Development and validation of a combined cuproptosis and immunogenic cell death prognostic model for diffuse large B-cell lymphoma

Abstract

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.

Keywords: DLBCL; cuproptosis; immunogenic cell death; lncRNA; prognostic model.

Figure 1

Identification of CRIRLs. (A) Sankey chart illustrating the relationship between CRGs and CRLs. (B) Sankey diagram of relationship between IRGs and IRLs. (C) Venn diagram of CRLs and IRLs. (D) The prognostic CRIRLs were analyzed using univariate Cox regression. (E, F) LASSO regression analysis displays the minimum lambda and optimal coefficients of prognostic CRIRLs.

Figure 2

Developing a predictive risk model using the CRIRLs in DLBCL. (A) Distribution of the patients’ normalized risk score. (B) Analysis of clinical prognosis in low-risk and high-risk groups of DLBCL samples. (C) Patients’ survival status along with their risk score. (D) t-SNE analysis. (E) PCA analysis. (F) The heatmap diagram of the expression of 4 prognostic CRIRLs.

Figure 3

Validation of the prognostic risk signature. (A, B) Stratification of CRIRLs into risk subgroups in training cohort. (C, D) Stratification of CRIRLs into risk subgroups in validation cohort. (E, F) Analysis of clinical prognosis outcomes for risk subgroups in training cohort and validation set of CRIRLs. (G, H) Expression of the 4 prognostic CRIRLs in training cohort and validation set.

Figure 4

Survival analysis of CRIRLs prognostic signature. (A) Age ≥65 (B) Age <65 (C) Male (D) Female (E) Stage I+II (F) Stage III+IV.

Figure 5

Independent prognostic analysis of CRIRLs score. (A, B) HR and P values of CRIRLs score and different clinical pathological features were evaluated based on univariate and multivariate Cox analyses. (C) Diagnostic effectiveness evaluation of CRIRLs score and clinical pathological features. (D) Time-dependent ROC curve shows the 1-, 3-, and 5-year AUC.

Figure 6

Relationship between the risk model and immune cell infiltration. (A) Fraction of 23 immune cells in high- and low-risk groups. (B) The expression level of immune checkpoints in high- and low-risk groups. (C) ESTIMATE score. (D) Immune score. (E) Stromal score. (F) Tumor purity.

Figure 7

Drug sensitivity analysis. (A) Crizotinib, (B) Dasatinib, (C) GW843682X, (D) MG-132, (E) Paclitaxel, (F) Rapamycin, (G) Saracatinib, (H) VX-680, (I) Sunitinib and (J) TAE684. (K–T) Correlation analysis of the risk score and drug sensitivity (IC50).

Figure 8

Validation the expression of CRIRLs. (A) ANKRD10-IT1, (B) HOXB-AS1, (C) LINC00520, (D) LINC01165 expression in human B lymphoid cell line and human DLBCL cell lines. ^*P < 0.05; ^**P < 0.01; ^***P < 0.001.