PROJECTS

Introduction

There now exists a vast amount of sequence data from tumors associated with many different cancer types, and efforts are ongoing to extract mechanistic insight from this information. Given all of this progress, what is now needed is an integrated computational and experimental strategy that will help place these alterations into context of the higher order biological mechanisms in cancer cells. Th...

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There now exists a vast amount of sequence data from tumors associated with many different cancer types, and efforts are ongoing to extract mechanistic insight from this information. Given all of this progress, what is now needed is an integrated computational and experimental strategy that will help place these alterations into context of the higher order biological mechanisms in cancer cells. This is the goal of the Cancer Cell Map Initiative, which will create a resource that can be used for cancer genome interpretation. This will allow us to identify key complexes and pathways to be studied in greater mechanistic detail to get a deeper understanding about the biology underlying different cancer states. Genomic data derived from tumor sequencing studies identifies key genes implicated in different cancer cells. Integrated physical and genetic networks based on these factors will help put the mutations into biological context, enabling the discovery of new disease genes as interacting partners become apparent. Ultimately, all of this knowledge will translate into improved ability to stratify and treat patients based on the particular networks that are altered.

Mapping the Pharmacogenetic Landscape for Precision Medicine

It is well known that cancer is tremendously heterogeneous with few tumors having the same set of mutated, amplified, or deleted genes. Clearly these molecular differences alter a tumor’s responsiveness to chemotherapy, but current knowledge of how the tumor genotype influences drug sensitivity is poor. We will seek to vastly increase our understanding of pharmacogenetic interactions in cancer (...

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It is well known that cancer is tremendously heterogeneous with few tumors having the same set of mutated, amplified, or deleted genes. Clearly these molecular differences alter a tumor’s responsiveness to chemotherapy, but current knowledge of how the tumor genotype influences drug sensitivity is poor. We will seek to vastly increase our understanding of pharmacogenetic interactions in cancer (gene-gene and gene-drug interactions). Recognizing that oncogenic transformation requires alteration of the function of many genes, we will use state-of-the-art high-throughput epistasis mapping and data analysis pipelines to systematically interrogate the function and pairwise interactions of a panel cancer driver genes and therapeutic targets in both head and neck squamous cell carcinoma and breast cancer, expecting to identify many new synthetic lethal relationships. Anticipating the discovery of multiple therapeutically relevant synthetic lethal interactions, we have already formulated a plan for rapid clinical testing of the most promising hits as new treatment arms on the I-SPY 2 trial in breast cancer. Through this work, we expect to develop fundamental new insights into the genetic logic and functional synergies underlying cancer pathways as well as to greatly expand the ability of clinicians to practice precision oncology.