TY - JOUR
T1 - The Immune Landscape of Cancer
AU - The Cancer Genome Atlas Research Network
AU - Thorsson, Vésteinn
AU - Gibbs, David L.
AU - Brown, Scott D.
AU - Wolf, Denise
AU - Bortone, Dante S.
AU - Ou Yang, Tai Hsien
AU - Porta-Pardo, Eduard
AU - Gao, Galen F.
AU - Liu, Yuexin
AU - Uppore Kukkillaya, Arvind Rao
AU - Chen, Ken
AU - Weinstein, John N.
AU - Zhang, Wei
AU - Akbani, Rehan
AU - Broom, Bradley M.
AU - Ju, Zhenlin
AU - Kanchi, Rupa Sridevi
AU - Korkut, Anil
AU - Li, Jun
AU - Liang, Han
AU - Ling, Shiyun
AU - Liu, Wenbin
AU - Lu, Yiling
AU - Mills, Gordon B
AU - Zhang, Jiexin
AU - Liu, Xiuping
AU - Wang, Linghua
AU - Fregnani, José Humberto T. G.
AU - Reis, Rui M. V.
AU - Ajani, Jaffer A.
AU - Behrens, Carmen
AU - Bondaruk, Jolanta
AU - Broaddus, Russell
AU - Czerniak, Bogdan
AU - Esmaeli, Bita
AU - Fujimoto, Junya
AU - Gershenwald, Jeffrey
AU - Guo, Charles
AU - Lazar, Alexander J.
AU - Logothetis, Christopher
AU - Meric-Bernstam, Funda
AU - Moran, Cesar
AU - Ramondetta, Lois
AU - Rice, David
AU - Sood, Anil
AU - Tamboli, Pheroze
AU - Thompson, Timothy
AU - Troncoso, Patricia
AU - Tsao, Anne
AU - Wistuba, Ignacio
N1 - Publisher Copyright:
© 2018 The Authors
PY - 2018/4/17
Y1 - 2018/4/17
N2 - We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes—wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant—characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field. Thorsson et al. present immunogenomics analyses of more than 10,000 tumors, identifying six immune subtypes that encompass multiple cancer types and are hypothesized to define immune response patterns impacting prognosis. This work provides a resource for understanding tumor-immune interactions, with implications for identifying ways to advance research on immunotherapy.
AB - We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes—wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant—characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field. Thorsson et al. present immunogenomics analyses of more than 10,000 tumors, identifying six immune subtypes that encompass multiple cancer types and are hypothesized to define immune response patterns impacting prognosis. This work provides a resource for understanding tumor-immune interactions, with implications for identifying ways to advance research on immunotherapy.
KW - cancer genomics
KW - immune subtypes
KW - immuno-oncology
KW - immunomodulatory
KW - immunotherapy
KW - integrative network analysis
KW - tumor immunology
KW - tumor microenvironment
UR - http://www.scopus.com/inward/record.url?scp=85044934017&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044934017&partnerID=8YFLogxK
U2 - 10.1016/j.immuni.2018.03.023
DO - 10.1016/j.immuni.2018.03.023
M3 - Article
C2 - 29628290
AN - SCOPUS:85044934017
SN - 1074-7613
VL - 48
SP - 812-830.e14
JO - Immunity
JF - Immunity
IS - 4
ER -