Lack of expression of the proteins GMPR2 and PPARα are associated with the basal phenotype and patient outcome in breast cancer

PPARα phosphorylation regulates colorectal tumor immune escape

A high level of PD-L1 in cancer cells promotes tumor immune escape and inhibits tumor immunotherapy. Although PD-L1 gene expression is upregulated by multiple pathways, its gene transcriptional repression is still unclear. Here we found that loss of PPARα, one of the peroxisome-proliferator-activated receptors (PPARs) family members, promoted colorectal tumor immune escape. Mechanistically, PPARα directly bound to the PD-L1 promoter resulting in its gene transcriptional repression, which in turn increased T cell activity, and PPARα agonist enhanced this event. However, ERK induced PPARα-S12 phosphorylation leading to blockade of PPARα-mediated PD-L1 transcriptional repression, and the combination of ERK inhibitor with PPARα agonist significantly inhibited tumor immune escape. These findings suggest that the ERK-PPARα pathway inhibited PD-L1 gene transcriptional repression and promoted colorectal tumor immune escape.

Circadian clock and lipid metabolism disorders: a potential therapeutic strategy for cancer

Recent research has emphasized the interaction between the circadian clock and lipid metabolism, particularly in relation to tumors. This review aims to explore how the circadian clock regulates lipid metabolism and its impact on carcinogenesis. Specifically, targeting key enzymes involved in fatty acid synthesis (SREBP, ACLY, ACC, FASN, and SCD) has been identified as a potential strategy for cancer therapy. By disrupting these enzymes, it may be possible to inhibit tumor growth by interfering with lipid metabolism. Transcription factors, like SREBP play a significant role in regulating fatty acid synthesis which is influenced by circadian clock genes such as BMAL1, REV-ERB and DEC. This suggests a strong connection between fatty acid synthesis and the circadian clock. Therefore, successful combination therapy should target fatty acid synthesis in addition to considering the timing and duration of drug use. Ultimately, personalized chronotherapy can enhance drug efficacy in cancer treatment and achieve treatment goals.

Cannabinoids Reduce Melanoma Cell Viability and Do Not Interfere with Commonly Used Targeted Therapy in Metastatic Melanoma In Vivo and In Vitro

Background: Cannabinoids are mainly used for recreational purposes, but also made their way into oncology, since these substances can be taken to increase appetite in tumour cachexia. Since there are some hints in the literature that cannabinoids might have some anti-cancerous effects, the aim of this study was to study if and how cannabinoids mediate pro-apoptotic effects in metastatic melanoma in vivo and in vitro and its value besides conventional targeted therapy in vivo. Methods: Several melanoma cell lines were treated with different concentrations of cannabinoids, and anti-cancerous efficacy was assessed by proliferation and apoptosis assays. Subsequent pathway analysis was performed using apoptosis, proliferation, flow cytometry and confocal microscopy data. The efficacy of cannabinoids in combination with trametinib was studied in NSG mice in vivo. Results: Cannabinoids reduced cell viability in multiple melanoma cell lines in a dose-dependent way. The effect was mediated by CB1, TRPV1 and PPARα receptors, whereby pharmacological blockade of all three receptors protected from cannabinoid-induced apoptosis. Cannabinoids initiated apoptosis by mitochondrial cytochrome c release with consecutive activation of different caspases. Essentially, cannabinoids significantly decreased tumour growth in vivo and were as potent as the MEK inhibitor trametinib. Conclusions: We could demonstrate that cannabinoids reduce cell viability in several melanoma cell lines, initiate apoptosis via the intrinsic apoptotic pathway by cytochrome c release and caspase activation and do not interfere with commonly used targeted therapy.

Leptin signaling in breast cancer and its crosstalk with peroxisome proliferator-activated receptors α and γ

Obesity may create a mitogenic microenvironment that influences tumor initiation and progression. The obesity-associated adipokine, leptin regulates energy metabolism and has been implicated in cancer development. It has been shown that some cell types other than adipocytes can express leptin and leptin receptors in tumor microenvironments. It has been shown that peroxisome proliferator-activated receptors (PPAR) agonists can affect leptin levels and vice versa leptin can affect PPARs. Activation of PPARs affects the expression of several genes involved in aspects of lipid metabolism. In addition, PPARs regulate cancer cell progression through their action on the tumor cell proliferation, metabolism, and cellular environment. Some studies have shown an association between obesity and several types of cancer, including breast cancer. There is some evidence that suggests that there is crosstalk between PPARs and leptin during the development of breast cancer. Through a systematic review of previous studies, we have reviewed the published relevant articles regarding leptin signaling in breast cancer and its crosstalk with peroxisome proliferator-activated receptors α and γ.

