Objective:To study the immunological characteristics of recombinant Rv3425 protein,to evaluate its diagnosis value and the role in the pathogenicity. Methods: Rv3425 gene was cloned into pET28a vector,the recombinant protein was induced and purified;we analyzed the antigenicity and specificity of Rv3425 by ELISA ( Enzyme-linked immuno sorbent assay) and Western blot methods,apoptosis effect of Rv3425 to macrophage was deteced by FCM ( Flow cytometry method ) . Results: Purified prokaryotic expressed protein Rv3425 was acquired,we found Rv3425 could elicit high level of IFN-γin spleen cells and combine with the serum of iH37Rv (inactivated mycobacterium tuberculosis) immunized mice;the specific IgG and IgM antibodies of TB (Tuberculosis) patients were significantly higher than healthy donors;Rv3425 also could induce the necrosis of macrophage. Conclusion:Our study found that Rv3425 had strong antigenicity and could induce the apoptosis of macrophage,these findings were very important for the research of TB diagnosis and pathogenicity.

Objective:To investigate the relationship between transcription factors (TFs) and the prognosis of colon cancer, and to construct a prognosis model through TCGA and GEO dual databases, so as to quantify the risk of patients and guide clinical treatment decisions.Methods:The transcriptome and clinical data of colon cancer in TCGA and GEO databases were used in this study. The transcriptome data were annotated and the gene expression was calculated. The difference analysis of TFs in TCGA and GEO (log2FC > 1, P-value (Fdr) < 0.05) was performed. The difference TFs of double data intersection were used for correlation prognosis analysis ( P<0.01). The risk coefficient and risk value of prognosis-related TFs were calculated by COX multivariate analysis, and the prognosis model of TFs was constructed by COX model with "survival" and "glmnet" package. The survival curve ( P<0.001) and ROC curve (AUC>0.75) of the sequence set and verification set were drawn, and the distribution of risk value was visualized. After grouping according to risk value, GSEA enrichment analysis was calculated, gene set grid was constructed, target genes were predicted, and finally, pathway enrichment analysis of GO and KEGG was carried out. Results:387 TFs with different expressions in TCGA and GEO databases were used to draw heat map, volcanic map and TFs-related forest map, and the prognosis model of colon cancer was constructed according to COX multivariate analysis=0.310×HSF4+0.137×IRX3-0.127×ATOH1+0.290×OVOL3+0.137×HOXC6+0.155×SIX2+0.092×ZNF556-0.444×CXXC5+0.429×TIGD1+0.413×TCF7L1. Through enrichment analysis, our results showed that these prognostic factors may directly or indirectly act on cancer pathways, such as basic cell carcinoma and cancer signaling pathway, local tissue-cell adhesion, and extracellular matrix.Conclusions:The constructed TFs prognosis model of colon cancer can quantify the prognostic risk of colon cancer, and its high-risk group is an independent risk factor of colon cancer prognosis. This model is a new way to evaluate the prognosis of colon cancer.