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Evidence suggests that abnormal DNA methylation patterns play a crucial role in the etiology and pathogenesis of colon adenocarcinoma (COAD). In this study, we identified a total of 97 methylation-driven genes (MDGs) through a comprehensive analysis of the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Univariate Cox regression analysis identified four MDGs (CBLN2, RBM47, SLCO4C1, and TMEM220) associated with overall survival (OS) in COAD patients. A risk prediction model was then developed based on these four MDGs to predict the prognosis of COAD patients. We also created a nomogram that incorporated risk scores, age, and TNM stage to promote a personalized prediction of OS in COAD patients. Compared with the traditional TNM staging system, our new nomogram was better at predicting the OS of COAD patients. In cell experiments, we confirmed that the mRNA expression levels of CLBN2 and TMEM220 were regulated by the methylation of their promoter regions. Moreover, immunohistochemistry showed that CBLN2 and TMEM220 were potential prognostic biomarkers for COAD patients. In summary, we have established a risk prediction model and nomogram that might be effectively utilized to promote the prediction of OS in COAD patients.

Hepatocellular carcinoma (HCC) is the most common fatal cancer worldwide, patients with HCC have a high mortality rate and poor prognosis. PANoptosis is a novel discovery of programmed cell death associated with cancer development. However, the role of PANoptosis in HCC remains obscure. In this study, we enrolled 274 PANoptosis-related genes (PANRGs) and screened 8 genes to set up a prognostic model. A previous scoring system calculated PANscore was utilized to quantify the individual risk level of each HCC patient, and the reliability of the prognostic model has been validated in an external cohort. Nomogram constructed with PANscore and clinical characteristics were used to optimize individualized treatment for each patient. Single-cell analysis revealed a PANoptosis model associated with tumor immune cell infiltration, particularly natural killer (NK) cells. Further exploration of hub genes and assessment of the prognostic role of these 4 hub genes in HCC by quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC). In conclusion, we evaluated a PANoptosis-based prognostic model as a potential prognostic biomarker for HCC patients.

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Introduction: Coronary artery disease (CAD) is one of the most life-threatening cardiovascular emergencies with high mortality and morbidity. Increasing evidence has demonstrated that the degree of hypoxia is closely associated with the development and survival outcomes of CAD patients. However, the role of hypoxia in CAD has not been elucidated.Methods: Based on the GSE113079 microarray dataset and the hypoxia-associated gene collection, differential analysis, machine learning, and validation of the screened hub genes were carried out.Results: In this study, 54 differentially expressed hypoxia-related genes (DE-HRGs), and then 4 hub signature genes (ADM, PPFIA4, FAM162A, and TPBG) were identified based on microarray datasets GSE113079 which including of 93 CAD patients and 48 healthy controls and hypoxia-related gene set. Then, 4 hub genes were also validated in other three CAD related microarray datasets. Through GO and KEGG pathway enrichment analyses, we found three upregulated hub genes (ADM, PPFIA4, TPBG) were strongly correlated with differentially expressed metabolic genes and all the 4 hub genes were mainly enriched in many immune-related biological processes and pathways in CAD. Additionally, 10 immune cell types were found significantly different between the CAD and control groups, especially CD8 T cells, which were apparently essential in cardiovascular disease by immune cell infiltration analysis. Furthermore, we compared the expression of 4 hub genes in 15 cell subtypes in CAD coronary lesions and found that ADM, FAM162A and TPBG were all expressed at higher levels in endothelial cells by single-cell sequencing analysis.Discussion: The study identified four hypoxia genes associated with coronary heart disease. The findings provide more insights into the hypoxia landscape and, potentially, the therapeutic targets of CAD.