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Molecular Cancer Research
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Cancer Genes and Networks

MYC Activity Inference Captures Diverse Mechanisms of Aberrant MYC Pathway Activation in Human Cancers

Evelien Schaafsma, Yanding Zhao, Lanjing Zhang, Yong Li and Chao Cheng
Evelien Schaafsma
1Department of Molecular and Systems Biology, Dartmouth College, Hanover, New Hampshire.
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Yanding Zhao
2Department of Medicine, Baylor College of Medicine, Houston, Texas.
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Lanjing Zhang
3Department of Biological Sciences, Rutgers University, Newark, New Jersey.
4Department of Pathology, Princeton Medical Center, Plainsboro, New Jersey.
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Yong Li
5Department of Medicine, Section of Epidemiology and Population Sciences, Baylor College of Medicine, Houston, Texas.
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Chao Cheng
2Department of Medicine, Baylor College of Medicine, Houston, Texas.
6Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas.
7Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire.
8The Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, Texas.
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  • ORCID record for Chao Cheng
  • For correspondence: chao.cheng@bcm.edu
DOI: 10.1158/1541-7786.MCR-20-0526 Published March 2021
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Abstract

c-MYC (MYC) is deregulated in more than 50% of all cancers. While MYC amplification is the most common MYC-deregulating event, many other alterations can increase MYC activity. We thus systematically investigated MYC pathway activity across different tumor types. Using a logistic regression framework, we established tumor type–specific, transcriptomic-based MYC activity scores that can accurately capture MYC activity. We show that MYC activity scores reflect a variety of MYC-regulating mechanisms, including MYCL and/or MYCN amplification, MYC promoter methylation, MYC mRNA expression, lncRNA PVT1 expression, MYC mutations, and viral integrations near the MYC locus. Our MYC activity score incorporates all of these mechanisms, resulting in better prognostic predictions compared with MYC amplification status, MYC promoter methylation, and MYC mRNA expression in several cancer types. In addition, we show that tumor proliferation and immune evasion are likely contributors to this reduction in survival. Finally, we developed a MYC activity signature for liquid tumors in which MYC translocation is commonly observed, suggesting that our approach can be applied to different types of genomic alterations. In conclusion, we developed a MYC activity score that captures MYC pathway activity and is clinically relevant.

Implications: By using cancer type–specific MYC activity profiles, we were able to assess MYC activity across many more tumor types than previously investigated. The range of different MYC-related alterations captured by our MYC activity score can be used to facilitate the application of future MYC inhibitors and aid physicians to preselect patients for targeted therapy.

Footnotes

  • Note: Supplementary data for this article are available at Molecular Cancer Research Online (http://mcr.aacrjournals.org/).

  • Mol Cancer Res 2021;19:414–28

  • Received June 10, 2020.
  • Revision received August 21, 2020.
  • Accepted November 20, 2020.
  • Published first November 24, 2020.
  • ©2020 American Association for Cancer Research.
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Molecular Cancer Research: 19 (3)
March 2021
Volume 19, Issue 3
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MYC Activity Inference Captures Diverse Mechanisms of Aberrant MYC Pathway Activation in Human Cancers
Evelien Schaafsma, Yanding Zhao, Lanjing Zhang, Yong Li and Chao Cheng
Mol Cancer Res March 1 2021 (19) (3) 414-428; DOI: 10.1158/1541-7786.MCR-20-0526

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MYC Activity Inference Captures Diverse Mechanisms of Aberrant MYC Pathway Activation in Human Cancers
Evelien Schaafsma, Yanding Zhao, Lanjing Zhang, Yong Li and Chao Cheng
Mol Cancer Res March 1 2021 (19) (3) 414-428; DOI: 10.1158/1541-7786.MCR-20-0526
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Molecular Cancer Research
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