Skip to main content
  • Integrated Prognostication of Molecular Oligodendroglioma in The Cancer Genome Atlas

    Final Number:
    34

    Authors:
    Sameer H. Halani BA, MS; Michael Nalisnik; Chad Holder; Jun Kong; Jose Enrique Velazquez Vega; Jeffrey J. Olson MD; Lee Cooper; Daniel J Brat

    Study Design:
    Laboratory Investigation

    Subject Category:

    Meeting: Congress of Neurological Surgeons 2016 Annual Meeting

    Introduction: Recent advances indicate that diffuse lower-grade gliomas are comprised of discrete, molecularly-defined disease subtypes based on IDH-mutational and 1p19q-codeletion status.1 LGGs defined by IDH mutations and 1p/19q co-deletion, corresponding to the molecular definition of ‘oligodendroglioma’ by the WHO, represent an important LGG subset whose clinical course is difficult to predict on initial presentation and early in the disease course. Using The Cancer Genome Atlas (TCGA) and model-based image analyses, we have integrated genomic profiles, magnetic resonance (MR) imaging characteristics, and histopathological features of molecular oligodendroglioma to provide possible explanation for variability in clinical course.

    Methods: Molecular oligodendroglioma in TCGA database with genomic characterization; representative digital histopathological slides; and pre-operative MR images were identified (n=49). Using model-based image analysis, endothelial cell density was quantified from digital slides. MR images were reviewed for the presence of contrast enhancement and radiographic necrosis. Survival analyses, Chi-square tests, and Wilcoxon rank-sums were used to identify correlations between histological grade, contrast enhancement, radiographic necrosis, endothelial density, and key genetic alterations in PIK3.

    Results: Overall survival was predicted by WHO histological grade (GII = 149.9 months; GIII = 83.9 months, p=0.005) (Fig1). Contrast-enhancing (CE+) tumors demonstrated worse overall survival compared to non-enhancing (CE-) tumors (Fig2), while tumors with radiographic necrosis (n=17) showed the worst overall survival (Fig3). 21 of 22 CE+ tumors were WHO grade III. Increased endothelial cell density was found in the following subsets: grade III, + radiographic necrosis, and mutated PIK3 (Fig4A-C).

    Conclusions: Integration of classic histological grading systems and MR characteristics better predict overall survival, and differentiate indolent from aggressive behavior in molecular oligodendroglioma. Markers associated with poor prognosis include tumor proliferation and angiogenesis, represented by endothelial cell density and +CE on MR images. Further investigation of PIK3 mutational status may shed light on a molecular basis for increased angiogenesis.

    Patient Care: The advances that have occurred in the molecular understanding of LGG, including oligodendroglioma, represent much more than shifting definitions and diagnostic platforms. We are now at a point in time where cohesive disease groups have been clearly delineated, offering the chance to investigate the molecular, biological and clinical properties of diffuse gliomas with better clarity. These findings open the door for many opportunities to understand networks, signaling pathways and biomarkers of progression and response to therapy in this disease now that it has been defined in a biologically meaningful manner. Ultimately, this will allow for definitive advancement in the understanding of how oligodendroglioma progresses and to offer solutions for optimal clinical care and therapeutic targets.

    Learning Objectives: By the conclusion of this session, participants should be able to: 1.) Identify the molecular signature of oligodendroglioma 2.) Understand the importance of histological grading and radiographic features in the new paradigm of molecular classification for lower-grade gliomas 3.) Appreciate the role of image-based analysis in quantifying and better prognosticating brain tumors

    References: 1. Cancer Genome Atlas Research N, Brat DJ, Verhaak RG, et al. Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas. N Engl J Med. Jun 25 2015;372(26):2481-2498

We use cookies to improve the performance of our site, to analyze the traffic to our site, and to personalize your experience of the site. You can control cookies through your browser settings. Please find more information on the cookies used on our site. Privacy Policy