Lewis, Erika

Abstract High grade glioma (HGG) represents a group of devastating diseases with dismal prognosis. Surgical resection of the contrast enhancing (CE) region of HGG remains the mainstay of treatment, but recurrence inevitably arises from the unresected non-contrast enhancing (NE) region, surgically inaccessible due to cancer cell invasion into healthy brain tissue. Due to its critical role in recurrence, understanding of the NE region is central to the improvement of clinical outcomes. We reveal the biological characteristics of this region through image localized multi-regional sampling. We linked microenvironmental characteristics measured by multi-parametric MRI to genomic mutations and transcriptional phenotypes using mixed effect modeling which allowed us to control for individualized patient effects. We first confirmed that T2 is a significant indicator of IDH mutation status in the NE region, being the first description of such a relationship in a HGG cohort. We found the combination of EGFR amplification and CDKN2A homozygous loss was associated with a significantly lower mean diffusivity (MD) compared to double wild type tumors in the NE region, indicating the presence of greater cellular packing and proliferation in EGFR amplification/CDKN2A loss regions. Finally, using single cell pathway based tumor classifications, we showed that nK2, a DSC-MRI metric representing cell size heterogeneity, correlated positively with neuronal signature and negatively with glycolytic/plurimetabolic signature within the NE tumor, indicating that glycolytic/plurimetobolic tumors possessed a high amount of cell size heterogeneity compared to neuronal samples. This hypothesis was supported using digital reference object (DRO) modeling which confirmed that cell size and heterogeneity drove the differential nK2 signal between neuronal and glycolytic/plurimetabolic samples. We identified immune cell infiltrate as one possible mechanism of increased cell size heterogeneity using transcriptomic signature analysis which found more immune cell signatures within glycolytic/plurimetobolic tumors compared to neuronal. Collectively this study demonstrates the central role of multi-parametric MRI as a non-invasive measure of tumor biology and a tool for understanding the clinically critical NE region which can then inform new therapies targeting this region of HGG recurrence. Citation Format: Matthew Flick, Taylor Weiskittel, Kevin Meng-Lin, Fulvio D'Angelo, Francesca Caruso, Shannon Ensign, Mylan Blomquist, Luija Wang, Christopher Sereduk, Gustavo De Leon, Ashley Nespodzany, Javier Urcuyo, Ashlynn Gonzalez, Lee Curtin, Kyle Singleton, Aliya Anil, Natenael Simmineh, Erika Lewis, Teresa Noviello, Reyna Patel, Panwen Wang, Junwen Wang, Jennifer Eschbacher, Andrea Hawkins-Daarud, Pamela Jackson, Kris Smith, Peter Nakaji, Bernard Bendok, Richard Zimmerman, Chandan Krishna, Devi Patra, Naresh Patel, Mark Lyons, Matthew Neal, Kliment Donev, Maciej Mrugala, Alyx Porter, Scott Beeman, Yuxiang Zhou, Leslie Baxter, Christopher Plaisier, Jing Li, Hu Li, Anna Lasorella, Chad Quarles, Kristin Swanson, Michele Ceccarelli, Antonio Iavarone, Nhan Tran, Leland Hu. Multi-parametric MRI maps regional heterogeneity of high grade glioma phenotypes. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5621.

Abstract The brain is notoriously difficult to access because of its location and protective mechanisms, both internal and external. Imaging-based approaches, such as multiparametric magnetic resonance imaging (mpMRI), provide a method to bypass these obstacles. mpMRI can capture a wide range of data from tumors embedded in brain tissue through various imaging features. However, the biological function captured by each imaging feature remains largely unknown, particularly within the aggressive disease glioblastoma multiforme (GBM). We integrated our GBM SYstems Genetics Network AnaLysis (gbmSYGNAL) gene regulatory network (Plaisier, et al. 2016), based on the multi-omic patient data from The Cancer Genome Atlas (TCGA), with mpMRI-localized patient tumor biopsies. The gbmSYGNAL network was reconstructed within the new image-localized biopsies, and associations revealed a strong connection between the spoiled gradient recalled echo + contrast (SPGR+C) feature and the immune hallmarks of cancer. The SPGR+C method generates an image by employing a contrast agent that bypasses the blood brain barrier (BBB) through leaky blood vessels that have weakened from the force of the rapidly growing GBM tumor. Furthermore, a significant association between SPGR+C signal and the presence of both infiltrating macrophages and T cells indicated that peripheral immune cells may also cross the BBB at these leaky sites. Separately, the mean diffusivity (MD) & T2 features were linked to the sustained angiogenesis hallmark. These features displayed high association with angiogenic genes, such as FLT1, KDR, and PDGFRB, and correlated with the presence of histologically identified vessels. Detection of these disease-relevant functions via mpMRI features has powerful clinical applications, providing a non-invasive approach to GBM diagnosis, prognosis, and treatment direction.