| Objective:Gastric cancer is the most common malignant tumor of the digestive system.The incidence and mortality of gastric cancer in China is significantly higher than that of other countries,which seriously threatens human health.Since there is no specific change in early gastric cancer,most patients are found to be in the progressive stage.The rapid development of surgery and adjuvant chemoradiotherapy has improved the survival time of gastric cancer patients to a certain extent,but the 5-year survival rate of gastric cancer patients is less than 30% due to chemical resistance and other reasons.Therefore,it is particularly important to search for biomarkers that can predict the prognosis and therapeutic effect of gastric cancer patients.Long non-coding RNA(lncRNA)is a type of RNA whose transcription length exceeds 200 nucleotides,which has no protein-coding ability due to partial or complete deletion of open reading frame sequence.However,recent studies have shown that lncRNA has a wide range of biological functions and plays an important role in the development and progression of tumors.It can regulate the proliferation,differentiation,invasion and metastasis of tumor cells and other biological processes,and is expected to become a new biomarker for tumor diagnosis and prognosis and a potential therapeutic target.The expression of lncRNA can be detected in human tissues and body fluids,which is specific to tissues and cells.The purpose of this study was to screen the differentially expressed lncRNA in gastric cancer and paracancer tissues by bioinformatics.The prognostic risk model for gastric cancer was constructed based on TCGA databse and to further screen lncRNA related to gastric cancer prognosis,so as to provide research direction and theoretical basis for the follow-up experiments.Methods:Based on the transcriptome sequencing data of gastric cancer and the detailed clinical data of gastric cancer patients downloaded from the human tumor genome database(The CancerGenome Atlas,TCGA),the expression matrix of lncRNA data was extracted from transcriptome sequencing data.The threshold value was set at the corrected P<0.05 and the differential expression multiple>2(FDR<0.05and |log FC|>2),use the "edgeR" package in R language to screen the lncRNA of differential expression in gastric cancer and adjacent tissues,combine lncRNA expression data with downloaded survival data,screen of prognostic lncRNA in gastric cancer patients by univariate Cox regression analysis based on set P values.Using LASSO regression analysis to reduce overfitting of data by the "glmnet" package and "survival" package in R language,and choose the smallest ? value as the best reference value to screen and prognosis the more critical lncRNA.Finally,the lncRNA model related to the prognosis of gastric cancer was established by multivariate Cox regression analysis.Using the median of the calculated risk score as the critical value,patients were divided into high-risk groups and low-risk groups.The predictive ability of the model at 3-year and 5-year survival was evaluated using the receiver operating characteristic(ROC)curve,the C index was calculated to further evaluate the prognosis model,and then the survival curve of the high-low risk groups was plotted by Kaplan-Meier(K-M)survival analysis.K-M survival analysis was performed on the statistically different lncRNA in Cox multivariate regression analysis to determine the prognostic biomarkers.Results:(1)In this study,1272 differentially expressed lncRNA were screened based on TCGA data,including 1051 up-regulated lncRNA and 221 down-regulated lncRNA.(2)Univariate Cox regression analysis was performed on 1272 differentially expressed lncRNA,and a total of 68 differentially expressed lncRNA were obtained based on P<0.05 as the screening criterion,which was related to the prognosis of patients with gastric cancer.(3)Further LASSO regression analysis results showed that 25 lncRNA correlated with the prognosis of gastric cancer patients were finally obtained(P<0.05).(4)The 25 lncRNA obtained from the LASSO regression analysis were subjected to multivariate regression analysis,the expression data and regression coefficients of each lncRNA were extracted,and the prognostic risk model of gastriccancer based on 25 lncRNA was constructed.Median divides patients into high and low risk groups.K-M survival curve results show that the high-risk group of patients with poor prognosis(P<0.01).The ROC curve results showed that the area under the curve of the 3-year survival rate and 5-year survival rate were 0.804 and 0.79,respectively,and the C index was 0.73,indicating that the model has good predictive ability.(5)Multivariate regression analysis of the obtained 25 differentially expressed lncRNA showed that only 4 differentially expressed lncRNA were statistically significant(P<0.05).Further survival analysis showed that only lncRNA AL109615.2was associated with the prognosis of patients with gastric cancer.Conclusion:Based on TCGA database,we successfully constructed a prognostic model of gastric cancer based on the expression levels of 25 lncRNA,with good predictive efficacy,and determined that lncRNA AL109615.2 can be used as a biomarker for poor prognosis of gastric cancer patients. |
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