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Summary

Excerpt
 As part of the Cancer Imaging Program (CIP) mission to link archived images from the Cancer Imaging Archive (TCIA) with phenotype research performed under the auspices of the Cancer

The Cancer Genome Atlas (TCGA)

, glioma tissue data and images have been correlated.

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Glioma Phenotype Research Group is part of

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According to the TCGA page on GBM, researchers have already made the following types of discoveries with this data:

  • Identified a new subtype of GBM that affects younger adults and has an increased survival rate. A subset of GBM tumors had large groups of genes with specific chemical changes or 'marks' called methylation. The methylation of these genes may account for improved survival in these patients when compared to patients with other subtypes of GBM. These findings could aid in development of new treatment options.
  • Recognized four distinct molecular subtypes of GBM that respond differently to aggressive therapies. Patients with one subtype survive about 50 percent longer than those with other GBM subtypes. Knowing a tumor's subtype could help match each patient to the most effective therapy. See more information about TCGA brain tumor subtype studies.
  • Identified possible mechanisms that can cause some GBM tumors to become resistant to therapy after treatment with the standard chemotherapy, temozolomide, which can cause gene mutations leading to tumor resistance. If GBM tumors return after successful treatment with temozolomide, the new gene mutations make the tumor resistant to further drug treatment. This finding could be used to develop new drugs that will not activate this drug resistance mechanism.
  • Pinpointed four gene mutations in GBM tumors that may provide new insights into the biology of this disease.
    • NF1, a gene identified as the cause of neurofibromatosis 1, a rare, inherited disorder characterized by uncontrolled tissue growth along nerves.
    • ERBB2, a gene involved in breast cancer.
    • TP53, a gene involved in many types of cancers.
    • PIK3R1, a gene that controls an enzyme found in many cancers.

Per the TCGA page on LGG, researchers also hope to make the following types of discoveries:

  • Define gene expression patterns of adult LGGs compared with pediatric cases that have been studied in other programs.
  • Determine if there are genomic changes that correlate with malignancy.
  • Examine genetic changes that emerge when LGG becomes GBM.
  • Identify clinical features that are associated with a specific pattern of genomic changes.

Research and Publications

Per TCGA and TCIA Guidelines the following limitations from the freedom-to-publish criteria are in effect for the glioma data sets:

Tumor Type

TCGA-GBM

No restrictions; all data available without limitations

No restrictions; image data available without limitations.

TCGA-LGG

No restrictions; all data available without limitations

Publication limitations in place until 6/30/2015; Please check with help@cancerimagingarchive.net prior to any publication.

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TCGA-GBM/LGG Marker Paper and Image Source Sites (ISS)

the Cancer Imaging Project TCGA Radiology Initiative; an effort to build a research community focused on connecting cancer phenotypes to genotypes by providing clinical images matched to tissue specimens analyzed for The Cancer Genome Atlas (TCGA).

Imaging Source Site (ISS) groups Groups are populated being formed and governed by participants from institutions providing that have provided imaging data to the archive for a given cancer type. Modeled after TCGA analysis groups, these ISS groups have are given the opportunity to publish a marker paper for a given cancer type per the aforementioned publication policy. The TCGA Glioma Phenotype Research Group's formation pre-dated current TCIA policies on TCGA related publications; thus,there is no ISS marker paper for TCGA-GBM imaging data. However, several publications and numerous conference presentations utilizing this data have been generated by the research groups outlined below in the references section. Analysis of TCGA-LGG imaging data is underway. Current TCGA-GBM and TCGA-LGG source sites include:

  • ThomasJeffersonUniversity
  • HenryFordHospital
  • UniversityofCalifornia,San Francisco
  • MDAndersonCancerCenter
  • EmoryUniversity
  • Mayo Clinic
  • CWRUSchoolof Medicine

Please contact help@cancerimagingarchive.net if type per the guidelines in the table above. This opportunity will generate increased participation in building these multi-institutional data sets as they become an open community resource. Current TCGA-GBM (glioblastoma) and TCGA-LGG (low grade glioma) source sites include:

  • Thomas Jefferson University
  • Henry Ford Hospital
  • University of California, San Francisco
  • MD Anderson Cancer Center
  • Emory University
  • Mayo Clinic
  • Case Western Reserve University School of Medicine

A number of other collaborators have also been invited to join the group by its members.  Please contact Adam Flanders (adam.flanders@jefferson.edu) if you have scientific questions for TCGA-GBM/LGG ISS or if you are interested in collaborating with their group.

