Research Paper Volume 15, Issue 23 pp 14242—14262
Two lncRNA signatures with cuproptosis as a novel prognostic model and clinicopathological value for endometrioid endometrial adenocarcinoma
- 1 Department of Pathology, The First Affiliated Hospital of Shantou University Medical College, Shantou 515041, Guangdong, China
Received: June 21, 2023 Accepted: November 2, 2023 Published: December 11, 2023
https://doi.org/10.18632/aging.205299How to Cite
Copyright: © 2023 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Objective: Cuproptosis may contribute to tumorigenesis. However, the predictive value and therapeutic significance of cuproptosis-related lncRNAs (CRLs) in endometrioid endometrial adenocarcinoma (EEA) remains unknown.
Methods: We obtained RNA-seq data from TCGA database and searched the Literature to identify cuproptosis-related genes. Using machine learning models, we identified prognostic lncRNAs for cuproptosis. Immune properties and drug sensitivity were investigated based on these signatures. Further, a ceRNA network was constructed by bioinformatics and in vitro experiments were performed.
Results: We determined two cuproptosis-related signatures to build the prognostic model in EEA. Afterward, the risk scores of two cuproptosis-related signatures were associated with clinicopathological molecular typing and as independent prognostic factors for EEA. In addition, we observed significant differences in immune function, checkpoints, and CD8+ T lymphocyte infiltration between the two risk groups. Furthermore, chemotherapy drugs such as AKT inhibitors exhibited lower IC50 values in the high-risk group. We speculate that ACOXL-AS1 can be served as an endogenous ‘sponge’ to regulate the expression of MTF1 by miR-421. Through in vitro experiments, we preliminarily validated the ceRNA network relationship in the cellular model.
Conclusion: In EEAs, this study proposed a broad molecular signature of CRLs are promising biomarkers for predicting clinical outcomes and therapeutic responses.