Dataset Information

Decomposing Oncogenic Transcriptional Signatures to Generate Maps of Divergent Cellular States.

ABSTRACT: The systematic sequencing of the cancer genome has led to the identification of numerous genetic alterations in cancer. However, a deeper understanding of the functional consequences of these alterations is necessary to guide appropriate therapeutic strategies. Here, we describe Onco-GPS (OncoGenic Positioning System), a data-driven analysis framework to organize individual tumor samples with shared oncogenic alterations onto a reference map defined by their underlying cellular states. We applied the methodology to the RAS pathway and identified nine distinct components that reflect transcriptional activities downstream of RAS and defined several functional states associated with patterns of transcriptional component activation that associates with genomic hallmarks and response to genetic and pharmacological perturbations. These results show that the Onco-GPS is an effective approach to explore the complex landscape of oncogenic cellular states across cancers, and an analytic framework to summarize knowledge, establish relationships, and generate more effective disease models for research or as part of individualized precision medicine paradigms.

SUBMITTER: Kim JW

PROVIDER: S-EPMC5639711 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Decomposing Oncogenic Transcriptional Signatures to Generate Maps of Divergent Cellular States.

Kim Jong Wook JW Abudayyeh Omar O OO Yeerna Huwate H Yeang Chen-Hsiang CH Stewart Michelle M Jenkins Russell W RW Kitajima Shunsuke S Konieczkowski David J DJ Medetgul-Ernar Kate K Cavazos Taylor T Mah Clarence C Ting Stephanie S Van Allen Eliezer M EM Cohen Ofir O Mcdermott John J Damato Emily E Aguirre Andrew J AJ Liang Jonathan J Liberzon Arthur A Alexe Gabriella G Doench John J Ghandi Mahmoud M Vazquez Francisca F Weir Barbara A BA Tsherniak Aviad A Subramanian Aravind A Meneses-Cime Karina K Park Jason J Clemons Paul P Garraway Levi A LA Thomas David D Boehm Jesse S JS Barbie David A DA Hahn William C WC Mesirov Jill P JP Tamayo Pablo P

Cell systems 20170801 2

The systematic sequencing of the cancer genome has led to the identification of numerous genetic alterations in cancer. However, a deeper understanding of the functional consequences of these alterations is necessary to guide appropriate therapeutic strategies. Here, we describe Onco-GPS (OncoGenic Positioning System), a data-driven analysis framework to organize individual tumor samples with shared oncogenic alterations onto a reference map defined by their underlying cellular states. We applie ...[more]

PMID: 28837809

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Project description:Eosinophils are multifunctional, evolutionary conserved leukocytes that are involved in a plethora of responses ranging from regulation of tissue homeostasis to host defense and cancer. Eosinophils have been studied mostly in the context of Type 2 inflammatory responses such as those found in allergy. Nonetheless, it is now evident that they participate in Type 1 inflammatory responses and can respond to Type 1 cytokines such as IFN-γ. Recent data suggest that the pleotropic roles of eosinophils are due to heterogeneous responses to environmental cues. Despite this, the activation profile of eosinophils, in response to various stimuli is yet to be defined. To better understand the transcriptional spectrum of eosinophil activation, we exposed eosinophils to Type 1 (e.g. IFN-γ, E. coli) vs. Type 2 (e.g. IL-4) conditions and subjected them to global RNA sequencing. Our analyses show that IL-4, IFN-γ, E. coli and IFN-γ in the presence of E. coli (IFN-γ/E. coli)-stimulated eosinophils acquire distinct transcriptional profiles, which polarize them towards what we termed Type 1 and Type 2 eosinophils. Bioinformatics analyses using Gene Ontology based on biological processes revealed that different stimuli induced distinct pathways in eosinophils. These pathways were confirmed using functional assays by assessing cytokine/chemokine release (i.e. CXCL9, CCL24, TNF-α and IL-6) from eosinophils following activation. In addition, analysis of cell surface markers highlighted CD101 and CD274 as potential cell surface markers that distinguish between Type 1 and Type 2 eosinophils, respectively. Finally, the transcriptome signature of Type 1 eosinophils resembled that of eosinophils that were obtained from mice with experimental colitis whereas the transcriptome signature of Type 2 eosinophils resembled that of eosinophils from experimental asthma. Our data demonstrate that eosinophils are polarized to distinct "Type 1" and "Type 2" phenotypes following distinct stimulations. These findings provide fundamental knowledge regarding the heterogeneity of eosinophils and support the presence of transcriptional differences between Type 1 and Type 2 cells that are likely reflected by their pleotropic activities in diverse disease settings.

Dataset Information

Decomposing Oncogenic Transcriptional Signatures to Generate Maps of Divergent Cellular States.

Publications

Decomposing Oncogenic Transcriptional Signatures to Generate Maps of Divergent Cellular States.

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