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

Author

Listed:
  • Leland S. Hu

    (Mayo Clinic Arizona
    Mayo Clinic Arizona
    Mayo Clinic Arizona)

  • Fulvio D’Angelo

    (University of Miami)

  • Taylor M. Weiskittel

    (Mayo Clinic Alix School of Medicine Minnesota
    Mayo Clinic)

  • Francesca P. Caruso

    (University of Naples, “Federico II”
    BIOGEM Institute of Molecular Biology and Genetics)

  • Shannon P. Fortin Ensign

    (Mayo Clinic Arizona
    Mayo Clinic Arizona)

  • Mylan R. Blomquist

    (Mayo Clinic Arizona
    Mayo Clinic
    Mayo Clinic Alix School of Medicine Arizona)

  • Matthew J. Flick

    (Mayo Clinic Arizona
    Mayo Clinic Arizona
    Mayo Clinic Alix School of Medicine Arizona)

  • Lujia Wang

    (Georgia Institute of Technology)

  • Christopher P. Sereduk

    (Mayo Clinic Arizona
    Mayo Clinic Arizona)

  • Kevin Meng-Lin

    (Mayo Clinic)

  • Gustavo Leon

    (Mayo Clinic Arizona)

  • Ashley Nespodzany

    (Dignity Health)

  • Javier C. Urcuyo

    (Mayo Clinic Arizona)

  • Ashlyn C Gonzales

    (Dignity Health)

  • Lee Curtin

    (Mayo Clinic Arizona)

  • Erika M. Lewis

    (Arizona State University)

  • Kyle W. Singleton

    (Mayo Clinic Arizona)

  • Timothy Dondlinger

    (Imaging Biometrics, LLC, Elm Grove)

  • Aliya Anil

    (Dignity Health)

  • Natenael B. Semmineh

    (University of Texas MD Anderson Cancer Center)

  • Teresa Noviello

    (University of Naples, “Federico II”
    BIOGEM Institute of Molecular Biology and Genetics)

  • Reyna A. Patel

    (Mayo Clinic Arizona)

  • Panwen Wang

    (Mayo Clinic Arizona)

  • Junwen Wang

    (The University of Hong Kong)

  • Jennifer M. Eschbacher

    (Dignity Health)

  • Andrea Hawkins-Daarud

    (Mayo Clinic Arizona)

  • Pamela R. Jackson

    (Mayo Clinic Arizona)

  • Itamar S. Grunfeld

    (The City University of New York
    The City University of New York)

  • Christian Elrod

    (Avinger Incorporated)

  • Gina L. Mazza

    (Mayo Clinic Arizona)

  • Sam C. McGee

    (Arizona State University)

  • Lisa Paulson

    (Mayo Clinic Arizona)

  • Kamala Clark-Swanson

    (Mayo Clinic Arizona)

  • Yvette Lassiter-Morris

    (Mayo Clinic Arizona)

  • Kris A. Smith

    (Barrow Neurological Institute, Dignity Health)

  • Peter Nakaji

    (Banner University Medical Center, University of Arizona)

  • Bernard R. Bendok

    (Mayo Clinic Arizona)

  • Richard S. Zimmerman

    (Mayo Clinic Arizona)

  • Chandan Krishna

    (Mayo Clinic Arizona)

  • Devi P. Patra

    (Mayo Clinic Arizona)

  • Naresh P. Patel

    (Mayo Clinic Arizona)

  • Mark Lyons

    (Mayo Clinic Arizona)

  • Matthew Neal

    (Mayo Clinic Arizona)

  • Kliment Donev

    (Mayo Clinic Arizona)

  • Maciej M. Mrugala

    (Mayo Clinic Arizona)

  • Alyx B. Porter

    (Mayo Clinic Arizona)

  • Scott C. Beeman

    (Arizona State University)

  • Todd R. Jensen

    (Jensen Informatics LLC)

  • Kathleen M. Schmainda

    (Medical College of Wisconsin)

  • Yuxiang Zhou

    (Mayo Clinic Arizona)

  • Leslie C. Baxter

    (Mayo Clinic Arizona
    Departments of Psychiatry and Psychology)

  • Christopher L. Plaisier

    (Arizona State University)

  • Jing Li

    (Georgia Institute of Technology)

  • Hu Li

    (Mayo Clinic)

  • Anna Lasorella

    (University of Miami)

  • C. Chad Quarles

    (University of Texas MD Anderson Cancer Center)

  • Kristin R. Swanson

    (Mayo Clinic Arizona
    Mayo Clinic Arizona)

  • Michele Ceccarelli

    (University of Miami)

  • Antonio Iavarone

    (University of Miami)

  • Nhan L. Tran

    (Mayo Clinic Arizona
    Mayo Clinic Arizona)

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.

Suggested Citation

  • Leland S. Hu & Fulvio D’Angelo & Taylor M. Weiskittel & Francesca P. Caruso & Shannon P. Fortin Ensign & Mylan R. Blomquist & Matthew J. Flick & Lujia Wang & Christopher P. Sereduk & Kevin Meng-Lin & , 2023. "Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41559-1
    DOI: 10.1038/s41467-023-41559-1
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    References listed on IDEAS

    as
    1. Floris P. Barthel & Kevin C. Johnson & Frederick S. Varn & Anzhela D. Moskalik & Georgette Tanner & Emre Kocakavuk & Kevin J. Anderson & Olajide Abiola & Kenneth Aldape & Kristin D. Alfaro & Donat Alp, 2019. "Longitudinal molecular trajectories of diffuse glioma in adults," Nature, Nature, vol. 576(7785), pages 112-120, December.
    2. Véronique Frattini & Stefano M. Pagnotta & Tala & Jerry J. Fan & Marco V. Russo & Sang Bae Lee & Luciano Garofano & Jing Zhang & Peiguo Shi & Genevieve Lewis & Heloise Sanson & Vanessa Frederick & Ang, 2018. "A metabolic function of FGFR3-TACC3 gene fusions in cancer," Nature, Nature, vol. 553(7687), pages 222-227, January.
    Full references (including those not matched with items on IDEAS)

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