1. Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer
- Author
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Matthew E. Monroe, Saravana M. Dhanasekaran, Brian R. Rood, Zeynep H. Gümüş, Jena Lilly, Samuel G. Winebrake, Richard G. Ivey, William Bocik, Mahdi Sarmady, Alicia Francis, Lamiya Tauhid, Nathan Edwards, Lizabeth Katsnelson, Rui Zhao, Matilda Broberg, Jo Lynne Rokita, Mateusz Koptyra, Henry Rodriguez, Cassie Kline, Shrabanti Chowdhury, Nicole Tignor, Ying Wang, Christopher R. Kinsinger, Antonio Colaprico, Amanda G. Paulovich, Weiping Ma, Emily S. Boja, Tara Hiltke, Sabine Mueller, Liang-Bo Wang, Javad Nazarian, Marcin J. Domagalski, Karl K. Weitz, Jessica B. Foster, Robert Lober, Carina A. Leonard, Bo Zhang, Gerald A. Grant, Anna Calinawan, Gonzalo Lopez, Shuang Cai, Joanna J. Phillips, Guo Ci Teo, July E. Palma, Felipe da Veiga Leprevost, Yiran Guo, Angela Waanders, Xiaoyu Song, Li Ding, Allison Heath, Steven P. Gygi, Rosalie K. Chu, Vasileios Stathias, Bailey Farrow, Oren J. Becher, Dmitry Rykunov, Nithin D. Adappa, Ron Firestein, Adam C. Resnick, Marcin Cieślik, Jennifer Mason, D. R. Mani, Selim Kalayci, Boris Reva, Antonio Iavarone, MacIntosh Cornwell, Uliana J. Voytovich, Gabrielle S. Stone, Miguel A. Brown, Jacob J. Kennedy, Tao Liu, Ronald J. Moore, Emily Kawaler, Eric H. Raabe, Marina A. Gritsenko, Valerie Baubet, Francesca Petralia, Maciej Wiznerowicz, Olena Morozova Vaske, Eric E. Schadt, Ian F. Pollack, Arul M. Chinnaiyan, Meghan Connors, Jason E. Cain, Lei Zhao, Matthew A. Wyczalkowski, Nalin Gupta, Bing Zhang, Jiayi Ji, Marilyn M. Li, Samuel Rivero-Hinojosa, Mariarita Santi, Wenke Liu, John Szpyt, Brian Ennis, Alexey I. Nesvizhskii, Joshua M. Wang, Jeffrey P. Greenfield, Sanjukta Guha Thakurta, Hui Yin Chang, Peter B. McGarvey, Xi Chen, Karen A. Ketchum, Stephan C. Schürer, Sarah Leary, Lili Blumenberg, Matthew J. Ellis, Pei Wang, Anna Maria Buccoliero, Karsten Krug, Chiara Caporalini, Gad Getz, David E. Kram, Pichai Raman, Eric M. Jackson, James N. Palmer, Mehdi Mesri, Kelly V. Ruggles, Chunde Li, Jun Zhu, Sonia Partap, Jeffrey R. Whiteaker, Mirko Scagnet, Krutika S. Gaonkar, Azra Krek, Allison M. Morgan, Tatiana Omelchenko, Richard D. Smith, Elizabeth Appert, Karin D. Rodland, Derek Hanson, Phillip B. Storm, Jamie Moon, Vladislav A. Petyuk, Nathan Young, Travis D. Lorentzen, David Fenyö, Angela N. Viaene, Seungyeul Yoo, Yuankun Zhu, Nicholas A Vitanza, Toan Le, Tatiana Patton, and Ana I. Robles
- Subjects
DNA Copy Number Variations ,Computational biology ,Biology ,Proteomics ,Article ,General Biochemistry, Genetics and Molecular Biology ,Ganglioglioma ,03 medical and health sciences ,Lymphocytes, Tumor-Infiltrating ,0302 clinical medicine ,Glioma ,medicine ,Humans ,Gene Regulatory Networks ,RNA, Messenger ,Copy-number variation ,Phosphorylation ,Child ,Proteogenomics ,030304 developmental biology ,Medulloblastoma ,0303 health sciences ,Brain Neoplasms ,Genome, Human ,Phosphoproteomics ,Phosphoproteins ,medicine.disease ,Gene Expression Regulation, Neoplastic ,Mutation ,Atypical teratoid rhabdoid tumor ,Neoplasm Grading ,Neoplasm Recurrence, Local ,Transcriptome ,030217 neurology & neurosurgery - Abstract
We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.
- Published
- 2020