A Study Of The Potential Application Value Of High-Throughput Sequencing For The Detection Of Genetic Mutations In Targeted Drugs For Tyrosine Kinase Inhibitor In Bladder Cancer

Objective:Mutation and mutational functional regions of bladder cancer-related genes were analyzed using high-throughput sequencing techniques to explore the relationship between mutations and bladder cancer’s clinical characteristics,prognosis,and clinical significance.The potential application of gene mutations in targeted drugs for bladder cancer tyrosine kinase inhibitors was explored based on information from the bladder cancer gene mutation profile.Methods:A total of 47 bladder cancer patients,including 32 males and 15 females,were collected from April to October 2020 at the urology department of Chengde Medical College Affiliated Hospital.The minimum age was 25 years old,the maximum was 89 years old,and the average age was 63±11.85 years old.There were 24 cases of muscular invasive bladder cancer(MIBC)and 23 cases of non-muscular invasive bladder cancer(NMIBC).The Nextseq CN500 System,a high-throughput sequencing platform,was used to perform gene sequencing,characterize gene detection results,and systematically analyze the relationship between high-frequency mutated genes and clinical pathologies.Bladder cancer patients were followed every1 to 3 months for a year after surgery and every 3 to 6 months for a second year.Follow-up included B-ultrasound,CT,and cystoscopy,with follow-up ranging from 6 to 23 months.The Kaplan-Meier method and log-rank test were used for the analysis,and Kaplan-Meier survival curves were plotted.To analyze the prognosis of patients with bladder cancer and the relationship between high frequency mutated genes and progression-free survival(PFS)and overall survival(OS),and to analyze the risk factors affecting the recurrence or death of bladder cancer by Cox proportional risk regression model.Based on the genetic mutation information detected,we searched the OncoKB database for targeted tyrosine kinase inhibitors for the treatment of bladder cancer.Results:A total of 29 mutant genes,61 exons and 95 gene mutation sites were detected in this study.TP53,FGFR3,PIK3CA,ERBB2,MUC4 and KRAS have higher mutation frequencies,accounting for 59.92%of the total mutation frequency.The mutation frequency of TP53 gene was higher in MIBC and the difference was statistically significant(χ~2=16.045,P=0.000).The mutation frequency of FGFR3 in NMIBC was higher and the difference was statistically significant(χ~2=11.284,P=0.001).TP53 and FGFR3 genes were correlated with clinical T stage,TP53 mutation frequency of bladder cancer T2b stage was higher,the difference was statistically significant(χ~2=21.433,P=0.000),FGFR3 gene mutation frequency of bladder cancer T1 stage was higher.The difference was statistically significant(χ~2=12.566,P=0.014).There were no significant differences in TP53,FGFR3,PIK3CA,ERBB2,MUC4 and KRAS genes in age,sex and smoking history(P>0.05).By February 28,2022,the shortest follow-up was 6 months,the longest was 23 months,and the median follow-up was 21 months.Kaplan-Meier analysis showed that PFS in the TP53(-)group were significantly better than those in the TP53(+)group.log-rank test confirmed the correlation between TP53 and PFS(P<0.05).Tumor T stage was significantly correlated with PFS(P<0.05),and PFS decreased with the progression of tumor stage.Other genes and factors have not been shown to be associated with PFS.In univariate analysis of factors affecting postoperative PFS in patients with bladder cancer by Cox proportional risk model,positive TP53 gene and bladder cancer T stage were correlated with PFS(P<0.05).Targeted tyrosine kinase inhibitors for the treatment of bladder cancer include AZD1775,ertatinib,AZD4547,BGJ398and are often based on mutations detected in the OncoKB database.Conclusion:1.The mutations in the genes TP53,FGFR3,PIK3CA,ERBB2,MUC4and KRAS are found with high frequency in bladder cancer patients.2.The TP53 gene is significantly associated with stage T2b bladder cancer and the FGFR3 gene is significantly associated with stage T1 bladder cancer;The genes TP53,FGFR3 and PIK3CA may play a predictive role in the prognosis of bladder cancer.3.High-throughput sequencing technology can be used to detect genetic mutations in bladder cancer and to predict targeted tyrosine kinase inhibitors for the treatment of bladder cancer.