| In recent years,lots of studies have confirmed that the incidence rate of gallbladder cancer has gradually increased with age.The morbidity is about 0.16/100 thousand in 20~49years old,1.47/100 thousand in 50~64 years old,4.91/100 thousand in 65~74 years old,and8.69/100 thousand over 75 years old.Due to hard to detect and progress quickly,the patient of gallbladder cancer has poor prognosis.Radical surgery is the main treatment method to cure gallbladder cancer.Because of organ dysfunction and multiple underlying diseases,elderly patients have poor tolerance to surgery,increased risk of postoperative complications and short survival time.How to evaluate the prognosis of elderly patients accurately,and then improve their postoperative survival time,is a crucial clinical issue to be solved.Therefore,it is of great clinical significance to explore the risk factors and establish a prediction model to evaluate the postoperative survival rate of elderly patients with gallbladder cancer.In addition,with the continuous development and application of gene sequencing technology,gene sequencing data of miRNAs related to gallbladder cancer are constantly enriched.Screening miRNAs related to survival of gallbladder cancer and constructing a miRNA-mRNA regulatory network by bioinformatics methods will help clarify the possible pathogenesis and provide research evidence to diagnose and therapy gallbladder cancer.Objectives:1.To explore the clinicopathological factors affecting prognosis of elderly patients with gallbladder cancer after surgery,and to construct a nomogram to predict the survival rate of elderly gallbladder cancer patients after surgery.2.To explore the survival-related miRNAs and analysis functions in gallbladder cancer,and to construct a miRNA-mRNA co-expression network related to the survival of gallbladder cancer patients.Method:Part Ⅰ:1.Data were extracted from the National Surveillance,Epidemiology,and End Results(SEER)database.2.The clinical,pathological and follow-up information of elderly patients(≥ 60 years old)with gallbladder cancer who underwent surgical treatment from 2004 to 2015 were selected.At the same time,patients with incomplete clinical and survival data,sarcomas or neuroendocrine tumors,multiple tumors and postoperative survival time less than 1month were excluded.3.Kaplan-Meier survival curve was used to calculate the overall survival rate and cancerspecific survival rate of the gallbladder cancer patients in the training set;Univariate and multivariate Cox proportional hazard regression models were used to screen the independent risk factors affecting the survival rate of the elderly patients after surgery;The nomogram model was applied to predict the 3-and 5-year survival rate of the patients.4.The accuracy of nomogram was evaluated by C-index,calibration chart and external validation set,and the prediction efficiency of nomogram and 8th TNM staging system was evaluated by C-index and the area under the ROC curve(AUC).Part Ⅱ:1.Data were downloaded from Gene Expression Omnibus(GEO)database.The miRNA chips and mRNA chips related to gallbladder cancer were retrieved,and the differentially expressed miRNA and mRNA between cancer and normal tissues were screened.2.According to the survival time of patients,the survival-related miRNAs of gallbladder cancer were screened out,and the target genes of these miRNAs were predicted by using the common database(miRDB and Targetscan).Then the differentially expressed mRNA was matched to exclude the non-target genes.3.The DAVID database was used to perform functional enrichment analysis(Gene Ontology,GO)and signal pathway analysis(Kyoto Encyclopedia of Genes and Genomes,KEGG)of target genes.4.Protein-protein interaction(PPI)network was built and visualized by the STRING database and Cytoscape software.The Cyto Hubba plug-in was used to identify hub genes in the PPI network.5.MiRNA-mRNA co-expression network of gallbladder cancer patients was constructed by Cytoscape software.Results:Part Ⅰ:1.A total of 1076 eligible elderly patients with gallbladder cancer were screened from the SEER database,with a median follow-up time of 64 months(1-152 months).Patients were randomly divided into a training set of 776 people and a validation set of 320 people.2.Kaplan-Meier survival curve results showed that the overall survival rates and cancerspecific survival rates of patients in the training set at 3-and 5-years after surgery were34%,27%,and 39% and 27%,respectively.3.Univariate and multivariate regression analysis indicated that age,pathological grade,tumor size,lymph node ratio,T stage and M stage were independent risk factors for overall survival after surgery(all P <0.05).Age,tumor size,lymph node ratio,T stage,and M stage were independent risk factors for cancer-specific survival after surgery(all P <0.05).4.Based on the above risk factors,a nomogram was constructed to predict the overall survival and cancer-specific survival of elderly patients with gallbladder cancer at 3-and 5-year after surgery.The C-index of the nomogram models were 0.727(95% CI:0.705-0.749)and 0.742(95% CI: 0.718-0.766),respectively,and the C-index of the external validation set were 0.729(95% CI: 0.692-0.766)and 0.729(95% CI: 0.689-0.768),respectively.5.The AUC of the 3-and 5-year overall survival rates predicted by the nomogram were0.796 and 0.786,respectively,and the AUC of the cancer-specific survival rates were0.811 and 0.804,respectively.The AUC predicted by the 8th TNM staging system were0.765 and 0.765 respectively,and the AUC of cancer-specific survival were 0.784 and0.787 respectively.The C-index of the 8th TNM staging system were 0.681(95% CI:0.657-0.704)and 0.704(95% CI: 0.680-0.728),which were significantly different from the nomogram.Part Ⅱ:1.One miRNA chip(GSE107165)and one mRNA chip(GSE76633)were downloaded from the GEO database.After differential expression analysis,11 survival-related miRNAs were obtained,including 7 down-regulated miRNAs(miR-29c-5p,miR-145-5p,miR-192-5p,miR-194-5p,miR-215,miR-320 b,miR-338-3p)and 4 up-regulated miRNAs(miR-575,miR-4430,miR-4462,miR-6129).2.269 target genes(204 up-regulated and 65 down-regulated)related to gallbladder cancer were obtained by online database and mRNA chip.3.The results of GO enrichment analysis and KEGG pathway analysis showed that these target genes are mainly involved in the proliferation,invasion and migration of gallbladder cancer through PI3K/Akt signaling pathway and Rap1 signaling pathway.4.12 hub genes(BRCA1,EFNB2,GLI3,EXO1,H2 AFX,IGF1R,ITGA6,ITPKB,RUNX2,SHH,SOX9,and THBS1)were identified through the PPI network.5.By integrating miRNA and mRNA information,a miRNA-mRNA network related to the survival of gallbladder cancer patients was constructed.Conclusion:Part I:1.Age,pathological grade,tumor size,lymph node ratio,T stage and M stage are independent risk factors for overall survival after surgery.Age,tumor size,lymph node ratio,T stage and M stage are independent risk factors for cancer-specific survival after surgery.2.A new nomogram for predicting the postoperative survival of elderly patients with gallbladder cancer is constructed.The model is easy to operate and has high accuracy,which is better than TNM staging evaluation system.Part II:11 miRNAs and 12 key genes related to the survival of gallbladder cancer are identified,and then a miRNA-mRNA co-expression network related to the survival of gallbladder cancer is constructed,which is helpful to explore the new pathogenesis and therapeutic targets of gallbladder cancer. |
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