This proposed CTDD program will help translate the enormous resource of high- throughput cancer genome characterizations into functionally validated, cancer-genotype based therapeutic targets. Over the past several years, members of this project have developed powerful tools and strategies for functionally annotating cancer genomes. These have enabled the identification and validation over fifty cancer genes, several of which are compelling therapeutic targets. Here, we propose to synthesize and optimize those strategies into a unified blueprint that can be applied across many tumor types. At the core of our philosophy is the use of powerful computational tools to narrow the extent of the genome that must be surveyed functionally. This enables the use of more precise human and mouse models to assess drivers and dependencies and approaches to combinatorial interactions that could not be carried out on a genome wide scale. We will apply these tools to select cancer types and gene sets in order to identify new oncogenic drivers, genotype-specific cancer dependencies, and to test strategies for the systematic identification of targets for combination therapies. We envision the impact of our project not only as the identification of genomically informed targets for several tumor types but also as providing tools and strategies that can be used throughout the consortium and the community.

Public Health Relevance

Technological breakthroughs in genomics have enabled a comprehensive characterization of the genetic abnormalities in many human tumor types. What is needed now are equally powerful methods for translating these genomic characterizations into functionally validated cancer therapeutic targets and ultimately new treatments. We propose to synthesize and optimize informatics, functional, and in vivo strategies into a unified blueprint that can be applied across many tumor types.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Research Project--Cooperative Agreements (U01)
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Special Emphasis Panel (ZCA1-SRLB-V (J1))
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Gerhard, Daniela
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Cold Spring Harbor Laboratory
Cold Spring Harbor
United States
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Chio, Iok In Christine; Tuveson, David A (2017) ROS in Cancer: The Burning Question. Trends Mol Med 23:411-429
Öhlund, Daniel; Handly-Santana, Abram; Biffi, Giulia et al. (2017) Distinct populations of inflammatory fibroblasts and myofibroblasts in pancreatic cancer. J Exp Med 214:579-596
Roe, Jae-Seok; Hwang, Chang-Il; Somerville, Tim D D et al. (2017) Enhancer Reprogramming Promotes Pancreatic Cancer Metastasis. Cell 170:875-888.e20
Feigin, Michael E; Garvin, Tyler; Bailey, Peter et al. (2017) Recurrent noncoding regulatory mutations in pancreatic ductal adenocarcinoma. Nat Genet 49:825-833
Hwang, Chang-Il; Boj, Sylvia F; Clevers, Hans et al. (2016) Preclinical models of pancreatic ductal adenocarcinoma. J Pathol 238:197-204
Manchado, Eusebio; Huang, Chun-Hao; Tasdemir, Nilgun et al. (2016) A Pipeline for Drug Target Identification and Validation. Cold Spring Harb Symp Quant Biol 81:257-267
Lee, Hong-Jen; Li, Chien-Feng; Ruan, Diane et al. (2016) The DNA Damage Transducer RNF8 Facilitates Cancer Chemoresistance and Progression through Twist Activation. Mol Cell 63:1021-33
Ebbesen, Saya H; Scaltriti, Maurizio; Bialucha, Carl U et al. (2016) Pten loss promotes MAPK pathway dependency in HER2/neu breast carcinomas. Proc Natl Acad Sci U S A 113:3030-5
Cancer Target Discovery and Development Network (2016) Transforming Big Data into Cancer-Relevant Insight: An Initial, Multi-Tier Approach to Assess Reproducibility and Relevance. Mol Cancer Res 14:675-82
Fang, Han; Bergmann, Ewa A; Arora, Kanika et al. (2016) Indel variant analysis of short-read sequencing data with Scalpel. Nat Protoc 11:2529-2548

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