New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction
Increasing evidence indicates that glioma topographic location is linked to the cellular origin, molecular alterations and genetic profile. This research aims to (a) reveal the underlying mechanisms of tumor location predilection in glioblastoma multiforme (GBM) and lower‐grade glioma (LGG) and (b)...
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Veröffentlicht in: | International journal of cancer 2023-03, Vol.152 (5), p.998-1012 |
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description | Increasing evidence indicates that glioma topographic location is linked to the cellular origin, molecular alterations and genetic profile. This research aims to (a) reveal the underlying mechanisms of tumor location predilection in glioblastoma multiforme (GBM) and lower‐grade glioma (LGG) and (b) leverage glioma location features to predict prognosis. MRI images from 396 GBM and 190 LGG (115 astrocytoma and 75 oligodendroglioma) patients were standardized to construct frequency maps and analyzed by voxel‐based lesion‐symptom mapping. We then investigated the spatial correlation between glioma distribution with gene expression in healthy brains. We also evaluated transcriptomic differences in tumor tissue from predilection and nonpredilection sites. Furthermore, we quantitively characterized tumor anatomical localization and explored whether it was significantly related to overall survival. Finally, we employed a support vector machine to build a survival prediction model for GBM patients. GBMs exhibited a distinct location predilection from LGGs. GBMs were nearer to the subventricular zone and more likely to be localized to regions enriched with synaptic signaling, whereas astrocytoma and oligodendroglioma tended to occur in areas associated with the immune response. Synapse, neurotransmitters and calcium ion channel‐related genes were all activated in GBM tissues coming from predilection regions. Furthermore, we characterized tumor location features in terms of a series of tumor‐to‐predilection distance metrics, which were able to predict GBM 1‐year survival status with an accuracy of 0.71. These findings provide new perspectives on our understanding of tumor anatomic localization. The spatial features of glioma are of great value in individual therapy and prognosis prediction.
What's new?
The spatial distribution of glioma is nonrandom. However, whether pathological grade influences glioma distribution across the brain remains unclear. Here, the authors built a population‐based frequency map for 396 patients with glioblastoma multiforme and 190 patients with lower‐grade glioma, revealing their distinct topographic localization patterns. Further results suggested that neuron and glioma synaptic interactions and electrochemical communications were involved in determining glioblastoma multiforme location, bringing a new perspective on glioma location predilection and gliomagenesis. Moreover, based on the identified tumor location features, the authors bui |
doi_str_mv | 10.1002/ijc.34336 |
format | Article |
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What's new?
The spatial distribution of glioma is nonrandom. However, whether pathological grade influences glioma distribution across the brain remains unclear. Here, the authors built a population‐based frequency map for 396 patients with glioblastoma multiforme and 190 patients with lower‐grade glioma, revealing their distinct topographic localization patterns. Further results suggested that neuron and glioma synaptic interactions and electrochemical communications were involved in determining glioblastoma multiforme location, bringing a new perspective on glioma location predilection and gliomagenesis. Moreover, based on the identified tumor location features, the authors built a survival prediction model for patients with glioblastoma multiforme.