Summary
| 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 Genome Atlas (TCGA), glioma tissue data and images have been correlated. |
The TCGA Glioma Phenotype Research Group is part of the CIP TCGA Radiology Initiative focused on analyzing images from the TCGA-Glioblastoma Multiforme (GBM) and TCGA-Lower Grade Glioma (LGG) collections. Images correlating to the GBM and LGG tissue data in the TCGA Data Portal continue to be gathered for submission to TCIA.
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:
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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. |
Please contact us at help@cancerimagingarchive.net if you have any questions about these policies.
TCGA-GBM/LGG Marker Paper and Image Source Sites (ISS)
Imaging Source Site (ISS) groups are populated and governed by participants from institutions providing imaging data to the archive for a given cancer type. Modeled after TCGA analysis groups, these groups have 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 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:
Citation | TCIA Shared Lists (Help Using Shared Lists) | Supporting Materials |
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MR Imaging Predictors of Molecular Profile and Survival: Multi-institutional Study of the TCGA Glioblastoma Data Set.
Gutman DA, Cooper LA, Hwang SN, Holder CA, Gao J, Aurora TD, Dunn WD Jr, Scarpace L, Mikkelsen T, Jain R, Wintermark M, Jilwan M, Raghavan P, Huang E, Clifford RJ, Mongkolwat P, Kleper V, Freymann J, Kirby J, Zinn PO, Moreno C, Jaffe C, Colen R, Rubin DL, Saltz J, Flanders A, Brat DJ.
Radiology. 2013 May;267(2):560-9. doi: 10.1148/radiol.13120118. Epub 2013 Feb 7. (link) | | |
Genomic Mapping and Survival Prediction in Glioblastoma: Molecular Subclassification Strengthened by Hemodynamic Imaging Biomarkers.
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.
Radiology. 2013 Apr;267(1):212-20. doi: 10.1148/radiol.12120846. Epub 2012 Dec 13. (link) | - 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)
| - 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.
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A Novel Volume-Age-KPS (VAK) Glioblastoma Classification Identifies a Prognostic Cognate microRNA-Gene Signature.
Zinn PO, Sathyan P, Mahajan B, Bruyere J, Hegi M, et al. (2012)
PLoS ONE 7(8): e41522. doi:10.1371/journal.pone.0041522 (link) | | |
Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes in Glioblastoma Multiforme.
Zinn PO, Majadan B, Sathyan P, Singh SK, Majumder S, et al. 2011
PLoS ONE 6(10): e25451. doi:10.1371/journal.pone.0025451 (link) | - Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes
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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:
- ASNR 2013 (May 18 - 23, 2013, San Diego, CA)
- RSNA 2012 (Nov 25-Nov 30, 2012, Chicago, IL)
- ASNR 2012 (April 21-26, 2012, New York, NY)
- RSNA 2011 (Nov 27-Dec 2, 2011, Chicago, IL)
- SNO 2011 (Nov 17-20, 2011, Orange County, CA)
- The Cancer Genome Atlas Network Symposium (Nov 17-18, 2011, Washington, DC)
- Neuroimaging Predictors of Survival, Pathology, and Molecular Profiles in TCGA Glioblastomas. David A Gutman, Lee A.D. Cooper, Joel Saltz, Adam Flanders, Dan Brat and the TCGA Glioma Phenotype Research Group (Slides, Presentation Video)
- ASNR 2011 (June 4-9, 2011, Seattle, WA)