Ligand-activated PPARδ expression promotes hepatocellular carcinoma progression by regulating the PI3K-AKT signaling pathway

Activation of PPARδ in bone marrow endothelial progenitor cells improves their hematopoiesis-supporting ability after myelosuppressive injury

Dysfunctional bone marrow (BM) endothelial progenitor cells (EPCs) with high levels of reactive oxygen species (ROS) are responsible for defective hematopoiesis in poor graft function (PGF) patients with acute leukemia or myelodysplastic neoplasms post-allotransplant. However, the underlying mechanism by which BM EPCs regulate their intracellular ROS levels and the capacity to support hematopoiesis have not been well clarified. Herein, we demonstrated decreased levels of peroxisome proliferator-activated receptor delta (PPARδ), a lipid-activated nuclear receptor, in BM EPCs of PGF patients compared with those with good graft function (GGF). In vitro assays further identified that PPARδ knockdown contributed to reduced and dysfunctional BM EPCs, characterized by the impaired ability to support hematopoiesis, which were restored by PPARδ overexpression. Moreover, GW501516, an agonist of PPARδ, repaired the damaged BM EPCs triggered by 5-fluorouracil (5FU) in vitro and in vivo. Clinically, activation of PPARδ by GW501516 benefited the damaged BM EPCs from PGF patients or acute leukemia patients in complete remission (CR) post-chemotherapy. Mechanistically, we found that increased expression of NADPH oxidases (NOXs), the main ROS-generating enzymes, may lead to elevated ROS level in BM EPCs, and insufficient PPARδ may trigger BM EPC damage via ROS/p53 pathway. Collectively, we found that defective PPARδ contributes to BM EPC dysfunction, whereas activation of PPARδ in BM EPCs improves their hematopoiesis-supporting ability after myelosuppressive therapy, which may provide a potential therapeutic target not only for patients with leukemia but also for those with other cancers.

Lipid Metabolism as a Potential Target of Liver Cancer

Hepatocellular carcinoma (HCC) stands as a severe malignant tumor with a profound impact on overall health, often accompanied by an unfavorable prognosis. Despite some advancements in the diagnosis and treatment of this disease, improving the prognosis of HCC remains a formidable challenge. It is noteworthy that lipid metabolism plays a pivotal role in the onset, development, and progression of tumor cells. Existing research indicates the potential application of targeting lipid metabolism in the treatment of HCC. This review aims to thoroughly explore the alterations in lipid metabolism in HCC, offering a detailed account of the potential advantages associated with innovative therapeutic strategies targeting lipid metabolism. Targeting lipid metabolism holds promise for potentially enhancing the prognosis of HCC.

Prognostic analysis and risk assessment based on RNA editing in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, and prognosis assessment is crucial for guiding treatment decisions. In this study, we aimed to develop a personalized prognostic model for HCC based on RNA editing. RNA editing is a post-transcriptional process that can affect gene expression and, in some cases, play a role in cancer development. By analyzing RNA editing sites in HCC, we sought to identify a set of sites associated with patient prognosis and use them to create a prognostic model. We gathered RNA editing data from the Synapse database, comprising 9990 RNA editing sites and 250 HCC samples. Additionally, we collected clinical data for 377 HCC patients from the Cancer Genome Atlas (TCGA) database. We employed a multi-step approach to identify prognosis-related RNA editing sites (PR-RNA-ESs). We assessed how patients in the high-risk and low-risk groups, as defined by the model, fared in terms of survival. A nomogram was developed to predict the precise survival prognosis of HCC patients and assessed the prognostic model's utility through a receiver operating characteristic (ROC) analysis and decision curve analysis (DCA). Our analysis identified 33 prognosis-related RNA editing sites (PR-RNA-ESs) associated with HCC patient prognosis. Using a combination of LASSO regression and cross-validation, we constructed a prognostic model based on 13 PR-RNA-ESs. Survival analysis demonstrated significant differences in the survival outcomes of patients in the high-risk and low-risk groups defined by this model. Additionally, the differential expression of the 13 PR-RNA-ESs played a role in shaping patient survival. Risk-prognostic investigations further distinguished patients based on their risk levels. The nomogram enabled precise survival prognosis prediction. Our study has successfully developed a highly personalized and accurate prognostic model for individuals with HCC, leveraging RNA editing data. This model has the potential to revolutionize clinical evaluation and medical management by providing individualized prognostic information. The identification of specific RNA editing sites associated with HCC prognosis and their incorporation into a predictive model holds promise for improving the precision of treatment strategies and ultimately enhancing patient outcomes in HCC.