MiR-93/miR-375: Diagnostic Potential, Aggressiveness Correlation and Common Target Genes in Prostate Cancer

Dysregulation of miRNAs has a fundamental role in the initiation, development and progression of prostate cancer (PCa). The potential of miRNA in gene therapy and diagnostic applications is well documented. To further improve miRNAs' ability to distinguish between PCa and benign prostatic hyperplasia (BPH) patients, nine miRNA (-21, -27b, -93, -141, -205, -221, -182, -375 and let-7a) with the highest reported differentiation power were chosen and for the first time used in comparative studies of serum and prostate tissue samples. Spearman correlations and response operating characteristic (ROC) analyses were applied to assess the capability of the miRNAs present in serum to discriminate between PCa and BPH patients. The present study clearly demonstrates that miR-93 and miR-375 could be taken into consideration as single blood-based non-invasive molecules to distinguish PCa from BPH patients. We indicate that these two miRNAs have six common, PCa-related, target genes (CCND2, MAP3K2, MXI1, PAFAH1B1, YOD1, ZFYVE26) that share the molecular function of protein binding (GO:0005515 term). A high diagnostic value of the new serum derived miR-182 (AUC = 0.881, 95% confidence interval, CI = 0.816-0.946, p < 0.0001, sensitivity and specificity were 85% and 79%, respectively) is also described.

PPARα agonist alleviates tumor growth and chemo-resistance associated with the inhibition of glucose metabolic pathway

As a nuclear receptor, peroxisome-proliferator-activated receptor α (PPARα) plays a critical role in regulation of metabolism and cancer, while the effect of PPARα agonist on cancer cell glucose metabolism-linked tumor growth is still unclear. Here we found that PPARα agonist (Wy14,643) decreased Glut1 (Glucose transporter 1) gene and protein expressions of colorectal cancer cell lines in response to normoxia or hypoxia. Dual-luciferase analysis showed that Wy14,643 inhibited Glut1 transcription activity. Importantly, ChIP-qPCR analysis showed that Wy14,643 increased the binding of PPARα to Glut1 promoter region. Wy14,643 suppressed Glut1 transcription activity resulting in reduced influx of glucose in cancer cells in response to normoxia or hypoxia. Further analysis showed that Wy14,643-mediated inhibition of tumor growth and chemo-resistance was associated with inhibition of mTOR pathway. Taken together, PPARα agonist Wy14,643 suppressed Glut1 transcription activity, glucose uptake and mTOR pathway in colorectal cancer cells, which was involved in reduced tumor growth and chemo-resistance. These findings provided a novel therapy strategy for cancer progression.

PPARα gene is a diagnostic and prognostic biomarker in clear cell renal cell carcinoma by integrated bioinformatics analysis

Genetic alterations in lipid metabolism genes are correlated with progression and poor prognosis of Clear cell renal cell carcinoma (ccRCC). PPARα play a critical role in lipid metabolism. This study aimed to identify that PPARα is a diagnosis and prognostic biomarker in ccRCC by integrated bioinformatics analysis. UALCAN database was used to explore the differential expression status and prognostic value of PPARα gene in various tumor types, qRT-PCR and immunohistochemical staining experiments were utilized for validation. Next, ccRCC data were obtained from TCGA. Correlation between PPARα expression levels and patients' clinicopathological characteristics was assessed, and the clinically diagnosis and prognostic value of PPARα were explored in ccRCC. According to the gene set enrichment analysis (GSEA) analysis, PPARα gene associated biological pathways were identified. PPARα has prognostic significance only in ccRCC tumors. Expression of PPARα was associated with ccRCC stages. PPARα was significantly down-regulated in ccRCC and associated with survival. Gender, tumor dimension, grade and stage showed a significant relevance with PPARα expression. Lower PPARα expression revealed significantly poorer survival and progression compared with higher PPARα expression. Adjusted by other clinical risk factors, PPARα remained an independent prognostic factor. Moreover, Low PPARα expression was a potential diagnostic biomarker of ccRCC. A nomogram was constructed based on PPARα expression and other clinicopathological risk factors, and it performed well in predict patients survival. GSEA analysis showed that PPARα gene associated biological pathways were enriched in mTOR pathway, AKT pathway, IGF1-mTOR pathway and Wnt signaling pathways. In conclusion, PPARα expression was decreased in ccRCC tumors. Lower expression of PPARα is closely correlated with poorer survival. It can be used as a clinically diagnosis and prognostic biomarker in ccRCC.

