Details

Autor(en) / Beteiligte

• Dou, Yongchao
• Da Veiga Leprevost, Felipe
• Geffen, Yifat
• Calinawan, Anna P.
• Aguet, François
• Birger, Chet
• Cao, Song
• Chaudhary, Rekha
• Cieslik, Marcin
• Colaprico, Antonio
• Zhou, Daniel Cui
• Day, Corbin
• Domagalski, Marcin J.
• Fenyö, David
• Foltz, Steven M.
• Gonzalez-Robles, Tania
• Gümüş, Zeynep H.
• Heiman, David
• Hong, Runyu
• Hu, Yingwei
• Jaehnig, Eric J.
• Ji, Jiayi
• Jiang, Wen
• Ketchum, Karen A.
• Klein, Robert J.
• Liao, Yuxing
• Lindgren, Caleb M.
• Ma, Weiping
• Ma, Lei
• MacCoss, Michael J.
• Martins Rodrigues, Fernanda
• Nguyen, Ngoc
• Oldroyd, Robert
• Reva, Boris
• Rudnick, Paul
• Savage, Sara R.
• Schnaubelt, Michael
• Schraink, Tobias
• Shi, Zhiao
• Singhal, Deepak
• Storrs, Erik
• Thangudu, Ratna R.
• Thiagarajan, Mathangi
• Wang, Liang-Bo
• Wang, Joshua M.
• Wen, Bo
• Wu, Yige
• Wyczalkowski, Matthew A.
• Xin, Yi
• Yao, Lijun
• Zhang, Hui
• Zhang, Qing
• Getz, Gad
• Ding, Li
• Nesvizhskii, Alexey I.
• Robles, Ana I.
• Payne, Samuel H.
• Lazar, Alexander J.
• Paulovich, Amanda G.
• Iavarone, Antonio
• Chinnaiyan, Arul M.
• Druker, Brian J.
• Kumar-Sinha, Chandan
• Newton, Chelsea J.
• Smith, Richard D.
• Huntsman, Emily
• Schadt, Eric E.
• An, Eunkyung
• Petralia, Francesca
• Cho, Hanbyul
• Rodriguez, Henry
• Kolodziejczak, Iga
• Johnson, Jared L.
• Bavarva, Jasmin
• Tan, Jimin
• Clauser, Karl R.
• Krug, Karsten
• Cantley, Lewis C.
• Wiznerowicz, Maciej
• Anurag, Meenakshi
• Mesri, Mehdi
• Gillette, Michael A.
• Birrer, Michael J.
• Ceccarelli, Michele
• Dhanasekaran, Saravana M.
• Edwards, Nathan
• Tignor, Nicole
• Babur, Özgün
• Pugliese, Pietro
• Jewell, Scott D.
• Satpathy, Shankha
• Chowdhury, Shrabanti
• Schürer, Stephan
• Carr, Steven A.
• Hiltke, Tara
• Yaron, Tomer M.
• Liu, Wenke
• Song, Yizhe
• Zhang, Zhen

Titel

Proteogenomic data and resources for pan-cancer analysis

Ist Teil von

• Cancer cell, 2023-08, Vol.41 (8), p.1397-1406

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2023

Quelle

MEDLINE

Beschreibungen/Notizen

• The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data. Li et al. present a data compendium from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), covering tumor cohorts from 10 cancer types. This pan-cancer resource provides comprehensive molecular characterization of tumors, with genomic and proteomic data to connect genomic aberrations to cancer phenotypes.