A combinatorial radiographic phenotype may stratify patient survival and be associated with invasion and proliferation characteristics in glioblastoma

View More View Less
  • 1 Departments of Bioinformatics and Computational Biology,
  • 2 Neurosurgery, and
  • 7 Diagnostic Radiology, University of Texas M.D. Anderson Cancer Center, Houston, Texas;
  • 3 Department of Biomedical Informatics, Emory University, Atlanta, Georgia;
  • 4 Department of Radiology, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania;
  • 5 Department of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, Tennessee;
  • 6 Department of Radiology, Stanford University, Stanford, California;
  • 8 Department of Neurosurgery, Baylor College of Medicine, Houston, Texas;
  • 9 Department of Radiology, New York University School of Medicine, New York, New York;
  • 10 Department of Interventional Neuroradiology, Stanford Medical Center, Stanford, California;
  • 11 Leidos Biomedical Research, Inc., Frederick National Laboratory, Frederick, Maryland, and
  • 12 Department of Radiology, Boston University School of Medicine, Boston, Massachusetts
Restricted access

Purchase Now

USD  $45.00

JNS + Pediatrics - 1 year subscription bundle (Individuals Only)

USD  $505.00

JNS + Pediatrics + Spine - 1 year subscription bundle (Individuals Only)

USD  $600.00
Print or Print + Online

OBJECT

Individual MRI characteristics (e.g., volume) are routinely used to identify survival-associated phenotypes for glioblastoma (GBM). This study investigated whether combinations of MRI features can also stratify survival. Furthermore, the molecular differences between phenotype-induced groups were investigated.

METHODS

Ninety-two patients with imaging, molecular, and survival data from the TCGA (The Cancer Genome Atlas)-GBM collection were included in this study. For combinatorial phenotype analysis, hierarchical clustering was used. Groups were defined based on a cutpoint obtained via tree-based partitioning. Furthermore, differential expression analysis of microRNA (miRNA) and mRNA expression data was performed using GenePattern Suite. Functional analysis of the resulting genes and miRNAs was performed using Ingenuity Pathway Analysis. Pathway analysis was performed using Gene Set Enrichment Analysis.

RESULTS

Clustering analysis reveals that image-based grouping of the patients is driven by 3 features: volume-class, hemorrhage, and T1/FLAIR-envelope ratio. A combination of these features stratifies survival in a statistically significant manner. A cutpoint analysis yields a significant survival difference in the training set (median survival difference: 12 months, p = 0.004) as well as a validation set (p = 0.0001). Specifically, a low value for any of these 3 features indicates favorable survival characteristics. Differential expression analysis between cutpoint-induced groups suggests that several immune-associated (natural killer cell activity, T-cell lymphocyte differentiation) and metabolism-associated (mitochondrial activity, oxidative phosphorylation) pathways underlie the transition of this phenotype. Integrating data for mRNA and miRNA suggests the roles of several genes regulating proliferation and invasion.

CONCLUSIONS

A 3-way combination of MRI phenotypes may be capable of stratifying survival in GBM. Examination of molecular processes associated with groups created by this combinatorial phenotype suggests the role of biological processes associated with growth and invasion characteristics.

ABBREVIATIONSAUC = area under the curve; EMT = epithelial-to-mesenchymal transition; FDR = false discovery rate; GBM = glioblastoma; GSEA = Gene Set Enrichment Analysis; IPA = Ingenuity Pathway Analysis; miRNA = microRNA; OXPHOS = oxidative phosphorylation; PFS = progression-free survival; ROC = receiver operating characteristic; TCGA = The Cancer Genome Atlas; TCIA = The Cancer Imaging Archive; VASARI = Visually AcceSAble Rembrandt Images.

JNS + Pediatrics - 1 year subscription bundle (Individuals Only)

USD  $505.00

JNS + Pediatrics + Spine - 1 year subscription bundle (Individuals Only)

USD  $600.00

Contributor Notes

Correspondence Arvind Rao, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Unit 1410, Houston, TX 77030. email: aruppore@mdanderson.org.

INCLUDE WHEN CITING Published online October 16, 2015; DOI: 10.3171/2015.4.JNS142732.

Disclosure Mr. Kirby has direct stock ownership in Myriad Genetics.

  • 1

    Benjamini Y, & Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Royal Stat Soc Series B-Methodological 57:289300, 1995

    • Search Google Scholar
    • Export Citation
  • 2

    Chen H, , Chen Y, , Zhao Y, , Fan W, , Zhou K, & Liu Y, : Association of sequence variants on chromosomes 20, 11, and 5 (20q13.33, 11q23.3, and 5p15.33) with glioma susceptibility in a Chinese population. Am J Epidemiol 173:915922, 2011

    • Search Google Scholar
    • Export Citation
  • 3

    Cloughesy TF, , Cavenee WK, & Mischel PS: Glioblastoma: from molecular pathology to targeted treatment. Annu Rev Pathol 9:125, 2014

  • 4

    Diehn M, , Nardini C, , Wang DS, , McGovern S, , Jayaraman M, & Liang Y, : Identification of noninvasive imaging surrogates for brain tumor gene-expression modules. Proc Natl Acad Sci USA 105:52135218, 2008

