Abstract: Objective To construct a prognostic model for cervical cancer based on tumor immune cycle related⁃genes (TICRGs), and to detect the expression of modeling factors in clinical tissue samples to verify the efficacy of the model. Methods The transcriptome profile of cervical cancer samples in TCGA database was used as the training set, and the cervical cancer genes expression profile GSE44001 in the GEO database was used as the validation set. The transcriptome data of tumor samples and normal cervical tissues were compared and analyzed to obtain cervical cancer TICRGs. The prognostic TICRGs were screened by the univariable Cox regression, and the prognostic model of cervical cancer was constructed by LASSO⁃Cox analysis method. The area under the curve (AUC) of receiver operating characteristic (ROC) curve and concordance index (C⁃index) were used to evaluate the model. GSE44001 data set was used to externally verify the model, and the feasibility of the model was verified by the multi⁃color fluorescence immunohistochemistry experiment. Results A cervical cancer prognosis model consisting of CCL17, CXCL3 and VTCN1 was constructed in this study. Prognostic survival analysis showed a significant difference in prognosis between the high⁃risk and low⁃risk groups (P<0.001). The ROC curve and the C⁃index indicated that the model showed moderate prognostic efficacy. Multivariable Cox regression showed that risk score was an independent prognostic factor for cervical cancer patients ( P=0.010). Immunoinfiltration analysis revealed that CD8+T cells was a protective factor for the prognosis of cervical cancer(P=0.017). The results of the multi⁃color fluorescence immunohistochemistry experiment were consistent with the results of the prognostic model. Conclusions The prognostic model constructed based on tumor immune cycle⁃related genes CCL17, CXCL3 and VTCN1 has moderate predictive efficacy in predicting the prognosis of patients with cervical cancer. 

Key words:  Cervical cancer, Prognostic model, Tumor immune cycle related genes, Multi?color , fluorescence immunohistochemistry