PROJECT 1: SYSTEMATIC IDENTIFICATION OF DRIVER NETWORKS IN CANCER SUMMARY A vast number of mutations contribute to cancer, but the observed nonrandom combinations of those leading to transformation highlight the importance of hallmark pathways and networks in cancer progression. While many pathways have been implicated in cancer, attributes such as tumor heterogeneity, tissue of origin, and degree of progression lead to each case exhibiting a unique subset of altered pathways. Taken together, this diversity among cancer types and their origins has complicated the development of targeted cancer treatments. We propose here to systematically identify the protein networks that drive cancer, across a range of tumor types starting with head and neck squamous cell carcinoma (HNSCC) and breast cancer (BC). Coupled with functional validation and highresolution structural analysis of the key protein interactions and complexes, we anticipate major insights into the underlying tumor biology as well as the potential to unravel genetic vulnerabilities of therapeutic relevance. In Project 1, CCMI investigators will build a physical interaction mapping pipeline focused on understanding the underlying network biology behind cancer. To this end, we are targeting 80 genes genetically linked to either HNSCC or BC and subjecting the wildtype proteins and numerous mutant forms to affinity purification mass spectrometry (APMS) in a panel of relevant cancer subtype cell lines (Aim 1). To complement these data we will perform functional kinome screens using the high throughput kinaseactivity mapping (HTKAM) platform, which will quantify how kinase signaling networks are rewired by different protein mutations, and in different cellular backgrounds. Next, we will use the computational technique of network propagation to define the major mutated driver pathways underlying each disease subtype, in which physical protein interactions are integrated with somatic and germline mutations identified in tumor genomes. The results of this network characterization (Aim 1) and integrative analysis (Aim 2) will identify network components that could serve as targets for therapeutic intervention; in Aim 3 we will perform cellular assays to validate these network targets. Lastly, in Aim 4 we will use cryogenic electron microscopy (cryoEM) to structurally characterize therapeutically actionable protein complexes and develop technology to enable the screening of many more. Successful completion of this work will yield a network mapping pipeline that can be extended to many cancer types and will aid in the rational selection of therapeutic targets with greater precision and speed.