Construction and validation of cervical cancer prognosis model based on RNA-binding proteins
ZHANG Zhe
WU Jie
WU Tingting
HU Chengbiao
SONG Shaohui
MA Wenlong
DONG Xunhu
Abstract：Objective To construct a core RNA-binding proteins(RBPs)related prognosis model in cervical cancer(CC)and preliminarily screen the prognostic biomarkers.Methods The expression levels of 1 542 RBPs in CC were compared in Genotype-Tissue Expression and The Cancer Genome Atlas(TCGA)to screen the differential expressed RBPs(DERBPs,log2FC＞1 and FDR＜0.05).The TCGA cohort was randomly divided into training cohort and testing cohort according to the ratio of 2:1.The CC prognosis model was constructed by univariate Cox regression,least absolute shrinkage and selection operator and stepwise multivariate Cox regression in the training cohort,and verified in the testing cohort.Finally,a nomogram was established and hub gene was screened based on the model in vitro to evaluate and verify the efficacy of the model.Results Nine core RBPs were screened out from 348 DERBPs and the model was constructed.Survival analysis showed that the overall survival rate of CC patients in the high-risk group was significantly lower than that in the low-risk group(P＜0.001),and ROC curves(AUC＞0.8)indicated that the model had moderate predictive ability,which could be used as an independent prognostic factor for CC patients(HR=1.152,95％CI:1.106-1.200,P＜0.001).All the above results were verified in the testing cohort.A nomogram based on 9 RBPs was constructed in the TCGA cohort,and the calibration curves showed that it had good accuracy.Finally,in vitro experiments confirmed that after silencing the expression of RBM38 in CC cells,the cell proliferation,migration and invasion ability were significantly enhanced(P＜0.05),which was consistent with the predicted results.Conclusion In this study,a CC prognostic model composed of 9 RBPs is successfully constructed,which can be used as an independent prognostic biomarker of CC and has moderate predictive ability.The results may provide potential therapeutic targets and prognostic biomarkers for CC patients.
Keywords：cervical cancerbioinformaticsThe Cancer Genome Atlasprognostic model
Publication Date：2024-07-28
Online Publishing Date：2026-08-26(First online date of this platform, not the publication date of the document)
Pages：8( 805-812 )