Potential biomarker α2M for multiple myeloma in remission phase: quantitative proteomics and bioinformatics analysis
10.3760/cma.j.cn115356-20241125-00179
- VernacularTitle:多发性骨髓瘤缓解期潜在生物标志物α2M：定量蛋白质组学和生物信息学分析
- Author:
Xiaoxiao WU
1
;
Jianying GUO
;
Haiteng DENG
;
Wenming CHEN
Author Information
1. 首都医科大学附属北京朝阳医院血液科，北京 100020
- Keywords:
Multiple myeloma;
Alpha-macroglobulins;
Proteomics;
Computational biology;
Tumor markers, biological
- From:
Journal of Leukemia & Lymphoma
2025;34(8):481-488
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the biomarkers associated with multiple myeloma in remission phase (MM-RP) in order to provide potential indicators for disease monitoring and prognostic evaluation.Methods:Bone marrow blood samples were prospectively collected from 9 newly diagnosed multiple myeloma (NDMM) patients and 9 MM-RP patients in Beijing Chaoyang Hospital of Capital Medical University from January to October 2020. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed for proteomic analysis in 3 independent experiments, each containing 3 paired NDMM and MM-RP samples. Differentially expressed proteins (DEP) consistently identified across all 3 experiments were considered potential MM-RP biomarkers. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database were used for enrichment analyses of the biological functions of these potential biomarkers. Protein-protein interaction (PPI) networks were constructed using the STRING 11.5 database, and α-2-macroglobulin (α2M) was identified as a hub protein. The UCSC Xena database was utilized, and the overall survival (OS) of MM patients with high or low α2M expression [stratified by the average level of α2M transcriptome sequencing (RNA-seq) data] was analyzed by using Kaplan-Meier. A multivariate Cox proportional hazards model adjusted for age, International Staging System (ISS) stage and treatment regimen was employed to analyze the impact of α2M expression on OS of MM patients. The Human Protein Atlas (HPA) database was used to examine α2M mRNA expression patterns in 33 cancer types. The correlation of drug sensitivity [50% inhibiting concentration ( IC50)] with α2M expression was assessed using pharmacogenomic data from the GSCALite platform. Results:Among 104 proteins consistently identified in 3 proteomic experiments, 34 DEP were found between NDMM and MM-RP (∣fold change∣>1.0 and P < 0.05), including 25 upregulated DEP and 9 downregulated DEP in MM-RP. GO analysis showed that the identified MM-RP potential markers were mainly involved in biological processes such as complement activation and humoral immune response, and the molecular functions mainly involved serine hydrolase activity, serine peptidase activity, etc., and were mainly distributed in secretory granules, blood particles, and other parts; KEGG enrichment analysis showed that biomarkers were mainly enriched in the complement and coagulation cascade pathways. In the human α2M PPI network constructed using data from the STRING database, there were 10 proteins that interacted with α2M, with a connectivity of 7.82, and had direct interactions with 71% of the proteins in the network, the betweenness centrality value was 0.06, and the closeness centrality value was 1, indicating significant network centrality feature of α2M. In the constructed PPI network of α2M protein and DEP screened by proteomics, there were interactions between α2M protein and 11 MM-RP markers screened by proteomics, and the betweenness centrality value of α2M reached 0.50, the closeness centrality value was 0.67, indicating that α2M was at the core position of the PPI network. UCSC Xena analysis revealed that MM patients with low α2M expression (523 cases) had worse OS than those with high expression (336 cases) ( P =0.024). Multivariate Cox regression analysis confirmed that low α2M expression was an independent risk factor for poor OS (compared with high α2M expression: HR = 0.726, 95% CI: 0.550-0.960, P = 0.024). HPA database analysis demonstrated that the α2M expression levels were variable in different types of cancer, its level in glioblastoma multiforme, clear cell renal cell carcinoma, and stomach adenocarcinoma was higher than that in normal tissues (all P < 0.05), and its level in urothelial carcinoma, breast cancer and cervical squamous cell carcinoma was lower than that in normal tissues (all P < 0.05). GSCALite analysis revealed negative correlations between α2M expression level and IC50 values of B-Raf kinase inhibitors, B-Raf V600E inhibitors and dabrafenib mesylate. Conclusions:α2M expression level in MM-RP patients is lower than that in NDMM patients, and its expression level may be related to the prognosis of patients, which is expected to become a novel biomarker reflecting the disease activity of MM.
