The Analyzation Of Tne Correlation Between Genomic Instability Related LncRNA And The Clinical Outcome Of AML Based On Online Databases

Objective: Genomic instability is a widely described mechanism of leukemia,and it also plays a role in the transformation of other blood diseases to leukemia.In this study,the lncRNA associated with genomic instability was screened from the acute myeloid leukemia data set of TCGA database,and a prognostic model was established to predict the prognosis of patients with acute myeloid leukemia by using these lncRNA.Methods: 1.The clinical characteristics,RNA-seq expression data and gene mutation information datasets of AML patients were downloaded by online database TCGA.2.Based on the hypothesis of gene mutation,a computational framework was designed to screen the lncRNA related to genomic instability.3.The selected lncRNA was analyzed by GO functional enrichment analysis and KEGG pathway enrichment analysis to predict whether its function was related to genomic instability.4.The prognostic model was constructed by factor regression analysis,and the model was evaluated and tested by Kaplan-Meier method,log-rank test,ROC curve and so on.Results: 1.The clinical characteristics,gene mutation data and RNA expression profile of patients with acute myeloid leukemia were obtained from TCGA database.The gene name of the expression data was annotated,and a new file was obtained by combining with clinical information data.two。.Based on the hypothesis of gene mutation,the patients were divided into genomic stable group and genomic instability group,and 59 differentially expressed lncRNA were screened between the two groups.3.Functional enrichment analysis was performed to predict whether the potential functions and pathways involved in 59 lncRNA were related to genomic instability.4.AML patients from TCGA data sets were divided into training set and test group.The relationship between the expression level of 59 genomic instability-related lncRNA and the survival time of training set was analyzed by univariate Cox risk regression.It was found that 7lncRNA related to genomic instability were significantly related to the prognosis of AML patients.The common clinical characteristics of the 7 candidate lncRNA,such as sex and age,were analyzed by multivariate Cox risk regression analysis.Four of them still had prognostic significance in multivariate Cox analysis,and the best predictive effect could be identified as independent prognostic predictor lncRNA(AL031005.1,AC004381.1,AL512413.1 and LINC01436).Then,according to the coefficient of multivariate Cox analysis and the expression level of 4 independent prognosis-related lncRNA,a genomic instability-related lncRNA model(GILnc Sig)was constructed to evaluate the prognostic risk of AML patients.5.Kaplan-Meier analysis showed that the survival outcome of the low-risk group was significantly better than that of the high-risk group.The ROC curve analysis of GILnc Sig shows that the model has good performance.Conclusion: In this study,a computational framework based on gene mutation hypothesis was used to screen lncRNA,related to genomic instability,and a prognostic model of AML patients was established by combining lncRNA expression profile with AML gene mutation profile and clinical information.It provides an idea for more accurate prognosis of AML patients and further exploration of genomic instability and the pathogenesis of AML.