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This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Uterine Corpus Endometrial Carcinoma (CPTAC-UCEC) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC |
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patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. |
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Imaging from each cancer type will be contained in its own TCIA Collection, with the collection name "CPTAC-cancertype".
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Radiology imaging is collected from standard of care imaging performed on patients immediately before the pathological diagnosis, and from follow-up scans where available. For this reason the radiology image data sets are heterogeneous in terms of scanner modalities, manufacturers and acquisition protocols. Pathology imaging is collected as part of the CPTAC qualification workflow
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All CPTAC cohorts are released as either a single combined cohort, or split into Discovery and Confirmatory where applicable. There are two main types of proteomic studies: discovery proteomics and targeted proteomics. The term "discovery proteomics" is in reference to "untargeted" identification and quantification of a maximal number of proteins in a biological or clinical sample. The term “targeted proteomics” refers to quantitative measurements on a defined subset of total proteins in a biological or clinical sample, often following the completion of discovery proteomics studies to confirm interesting targets selected. Commonly used proteomic technologies and platforms are different types of mass spectrometry and protein microarrays depending on the needs, throughput and sample input requirement of an analysis, with further development on nanotechnologies and automation in the pipeline in order to improve the detection of low abundance proteins, increase throughput, and selectively reach a target protein in vivo. Once the protein targets of interest are identified, high-throughput targeted assays are developed for confirmatory studies: tests to affirm that the initial tests were accurate. A summary of CPTAC imaging efforts can be found on the CPTAC Imaging Proteomics page.
CPTAC Imaging Special Interest Group
You can join the CPTAC Imaging Special Interest Group to be notified of webinars & data releases, collaborate on common data wrangling tasks and seek out partners to explore research hypotheses! Artifacts from previous webinars such as slide decks and video recordings can be found on the CPTAC SIG Webinars page.
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<iframe src="https://player.vimeo.com/video/385284266" width="640" height="400" frameborder="0" allow="autoplay; fullscreen" allowfullscreen></iframe> |
On January 14, 2020 Emily Kawaler presented the consortium's proteogenomic analyses of the CPTAC-UCEC. This deep dive into the UCEC genomic and proteomic datasets will help researchers better understand how they can be correlated with features derived from the imaging data. (Download the slides)
Acknowledgements
We would like to acknowledge the individuals and institutions that have provided data for this collection:
- Beaumont Health System, Royal Oak, MI - Special thanks to George D. Wilson, PhD from the Department of Radiation Oncology Research, Barbara Pruetz of the Biobank, Debra Kapczynski, MHSA, CIIP, RT(R)(CT) and Rachel Deyer from the Department of Diagnostic Radiology.
- Boston Medical Center, Boston, MA - Special thanks to Chris D. Andry M.Phil, PhD from the Department of Pathology and Laboratory Medicine, Margaret Lavoye
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- , Artem Kaliaev, Wilson Chavez, Stephan Anderson, Jorge Soto, and Mitchell Horn from the Department of Radiology, Elizabeth Duffy, MA and Cheryl Spencer, MA of the Biobank.
- International Institute for Molecular Oncology, Poznań, Poland - Special thanks to Maciej Wiznerowicz MD, PhD and Jan Lubiński MD PhD, Rafal Matkowski, MD, PhD, Marcin Jędryka MD, PhD, and Andrzej Czekański MD PhD, from Lower Silesia Cancer Center in Wrocław, Poland.
- St. Joseph's Hospital and Medical Center, Phoenix, AZ - Special thanks to Jennifer Eschbacher, MD from the Department of Neuropathology, Catherine Seiler, PhD, Rosy Singh and Beth Hermes from the Biobank Core Facility, and Victor Sisneros, RT(R)(CT), CPSA.
- BioPartners, CA - Special thanks to Alexander Gasparian, PhD. from the Department of Drug Discovery and Biomedical Sciences, University of South Carolina College of Pharmacy, Kakhaber Zaalishvili, MD Medical Advisor and Staff Pathologist at BioPartners, LLC, Milla Gorodnia, President of BioPartners, Inc., Victoria Christensen, Global Business Development/Project Coordination Manager, Oksana Havryliuk, MD. Chief of Research department of radiodiagnostics of NCI (Ukraine), Marianna Gredil’, Director of BioPartners, LLC, and Anna Legenka Chief of the Data Department at BioPartners, LLC
- University of Pittsburgh/UPMC, Pittsburgh, PA - Special thanks to Scott Beasley (MD, FACR) and Rose Jarosz in the Department of Radiology; Rajiv Dhir (MBBS, MBA) and Tony Green (HT (ASCP), AS) in the Department of Pathology (PBC).
- University of Kansas Medical Center – Special thanks to Andrew K. Godwin, PhD and Rashna Madan, MBBS from the Department of Pathology and Laboratory Medicine and Monica Mays, Lauren DiMartino, and Alex Webster from the University of Kansas Cancer Center.
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Choosing the Download option will provide you with a file to launch the TCIA Download Manager to download the entire collection. If you want to browse or filter the data to select only specific scans/studies please use the Search By Collection option.
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These collections are freely available to browse, download, and use for commercial, scientific and educational purposes as outlined in the Creative Commons Attribution 3.0 Unported License. Questions may be directed to help@cancerimagingarchive.net. Please be sure to acknowledge both this data set and TCIA in publications by including the following citations in your work:
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