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The Heterogeneity of Tumour-Associated Macrophages Contributes to the Recurrence and Outcomes of Glioblastoma Patients
Cellular heterogeneity and immune cell molecular phenotypes may be involved in the malignant progression of glioblastoma (GBM). In this study, we aimed to know whether the heterogeneity of tumour-associated macrophages contributes to the recurrence and outcomes of glioblastoma patients. Single-cell...
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Published in: | Journal of molecular neuroscience 2023, Vol.73 (1), p.1-14 |
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description | Cellular heterogeneity and immune cell molecular phenotypes may be involved in the malignant progression of glioblastoma (GBM). In this study, we aimed to know whether the heterogeneity of tumour-associated macrophages contributes to the recurrence and outcomes of glioblastoma patients. Single-cell RNA sequencing (scRNA-Seq) data were used to assess the heterogeneity of CD45 + immune cells in recurrent GBM and analyse differentially expressed genes (DEGs) in master cells. Then, a prognostic signature based on the identified DEGs was established and validated, the correlation between risk score and tumour microenvironment (TME) was explored. The correlation between immune infiltration and
LGMN
, an important DEG in GBM tumour-associated macrophages (TAMs) was illuminated, using integrated bioinformatics analyses. Finally, immunohistochemistry and multiplex immunohistochemistry (mIHC) were used to analyse the expression of
LGMN
in GBM tissues from our hospital. scRNA-Seq analysis showed that the heterogeneity of recurrent GBM mainly comes from TAMs, which can be divided into 8 cell subclusters. Among these subclusters, TAM1 (markers: CXCL10, ADORA3), TAM3 (markers: MRC1, CFP), TAM4 (markers: GPNMB, PLTP), and TAM5 (markers: CCL4, IRAK2) were specifically present in recurrent GBM. After 342 DEGs in TAMs were identified, a prognostic signature was established based on 13 TAM-associated DEGs, and this signature could serve as an excellent prognostic predictor for patients with GBM.
LGMN
, one of 13 TAM-associated DEGs, was an important gene in lysosome pathway, we found that macrophage infiltration levels were higher after
LGMN
upregulation. GBM tissues from our hospital were collected for histopathologic validation, then
LGMN
was co-expressed with CD68, which is associated with the immune regulation of GBM. In conclusion, cell heterogeneity of TAMs is important for recurrent GBM, a prognostic signature based on 13 TAM-related DEGs can predict the survival outcome of GBM patients. An important DEG,
LGMN
may regulate the immune cell infiltration of GBM. |
doi_str_mv | 10.1007/s12031-022-02081-z |
format | article |
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LGMN
, an important DEG in GBM tumour-associated macrophages (TAMs) was illuminated, using integrated bioinformatics analyses. Finally, immunohistochemistry and multiplex immunohistochemistry (mIHC) were used to analyse the expression of
LGMN
in GBM tissues from our hospital. scRNA-Seq analysis showed that the heterogeneity of recurrent GBM mainly comes from TAMs, which can be divided into 8 cell subclusters. Among these subclusters, TAM1 (markers: CXCL10, ADORA3), TAM3 (markers: MRC1, CFP), TAM4 (markers: GPNMB, PLTP), and TAM5 (markers: CCL4, IRAK2) were specifically present in recurrent GBM. After 342 DEGs in TAMs were identified, a prognostic signature was established based on 13 TAM-associated DEGs, and this signature could serve as an excellent prognostic predictor for patients with GBM.
