B4GALT3 as a Key Glycosyltransferase Gene in Multiple Myeloma Progression: Insights From Bioinformatics, Machine Learning, and Experimental Validation.

IF 3 2区 医学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Apeng Yang, Mengying Ke, Lin Feng, Ye Yang, Junmin Chen, Zhiyong Zeng
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引用次数: 0

Abstract

Glycosylation abnormalities are critical in the progression of various cancers. However, their role in the onset and prognosis of multiple myeloma (MM) remains underexplored. This study aims to identify glycosyltransferase (GT)-related biomarkers and investigate their underlying mechanisms in MM. GT-related genes were extracted from the MMRF-CoMMpass and GSE57317 data sets. Potential biomarkers were identified using Cox regression and Lasso analyses. A glycosyltransferase-related prognostic model (GTPM) was developed by evaluating 113 machine learning algorithm combinations. The expression of B4GALT3, a key gene identified through this model, was analyzed in MM bone marrow samples using immunohistochemistry, quantitative PCR, and Western blot. Functional roles of B4GALT3 in MM cell behavior were assessed through knockdown experiments, and its mechanism of action was investigated. The GTPM stratified MM patients into high- and low-risk groups, with significantly better survival in the low-risk group (HR = 55.94, 95% CI = 40.48-77.31, p < 0.001). The model achieved AUC values of 0.98 and 0.99 for 1- and 3-year overall survival, outperforming existing gene signatures (including EMC92, UAMS70, and UAMS17). B4GALT3 expression was significantly elevated in advanced MM stages (p < 0.001) and correlated with poorer survival. Knockdown of B4GALT3 reduced MM cell proliferation, invasion, and increased apoptosis. Mechanistic analyses revealed that B4GALT3 modulates MM cell behavior via the Wnt/β-catenin/GRP78 pathway, primarily by regulating endoplasmic reticulum (ER) stress. This study developed a novel GTPM for predicting survival in MM and identified B4GALT3 as a key gene influencing disease progression. Experimental evidence highlights B4GALT3's role in modulating ER stress and Wnt/β-catenin pathways, positioning it as a potential prognostic biomarker and therapeutic target in MM.

B4GALT3是多发性骨髓瘤进展中的关键糖基转移酶基因:来自生物信息学、机器学习和实验验证的见解。
糖基化异常在各种癌症的进展中是至关重要的。然而,它们在多发性骨髓瘤(MM)发病和预后中的作用仍未得到充分探讨。本研究旨在鉴定糖基转移酶(GT)相关的生物标志物,并探讨其在MM中的潜在机制。从MMRF-CoMMpass和GSE57317数据集中提取GT相关基因。使用Cox回归和Lasso分析确定潜在的生物标志物。通过评估113种机器学习算法组合,建立了糖基转移酶相关预后模型(GTPM)。采用免疫组织化学、定量PCR、Western blot等方法分析MM骨髓样本中B4GALT3基因的表达。通过敲低实验评估B4GALT3在MM细胞行为中的功能作用,并探讨其作用机制。GTPM将MM患者分为高危组和低危组,低危组患者生存率显著提高(HR = 55.94, 95% CI = 40.48-77.31, p
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来源期刊
Molecular Carcinogenesis
Molecular Carcinogenesis 医学-生化与分子生物学
CiteScore
7.30
自引率
2.20%
发文量
112
审稿时长
2 months
期刊介绍: Molecular Carcinogenesis publishes articles describing discoveries in basic and clinical science of the mechanisms involved in chemical-, environmental-, physical (e.g., radiation, trauma)-, infection and inflammation-associated cancer development, basic mechanisms of cancer prevention and therapy, the function of oncogenes and tumors suppressors, and the role of biomarkers for cancer risk prediction, molecular diagnosis and prognosis.
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