    • Search Google Scholar
    • Export Citation
  • 5

    Ermoian RP, , Kaprealian T, , Lamborn KR, , Yang X, , Jelluma N, & Arvold ND, : Signal transduction molecules in gliomas of all grades. J Neurooncol 91:1926, 2009

    • Search Google Scholar
    • Export Citation
  • 6

    Furnari FB, , Fenton T, , Bachoo RM, , Mukasa A, , Stommel JM, & Stegh A, : Malignant astrocytic glioma: genetics, biology, and paths to treatment. Genes Dev 21:26832710, 2007

    • Search Google Scholar
    • Export Citation
  • 7

    Gower JC: General coefficient of similarity and some of its properties. Biometrics 27:857, 1971

  • 8

    Griguer CE, & Oliva CR: Bioenergetics pathways and therapeutic resistance in gliomas: emerging role of mitochondria. Curr Pharm Des 17:24212427, 2011

    • Search Google Scholar
    • Export Citation
  • 9

    Gutman DA, , Cooper LA, , Hwang SN, , Holder CA, , Gao J, & Aurora TD, : MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set. Radiology 267:560569, 2013

    • Search Google Scholar
    • Export Citation
  • 10

    Hammoud MA, , Sawaya R, , Shi W, , Thall PF, & Leeds NE: Prognostic significance of preoperative MRI scans in glioblastoma multiforme. J Neurooncol 27:6573, 1996

    • Search Google Scholar
    • Export Citation
  • 11

    Hur K, , Toiyama Y, , Takahashi M, , Balaguer F, , Nagasaka T, & Koike J, : MicroRNA-200c modulates epithelial-to-mesenchymal transition (EMT) in human colorectal cancer metastasis. Gut 62:13151326, 2013

    • Search Google Scholar
    • Export Citation
  • 12

    Ivkovic S, , Beadle C, , Noticewala S, , Massey SC, , Swanson KR, & Toro LN, : Direct inhibition of myosin II effectively blocks glioma invasion in the presence of multiple motogens. Mol Biol Cell 23:533542

    • Search Google Scholar
    • Export Citation
  • 13

    Jain R, , Poisson L, , Narang J, , Gutman D, , Scarpace L, & Hwang SN, : Genomic mapping and survival prediction in glioblastoma: molecular subclassification strengthened by hemodynamic imaging biomarkers. Radiology 267:212220, 2013

    • Search Google Scholar
    • Export Citation
  • 14

    Janiszewska M, , Suvà ML, , Riggi N, , Houtkooper RH, , Auwerx J, & Clément-Schatlo V, : Imp2 controls oxidative phosphorylation and is crucial for preserving glioblastoma cancer stem cells. Genes Dev 26:19261944, 2012

    • Search Google Scholar
    • Export Citation
  • 15

    Katakowski M, , Zheng X, , Jiang F, , Rogers T, , Szalad A, & Chopp M: MiR-146b-5p suppresses EGFR expression and reduces in vitro migration and invasion of glioma. Cancer Invest 28:10241030, 2010

    • Search Google Scholar
    • Export Citation
  • 16

    Korpal M, , Lee ES, , Hu G, & Kang Y: The miR-200 family inhibits epithelial-mesenchymal transition and cancer cell migration by direct targeting of E-cadherin transcriptional repressors ZEB1 and ZEB2. J Biol Chem 283:1491014914, 2008

    • Search Google Scholar
    • Export Citation
  • 17

    Pope WB, , Sayre J, , Perlina A, , Villablanca JP, , Mischel PS, & Cloughesy TF: MR imaging correlates of survival in patients with high-grade gliomas. AJNR Am J Neuroradiol 26:24662474, 2005

    • Search Google Scholar
    • Export Citation
  • 18

    Lacroix M, , Abi-Said D, , Fourney DR, , Gokaslan ZL, , Shi W, & DeMonte F, : A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. J Neurosurg 95:190198, 2001

    • Search Google Scholar
    • Export Citation
  • 19

    Lee HK, , Bier A, , Cazacu S, , Finniss S, , Xiang C, & Twito H, : MicroRNA-145 is downregulated in glial tumors and regulates glioma cell migration by targeting connective tissue growth factor. PLoS One 8:e54652, 2013

    • Search Google Scholar
    • Export Citation
  • 20

    Liu X, , Zhang Z, , Sun L, , Chai N, , Tang S, & Jin J, : MicroR-NA-499-5p promotes cellular invasion and tumor metastasis in colorectal cancer by targeting FOXO4 and PDCD4. Carcinogenesis 32:17981805, 2011

    • Search Google Scholar
    • Export Citation
  • 21

    Mischel PS, & Cloughesy TF: Targeted molecular therapy of GBM. Brain Pathol 13:5261, 2003

  • 22

    Nikaki A, , Piperi C, & Papavassiliou AG: Role of microRNAs in gliomagenesis: targeting miRNAs in glioblastoma multiforme therapy. Expert Opin Investig Drugs 21:14751488, 2012

