Cytolytic Immunoregulatory Factor TIM3 Affects Nomogram Model And Prognostic Risk Assessment For Patients With Lung Adenocarcinoma By Multi-omics Analysis

[Background and Objective] Lung cancer is one of the malignant tumors with high morbidity and mortality in the world today.In pathological classification,lung adenocarcinoma has replaced the original lung squamous cell carcinoma and become the main pathological type of lung cancer.With the deepening of the research on the pathological characteristics and molecular mechanism of lung adenocarcinoma,the clinical diagnosis and treatment plan is constantly updated,but there is still a lack of specific biomarkers and targets of great value for the analysis of survival prognosis and drug sensitivity of lung adenocarcinoma.However,its biological characteristics and prognostic value in lung adenocarcinoma remain unclear.Therefore,based on bioinformatics technology,this study adopted multi-omics research methods to analyze the influence of cytolytic activity related gene TIM3 on survival prognosis and drug resistance risk assessment of lung adenocarcinoma.[Materials and Methods] In this study,clinical group data and transcriptome data related to survival prognosis of lung adenocarcinoma were downloaded from the TCGA database,GEO database and Gene Cards database,and data related to drug sensitivity of GDSC,the world’s largest pharmacogenomics database,were further integrated.We combined Cox single factor regression and lasso regression feature selection algorithm to screen out the key genes of cytolytic activity in lung adenocarcinoma,and applied multi-omics research to explore the clinical predictive value of the model,including onset risk,independent prognosis,clinical relevance,signal transduction pathways,drug sensitivity and the correlation of immune regulatory factors,etc.Using TCGA data as experimental group and GEO data as external control group,a Nomogram model was constructed to verify the validity and accuracy of the model.The survival curve was generated by the Kaplan-meier method,and the cox proportional hazard model was used for multivariate analysis.In this study,32 pairs of fresh tissue samples of lung adenocarcinoma and paracancer tissues were collected for real-time quantitative PCR,immunohistochemical and cellular immunofluorescence experiments,etc.,to analyze and compare the expression difference of TIM-3 m RNA between lung adenocarcinoma and paracancer tissues,and explore the characteristics of tumor immune microenvironment.Recruitment of immune cells,types of immune cells and molecular subtype analysis,further analysis of the expression of immunomodulatory factors in tumor tissues,as well as key immunomodulatory factors to verify and screen influencing factors.[Research Results] A total of 450 genes related to cytolytic activity were differentially expressed,of which 273 genes were up-regulated and 177 genes were down-regulated.A total of 91 key genes related to cytolytic activity related to the prognosis of lung adenocarcinoma were screened by Cox single factor regression.The ROC curve results showed that the AUC values of 1,3,and 5 years in the training set and test set were all greater than 0.7,indicating that the model has a valid verification.This Nomogram model suggests that risk scores play a significant role in predicting the prognosis of lung adenocarcinoma,the level of risk score is significantly related to the sensitivity of patients to AKT.inhibitor.VIII,Lenalidomide and Tipifarnib(P<0.05).Our study also found that receptor and MHC genes related to immunomodulatory and chemokines are more highly expressed in the high-risk group,including HAVCR2.In addition,the expression level of TIM3 in lung adenocarcinoma tissues was significantly higher than that in paracancer tissues by PCR and immunofluorescence assay(P<0.05).[Research Conclusion] HAVCR2(TIM3)immunoregulatory factors affect the expression of key genes that affect cytolytic activity in lung adenocarcinoma,and to some extent indirectly affect the survival and prognosis.It has certain guiding value for the future clinical diagnosis and treatment of lung adenocarcinoma and the construction and evaluation of survival prognosis risk model.