</description><identifier>ISSN: 0020-7136</identifier><identifier>EISSN: 1097-0215</identifier><identifier>DOI: 10.1002/ijc.34336</identifier><identifier>PMID: 36305649</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Astrocytoma ; Brain cancer ; Brain Neoplasms - pathology ; Brain tumors ; Cancer ; frequency map ; GBM ; Gene expression ; Gene mapping ; Glioblastoma ; Glioblastoma - pathology ; Glioma ; Glioma - pathology ; Humans ; Immune response ; LGG ; Localization ; Medical prognosis ; Medical research ; Neurotransmitters ; Oligodendroglioma ; Oligodendroglioma - genetics ; Prediction models ; Prognosis ; Subventricular zone ; survival prediction ; synapse ; Transcriptome ; Transcriptomics ; Tumor Immunology and Microenvironment</subject><ispartof>International journal of cancer, 2023-03, Vol.152 (5), p.998-1012</ispartof><rights>2022 The Authors. published by John Wiley & Sons Ltd on behalf of UICC.</rights><rights>2022 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.</rights><rights>2022. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4446-c2ba17d4a5f0d00634bb26bd04af18bfb730b89e2942908f17fe6921202d10da3</citedby><cites>FETCH-LOGICAL-c4446-c2ba17d4a5f0d00634bb26bd04af18bfb730b89e2942908f17fe6921202d10da3</cites><orcidid>0000-0003-1043-6951 ; 0000-0002-9394-5016</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fijc.34336$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fijc.34336$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,315,782,786,887,1419,27931,27932,45581,45582</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36305649$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bao, Hongbo</creatorcontrib><creatorcontrib>Ren, Peng</creatorcontrib><creatorcontrib>Yi, Liye</creatorcontrib><creatorcontrib>Lv, Zhonghua</creatorcontrib><creatorcontrib>Ding, Wencai</creatorcontrib><creatorcontrib>Li, Chenlong</creatorcontrib><creatorcontrib>Li, Siyang</creatorcontrib><creatorcontrib>Li, Zhipeng</creatorcontrib><creatorcontrib>Yang, Xue</creatorcontrib><creatorcontrib>Liang, Xia</creatorcontrib><creatorcontrib>Liang, Peng</creatorcontrib><title>New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction</title><title>International journal of cancer</title><addtitle>Int J Cancer</addtitle><description>Increasing evidence indicates that glioma topographic location is linked to the cellular origin, molecular alterations and genetic profile. This research aims to (a) reveal the underlying mechanisms of tumor location predilection in glioblastoma multiforme (GBM) and lower‐grade glioma (LGG) and (b) leverage glioma location features to predict prognosis. MRI images from 396 GBM and 190 LGG (115 astrocytoma and 75 oligodendroglioma) patients were standardized to construct frequency maps and analyzed by voxel‐based lesion‐symptom mapping. We then investigated the spatial correlation between glioma distribution with gene expression in healthy brains. We also evaluated transcriptomic differences in tumor tissue from predilection and nonpredilection sites. Furthermore, we quantitively characterized tumor anatomical localization and explored whether it was significantly related to overall survival. Finally, we employed a support vector machine to build a survival prediction model for GBM patients. GBMs exhibited a distinct location predilection from LGGs. GBMs were nearer to the subventricular zone and more likely to be localized to regions enriched with synaptic signaling, whereas astrocytoma and oligodendroglioma tended to occur in areas associated with the immune response. Synapse, neurotransmitters and calcium ion channel‐related genes were all activated in GBM tissues coming from predilection regions. Furthermore, we characterized tumor location features in terms of a series of tumor‐to‐predilection distance metrics, which were able to predict GBM 1‐year survival status with an accuracy of 0.71. These findings provide new perspectives on our understanding of tumor anatomic localization. The spatial features of glioma are of great value in individual therapy and prognosis prediction.
What's new?
