A protein network map of head and neck cancer reveals PIK3CA mutant drug sensitivity

Author:

Swaney Danielle L.1234ORCID,Ramms Dana J.456ORCID,Wang Zhiyong46ORCID,Park Jisoo47ORCID,Goto Yusuke46,Soucheray Margaret1234ORCID,Bhola Neil48,Kim Kyumin1234ORCID,Zheng Fan47ORCID,Zeng Yan48,McGregor Michael1234ORCID,Herrington Kari A.9ORCID,O’Keefe Rachel48ORCID,Jin Nan48,VanLandingham Nathan K.48ORCID,Foussard Helene1234ORCID,Von Dollen John1234ORCID,Bouhaddou Mehdi1234ORCID,Jimenez-Morales David1234ORCID,Obernier Kirsten1234ORCID,Kreisberg Jason F.47ORCID,Kim Minkyu1234ORCID,Johnson Daniel E.8ORCID,Jura Natalia3410ORCID,Grandis Jennifer R.48ORCID,Gutkind J. Silvio456ORCID,Ideker Trey471112ORCID,Krogan Nevan J.1234ORCID

Affiliation:

1. Quantitative Biosciences Institute (QBI), University of California San Francisco, San Francisco, CA, USA.

2. J. David Gladstone Institutes, San Francisco, CA, USA.

3. Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, USA.

4. The Cancer Cell Map Initiative, San Francisco and La Jolla, CA.

5. Department of Pharmacology, University of California San Diego, La Jolla, CA.

6. Moores Cancer Center, University of California San Diego, La Jolla, CA.

7. Division of Genetics, Department of Medicine, University of California San Diego, La Jolla, CA.

8. Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA.

9. Department of Biochemistry and Biophysics Center for Advanced Light Microscopy at UCSF, University of California San Francisco, San Francisco, CA, USA.

10. Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA, USA.

11. Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.

12. Department of Computer Science, University of California San Diego, La Jolla, CA, USA.

Abstract

Mapping protein interactions driving cancer Cancer is a genetic disease, and much cancer research is focused on identifying carcinogenic mutations and determining how they relate to disease progression. Three papers demonstrate how mutations are processed through networks of protein interactions to promote cancer (see the Perspective by Cheng and Jackson). Swaney et al . focus on head and neck cancer and identify cancer-enriched interactions, demonstrating how point mutant–dependent interactions of PIK3CA, a kinase frequently mutated in human cancers, are predictive of drug response. Kim et al . focus on breast cancer and identify two proteins functionally connected to the tumor-suppressor gene BRCA1 and two proteins that regulate PIK3CA. Zheng et al . developed a statistical model that identifies protein networks that are under mutation pressure across different cancer types, including a complex bringing together PIK3CA with actomyosin proteins. These papers provide a resource that will be helpful in interpreting cancer genomic data. —VV

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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