整合单细胞和批量RNA图谱以揭示谷氨酰胺代谢在多发性骨髓瘤预后和免疫动态中的作用。

Integrating single-cell and bulk RNA profiles to uncover glutamine metabolism's role in prognosis and immune dynamics in multiple myeloma.

作者信息

Zhao Fei, Che Feifei

机构信息

Institute of HematoFlogy, Union Hospital, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.

Department of Hemotology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.

出版信息

BMC Cancer. 2025 May 19;25(1):887. doi: 10.1186/s12885-025-14239-0.

DOI:10.1186/s12885-025-14239-0

PMID:40389878

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12087063/

Abstract

OBJECTIVE

Multiple myeloma (MM) exhibits significant heterogeneity, leading to variable treatment responses and poor clinical outcomes. Glutamine metabolism-related genes (GMRGs) represent critical regulators of tumor biology, yet their prognostic and therapeutic significance in MM remains unexplored. This study aims to identify GMRG-driven tumor signatures and establish their clinical utility as prognostic biomarkers, therapeutic targets and enhancers of drug sensitivity.

METHODS

Integrated transcriptomic and single-cell sequencing analyses of public multi-omics cohorts enabled systematic identification of GMRGs in MM through weighted co-expression network analysis coupled with univariate Cox proportional hazards modeling. Clinically prioritized GMRGs showing elevated expression in patient specimens were functionally validated through proliferation assays and pharmacological sensitivity profiling.

RESULTS

Integrated multi-omics analysis combining single-cell sequencing with bulk transcriptomic profiling and prognostic screening identified 51 prognostic GMRGs, with 10 core signature genes selected for model construction. The risk stratification system demonstrated robust prognostic capacity validated across multiple independent MM cohorts. Pathway enrichment revealed significant involvement in immune system, cell cycle and tumor signaling. MM patient validation identified DLD, SFT2D2, and UBA2 as significantly upregulated genes that promote tumor growth through enhancement of proliferation. Mechanistic investigations via shRNA-mediated knockdown established that DLD and UBA2 silencing significantly enhanced therapeutic efficacy of MM inhibitors.

CONCLUSION

Multicohort-validated GMRGs (DLD/UBA2) drive MM progression and MM inhibitor responses. Clinical upregulation and functional silencing confirm dual therapeutic potential as prognostic biomarkers and drug-sensitizing targets.

摘要

目的

多发性骨髓瘤（MM）表现出显著的异质性，导致治疗反应各异且临床预后较差。谷氨酰胺代谢相关基因（GMRGs）是肿瘤生物学的关键调节因子，但其在MM中的预后和治疗意义仍未得到探索。本研究旨在识别由GMRGs驱动的肿瘤特征，并确立其作为预后生物标志物、治疗靶点和药物敏感性增强剂的临床应用价值。

方法

通过对公共多组学队列进行综合转录组学和单细胞测序分析，采用加权共表达网络分析结合单变量Cox比例风险模型，系统地识别MM中的GMRGs。通过增殖试验和药理敏感性分析，对在患者标本中表达升高的临床优先GMRGs进行功能验证。

结果

将单细胞测序与批量转录组分析及预后筛选相结合的综合多组学分析确定了51个预后GMRGs，并选择了10个核心特征基因用于模型构建。风险分层系统在多个独立的MM队列中验证了强大的预后能力。通路富集分析显示其显著参与免疫系统、细胞周期和肿瘤信号传导。MM患者验证确定DLD、SFT2D2和UBA2为显著上调的基因，它们通过增强增殖促进肿瘤生长。通过shRNA介导的敲低进行的机制研究表明，DLD和UBA2沉默显著增强了MM抑制剂的治疗效果。