PPARG Negatively Modulates Six2 in Tumor Formation of Clear Cell Renal Cell Carcinoma

The Role of Perirenal Adipose Tissue in Carcinogenesis-From Molecular Mechanism to Therapeutic Perspectives

Perirenal adipose tissue (PRAT) exhibits particular morphological features, with its activity being mainly related to thermogenesis. However, an expanded PRAT area seems to play a significant role in cardiovascular diseases, diabetes mellitus, and chronic kidney disease pathogenesis. Numerous studies have demonstrated that PRAT may support cancer progression and invasion, mainly in obese patients. The mechanism underlying these processes is of dysregulation of PRAT's secretion of adipokines and pro-inflammatory cytokines, such as leptin, adiponectin, chemerin, apelin, omentin-1, vistatin, nesfatin-1, and other pro-inflammatory cytokines, modulated by tumor cells. Cancer cells may also induce a metabolic reprogramming of perirenal adipocytes, leading to increased lipids and lactate transfer to the tumor microenvironment, contributing to cancer growth in a hypoxic milieu. In addition, the PRAT browning process has been specifically detected in renal cell carcinoma (RCC), being characterized by upregulated expression of brown/beige adipocytes markers (UCP1, PPAR-ɣ, c/EBPα, and PGC1α) and downregulated white fat cells markers, such as LEPTIN, SHOX2, HOXC8, and HOXC9. Considering its multifaceted role in cancer, modulation of PRAT's role in tumor progression may open new directions for oncologic therapy improvement. Considering the increasing evidence of the relationship between PRAT and tumor cells, our review aims to provide a comprehensive analysis of the perirenal adipocytes' impact on tumor progression and metastasis.

Peroxisome proliferator-activated receptors: Key regulators of tumor progression and growth

One of the main causes of death on the globe is cancer. Peroxisome-proliferator-activated receptors (PPARs) are nuclear hormone receptors, including PPARα, PPARδ and PPARγ, which are important in regulating cancer cell proliferation, survival, apoptosis, and tumor growth. Activation of PPARs by endogenous or synthetic compounds regulates tumor progression in various tissues. Although each PPAR isotype suppresses or promotes tumor development depending on the specific tissues or ligands, the mechanism is still unclear. PPARs are receiving interest as possible therapeutic targets for a number of disorders. Numerous clinical studies are being conducted on PPARs as possible therapeutic targets for cancer. Therefore, this review will focus on the existing and future uses of PPARs agonists and antagonists in treating malignancies. PubMed, Science Direct, and Scopus databases were searched regarding the effect of PPARs on various types of cancers until the end of May 2023. The results of the review articles showed the therapeutic influence of PPARs on a wide range of cancer on in vitro, in vivo and clinical studies. However, further experimental and clinical studies are needed to be conducted on the influence of PPARs on various cancers.

CPT2-mediated fatty acid oxidation inhibits tumorigenesis and enhances sorafenib sensitivity via the ROS/PPARγ/NF-κB pathway in clear cell renal cell carcinoma

Kidney cancer is a common kind of tumor with approximately 400,000 new diagnoses each year. Clear cell renal cell carcinoma (ccRCC) accounts for 70-80% of all renal cell carcinomas. Lipid metabolism disorder is a hallmark of ccRCC. With a better knowledge of the importance of fatty acid oxidation (FAO) in cancer, carnitine palmitoyltransferase 2 (CPT2) has gained prominence as a major mediator in the cancer metabolic pathway. However, the biological functions and mechanism of CPT2 in the progression of ccRCC are still unclear. Herein, we performed assays in vitro and in vivo to explore CPT2 functions in ccRCC. Moreover, we discovered that CPT2 induced FAO, which inhibited the generation of reactive oxygen species (ROS) by increasing nicotinamide adenine dinucleotide phosphate (NADPH) production. Additionally, we demonstrated that CPT2 suppresses tumor proliferation, invasion, and migration by inhibiting the ROS/ PPARγ /NF-κB pathway. Gene set enrichment analysis (GSEA) and drug sensitivity analysis showed that high expression of CPT2 in ccRCC was associated with higher sorafenib sensitivity, which was also validated in vitro and in vivo. In summary, our results suggest that CPT2 acts as a tumor suppressor in the development of ccRCC through the ROS/PPARγ/NF-κB pathway. Moreover, CPT2 is a potential therapeutic target for increasing sorafenib sensitivity in ccRCC.

Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma

Background

Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC.

Methods

A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data.

Results

The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB + low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC.

Conclusion

These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy.

