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Multigenic copy number alterations

多基因拷贝数改变

基本信息

批准号：
9333598
负责人：
Scott Powers
金额：
$ 55.2万
依托单位：
STATE UNIVERSITY NEW YORK STONY BROOK
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-03-15 至 2022-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9333598
关键词：
11q13 14q13 Address Affect Attention Automobile Driving Benchmarking Biological Breast Cancer cell line Breast Epithelial Cells CCND1 gene CRISPR/Cas technology Cataloging Catalogs Cell model Cells Clinical effectiveness Communities Computational algorithm Computing Methodologies Control Locus Cre-LoxP DHFR gene DNA DNA copy number Data Set Dependency ERBB2 gene Endometrial Carcinoma Engineering Epidermal Growth Factor Receptor Event Evolution Experimental Models FGF19 gene GRB7 gene Gene Combinations Gene Mutation Genes Genetic Genetic Recombination Genetic study Genome engineering Glioblastoma Goals Human Individual KRAS2 gene Link Malignant - descriptor Malignant Neoplasms Malignant neoplasm of esophagus Malignant neoplasm of liver Malignant neoplasm of lung Malignant neoplasm of ovary Methods Methotrexate Modeling Mutation Nature Oncogenes Oncogenic Oncoproteins PDGFRA gene PIK3CA gene Pathway interactions Patients Phenotype Phosphoproteins Phosphorylation Plasmids Play Primary carcinoma of the liver cells Property Proteins Proteomics RNA Research Resources Role Sampling Site Squamous cell carcinoma Stretching Structure System Technology Testing The Cancer Genome Atlas Therapeutic Time Work anticancer research base cancer genome cancer therapy combinatorial comparative computerized tools design genomic profiles improved lung Carcinoma malignant breast neoplasm malignant stomach neoplasm molecular subtypes mutant new therapeutic target next generation sequencing novel novel therapeutics screening success tool tumor tumor progression

项目摘要

Project Summary DNA copy number alterations (CNAs) are oncogenic drivers for many types of human cancer. For some cancers, e.g. certain ovarian, breast and endometrial cancers, it is very likely that CNAs, comprise the bulk of genetic alterations responsible for their highly malignant properties. CNAs may also be responsible for driving squamous carcinoma of the lung and for subsets of gastric and esophageal cancers. Relatively little attention is being paid to understanding this class of genetic alterations. More importantly, from a cancer treatment perspective, there is no roadmap for determining whether they induce selective dependencies that could be utilized for developing new therapeutics. As our group and others have discovered in the past several years, the vast majority of CNAs contain multiple driver genes, and this makes it considerably more difficult to study how they impact cancer progression compared to single-gene events. The overall goal of this project is to develop new tools and models to investigate multigenic CNAs so that they can be more readily studied and utilized in developing new therapeutics. In Aim 1, we will combine CRISPR/Cas9 and Cre-Lox genome engineering to accurately model multigenic CNAs and determine how they impact oncogenic phenotypes in normal mammary epithelial cells, similar to how mutations in single-gene alterations such as PIK3CA are currently studied. Once we have validated these new cell models, we will screen for induced dependencies. In Aim 2, we will develop and implement computational methods to extract information about specific CNAs from the warehouse of information present in large-scale integrated cancer genome datasets. We have extensive preliminary results that validate this approach, including the prediction of CNA-selective dependencies. Lastly, to truly understand how multigenic CNAs play a role in cancer, we must functionally probe the interactions between multiple drivers. We previously demonstrated that these interactions were key features of the oncogenicity of the 14q13 amplicon in lung cancer and 11q13 amplicon in liver cancer. Thus, our final goal is to develop and implement generalizable methods to study genetic interactions between multiple drivers (Aim 3). Our proposal is based on the premise that CNAs are important drivers in cancer but that the current research approach needs to be improved. The clinical effectiveness of targeted treatments for patients with HER2-amplified breast cancers underscores the enormous translational potential of CNAs. By developing the tools and models for CNAs described in this proposal, we will make a significant impact on understanding multigenic CNAs and will lay the groundwork for identifying associated dependencies and therapeutic strategies.

项目总结