The AC006262.5-miR-7855-5p-BPY2C axis facilitates hepatocellular carcinoma proliferation and migration

A pyroptosis-related lncRNA risk model for the prediction of prognosis and immunotherapy response in head and neck squamous cell carcinoma

Background

Recent research has highlighted pyroptosis as a key factor in cancer progression. This study aims to explore the association between pyroptosis-related signatures and overall survival (OS) in head and neck squamous cell carcinoma (HNSC) and develop a pyroptosis-related long non-coding RNA (lncRNA) risk model to predict prognosis and response to immunotherapy in HNSC.

Methods

We extracted expression data for 18 pyroptosis-related genes and identified lncRNA probes specific to HNSC by using datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Consensus clustering was performed to categorize HNSC patients into distinct subtypes. A six-lncRNA risk score model was constructed through univariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses. We evaluated the predictive ability of the lncRNA model for patients' survival and immunotherapy response. Gene expression was evaluated using immunohistochemistry (IHC) and Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR).

Results

Our analysis revealed two distinct pyroptosis-related subtypes in HNSC patients, Cluster A and Cluster B. Notably, patients in Cluster B exhibited significantly poorer overall survival compared to those in Cluster A. Through differential expression analysis, we identified six lncRNAs (AC002331.1, CTA-384D8.35, RP11-291B21.2, AC006262.5, RP1-27K12.2, and RP11-54H7.4) that were differentially expressed between these clusters. A 6-lncRNA risk score model was developed, which successfully stratified patients into high- and low-risk groups with distinct overall survival outcomes. Validation using RT-qPCR confirmed the differential expression of these six lncRNAs in HNSC tumor tissues compared to adjacent normal tissues, we found that the expression of CTA-384D8.35 was significantly increased in the tumor group (t=-6.203, P<0.001). Furthermore, the 6-lncRNA risk score model demonstrated a significant association with patient response to immunotherapy, with the low-risk group exhibiting a higher objective response rate to immune checkpoint blockade (ICB) therapy and longer survival compared to the high-risk group.

Conclusion

Our study underscores the role of pyroptosis signatures in HNSC prognosis and identifies two distinct pyroptosis subtypes with differing survival outcomes. The six-lncRNA risk score model offers a valuable tool for predicting patient prognosis and potential benefits from ICB therapy. These findings highlight the importance of pyroptosis and associated lncRNAs in the tumor microenvironment, paving the way for novel targeted therapies in HNSC.

Inflammation and Oxidative Stress Role of S100A12 as a Potential Diagnostic and Therapeutic Biomarker in Acute Myocardial Infarction

Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases with high morbidity and mortality. Numerous studies have indicated that S100A12 may has an essential role in the occurrence and development of AMI, and in-depth studies are currently lacking. The purpose of this study is to investigate the effect of S100A12 on inflammation and oxidative stress and to determine its clinical applicability in AMI. Here, AMI datasets used to explore the expression pattern of S100A12 in AMI were derived from the Gene Expression Omnibus (GEO) database. The pooled standard average deviation (SMD) was calculated to further determine S100A12 expression. The overlapping differentially expressed genes (DEGs) contained in all included datasets were recognized by the GEO2R tool. Then, functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, were carried out to determine the molecular function of overlapping DEGs. Gene set enrichment analysis (GSEA) was conducted to determine unrevealed mechanisms of S100A12. Summary receiver operating characteristic (SROC) curve analysis and receiver operating characteristic (ROC) curve analysis were carried out to identify the diagnostic capabilities of S100A12. Moreover, we screened miRNAs targeting S100A12 using three online databases (miRWalk, TargetScan, and miRDB). In addition, by comprehensively using enzyme-linked immunosorbent assay (ELISA), real-time quantitative PCR (RT-qPCR), Western blotting (WB) methods, etc., we used the AC16 cells to validate the expression and underlying mechanism of S100A12. In our study, five datasets related to AMI, GSE24519, GSE60993, GSE66360, GSE97320, and GSE48060 were included; 412 overlapping DEGs were identified. Protein-protein interaction (PPI) network and functional analyses showed that S100A12 was a pivotal gene related to inflammation and oxidative stress. Then, S100A12 overexpression was identified based on the included datasets. The pooled standard average deviation (SMD) also showed that S100A12 was upregulated in AMI (SMD = 1.36, 95% CI: 0.70-2.03, p = 0.024). The SROC curve analysis result suggested that S100A12 had remarkable diagnostic ability in AMI (AUC = 0.90, 95% CI: 0.87-0.92). And nine miRNAs targeting S100A12 were also identified. Additionally, the overexpression of S100A12 was further confirmed that it maybe promote inflammation and oxidative stress in AMI through comprehensive in vitro experiments. In summary, our study suggests that overexpressed S100A12 may be a latent diagnostic biomarker and therapeutic target of AMI that induces excessive inflammation and oxidative stress. Nine miRNAs targeting S100A12 may play a crucial role in AMI, but further studies are still needed. Our work provides a positive inspiration for the in-depth study of S100A12 in AMI.

Hepigenetics: A Review of Epigenetic Modulators and Potential Therapies in Hepatocellular Carcinoma

Hepatocellular carcinoma is the fifth most common cancer worldwide and the second most lethal, following lung cancer. Currently applied therapeutic practices rely on surgical resection, chemotherapy and radiotherapy, or a combination thereof. These treatment options are associated with extreme adversities, and risk/benefit ratios do not always work in patients' favor. Anomalies of the epigenome lie at the epicenter of aberrant molecular mechanisms by which the disease develops and progresses. Modulation of these anomalous events poses a promising prospect for alternative treatment options, with an abundance of felicitous results reported in recent years. Herein, the most recent epigenetic modulators in hepatocellular carcinoma are recapitulated on.