References

The following links contain publications from the main TCGA project, as well as their posted publication guidelines.

Publications utilizing TCGA-GBM imaging data from TCIA:

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Citation

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TCIA Shared Lists (Help Using Shared Lists)

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Supporting Materials

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Publications

TCGA Glioma Phenotype Research Group Publications

  1. Colen RR, Wang J, Singh SK, Gutman DA, Zinn PO. Glioblastoma: Imaging Genomic Mapping Reveals Sex-specific Oncogenic Associations of Cell Death. Radiology. 2014.

  2. Colen RR, Vangel M, Wang J, Gutman DA, Hwang SN, Wintermark M, Rajan J, Jilwan-Nicola M, Chen JY, Raghavan P, Holder CA, Rubin D, Huang E, Kirby J, Freymann J, Jaffee CC, Flanders A, Zinn PO. Imaging genomic mapping of an invasive MRI phenotype predicts patient outcome and metabolic dysfunction: a TCGA glioma phenotype research group project.BMC Medical Genomics, 2014. 7(1):30. doi:10.1186/1755-8794-7-30 (link)
  3. Gevaert O, Mitchell LA, Achrol AS, Xu J, Echegaray S, Steinberg GK, Chesier SH, Napel S, Zaharchuk G, Plevritis SK. Glioblastoma Multiforme: Exploratory Radiogenomic Analysis by Using Quantitative Image Features. Radiology, 2014. doi: 10.1148/radiol.14131731 (link)
  4. Jain R, Poisson L, Gutman D, Scarpace L, Hwang SN, Holder C, Wintermark M, Colen RR, Kirby J, Freymann J, Jaffe C, Mikkelsen T, Flanders A. Outcome Prediction in Patients with Glioblastoma by Using Imaging, Clinical, and Genomic Biomarkers: Focus on the Nonenhancing Component of the Tumor. Radiology. 2014 Aug;272(2):484-93. doi: 10.1148/radiol.14131691. Epub 2014 Mar 19. 2014 (link)
  5. Nicolasjilwan M, Hu Y, Yan C, Meerzaman D, Holder CA, Gutman D, et al. Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients. Journal of Neuroradiology, July 2014. doi: 10.1016/j.neurad.2014.02.006
  6. Wassal E, Zinn P, Colen R. DIFFUSION AND CONVENTIONAL MR IMAGING GENOMIC BIOMARKER SIGNATURE FOR EGFR MUTATION IDENTIFICATION IN GLIOBLASTOMA. Neuro-Oncology. 2014;16(suppl 5):v156-v7.
  7. Wassal E, Zinn P, Colen R. DIFFUSION AND CONVENTIONAL MR IMAGING GENOMIC BIOMARKER SIGNATURE PREDICTS IDH-1 MUTATION IN GLIOBLASTOMA PATIENTS. Neuro-Oncology. 2014;16(suppl 5):v157-v.

  8. Amer A, Zinn P, Colen R. IMMEDIATE POST OPERATIVE VOLUME OF ABNORMAL FLAIR SIGNAL PREDICTS PATIENT SURVIVAL IN GLIOBLASTOMA PATIENTS. Neuro-Oncology. 2014;16(suppl 5):v138-v.

  9. Amer A, Zinn P, Colen R. IMMEDIATE POST-RESECTION PERICAVITARIAN DWI HYPERINTENSITY IN GLIOBLASTOMA PATIENTS IS PREDICTIVE OF PATIENT OUTCOME. Neuro-Oncology. 2014;16(suppl 5):v138-v9.
  10. Gutman DA, Cooper LAD, Hwang SN, Holder CA, Gao J, Aurora TD, Dunn WD

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  1. , Scarpace L, Mikkelsen T, Jain R, Wintermark M, Jilwan M, Raghavan P, Huang E, Clifford RJ,

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  1. Monqkolwat P, Kleper V, Freymann J, Kirby J, Zinn PO, Moreno

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  1. CS, Jaffe C, Colen R, Rubin DL, Saltz J, Flanders A, Brat DJ.

