Predictive potential of cuproptosis-related genes in multiple myeloma: Comprehensive analysis based on bone marrow whole-genome sequencing

Abstract

Abstract Purpose: The primary objective of this study was to identify potential CRGs in patients with MM and develop a predictive model to enhance prognostic outcomes for individuals with MM. Methods: We leveraged transcriptome sequencing data from patients with MM, combined with clinical information from the TCGA-MMRF dataset and the GSE4581 dataset from the GEO database. Through analysis, we pinpointed three genes—CDKN2A, PDE3B, and UBE2D1 that exhibited a significant association with the prognosis of patients with MM. This association was confirmed through a combination of univariate and multivariate Cox regression analyses. Subsequently, we employed LASSO-Cox regression analysis to construct a risk-prognostic model centered around these three CRGs. Results: Notably, the model revealed that high-risk patients with MM experienced significantly shorter overall survival times. Intriguingly, We have unveiled a propensity for high-risk patients with MM to develop an immunosuppressive tumor microenvironment. Finally, to substantiate our findings, we conducted in-depth examinations of the expression of these three CRGs at the cellular level using quantitative reverse transcription–polymerase chain reaction and Western blotting. Conclusion: Our research collectively reveals the molecular scenery in the MM microenvironment through the development of a prognostic model focused on CRGs.