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Updated: Jul 4, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Development and validation of a combined cuproptosis and immunogenic cell death prognostic model for diffuse large
Nana Wang1, Shanshan Shi2, Moran Li1
1Department of Hematology, Qilu Hospital of Shandong University, Jinan 250012, China.
Background:
Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma worldwide with a high degree of heterogeneity. Cuproptosis and immunogenic cell death (ICD) have been considered to be vital for tumor progression. However, current understanding of cuproptosis and immunogenic cell death in DLBCL is still very limited. We aim to explore a prognostic model combining cuproptosis and immunogenic cell death in DLBCL.
Methods:
Pearson's correlation analysis was utilized to acquire lncRNAs associated with cuproptosis and immunogenic cell death. Prognostic biomarker identification and model construction involved the use of univariate Cox regression, least absolute shrinkage and selection operator (LASSO) Cox regression, and multivariate Cox regression. We assessed the predictive capability of the risk model by conducting Kaplan-Meier analysis and time-dependent ROC analysis. The analysis and comparison of immune infiltration and drug sensitivity were conducted in this study. Moreover, RT-qPCR was employed to validate the expression of lncRNAs associated with cuproptosis and immunogenic cell death in DLBCL cell lines.
Results:
We identified 4 prognosis-related lncRNAs (ANKRD10-IT1, HOXB-AS1, LINC00520 and LINC01165) that were correlated with cuproptosis and immunogenic cell death. The model was verified to have a good and independent predictive ability in the prognostic prediction of DLBCL patients. Moreover, significant difference was observed in immune infiltration and drug sensitivity between high- and low-risk groups.
Conclusion:
Our discoveries could enhance the comprehension of the role of cuproptosis and ICD in DLBCL, potentially offering novel viewpoints and knowledge for personalized and precise treatment of DLBCL individuals.
