Constructing And Verifying A Prognostic Model Of Pyroptosis-related LncRNA In Gastric Cancer

ObjectiveResearching the value of proptosis-related long non-coding RNAs(PRLs)as a prognostic tool in stomach adenocarcinoma(STAD),and further exploring the relationship between the prognostic model and the immune infiltration and pharmacological landscape,so as to promote the prognostic management and personalized therapy of gastric cancer.MethodsDownloading STAD data from the Cancer Genome Atlas(TCGA)database for organization,merging expression data and clinical information and extracting differentially expressed lnc RNA expression data,single factor COX regression was used to obtain lnc RNA with prognostic value.Cross-referencing from different databases obtained 37 apoptosis-related genes and Pearson correlation analysis was used to identify prognostic lnc RNA co-expressed with apoptosis gene.Using the least absolute shrinkage and selection operator(LASSO)analyzes,four apoptosis-related lnc RNA were ultimately established to construct a risk model.All samples were randomly divided into training group and verification group in 1:1 ratio.Model calculation of the risk score of each sample,divided into high and low risk group according to the median of the risk scores.Then perform survival analysis,independent prognosis analysis,ROC analysis to evaluate the predictive performance of the model.The expression of four lnc RNAs in gastric cancer cell lines and normal gastric cell lines were explored by q PCR experiments.Finally,functional enrichment,immunostaining,and pharmacological landscape between different risk groups were further studied to explore the potential clinical value of the model.Results1.Based on the differential analysis,1989 differentially expressed lnc RNAs were obtained.Single factor Cox regression was used to screen 122 lnc RNAs which were significantly associated with overall survival time(OS)of STAD patients.Through co-expression analysis,30 prognostic lnc RNAs related to apoptosis were obtained.2.Using LASSO regression analysis,4 pyroptosis-related lnc RNAs(LINC01614,VCAN-AS1,LINC01697,AC129507.1)were determined to construct a prognostic model,and all 4 lnc RNAs were found to be risk factors(HR>1,p<0.05).3.The training group and the validation group both showed poor prognosis in the high risk group than in the low risk group after survival analysis(p < 0.05).Independent prognostic analysis showed that this model risk score could be used as an independent prognostic indicator(COX regression was p < 0.01 for single/multi factor).The AUC values of 1,3,5 years in time dependent ROC analysis were 0.671,0.735,0.809 respectively,indicating a good prognosis efficiency.4.QPCR analysis verified the differential expression of four lnc RNAs(LINC01614,VCAN-AS1,LINC01697,AC129507.1)in gastric cancer cell lines and normal cell lines(p <0.05),which was consistent with bioinformatics analysis results.5.The risk score model was enriched in muscle motion and cell adhesion-related pathways.The resting memory CD4(+)T cells,M0 macrophages,resting NK cells,and helper follicular T cells content were higher in the low-risk group than in the high-risk group,and the survival advantage was obvious.The high-risk group had higher single-cell,M2 macrophage,resting dendritic cell(DC),and resting hypertrophic cell contents than the low-risk group.6.The drug sensitivity of cisplatin,oxaliplatin,gemcitabine and sorafenib in the high risk group was higher than that in the low risk group,while the sensitivity of dacarbazine and Uprosertib inhibitor was lower than that in the low risk group.Conclusions1.We constructed a prognostic model composed of four PRLs(LINC01614,VCAN-AS1,LINC01697 and AC129507.1).2.The model has good predictive performance for prognosis,with high-risk groups having poorer prognosis than the low-risk ones.3.The expression differences in the high-risk group are related to "cell adhesion molecules" and "energy metabolism" associated with malignant tumors.The low-risk group has higher abundance of multiple immune infiltrations and a significant survival advantage,and the high-risk group has more hypertrophic cells,which is one of the reasons for the poor prognosis.High-risk groups are more sensitive to drugs such as cisplatin,oxaliplatin,gefitinib,and sorafenib.The model has certain clinical guidance for the prognostic management and personalized treatment of gastric cancer.