| Background and PurposeLung cancer has the highest incidence and mortality among malignant tumors in the world,which seriously affects human health.According to the pathological types,lung cancer can be mainly divided into two categories:small cell lung cancer and lung cancer.Lung cancer includes lung squamous cell carcinoma,lung adenocarcinoma and large cell lung cancer and other pathological subtypes,of which lung squamous cell carcinoma accounts for about 30%and lung adenocarcinoma accounts for about 65%.However,most lung cancers are found at an advanced stage,and the therapeutic effect is unsatisfactory because of their high degree of malignancy and heterogeneity.Existing treatments for lung cancer include surgery,radiation therapy,chemotherapy,targeted therapy,and immunotherapy.The application of targeted drugs for driver gene mutation,such as first-,second-and third-generation EGFR and ALK inhibitors,improves the prognosis of patients with lung adenocarcinoma with gene mutation and improves the overall survival time of lung adenocarcinoma to 3.5 years.Because the gene mutation rate of lung squamous cell carcinoma is less than 5%,and the overall effect is not satisfactory for the treatment effect.Although some progress has been made in the study of targeted therapy for lung cancer,there is a lack of effective therapeutic targets and targeted drugs for most patients with lung squamous cell carcinoma without driver gene mutations.However,clinically,we found that some patients with locally advanced squamous cell carcinoma of the lung had a better prognosis.With the rise of high-throughput sequencing technology and the development and completion of various genome projects,genomic data has shown an explosive growth trend.Bioinformatics links statistics to genomics and clinical information.Bioinformatics provides a way to find genes that affect prognosis.Therefore,we tried to use bioinformatics methods to find genes related to predicting prognosis by analysis,so as to guide the treatment of locally advanced lung squamous cell carcinoma.Materials and MethodsIn this study,we collected the clinical data of 6 pairs of patients with stage IIIB lung squamous cell carcinoma in Nanfang Hospital and Guangdong General Hospital from January 2008 to May 2010.Including gender,age,smoking status,PS score,and complete follow-up data,including recurrence after treatment,overall survival.According to the length of disease-free survival(bounded by DFS=24 months),patients were divided into two groups:the better prognosis group and the poor prognosis group.Genes that may affect the poor prognosis of stage ?B lung squamous cell carcinoma were screened by bioinformatics methods and further validated in the TCGA database.Results1.Differential gene analysis of stage ?B lung squamous cell carcinoma and tissue revealed 762 differentially expressed genes,of which 454 were up-regulated differentially expressed genes and 308 were down-regulated differentially expressed genes;2.Differential gene analysis of stage ?B lung squamous cell carcinoma with poor prognosis yielded 315 differentially expressed genes,of which 193 were up-regulated differentially expressed genes and 122 were down-regulated differentially expressed genes;3.Further analysis obtained differential genes that were up-regulated only in the poor prognosis group,a total of 64;4.Through bioinformatics analysis(including GO,KEGG,PPI)of 64 up-regulated differentially expressed genes,it was found that most of the genes were associated with immune function;5.Further validation by the TCGA database confirmed that stage IIIB lung squamous with high CTSZ gene expression had a poor survival prognosis.(P<0.05)ConclusionBy means of bioinformatics analysis,we screened 64 up-regulated differentially expressed genes that may be used as prognostically related genes in locally advanced lung squamous cell carcinoma,and further analysis revealed that the up-regulated expression of CTSZ gene was an independent factor for poor prognosis in locally advanced lung squamous cell carcinoma(P<0.05)... |
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