantly increased after LPS induction when compared with the PBS group (p < 0.01), whereas the immunopositivity to AMPKα2 in the quercetin treatment group significantly decreased when compared with the LPS group (p < 0.01 or p < 0.05). The LPS-induced high expressions of transcription factor PPARα and glucose transporter (SGLT1) were blocked by quercetin in the duodena, ceca, and livers. Quercetin treatment improved the LPS-induced decrease in APOA4 in the duodena, ceca, and livers. The mRNA expression of PEPT1 in the duodena and ceca increased after LPS challenge, whereas quercetin could downregulate PEPT1 gene expression. These data demonstrate that quercetin improved the energy deficiency induced by LPS in chicken embryos. The LPS-induced inflammation model was established to avoid the effect of LPS exposure from the environment and intestinal flora. The results form the basis the administration of quercetin pretreatment (in ovo infection) to improve the energy state of chicken embryos and improve the inflammation response.

RUNX2 recruits the NuRD(MTA1)/CRL4B complex to promote breast cancer progression and bone metastasis

Runt-related transcription factor 2 (RUNX2) is an osteogenesis-related transcription factor that has emerged as a prominent transcription repressing factor in carcinogenesis. However, the role of RUNX2 in breast cancer metastasis remains poorly understood. Here, we show that RUNX2 recruits the metastasis-associated 1 (MTA1)/NuRD and the Cullin 4B (CUL4B)-Ring E3 ligase (CRL4B) complex to form a transcriptional-repressive complex, which catalyzes the histone deacetylation and ubiquitylation. Genome-wide analysis of the RUNX2/NuRD(MTA1)/CRL4B complex targets identified a cohort of genes including peroxisome proliferator-activated receptor alpha (PPARα) and superoxide dismutase 2 (SOD2), which are critically involved in cell growth, epithelial-to-mesenchymal transition (EMT) and invasion. We demonstrate that the RUNX2/NuRD(MTA1)/CRL4B complex promotes the proliferation, invasion, tumorigenesis, bone metastasis, cancer stemness of breast cancer in vitro and in vivo. Strikingly, RUNX2 expression is upregulated in multiple human carcinomas, including breast cancer. Our study suggests that RUNX2 is a promising potential target for the future treatment strategies of breast cancer.

Comprehensive Bioinformatics Analysis of Toll-Like Receptors (TLRs) in Pan-Cancer

Background

To conduct a comprehensive bioinformatics analysis on the transcriptome signatures of Toll-like receptors (TLRs) in pan-cancer. Materials and methods. A total of 11,057 tissues consisting of 33 types of carcinoma in The Cancer Genome Atlas (TCGA) were retrieved, and then we further explored the correlation between TLRs' expression with tumorigenesis, immune infiltration, and drug sensitivity. We conducted a comprehensive bioinformatics analysis on TLR1 to 10 in pan-cancer, including differential expression analysis between normal and tumor tissues, differential immune subtype correlation, survival analysis, tumor immune infiltration estimating, stemness indices correlation, and drug responses correlation.

Results

TLR2 was highly expressed in most types of tumors. TLR9 was hardly expressed compared to other TLR genes, which lead to TLR9 showing less correlation with both immune-estimate scores and stromal-estimate scores. All the TLRs were related with immune subtype of tumor samples that all of them were differentially expressed in differential immune subtype samples. The expression of TLRs was positively related with immune-estimate scores and stromal-estimate scores in almost all types of tumor. The expression of TLRs was negatively correlated with mRNA expression-based stemness scores (RNAss) in nearly almost type of tumors except kidney renal clear cell carcinoma (KIRC) and also negatively correlated with DNA methylation-based stemness scores (DNAss) in many types of tumors except adrenocortical carcinoma (ACC), cholangiocarcinoma (CHOL), KIRC, acute myeloid leukemia (LAML), low-grade glioma (LGG), testicular germ cell tumors (TGCT), thyroid carcinoma (THCA), thymoma (THYM), and uveal melanoma (UVM). The expression of TLR9 was significantly positively correlated with the drug sensitivity of fluphenazine, alectinib, carmustine, and 7−hydroxystaurosporine. TLR7 was significantly positively correlated with the drug sensitivity of alectinib.

Conclusions

Our study reveals the significant role of TLRs family in pan-cancer and provides potential therapeutic strategies of cancer.

Identification of a Novel PPAR Signature for Predicting Prognosis, Immune Microenvironment, and Chemotherapy Response in Bladder Cancer

Background

Mounting evidence has confirmed that peroxisome proliferator-activated receptors (PPARs) played a crucial role in the development and progression of bladder cancer (BLCA). The purpose of this study is to comprehensively investigate the function and prognostic value of PPAR-targeted genes in BLCA.

Methods

The RNA sequencing data and clinical information of BLCA patients were acquired from The Cancer Genome Atlas (TCGA). The differentially expressed PPAR-targeted genes were investigated. Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis were performed for screening prognostic PPAR-targeted genes and constructing the prognostic PPAR signature and then validated by GSE13507 cohort and GSE32894 cohort. A nomogram was constructed to predict the outcomes of BLCA patients in combination with PPAR signature and clinical factors. Gene set enrichment analysis (GSEA) and immune cell infiltration were implemented to explore the molecular characteristics of the signature. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to predict the chemotherapy responses of the prognostic signature. The candidate small molecule drugs targeting PPAR-targeted genes were screened by the CMAP database.

