Based On Endoplasmic Reticulum Stress-related LncRNA,a Prognostic Risk Assessment Model For Lung Adenocarcinoma Was Constructed And Clinical Value Evaluation

Objective : Lung cancer is the leading cause of cancer-related death worldwide,and lung adenocarcinoma is the most common subtype of lung cancer.A large number of patients are usually found in the late stage.In addition to surgical treatment,radiotherapy and chemotherapy are also the main methods of treatment.Recent advances in immunotherapy and targeted therapy have provided more hope for the treatment of lung adenocarcinoma.Long non-coding RNA(LncRNA)plays an important role in regulating target gene expression and protein translation,and its abnormal expression is related to tumor development.The accumulation of unfolded proteins in the endoplasmic reticulum will lead to endoplasmic reticulum stress(ERS)and trigger unfolded protein response(UPR).ERS has also been shown to promote the occurrence and development of tumors.Therefore,it is very important to study the role of ERS-related LncRNA for the development of effective cancer treatment and prevention strategies.In this paper,multiple databases were used for bioinformatics analysis,combined with endoplasmic reticulum stress(ERS)-related prognostic LncRNA in lung adenocarcinoma(LUAD),to explore the role of ERS-related LncRNA in LUAD prognosis,immunity and multiple targeted drug therapy,and to provide research basis for LUAD prognosis and clinical treatment.Methods : LUAD-related transcriptome and clinical data were downloaded using the Cancer Genome Atlas(TCGA).The downloaded data were collated using straberryperl version 5.30 and relevant clinical information was extracted.The endoplasmic reticulum stress genes were downloaded from the official website of GSEA,and the co-expression analysis was performed with LncRNA,and then the difference analysis was performed to combine the differential LncRNA and clinical data related to ERS in lung adenocarcinoma.Firstly,univariate COX and multivariate COX risk proportional regression analysis and Lasso regression analysis were performed to screen out LncRNAs related to the prognosis of LUAD and construct a prognostic model.Secondly,the prognostic effect of the model was evaluated by ROC(Receiver Operating Characteristic)and Kaplan-Meier analysis survival curve.After that,the median of model risk score was used for grouping verification and survival analysis to evaluate the degree of differentiation between high and low risk groups of the model.Then,gene probe enrichment analysis(GSEA)was used for pathway enrichment to analyze the differences between the screened LncRNA and the high and low risk groups of LUAD patients in more detail.Finally,the differences in drug sensitivity,immune cell survival and immune checkpoints between high and low risk groups of lung adenocarcinoma were analyzed.Results : 1.Through single factor COX risk regression analysis,36 LncRNAs significantly related to LUAD survival prognosis were screened out.After constructing and optimizing the model by Lasso-Cox method,11 LncRNAs were finally obtained.That is,AC023906.5,LINC01537,AC026462.3,AC026356.1,AL162632.3,AP000942.5,LINC02147,AL031600.2,AC026355.2,AC023202.1 and AC091132.2 are LncRNAs related to LUAD prognosis.These LncRNAs and their regression coefficients are used to construct a risk assessment model related to LUAD prognosis.2.The ROC curve analysis(AUC = 0.727),survival analysis and independent prognostic analysis showed that the model had good sensitivity and specificity and could be used as a potential prognostic marker for LUAD.3.According to the difference analysis of drug sensitivity,it is suggested that LUAD patients in the high-risk group of the model may have better chemotherapy response to SCH772984,BI-2536,ERK-6604,IGF1R3801,Foretinib,and Cytarabine.At the same time,it was found that LUAD patients in the low-risk group were more sensitive to SB216763,Ribociclib,BMS-754807,Doramapimod,Axitinib,and GSK269962 A,which was beneficial to explore personalized treatment options for different populations of LUAD patients.4.Based on the grouping of the above model,through immune cell survival analysis,it was found that the infiltration level of CD4 Th2 was negatively correlated with the prognosis of patients,and the infiltration level of most other immune cells was positively correlated with the prognosis of patients.The immune function of the low-risk group of the model is relatively more active,and the anti-CD276 and TNFSF4 immunotherapy may be more effective in the high-risk group of the model,indicating that the low-risk group is more prone to immune escape than the high-risk group.Conclusion: In this study,a stable prognostic model based on ERS-related gene co-expressed LncRNA was established to identify LUAD prognostic LncRNA :AC023906.5,LINC01537,AC026462.3,AC026356.1,AL162632.3,AP000942.5,LINC02147,AL031600.2,AC026355.2,AC023202.1 and AC091132.2,and a LUAD clinical prognostic model was constructed.The model has good sensitivity and specificity.It can also help to predict drug sensitivity and immune function.