Project 1: Systematic Physical and Spatial Mapping of Cancer Driver Networks

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CCMI v2.0 Project 1: Systematic physical and spatial mapping of driver networks in cancer Project Leads: Nevan Krogan and Emma Lundberg; Co-Investigators: Alan Ashworth, Jean-Philippe Coppe, Jennifer Grandis, Silvio Gutkind, Natalia Jura and Laura van ’t Veer SUMMARY Tumors display complex mutational profiles that appear as a random pattern of mutations in genetic studies. However, it is their non-random combination and convergence on cancer pathways that lead to transformation. Specific pathways such as the PI3K or p53 axis are recurrently mutated in a majority of cancers but besides such pan-cancer mutated pathways, each tumor harbors 20 to over 1,000 additional mutations that are rarely seen across the patient population. Tumor heterogeneity, tissue of origin, and degree of progression give each case a unique subset of altered pathways and has hampered the development of targeted cancer therapies. Mapping genetic mutations onto previously identified cellular pathways can provide insights for clinical characterization. To efficiently leverage pathway networks for therapeutic strategies, in Project 1 we will identify and characterize cancer driver pathways. To this end, we will combine physical and spatial protein interactions with large scale genomic data and apply a suite of proteomic technologies with in vitro imaging through cryo-electron microscopy (cryo-EM) to systematically map protein networks in an orthogonal (cancer specific) or transversal (across cancers) manner. Specifically, we will systematically identify the network of key regulators of the PI3K pathway and p53 across breast (BRCA), head and neck (HNSCC) and lung squamous cancers (LUSC), and complement our previous work on HNSCC and BRCA by identifying driver networks in LUSC. Guided by proteomic approaches coupled with sophisticated imaging and high-resolution structural analysis of key complexes with functional validation, Project 1 will gain insights into the underlying molecular biology of these cancers and unravel genetic vulnerabilities of therapeutic relevance. In Aim 1, we will map the protein-protein interactions (PPIs) of 30 proteins (and 12 mutants in 6 of those proteins) of the PI3K pathway and 10 mutants of p53 across HNSCC, BRCA and LUSC. We will also define the physical interactions of the 30 most recurrently altered proteins (and 20 associated mutants in 9 of the proteins) in LUSC, complementing our previous work on HNSCC and BRCA. Using the Human Protein Atlas resource of antibodies, Aim 2 will focus on macroscopic mapping of the spatial subcellular organization of key oncogenic drivers and their interactors defined in Aim 1. Aim 3 will exploit recent advances in cryo-EM to structurally characterize key complexes, including those in the PI3K pathway. Finally, predictions from the previous aims will be tested in Aim 4 in cell lines, primary cells and mouse models and with clinical data.