1. ETMM-09 TARGETING GLIOBLASTOMA MULTIFORME METABOLISM AT THE INVASIVE TUMOR FRONT
- Author
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Jungwha Cha, Erin A Akins, Manish K. Aghi, Joseph H Garcia, Sanjay Kumar, Angad Beniwal, Kayla J Wolfe, and Saket Jain
- Subjects
Malignant Brain Neoplasm ,medicine.diagnostic_test ,Metabolism ,Biology ,medicine.disease ,Phenotype ,Supplement Abstracts ,Epigenome, Transcriptome, Metabolome and Modeling ,Biopsy ,Gene expression ,Cancer research ,medicine ,AcademicSubjects/MED00300 ,AcademicSubjects/MED00310 ,KEGG ,Gene ,Glioblastoma - Abstract
Glioblastoma (GBM) is a primary malignant brain tumor with a median survival under two years. The poor prognosis GBM caries is largely due to cellular invasion, which enables escape from resection and drives inevitable recurrence. Numerous factors have been proposed as the primary driving forces behind GBM’s ability to invade adjacent tissues rapidly, including alterations in its cellular metabolism. Though studies have investigated links between GBM’s metabolic profile and its invasive capabilities, these studies have had two notable limitations. First, while infiltrating GBM cells utilize adaptive cellular machinery to overcome stressors in their microenvironment, the cells at the invasive tumor front have rarely been sampled in previous studies, which have primarily used banked tissue taken from the readily accessible tumor core. Second, studies of invasion have primarily used two-dimensional (2D) culture systems, which fail to capture the dimensionality, mechanics, and heterogeneity of GBM invasion. To address these limitations, our team developed two complementary approaches: acquisition of site-directed biopsies from patient GBMs to define regional heterogeneity in invasiveness, and engineering of three dimensional (3D) platforms to study invasion in culture. Through utilization of these platforms, and by taking advantage of the system-wide, unbiased screens of metabolite profile and gene expression available, our team looked to accomplish the goal of identifying targetable metabolic factors which drive cellular invasion in GBM. Pilot RNA-Sequencing data revealed 87 of the top 250 (35%) genes preferentially expressed in the tumor invasive edge, and 30 of the top 250 (12%) genes preferentially expressed in the tumor core were involved in cellular metabolism. KEGG pathways analysis demonstrated enrichment of glycolytic, pentose phosphate, and response to amino acid starvation pathways at the tumor invasive edge. These preliminary studies demonstrate a distinct metabolic phenotype in invasive GBM cells which will be further explored with system wide screens.
- Published
- 2021