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Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, it has a poor prognosis due to its highly invasive and metastatic nature. Consequently, identifying effective prognostic markers and potential therapeutic targets has been extensively investigated. METTL5, an 18S rRNA methyltransferase, is abnormally high in HCC. But its biological function and prognostic significance in HCC remain largely unelucidated. This study aimed to investigate the role of METTL5 in HCC progression, and elucidate its possible molecular mechanisms in HCC via transcriptome sequencing, providing new insights for identifying new HCC prognostic markers and therapeutic targets. Methods: The METTL5 expression in HCC and paracancerous tissues was analyzed using HCC immunohistochemical microarrays and bioinformatic retrieval methods to correlate METTL5 with clinicopathological features and survival prognosis. We constructed a METTL5 knockdown hepatocellular carcinoma cell line model and an animal model to determine the effect of METTL5 on hepatocellular carcinoma progression. Subsequently, RNA sequencing was performed to analyze the molecular mechanism of METTL5 in HCC based on the sequencing results, and relevant experiments were performed to verify it. Results: We found that METTL5 expression was elevated in hepatocellular carcinoma tissues and correlated with poor patient prognosis, and in the analysis of clinicopathological features showed a correlation with TNM staging. In hepatocellular carcinoma cell lines with knockdown of METTL5, the malignant biological behavior was significantly reduced both in vitro and in vivo. Based on the sequencing results as well as the results of GO functional enrichment analysis and KEGG pathway enrichment analysis, we found that METTL5 could promote the generation and release of neutrophil extracellular capture network (NETs) and might further accelerate the progression of HCC. Conclusion: The m6A methyltransferase METTL5 is overexpressed in hepatocellular carcinoma (HCC) and correlates with poor prognosis. METTL5 accelerates malignant progression of HCC by promoting generation and release of the neutrophil extracellular traps (NETs) network, providing new insights for clinical biomarkers and immunotherapeutic targets in HCC prognosis. [ABSTRACT FROM AUTHOR]

AbstractHepatocellular carcinoma (HCC), as a malignancy derived from liver tissue, is typically associated with poor prognosis. Increasing evidence suggests a connection between pyrimidine metabolism and HCC progression. The purpose of this study was to establish a model applied to the prediction of HCC patients’ overall survival. Transcriptomic data of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) website. Pyrimidine metabolism-related genes (PMRGs) were collected from the Gene Set Enrichment Analysis (GSEA) website. Differential gene expression analysis was carried out on the HCC data, followed by an intersection of the differentially expressed genes (DEGs) and PMRGs. Subsequently, a prognostic model incorporating nine genes was established using univariate/multivariate Cox regression and Least absolute shrinkage and selection operator (LASSO) regression. Survival analysis demonstrated that the high-risk group defined by this model had considerably shorter overall survival than the low-risk group in both TCGA and Gene Expression Omnibus (GEO) datasets. Receiver operating characteristic (ROC) analysis indicated the good predictive capability of the model. CIBERSORT and single sample gene set enrichment analysis (ssGSEA) algorithms revealed significantly higher levels of Macrophages M0 and lower levels of natural killer (NK)_cells in the high-risk group compared to the low-risk group. The immunophenoscore (IPS) and the tumor immune dysfunction and exclusion (TIDE) score demonstrated that the model could significantly differentiate patients who would be more suitable for immunotherapy. Moreover, the CellMiner database was utilized to predict anti-tumor drugs significantly associated with the model genes. Collectively, the potential prognostic significance of pyrimidine metabolism in HCC was revealed in this study. The prognostic model aids in evaluating the survival time and immune status of HCC patients. [ABSTRACT FROM AUTHOR]

• NEK2 expression was upregulated in GC and was a predictor of a poor prognosis. • Multiple tumor pathways were hyperactivated in patients with high NEK2 expression. • NEK2 expression was negatively correlated with immune cell infiltration. • Patients with high NEK2 responded to drugs targeting cell cycle/DNA replication. • NEK2-derived genomic model and nomogram can better estimate survival probability. Gastric cancer (GC) is the most common form of gastrointestinal cancer, with a high mortality rate and limited treatment options. High levels of NEK2 are associated with malignant progression and a poor prognosis in several tumors; however, the role of NEK2 in GC remains unclear. We aimed to explore the potential role of NEK2 in the oncogenesis of GC and in the shaping of the tumor microenvironment (TME). The expression levels of NEK2 were analyzed using immunohistochemistry and real-time quantitative polymerase chain reaction. We found that NEK2 expression was upregulated in GC and was a predictor of a poor prognosis. Based on Kyoto Encyclopedia of Genes and Genomes pathway enrichment and gene set enrichment analyses, multiple tumor pathways were hyperactivated in patients with high NEK2 mRNA expression. Immunological characteristics indicated that NEK2 upregulation might lead to decreased immune cell infiltration and weakened immune activity in the cancer immunity cycle. Additionally, higher frequencies of amplifications and deletions were observed in the high NEK2 expression subpopulation. Based on the TME classification, patients with high expression of NEK2 were more susceptible to targeted therapy with drugs targeting the cell cycle and DNA replication. Following verification, a NEK2-derived genomic model reliably predicted the patient prognosis; A nomogram (radiation therapy, tumor/node/metastasis staging, and the NEK2-derived risk score) was used to better estimate an individual's survival probability. In summary, our findings indicate that NEK2 plays a vital role in the tumorigenesis of GC. [ABSTRACT FROM AUTHOR]