| Literature DB >> 33242424 |
Francesca Petralia1, Nicole Tignor1, Boris Reva1, Mateusz Koptyra2, Shrabanti Chowdhury1, Dmitry Rykunov1, Azra Krek1, Weiping Ma1, Yuankun Zhu2, Jiayi Ji3, Anna Calinawan1, Jeffrey R Whiteaker4, Antonio Colaprico5, Vasileios Stathias6, Tatiana Omelchenko7, Xiaoyu Song3, Pichai Raman8, Yiran Guo2, Miguel A Brown2, Richard G Ivey4, John Szpyt9, Sanjukta Guha Thakurta9, Marina A Gritsenko10, Karl K Weitz10, Gonzalo Lopez1, Selim Kalayci1, Zeynep H Gümüş1, Seungyeul Yoo1, Felipe da Veiga Leprevost11, Hui-Yin Chang11, Karsten Krug12, Lizabeth Katsnelson13, Ying Wang13, Jacob J Kennedy4, Uliana J Voytovich4, Lei Zhao4, Krutika S Gaonkar8, Brian M Ennis2, Bo Zhang2, Valerie Baubet2, Lamiya Tauhid2, Jena V Lilly2, Jennifer L Mason2, Bailey Farrow2, Nathan Young2, Sarah Leary14, Jamie Moon10, Vladislav A Petyuk10, Javad Nazarian15, Nithin D Adappa16, James N Palmer16, Robert M Lober17, Samuel Rivero-Hinojosa18, Liang-Bo Wang19, Joshua M Wang13, Matilda Broberg13, Rosalie K Chu10, Ronald J Moore10, Matthew E Monroe10, Rui Zhao10, Richard D Smith10, Jun Zhu1, Ana I Robles20, Mehdi Mesri20, Emily Boja20, Tara Hiltke20, Henry Rodriguez20, Bing Zhang21, Eric E Schadt1, D R Mani12, Li Ding22, Antonio Iavarone23, Maciej Wiznerowicz24, Stephan Schürer6, Xi S Chen25, Allison P Heath2, Jo Lynne Rokita8, Alexey I Nesvizhskii26, David Fenyö13, Karin D Rodland27, Tao Liu10, Steven P Gygi9, Amanda G Paulovich4, Adam C Resnick28, Phillip B Storm29, Brian R Rood30, Pei Wang31.
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.Entities:
Keywords: BRAF alteration; CPTAC; CTNNB1 mutation; kinase activity score; kinase substrate regulation; pediatric brain tumor; post-translational modification; proteomic cluster; recurrent versus primary tumors; tumor microenvironment
Year: 2020 PMID： 33242424 DOI： 10.1016/j.cell.2020.10.044
Source DB: PubMed Journal: Cell ISSN： 0092-8674 Impact factor: 41.582