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Copyright (c) 2023 Pufang Tan, Renshan Hao, Qi Zhu, Xiao Wu, Ye Zhang
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The undersigned hereby assign all rights, included but not limited to copyright, for this manuscript to CMB Association upon its submission for consideration to publication on Cellular and Molecular Biology. The rights assigned include, but are not limited to, the sole and exclusive rights to license, sell, subsequently assign, derive, distribute, display and reproduce this manuscript, in whole or in part, in any format, electronic or otherwise, including those in existence at the time this agreement was signed. The authors hereby warrant that they have not granted or assigned, and shall not grant or assign, the aforementioned rights to any other person, firm, organization, or other entity. All rights are automatically restored to authors if this manuscript is not accepted for publication.Construction and Validation of a risk model Based on Cuprotosis-related LncRNAsin Colon Adenocarcinoma
Corresponding Author(s) : Ye Zhang
Cellular and Molecular Biology,
Vol. 68 No. 12: Issue 12
Abstract
Cancer cells are significantly impacted by copper-induced cell death (cuprotosis). Long noncoding RNAs (lncRNAs) are crucial in the developmental process of colon adenocarcinoma (COAD). The ability of Cuprotosis-related lncRNA biomarkers to predict COAD prognosis, on the other hand, remains uncertain. This research intended to build a model of risk specifically for COAD based on cuprotosis-related lncRNAs. Univariable Cox, LASSO, as well as multivariable Cox analyses were utilized to identify cuprotosis-related lncRNAs linked with prognosis, and a model of risk was constructed. Five cuprotosis-related lncRNAs, AC008494.3, SNHG7, LINC02257, ZEB1-AS1, and AC116913.1, were discovered from the training set and utilized for the creation of a predictive model of risk. In the training and testing sets, as well as the total patient population, overall survival was dramatically lower for the high-risk patients than for the low-risk patients. The model's prognosis validity was confirmed by time-dependent areas under the ROC curves, which were identified as an independent prognosis element in multivariable COX regressive analysis. The established cuprotosis-related lncRNA-based predictive risk model was linked to chemotherapeutic sensitivity.in COAD patients, a model of risk based on five cuprotosis-related lncRNAs can predict prognosis and chemotherapeutic effectiveness.
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