Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Identification and Validation of Autophaggen-based Nomograms to Predict the Prognostic Value of Patients with Cervical Cancer

Version 1 : Received: 19 August 2020 / Approved: 21 August 2020 / Online: 21 August 2020 (08:39:58 CEST)

How to cite: Jiang, J.; Xu, H.; Zhao, P.; Lu, H. Identification and Validation of Autophaggen-based Nomograms to Predict the Prognostic Value of Patients with Cervical Cancer. Preprints 2020, 2020080476 (doi: 10.20944/preprints202008.0476.v1). Jiang, J.; Xu, H.; Zhao, P.; Lu, H. Identification and Validation of Autophaggen-based Nomograms to Predict the Prognostic Value of Patients with Cervical Cancer. Preprints 2020, 2020080476 (doi: 10.20944/preprints202008.0476.v1).

Abstract

Cervical cancer is a common malignancy in women and has a poor prognosis.More and more studies have shown that autophagy disorder is closely related to the occurrence of tumors. However, the prognostic role of autophagy gene in cervical cancer is still unclear. In this study, we constructed the risk signatures of autophagy related genes to predict the prognosis of cervical cancer. The expression profiles and clinical information of autophagy gene sets were downloaded from the TCGA and GES52903 queues as training sets and validation sets. The cervical normal tissue expression profile data from UCSC XENA website is GTEx data as a supplement to TCGA normal cervical tissue. Univariate COX regression analysis of 17 different autophagy genes with the Consensus approach tumor samples from the TCGA is divided into six subtypes, and the clinical traits in the six subtypes have different distribution, with further then absolute shrinkage and selection operator (LASSO) and multiariable COX regression method finally got seven autophagy genetic risk model is constructed, in the training set, the survival rate of high risk group is lower than the low risk group (p < 0.0001), the validation set,The AUC area of the receiver operating characteristic (ROC) curve, the training set is 0.894, and the verification set is 0.736. We find that the high and low risk score is closely related to the TMN stage (All P is less than 0.05).The nomogram shows that the risk score combined with other indicators such as age, G,T,M, and N better predicts 1-year, 2-year, 3-year survival, and the DCA curve shows that the risk model combined with other indicators produces better clinical efficacy.Then immune cells in 28 in the enrichment score, there were statistically significant differences, high and low risk most GSEA enrichment analysis, the main enrichment in G2 / M checkpoint high-risk score, Genes defining epithelial and mesenchymal transition, raised in response to the low oxygen levels (hypoxia) gene, gene is important to the mitotic spindle assembly, these are closely related with the occurrence of tumor . In conclusion, our constructed autophagy risk signature may be a prognostic tool for cervical cancer.

Subject Areas

cervical cancer; Autophagy; Predict; Prognostic; value

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