Zhongyu Qu

Background: This study assessed the adverse drug reactions (ADRs) associated with HDAC inhibitors using the VigiAccess database maintained by the World Health Organization (WHO). Furthermore, it compared the ADR profiles of three different drugs to identify the one with the lowest individualized risk for patients.Materials and methods: Data on adverse events of HDAC Inhibitors was retrieved from WHO-VigiAccess on 6 January 2025. We obtained data on age, gender, reporting year, and continent. Descriptive data related were calculated using Excel 2021. In this study, we used Excel software to analyze the characteristics of those who were harmed due to adverse reactions. For each drug, the reporting rate of adverse reactions was calculated by dividing the number of adverse reaction symptoms of this drug by the total number of adverse reaction reports. We listed the top 20 most frequent adverse reaction symptoms as common adverse reactions. By counting the frequency and proportion of these common adverse reactions, we conducted a comparative analysis of the adverse reaction situations of different drugs and classified them according to different types.Result: The WHO-VigiAccess database received 796, 1254, and 1658 ADR reports for Chidamide, Romidepsin, and Vorinostat respectively by 2024, with a total of 3,708. Gender distribution was relatively balanced (male:female ratio 0.81:1), and the 45–64 age group had the highest reporting rates, mostly from the Americas. Chidamide had higher rates in certain disorders, Romidepsin in others, and Vorinostat in specific ones. Common ADRs included thrombocytopenia etc., with some differences in rates among drugs. Serious ADR proportions were 0% for Chidamide, 2.27% for Romidepsin, and 1.02% for Vorinostat. 37 common signals were found, with Investigations having the most. Each drug had different ADR preferred terms (PTs) in renal/urinary and metabolism/nutrition disorders, with varying numbers of distinctive symptoms.Conclusion: Current comparative observational studies of these inhibitors indicate that there are both common and specific adverse reactions reported in the ADR data received by the WHO for these medications. Clinicians should enhance the rational use of these drugs by considering the characteristics of the reported ADRs.

Head and neck squamous cell carcinoma (HNSCC) ranks second among men and sixth globally, with a notable increase in HPV‐associated cases. However, the molecular underpinnings and immune landscape of HPV+ HNSCC remain incompletely understood. In this study, we first retrieved and harmonized single‐cell RNA sequencing (RNA‐Seq), bulk RNA‐Seq, and spatial transcriptomic profiles from public repositories. We then applied high‐dimensional weighted gene coexpression network analysis (hdWGCNA) and gene nonnegative matrix factorization (GeneNMF) to dissect HPV+ epithelial subpopulations, their extracellular matrix (ECM)–interacting ligand programs, and CXCL/complement immune circuits. Furthermore, we mapped the spatial niches of malignant and immune cells and constructed a consensus prognostic index using 101 machine learning algorithms. Our findings revealed transcriptionally distinct HPV+ epithelial clusters that activate viral oncogenesis, inflammatory pathways, and ECM‐sensing pathways. These cells communicate with stromal and immune compartments via CXCL axes and complement cascades, yet they are spatially segregated from lymphocytes. A high‐risk signature, identified as HPV‐related risk genes including TRMT112, stratified the TCGA‐HNSC and GSE65858 cohorts into patients with markedly worse 1‐, 2‐, and 3‐year survival rates (ROC–AUC 0.934, 0.968, and 0.973) and poor responses to immunotherapy. Notably, TRMT112 expression inversely correlated with cytotoxic T‐cell infiltration, mechanistically linking it to the formation of “cold” tumors. Our integrative analysis defines HPV‐driven epithelial subpopulations whose TRMT112‐enriched, immune‐excluded microenvironment contributes to therapeutic resistance, thus providing robust prognostic biomarkers and actionable targets for precision immunotherapy in HPV+ HNSCC.

Background: It is now understood that APOBEC3 family proteins (A3s) are essential in tumor progression, yet their involvement in tumor immunity and stemness across diverse cancer types remains poorly understood.Methods: In the present study, comprehensive genome-wide statistical and bioinformatic analyses were conducted to elucidate A3 family expression patterns, establishing clinically relevant correlations with prognosis, the tumor microenvironment(TME), immune infiltration, checkpoint blockade, and stemness across cancers. Different experimental techniques were applied, including RT–qPCR, immunohistochemistry, sphere formation assays, Transwell migration assays, and wound-healing assays, to investigate the impact of A3C on low-grade glioma (LGG) and glioblastoma multiforme (GBM), as well as its function in glioma stem cells(GSCs).Results: Dysregulated expression of A3s was observed in various human cancer tissues. The prognostic value of A3 expression differed across cancer types, with a link to particularly unfavorable outcomes in gliomas. A3s are associated with the the TME and stemness in multiple cancers. Additionally, we developed an independent prognostic model based on A3s expression, which may be an independent prognostic factor for OS in patients with glioma. Subsequent validation underscored a strong association between elevated A3C expression and adverse prognostic outcomes, higher tumor grades, and unfavorable histology in glioma. A potential connection between A3C and glioma progression was established. Notably, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses implicated A3C in immune system-related diseases, with heightened A3C levels contributing to an immunosuppressive tumor microenvironment (TME) in glioma. Furthermore, in vitro experiments substantiated the role of A3C in sustaining and renewing glioma stem cells, as A3C deletion led to diminished proliferation, invasion, and migration of glioma cells.Conclusion: The A3 family exhibits heterogeneous expression across various cancer types, with its expression profile serving as a predictive marker for overall survival in glioma patients. A3C emerges as a regulator of glioma progression, exerting its influence through modulation of the tumor microenvironment and regulation of stemness.