LGMN
, one of 13 TAM-associated DEGs, was an important gene in lysosome pathway, we found that macrophage infiltration levels were higher after
LGMN
upregulation. GBM tissues from our hospital were collected for histopathologic validation, then
LGMN
was co-expressed with CD68, which is associated with the immune regulation of GBM. In conclusion, cell heterogeneity of TAMs is important for recurrent GBM, a prognostic signature based on 13 TAM-related DEGs can predict the survival outcome of GBM patients. An important DEG,
LGMN
may regulate the immune cell infiltration of GBM.</description><identifier>ISSN: 0895-8696</identifier><identifier>EISSN: 1559-1166</identifier><identifier>DOI: 10.1007/s12031-022-02081-z</identifier><identifier>PMID: 36542317</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Bioinformatics ; Biomarkers ; Biomedical and Life Sciences ; Biomedicine ; Brain cancer ; Brain Neoplasms - metabolism ; Cancer ; CD45 antigen ; Cell Biology ; Cells ; CXCL10 protein ; Gene expression ; Gene Expression Regulation, Neoplastic ; Gene sequencing ; Genomes ; Genomics ; Glioblastoma ; Glioblastoma - metabolism ; Heterogeneity ; Hospitals ; Humans ; Immune system ; Immunohistochemistry ; Immunoregulation ; Infiltration ; IRAK protein ; Macrophages ; Macrophages - metabolism ; Medical prognosis ; Medical schools ; Membrane Glycoproteins - genetics ; Metastases ; Microenvironments ; Neoplasm Recurrence, Local - genetics ; Neoplasm Recurrence, Local - metabolism ; Neoplasm Recurrence, Local - pathology ; Neurochemistry ; Neurology ; Neurosciences ; Pharmacy ; Phenotypes ; Proteomics ; Tumor microenvironment ; Tumor Microenvironment - genetics ; Tumor-Associated Macrophages - metabolism ; Tumor-Associated Macrophages - pathology ; Tumors</subject><ispartof>Journal of molecular neuroscience, 2023, Vol.73 (1), p.1-14</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c326t-a4ec6cae37da092aefeb461c63cdcf1303d371f3a193898fdabb3bba3554131f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36542317$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xuan, Zixue</creatorcontrib><creatorcontrib>Fang, Ling</creatorcontrib><creatorcontrib>Zhang, Guobing</creatorcontrib><creatorcontrib>Zhang, Xin</creatorcontrib><creatorcontrib>Jiang, Jinying</creatorcontrib><creatorcontrib>Wang, Kai</creatorcontrib><creatorcontrib>Huang, Ping</creatorcontrib><title>The Heterogeneity of Tumour-Associated Macrophages Contributes to the Recurrence and Outcomes of Glioblastoma Patients</title><title>Journal of molecular neuroscience</title><addtitle>J Mol Neurosci</addtitle><addtitle>J Mol Neurosci</addtitle><description>Cellular heterogeneity and immune cell molecular phenotypes may be involved in the malignant progression of glioblastoma (GBM). In this study, we aimed to know whether the heterogeneity of tumour-associated macrophages contributes to the recurrence and outcomes of glioblastoma patients. Single-cell RNA sequencing (scRNA-Seq) data were used to assess the heterogeneity of CD45 + immune cells in recurrent GBM and analyse differentially expressed genes (DEGs) in master cells. Then, a prognostic signature based on the identified DEGs was established and validated, the correlation between risk score and tumour microenvironment (TME) was explored. The correlation between immune infiltration and
LGMN
, an important DEG in GBM tumour-associated macrophages (TAMs) was illuminated, using integrated bioinformatics analyses. Finally, immunohistochemistry and multiplex immunohistochemistry (mIHC) were used to analyse the expression of
LGMN
in GBM tissues from our hospital. scRNA-Seq analysis showed that the heterogeneity of recurrent GBM mainly comes from TAMs, which can be divided into 8 cell subclusters. Among these subclusters, TAM1 (markers: CXCL10, ADORA3), TAM3 (markers: MRC1, CFP), TAM4 (markers: GPNMB, PLTP), and TAM5 (markers: CCL4, IRAK2) were specifically present in recurrent GBM. After 342 DEGs in TAMs were identified, a prognostic signature was established based on 13 TAM-associated DEGs, and this signature could serve as an excellent prognostic predictor for patients with GBM.
