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Article: Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures

TitleIntegrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures
Authors
Issue Date28-Sep-2023
PublisherNature Research
Citation
Nature Communications, 2023, v. 14, n. 1, p. 6066 How to Cite?
Abstract

Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.


Persistent Identifierhttp://hdl.handle.net/10722/337418
ISSN
2023 Impact Factor: 14.7
2023 SCImago Journal Rankings: 4.887
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHu, Leland S-
dc.contributor.authorD’Angelo, Fulvio-
dc.contributor.authorWeiskittel, Taylor M-
dc.contributor.authorCaruso, Francesca P-
dc.contributor.authorFortin, Ensign Shannon P-
dc.contributor.authorBlomquist, Mylan R-
dc.contributor.authorFlick, Matthew J-
dc.contributor.authorWang, Lujia-
dc.contributor.authorSereduk, Christopher P-
dc.contributor.authorMeng-Lin, Kevin-
dc.contributor.authorde Leon, Gustavo-
dc.contributor.authorNespodzany, Ashley-
dc.contributor.authorUrcuyo, Javier C-
dc.contributor.authorGonzales, Ashlyn C-
dc.contributor.authorCurtin, Lee-
dc.contributor.authorLewis, Erika M-
dc.contributor.authorSingleton, Kyle W-
dc.contributor.authorDondlinger, Timothy-
dc.contributor.authorAnil, Aliya-
dc.contributor.authorSemmineh, Natenael B-
dc.contributor.authorNoviello, Teresa-
dc.contributor.authorPatel, Reyna A-
dc.contributor.authorWang, Panwen-
dc.contributor.authorWang, Junwen-
dc.contributor.authorEschbacher, Jennifer M-
dc.contributor.authorHawkins-Daarud, Andrea-
dc.contributor.authorJackson, Pamela R-
dc.contributor.authorGrunfeld, Itamar S-
dc.contributor.authorElrod, Christian-
dc.contributor.authorMazza, Gina L-
dc.contributor.authorMcGee, Sam C-
dc.contributor.authorPaulson, Lisa-
dc.contributor.authorClark-Swanson, Kamala-
dc.contributor.authorLassiter-Morris, Yvette-
dc.contributor.authorSmith, Kris A-
dc.contributor.authorNakaji, Peter-
dc.contributor.authorBendok, Bernard R-
dc.contributor.authorZimmerman, Richard S-
dc.contributor.authorKrishna, Chandan-
dc.contributor.authorPatra, Devi P-
dc.contributor.authorPatel, Naresh P-
dc.contributor.authorLyons, Mark-
dc.contributor.authorNeal, Matthew-
dc.contributor.authorDonev, Kliment-
dc.contributor.authorMrugala, Maciej M-
dc.contributor.authorPorter, Alyx B-
dc.contributor.authorBeeman, Scott C-
dc.contributor.authorJensen, Todd R-
dc.contributor.authorSchmainda, Kathleen M-
dc.contributor.authorZhou, Yuxiang-
dc.contributor.authorBaxter, Leslie C-
dc.contributor.authorPlaisier, Christopher L-
dc.contributor.authorLi, Jing-
dc.contributor.authorLi, Hu-
dc.contributor.authorLasorella, Anna-
dc.contributor.authorQuarles, C Chad-
dc.contributor.authorSwanson, Kristin R-
dc.contributor.authorCeccarelli, Michele-
dc.contributor.authorIavarone, Antonio-
dc.contributor.authorTran, Nhan L-
dc.date.accessioned2024-03-11T10:20:43Z-
dc.date.available2024-03-11T10:20:43Z-
dc.date.issued2023-09-28-
dc.identifier.citationNature Communications, 2023, v. 14, n. 1, p. 6066-
dc.identifier.issn2041-1723-
dc.identifier.urihttp://hdl.handle.net/10722/337418-
dc.description.abstract<p>Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.</p>-
dc.languageeng-
dc.publisherNature Research-
dc.relation.ispartofNature Communications-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleIntegrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures-
dc.typeArticle-
dc.identifier.doi10.1038/s41467-023-41559-1-
dc.identifier.scopuseid_2-s2.0-85172828207-
dc.identifier.volume14-
dc.identifier.issue1-
dc.identifier.spage6066-
dc.identifier.eissn2041-1723-
dc.identifier.isiWOS:001080410400034-
dc.identifier.issnl2041-1723-

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