Integrative Analysis of DNA Methylation Identified 12 Signature Genes Specific to Metastatic ccRCC

Diagnostic, predictive and prognostic molecular biomarkers in clear cell renal cell carcinoma: A retrospective study

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive subtype of kidney cancer. Many patients are diagnosed at advanced stages, making early detection crucial. Unfortunately, there are currently no noninvasive tests for ccRCC, emphasizing the need for new biomarkers. Additionally, ccRCC often develops resistance to treatments like radiotherapy and chemotherapy. Identifying biomarkers that predict treatment outcomes is vital for personalized care. The integration of artificial intelligence (AI), multi-omics analysis, and computational biology holds promise in bolstering detection precision and resilience, opening avenues for future investigations. The amalgamation of radiogenomics and biomaterial-basedimmunomodulation signifies a revolutionary breakthrough in diagnostic medicine. This review summarizes existing literature and highlights emerging biomarkers that enhance diagnostic, predictive, and prognostic capabilities for ccRCC, setting the stage for future clinical research.

GPX4, ferroptosis, and diseases

GPX4 (Glutathione peroxidase 4) serves as a crucial intracellular regulatory factor, participating in various physiological processes and playing a significant role in maintaining the redox homeostasis within the body. Ferroptosis, a form of iron-dependent non-apoptotic cell death, has gained considerable attention in recent years due to its involvement in multiple pathological processes. GPX4 is closely associated with ferroptosis and functions as the primary inhibitor of this process. Together, GPX4 and ferroptosis contribute to the pathophysiology of several diseases, including sepsis, nervous system diseases, ischemia reperfusion injury, cardiovascular diseases, and cancer. This review comprehensively explores the regulatory roles and impacts of GPX4 and ferroptosis in the development and progression of these diseases, with the aim of providing insights for identifying potential therapeutic strategies in the future.

Eleven metabolism‑related genes composed of Stard5 predict prognosis and contribute to EMT phenotype in HCC

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, with a high mortality and poor survival rate. Abnormal tumor metabolism is considered a hallmark of HCC and is a potential therapeutic target. This study aimed to identify metabolism-related biomarkers to evaluate the prognosis of patients with HCC.

METHOD

The Cancer Genome Atlas (TCGA) database was used to explore differential metabolic pathways based on high and low epithelial-mesenchymal transition (EMT) groupings. Genes in differential metabolic pathways were obtained for HCC metabolism-related molecular subtype analysis. Differentially expressed genes (DEGs) from the three subtypes were subjected to Lasso Cox regression analysis to construct prognostic risk models. Stard5 expression in HCC patients was detected by western blot and immunohistochemistry (IHC), and the role of Stard5 in the metastasis of HCC was investigated by cytological experiments.

RESULTS

Unsupervised clustering analysis based on metabolism-related genes revealed three subtypes in HCC with differential prognosis. A risk prognostic model was constructed based on 11 genes (STARD5, FTCD, SCN4A, ADH4, CFHR3, CYP2C9, CCL14, GADD45G, SOX11, SCIN, and SLC2A1) obtained by LASSO Cox regression analysis of the three subtypes of DEGs. We validated that the model had a good predictive power. In addition, we found that the high-risk group had a poor prognosis, higher proportion of Tregs, and responded poorly to chemotherapy. We also found that Stard5 expression was markedly decreased in HCC tissues, which was associated with poor prognosis and EMT. Knockdown of Stard5 contributed to the invasion and migration of HCC cells. Overexpression of Stard5 inhibited EMT in HCC cells.

CONCLUSION

We developed a new model based on 11 metabolism-related genes, which predicted the prognosis and response to chemotherapy or immunotherapy for HCC. Notably, we demonstrated for the first time that Stard5 acted as a tumor suppressor by inhibiting metastasis in HCC.

Chidamide, a novel histone deacetylase inhibitor, inhibits laryngeal cancer progression in vitro and in vivo

Although surgery is an important treatment for laryngeal cancer, surgery has a significant negative impact on the quality of life of patients, and many patients have poor tolerance to surgery. Therefore, alternative chemotherapeutic drugs are an important research hotspot. Chidamide is a histone deacetylase inhibitor that selectively inhibits the expression of type I and IIb histone deacetylases (1, 2, 3 and 10). It has a significant anticancer effect on a variety of solid tumours. This study verified the inhibitory effect of chidamide on laryngeal carcinoma. We conducted a variety of cellular and animal experiments to explore how chidamide inhibits the development of laryngeal cancer. The results showed that chidamide had significant antitumour activity against laryngeal carcinoma cells and xenografts and could induce cell apoptosis, ferroptosis and pyroptosis. This study provides a potential option for the treatment of laryngeal cancer.

