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

被引:0
作者
Mei, Nan [1 ]
Gong, Sha [1 ]
Wang, Lizhao [2 ]
Wang, Lu [1 ]
Wang, Jincheng [1 ]
Li, Jianpeng [3 ]
Bao, Yingying [4 ]
Zhang, Huanming [1 ]
Wang, Huaiyu [1 ]
机构
[1] Xi An Jiao Tong Univ, Affiliated Hosp 1, Dept Hematol, 277 West Yanta Rd, Xian 710061, Shaanxi, Peoples R China
[2] First Affiliated Hosp Xian Jiaotong Univ, Dept Hepatobiliary Surg, Xian, Shaanxi, Peoples R China
[3] Xi An Jiao Tong Univ, Affiliated Hosp 1, Dept Urol, Xian, Shaanxi, Peoples R China
[4] Xi An Jiao Tong Univ, Affiliated Hosp 1, Inst Gene & Cell Therapy, Xian, Shaanxi, Peoples R China
来源
BLOOD AND LYMPHATIC CANCER-TARGETS AND THERAPY | 2024年 / 14卷
关键词
multiple myeloma; NK cell-related genes; NK subtypes; prognostic model; ITM2C; NATURAL-KILLER-CELLS; EXPRESSION;
D O I
10.2147/BLCTT.S461529
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
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 ( P <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 ( P <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.
引用
收藏
页码:31 / 48
页数:18
相关论文
共 50 条
  • [31] Identification of the distinctive role of DPT in dilated cardiomyopathy: a study based on bulk and single-cell transcriptomic analysis
    Lu, Yang
    Wu, Qiongfeng
    Liao, Jie
    Zhang, Shaoshao
    Lu, Kai
    Yang, Shuaitao
    Wu, Yuwei
    Dong, Qian
    Yuan, Jing
    Zhao, Ning
    Du, Yimei
    ANNALS OF TRANSLATIONAL MEDICINE, 2021, 9 (18)
  • [32] Prognostic-related genes for pancreatic cancer typing and immunotherapy response prediction based on single-cell sequencing data and bulk sequencing data
    Wang, Xuefeng
    Jiang, Sicong
    Zhou, Xinhong
    Wang, Xiaofeng
    Li, Lan
    Tang, Jianjun
    ONCOLOGY RESEARCH, 2023, 31 (05) : 697 - 714
  • [33] Construction of a prognostic model related to copper dependence in breast cancer by single-cell sequencing analysis
    Guan, Xiao
    Lu, Na
    Zhang, Jianping
    FRONTIERS IN GENETICS, 2022, 13
  • [34] Integrative Analysis of Bulk RNA-Seq and Single-Cell RNA-Seq Unveils Novel Prognostic Biomarkers in Multiple Myeloma
    Zhao, Jing
    Wang, Xiaoning
    Zhu, Huachao
    Wei, Suhua
    Zhang, Hailing
    Ma, Le
    He, Pengcheng
    BIOMOLECULES, 2022, 12 (12)
  • [35] Identification and validation of a prognostic model based on three TLS-Related genes in oral squamous cell carcinoma
    Sun, Bincan
    Gan, Chengwen
    Tang, Yan
    Xu, Qian
    Wang, Kai
    Zhu, Feiya
    CANCER CELL INTERNATIONAL, 2024, 24 (01)
  • [36] Bioinformatics analysis of the tumor microenvironment in melanoma - Constructing a prognostic model based on CD8+T cell-related genes: An observational study
    He, Zhenghao
    Chen, Manli
    Luo, Zhijun
    MEDICINE, 2024, 103 (32) : e38924
  • [37] Combined analysis of bulk and single-cell RNA sequencing reveals novel natural killer cell-related prognostic biomarkers for predicting immunotherapeutic response in hepatocellular carcinoma
    Zhang, Kai
    Yuan, Enwu
    FRONTIERS IN IMMUNOLOGY, 2023, 14
  • [38] Single-cell transcriptomic analysis of PB and BM NK cells from severe aplastic anaemia patients
    Liu, Chunyan
    Chen, Yingying
    Lu, Dan
    Liu, Bingnan
    Zhang, Tian
    Deng, Ling
    Liu, Zixuan
    Zhong, Congwei
    Fu, Rong
    CLINICAL AND TRANSLATIONAL MEDICINE, 2022, 12 (12):
  • [39] Single-cell transcriptomic analysis reveals a novel cell state and switching genes during hepatic stellate cell activation in vitro
    Wang, Hua
    Zheng, Shaoping
    Jiang, Hongbo
    Wang, Xuejia
    Zhou, Fengqin
    Weng, Zhihong
    JOURNAL OF TRANSLATIONAL MEDICINE, 2022, 20 (01)
  • [40] Identification and analysis of a cell communication prognostic signature for oral squamous cell carcinoma at bulk and single-cell levels
    Zhang, Xingwei
    Yang, Fan
    Dong, Chen
    Li, Baojun
    Zhang, Shuo
    Jiao, Xiaohui
    Chen, Dong
    JOURNAL OF CELLULAR AND MOLECULAR MEDICINE, 2024, 28 (22)