Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets

Abdulkadir Elmas; Serena Tharakan; Suraj Jaladanki; Matthew D. Galsky; Tao Liu; Kuan-lin Huang

doi:10.1038/s42003-021-02636-7

Communications Biology (Sep 2021)

Pan-cancer proteogenomic investigations identify post-transcriptional kinase targets

Abdulkadir Elmas,
Serena Tharakan,
Suraj Jaladanki,
Matthew D. Galsky,
Tao Liu,
Kuan-lin Huang

Affiliations

Abdulkadir Elmas: Center for Transformative Disease Modeling, Department of Genetics and Genomic Sciences, Tisch Cancer Institute, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai
Serena Tharakan: Center for Transformative Disease Modeling, Department of Genetics and Genomic Sciences, Tisch Cancer Institute, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai
Suraj Jaladanki: Center for Transformative Disease Modeling, Department of Genetics and Genomic Sciences, Tisch Cancer Institute, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai
Matthew D. Galsky: Division of Hematology and Medical Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai
Tao Liu: Biological Sciences Division, Pacific Northwest National Laboratory
Kuan-lin Huang: Center for Transformative Disease Modeling, Department of Genetics and Genomic Sciences, Tisch Cancer Institute, Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai

DOI: https://doi.org/10.1038/s42003-021-02636-7
Journal volume & issue: Vol. 4, no. 1
pp. 1 – 13

Abstract

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Elmas et al. develop an algorithm, OPPTI, to identify overexpressed kinase proteins across 10 cancer types using global mass spectrometry proteomics data from over 1000 cases. They reveal that protein-level aberrations, which are sometimes not observed using genomics, represent cancer vulnerabilities that may be targeted in precision oncology.

Published in Communications Biology

ISSN: 2399-3642 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science: Biology (General)
Website: https://www.nature.com/commsbio/

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