Based on TCGA and GEO big data, we screened the new genes that had not been reported in the studied tumors, and provided the preliminary data basis for the subsequent determination of tumor biomarkers.
Through TCGA or GEO database, combined with Creative Proteomics disease key gene patent database, we analyzed the genes that had not reported clinical correlation in the studied tumors, and analyzed the expression differences of target genes in paired tumor samples, as well as the correlation with tumor stage, grade and prognosis and survival time.
Objective gene expression difference in paired samples of tumor database: general linear model and multiple of expression difference were used to analyze the significant difference of target gene in big data paired samples.
Correlation analysis of the expression level of objective gene in tumor patients with different stages and grades in tumor database: Mann-Whitney U test was used to test whether there was significant difference in the expression level of target gene in tumor patients with different stages and grades, and Spearman's test was used to test the correlation between the expression level of target gene and staging and grading.
Analysis of correlation between objective gene and survival time in tumor database: Kaplan-Meier method (Log-Rank test statistics) was used to test whether the expression level of target gene had significant effect on survival time.
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