A protein interaction landscape of breast cancer
This study demonstrates that systematic PPI maps provide a useful resource in contextualizing uncharacterized mutations within signaling pathways and protein complexes within malignant and premalignant cellular contexts.
Abstract
<jats:title>Mapping protein interactions driving cancer</jats:title> <jats:p> 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 <jats:italic>et al</jats:italic> . 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 <jats:italic>et al</jats:italic> . focus on breast cancer and identify two proteins functionally connected to the tumor-suppressor gene BRCA1 and two proteins that regulate PIK3CA. Zheng <jats:italic>et al</jats:italic> . 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 </jats:p>