LGMN
, one of 13 TAM-associated DEGs, was an important gene in lysosome pathway, we found that macrophage infiltration levels were higher after
LGMN
upregulation. GBM tissues from our hospital were collected for histopathologic validation, then
LGMN
was co-expressed with CD68, which is associated with the immune regulation of GBM. In conclusion, cell heterogeneity of TAMs is important for recurrent GBM, a prognostic signature based on 13 TAM-related DEGs can predict the survival outcome of GBM patients. An important DEG,
LGMN
may regulate the immune cell infiltration of GBM.</description><subject>Bioinformatics</subject><subject>Biomarkers</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Brain cancer</subject><subject>Brain Neoplasms - metabolism</subject><subject>Cancer</subject><subject>CD45 antigen</subject><subject>Cell Biology</subject><subject>Cells</subject><subject>CXCL10 protein</subject><subject>Gene expression</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Gene sequencing</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Glioblastoma</subject><subject>Glioblastoma - metabolism</subject><subject>Heterogeneity</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Immune system</subject><subject>Immunohistochemistry</subject><subject>Immunoregulation</subject><subject>Infiltration</subject><subject>IRAK protein</subject><subject>Macrophages</subject><subject>Macrophages - metabolism</subject><subject>Medical prognosis</subject><subject>Medical schools</subject><subject>Membrane Glycoproteins - genetics</subject><subject>Metastases</subject><subject>Microenvironments</subject><subject>Neoplasm Recurrence, Local - genetics</subject><subject>Neoplasm Recurrence, Local - metabolism</subject><subject>Neoplasm Recurrence, Local - pathology</subject><subject>Neurochemistry</subject><subject>Neurology</subject><subject>Neurosciences</subject><subject>Pharmacy</subject><subject>Phenotypes</subject><subject>Proteomics</subject><subject>Tumor microenvironment</subject><subject>Tumor Microenvironment - genetics</subject><subject>Tumor-Associated Macrophages - metabolism</subject><subject>Tumor-Associated Macrophages - pathology</subject><subject>Tumors</subject><issn>0895-8696</issn><issn>1559-1166</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kU9P3DAQxS1UBMufL8ChstQLlxSPnTjJEa0KVKICoeVsTZzJEpTEW9upBJ8ew0Ir9cBh5JHeb95Y8xg7AfEdhCjPAkihIBNSphIVZM87bAFFUWcAWn9hC1HVRVbpWu-zgxAehZCQQ7XH9pUucqmgXLA_qwfiVxTJuzVN1Mcn7jq-mkc3--w8BGd7jNTyX2i92zzgmgJfuin6vplj6qPjMTnckZ29p8kSx6nlN3O0bkxy8rocetcMGKIbkd9i7GmK4YjtdjgEOn5_D9n9xY_V8iq7vrn8uTy_zqySOmaYk9UWSZUtiloiddTkGqxWtrUdKKFaVUKnEGpV1VXXYtOopkFVFDmoJByy063vxrvfM4Voxj5YGgacyM3ByLLQuhS5lAn99h_6mG4wpd8lqoRKSiHqRMktlc4RgqfObHw_on8yIMxrKmabikmpmLdUzHMa-vpuPTcjtX9HPmJIgNoCIUnTmvy_3Z_YvgC5ZJpP</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>Xuan, Zixue</creator><creator>Fang, Ling</creator><creator>Zhang, Guobing</creator><creator>Zhang, Xin</creator><creator>Jiang, Jinying</creator><creator>Wang, Kai</creator><creator>Huang, Ping</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7QR</scope><scope>7T7</scope><scope>7TK</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7N</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>2023</creationdate><title>The Heterogeneity of Tumour-Associated Macrophages Contributes to the Recurrence and Outcomes of Glioblastoma Patients</title><author>Xuan, Zixue ; Fang, Ling ; Zhang, Guobing ; Zhang, Xin ; Jiang, Jinying ; Wang, Kai ; Huang, Ping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c326t-a4ec6cae37da092aefeb461c63cdcf1303d371f3a193898fdabb3bba3554131f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Bioinformatics</topic><topic>Biomarkers</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Brain cancer</topic><topic>Brain Neoplasms - metabolism</topic><topic>Cancer</topic><topic>CD45 antigen</topic><topic>Cell Biology</topic><topic>Cells</topic><topic>CXCL10 protein</topic><topic>Gene expression</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Gene sequencing</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Glioblastoma</topic><topic>Glioblastoma - metabolism</topic><topic>Heterogeneity</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Immune system</topic><topic>Immunohistochemistry</topic><topic>Immunoregulation</topic><topic>Infiltration</topic><topic>IRAK protein</topic><topic>Macrophages</topic><topic>Macrophages - metabolism</topic><topic>Medical prognosis</topic><topic>Medical schools</topic><topic>Membrane Glycoproteins - genetics</topic><topic>Metastases</topic><topic>Microenvironments</topic><topic>Neoplasm Recurrence, Local - genetics</topic><topic>Neoplasm Recurrence, Local - metabolism</topic><topic>Neoplasm Recurrence, Local - pathology</topic><topic>Neurochemistry</topic><topic>Neurology</topic><topic>Neurosciences</topic><topic>Pharmacy</topic><topic>Phenotypes</topic><topic>Proteomics</topic><topic>Tumor microenvironment</topic><topic>Tumor Microenvironment - 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Academic</collection><jtitle>Journal of molecular neuroscience</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xuan, Zixue</au><au>Fang, Ling</au><au>Zhang, Guobing</au><au>Zhang, Xin</au><au>Jiang, Jinying</au><au>Wang, Kai</au><au>Huang, Ping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Heterogeneity of Tumour-Associated Macrophages Contributes to the Recurrence and Outcomes of Glioblastoma Patients</atitle><jtitle>Journal of molecular neuroscience</jtitle><stitle>J Mol Neurosci</stitle><addtitle>J Mol Neurosci</addtitle><date>2023</date><risdate>2023</risdate><volume>73</volume><issue>1</issue><spage>1</spage><epage>14</epage><pages>1-14</pages><issn>0895-8696</issn><eissn>1559-1166</eissn><abstract>Cellular heterogeneity and immune cell molecular phenotypes may be involved in the malignant progression of glioblastoma (GBM). In this study, we aimed to know whether the heterogeneity of tumour-associated macrophages contributes to the recurrence and outcomes of glioblastoma patients. Single-cell RNA sequencing (scRNA-Seq) data were used to assess the heterogeneity of CD45 + immune cells in recurrent GBM and analyse differentially expressed genes (DEGs) in master cells. Then, a prognostic signature based on the identified DEGs was established and validated, the correlation between risk score and tumour microenvironment (TME) was explored. The correlation between immune infiltration and
LGMN
, an important DEG in GBM tumour-associated macrophages (TAMs) was illuminated, using integrated bioinformatics analyses. Finally, immunohistochemistry and multiplex immunohistochemistry (mIHC) were used to analyse the expression of
LGMN
in GBM tissues from our hospital. scRNA-Seq analysis showed that the heterogeneity of recurrent GBM mainly comes from TAMs, which can be divided into 8 cell subclusters. Among these subclusters, TAM1 (markers: CXCL10, ADORA3), TAM3 (markers: MRC1, CFP), TAM4 (markers: GPNMB, PLTP), and TAM5 (markers: CCL4, IRAK2) were specifically present in recurrent GBM. After 342 DEGs in TAMs were identified, a prognostic signature was established based on 13 TAM-associated DEGs, and this signature could serve as an excellent prognostic predictor for patients with GBM.
LGMN
, one of 13 TAM-associated DEGs, was an important gene in lysosome pathway, we found that macrophage infiltration levels were higher after
LGMN
upregulation. GBM tissues from our hospital were collected for histopathologic validation, then
LGMN
was co-expressed with CD68, which is associated with the immune regulation of GBM. In conclusion, cell heterogeneity of TAMs is important for recurrent GBM, a prognostic signature based on 13 TAM-related DEGs can predict the survival outcome of GBM patients. An important DEG,
LGMN
may regulate the immune cell infiltration of GBM.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>36542317</pmid><doi>10.1007/s12031-022-02081-z</doi><tpages>14</tpages></addata></record> |
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subjects | Bioinformatics Biomarkers Biomedical and Life Sciences Biomedicine Brain cancer Brain Neoplasms - metabolism Cancer CD45 antigen Cell Biology Cells CXCL10 protein Gene expression Gene Expression Regulation, Neoplastic Gene sequencing Genomes Genomics Glioblastoma Glioblastoma - metabolism Heterogeneity Hospitals Humans Immune system Immunohistochemistry Immunoregulation Infiltration IRAK protein Macrophages Macrophages - metabolism Medical prognosis Medical schools Membrane Glycoproteins - genetics Metastases Microenvironments Neoplasm Recurrence, Local - genetics Neoplasm Recurrence, Local - metabolism Neoplasm Recurrence, Local - pathology Neurochemistry Neurology Neurosciences Pharmacy Phenotypes Proteomics Tumor microenvironment Tumor Microenvironment - genetics Tumor-Associated Macrophages - metabolism Tumor-Associated Macrophages - pathology Tumors |
title | The Heterogeneity of Tumour-Associated Macrophages Contributes to the Recurrence and Outcomes of Glioblastoma Patients |
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