Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer

Children's Brain Tumor Network; Clinical Proteomic Tumor Analysis Consortium

doi:10.1016/j.cell.2020.10.044

Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer

Children's Brain Tumor Network
, Clinical Proteomic Tumor Analysis Consortium

School of Medicine

Icahn School of Medicine at Mount Sinai
Children's Hospital of Philadelphia
Fred Hutchinson Cancer Research Center
University of Miami
Memorial Sloan-Kettering Cancer Center
Harvard University
Pacific Northwest National Laboratory
University of Michigan, Ann Arbor
Broad Institute
New York University
Seattle Children's Hospital
University of Washington
George Washington University
University of Zurich

Research output: Contribution to journal › Article › peer-review

267 Scopus citations

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.

Original language	English
Pages (from-to)	1962-1985.e31
Journal	Cell
Volume	183
Issue number	7
DOIs	https://doi.org/10.1016/j.cell.2020.10.044
State	Published - 23 Dec 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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

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10.1016/j.cell.2020.10.044

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@article{1a9fd6df1cf24d86a0b4c34dff29143c,

title = "Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer",

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.",

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",

author = "\{Children's Brain Tumor Network\} and \{Clinical Proteomic Tumor Analysis Consortium\} and Francesca Petralia and Nicole Tignor and Boris Reva and Mateusz Koptyra and Shrabanti Chowdhury and Dmitry Rykunov and Azra Krek and Weiping Ma and Yuankun Zhu and Jiayi Ji and Anna Calinawan and Whiteaker, \{Jeffrey R.\} and Antonio Colaprico and Vasileios Stathias and Tatiana Omelchenko and Xiaoyu Song and Pichai Raman and Yiran Guo and Brown, \{Miguel A.\} and Ivey, \{Richard G.\} and John Szpyt and \{Guha Thakurta\}, Sanjukta and Gritsenko, \{Marina A.\} and Weitz, \{Karl K.\} and Gonzalo Lopez and Selim Kalayci and G{\"u}m{\"u}{\c s}, \{Zeynep H.\} and Seungyeul Yoo and \{da Veiga Leprevost\}, Felipe and Chang, \{Hui Yin\} and Karsten Krug and Lizabeth Katsnelson and Ying Wang and Kennedy, \{Jacob J.\} and Voytovich, \{Uliana J.\} and Lei Zhao and Gaonkar, \{Krutika S.\} and Ennis, \{Brian M.\} and Bo Zhang and Valerie Baubet and Lamiya Tauhid and Lilly, \{Jena V.\} and Mason, \{Jennifer L.\} and Bailey Farrow and Nathan Young and Sarah Leary and Jamie Moon and Petyuk, \{Vladislav A.\} and Javad Nazarian and Derek Hanson",

note = "Publisher Copyright: {\textcopyright} 2020 Elsevier Inc.",

year = "2020",

month = dec,

day = "23",

doi = "10.1016/j.cell.2020.10.044",

language = "English",

volume = "183",

pages = "1962--1985.e31",

journal = "Cell",

issn = "0092-8674",

publisher = "Elsevier B.V.",

number = "7",

}

TY - JOUR

T1 - Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer

AU - Children's Brain Tumor Network

AU - Clinical Proteomic Tumor Analysis Consortium

AU - Petralia, Francesca

AU - Tignor, Nicole

AU - Reva, Boris

AU - Koptyra, Mateusz

AU - Chowdhury, Shrabanti

AU - Rykunov, Dmitry

AU - Krek, Azra

AU - Ma, Weiping

AU - Zhu, Yuankun

AU - Ji, Jiayi

AU - Calinawan, Anna

AU - Whiteaker, Jeffrey R.

AU - Colaprico, Antonio

AU - Stathias, Vasileios

AU - Omelchenko, Tatiana

AU - Song, Xiaoyu

AU - Raman, Pichai

AU - Guo, Yiran

AU - Brown, Miguel A.

AU - Ivey, Richard G.

AU - Szpyt, John

AU - Guha Thakurta, Sanjukta

AU - Gritsenko, Marina A.

AU - Weitz, Karl K.

AU - Lopez, Gonzalo

AU - Kalayci, Selim

AU - Gümüş, Zeynep H.

AU - Yoo, Seungyeul

AU - da Veiga Leprevost, Felipe

AU - Chang, Hui Yin

AU - Krug, Karsten

AU - Katsnelson, Lizabeth

AU - Wang, Ying

AU - Kennedy, Jacob J.

AU - Voytovich, Uliana J.

AU - Zhao, Lei

AU - Gaonkar, Krutika S.

AU - Ennis, Brian M.

AU - Zhang, Bo

AU - Baubet, Valerie

AU - Tauhid, Lamiya

AU - Lilly, Jena V.

AU - Mason, Jennifer L.

AU - Farrow, Bailey

AU - Young, Nathan

AU - Leary, Sarah

AU - Moon, Jamie

AU - Petyuk, Vladislav A.

AU - Nazarian, Javad

AU - Hanson, Derek

PY - 2020/12/23

Y1 - 2020/12/23

N2 - 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.

AB - 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.

KW - BRAF alteration

KW - CPTAC

KW - CTNNB1 mutation

KW - kinase activity score

KW - kinase substrate regulation

KW - pediatric brain tumor

KW - post-translational modification

KW - proteomic cluster

KW - recurrent versus primary tumors

KW - tumor microenvironment

UR - https://www.scopus.com/pages/publications/85097475909

U2 - 10.1016/j.cell.2020.10.044

DO - 10.1016/j.cell.2020.10.044

M3 - Article

C2 - 33242424

AN - SCOPUS:85097475909

SN - 0092-8674

VL - 183

SP - 1962-1985.e31

JO - Cell

JF - Cell

IS - 7

ER -

Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer

Abstract

UN SDGs

Keywords

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