Development of a tumor microenvironment‐related prognostic signature in glioma to predict immune landscape and potential therapeutic drugs
The involvement of the tumor microenvironment (TME) in the biology of gliomas has expanded, while it is yet uncertain its potential of supporting diagnosis and therapy choices. According to immunological characteristics and overall survival, cohorts of glioma patients from public databases were sepa...
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| Veröffentlicht in: | Journal of biochemical and molecular toxicology 2023-10, Vol.37 (10), p.e23448-n/a |
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| creator | Zhang, Yang Wu, Chunmiao Li, Qiang Fang, Sheng Hou, Min Zhang, Sunfu Dong, Xingyu |
| description | The involvement of the tumor microenvironment (TME) in the biology of gliomas has expanded, while it is yet uncertain its potential of supporting diagnosis and therapy choices. According to immunological characteristics and overall survival, cohorts of glioma patients from public databases were separated into two TME‐relevant clusters in this analysis. Based on differentially expressed genes between TME clusters and correlative regression analysis, a 21‐gene molecular classifier of TME‐related prognostic signature (TPS) was constructed. Afterward, the prognostic efficacy and effectiveness of TPS were assessed in the training and validation groups. The outcome demonstrated that TPS might be utilized alone or in conjunction with other clinical criteria to act as a superior prognostic predictor for glioma. Also, high‐risk glioma patients classified by TPS were considered to associate with enhanced immune infiltration, greater tumor mutation, and worse general prognosis. Finally, possible treatment medicines specialized for different risk subgroups of TPS were evaluated in drug databases. |
| doi_str_mv | 10.1002/jbt.23448 |
| format | Article |
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According to immunological characteristics and overall survival, cohorts of glioma patients from public databases were separated into two TME‐relevant clusters in this analysis. Based on differentially expressed genes between TME clusters and correlative regression analysis, a 21‐gene molecular classifier of TME‐related prognostic signature (TPS) was constructed. Afterward, the prognostic efficacy and effectiveness of TPS were assessed in the training and validation groups. The outcome demonstrated that TPS might be utilized alone or in conjunction with other clinical criteria to act as a superior prognostic predictor for glioma. Also, high‐risk glioma patients classified by TPS were considered to associate with enhanced immune infiltration, greater tumor mutation, and worse general prognosis. 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Finally, possible treatment medicines specialized for different risk subgroups of TPS were evaluated in drug databases.</description><subject>Cluster analysis</subject><subject>drug sensitivity</subject><subject>Glioma</subject><subject>Immunology</subject><subject>Immunosuppressive agents</subject><subject>Medical prognosis</subject><subject>Metastases</subject><subject>Patients</subject><subject>prognostic signature</subject><subject>Regression analysis</subject><subject>Risk groups</subject><subject>Subgroups</subject><subject>Tumor microenvironment</subject><subject>Tumors</subject><issn>1095-6670</issn><issn>1099-0461</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp1kc9OFTEUhxsjEQQXvoBp4gYXA-20084sBUQhJG5gPel0zlx7M23H_oGw4wFc8Iw-ib1ccGHiqift1y_nnB9C7yk5ooTUx-shHdWM8_YV2qOk6yrCBX39VDeVEJLsorcxrgkhTSebN2iXSSYayfke-nUGtzD7xYJL2E9Y4ZStD9gaHTy4WxO827z9fngMMKsEI16CXzkfk9E4mpVTKQfAxuHVbLwt_30hYDQ6YWNtdoBn5cao1QK4FHjxqfiMmnH6AaHc5o1pDHkVD9DOpOYI757PfXRz_uX69Ft19f3rxennq0ozytpKSd1oPsFI24HIQSjRsRE0I3qamKKtFAz4WLNpUESKQQ1UCM3aQXa6bfSk2D463HrLKD8zxNRbEzXMpVHwOfZ1y0hNGyF4QT_-g659Dq50V6jNFrloaKE-bamytBgDTP0SjFXhvqek30TUl4j6p4gK--HZmAcL41_yJZMCHG-BOzPD_f9N_eXJ9Vb5B7Mqn84</recordid><startdate>202310</startdate><enddate>202310</enddate><creator>Zhang, Yang</creator><creator>Wu, Chunmiao</creator><creator>Li, Qiang</creator><creator>Fang, Sheng</creator><creator>Hou, Min</creator><creator>Zhang, Sunfu</creator><creator>Dong, Xingyu</creator><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-1752-8920</orcidid></search><sort><creationdate>202310</creationdate><title>Development of a tumor microenvironment‐related prognostic signature in glioma to predict immune landscape and potential therapeutic drugs</title><author>Zhang, Yang ; Wu, Chunmiao ; Li, Qiang ; Fang, Sheng ; Hou, Min ; Zhang, Sunfu ; Dong, Xingyu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3138-a7c5c4fed18b07b6a693dec30cff3a18763e4d23fba076bab166c38b79c85cfa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Cluster analysis</topic><topic>drug sensitivity</topic><topic>Glioma</topic><topic>Immunology</topic><topic>Immunosuppressive agents</topic><topic>Medical prognosis</topic><topic>Metastases</topic><topic>Patients</topic><topic>prognostic signature</topic><topic>Regression analysis</topic><topic>Risk groups</topic><topic>Subgroups</topic><topic>Tumor microenvironment</topic><topic>Tumors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Yang</creatorcontrib><creatorcontrib>Wu, Chunmiao</creatorcontrib><creatorcontrib>Li, Qiang</creatorcontrib><creatorcontrib>Fang, Sheng</creatorcontrib><creatorcontrib>Hou, Min</creatorcontrib><creatorcontrib>Zhang, Sunfu</creatorcontrib><creatorcontrib>Dong, Xingyu</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of biochemical and molecular toxicology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Yang</au><au>Wu, Chunmiao</au><au>Li, Qiang</au><au>Fang, Sheng</au><au>Hou, Min</au><au>Zhang, Sunfu</au><au>Dong, Xingyu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of a tumor microenvironment‐related prognostic signature in glioma to predict immune landscape and potential therapeutic drugs</atitle><jtitle>Journal of biochemical and molecular toxicology</jtitle><addtitle>J Biochem Mol Toxicol</addtitle><date>2023-10</date><risdate>2023</risdate><volume>37</volume><issue>10</issue><spage>e23448</spage><epage>n/a</epage><pages>e23448-n/a</pages><issn>1095-6670</issn><eissn>1099-0461</eissn><abstract>The involvement of the tumor microenvironment (TME) in the biology of gliomas has expanded, while it is yet uncertain its potential of supporting diagnosis and therapy choices. 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| source | Wiley-Blackwell Journals |
| subjects | Cluster analysis drug sensitivity Glioma Immunology Immunosuppressive agents Medical prognosis Metastases Patients prognostic signature Regression analysis Risk groups Subgroups Tumor microenvironment Tumors |
| title | Development of a tumor microenvironment‐related prognostic signature in glioma to predict immune landscape and potential therapeutic drugs |
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