    • Search Google Scholar
    • Export Citation
  • 23

    Phillips JJ, , Huillard E, , Robinson AE, , Ward A, , Lum DH, & Polley MY, : Heparan sulfate sulfatase SULF2 regulates PDGFRa signaling and growth in human and mouse malignant glioma. J Clin Invest 122:911922, 2012

    • Search Google Scholar
    • Export Citation
  • 24

    Pope WB, , Mirsadraei L, , Lai A, , Eskin A, , Qiao J, & Kim HJ, : Differential gene expression in glioblastoma defined by ADC histogram analysis: relationship to extracellular matrix molecules and survival. AJNR Am J Neuroradiol 33:10591064, 2012

    • Search Google Scholar
    • Export Citation
  • 25

    Prins RM, , Soto H, , Konkankit V, , Odesa SK, , Eskin A, & Yong WH, : Gene expression profile correlates with T-cell infiltration and relative survival in glioblastoma patients vaccinated with dendritic cell immunotherapy. Clin Cancer Res 17:16031615, 2011

    • Search Google Scholar
    • Export Citation
  • 26

    Raza SM, , Lang FF, , Aggarwal BB, , Fuller GN, , Wildrick DM, & Sawaya R: Necrosis and glioblastoma: a friend or a foe? A review and a hypothesis. Neurosurgery 51:213, 2002

    • Search Google Scholar
    • Export Citation
  • 27

    Reichardt W, , Jung V, , Brunner C, , Klein A, , Wemmert S, & Romeike BF, : The putative serine/threonine kinase gene STK15 on chromosome 20q13.2 is amplified in human gliomas. Oncol Rep 10:12751279, 2003

    • Search Google Scholar
    • Export Citation
  • 28

    Salhia B, , Tran NL, , Symons M, , Winkles JA, , Rutka JT, & Berens ME: Molecular pathways triggering glioma cell invasion. Expert Rev Mol Diagn 6:613626, 2006

    • Search Google Scholar
    • Export Citation
  • 29

    Segal E, , Sirlin CB, , Ooi C, , Adler AS, , Gollub J, & Chen X, : Decoding global gene expression programs in liver cancer by noninvasive imaging. Nat Biotechnol 25:675680, 2007

    • Search Google Scholar
    • Export Citation
  • 30

    Shen H, , Decollogne S, , Dilda PJ, , Hau E, , Chung SA, & Luk PP, : Dual-targeting of aberrant glucose metabolism in glioblastoma. J Exp Clin Cancer Res 34:14, 2015

    • Search Google Scholar
    • Export Citation
  • 31

    Shatseva T, , Lee DY, , Deng Z, & Yang BB: MicroRNA miR-199a-3p regulates cell proliferation and survival by targeting caveolin-2. J Cell Sci 124:28262836, 2011

    • Search Google Scholar
    • Export Citation
  • 32

    Srinivasan S, , Patric IR, & Somasundaram K: A ten-microRNA expression signature predicts survival in glioblastoma. PLoS One 6:e17438, 2011

  • 33

    Stupp R, , Mason WP, , van den Bent MJ, , Weller M, , Fisher B, & Taphoorn MJ, : Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. N Engl J Med 352:987996, 2005

    • Search Google Scholar
    • Export Citation
  • 34

    Sun Y, , Shen S, , Liu X, , Tang H, , Wang Z, & Yu Z, : MiR-429 inhibits cells growth and invasion and regulates EMT-related marker genes by targeting Onecut2 in colorectal carcinoma. Mol Cell Biochem 390:1930, 2014

    • Search Google Scholar
    • Export Citation
  • 35

    Teplyuk NM, , Mollenhauer B, , Gabriely G, , Giese A, , Kim E, & Smolsky M, : MicroRNAs in cerebrospinal fluid identify glioblastoma and metastatic brain cancers and reflect disease activity. Neuro Oncol 14:689700, 2012

    • Search Google Scholar
    • Export Citation
  • 36

    Xia H, , Qi Y, , Ng SS, , Chen X, , Li D, & Chen S, : microRNA-146b inhibits glioma cell migration and invasion by targeting MMPs. Brain Res 1269:158165, 2009

    • Search Google Scholar
    • Export Citation
  • 37

    Zarkoob H, , Taube JH, , Singh SK, , Mani SA, & Kohandel M: Investigating the link between molecular subtypes of glioblastoma, epithelial-mesenchymal transition, and CD133 cell surface protein. PLoS One 8:e64169, 2013

    • Search Google Scholar
    • Export Citation
  • 38

    Zinn PO, , Mahajan B, , Sathyan P, , Singh SK, , Majumder S, & Jolesz FA, : Radiogenomic mapping of edema/cellular invasion MRI-phenotypes in glioblastoma multiforme. PLoS One 6:e25451, 2011. (Erratum in PLoS One 7:10.1371/annotation/b5267cb3-6aa7-47fc-a648-47f30a7cff3e, 2012)

    • Search Google Scholar
    • Export Citation

Metrics

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 827 354 3
PDF Downloads 345 142 1
EPUB Downloads 0 0 0