The Predictive Value of Monocytes in Immune Microenvironment and Prognosis of Glioma Patients Based on Machine Learning.

Journal: Frontiers in immunology
PMID: 33959130

Abstract

Gliomas are primary malignant brain tumors. Monocytes have been proved to actively participate in tumor growth. Weighted gene co-expression network analysis was used to identify meaningful monocyte-related genes for clustering. Neural network and SVM were applied for validating clustering results. Somatic mutation and copy number variation were used for defining the features of identified clusters. Differentially expressed genes (DEGs) between the stratified groups after performing elastic regression and principal component analyses were used for the construction of risk scores. Monocytes were associated with glioma patients' survival and exhibited high predictive value. The prognostic value of risk score in glioma was validated by the abundant expression of immune checkpoint and metabolic profile. Additionally, high risk score was positively associated with the expression of immunogenic and antigen presenting factors, which indicated high immune infiltration. A prognostic model based on risk score demonstrated high accuracy rate of receiver operating characteristic curves. Compared with previous studies, our research dissected functional roles of monocytes from large-scale analysis. Findings of our analyses strongly support an immune modulatory and prognostic role of monocytes in glioma progression. Notably, monocyte could be an effective predictor for therapy responses of glioma patients.

Authors

  • Nan Zhang
    Department of Pulmonary and Critical Care Medicine II, Emergency General Hospital, Beijing, China.
  • Ziyu Dai
    Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
  • Wantao Wu
    Department of Oncology, Xiangya Hospital, Central South University, Changsha, China.
  • Zeyu Wang
    Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
  • Hui Cao
  • Yakun Zhang
    College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
  • Zhanchao Wang
    Department of Orthopaedics, Changzheng Hospital, Naval Medical University, Shanghai, China.
  • Hao Zhang
    College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China.
  • Quan Cheng
    Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.

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