The spatial distribution of glioma is nonrandom. However, whether pathological grade influences glioma distribution across the brain remains unclear. Here, the authors built a population‐based frequency map for 396 patients with glioblastoma multiforme and 190 patients with lower‐grade glioma, revealing their distinct topographic localization patterns. Further results suggested that neuron and glioma synaptic interactions and electrochemical communications were involved in determining glioblastoma multiforme location, bringing a new perspective on glioma location predilection and gliomagenesis. Moreover, based on the identified tumor location features, the authors built a survival prediction model for patients with glioblastoma multiforme.</description><subject>Astrocytoma</subject><subject>Brain cancer</subject><subject>Brain Neoplasms - pathology</subject><subject>Brain tumors</subject><subject>Cancer</subject><subject>frequency map</subject><subject>GBM</subject><subject>Gene expression</subject><subject>Gene mapping</subject><subject>Glioblastoma</subject><subject>Glioblastoma - pathology</subject><subject>Glioma</subject><subject>Glioma - pathology</subject><subject>Humans</subject><subject>Immune response</subject><subject>LGG</subject><subject>Localization</subject><subject>Medical prognosis</subject><subject>Medical research</subject><subject>Neurotransmitters</subject><subject>Oligodendroglioma</subject><subject>Oligodendroglioma - genetics</subject><subject>Prediction models</subject><subject>Prognosis</subject><subject>Subventricular zone</subject><subject>survival prediction</subject><subject>synapse</subject><subject>Transcriptome</subject><subject>Transcriptomics</subject><subject>Tumor Immunology and Microenvironment</subject><issn>0020-7136</issn><issn>1097-0215</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp1kcFu1DAURa0KRIfCoj-ALLGBRdr3bMeZdIPQiJaiqt3QteU4ztSjxA52MtX8PabTVlCJlS376Oi-dwk5RjhBAHbqNuaEC87lAVkg1FUBDMtXZJH_oKiQy0PyNqUNAGIJ4g055JJDKUW9IO7a3lPnk1vfTSlfpkDXvQuDpl20v2brzY4Oekxn9DyGga6tt5MzVPuWTlH7ZKIbpzDkJxNitL2eLM2ONMet2-qejtG2zkwu-Hfkdaf7ZN8_nkfk9vzbz9X34urm4nL19aowQghZGNZorFqhyw5aAMlF0zDZtCB0h8umayoOzbK2rBashmWHVWdlzZABaxFazY_Il713nJvBtsb6HLRXY3SDjjsVtFP__nh3p9ZhqxDyMpFjNnx6NMSQV5AmNbhkbN9rb8OcFMsRONa8khn9-ALdhDn6PF-mJOSBoCoz9XlPmRhSirZ7ToOg_jSocoPqocHMfvg7_jP5VFkGTvfAvevt7v8mdfljtVf-BvNWpsI</recordid><startdate>20230301</startdate><enddate>20230301</enddate><creator>Bao, Hongbo</creator><creator>Ren, Peng</creator><creator>Yi, Liye</creator><creator>Lv, Zhonghua</creator><creator>Ding, Wencai</creator><creator>Li, Chenlong</creator><creator>Li, Siyang</creator><creator>Li, Zhipeng</creator><creator>Yang, Xue</creator><creator>Liang, Xia</creator><creator>Liang, Peng</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><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>7T5</scope><scope>7TO</scope><scope>7U9</scope><scope>H94</scope><scope>K9.</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-1043-6951</orcidid><orcidid>https://orcid.org/0000-0002-9394-5016</orcidid></search><sort><creationdate>20230301</creationdate><title>New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction</title><author>Bao, Hongbo ; Ren, Peng ; Yi, Liye ; Lv, Zhonghua ; Ding, Wencai ; Li, Chenlong ; Li, Siyang ; Li, Zhipeng ; Yang, Xue ; Liang, Xia ; Liang, Peng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4446-c2ba17d4a5f0d00634bb26bd04af18bfb730b89e2942908f17fe6921202d10da3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Astrocytoma</topic><topic>Brain cancer</topic><topic>Brain Neoplasms - pathology</topic><topic>Brain tumors</topic><topic>Cancer</topic><topic>frequency map</topic><topic>GBM</topic><topic>Gene expression</topic><topic>Gene mapping</topic><topic>Glioblastoma</topic><topic>Glioblastoma - pathology</topic><topic>Glioma</topic><topic>Glioma - pathology</topic><topic>Humans</topic><topic>Immune response</topic><topic>LGG</topic><topic>Localization</topic><topic>Medical prognosis</topic><topic>Medical research</topic><topic>Neurotransmitters</topic><topic>Oligodendroglioma</topic><topic>Oligodendroglioma - genetics</topic><topic>Prediction models</topic><topic>Prognosis</topic><topic>Subventricular zone</topic><topic>survival prediction</topic><topic>synapse</topic><topic>Transcriptome</topic><topic>Transcriptomics</topic><topic>Tumor Immunology and