Development and validation of a cuproptosis-associated prognostic model for diffuse large B-cell lymphoma

Abstract

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous disease. Therefore, more reliable biomarkers are required to better predict the prognosis of DLBCL. Cuproptosis is a novel identified form of programmed cell death (PCD) that is different from oxidative stress-related cell death (e.g., apoptosis, ferroptosis, and necroptosis) by Tsvetkov and colleagues in a recent study released in Science. Cuproptosis is copper-dependent PCD that is closely tied to mitochondrial metabolism. However, the prognostic value of cuproptosis-related genes (CRGs) in DLBCL remains to be further elucidated. In the present study, we systematically evaluated the molecular changes of CRGs in DLBCL and found them to be associated with prognosis. Subsequently, based on the expression profiles of CRGs, we characterized the heterogeneity of DLBCL by identifying two distinct subtypes using consensus clustering. Two isoforms exhibited different survival, biological functions, chemotherapeutic drug sensitivity, and immune microenvironment. After identifying differentially expressed genes (DEGs) between CRG clusters, we built a prognostic model with the Least absolute shrinkage and selection operator (LASSO) Cox regression analysis and validated its prognostic value by Cox regression analysis, Kaplan-Meier curves, and receiver operating characteristic (ROC) curves. In addition, the risk score can predict clinical characteristics, levels of immune cell infiltration, and prognosis. Furthermore, a nomogram incorporating clinical features and risk score was generated to optimize risk stratification and quantify risk assessment. Compared to the International Prognostic Index (IPI), the nomogram has demonstrated more accuracy in survival prediction. Furthermore, we validated the prognostic gene expression levels through external experiments. In conclusion, cuproptosis-related gene signature can serve as a potential prognostic predictor in DLBCL patients and may provide new insights into cancer therapeutic targets.

Prognostic utility of preoperative platelet‐to‐albumin ratio in surgically treated oral cavity cancer patients

“…Wang et al studied the data of patients diagnosed with diffuse large B-cell lymphoma and observed a U-shaped relationship between the PAR and progression-free survival; PARs greater than 8.6 or less than 2.7 were associated with shorter progression-free survival. 31 Because platelets constitute an inflammatory biomarker, both decreased and increased platelet counts can reflect immune dysfunction and adverse survival, which can be attributed to the potential nonlinear association between the PAR and prognosis in patients with lymphoma.…”

“…Considering the effects of factors such as infection and chronic hepatic dysfunction on serum platelet counts and albumin levels, 30 the PAR, which combines both parameters, may offer reduced measurement variability and enhance reliability when compared to using either parameter alone. Wang et al studied the data of patients diagnosed with diffuse large B‐cell lymphoma and observed a U‐shaped relationship between the PAR and progression‐free survival; PARs greater than 8.6 or less than 2.7 were associated with shorter progression‐free survival 31 . Because platelets constitute an inflammatory biomarker, both decreased and increased platelet counts can reflect immune dysfunction and adverse survival, which can be attributed to the potential nonlinear association between the PAR and prognosis in patients with lymphoma.…”

GPX4 is a potential diagnostic and therapeutic biomarker associated with diffuse large B lymphoma cell proliferation and B cell immune infiltration

“…To confirm that GPX4 is a potential oncogene, we analyzed GPX4's pan oncogene expression level through the TCGA database. Gene Expression Profiling Interaction Analysis (GEPIA, http://gepia.cancer-pku.cn/index/html ) It can be used to evaluate the RNA that expression data of 8587 normal TCGA samples and 9736 tumor samples, as well as the genotype tissue expression (GTEx) database [ 21 , 22 ]. When obtaining GPX4's gene expression profile, ANOVA method was used to compare with the following thresholds: | log2FC | cutof = 1, LogScale = log2 (TPM+1) and q value cutof = 0.01 [ 23 ].…”

“…Due to the convenience and ease of using blood for disease diagnosis in clinical practice, we evaluated the diagnostic performance and expression of GPX4 in DLBCL's peripheral blood using the GSE83632 dataset. In order to further evaluate GPX4's expression at DLBCL single cell transcriptome's level, we evaluated GPX4's expression level at DLBCL single cell transcription's level through single cell data GSE175510 [ 22 ].…”

Identification of a novel cuproptosis‐related gene signature for multiple myeloma diagnosis

“…Previous reports have described the functional roles of cuproptosis‐related genes (CRGs) in cancer development. For instance, CRGs were used to predict clinical outcome and immune response in hematological malignancies, including acute myeloid leukemia 21,22 and diffuse large B‐cell lymphoma 23 . The results of recent studies have emphasized the potential utility of CRGs in the development of prognostic models for MM 24,25 .…”