A protein interaction landscape of breast cancer.

Cancers have been associated with a diverse array of genomic alterations. To help mechanistically understand such alterations in breast-invasive carcinoma, we applied affinity purification­mass spectrometry to delineate comprehensive biophysical interaction networks for 40 frequently altered breast cancer (BC) proteins, with and without relevant mutations, across three human breast cell lines. These networks identify cancer-specific protein-protein interactions (PPIs), interconnected and enriched for common and rare cancer mutations, that are substantially rewired by the introduction of key BC mutations. Our analysis identified BPIFA1 and SCGB2A1 as PIK3CA-interacting proteins, which repress PI3K-AKT signaling, and uncovered USP28 and UBE2N as functionally relevant interactors of BRCA1. We also show that the protein phosphatase 1 regulatory subunit spinophilin interacts with and regulates dephosphorylation of BRCA1 to promote DNA double-strand break repair. Thus, PPI landscapes provide a powerful framework for mechanistically interpreting disease genomic data and can identify valuable therapeutic targets.

KRASG12C inhibition produces a driver-limited state revealing collateral dependencies.

Inhibitors targeting KRASG12C, a mutant form of the guanosine triphosphatase (GTPase) KRAS, are a promising new class of oncogene-specific therapeutics for the treatment of tumors driven by the mutant protein. These inhibitors react with the mutant cysteine residue by binding covalently to the switch-II pocket (S-IIP) that is present only in the inactive guanosine diphosphate (GDP)-bound form of KRASG12C, sparing the wild-type protein. We used a genome-scale CRISPR interference (CRISPRi) functional genomics platform to systematically identify genetic interactions with a KRASG12C inhibitor in cellular models of KRASG12C mutant lung and pancreatic cancer. Our data revealed genes that were selectively essential in this oncogenic driver-limited cell state, meaning that their loss enhanced cellular susceptibility to direct KRASG12C inhibition. We termed such genes "collateral dependencies" (CDs) and identified two classes of combination therapies targeting these CDs that increased KRASG12C target engagement or blocked residual survival pathways in cells and in vivo. From our findings, we propose a framework for assessing genetic dependencies induced by oncogene inhibition.