Jianming Wei

Neutrophils expelling neutrophil extracellular traps (NETs) during the process of NETosis play a critical role in tumor development. In this study, we aimed to identify a prognostic NETosis-related gene signature that could predict the immunetherapy response and explore the expression of these genes in hepatocellular carcinoma (HCC). Differentially expressed NETosis-related genes were identified from the GSE80489 dataset in the Gene Expression Omnibus (GEO), and a protein–protein interaction (PPI) network was constructed using Cytoscape and the STRING database. Gene Ontology (GO) enrichment analysis revealed associations with chemical stimuli and the positive regulation of cellular processes in HCC. A total of 37 differentially expressed NETosis-related genes were identified, and SNORA31, PMAIP1, GLA, CXCL1, and ADM were selected to construct a prognostic signature. In the training cohort, the low-risk group demonstrated significantly better overall survival (OS) compared to the high-risk group (P = 2.715e−06), and multivariable analysis confirmed that this signature was an independent prognostic factor for HCC (HR = 1.630, 95% CI = 1.295–2.052, P < 0.001). This signature also significantly predicted OS in validation cohorts (P = 9.704e−03) and was associated with HCC patients' OS according to the Kaplan–Meier Plotter. Moreover, it could predict the immunotherapy response in HCC patients. Finally, we investigated the expression of NETosis-related genes in single-cell subtypes and in the HepG2 cell line, providing further insights into their relevance in HCC. Overall, this NETosis-related gene signature serves as a prognostic indicator and a potential predictor for immunotherapy response in HCC.

Background CST1 , acting as an oncogene, plays a critical role in tumor microenvironment (TME) remodeling. However, the function of CST1 in gastric cancer (GC) remains elusive. The purpose of this study was to explore the prognostic significance, tumor immune cell infiltration and biological functions of CST1 as a novel therapeutic candidate biomarker for GC.Methods Differentially expressed genes (DEGs) were identified using the library (“limma”) package of R software. Gene Set Enrichment Analysis (GSEA) was applied to explore the molecular function of CST1 . CST1 expression in GC cell lines was detected using quantitative real-time PCR (RT-qPCR) in vitro. Cell proliferation, migration, and invasion were measured using the cell counting kit-8 assay and Transwell assay.Results A total of 142 common DEGs were screened out in four datasets. Four overlapped DEGs ( CST1 , CLDN4 , CLDN7 and CLDN1 ) were identified and validated in TCGA database. CST1 was the most significant to be selected for further study. Bioinformatics analysis revealed that CST1 expression was associated with in tumor immune cell infiltration and clinical factors in GC. The survival analysis showed that CST1 overexpression predicted poor outcome in GC patients. In Cancer Cell Line Encyclopedia (CCLE) database, the expression of SULT1C4 , PAGE4 and FPR3 was significant positively related to CST1 . CST1 was also upregulated in GC cells AGS by qRT-PCR. Finally, we found that CST1 promoted cell proliferation, invasion, and migration in GC.Conclusion This study reveals that CST1 is a promising candidate biomarker for prognosis and potential therapy target for GC.