Results

We constructed and validated the prognostic signature comprising of 4 PPAR-targeted genes (CPT1B, CALR, AHNAK, and FADS2), which was an independent prognostic biomarker in BLCA patients. A nomogram based on the signature and clinical factors was established in the TCGA set, and the calibration plots displayed the excellent predictive capacity. GSEA analysis indicated that PPAR signature was implicated in multiple oncogenic signaling pathways and correlated with tumor immune cell infiltration. Patients in the high-risk groups showed greater sensitivity to chemotherapy than those in the low-risk groups. Moreover, 11 candidate small molecule drugs were identified for the treatment of BLCA.

Conclusion

We constructed and validated a novel PPAR signature, which showed the excellent performance in predicting prognosis and chemotherapy sensitivity of BLCA patients.

PPARα: An emerging target of metabolic syndrome, neurodegenerative and cardiovascular diseases

Peroxisome proliferator-activated receptor α (PPARα) is a ligand-activated transcription factor that is involved in lipid metabolism of various tissues. Different metabolites of fatty acids and agonists like fibrates activate PPARα for its transactivative or repressive function. PPARα is known to affect diverse human diseases, and we focus on advanced studies of its transcriptional regulation in these diseases. In MAFLD, PPARα shows a protective function with its upregulation of lipid oxidation and mitochondrial biogenesis and transcriptional repression of inflammatory genes, which is similar in Alzheimer's disease and cardiovascular disease. Activation of PPARα also prevents the progress of diabetes complications; however, its role in diabetes and cancers remains uncertain. Some PPARα-specific agonists, such as Wy14643 and fenofibrate, have been applied in metabolic syndrome treatment, which might own potential in wider application. Future studies may further explore the functions and interventions of PPARα in cancer, diabetes, immunological diseases, and neurodegenerative disease.

Identification of enhancer RNAs for the prognosis of head and neck squamous cell carcinoma

BACKGROUND

Enhancer RNAs (eRNAs) play an important role in carcinogenesis. The landscape of eRNAs in head and neck squamous cell carcinoma (HNSCC) remains largely unknown.

METHODS

The eRNA expression matrix was obtained from the enhancer RNA in the cancer database. Functional enrichment analyses were performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG). Prognostic eRNAs were identified using Cox regression analysis, and a prognostic prediction model was constructed based on coefficients.

RESULTS

KEGG analysis showed that eRNA-related transcription factors were mainly enriched in herpes simplex virus 1 (HSV1) infection. The zinc finger (ZNF) family may play an essential role in HNSCC. ENSR00000188847, ENSR00000250663, ENSR00000313345, ENSR00000317887, and ENSR00000336429 were identified. The prediction model was robust.

CONCLUSIONS

We constructed a robust 5-eRNA prognostic prediction model, and these eRNAs are potential biomarkers for HNSCC prognosis.

Identification of candidate biomarkers correlated with poor prognosis of breast cancer based on bioinformatics analysis

Breast cancer (BC) is a malignancy with high incidence among women in the world. This study aims to screen key genes and potential prognostic biomarkers for BC using bioinformatics analysis. Total 58 normal tissues and 203 cancer tissues were collected from three Gene Expression Omnibus (GEO) gene expression profiles, and then the differential expressed genes (DEGs) were identified. Subsequently, the Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway were analyzed to investigate the biological function of DEGs. Additionally, hub genes were screened by constructing a protein–protein interaction (PPI) network. Then, we explored the prognostic value and molecular mechanism of these hub genes using Kaplan–Meier (KM) curve and Gene Set Enrichment Analysis (GSEA). As a result, 42 up-regulated and 82 down-regulated DEGs were screened out from GEO datasets. The DEGs were mainly related to cell cycles and cell proliferation by GO and KEGG pathway analysis. Furthermore, 12 hub genes (FN1, AURKA, CCNB1, BUB1B, PRC1, TPX2, NUSAP1, TOP2A, KIF20A, KIF2C, RRM2, ASPM) with a high degree were identified initially, among which, 11 hub genes were significantly correlated with the prognosis of BC patients based on the Kaplan–Meier-plotter. GSEA reviewed that these hub genes correlated with KEGG_CELL_CYCLE and HALLMARK_P53_PATHWAY. In conclusion, this study identified 11 key genes as BC potential prognosis biomarkers on the basis of integrated bioinformatics analysis. This finding will improve our knowledge of the BC progress and mechanisms.

miR-22-3p/PGC1β Suppresses Breast Cancer Cell Tumorigenesis via PPARγ

In this study, we found that miR-22-3p expression was decreased in breast cancer (BC) cell lines and tissues. Overexpression of miR-22-3p inhibited the proliferation and migration of BC cells in vitro and in vivo, while depletion of miR-22-3p exhibited the opposite effect. Importantly, miR-22-3p could directly target PGC1β and finally regulate the PPARγ pathway in BC. In conclusion, miR-22-3p/PGC1β suppresses BC cell tumorigenesis via PPARγ, which may become a potential biomarker and therapeutic target.

The gut microbiome-bile acid axis in hepatocarcinogenesis

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and is a leading cause of cancer-related deaths globally, with few effective therapeutic options. Bile acids (BAs) are synthesized from cholesterol in the liver and can be modulated by farnesoid X receptor (FXR) and G-protein coupled BA receptor 1 (GPBAR1/TGR5). Alterations in BAs can affect hepatic metabolic homeostasis and contribute to the pathogenesis of liver cancer. Increasing evidence points to the key role of bacterial microbiota in the promotion and development of liver cancer. They are also involved in the regulation of BA synthesis and metabolism. The purpose of this review is to integrate related articles involving gut microbiota, BAs and HCC, and review how the gut microbiota-BA signaling axis can possibly influence the development of HCC.