Prevalence and clinicopathologic characteristics of the molecular subtypes in malignant glioma: a multi-institutional analysis of 941 cases
Glioblastoma can be classified into four distinct molecular subtypes (Proneural, Neural, Classical and Mesenchymal), based on gene expression profiling. This study aimed to investigate the prevalence, clinicopathologic features and overall survival (OS) of the four molecular subtypes among all malig...
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| description | Glioblastoma can be classified into four distinct molecular subtypes (Proneural, Neural, Classical and Mesenchymal), based on gene expression profiling. This study aimed to investigate the prevalence, clinicopathologic features and overall survival (OS) of the four molecular subtypes among all malignant gliomas.
A total of 941 gene expression arrays with clinical data were obtained from the Rembrandt, GSE16011 and CGGA datasets. Molecular subtypes were predicted with a prediction analysis of microarray.
Among 941 malignant gliomas, 32.73% were Proneural, 15.09% Neural, 19.77% Classical and 32.41% Mesenchymal. The Proneural and Neural subtypes occurred largely in low-grade gliomas, while the Classical and Mesenchymal subtypes were more frequent in high-grade gliomas. A survival analysis showed that the Proneural subtype displayed a good prognosis, Neural had an intermediate correlation with overall survival, Mesenchymal had a worse prognosis than Neural, and Classical had the worst clinical outcome. Furthermore, oligodendrocytomas were preferentially assigned to the Proneural subtype, while the Mesenchymal subtype included a higher percentage of astrocytomas, compared with oligodendrocytomas. Additionally, nearly all classical gliomas harbored EGFR amplifications. Classical anaplastic gliomas have similar clinical outcomes as their glioblastoma counterparts and should be treated more aggressively.
Molecular subtypes exist stably in all histological malignant gliomas subtypes. This could be an important improvement to histological diagnoses for both prognosis evaluations and clinical outcome predictions. |
| doi_str_mv | 10.1371/journal.pone.0094871 |
| format | Article |
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A total of 941 gene expression arrays with clinical data were obtained from the Rembrandt, GSE16011 and CGGA datasets. Molecular subtypes were predicted with a prediction analysis of microarray.
Among 941 malignant gliomas, 32.73% were Proneural, 15.09% Neural, 19.77% Classical and 32.41% Mesenchymal. The Proneural and Neural subtypes occurred largely in low-grade gliomas, while the Classical and Mesenchymal subtypes were more frequent in high-grade gliomas. A survival analysis showed that the Proneural subtype displayed a good prognosis, Neural had an intermediate correlation with overall survival, Mesenchymal had a worse prognosis than Neural, and Classical had the worst clinical outcome. Furthermore, oligodendrocytomas were preferentially assigned to the Proneural subtype, while the Mesenchymal subtype included a higher percentage of astrocytomas, compared with oligodendrocytomas. Additionally, nearly all classical gliomas harbored EGFR amplifications. Classical anaplastic gliomas have similar clinical outcomes as their glioblastoma counterparts and should be treated more aggressively.
