HIF2α-induced upregulation of RNASET2 promotes triglyceride synthesis and enhances cell migration in clear cell renal cell carcinoma

RNASET2 Deficiency Induces Hepatocellular Carcinoma Metastasis through Cholesterol-Triggered MET Activation

Metastasis remains a significant challenge in the treatment of hepatocellular carcinoma (HCC). The role of ribonuclease T2 (RNASET2) in HCC is still uncertain, although it has been reported to have contradictory effects on some cancers. Here, it is demonstrated that RNASET2 knockout leads to significant accumulation of cholesterol, which in turn promotes MET-mediated HCC metastasis. Mechanistically, the absence of RNASET2 hinders the degradation of RNA into uridine, thereby reducing the conversion to UTP. This reduction restrains glucuronate metabolism and the expression of the related enzyme UDP-glucuronosyltransferase (UGT)1A1, ultimately resulting in the accumulation of cholesterol due to decreased formation of glucuronidated-bile acids. The administration of cholesterol induces the migration and invasion of HCC cells through MET (mesenchymal-epithelial transition factor) activation. However, the deficiency of RNASET2-induced HCC metastasis can be reversed by blocking MET with shRNA or savolitinib. The study identifies RNASET2 as a key regulator that coordinates RNA, glucuronate, and cholesterol metabolism. Its deficiency drives HCC metastasis through cholesterol-triggered MET activation. These findings highlight the potential of targeting RNASET2 and MET in improving the prognosis of HCC.

Comprehensive analysis of LD-related genes signature for predicting prognosis and immunotherapy response in clear cell renal cell carcinoma

BACKGROUND

Lipid droplets (LD) in renal clear cell carcinoma (ccRCC)play a crucial role in lipid metabolism and immune response modulation. The purpose of this study was to create a LD-related signature to predict prognosis and guide the immunotherapy and targeted therapy in ccRCC patients.

METHODS

We conducted a comprehensive analysis using transcriptional profiles and clinical data obtained from The Cancer Genome Atlas (TCGA). LD-related genes were identified from existing literature and the GeneCards database, and differentially expressed genes were determined. Sequentially, we conducted Cox regression analysis and Lasso regression analysis, to establish a prognostic risk model. The performance of the risk model was evaluated using Kaplan-Meier (KM) analysis and time-dependent receiver operating characteristic (ROC) analysis. Additionally, gene set enrichment analysis (GSEA), ESTIMATE, CIBERSORT, and immunophenoscore (IPS) algorithm were used to assess the tumor microenvironment (TME) and treatment response.

RESULTS

We constructed a risk signature with four LD-related genes in the TCGA dataset, which could be an independent prognostic factor in ccRCC patients. Then, patients were classified into two risk groups and exhibited notable differences in overall survival (OS), progression-free survival (PFS), and TME characteristics. Furthermore, we developed a comprehensive nomogram based on clinical features, which demonstrated good prognostic predictive value. According to the results of GSEA analysis, immune-related pathways were found to be significantly enriched in the high-risk group. Additionally, the high-risk group displayed high levels of immune cell infiltration, TMB and IPS scores, indicating better efficacy of immune checkpoint inhibitors (ICIs). Finally, high-risk demonstrated reduced IC50 values compared to the low-risk counterpart for specific targeted and chemotherapeutic drugs, suggesting that the patients receiving these targeted drugs in high-risk group had better treatment outcomes.

CONCLUSIONS

Our findings suggested that the LD-related gene signature could potentially predict the prognosis of ccRCC patients. Additionally, it showed promise for predicting responses to immunotherapy and targeted therapy in ccRCC patients. These insights might potentially have guided the clinical management of these patients, but further validation and broader data analysis are needed to confirm these preliminary observations.

Targeting lipid droplets and lipid droplet-associated proteins: a new perspective on natural compounds against metabolic diseases

BACKGROUND

Lipid droplet (LD) is a metabolically active organelle, which changes dynamically with the metabolic state and energy requirements of cells. Proteins that either insert into the LD phospholipid monolayer or are present in the cytoplasm, playing a crucial role in lipid homeostasis and signaling regulation, are known as LD-associated proteins.

METHODS

The keywords "lipid droplets" and "metabolic diseases" were used to obtain literature on LD metabolism and pathological mechanism. After searching databases including Scopus, OVID, Web of Science, and PubMed from 2013 to 2024 using terms like "lipid droplets", "lipid droplet-associated proteins", "fatty liver disease", "diabetes", "diabetic kidney disease", "obesity", "atherosclerosis", "hyperlipidemia", "natural drug monomers" and "natural compounds", the most common natural compounds were identified in about 954 articles. Eventually, a total of 91 studies of 10 natural compounds reporting in vitro or in vivo studies were refined and summarized.