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.

Activation of PPARs Modulates Signalling Pathways and Expression of Regulatory Genes in Osteoclasts Derived from Human CD14+ Monocytes

Osteoclasts are the sole bone resorbing cell in the body and their over activity is key in the development of osteoporosis. Osteoclastogenesis is mediated by receptor activator of nuclear factor κB ligand (RANKL) signalling pathways. Unsaturated fatty acids (UFA) are known to inhibit osteoclastogenesis by targeting RANKL signalling. However, the mechanisms of action remain unclear. Peroxisome proliferator activated receptors (PPARs) are a family of nuclear receptors, with three known isoforms (PPAR-α, PPAR-β/δ and PPAR-γ), that are known to bind UFAs and are expressed in osteoclasts. In this study, we aimed to determine how different families of UFAs activate PPARs and how PPAR activation influences osteoclast signalling. Human CD14+ monocytes were seeded into cluster plates with RANKL and macrophage colony stimulating factor (M-CSF) in the presence of PPAR agonists or different types of UFAs. All the PPAR agonists were shown to upregulate the activity of their respective receptors. Polyunsaturated fatty acids increased PPAR-α to a greater extent than monounsaturated fatty acids (MUFAs), which favoured PPAR-β/δ activation. All PPAR agonists inhibited osteoclastogenesis. The activation of RANKL signalling pathways and expression of key osteoclast genes were downregulated by PPAR agonists. This study reveals that PPAR activation can inhibit osteoclastogenesis through modulation of RANKL signalling.

PPARα Enhances Cancer Cell Chemotherapy Sensitivity by Autophagy Induction

PPARα (peroxisome-proliferator-activated receptor α) plays a critical role in regulation of inflammation and cancer, while the regulatory mechanism of PPARα on cancer cell autophagy is still unclear. Here we found that PPARα enhanced autophagy in HEK293T, SW480, and Hela cell lines, which was independent of PPARα transcription activity. PPARα induced antiapoptotic Bcl2 protein degradation resulting in release of the Beclin-1/VPS34 complex. Consistently, silenced PPARα reversed this event. PPARα-induced autophagy significantly inhibited tumor growth and enhanced SW480 cancer cell sensitivity to chemotherapy drugs. Moreover, PPARα agonist increased SW480 cancer cell chemotherapy sensitivity. These findings revealed a novel mechanism of PPARα/Bcl2/autophagy pathway suppressed tumor progression and enhanced chemotherapy sensitivity, which is a potential drug target for cancer treatment.

Analysis of key genes and signaling pathways involved in Helicobacter pylori-associated gastric cancer based on The Cancer Genome Atlas database and RNA sequencing data

BACKGROUND

Helicobacter pylori (H. pylori) infection is associated with the development of gastric cancer, although the mechanism is unclear. Herein, this study aimed to clarify the key genes and signaling pathways involved in H. pylori pathogenesis based on The Cancer Genome Atlas (TCGA) database and RNA sequencing analysis.

MATERIALS AND METHODS

Forty-nine gastric cancer samples (16 with H. pylori and 33 without H. pylori) and 35 cancer-adjacent normal samples from TCGA database were analyzed by bioinformatics. The differentially expressed genes between H. pylori-positive and H. pylori-negative patients were verified in 18 gastric cancer (GC) samples (9 with H. pylori and 9 without H. pylori), which were analyzed using RNA sequencing. Survival analysis was carried out to explore associations between the differentially expressed genes and prognosis. Bioinformatics analysis was performed to determine the signaling pathways associated with H. pylori.

RESULTS

The baseline level of clinical features from TCGA database and RNA sequencing showed no differences between the H. pylori-positive and H. pylori-negative GC groups (P > 0.05). TP53 was shown to be upregulated in the H. pylori-positive group in both TCGA database and RNA sequencing data, which also showed higher expression in the GC tissues than in adjacent normal tissues (P < 0.05). CCDC151, CHRNB2, GMPR2, HDGFRP2, and VSTM2L were shown to be downregulated in the H. pylori-positive group by both TCGA database and RNA sequencing, which also showed lower expression in the GC tissues than in adjacent normal tissues (P < 0.05). GC patients with low expression levels of HDGFRP2 had a poor prognosis (P < 0.05). Thirty-three signaling pathways and 10 biological processes were found to be positively associated with H. pylori infection (P < 0.05, FDR < 0.05).