GPX4: The hub of lipid oxidation, ferroptosis, disease and treatment

Glutathione peroxidase 4 (GPx4) moonlights as structural protein and antioxidase that powerfully inhibits lipid oxidation. In the past years, it is considered as a key regulator of ferroptosis, which takes role in the lipid and amine acid metabolism and influences the cell aging, oncogenesis, and cell death. More and more evidences show that targeting GPX4-induced ferroptosis is a promising strategy for disease therapy, especially cancer treatment. In view of these, we generalize the function of GPX4 and regulatory mechanism between GPX4 and ferroptosis, discuss its roles in the disease pathology, and focus on the recent advances of disease therapeutic potential.

Heterogeneous nuclear ribonucleoprotein A/B: an emerging group of cancer biomarkers and therapeutic targets

Heterogeneous nuclear ribonucleoprotein A/B (hnRNPA/B) is one of the core members of the RNA binding protein (RBP) hnRNPs family, including four main subtypes, A0, A1, A2/B1 and A3, which share the similar structure and functions. With the advance in understanding the molecular biology of hnRNPA/B, it has been gradually revealed that hnRNPA/B plays a critical role in almost the entire steps of RNA life cycle and its aberrant expression and mutation have important effects on the occurrence and progression of various cancers. This review focuses on the clinical significance of hnRNPA/B in various cancers and systematically summarizes its biological function and molecular mechanisms.

STARD5 as a potential clinical target of hepatocellular carcinoma

To reveal whether STARD5 is a potential biomarker for diagnosis and prognosis of HCC. Using gene expression omnibus and the cancer genome atlas (TCGA) to screen differentially expressed genes in HCC and STARD5 was selected by LASSO algorithm. Then, we analyzed the association between STARD5 and clinical characteristics of HCC patients in TCGA and International Cancer Genome Consortium. Meanwhile, the mRNA and protein level of STARD5 was also verified by collecting 87 cases of HCC patients' liver tissues using qRT-PCR and WB. Next, we applied gene set enrichment analysis (GSEA) for pathways analysis of STARD5. Finally, TIMER1.0 and TISIDB were used to explore the correlation of STARD5 with immune cell infiltration. The expression of STARD5 was lower in HCC and negatively correlated with tumor grade (p < 0.05), while high expression of STARD5 suggested a better prognosis for HCC patients (p < 0.01) and it could be an independent prognostic predictor (p < 0.001). Meanwhile, STARD5 also had strong diagnostic accuracy for HCC patients. GSEA revealed that STARD5-related genes were mainly enriched in E2F targets, G2M checkpoint and KRAS signaling. The TIMER1.0 and TISIDB databases found a negative correlation between STARD5 and tumor immune infiltrating cells. STARD5 could be used as a potential target for HCC diagnosis and prognosis.

Epigenetic inactivation of ACAT1 promotes epithelial-mesenchymal transition of clear cell renal cell carcinoma

BACKGROUND

Acetyl-CoA acyltransferase 1 (ACAT1) is a key enzyme catalyzing the production of mitochondrial ketone bodies. We have shown that ACAT1 is down-regulated in kidney renal clear cell carcinoma (KIRC) previously.

OBJECTIVE

To investigate the reasons for downregulation of ACAT1 in KIRC and explore the underlying mechanisms involved in metastatic inhibition regulated by ACAT1.

METHODS

The Gene Expression Omnibus (GEO) database was queried for meta-analysis of ACAT1 mRNA expression in KIRC. The UALCAN website was used to compare the methylation levels of the ACAT1 promoter region in KIRC and normal tissues. RT-qPCR was used to quantitate ACAT1 transcription levels. The GCBI and Tarbase V.8 databases were used to predict miRNAs that may target the mRNA of ACAT1. The correlation between mRNA expression of ACAT1, MMP7 (matrix metallopeptidase 7), CDH1 (E-cadherin), EpCAM (epithelial cell adhesion molecule), and VIM (vimentin) was analyzed. Extracellular MMP7 protein was quantitated using an ELISA assay.

RESULTS

The methylation level of the ACAT1 promoter region in KIRC was significantly higher than that in the normal kidney tissues. The ACAT1 mRNA expression in the KIRC cell lines was restored after treatment with 5-aza-dC (p < 0.05). MiR-21-5p is a conserved microRNA targeting ACAT1. It is expressed at a significantly higher level in KIRC than in normal tissues (p < 0.001). MiR-21-5p miRNA expression negatively correlates with ACAT1 mRNA expression. The expression of miR-21-5p is higher at the T3-T4 stages and in the histologic grades G3-G4. Patients with high miR-21-5p expression tended to have lower overall survival, suggesting that miR-21-5p could serve as a potentially valuable diagnostic biomarker for KIRC (AUC = 0.957; p < 0.001). A mimetic of miR-21-5p inhibited the expression of ACAT1 mRNA and protein. In addition, ACAT1 mRNA expression positively correlates with CDH1 and EpCAM but is negatively correlated with VIM. Overexpression of ACAT1 suppresses the secretion of MMP7 in KIRC cells.