Molecular subtypes exist stably in all histological malignant gliomas subtypes. This could be an important improvement to histological diagnoses for both prognosis evaluations and clinical outcome predictions.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0094871</identifier><identifier>PMID: 24755548</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Astrocytoma ; Biology and Life Sciences ; Biomarkers, Tumor - metabolism ; Brain cancer ; Brain Neoplasms - classification ; Brain Neoplasms - epidemiology ; Brain Neoplasms - genetics ; Brain Neoplasms - pathology ; Brain tumors ; Care and treatment ; Classification ; Clinical outcomes ; Diagnosis ; DNA microarrays ; Epidermal growth factor receptors ; Gene expression ; Gene Expression Regulation, Neoplastic ; Genomes ; Glioblastoma ; Glioma ; Glioma - classification ; Glioma - epidemiology ; Glioma - genetics ; Glioma - pathology ; Gliomas ; Hospitals ; Humans ; Medical diagnosis ; Medical prognosis ; Medical research ; Medicine and Health Sciences ; Mesenchyme ; Mutation ; Neoplasm Grading ; Neurosurgery ; Predictions ; Prevalence ; Prevalence studies (Epidemiology) ; Prognosis ; Quality ; Receptor, Epidermal Growth Factor - metabolism ; Research and Analysis Methods ; ROC Curve ; Stem cell research ; Studies ; Survival ; Survival Analysis ; World Health Organization</subject><ispartof>PloS one, 2014-04, Vol.9 (4), p.e94871-e94871</ispartof><rights>COPYRIGHT 2014 Public Library of Science</rights><rights>2014 Lin et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2014 Lin et al 2014 Lin et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c758t-a0ccd3d4b328be3b6d54b69c6fbb159184c47424e5943cfa7c235e2fdb081d7b3</citedby><cites>FETCH-LOGICAL-c758t-a0ccd3d4b328be3b6d54b69c6fbb159184c47424e5943cfa7c235e2fdb081d7b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3995672/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3995672/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24755548$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lin, Ning</creatorcontrib><creatorcontrib>Yan, Wei</creatorcontrib><creatorcontrib>Gao, Kaiming</creatorcontrib><creatorcontrib>Wang, Yinyi</creatorcontrib><creatorcontrib>Zhang, Junxia</creatorcontrib><creatorcontrib>You, Yongping</creatorcontrib><title>Prevalence and clinicopathologic characteristics of the molecular subtypes in malignant glioma: a multi-institutional analysis of 941 cases</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Glioblastoma can be classified into four distinct molecular subtypes (Proneural, Neural, Classical and Mesenchymal), based on gene expression profiling. This study aimed to investigate the prevalence, clinicopathologic features and overall survival (OS) of the four molecular subtypes among all malignant gliomas.
A total of 941 gene expression arrays with clinical data were obtained from the Rembrandt, GSE16011 and CGGA datasets. Molecular subtypes were predicted with a prediction analysis of microarray.
Among 941 malignant gliomas, 32.73% were Proneural, 15.09% Neural, 19.77% Classical and 32.41% Mesenchymal. The Proneural and Neural subtypes occurred largely in low-grade gliomas, while the Classical and Mesenchymal subtypes were more frequent in high-grade gliomas. A survival analysis showed that the Proneural subtype displayed a good prognosis, Neural had an intermediate correlation with overall survival, Mesenchymal had a worse prognosis than Neural, and Classical had the worst clinical outcome. Furthermore, oligodendrocytomas were preferentially assigned to the Proneural subtype, while the Mesenchymal subtype included a higher percentage of astrocytomas, compared with oligodendrocytomas. Additionally, nearly all classical gliomas harbored EGFR amplifications. Classical anaplastic gliomas have similar clinical outcomes as their glioblastoma counterparts and should be treated more aggressively.
Molecular subtypes exist stably in all histological malignant gliomas subtypes. This could be an important improvement to histological diagnoses for both prognosis evaluations and clinical outcome predictions.