CONCLUSIONS

These results indicate that some genes (TP53, CCDC151, CHRNB2, GMPR2, HDGFRP2, VSTM2L) and previously unidentified signaling pathways (eg, the Hippo signaling pathway) might play an important role in H. pylori-associated GC.

Decreased expression of peroxisome proliferator-activated receptor alpha indicates unfavorable outcomes in hepatocellular carcinoma

Introduction

Hepatocellular carcinoma (HCC) has a close relationship with lipid metabolism. Peroxisome proliferator-activated receptor α (PPARα) plays a crucial role in the regulation of fatty acid oxidation in the liver. However, the role of PPARα in HCC remains unclear.

Methods

A total of 804 HCC specimens were collected to construct a tissue microarray and for immunohistochemical analysis. The relationship between PPARα expression and clinical features of HCC patients was analyzed. Kaplan–Meier analysis was conducted to assess the prognostic value of PPARα expression levels.

Results

The expression of PPARα in HCC was noticeably decreased in HCC tissues. HCC patients with high levels of PPARα expression in cytoplasm had smaller tumors (P=0.027), less vascular invasion (P=0.049), and a higher proportion of complete involucrum (P=0.038). Kaplan–Meier analysis showed that HCC patients with low PPARα expression in the cytoplasm had significantly worse outcomes in terms of overall survival (P<0.001), disease-free survival (P=0.024), and the probability of recurrence (P=0.037). Similarly, overall survival was significantly shorter in HCC patients with negative PPARα expression in the nucleus (P=0.034). Multivariate Cox analyses indicated that tumor size (P=0.001), TNM stage (P<0.001), vascular invasion (P<0.001), and PPARα expression in the cytoplasm (P<0.001) were found to be independent prognostic variables for overall survival.

Conclusion

Our data revealed that PPARα expression was decreased in HCC samples. High PPARα expression was correlated with longer survival times in HCC patients, and served as an independent factor for better outcomes. Our study therefore provides a promising biomarker for prognostic prediction and a potential therapeutic target for HCC.

Peroxisome proliferator-activated receptors (PPARs) are potential drug targets for cancer therapy

Peroxisome-proliferator-activated receptors (PPARs) are nuclear hormone receptors including PPARα, PPARδ and PPARγ, which play an important role 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. In this review, we summarized the regulative mechanism of PPARs on cancer progression.

PPARα regulates tumor progression, foe or friend?

PPARα belongs to the peroxisome-proliferator-activated receptors (PPARs) family that consists of PPARα, PPARδ, and PAPRγ. Activation of PPARα by ligands including fatty acids and their derivatives as well as some synthetic compounds regulates tumor progression in various tissues. Activated PPARα inhibits or promotes tumorigenesis depending on the specific tissues, but the molecular mechanism is still unclear. In this review, the recent progress of PPARα regulating tumorigenesis is discussed.

Human germline and pan-cancer variomes and their distinct functional profiles

Identification of non-synonymous single nucleotide variations (nsSNVs) has exponentially increased due to advances in Next-Generation Sequencing technologies. The functional impacts of these variations have been difficult to ascertain because the corresponding knowledge about sequence functional sites is quite fragmented. It is clear that mapping of variations to sequence functional features can help us better understand the pathophysiological role of variations. In this study, we investigated the effect of nsSNVs on more than 17 common types of post-translational modification (PTM) sites, active sites and binding sites. Out of 1 705 285 distinct nsSNVs on 259 216 functional sites we identified 38 549 variations that significantly affect 10 major functional sites. Furthermore, we found distinct patterns of site disruptions due to germline and somatic nsSNVs. Pan-cancer analysis across 12 different cancer types led to the identification of 51 genes with 106 nsSNV affected functional sites found in 3 or more cancer types. 13 of the 51 genes overlap with previously identified Significantly Mutated Genes (Nature. 2013 Oct 17;502(7471)). 62 mutations in these 13 genes affecting functional sites such as DNA, ATP binding and various PTM sites occur across several cancers and can be prioritized for additional validation and investigations.

Multivariate hypergeometric similarity measure

We propose a similarity measure based on the multivariate hypergeometric distribution for the pairwise comparison of images and data vectors. The formulation and performance of the proposed measure are compared with other similarity measures using synthetic data. A method of piecewise approximation is also implemented to facilitate application of the proposed measure to large samples. Example applications of the proposed similarity measure are presented using mass spectrometry imaging data and gene expression microarray data. Results from synthetic and biological data indicate that the proposed measure is capable of providing meaningful discrimination between samples, and that it can be a useful tool for identifying potentially related samples in large-scale biological data sets.