The prognostic value and immune correlation of IL18 expression and promoter methylation in renal cell carcinoma

Multi-cohort validation: A comprehensive exploration of prognostic marker in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common form of RCC. It is characterized by resistance to traditional radiotherapy and chemotherapy, as well as an unfavorable clinical prognosis. Although TYMP is implicated in the advancement of tumor progression, the role of TYMP in ccRCC is still not understood. Heightened TYMP expression was identified in ccRCC through database mining and confirmed in RCC cell lines. Indeed, TYMP knockdown impacted RCC cell proliferation, migration, and invasion in vitro. TYMP showed a positive correlation with clinicopathological parameters (histological grade, pathological stage). Moreover, patients with high TYMP expression were indicative of poor prognosis in TCGA-ccRCC and external cohorts. The results of single-cell analysis showed that the distribution of TYMP was predominantly observed in monocytes and macrophages. Furthermore, there is a significant association between TYMP and immune status. Methylation analysis further elucidated the relationship between TYMP expression and multiple methylation sites. Drug sensitivity analysis unveiled potential pharmaceutical options. Additionally, mutation analyses identified an association between TYMP and the ccRCC driver genes like BAP1 and ROS1. In summary, TYMP may serve as a reliable prognostic indicator for ccRCC.

Identification and analysis of chemokine-related and NETosis-related genes in acute pancreatitis to develop a predictive model

Background: Chemokines and NETosis are significant contributors to the inflammatory response, yet there still needs to be a more comprehensive understanding regarding the specific molecular characteristics and interactions of NETosis and chemokines in the context of acute pancreatitis (AP) and severe AP (SAP). Methods: To address this gap, the mRNA expression profile dataset GSE194331 was utilized for analysis, comprising 87 AP samples (77 non-SAP and 10 SAP) and 32 healthy control samples. Enrichment analyses were conducted for differentially expressed chemokine-related genes (DECRGs) and NETosis-related genes (DENRGs). Three machine-learning algorithms were used for the identification of signature genes, which were subsequently utilized in the development and validation of nomogram diagnostic models for the prediction of AP and SAP. Furthermore, single-gene Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were performed. Lastly, an interaction network for the identified signature genes was constructed. Results: We identified 12 DECRGs and 7 DENRGs, and enrichment analyses indicated they were primarily enriched in cytokine-cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and T cell receptor signaling pathway. Moreover, these machine learning algorithms finally recognized three signature genes (S100A8, AIF1, and IL18). Utilizing the identified signature genes, we developed nomogram models with high predictive accuracy for AP and differentiation of SAP from non-SAP, as demonstrated by area under the curve (AUC) values of 0.968 (95% CI 0.937-0.990) and 0.862 (95% CI 0.742-0.955), respectively, in receiver operating characteristic (ROC) curve analysis. Subsequent single-gene GESA and GSVA indicated a significant positive correlation between these signature genes and the proteasome complex. At the same time, a negative association was observed with the Th1 and Th2 cell differentiation signaling pathways. Conclusion: We have identified three genes (S100A8, AIF1, and IL18) related to chemokines and NETosis, and have developed accurate diagnostic models that might provide a novel method for diagnosing AP and differentiating between severe and non-severe cases.

Nucleic acid and protein methylation modification in renal diseases

Although great efforts have been made to elucidate the pathological mechanisms of renal diseases and potential prevention and treatment targets that would allow us to retard kidney disease progression, we still lack specific and effective management methods. Epigenetic mechanisms are able to alter gene expression without requiring DNA mutations. Accumulating evidence suggests the critical roles of epigenetic events and processes in a variety of renal diseases, involving functionally relevant alterations in DNA methylation, histone methylation, RNA methylation, and expression of various non-coding RNAs. In this review, we highlight recent advances in the impact of methylation events (especially RNA m6A methylation, DNA methylation, and histone methylation) on renal disease progression, and their impact on treatments of renal diseases. We believe that a better understanding of methylation modification changes in kidneys may contribute to the development of novel strategies for the prevention and management of renal diseases.

The Role of IL-18 in P2RX7-Mediated Antitumor Immunity

Cancer is the leading cause of death worldwide despite the variety of treatments that are currently used. This is due to an innate or acquired resistance to therapy that encourages the discovery of novel therapeutic strategies to overcome the resistance. This review will focus on the role of the purinergic receptor P2RX7 in the control of tumor growth, through its ability to modulate antitumor immunity by releasing IL-18. In particular, we describe how the ATP-induced receptor activities (cationic exchange, large pore opening and NLRP3 inflammasome activation) modulate immune cell functions. Furthermore, we recapitulate our current knowledge of the production of IL-18 downstream of P2RX7 activation and how IL-18 controls the fate of tumor growth. Finally, the potential of targeting the P2RX7/IL-18 pathway in combination with classical immunotherapies to fight cancer is discussed.