</description><subject>Analysis</subject><subject>Astrocytoma</subject><subject>Biology and Life Sciences</subject><subject>Biomarkers, Tumor - metabolism</subject><subject>Brain cancer</subject><subject>Brain Neoplasms - classification</subject><subject>Brain Neoplasms - epidemiology</subject><subject>Brain Neoplasms - genetics</subject><subject>Brain Neoplasms - pathology</subject><subject>Brain tumors</subject><subject>Care and treatment</subject><subject>Classification</subject><subject>Clinical outcomes</subject><subject>Diagnosis</subject><subject>DNA microarrays</subject><subject>Epidermal growth factor receptors</subject><subject>Gene expression</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Genomes</subject><subject>Glioblastoma</subject><subject>Glioma</subject><subject>Glioma - classification</subject><subject>Glioma - epidemiology</subject><subject>Glioma - genetics</subject><subject>Glioma - pathology</subject><subject>Gliomas</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Medical diagnosis</subject><subject>Medical prognosis</subject><subject>Medical research</subject><subject>Medicine and Health Sciences</subject><subject>Mesenchyme</subject><subject>Mutation</subject><subject>Neoplasm Grading</subject><subject>Neurosurgery</subject><subject>Predictions</subject><subject>Prevalence</subject><subject>Prevalence studies (Epidemiology)</subject><subject>Prognosis</subject><subject>Quality</subject><subject>Receptor, Epidermal Growth Factor - metabolism</subject><subject>Research and Analysis Methods</subject><subject>ROC Curve</subject><subject>Stem cell research</subject><subject>Studies</subject><subject>Survival</subject><subject>Survival Analysis</subject><subject>World Health Organization</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNk9tu1DAQhiMEoqXwBggsISG42CWO7Ry4QKoqDitVKuJ0a02cSdYrx97aTsU-Ay-Nt7utuqgXKBeJnO__ZzyHLHtO8zllFX23cpO3YOZrZ3Ge5w2vK_ogO6YNK2ZlkbOHd76PsichrPJcsLosH2dHBa-EELw-zv589XgFBq1CArYjymirlVtDXDrjBq2IWoIHFdHrELUKxPUkLpGMzqCaDHgSpjZu1hiItmQEowcLNpLBaDfCewJknEzUM22TPE5Ru5R0CgVmE_S1W8MpURAwPM0e9WACPtu_T7Kfnz7-OPsyO7_4vDg7PZ-pStRxBrlSHet4y4q6RdaWneBt2aiyb1sqGlpzxStecBQNZ6qHShVMYNF3bV7TrmrZSfZy57s2Lsh9HYOkIkmrXFRNIhY7onOwkmuvR_Ab6UDL6wPnBwk-VcOgZEXTpLwUdKrmeZ9DWzFIdS46QfsCafL6sI82tSN2Cm30YA5MD_9YvZSDu5KsaURZFcngzd7Au8sJQ5SjDgqNAYtu2uVd09TNMqGv_kHvv92eGlLjpba9S3HV1lSesjQY6R5sS83vodLT4ZgmxGKv0_mB4O2BIDERf8cBphDk4vu3_2cvfh2yr--wSwQTl8GZ61EKhyDfgcq7EDz2t0WmudzuzE015HZn5H5nkuzF3Qbdim6WhP0FRiYUWA</recordid><startdate>20140401</startdate><enddate>20140401</enddate><creator>Lin, Ning</creator><creator>Yan, Wei</creator><creator>Gao, Kaiming</creator><creator>Wang, Yinyi</creator><creator>Zhang, Junxia</creator><creator>You, Yongping</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20140401</creationdate><title>Prevalence and clinicopathologic characteristics of the molecular subtypes in malignant glioma: a multi-institutional analysis of 941 cases</title><author>Lin, Ning ; Yan, Wei ; Gao, Kaiming ; Wang, Yinyi ; Zhang, Junxia ; You, Yongping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c758t-a0ccd3d4b328be3b6d54b69c6fbb159184c47424e5943cfa7c235e2fdb081d7b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Analysis</topic><topic>Astrocytoma</topic><topic>Biology and Life Sciences</topic><topic>Biomarkers, Tumor - metabolism</topic><topic>Brain cancer</topic><topic>Brain Neoplasms - classification</topic><topic>Brain Neoplasms - epidemiology</topic><topic>Brain Neoplasms - genetics</topic><topic>Brain Neoplasms - pathology</topic><topic>Brain tumors</topic><topic>Care and treatment</topic><topic>Classification</topic><topic>Clinical outcomes</topic><topic>Diagnosis</topic><topic>DNA microarrays</topic><topic>Epidermal growth factor receptors</topic><topic>Gene expression</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Genomes</topic><topic>Glioblastoma</topic><topic>Glioma</topic><topic>Glioma - classification</topic><topic>Glioma - epidemiology</topic><topic>Glioma - genetics</topic><topic>Glioma - pathology</topic><topic>Gliomas</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Medical diagnosis</topic><topic>Medical prognosis</topic><topic>Medical research</topic><topic>Medicine and Health Sciences</topic><topic>Mesenchyme</topic><topic>Mutation</topic><topic>Neoplasm Grading</topic><topic>Neurosurgery</topic><topic>Predictions</topic><topic>Prevalence</topic><topic>Prevalence studies (Epidemiology)</topic><topic>Prognosis</topic><topic>Quality</topic><topic>Receptor, Epidermal Growth Factor - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lin, Ning</au><au>Yan, Wei</au><au>Gao, Kaiming</au><au>Wang, Yinyi</au><au>Zhang, Junxia</au><au>You, Yongping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Prevalence and clinicopathologic characteristics of the molecular subtypes in malignant glioma: a multi-institutional analysis of 941 cases</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2014-04-01</date><risdate>2014</risdate><volume>9</volume><issue>4</issue><spage>e94871</spage><epage>e94871</epage><pages>e94871-e94871</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Glioblastoma can be classified into four distinct molecular subtypes (Proneural, Neural, Classical and Mesenchymal), based on gene expression profiling. This study aimed to investigate the prevalence, clinicopathologic features and overall survival (OS) of the four molecular subtypes among all malignant gliomas.