RESULTS

The most frequently used natural compounds include Berberine, Mangostin, Capsaicin, Caffeine, Genistein, Epigallocatechin-3-gallate, Chlorogenic acid, Betaine, Ginsenoside, Resveratrol. These natural compounds interact with LD-associated proteins and help ameliorate abnormal LDs in various metabolic diseases.

CONCLUSION

Natural compounds involved in the regulation of LDs and LD-associated proteins hold promise for treating metabolic diseases. Further research into these interactions may lead to new therapeutic applications.

Lipid droplets: a candidate new research field for epithelial ovarian cancer

Ovarian clear cell carcinoma (OCCC) is a histological subtype that constitutes approximately 20% of epithelial ovarian cancer cases in Asian countries, but has a relatively low incidence in Western countries. Meanwhile, clear cell renal cell carcinoma (ccRCC) is a major subtype of kidney cancer. OCCC and ccRCC resemble one another histologically and have clear cytoplasmic appearances. Studies have revealed some genetic similarities between OCCC and ccRCC. However, information regarding common biological background factors between these cancers remains scarce. For example, accumulation of cellular lipid droplets was shown to play a crucial role in ccRCC progression, while similar information is lacking for OCCC. In this perspective article, we propose that lipid droplets may be candidates for future exploration to better understand the common biological backgrounds between OCCC and ccRCC, potentially leading to subtype-specific treatment strategies. We further discuss the relationship between poly ADP-ribose polymerase inhibition treatment and lipid metabolism because this therapeutic strategy has attracted considerable attention as a treatment for epithelial ovarian cancer.

Pathogenic Roles for RNASET2 in Clear Cell Renal Cell Carcinoma

A specific splicing isoform of RNASET2 is associated with worse oncologic outcomes in clear cell renal cell carcinoma (ccRCC). However, the interplay between wild-type RNASET2 and its splice variant and how this might contribute to the pathogenesis of ccRCC remains poorly understood. We sought to better understand the relationship of RNASET2 in the pathogenesis of ccRCC and the interplay with a pathogenic splicing isoform (RNASET2-SV) and the tumor immune microenvironment. Using data from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium, we correlated clinical variables to RNASET2 expression and the presence of a specific RNASET2-SV. Immunohistochemical staining with matched RNA sequencing of ccRCC patients was then utilized to understand the spatial relationships of RNASET2 with immune cells. Finally, in vitro studies were performed to demonstrate the oncogenic role of RNASET2 and highlight its potential mechanisms. RNASET2 gene expression is associated with higher grade tumors and worse overall survival in The Cancer Genome Atlas cohort. The presence of the RNASET2-SV was associated with increased expression of the wild-type RNASET2 protein and epigenetic modifications of the gene. Immunohistochemical staining revealed increased intracellular accumulation of RNASET2 in patients with increased RNA expression of RNASET2-SV. In vitro experiments reveal that this accumulation results in increased cell proliferation, potentially from altered metabolic pathways. RNASET2 exhibits a tumor-promoting role in the pathogenesis of ccRCC that is increased in the presence of a specific RNASET2-SV and associated with changes in the cellular localization of the protein.

Emergence of Lipid Droplets in the Mechanisms of Carcinogenesis and Therapeutic Responses

Cancer shares common risk factors with cardiovascular diseases such as dyslipidemia, obesity and inflammation. In both cases, dysregulations of lipid metabolism occur, and lipid vesicles emerge as important factors that can influence carcinogenesis. In this review, the role of different lipids known to be involved in cancer and its response to treatments is detailed. In particular, lipid droplets (LDs), initially described for their role in lipid storage, exert multiple functions, from the physiological prevention of LD coalescence and regulation of endoplasmic reticulum homeostasis to pathological involvement in tumor progression and aggressiveness. Analysis of LDs highlights the importance of phosphatidylcholine metabolism and the diversity of lipid synthesis enzymes. In many cancers, the phosphatidylcholine pathways are disrupted, modifying the expression of genes coding for metabolic enzymes. Tumor microenvironment conditions, such as hypoxia, different types of stress or inflammatory conditions, are also important determinants of LD behavior in cancer cells. Therefore, LDs represent therapeutic targets in cancer, and many lipid mediators have emerged as potential biomarkers for cancer onset, progression, and/or resistance.