Integrated Analysis of the Expression Characteristics, Prognostic Value, and Immune Characteristics of PPARG in Breast Cancer

Background: Breast cancer (BRCA) is the most frequent malignancy. Identification of potential biomarkers could help to better understand and combat the disease at early stages. Methods: We selected the overlapping genes of differential expressed genes and genes in BRCA-highly correlated modules by Weighted Gene Co-Expression Network Analysis (WGCNA) in TCGA and GEO data and performed KEGG and GO enrichment. PPARG was achieved from Protein-Protein Interaction (PPI) network analysis and prognostic analysis. TIMER, UALCAN, GEO, TCGA, and western blot analysis were used to validate the expression of PPARG in BRCA. PPARG was further analyzed by DNA methylation, immune parameters, and tumor mutation burden. Results: Among 381 overlapping genes, the lipid metabolic process was identified as highly enriched pathways in BRCA by TCGA and GEO data. When the prognostic analysis of 10 core genes by PPI network was performed, results revealed that high expression of PPARG was significantly correlated to a better prognosis. PPARG was lesser expression in BRCA according to TIMER, UALCAN, GEO, TCGA, and western blot in both mRNA level and protein level. PPARG had several high DNA methylation level sites and the methylation level is negatively correlated to expression. PPARG is also correlated to TNM stages, tumor microenvironment, and tumor burden. Conclusions: Findings of our study identified the PPARG as a potential biomarker by confirming its low expression in BRCA and its correlation to prognosis. Moreover, its correlation to DNA methylation and tumor microenvironment may guide new therapeutic strategies for BRCA patients.

Study of the Active Components and Molecular Mechanism of Tripterygium wilfordii in the Treatment of Diabetic Nephropathy

We aimed to explore the active ingredients and molecular mechanism of Tripterygium wilfordii (TW) in the treatment of diabetic nephropathy (DN) through network pharmacology and molecular biology. First, the active ingredients and potential targets of TW were obtained through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and related literature materials, and Cytoscape 3.7.2 software was used to construct the active ingredient-target network diagram of TW. Second, the target set of DN was obtained through the disease database, and the potential targets of TW in the treatment of DN were screened through a Venn diagram. A protein interaction network diagram (PPI) was constructed with the help of the String platform and Cytoscape 3.7.2. Third, the ClueGO plug-in tool was used to enrich the GO biological process and the KEGG metabolic pathway. Finally, molecular docking experiments and cell pathway analyses were performed. As a result, a total of 52 active ingredients of TW were screened, and 141 predicted targets and 49 target genes related to DN were identified. The biological process of GO is mediated mainly through the regulation of oxygen metabolism, endothelial cell proliferation, acute inflammation, apoptotic signal transduction pathway, fibroblast proliferation, positive regulation of cyclase activity, adipocyte differentiation and other biological processes. KEGG enrichment analysis showed that the main pathways involved were AGE-RAGE, vascular endothelial growth factor, HIF-1, IL-17, relaxin signalling pathway, TNF, Fc epsilon RI, insulin resistance and other signaling pathways. It can be concluded that TW may treat DN by reducing inflammation, reducing antioxidative stress, regulating immunity, improving vascular disease, reducing insulin resistance, delaying renal fibrosis, repairing podocytes, and reducing cell apoptosis, among others, with multicomponent, multitarget and multisystem characteristics.

53 years old is a reasonable cut-off value to define young and old patients in clear cell renal cell carcinoma: a study based on TCGA and SEER database

Background

The objectives of this study were to screen out cut-off age value and age-related differentially expressed genes (DEGs) in clear cell renal cell carcinoma (CCRCC) from Surveillance Epidemiology and End Results (SEER) database and The Cancer Genome Atlas (TCGA) database.

Methods

We selected 45,974 CCRCC patients from SEER and 530 RNA-seq data from TCGA database. The age cut-off value was defined using the X-tile program. Propensity score matching (PSM) was used to balance the differences between young and old groups. Hazard ratio (HR) was applied to evaluate prognostic risk of age in different subgroups. Age-related DEGs were identified via RNA-seq data. Survival analysis was used to assess the relationship between DEGs and prognosis.

Results

In this study, we divided the patients into young (n = 14,276) and old (n = 31,698) subgroups according to cut-off value (age = 53). Age > 53 years was indicated as independent risk factor for overall survival (OS) and cancer specific survival (CSS) of CCRCC before and after PSM. The prognosis of old group was worse than that in young group. Eleven gene were differential expression between the younger and older groups in CCRCC. The expression levels of PLA2G2A and SIX2 were related to prognosis of the elderly.

Conclusion

Fifty-three years old was cut-off value in CCRCC. The prognosis of the elderly was worse than young people. It remind clinicians that more attention and better treatment should be given to CCRCC patients who are over 53 years old. PLA2G2A and SIX2 were age-related differential genes which might play an important role in the poor prognosis of elderly CCRCC patients.

A New Prognostic Risk Model Based on PPAR Pathway-Related Genes in Kidney Renal Clear Cell Carcinoma

OBJECTIVE

This study is aimed at using genes related to the peroxisome proliferator-activated receptor (PPAR) pathway to establish a prognostic risk model in kidney renal clear cell carcinoma (KIRC).

