Identification of a novel monocyte/macrophage-related gene signature for predicting survival and immune response in acute myeloid leukemia

被引:0
|
作者
Zhan, Yun [1 ,2 ,4 ]
Ma, Sixing [2 ,3 ]
Zhang, Tianzhuo [1 ,4 ]
Zhang, Luxin [1 ,4 ]
Zhao, Peng [1 ,4 ]
Yang, Xueying [1 ,4 ]
Liu, Min [1 ,4 ]
Cheng, Weiwei [1 ,4 ]
Li, Ya [1 ,4 ]
Wang, Jishi [1 ,2 ,4 ]
机构
[1] Guizhou Med Univ, Dept Hematol, Affiliated Hosp, Guiyang 550004, Peoples R China
[2] Guizhou Med Univ, Dept Clin Med Sch, Guiyang 550004, Peoples R China
[3] Guizhou Med Univ, Dept Vasc Surg, Affiliated Hosp, Guiyang 550004, Peoples R China
[4] Guizhou Med Univ, Guizhou Prov Inst Hematol, Guizhou Prov Hematopoiet Stem Cell Transplantat C, Affiliated Hosp, Guiyang 550004, Peoples R China
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
基金
中国国家自然科学基金;
关键词
Monocyte; macrophage; Tumor immune microenvironment; Immune response; AML; CHECKPOINT BLOCKADE; DISCOVERY; CELLS;
D O I
10.1038/s41598-024-64567-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Acute myeloid leukemia (AML) is a heterogeneous hematological tumor with poor immunotherapy effect. This study was to develop a monocyte/macrophage-related prognostic risk score (MMrisk) and identify new therapeutic biomarkers for AML. We utilized differentially expressed genes (DEGs) in combination with single-cell RNA sequencing to identify monocyte/macrophage-related genes (MMGs). Eight genes were selected for the construction of a MMrisk model using univariate Cox regression analysis and LASSO regression analysis. We then validated the MMrisk on two GEO datasets. Lastly, we investigated the immunologic characteristics and advantages of immunotherapy and potential targeted drugs for MMrisk groups. Our study identified that the MMrisk is composed of eight MMGs, including HOPX, CSTB, MAP3K1, LGALS1, CFD, MXD1, CASP1 and BCL2A1. The low MMrisk group survived longer than high MMrisk group (P < 0.001). The high MMrisk group was positively correlated with B cells, plasma cells, CD4 memory cells, Mast cells, CAFs, monocytes, M2 macrophages, Endothelial, tumor mutation, and most immune checkpoints (PD1, Tim-3, CTLA4, LAG3). Furthermore, drug sensitivity analysis showed that AZD.2281, Axitinib, AUY922, ABT.888, and ATRA were effective in high-risk MM patients. Our research shows that MMrisk is a potential biomarker which is helpful to identify the molecular characteristics of AML immunology.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Identification of novel cell glycolysis related gene signature predicting survival in patients with endometrial cancer
    Wang, Zi-Hao
    Zhang, Yun-Zheng
    Wang, Yu-Shan
    Ma, Xiao-Xin
    CANCER CELL INTERNATIONAL, 2019, 19 (01)
  • [42] Novel Gene Signature Reveals Prognostic Model in Acute Myeloid Leukemia
    Qu, Ying
    Zhang, Shuying
    Qu, Yanzhang
    Guo, Heng
    Wang, Suling
    Wang, Xuemei
    Huang, Tianjiao
    Zhou, Hong
    FRONTIERS IN GENETICS, 2020, 11
  • [43] Identification of novel cell glycolysis related gene signature predicting survival in patients with breast cancer
    Jiang, Feng
    Wu, Chuyan
    Wang, Ming
    Wei, Ke
    Wang, Jimei
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [44] Identification of novel cell glycolysis related gene signature predicting survival in patients with breast cancer
    Feng Jiang
    Chuyan Wu
    Ming Wang
    Ke Wei
    Jimei Wang
    Scientific Reports, 11
  • [45] Identification of a novel lipid metabolism-related gene signature for predicting colorectal cancer survival
    Huang, Yanpeng
    Zhou, Jinming
    Zhong, Haibin
    Xie, Ning
    Zhang, Fei-Ran
    Zhang, Zhanmin
    FRONTIERS IN GENETICS, 2022, 13
  • [46] Development and validation of a novel M1 macrophage-related gene prognostic signature for lung cancer
    Zhu, Shumin
    Li, Yanming
    Mao, Yafei
    Li, Xinyuan
    Gao, Shichao
    Geng, Yulan
    Ma, Jin
    JOURNAL OF THORACIC DISEASE, 2023, 15 (03) : 1267 - 1278
  • [47] A novel N7-Methylguanine-related gene signature for predicting prognosis in acute myeloid leukemia: bioinformatic analysis and experimental verification
    Zhao, Ranran
    Yang, Lulu
    Liu, Chenchen
    Jiang, Ruoyu
    Huang, Qianlei
    Wang, Qin
    Wu, Xiaojin
    HEMATOLOGY, 2024, 29 (01)
  • [48] Identification and validation of M2 macrophage-related gene signature as a novel prognostic model for head and neck squamous cell carcinoma
    He, Shengmei
    Chen, Huarong
    Li, Changya
    Feng, Bao
    Zhang, Ruizhe
    Zhao, Houyu
    Zhuo, Xianlu
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [49] Identification of immune related gene signature for predicting prognosis of cholangiocarcinoma patients
    Zhang, Zi-jian
    Huang, Yun-peng
    Liu, Zhong-tao
    Wang, Yong-xiang
    Zhou, Hui
    Hou, Ke-xiong
    Tang, Ji-wang
    Xiong, Li
    Wen, Yu
    Huang, Sheng-fu
    FRONTIERS IN IMMUNOLOGY, 2023, 14
  • [50] Identification and validation of a siglec-based and aging-related 9-gene signature for predicting prognosis in acute myeloid leukemia patients
    Shi, Huiping
    Gao, Liang
    Zhang, Weili
    Jiang, Min
    BMC BIOINFORMATICS, 2022, 23 (01)