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Data Sheet 1_Development of a mitochondria-related gene signature for prognostic assessment in diffuse large B cell lymphoma.docx

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Development_of_a_mitochondria-related_gene_signature_for_prognostic_assessment_in_diffuse_large_B_cell_lymphoma_docx/28631966
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BackgroundMitochondria-related genes (MitoRGs) play a critical role in the pathogenesis of various cancer types. This study aims to develop a novel prognostic model based on a MitoRGs signature for patients with diffuse large B cell lymphoma (DLBCL). MethodsClinical data and gene expression profiles of DLBCL patients were obtained from four datasets in the Gene Expression Omnibus (GEO) database. The Least Absolute Shrinkage and Selection Operator (Lasso) Cox regression analysis, along with multivariate Cox regression analysis, was employed to develop a prognostic MitoRGs signature for patients with DLBCL within the training cohort. The prognostic efficacy of the model was assessed using Kaplan-Meier survival analysis and Receiver Operating Characteristic (ROC) curve analysis. The validation cohorts were used to substantiate the model’s predictive capability. Single-sample gene set enrichment analysis (ssGSEA) was employed to examine immune infiltration across various risk groups, and the sensitivities to potential therapeutic agents for patients with DLBCL were also assessed. The role of the mitochondrial-related gene PCK2 in cell proliferation and apoptosis was investigated under varying glucose concentrations. ResultsAn eight-MitoRG signature exhibited independent prognostic significance and robust predictive capability for the survival outcomes of DLBCL patients. Notably, it effectively predicted prognosis across various DLBCL patient subgroups and enhanced the prognostic utility of the International Prognostic Index (IPI) score. Analyses utilizing ssGSEA and assessments of drug sensitivities identified distinct patterns of immune infiltration and differential responses to therapeutic agents among patients stratified into various risk groups. Moreover, a prognostic nomogram integrating age, IPI score, and MitoRGs signature was further developed, demonstrating enhanced prognostic accuracy and clinical applicability for DLBCL patients. In addition, research on phosphoenolpyruvate carboxykinase 2 (PCK2) indicated that silencing PCK2 expression inhibits cellular proliferation and induces apoptosis under conditions of low glucose. ConclusionWe developed an innovative prognostic MitoRGs signature to predict outcomes and enhance the prognostic utility of the IPI score in DLBCL, offering a novel perspective for the treatment of DLBCL.
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2025-03-20
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