Microenvironment</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bao, Hongbo</creatorcontrib><creatorcontrib>Ren, Peng</creatorcontrib><creatorcontrib>Yi, Liye</creatorcontrib><creatorcontrib>Lv, Zhonghua</creatorcontrib><creatorcontrib>Ding, Wencai</creatorcontrib><creatorcontrib>Li, Chenlong</creatorcontrib><creatorcontrib>Li, Siyang</creatorcontrib><creatorcontrib>Li, Zhipeng</creatorcontrib><creatorcontrib>Yang, Xue</creatorcontrib><creatorcontrib>Liang, Xia</creatorcontrib><creatorcontrib>Liang, Peng</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>International journal of cancer</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bao, Hongbo</au><au>Ren, Peng</au><au>Yi, Liye</au><au>Lv, Zhonghua</au><au>Ding, Wencai</au><au>Li, Chenlong</au><au>Li, Siyang</au><au>Li, Zhipeng</au><au>Yang, Xue</au><au>Liang, Xia</au><au>Liang, Peng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction</atitle><jtitle>International journal of cancer</jtitle><addtitle>Int J Cancer</addtitle><date>2023-03-01</date><risdate>2023</risdate><volume>152</volume><issue>5</issue><spage>998</spage><epage>1012</epage><pages>998-1012</pages><issn>0020-7136</issn><eissn>1097-0215</eissn><abstract>Increasing evidence indicates that glioma topographic location is linked to the cellular origin, molecular alterations and genetic profile. This research aims to (a) reveal the underlying mechanisms of tumor location predilection in glioblastoma multiforme (GBM) and lower‐grade glioma (LGG) and (b) leverage glioma location features to predict prognosis. MRI images from 396 GBM and 190 LGG (115 astrocytoma and 75 oligodendroglioma) patients were standardized to construct frequency maps and analyzed by voxel‐based lesion‐symptom mapping. We then investigated the spatial correlation between glioma distribution with gene expression in healthy brains. We also evaluated transcriptomic differences in tumor tissue from predilection and nonpredilection sites. Furthermore, we quantitively characterized tumor anatomical localization and explored whether it was significantly related to overall survival. Finally, we employed a support vector machine to build a survival prediction model for GBM patients. GBMs exhibited a distinct location predilection from LGGs. GBMs were nearer to the subventricular zone and more likely to be localized to regions enriched with synaptic signaling, whereas astrocytoma and oligodendroglioma tended to occur in areas associated with the immune response. Synapse, neurotransmitters and calcium ion channel‐related genes were all activated in GBM tissues coming from predilection regions. Furthermore, we characterized tumor location features in terms of a series of tumor‐to‐predilection distance metrics, which were able to predict GBM 1‐year survival status with an accuracy of 0.71. These findings provide new perspectives on our understanding of tumor anatomic localization. The spatial features of glioma are of great value in individual therapy and prognosis prediction.
What's new?
The spatial distribution of glioma is nonrandom. However, whether pathological grade influences glioma distribution across the brain remains unclear. Here, the authors built a population‐based frequency map for 396 patients with glioblastoma multiforme and 190 patients with lower‐grade glioma, revealing their distinct topographic localization patterns. Further results suggested that neuron and glioma synaptic interactions and electrochemical communications were involved in determining glioblastoma multiforme location, bringing a new perspective on glioma location predilection and gliomagenesis. Moreover, based on the identified tumor location features, the authors built a survival prediction model for patients with glioblastoma multiforme.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><pmid>36305649</pmid><doi>10.1002/ijc.34336</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0003-1043-6951</orcidid><orcidid>https://orcid.org/0000-0002-9394-5016</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Astrocytoma Brain cancer Brain Neoplasms - pathology Brain tumors Cancer frequency map GBM Gene expression Gene mapping Glioblastoma Glioblastoma - pathology Glioma Glioma - pathology Humans Immune response LGG Localization Medical prognosis Medical research Neurotransmitters Oligodendroglioma Oligodendroglioma - genetics Prediction models Prognosis Subventricular zone survival prediction synapse Transcriptome Transcriptomics Tumor Immunology and Microenvironment |
title | New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction |
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