Exploring The Prognostic Value And Potential Mechanism Of Alternative Splicing Events In Geriatric Lung Adenocarcinoma

BackgroundLung cancer is the malignant tumor with the highest mortality.According to the latest statistics from the American Cancer Society,lung cancer mainly occurs in the elderly.Most people diagnosed with lung cancer are 65 or older,the average age at diagnosis is about 70.Considering that elderly patients always have more complications and poor prognosis,many clinical trial inclusion criteria exclude elderly patients.Thus,more attention should be paid to geriatric patients.Alternative splicing(AS),an essential process for the maturation of mRNAs,is involved in tumorigenesis and tumor progression,including angiogenesis,apoptosis,and metastasis.AS changes can be frequently observed in different tumors,including geriatric lung adenocarcinoma(GLAD).Previous studies have reported an association between AS events and tumorigenesis,and showed that AS has diagnostic value and is considered a potential drug target,but have lacked a systematic analysis of its underlying mechanisms.The Cancer Genome Atlas(TCGA)is a project that classifies the major cancer-related genomic alterations.Many studies have established predictive models that pay closer attention to the interaction of multiple genes.However,no study currently has provided evidence supporting the prognostic value of AS events in GLAD.Given the high incidence of splicing defects in lung adenocarcinoma,the potential connection between SFs and AS events in GLAD deserves further exploration and supporting evidence.ObjectiveTo establish a prognostic model of elderly lung adenocarcinoma based on variable shearing.Explore the network of splicing factors and survival-related variable splicing events,and further clarify the potential molecular mechanisms regulating variable splicing events in elderly lung adenocarcinoma.Methods1.The clinical information of 251 elderly patients with LUAD(ages 65-89)and mRNA expression data was downloaded from the TCGA Genomic Data Commons(GDC)database.Cancer-related AS events were selected in 59 normal controls and 513 tumor tissues from the TCGA SpliceSeq database.2.Univariate Cox regression analyses were conducted to select survival associated AS events.Least absolute shrinkage and selection operator(LASSO)regression analysis was used to screen and eliminate genes with high correlation to construct a credible prognostic index model.Univariate analyses and multivariate analyses were performed to explore independent survival-related prognostic factors.3.Based on the median value of the risk score calculated by the prognostic index(PI)model,cases were divided into high-risk and low-risk groups.The survival analysis was analyzed by the Kaplan-Meier method.To certify the reliability of the model in predicting prognosis,the survival receiver-operator characteristic(ROC)package in R was used to calculate the area under the curve(AUC)of the ROC curve for each model.Models with AUC>0.7 were more effective models.Then we substituted data from non-elderly lung adenocarcinoma patients(ages 3 3～64)into the PI models4.We downloaded the information regarding SFs from the database SpliceAid2.The mRNA expression of SFs in geriatric lung adenocarcinoma was downloaded from the TCGA database.Survival-related SFs were screened by univariate Cox regression analysis.Pearson correlation analysis was used to analyze the correlation between survival-related SFs and AS events with independent predictive significance.Cytoscape v3.7.1 software was used to visualize the potential regulatory network between AS and SFs.The Gene Ontology(GO)terms and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways were used to assess the functions associated with the most significant prognosis-related AS events.5.Download the immunohistochemical results of the genes DDX39B,SRRM2,DDX17,RBM5 and ATAD3A from the database THPA(The Human Protein Atlas)in lung tissues and lung adenocarcinoma tissues,and use Image J software to analyze the gene expression in normal tissues and pathological tissues.6.Collect 15 fresh cancer tissues from patients with lung adenocarcinoma diagnosed by puncture in the First Affiliated Hospital of Zhengzhou University.The fresh tissue specimens were cut and quickly placed in liquid nitrogen for cryopreservation.Among them,7 cases did not metastasize during specimen collection,and 8 cases metastasized during specimen collection.Real time PCR(rt-PCR)technology was used to detect the expression levels of DDX39B,DDX17,SRRM2,RBM5 and ATAD3A genes in 15 cases of lung adenocarcinoma tissues.Results1.In the univariate Cox hazard analyses,the TNM stage,tumor stage,lymph node metastasis,and risk score of eight PI models were significantly correlated with the survival time of elderly patients with LUAD(P<0.05).However,no significant correlations were observed between survival time and age,sex,or distant metastasis.According to the multivariate cox hazard analysis,only the risk score of eight PI models significantly correlated with the survival time of geriatric patients with LUAD(P<0.001).2.Of seven types of AS events,ES was the most common type.A total of 16,793 ES events were observed in 6475 genes,of which only 1744 genes were involved in the ES event.After combining AS data and survival data,a total of 2381 survival-related AS events in 1633 genes were reported through the univariate Cox regression analysis.3.The ROC curve analyses showed that eight models had predictive significance for prognosis.The PI model of AA events was the most effective at estimating the prognosis of geriatric patients with LUADs,with an AUC value of 0.87.The results showed that all the PI models could achieve good stratification of the prognosis of the low-and high-risk groups.Kaplan-Meier curve analysis showed that the survival time of the low-risk group was significantly longer than the high-risk group.After substituting the data of non-elderly lung adenocarcinoma patients into the prognosis model,we found that there was no significant difference in survival.4.A total of 19 SF and 54 AS events were selected by Pearson’s analysis.Generally,AS events with high-risk were mainly negatively correlated with SFs,whereas AS events with low-risk were mainly positively correlated.Several SFs in key nodes were frequently related to splicing events in GLAD,mainly including DDX39B,DDX17,SRRM2,CIRBP,and RBM5.5.1n GO terms,genes were mostly enriched in terms involving RNA-dependent ATPase activity,RNA helicase activity,snRNA binding,and mRNA binding.3 KEGG pathways were enriched in the AS-SFs network,including the spliceosome,the mRNA surveillance pathway,and RNA transport.DDX39B was involved in 6 biological functions.6.Image J analysis shows that DDX39B,SRRM2,RBM5 and ATAD3A are expressed in normal lung tissues and lung cancer tissues with differences.There was no difference in DDX17 expression.7.PCR analysis showed that DDX39B,DDX17,SRRM2,RBM5 and ATAD3A genes were expressed in 15 cases of lung adenocarcinoma tissues.The expression of DDX39B was different in metastatic and non-metastatic patients.Conclusion1.The survival-related prognostic model of elderly patients with lung adenocarcinoma established based on variable shearing has high predictive value,and the prognostic model related to AA shearing event is the most effective.This prognostic model is not suitable for non-elderly patients with lung adenocarcinoma.2.A total of 19 shear factors are highly involved in the regulation of 54 survival-related shear events.The key node splicing factors include DDX39B,DDX17,SRRM2,CIRBP and RBM5,among which DDX39B participates in 6 biological functions,which provides ideas for further exploring the mechanism of elderly lung adenocarcinoma.3.There are differences in the expression of DDX39B,SRRM2,RBM5 and ATAD3A in normal tissues and lung adenocarcinoma tissues.The expression of DDX39B in lung cancer tissues of metastatic patients is higher than that in non-metastatic patients.