壞死基因相關預印版文章，預印版只供參考
第一篇：https://www.researchsquare.com/article/rs-1060995/v1
第二篇：https://www.researchsquare.com/article/rs-970714/v1
Validation and Application of Prognostic Signature Based on Necroptosis-related Genes in Patients With Thyroid Carcinoma
Abstract
Objective
To explore the relationship between thyroid carcinoma (TC) and necroptosis, and to construct a related prognostic signature to assist in diagnosis and treatment.
Methods and Results
A total of 159 necroptosis-related genes (NRGs) were screened for in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database; 38 differentially expressed NRGs (DENGs) of TC were identified from The Cancer Genome Atlas/Genomic Data Commons database (TCGA/GDC); and GO, KEGG, and GSEA enrichment analysis showed that they were mostly related to cell necrosis, autophagy, P53, and other signaling pathways. Univariate and multivariate Cox regression and Lasso regression were used to screen for DENGs associated with prognosis, and a prognostic signature about?BID, H2AC12, STAT1, IFNA21, IL1A?was established. The patients were then divided into high-risk and low-risk groups according to the median value of the prognostic signature, and their overall survival (OS) was analyzed via the Kaplan-Meier method. The predictive accuracy was also determined using receiver operating characteristic (ROC) curve analysis. Additionally, we performed stratification analyses based on different clinical variables and evaluated the correlations between risk score and clinical variables. The independent prognostic value of the signature was further confirmed by multivariate Cox regression analysis, and decision curve analysis (DCA) was employed to evaluate the quality of the prognostic model and its clinical utility.
Conclusion
We successfully constructed a novel necroptosis-related signature for the prediction of prognosis in patients with TC.
KEYWORDS
necroptosis, thyroid carcinoma, risk score, The Cancer Genome Atlas, nomogram, prognostic biomarker
Kidney Renal Clear Cell Carcinoma: Development and Validation of Prognostic Index of Necroptosis-Related Genes
Abstract
Background:?Renal carcinoma is a frequent kind of malignant tumour of the urinary system, and its prevalence is increasing.
Methods:?The predictive significance of Necroptosis-related genes (NRGs) in 539 Kidney renal clear cell carcinoma (KIRC) samples from The Cancer Genome Atlas (TCGA) datasets was investigated. We wanted to show how NRGs interact with immunological checkpoints and m6A in KIRC. In the Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis was employed to study gene expression enrichment. Lasso regression was used to build the predictive model. According to a co-expression study, gene expression is directly related to necroptosis. In the absence of additional clinical signs, NRGs was shown to be partly overexpressed in high-risk individuals, indicating that they might be used in a model to predict KIRC prognosis. GSEA identified immunological and tumour-related pathways in the high-risk group.
Results:?According to TCGA, immune checkpoint and m6A genes differ considerably between the low-risk and high-risk groups. PLA2G4D, H2AC17, H2AC7, IRF9, and other genes varied between the two risk groups. NRGs are linked to the onset and development of KIRC.
Conclusions:??Using matching predictive models, the prognosis of KIRC patients may be predicted. NRGs and the association of immunological checkpoints and m6A with NRGs in KIRC may represent potential therapeutic targets that should be investigated further.
