利用单细胞和转录组数据分析鉴定基于NK细胞相关基因的多发性骨髓瘤预后模型

Identification of a Prognostic Model Based on NK Cell-Related Genes in Multiple Myeloma Using Single-Cell and Transcriptomic Data Analysis.

作者信息

Mei Nan, Gong Sha, Wang Lizhao, Wang Lu, Wang Jincheng, Li Jianpeng, Bao Yingying, Zhang Huanming, Wang Huaiyu

机构信息

Department of Hematology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China.

Department of Breast Surgery, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China.

出版信息

Blood Lymphat Cancer. 2024 Jun 4;14:31-48. doi: 10.2147/BLCTT.S461529. eCollection 2024.

DOI:10.2147/BLCTT.S461529

PMID:38854627

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11162243/

Abstract

BACKGROUND

Multiple myeloma (MM), an incurable plasma cell malignancy. The significance of the relationship between natural killer (NK) cell-related genes and clinical factors in MM remains unclear.

METHODS

Initially, we extracted NK cell-related genes from peripheral blood mononuclear cells (PBMC) of healthy donors and MM samples by employing single-cell transcriptome data analysis in TISCH2. Subsequently, we screened NK cell-related genes with prognostic significance through univariate Cox regression analysis and protein-protein interaction (PPI) network analysis. Following the initial analyses, we developed potential subtypes and prognostic models for MM using consensus clustering and lasso regression analysis. Additionally, we conducted a correlation analysis to explore the relationship between clinical features and risk scores. Finally, we constructed a weighted gene co-expression network analysis (WGCNA) and identified differentially expressed genes (DEGs) within the MM cohort.

RESULTS

We discovered that 153 NK cell-related genes were significantly associated with the prognosisof MM patients ( <0.05). Patients in NK cluster A exhibited poorer survival outcomes compared to those in cluster B. Furthermore, our NK cell-related genes risk model revealed that patients with a high risk score had significantly worse prognoses ( <0.05). Patients with a high risk score were more likely to exhibit adverse clinical markers. Additionally, the nomogram based on NK cell-related genes demonstrated strong prognostic performance. The enrichment analysis indicated that immune-related pathways were significantly correlated with both the NK subtypes and the NK cell-related genes risk model. Ultimately, through the combined use of WGCNA and DEGs analysis, and by employing Venn diagrams, we determined that ITM2C is an independent prognostic marker for MM patients.

CONCLUSION

In this study, we developed a novel model based on NK cell-related genes to stratify the prognosis of MM patients. Notably, higher expression levels of ITM2C were associated with more favorable survival outcomes in these patients.

摘要

背景

多发性骨髓瘤（MM）是一种无法治愈的浆细胞恶性肿瘤。自然杀伤（NK）细胞相关基因与MM临床因素之间关系的意义仍不清楚。

方法

首先，我们通过在TISCH2中进行单细胞转录组数据分析，从健康供体和MM样本的外周血单个核细胞（PBMC）中提取NK细胞相关基因。随后，我们通过单变量Cox回归分析和蛋白质-蛋白质相互作用（PPI）网络分析筛选出具有预后意义的NK细胞相关基因。在初步分析之后，我们使用一致性聚类和套索回归分析为MM开发了潜在的亚型和预后模型。此外，我们进行了相关性分析，以探讨临床特征与风险评分之间的关系。最后，我们构建了加权基因共表达网络分析（WGCNA）并鉴定了MM队列中的差异表达基因（DEG）。

结果

我们发现153个NK细胞相关基因与MM患者的预后显著相关（<0.05）。与B组患者相比，NK A簇中的患者生存结果较差。此外，我们的NK细胞相关基因风险模型显示，高风险评分的患者预后明显更差（<0.05）。高风险评分的患者更有可能表现出不良临床标志物。此外，基于NK细胞相关基因的列线图显示出强大的预后性能。富集分析表明，免疫相关途径与NK亚型和NK细胞相关基因风险模型均显著相关。最终，通过联合使用WGCNA和DEG分析，并使用维恩图，我们确定ITM2C是MM患者的独立预后标志物。