The Genomic Data Commons (GDC) data release 22 is now available and includes data from the CPTAC Glioblastoma Multiforme Discovery Study.
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The Genomic Data Commons (GDC) data release 22 is now available and includes data from the CPTAC Glioblastoma Multiforme Discovery Study.
The Clinical Proteomic Tumor Analysis Consortium (CPTAC), sponsored by the National Cancer Institute’s (NCI) Office of Cancer Clinical Proteomics Research (OCCPR) and managed by The Frederick National Laboratory for Cancer Research (FNLCR), is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteomics, genomics and proteogenomics.
Glioblastoma Multiforme Discovery Study proteomic and phosphoproteomic data previously available only on thte CPTAC Data Portal is now available on the Proteomic Data Commons.
TCIA has released its quarterly update for CPTAC radiology data with 44 new radiology cases! These cases span cutaneous melanoma, glioblastoma multiforme, head & neck squamous cell carcinoma, lung squamous cell carcinoma, lung adenocarcinoma, pancreatic ductal adenocarcinoma and sarcoma tumor tissue types. In addition, the TCIA monthly histopathology report lists the addition of 10 new pathology slides
Antibodies are among the most commonly used tools in the biological sciences - put to work in many experiments to identify and isolate other molecules. NCI’s Antibody Program has developed more than 500 available antibodies that have been designed and optimized, with the vast majority developed as fit-for-purpose reagents.
Proteomic and phosphoproteomic data for the CPTAC Glioblastoma Discovery Study is now available on the CPTAC Data Portal.
And there's more!!! Another new batch of CPTAC histopathology imaging data has been released and is now publicly available on the TCIA CPTAC Pathology Portal.
As part of NIH’s mission for collaboration and team science, Dr. Matthew Ellis, Co-Principal Investigator of the CPTAC Proteogenomic Translational Research Center and Dr.
Did you know about NCI’s Proteomic (CPTAC) Assay Portal? It’s a free resource for biological scientists performing mass spectroscopy. The portal houses more than 2300 fit-for-purpose, proteomic assays designed and optimized for anyone to use. Each assay is validated using CPTAC experimental g
A new batch of CPTAC histopathology imaging data has been released and is now publicly available on the TCIA CPTAC Pathology Portal.
The TCIA quarterly report lists the addition of 76 new pathology slides and 25 new pathology subjects for the cutaneous melanoma, glioblastoma multiforme, and sarcoma tumor types.
TCIA has partnered with CPTAC to host both the radiology and pathology imaging data generated by the CPTAC Program. Imaging data is available for 10 cancer types including AML, clear cell renal cell carcinoma, head & neck squamous cell carcinoma, lung squamous cell...
The Proteomic Data Commons (PDC) has released data from the Children's Brain Tumor Tissue Consortium (CBTTC): Pediatric Brain Tumor Atlas dataset!
Data Release-20 from the Genomic Data Commons (GDC) includes genomics from a new CPTAC project!
The CPTAC Proteogenomic Confirmatory Study examined prospectively collected colon, breast and ovarian tumors for analysis, including harmonized whole exome sequencing, RNA-Seq, and miRNA-Seq that is now available. Complimentary proteomic and phosphoproteomic analysis can also be found on the CPTAC Data Portal and the Proteomic Data Commons (PDC).
CPTAC has provided the Genomic Data Commons (GDC) with genomic data from over 600 cancer patients with diverse disease types including...
Investigators with the Clinical Proteomic Tumor Analysis Consortium (CPTAC) have generated the most comprehensive multi-omics dataset for clear cell renal cell carcinoma (ccRCC), the most commonly diagnosed kidney cancer subtype. The investigators used integrative proteogenomics, to reveal new insights into kidney cancer.
Over three hundred proteomic explorers and Clinical Proteomics Tumor Analysis Consortium (CPTAC) participants from around the country convened on the NIH Bethesda campus to share cutting-edge proteogenomic research in the first ever, public-facing CPTAC Scientific Symposium.
Large multi-omics datasets are becoming increasingly popular for studying biological systems including the identification of biological pathways, or more broadly defined gene sets, that are associated with certain biological or clinical features of interest.
Hepatocellular carcinoma (HCC), the most common form of liver cancer, occurs most often in people with hepatitis B or C viral (HBV or HCV) infections who drink large amounts of alcohol. Unlike the recent progress of antiviral-eliminating therapy for HCV, current antiviral therapy is only able to reduce rather than eliminate HBV and is estimated to affect 292 million peop
UniProt, the leading online protein reference library, has teamed up with CPTAC! Now, search results for your protein-of-interest will include links to the CPTAC Assay Portal for relevant peptides and assay protocols, while giving CPTAC users all the rich functional annotation in UniProt!
RAS gene mutations and their pathways have stymied cancer researchers for decades. RAS-driven cancers make up more than 30% of all human cancers due to their association with uncontrollable cell growth, death-signal evasion, and drug resistance. In 2014, the National Cancer Institu
Genomics platform cBioPortal offers a “biologist-friendly” resource for querying mutations, copy number variations and gene expression. It contains data from The Cancer Genome Atlas (TCGA) which includes proteomics data in the form of arrays that use antibodies to track protein levels. CPTAC mass spectrometry-based proteomics, however, has more information than the arrays provide.
The Journal of Molecular & Cellular Proteomics has released a special issue this month (August 2019) on Multi-Omics Integration. The issue sets out to show how multi-omics research is integral to the understanding of biological systems. It touts work from several of our CPTAC investigators who share their cutting