METHODS

For this study, we first found the PPAR pathway-related genes on the gene set enrichment analysis (GSEA) website and found the KIRC mRNA expression data and clinical data through TCGA database. Subsequently, we used R language and multiple R language expansion packages to analyze the expression, hazard ratio analysis, and coexpression analysis of PPAR pathway-related genes in KIRC. Afterward, using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website, we established the protein-protein interaction (PPI) network of genes related to the PPAR pathway. After that, we used LASSO regression curve analysis to establish a prognostic survival model in KIRC. Finally, based on the model, we conducted correlation analysis of the clinicopathological characteristics, univariate analysis, and multivariate analysis.

RESULTS

We found that most of the genes related to the PPAR pathway had different degrees of expression differences in KIRC. Among them, the high expression of 27 genes is related to low survival rate of KIRC patients, and the high expression of 13 other genes is related to their high survival rate. Most importantly, we used 13 of these genes successfully to establish a risk model that could accurately predict patients' prognosis. There is a clear correlation between this model and metastasis, tumor, stage, grade, and fustat.

CONCLUSIONS

To the best of our knowledge, this is the first study to analyze the entire PPAR pathway in KIRC in detail and successfully establish a risk model for patient prognosis. We believe that our research can provide valuable data for future researchers and clinicians.

A New Prognostic Risk Model Based on PPAR Pathway-Related Genes in Kidney Renal Clear Cell Carcinoma

Objective

This study is aimed at using genes related to the peroxisome proliferator-activated receptor (PPAR) pathway to establish a prognostic risk model in kidney renal clear cell carcinoma (KIRC).

Methods

For this study, we first found the PPAR pathway-related genes on the gene set enrichment analysis (GSEA) website and found the KIRC mRNA expression data and clinical data through TCGA database. Subsequently, we used R language and multiple R language expansion packages to analyze the expression, hazard ratio analysis, and coexpression analysis of PPAR pathway-related genes in KIRC. Afterward, using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website, we established the protein-protein interaction (PPI) network of genes related to the PPAR pathway. After that, we used LASSO regression curve analysis to establish a prognostic survival model in KIRC. Finally, based on the model, we conducted correlation analysis of the clinicopathological characteristics, univariate analysis, and multivariate analysis.

Results

We found that most of the genes related to the PPAR pathway had different degrees of expression differences in KIRC. Among them, the high expression of 27 genes is related to low survival rate of KIRC patients, and the high expression of 13 other genes is related to their high survival rate. Most importantly, we used 13 of these genes successfully to establish a risk model that could accurately predict patients' prognosis. There is a clear correlation between this model and metastasis, tumor, stage, grade, and fustat.

Conclusions

To the best of our knowledge, this is the first study to analyze the entire PPAR pathway in KIRC in detail and successfully establish a risk model for patient prognosis. We believe that our research can provide valuable data for future researchers and clinicians.

Quantitative assessment of the association of polymorphisms in the metallothionein 2A gene with cancer risk

Objective

The aim of the study was to quantitatively assess the association of metallothionein 2A (MT2A) polymorphisms rs28366003 and rs1610216 with cancer risk.

Methods

Crude odd ratios (OR) with 95% confidence intervals (CI) were used to estimate associations of the polymorphisms with cancer risk.

Results

Six eligible case-control studies with 1899 cases and 2437 controls focused on rs28366003, and three of those six studies, with 548 cases and 926 controls, additionally focused on rs1610216. Pooled analysis showed that MT2A rs28366003 and rs1610216 were associated with cancer risk: (AG + GG) vs. AA, OR = 2.67; GG vs. (AG + AA), OR = 5.97; GG vs. AA, OR = 6.80; AG vs. AA, OR = 2.46; G vs. A, OR = 2.67 for rs28366003; and CC vs. (TC+TT), OR = 2.51; CC vs. TT, OR = 2.42 for rs1610216. Subgroup analysis based on ethnicity showed a significant association of rs28366003 with cancer risk in Asian and Caucasian populations. However, a significant association of rs1610216 with cancer risk was found only in the Asian population.

Conclusion

MT2A rs28366003 and rs1610216 polymorphisms were associated with cancer risk and might serve as genetic biomarkers for predicting cancer risk. However, larger studies are needed to confirm these findings.

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.

HOXC11 functions as a novel oncogene in human colon adenocarcinoma and kidney renal clear cell carcinoma

AIMS

Accumulating evidence has confirmed the involvement of the homeobox (HOX) gene family in carcinogenesis. HOXC11, belongs to the homeobox-C (HOXC) gene cluster, has been reported to play important roles in the development of several cancers. However, its expression and clinical value in pan-cancer remain elusive.

