Research Paper Volume 16, Issue 5 pp 4920—4942
Establishment of an immunogenic cell death-related model for prognostic prediction and identification of therapeutic targets in endometrial carcinoma
- 1 Department of Obstetrics and Gynecology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, Anhui, China
- 2 NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract (Anhui Medical University), Hefei 230032, Anhui, China
- 3 Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People’s Republic of China, Hefei 230032, Anhui, China
Received: August 21, 2023 Accepted: February 2, 2024 Published: March 8, 2024
https://doi.org/10.18632/aging.205647How to Cite
Copyright: © 2024 Liu 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: Studies have firmly established the pivotal role of the immunogenic cell death (ICD) in the development of tumors. This study seeks to develop a risk model related to ICD to predict the prognosis of patients with endometrial carcinoma (EC).
Materials and Methods: RNA-seq data of EC retrieved from TCGA database were analyzed using R software. We determined clusters based on ICD-related genes (ICDRGs) expression levels. Cox and LASSO analyses were further used to build the prediction model, and its accuracy was evaluated in the train and validation sets. Finally, in vitro and in vivo experiments were conducted to confirm the impact of the high-risk gene IFNA2 on EC.
Results: Patients were sorted into two ICD clusters, with survival analysis revealing divergent prognoses between the clusters. The Cox regression analysis identified prognostic risk genes, and the LASSO analysis constructed a model based on 9 of these genes. Notably, this model displayed excellent predictive accuracy when validated. Finally, increased IFNA2 levels led to decreased vitality, proliferation, and invasiveness in vitro. IFNA2 also has significant tumor inhibiting effect in vivo.
Conclusions: The ICD-related model can accurately predict the prognosis of patients with EC, and IFNA2 may be a potential treatment target.
Abbreviations
ICD: immunogenic cell death; EC: endometrial carcinoma; TCGA: The Cancer Genome Atlas; OS: overall survival; LASSO: Least Absolute Shrinkage and Selector Operation; TME: the tumor microenvironment; DAMPs: damage-associated molecular patterns; DCs: dendritic cells; ICDRGs: ICD-related genes; Tregs: regulatory T cells; NK: natural killer; HR: hazard ratio; TAMs: tumor-associated macrophages; RNA-seq: transcriptome sequencing; DEGs: differentially expressed genes; ROC: receiver operating characteristic curve; AUC: area under the curve; PCA: principal component analysis; t-SNE: t-distributed stochastic neighbor embedding; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; ESTIMATE: Estimation of Stromal and Immune cells in Malignant Tumor tissues using expression data; HLA: human leukocyte antigen; FBS: fetal bovine serum; CCK8: cell counting kit 8; PBS: phosphate-buffered saline; PFA: paraformaldehyde; KM: Kaplan-Meier.