Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment
Monocytes are pivotal immune cells in eliciting specific immune responses and can exert a significant impact on the progression, prognosis, and immunotherapy of intracranial aneurysms (IAs). The objective of this study was to identify monocyte/macrophage (Mo/MΦ)-associated gene signatures to elucida...
| Published in: | Frontiers in Immunology |
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| Main Authors: | , , , , , , , , |
| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-06-01
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1397475/full |
| _version_ | 1850373372668542976 |
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| author | Yifan Xu Pin Guo Guipeng Wang Xiaojuan Sun Chao Wang Huanting Li Zhenwen Cui Pining Zhang Yugong Feng |
| author_facet | Yifan Xu Pin Guo Guipeng Wang Xiaojuan Sun Chao Wang Huanting Li Zhenwen Cui Pining Zhang Yugong Feng |
| author_sort | Yifan Xu |
| collection | DOAJ |
| container_title | Frontiers in Immunology |
| description | Monocytes are pivotal immune cells in eliciting specific immune responses and can exert a significant impact on the progression, prognosis, and immunotherapy of intracranial aneurysms (IAs). The objective of this study was to identify monocyte/macrophage (Mo/MΦ)-associated gene signatures to elucidate their correlation with the pathogenesis and immune microenvironment of IAs, thereby offering potential avenues for targeted therapy against IAs. Single-cell RNA-sequencing (scRNA-seq) data of IAs were acquired from the Gene Expression Synthesis (GEO) database. The significant infiltration of monocyte subsets in the parietal tissue of IAs was identified using single-cell RNA sequencing and high-dimensional weighted gene co-expression network analysis (hdWGCNA). The integration of six machine learning algorithms identified four crucial genes linked to these Mo/MΦ. Subsequently, we developed a multilayer perceptron (MLP) neural model for the diagnosis of IAs (independent external test AUC=1.0, sensitivity =100%, specificity =100%). Furthermore, we employed the CIBERSORT method and MCP counter to establish the correlation between monocyte characteristics and immune cell infiltration as well as patient heterogeneity. Our findings offer valuable insights into the molecular characterization of monocyte infiltration in IAs, which plays a pivotal role in shaping the immune microenvironment of IAs. Recognizing this characterization is crucial for comprehending the limitations associated with targeted therapies for IAs. Ultimately, the results were verified by real-time fluorescence quantitative PCR and Immunohistochemistry. |
| format | Article |
| id | doaj-art-73b98ef8f0244a50b795a4e86d8aab82 |
| institution | Directory of Open Access Journals |
| issn | 1664-3224 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| spelling | doaj-art-73b98ef8f0244a50b795a4e86d8aab822025-08-19T23:00:26ZengFrontiers Media S.A.Frontiers in Immunology1664-32242024-06-011510.3389/fimmu.2024.13974751397475Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironmentYifan Xu0Pin Guo1Guipeng Wang2Xiaojuan Sun3Chao Wang4Huanting Li5Zhenwen Cui6Pining Zhang7Yugong Feng8Department of Neurosurgery, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Neurosurgery, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Urology, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Oncology, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Neurosurgery, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Neurosurgery, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Neurosurgery, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, ChinaDepartment of Neurosurgery, The Affiliated Hospital of Qingdao University, Qingdao, ChinaMonocytes are pivotal immune cells in eliciting specific immune responses and can exert a significant impact on the progression, prognosis, and immunotherapy of intracranial aneurysms (IAs). The objective of this study was to identify monocyte/macrophage (Mo/MΦ)-associated gene signatures to elucidate their correlation with the pathogenesis and immune microenvironment of IAs, thereby offering potential avenues for targeted therapy against IAs. Single-cell RNA-sequencing (scRNA-seq) data of IAs were acquired from the Gene Expression Synthesis (GEO) database. The significant infiltration of monocyte subsets in the parietal tissue of IAs was identified using single-cell RNA sequencing and high-dimensional weighted gene co-expression network analysis (hdWGCNA). The integration of six machine learning algorithms identified four crucial genes linked to these Mo/MΦ. Subsequently, we developed a multilayer perceptron (MLP) neural model for the diagnosis of IAs (independent external test AUC=1.0, sensitivity =100%, specificity =100%). Furthermore, we employed the CIBERSORT method and MCP counter to establish the correlation between monocyte characteristics and immune cell infiltration as well as patient heterogeneity. Our findings offer valuable insights into the molecular characterization of monocyte infiltration in IAs, which plays a pivotal role in shaping the immune microenvironment of IAs. Recognizing this characterization is crucial for comprehending the limitations associated with targeted therapies for IAs. Ultimately, the results were verified by real-time fluorescence quantitative PCR and Immunohistochemistry.https://www.frontiersin.org/articles/10.3389/fimmu.2024.1397475/fullintracranial aneurysmsingle-cell sequencingmachine learningimmune microenvironmenthub genes |
| spellingShingle | Yifan Xu Pin Guo Guipeng Wang Xiaojuan Sun Chao Wang Huanting Li Zhenwen Cui Pining Zhang Yugong Feng Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment intracranial aneurysm single-cell sequencing machine learning immune microenvironment hub genes |
| title | Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment |
| title_full | Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment |
| title_fullStr | Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment |
| title_full_unstemmed | Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment |
| title_short | Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment |
| title_sort | integrated analysis of single cell sequencing and machine learning identifies a signature based on monocyte macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment |
| topic | intracranial aneurysm single-cell sequencing machine learning immune microenvironment hub genes |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2024.1397475/full |
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