Roles of peroxisome proliferator-activated receptors in hepatocellular carcinoma

Hepatocellular carcinoma (HCC), the main pathological type of liver cancer, is linked to risk factors such as viral hepatitis, alcohol intake and non-alcoholic fatty liver disease (NAFLD). Recent advances have greatly improved our understanding that NAFLD is playing a major risk factor for HCC. Peroxisome proliferator-activated receptors (PPARs) are a class of transcription factors divided into three subtypes: PPARα (PPARA), PPARδ/β (PPARD) and PPARγ (PPARG). As important nuclear receptors, PPARs are involved in many physiological processes, and PPARs can improve NAFLD by regulating lipid metabolism, accelerating fatty acid oxidation and inhibiting inflammation. In recent years, some studies have shown that PPARs can participate in the occurrence and development of HCC by regulating metabolic pathways. In addition, PPAR modulators have been reported to inhibit the proliferation and metastasis of HCC cells and can enhance the curative effect of conventional treatments. This article reviews the role of PPARs in the occurrence and development of HCC, as well as its value in the diagnosis, treatment and prognosis of HCC, in order to provide directions for future research.

Functional role of MicroRNA/PI3K/AKT axis in osteosarcoma

Osteosarcoma (OS) is a primary malignant bone tumor that occurs in children and adolescents, and the PI3K/AKT pathway is overactivated in most OS patients. MicroRNAs (miRNAs) are highly conserved endogenous non-protein-coding RNAs that can regulate gene expression by repressing mRNA translation or degrading mRNA. MiRNAs are enriched in the PI3K/AKT pathway, and aberrant PI3K/AKT pathway activation is involved in the development of osteosarcoma. There is increasing evidence that miRNAs can regulate the biological functions of cells by regulating the PI3K/AKT pathway. MiRNA/PI3K/AKT axis can regulate the expression of osteosarcoma-related genes and then regulate cancer progression. MiRNA expression associated with PI3K/AKT pathway is also clearly associated with many clinical features. In addition, PI3K/AKT pathway-associated miRNAs are potential biomarkers for osteosarcoma diagnosis, treatment and prognostic assessment. This article reviews recent research advances on the role and clinical application of PI3K/AKT pathway and miRNA/PI3K/AKT axis in the development of osteosarcoma.

DLGAP4 acts as an effective prognostic predictor for hepatocellular carcinoma and is closely related to tumour progression

Disc large associated protein 4 (DLGAP4) plays an important role in neurological diseases, but the role and mechanism of DLGAP4 in hepatocellular carcinoma (HCC) remain unclear. In this study, the prognostic effect of DLGAP4 on HCC patients was investigated by means of bioinformatics. The correlation of DLGAP4 expression with the prognosis of HCC patients was evaluated by TCGA data analysis, and the correlation between DLGAP4 expression and the clinical characteristics of HCC patients was evaluated by the Wilcoxon signed rank test and logistic regression analysis. Kaplan‒Meier and Cox regression methods were used to assess the effect of DLGAP4 expression level on overall survival, and nomograms were used to illustrate the correlation between DLGAP4 gene expression and HCC risk. The genes related to DLGAP4 in HCC were screened, and GO/KEGG enrichment analysis was performed. Furthermore, in vitro and in vivo experiments were conducted to detect the effect of DLGAP4 expression on the proliferation, migration and metastasis of HCC cells. We also examined the effect of DLGAP4 expression on enriched pathway proteins to explore the possible mechanism. The expression levels of DLGAP4 were significantly higher in HCC cell lines and tissue samples than in normal liver cell lines and tissues. The expression of DLGAP4 was significantly associated with clinical characteristics. Survival analysis showed that high expression of DLGAP4 was associated with a poor prognosis in HCC. Multivariate analysis showed that high expression of DLGAP4 was an independent risk factor affecting the overall survival rate in HCC patients. By means of ROC curve analysis and nomograms, we determined the value of DLGAP4 expression in the diagnosis and prognosis evaluation of HCC. GO/KEGG enrichment analysis showed that the PPAR signalling pathway was differentially enriched in patients with high expression of DLGAP4. According to in vitro and in vivo experiments, DLGAP4 knockdown inhibited the proliferation and metastasis of HCC cells and decreased the expression of PPARβ/δ protein. In contrast, overexpression of DLGAP4 promoted the proliferation and metastasis of HCC cell, and increased the expression of PPARβ/δ protein.In contrast, overexpression of DLGAP4 promoted the proliferation and metastasis of HCC cells and increased the expression of PPARβ/δ protein. The results show a close correlation between DLGAP4 expression and clinicopathological features of HCC, and DLGAP4 can be used as a prediction biomarker of HCC.