Bioinformatics Analysis Of Acute Myeloid Leukaemia Patients On The Basis Of Cell Senescence Genes

Objective:Acute myeloid leukemia(AML)is a blood malignancy that is aggressive and characterized by the clonal proliferation of hemopoietic progenitor cells.The overall prognosis of AML remains unsatisfactory with a 5-year survival rate of less than 40%,despite recent improvements in risk classification,combination chemotherapy,and haematopoietic stem cell transplantation.Recent research has demonstrated that cellular senescence can be interfered with to impact the overall survival(OS)of AML mice.Senescence has been shown to increase the occurrence of haematological malignancies,including AML,through a variety of pathways.Unfortunately,little progress has been made in figuring out how senescence genes(Sn Gs)work in AML and how they are used clinically.Methods:Transcriptome data,somatic mutation data,and clinical information of the samples were downloaded from the Cancer Genome Atlas(TCGA)as a training set,and then normal transcriptome data were retrieved from the Genotype-Tissue Expression(GTEx)database.To identify TCGA cohort subtypes,the k-means clustering technique was used to analyze differentially expressed senescence genes(DESn Gs).These DESn Gs were then subjected to univariate regression analysis.To find the signature genes of cellular senescence in AML and build prognostic models,further Cox regression analysis was carried out using the Support Vector Machine(SVM)algorithm and the Least Absolute Shrinkage and Selection Operator(LASSO).The predictive effect on OS was investigated using KM survival analysis,ROC curve,univariate and multivariate Cox regression analysis,and subgroup analysis.The findings were confirmed in the GSE37642-96 cohort.We also used GSEA enrichment to analyze the probable biological roles of the gene signatures associated with cellular senescence,and the CIBERSORT method to compare immune cell infiltration between clustered subgroups and high-and low-risk groups.The maftools function was used to analyse the difference in somatic mutations between high and low risk groups in the TCGA cohort.Finally,we performed risk score and correlation analysis between signature genes and immune cells.Results:The TCGA cohort could be split into two subtypes using the K-means method based on 74 DESn Gs,and the OS and immune cell infiltration of the two subtypes varied.Twenty DESn Gs were substantially linked with OS according to a univariate Cox regression study of 74 DESn Gs.Six signature genes(HAUS7,ATP6V0 C,SOX4,CCNJ,NEMP1 and QSER1)were discovered by SVM analysis.By using LASSO Cox regression analysis,a prognostic model made up of 11 Sn Gs(MX1,OPTN,CPQ,HAUS7,C3orf14,PAGR1,ECHDC3,SOX4,TOP2 A,MIS18BP1 and QSER1)with strong predictive power was developed.The TCGA cohort was split into high-risk and low-risk groups based on the risk score.When compared to patients in the low-risk group,the OS of patients in the high-risk group was considerably lower.This signature was approved by the external validation set GSE37642 and can be used as an independent prognostic predictor after adjusting for clinicopathological characteristics.Age was also a reliable predictive predictor,according to both univariate and multivariate Cox analyses of clinical features.In a similar way,we also analysed the clinical characteristics of the two sets of data and combined the risk scores to create a nomogram.The GSEA enrichment analysis revealed that the majority of the genes implicated in cell senescence were engaged in the cell cycle.Immune cell infiltration disparities among AML patients were linked to variations in overall survival,according to analysis of tumor-infiltrating immune cells.Somatic mutation analysis revealed a connection between the kind of altered genes and the variation in OS among AML patients.Conclusions:1.HAUS7,SOX4 and QSER1 may be potential prognostic biomarkers for AML patients.2.The nomogram and prognostic model based on the combination of cellular senescence characteristic genes and age have good predictive ability.3.Major biological functions,immune cell infiltration and somatic cell mutation are the reasons for the different prognosis of AML patients.