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Nature. 2019 Jul;571(7765):355-360. doi: 10.1038/s41586-019-1367-0. Epub 2019 Jul 3.

Somatic mutations and cell identity linked by Genotyping of Transcriptomes.

Author information

1
Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
2
New York Genome Center, New York, NY, USA.
3
Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
4
Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
5
Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
6
Tri-Institutional MD-PhD Program, Weill Cornell Medicine, Rockefeller University, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
7
Richard T. Silver MD Myeloproliferative Neoplasms Center, Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
8
Tri-Institutional Training Program in Computational Biology and Medicine, Memorial Sloan Kettering Cancer Center, Cornell University, Weill Cornell Medicine, New York, NY, USA.
9
Epigenomics Core Facility, Weill Cornell Medicine, New York, NY, USA.
10
Oxford Nanopore Technologies, New York, NY, USA.
11
Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, USA.
12
Division of Hematology and Medical Oncology, Department of Medicine, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
13
Department of Systems Biology, Columbia University Medical Center, New York, NY, USA.
14
Technology Innovation Lab, New York Genome Center, New York, NY, USA.
15
New York Genome Center, New York, NY, USA. dlandau@nygenome.org.
16
Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. dlandau@nygenome.org.
17
Division of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA. dlandau@nygenome.org.
18
Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA. dlandau@nygenome.org.

Abstract

Defining the transcriptomic identity of malignant cells is challenging in the absence of surface markers that distinguish cancer clones from one another, or from admixed non-neoplastic cells. To address this challenge, here we developed Genotyping of Transcriptomes (GoT), a method to integrate genotyping with high-throughput droplet-based single-cell RNA sequencing. We apply GoT to profile 38,290 CD34+ cells from patients with CALR-mutated myeloproliferative neoplasms to study how somatic mutations corrupt the complex process of human haematopoiesis. High-resolution mapping of malignant versus normal haematopoietic progenitors revealed an increasing fitness advantage with myeloid differentiation of cells with mutated CALR. We identified the unfolded protein response as a predominant outcome of CALR mutations, with a considerable dependency on cell identity, as well as upregulation of the NF-κB pathway specifically in uncommitted stem cells. We further extended the GoT toolkit to genotype multiple targets and loci that are distant from transcript ends. Together, these findings reveal that the transcriptional output of somatic mutations in myeloproliferative neoplasms is dependent on the native cell identity.

PMID:
31270458
DOI:
10.1038/s41586-019-1367-0

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