MATERIALS AND METHODS

Bioinformatics analysis, CCK-8 assay, Flow cytometry and Western blot were used to analyze gene expression and patient survival, cell proliferation, cell apoptosis and protein level, respectively.

KEY FINDINGS

In this study, we comprehensively analyzed the expression profile and prognostic value of HOXC11 in human pan-cancer using online The Cancer Genome Atlas (TCGA) databases. HOXC11 was widely up-regulated in tumor tissues when compared with the normal tissues in pan-cancer across nine cancer types. In addition, high mRNA level of HOXC11 predicted poor overall survival (OS) of patients with adrenocortical carcinoma (ACC), colon adenocarcinoma (COAD), kidney renal clear cell carcinoma (KIRC), mesothelioma (MESO) and pancreatic adenocarcinoma (PAAD), respectively. By comparative analysis, we found that HOXC11 was up-regulated and closely correlated patient OS in COAD and KIRC. Functionally, down-regulation of HOXC11 inhibited cell proliferation but promoted apoptosis of COAD and KIRC in vitro. Mechanistically, HOXC11 promoted cell proliferation of COAD and KIRC might by inactivating the peroxisome proliferator-activated receptor gamma (PPARγ) signaling pathway.

SIGNIFICANCE

Our findings suggest that HOXC11 may act as a tumor driving gene in COAD and KIRC.

Pharmacological Treatment of Chemotherapy-Induced Neuropathic Pain: PPARγ Agonists as a Promising Tool

Chemotherapy-induced neuropathic pain (CINP) is one of the most severe side effects of anticancer agents, such as platinum- and taxanes-derived drugs (oxaliplatin, cisplatin, carboplatin and paclitaxel). CINP may even be a factor of interruption of treatment and consequently increasing the risk of death. Besides that, it is important to take into consideration that the incidence of cancer is increasing worldwide, including colorectal, gastric, lung, cervical, ovary and breast cancers, all treated with the aforementioned drugs, justifying the concern of the medical community about the patient’s quality of life. Several physiopathological mechanisms have already been described for CINP, such as changes in axonal transport, mitochondrial damage, increased ion channel activity and inflammation in the central nervous system (CNS). Another less frequent event that may occur after chemotherapy, particularly under oxaliplatin treatment, is the central neurotoxicity leading to disorders such as mental confusion, catatonia, hyporeflexia, etc. To date, no pharmacological therapy has shown satisfactory effect in these cases. In this scenario, duloxetine is the only drug currently in clinical use. Peroxisome proliferator-activated receptors (PPARs) belong to the class of nuclear receptors and are present in several tissues, mainly participating in lipid and glucose metabolism and inflammatory response. There are three PPAR isoforms: α, β/δ and γ. PPARγ, the protagonist of this review, is expressed in adipose tissue, large intestine, spleen and neutrophils. This subtype also plays important role in energy balance, lipid biosynthesis and adipogenesis. The effects of PPARγ agonists, known for their positive activity on type II diabetes mellitus, have been explored and present promising effects in the control of neuropathic pain, including CINP, and also cancer. This review focuses largely on the mechanisms involved in chemotherapy-induced neuropathy and the effects of the activation of PPARγ to treat CINP. It is the aim of this review to help understanding and developing novel CINP therapeutic strategies integrating PPARγ signalling.

Differential Expression Profiles of the Transcriptome and miRNA Interactome in Synovial Fibroblasts of Rheumatoid Arthritis Revealed by Next Generation Sequencing

Using next-generation sequencing to decipher the molecular mechanisms underlying aberrant rheumatoid arthritis synovial fibroblasts (RASF) activation, we performed transcriptome-wide RNA-seq and small RNA-seq on synovial fibroblasts from rheumatoid arthritis (RA) subject and normal donor. Differential expression of mRNA and miRNA was integrated with interaction analysis, functional annotation, regulatory network mapping and experimentally verified miRNA–target interaction data, further validated with microarray expression profiles. In this study, 3049 upregulated mRNA and 3552 downregulated mRNA, together with 50 upregulated miRNA and 35 downregulated miRNA in RASF were identified. Interaction analysis highlighted contribution of miRNA to altered transcriptome. Functional annotation revealed metabolic deregulation and oncogenic signatures of RASF. Regulatory network mapping identified downregulated FOXO1 as master transcription factor resulting in altered transcriptome of RASF. Differential expression in three miRNA and corresponding targets (hsa-miR-31-5p:WASF3, hsa-miR-132-3p:RB1, hsa-miR-29c-3p:COL1A1) were also validated. The interactions of these three miRNA–target genes were experimentally validated with past literature. Our transcriptomic and miRNA interactomic investigation identified gene signatures associated with RASF and revealed the involvement of transcription factors and miRNA in an altered transcriptome. These findings help facilitate our understanding of RA with the hope of serving as a springboard for further discoveries relating to the disease.