Abstract
Background: Autophagy plays an important role in the development of cancer. However, the prognostic value of autophagy-related genes (ARGs) in cervical cancer (CC) is unclear. The purpose of this study is to construct a survival model for predicting the prognosis of CC patients based on ARG signature.Methods: ARGs were obtained from the Human Autophagy Database and Molecular Signatures Database. The expression profiles of ARGs and clinical data were downloaded from the TCGA database. Differential expression analysis of CC tissues and normal tissues was performed using R software to screen out ARGs with an aberrant expression. Univariate Cox, Lasso, and multivariate Cox regression analyses were used to construct a prognostic model which was validated by using the test set and the entire set. We also performed an independent prognostic analysis of risk score and some clinicopathological factors of CC. Finally, a clinical practical nomogram was established to predict individual survival probability.Results: Compared with normal tissues, there were 63 ARGs with an aberrant expression in CC tissues. A risk model based on 3 ARGs was finally obtained by Lasso and Cox regression analysis. Patients with high risk had significantly shorter overall survival (OS) than low-risk patients in both train set and validation set. The ROC curve validated its good performance in survival prediction, suggesting that this model has a certain extent sensitivity and specificity. Multivariate Cox analysis showed that the risk score was an independent prognostic factor. Finally, we mapped a nomogram to predict 1-, 3-, and 5-year survival for CC patients. The calibration curves indicated that the model was reliable.Conclusion: A risk prediction model based on CHMP4C, FOXO1, and RRAGB was successfully constructed, which could effectively predict the prognosis of CC patients. This model can provide a reference for CC patients to make precise treatment strategy.
Highlights
Autophagy is a self-degradative process that is important for maintaining nutrient and energy homeostasis and eliminating intracellular pathogens (Glick et al, 2010; Jiang and Mizushima, 2014; Yu et al, 2018a)
Kyoto Encyclopedia of Genes and Genomics (KEGG) signaling pathway analysis showed that DE-ARGS were involved in some cancerrelated signaling pathway such as apoptosis, cellular senescence, p53 signaling pathway, and HIF-1 signaling pathway (Figure 2B)
Calibration curves revealed that the predicted and actual survival rates were well matched at 1, 3, and 5 years (Figures 7C–E). These findings suggested that the nomogram has a high accuracy in predicting overall survival
Summary
Autophagy is a self-degradative process that is important for maintaining nutrient and energy homeostasis and eliminating intracellular pathogens (Glick et al, 2010; Jiang and Mizushima, 2014; Yu et al, 2018a). Autophagy is generally considered to be a survival mechanism and widely involved in a variety of pathophysiological processes such as cancer, metabolism, and cardiovascular disease (Choi et al, 2013). Cancer cells have evolved to use autophagy as an adaptive mechanism to survive under extreme stress in the tumor microenvironment and to enhance the resistance of anticancer drugs. Autophagy plays a dual role in many cancers both promoting and suppressing cancers, depending on the tumor microenvironment (Yun and Lee, 2018). It is of great significance to further explore the potential role of autophagy in tumor genesis and development. Autophagy plays an important role in the development of cancer. The prognostic value of autophagy-related genes (ARGs) in cervical cancer (CC) is unclear. The purpose of this study is to construct a survival model for predicting the prognosis of CC patients based on ARG signature
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