CONCLUSION

Expression of ACAT1 in KIRC is controlled at two levels, firstly by the hypermethylation of the ACAT1 promoter region and secondly by overexpression of miR-21-5p. Downregulation of ACAT1 expression correlates with epithelial-mesenchymal transition (EMT).

Integrative 5-Methylcytosine Modification Immunologically Reprograms Tumor Microenvironment Characterizations and Phenotypes of Clear Cell Renal Cell Carcinoma

The tumor microenvironment (TME) affects the biologic malignancy of clear cell renal cell carcinoma (ccRCC). The influence of the 5-methylcytosine (m⁵C) epigenetic modification on the TME is unknown. We comprehensively assessed m⁵C modification patterns of 860 ccRCC samples (training, testing, and real-world validation cohorts) based on 17 m⁵C regulators and systematically integrated the modification patterns with TME cell-infiltrating characterizations. Our results identified distinct m⁵C modification clusters with gradual levels of immune cell infiltration. The distinct m⁵C modification patterns differ in clinicopathological features, genetic heterogeneity, patient prognosis, and treatment responses of ccRCC. An elevated m⁵C score, characterized by malignant biologic processes of tumor cells and suppression of immunity response, implies an immune-desert TME phenotype and is associated with dismal prognosis of ccRCC. Activation of exhausted T cells and effective immune infiltration were observed in the low m⁵C score cluster, reflecting a noninflamed and immune-excluded TME phenotype with favorable survival and better responses to immunotherapy. Together, these findings provide insights into the regulation mechanisms of DNA m⁵C methylation modification patterns on the tumor immune microenvironment. Comprehensive assessment of tumor m⁵C modification patterns may enhance our understanding of TME cell-infiltrating characterizations and help establish precision immunotherapy strategies for individual ccRCC patients.

Identification of Prognostic Metabolism-Related Genes in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a cancer with abnormal metabolism. The purpose of this study was to investigate the effect of metabolism-related genes on the prognosis of ccRCC patients.

Methods

The data of ccRCC patients were downloaded from the TCGA and the GEO databases and clustered using the nonnegative matrix factorization method. The limma software package was used to analyze differences in gene expression. A random forest model was used to screen for important genes. A novel Riskscore model was established using multivariate regression. The model was evaluated based on the metabolic pathway, immune infiltration, immune checkpoint, and clinical characteristics.

Results

According to metabolism-related genes, kidney clear cell carcinoma (KIRC) datasets downloaded from TCGA were clustered into two groups and showed significant differences in prognosis and immune infiltration. There were 667 differentially expressed genes between the two clusters, of which 408 were screened by univariate analysis. Finally, 12 differentially expressed genes (MDK, SLC1A1, SGCB, C4orf3, MALAT1, PILRB, IGHG1, FZD1, IFITM1, MUC20, KRT80, and SALL1) were filtered out using the random forest model. The model of Riskscore was obtained by multiplying the expression levels of these 12 genes with the corresponding coefficients of the multivariate regression. We found that the Riskscore correlated with the expression of these 12 genes; the high Riskscore matched the low survival rate verified in the verification set. The analysis found that the Riskscore model was associated with most of the metabolic processes, immune infiltration of cells such as plasma cells, immune checkpoints such as PD-1, and clinical characteristics such as M stage.

Conclusion

We established a new Riskscore model for the prognosis of ccRCC based on metabolism. The genes in the model provided several novel targets for the study of ccRCC.

hnRNP A/B Proteins: An Encyclopedic Assessment of Their Roles in Homeostasis and Disease

The hnRNP A/B family of proteins is canonically central to cellular RNA metabolism, but due to their highly conserved nature, the functional differences between hnRNP A1, A2/B1, A0, and A3 are often overlooked. In this review, we explore and identify the shared and disparate homeostatic and disease-related functions of the hnRNP A/B family proteins, highlighting areas where the proteins have not been clearly differentiated. Herein, we provide a comprehensive assembly of the literature on these proteins. We find that there are critical gaps in our grasp of A/B proteins' alternative splice isoforms, structures, regulation, and tissue and cell-type-specific functions, and propose that future mechanistic research integrating multiple A/B proteins will significantly improve our understanding of how this essential protein family contributes to cell homeostasis and disease.