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  1.  MR Imaging Predictors of Molecular Profile and Survival: Multi-institutional Study of the TCGA Glioblastoma Data Set. Radiology. 2013 May:267(2):560-

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  1. 569,doi:10.1148/radiol.13120118

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  1. (link)

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  1. Jain R, Poisson L, Narang J, Gutman D, Scarpace L, Hwang SN, Holder C, Wintermark M, Colen RR, Kirby J, Freymann J, Brat DJ, Jaffe C, Mikkelsen T.

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  1.  Genomic Mapping and Survival Prediction in Glioblastoma: Molecular Subclassification Strengthened by Hemodynamic Imaging Biomarkers. Radiology, 2013 Apr:267(1):212

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  1. –220, doi:10.1148/radiol.12120846

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  1. (link)

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  • TCGA-GBM DSC T2* MR Perfusion  (contains the raw perfusion image studies)
  • TCGA-GBM DSC T2* nordicICE (contains the post-processed nordiceICE perfusion image studies)

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  • A spreadsheet contains scaling factors, rCBV values, and scanner info as well as text files which contain text dumps of Digital Imaging and Communications in Medicine (DICOM) elements for nordicICE perfusion image studies are available at: DSC T2* MR Perfusion Analysis.
  1. Zinn PO, Colen RR. Imaging Genomic Mapping in Glioblastoma. Neurosurgery 60:126-130. Aug 2013 (link)
  2. Jain R, Poisson L, Narang J, Scarpace L, Rosenblum ML, Rempel S, Mikkelson T. Correlation of Perfusion Parameters with Genes Related to Angiogenesis Regulation in Glioblastoma: A Feasibility Study. American Journal of Neuroradiology, 2012. 33(7):1343-1348 [Epub ahead of print] (link)
  3. Zinn PO, Sathyan P, Mahajan B, Bruyere J, Hegi M, et al. (2012)

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  1.  A Novel Volume-Age-KPS (VAK) Glioblastoma Classification Identifies a Prognostic Cognate microRNA-Gene Signature. PLoS ONE, 2012 7(8): e41522. doi:10.1371/journal.pone.0041522 (link)

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  1. Zinn PO, Majadan B, Sathyan P, Singh SK, Majumder S, et al. 2011

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  1. Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes in Glioblastoma Multiforme. PLoS ONE, 2011 6(10): e25451. doi:10.1371/journal.pone.0025451 (link)

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  1. Zinn, P. O., M. Hatami, et al. (2015). "138 Diffusion MRI ADC Mapping of Glioblastoma Edema/

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Note: For more information on how shared lists are used to cite and share data please view our TCIA Citation Guidelines.

Conference abstracts utilizing TCGA-GBM imaging data from TCIA:

  1. Tumor Invasion and Associated Gene Signatures." Neurosurgery 62: 210.

Publications written by other members of the research community can be found on our TCIA Publications page.  Please contact us at help@cancerimagingarchive.net if you have a publication you would like us to add.

TCGA Genomics Publications

Read the 2008 Nature paper and 2013 Cell paper to learn more about the GBM genomic study.  Read the New England Journal of Medicine LGG paper to learn more about the LGG genomic study.  Additional TCGA publications can be found at: http://cancergenome.nih.gov/publications.

Publication Policies

Per TCGA and TCIA Guidelines, formal permission requests are no longer required to submit publications using TCGA-GBM or TCGA-LGG data.  Please see the following links for more information about the freedom-to-publish criteria for these data sets:

Data Source

Status

TCGA Data Portal Publication Guidelines

No restrictions; all data available without limitations.

TCIA Data Usage Policies and Restrictions

No restrictions; all data available without limitations.

Please contact us at help@cancerimagingarchive.net if you have any questions about these policies.