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  • New Practice-Changing Study Findings Presented at ASCO

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    JAMA. 2014; 312(3):218-219. doi: 10.1001/jama.2014.7708
  • Glioblastoma and Other Malignant Gliomas: A Clinical Review

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    JAMA. 2013; 310(17):1842-1850. doi: 10.1001/jama.2013.280319

    Omuro and DeAngelis review the clinical management of malignant gliomas, including genetic and environmental risk factors such as cell phones, diagnostic pitfalls, symptom management, specific antitumor therapy, and common complications.

  • Gliomas

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    JAMA. 2010; 303(10):1000-1000. doi: 10.1001/jama.303.10.1000
  • JAMA March 10, 2010

    Figure 2: Magnetic Resonance Spectroscopy at Second Recurrence of Ms Q's Tumor

    The 3 peaks from left to right represent choline, creatinine, and N-acetylaspartate. In normal brain, N-acetylaspartate is the prevalent peak. In tumors of higher grade, the choline peak becomes the largest and the ratio of choline to creatinine is indicative of the grade. Ratios of 2 or higher are associated with more malignant phenotypes in gliomas. Here, the ratio is 2.87. The tumor otherwise had features consistent with a low-grade recurrence; the magnetic resonance spectroscopy was the only indicator of a malignant regrowth.
  • Clinical and Mutational Spectrum of Neurofibromatosis Type 1–like Syndrome

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    JAMA. 2009; 302(19):2111-2118. doi: 10.1001/jama.2009.1663
  • JAMA July 15, 2009

    Figure 1: Gene Dosage Alterations Across the Glioma Genome

    Cartesian line diagrams depict the frequency of gene dosage alteration across a tumor population for genes mapped according to genome position along the chromosomes (X and Y chromosomes omitted). Gene dosage profiles were generated using circular binary segmentation change point analysis of microarray-based genomic hybridization profiles. Both the discovery and validation sets show consistently high frequencies of alterations involving chromosomes 1p, 7, 8q, 9p, 10, 12, 13, 19, 20, and 22. IMAGE indicates Integrated Molecular Analysis of Genomes and Their Expression Consortium.
  • JAMA July 15, 2009

    Figure 2: Model of a Nonrandom Genetic Landscape in Gliomas: Discovery Set

    A permutation-based approach, which calculates the probabilistic fit for the coincidence of distinct chromosomal alterations, was applied to the gene dosage data in the discovery set from Stanford University. The gene dosage data generated by the circular binary segmentation change point algorithm were averaged according to 802 cytogenetic bands (cytobands)—subregions of a chromosome visible microscopically after special staining—that correspond to an International System for Human Cytogenetic Nomenclature (ISCN) 850 chromosome ideogram. The association map (A) indicates chromosomal regions (territories) with significant co-occurrence of gene dosage alteration (false-discovery rate [FDR]–corrected P<.05). Red scores denote the significant association of 2 chromosomal gains or 2 chromosomal losses; blue scores, the significant association of a gain and a loss event. The color gradation reflects a score that indicates the significance of cytoband-cytoband associations. The association map shows a consistent pattern of significant associations, which denotes a nonrandom genetic landscape in gliomas. B, Chromosomal territories that showed an alteration frequency of greater than 10% (involving chromosomes 1p, 7, 8q, 9p, 10, 12, 13, 19, 20, and 22) in the discovery set and their significant associations are mapped to a human ISCN-850 chromosome ideogram. (See interactive Figure 1 showing significant associations in the discovery and validation sets).
  • JAMA July 15, 2009

    Figure 3: Model of a Nonrandom Genetic Landscape in Gliomas: Confirmation by Validation Set

    Permutation-based approach described in Figure 2 was applied to the validation set from The Cancer Genome Atlas Pilot Project (TCGA). The association map (A) indicates chromosomal regions (territories) with significant co-occurrence of gene dosage alteration (false-discovery rate [FDR]–corrected P<.05). Red scores denote the significant association of 2 chromosomal gains or 2 chromosomal losses; blue scores, the significant association of a gain and a loss event. The color gradation reflects a score that indicates the significance of cytoband-cytoband associations. The association map shows a consistent pattern of significant associations, which denotes a nonrandom genetic landscape in gliomas. B, Significant associations identified in the discovery set (Figure 2B) that were confirmed in the TCGA validation set. The blue bars and corresponding blue labels indicate chromosome territories with TCGA-confirmed significant associations to other territories (TCGA-validated nonrandom genetic landscape). (See interactive Figure 1 showing significant associations in the discovery and validation sets).
  • JAMA July 15, 2009