A total of 941 gene expression arrays with clinical data were obtained from the Rembrandt, GSE16011 and CGGA datasets. Molecular subtypes were predicted with a prediction analysis of microarray.
Among 941 malignant gliomas, 32.73% were Proneural, 15.09% Neural, 19.77% Classical and 32.41% Mesenchymal. The Proneural and Neural subtypes occurred largely in low-grade gliomas, while the Classical and Mesenchymal subtypes were more frequent in high-grade gliomas. A survival analysis showed that the Proneural subtype displayed a good prognosis, Neural had an intermediate correlation with overall survival, Mesenchymal had a worse prognosis than Neural, and Classical had the worst clinical outcome. Furthermore, oligodendrocytomas were preferentially assigned to the Proneural subtype, while the Mesenchymal subtype included a higher percentage of astrocytomas, compared with oligodendrocytomas. Additionally, nearly all classical gliomas harbored EGFR amplifications. Classical anaplastic gliomas have similar clinical outcomes as their glioblastoma counterparts and should be treated more aggressively.
Molecular subtypes exist stably in all histological malignant gliomas subtypes. This could be an important improvement to histological diagnoses for both prognosis evaluations and clinical outcome predictions.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24755548</pmid><doi>10.1371/journal.pone.0094871</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Analysis Astrocytoma Biology and Life Sciences Biomarkers, Tumor - metabolism Brain cancer Brain Neoplasms - classification Brain Neoplasms - epidemiology Brain Neoplasms - genetics Brain Neoplasms - pathology Brain tumors Care and treatment Classification Clinical outcomes Diagnosis DNA microarrays Epidermal growth factor receptors Gene expression Gene Expression Regulation, Neoplastic Genomes Glioblastoma Glioma Glioma - classification Glioma - epidemiology Glioma - genetics Glioma - pathology Gliomas Hospitals Humans Medical diagnosis Medical prognosis Medical research Medicine and Health Sciences Mesenchyme Mutation Neoplasm Grading Neurosurgery Predictions Prevalence Prevalence studies (Epidemiology) Prognosis Quality Receptor, Epidermal Growth Factor - metabolism Research and Analysis Methods ROC Curve Stem cell research Studies Survival Survival Analysis World Health Organization |
| title | Prevalence and clinicopathologic characteristics of the molecular subtypes in malignant glioma: a multi-institutional analysis of 941 cases |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-04T19%3A15%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Prevalence%20and%20clinicopathologic%20characteristics%20of%20the%20molecular%20subtypes%20in%20malignant%20glioma:%20a%20multi-institutional%20analysis%20of%20941%20cases&rft.jtitle=PloS%20one&rft.au=Lin,%20Ning&rft.date=2014-04-01&rft.volume=9&rft.issue=4&rft.spage=e94871&rft.epage=e94871&rft.pages=e94871-e94871&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0094871&rft_dat=%3Cgale_plos_%3EA375584039%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1518470579&rft_id=info:pmid/24755548&rft_galeid=A375584039&rft_doaj_id=oai_doaj_org_article_3299c75cadc840f0ab73a5382d51f2e1&rfr_iscdi=true |