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Quantifying Tumor Heterogeneity via MRI Habitats to Characterize Microenvironmental Alterations in HER2+ Breast Cancer.
Kazerouni, Anum S; Hormuth, David A; Davis, Tessa; Bloom, Meghan J; Mounho, Sarah; Rahman, Gibraan; Virostko, John; Yankeelov, Thomas E; Sorace, Anna G.
Afiliação
  • Kazerouni AS; Department of Radiology, The University of Washington, Seattle, WA 98104, USA.
  • Hormuth DA; Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX 78712, USA.
  • Davis T; Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA.
  • Bloom MJ; Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
  • Mounho S; Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
  • Rahman G; Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
  • Virostko J; Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
  • Yankeelov TE; Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78712, USA.
  • Sorace AG; Department of Diagnostic Medicine, The University of Texas at Austin, Austin, TX 78712, USA.
Cancers (Basel) ; 14(7)2022 Apr 06.
Article em En | MEDLINE | ID: mdl-35406609
ABSTRACT
This study identifies physiological habitats using quantitative magnetic resonance imaging (MRI) to elucidate intertumoral differences and characterize microenvironmental response to targeted and cytotoxic therapy. BT-474 human epidermal growth factor receptor 2 (HER2+) breast tumors were imaged before and during treatment (trastuzumab, paclitaxel) with diffusion-weighted MRI and dynamic contrast-enhanced MRI to measure tumor cellularity and vascularity, respectively. Tumors were stained for anti-CD31, anti-ɑSMA, anti-CD45, anti-F4/80, anti-pimonidazole, and H&E. MRI data was clustered to identify and label each habitat in terms of vascularity and cellularity. Pre-treatment habitat composition was used stratify tumors into two "tumor imaging phenotypes" (Type 1, Type 2). Type 1 tumors showed significantly higher percent tumor volume of the high-vascularity high-cellularity (HV-HC) habitat compared to Type 2 tumors, and significantly lower volume of low-vascularity high-cellularity (LV-HC) and low-vascularity low-cellularity (LV-LC) habitats. Tumor phenotypes showed significant differences in treatment response, in both changes in tumor volume and physiological composition. Significant positive correlations were found between histological stains and tumor habitats. These findings suggest that the differential baseline imaging phenotypes can predict response to therapy. Specifically, the Type 1 phenotype indicates increased sensitivity to targeted or cytotoxic therapy compared to Type 2 tumors.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article