    Figure 4: Complex Network of Glioma Gene Interactions Highlighting Hub Gene–Hub Gene and Hub Gene–Hub-Interacting Gene Interactions

    Graphical representation of the interactions and networking of 214 glioma genes. The 214 genes represent the subset of all 1562 genes with significant gene dosage–transcript relationships (false-discovery rate–adjusted q<.10) that map to the top-scoring subnetworks identified in a network modeling approach using Ingenuity Pathway Analysis. These subnetworks were merged using a force-directed layout algorithm to form a composite network representing the underlying biology of the process. Genes are represented as nodes using various shapes that represent the functional class of the gene product. The interactions of genes with tumor-related biological functions and fulfilling the criterion of a network hub (11 genes) or interacting with hub genes (hub-interacting gene; 92 genes) are highlighted. Hub gene refers to a gene that shows a number of interactions with other genes (the hub-interacting genes or other hub genes) that is above the 95% quantile of the overall distribution of the number of interactions of all genes in the network (eFigure 5A). Cooperatively tumorigenic interactions are interactions for which integration of the mode of interaction for a hub-hub (solid red lines) or hub–hub-interacting gene pair (blue lines) with the direction of gene dosage–gene expression change (gain or loss) reveals an effect on this interaction that synergistically promotes tumorigenesis. Paired t testing comparing the number of cooperative vs noncooperative interactions for 11 hub genes with each other and 92 hub-interacting genes with tumor-related functions reveals a significant prevalence (P = .003) of cooperatively tumorigenic interactions (125 [71.8%] of all 174 interactions) (eFigure 4). (See interactive Figure 2 of the complete network).
  • JAMA July 15, 2009

    Figure 7: Multigene Risk Scoring Model in Malignant Gliomas

    Patient assignment to low-, moderate-, and high-risk groups is based on risk scores generated by the number of gene dosage alterations (0-2, 3-4, and 5-7, respectively) of 7 landscape genes (POLD2, CYCS, MYC, AKR1C3, YME1L1, ANXA7, and PDCD4), each of which was individually linked to patient survival in Cox proportional hazard regression analyses in The Cancer Genome Atlas Pilot Project (TCGA). A, Kaplan-Meier estimates of overall survival for the 3 groups in 189 glioblastomas from TCGA) with available survival data. Median follow-up for the low-, moderate-, and high-risk groups was 62.9 (range, 10.6-503.4), 49.3 (range, 2.4-307.4), and 51.0 (range, 1.1-183.1) weeks, respectively. B, Estimates of overall survival in the University of Texas M. D. Anderson Cancer Center (MDA) validation set of 76 high-grade gliomas. Median follow-up for the low-, moderate-, and high-risk groups was 175 (range, 33-477) weeks, 70 (range, 12-467) weeks, and 62 (range, 3-311) weeks, respectively. C, Estimates of overall survival in the University of California, Los Angeles (UCLA) validation set of 70 high-grade gliomas. Median follow-up for the low-, moderate-, and high-risk groups was 128.5 (range, 6-359) weeks, 58.5 (range, 8-320) weeks, and 49 (range, 1-147) weeks, respectively. D, Estimates of overall survival in the unified validation set of 191 glioblastomas. Median follow-up for the low-, moderate-, and high-risk groups was 73 (range, 1-479), 57.5 (range, 8-313), and 47 (range, 1-242) weeks, respectively.
  • A Network Model of a Cooperative Genetic Landscape in Brain Tumors

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    JAMA. 2009; 302(3):261-275. doi: 10.1001/jama.2009.997
  • Patterns of Care for Adults With Newly Diagnosed Malignant Glioma

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    JAMA. 2005; 293(5):557-564. doi: 10.1001/jama.293.5.557
  • JAMA November 14, 2012

    Figure 2: Survival Analysis Comparing Favored Surgical Strategies for Low-Grade Gliomas

    This is a regional comparison of results of the 2 favored surgical strategies (but including patients at hospital A treated with resection and patients at hospital B undergoing biopsy only). Biopsy preferred (hospital A): 29% initial resections. Resection preferred (hospital B): 86% initial resections. There was a significant difference in survival between patients treated at the 2 hospitals (P = .01). The shaded areas indicate 95% CIs. Median survival was 5.9 years (95% CI, 4.5-7.3) in the center in which biopsy and watchful waiting was preferred. Median survival was not reached in the center in which early resection was the preferred strategy.