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Large-Scale Genetic Analyses of Human Cancer

人类癌症的大规模基因分析

基本信息

批准号：
10017159
负责人：
Valsamo Anagnostou
金额：
$ 31.11万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2006
资助国家：
美国
起止时间：
2006-05-01 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10017159
关键词：
Affect Amino Acid Sequence Antigens Autologous Binding Biological Assay Cancer Etiology Cancer Patient Candidate Disease Gene Cell Culture Techniques Cells Clinical Clonality Code Colorectal Cancer Complex Cytotoxic T-Lymphocytes DNA Sequence Alteration Data Detection Development Diagnostic Disease Progression Equilibrium Evolution Funding Future Gene Expression Genes Genetic Genomics Grant Head Cancer Histocompatibility Antigens Class I Human Immune Immune Targeting Immune checkpoint inhibitor Immune response Immune system Immunologics Immunotherapy Individual Intervention Knowledge Large-Scale Sequencing Lead Link Liquid substance Malignant Female Reproductive System Neoplasm Malignant Neoplasms Malignant neoplasm of brain Malignant neoplasm of lung Malignant neoplasm of pancreas Measures Mediating Methods Molecular Monitor Mutation Neck Cancer Outcome Pathway interactions Patient Selection Patients Protein Sequence Analysis Research Project Grants Resistance Resistance development Somatic Mutation T cell response T-Cell Receptor T-Lymphocyte T-cell receptor repertoire Therapeutic Therapeutic Intervention Time Translating Work anti-tumor immune response cancer genome cancer genomics combinatorial exome sequencing genetic analysis genome-wide analysis immune checkpoint blockade immunogenic improved insight liquid biopsy malignant breast neoplasm neoantigens novel novel strategies patient response predicting response predictive test pressure response response biomarker success targeted agent targeted treatment therapy development therapy outcome therapy resistant treatment strategy tumor tumor DNA tumor progression tumorigenesis

项目摘要

PROJECT SUMMARY Human cancers are caused by the accumulation of mutations in specific genes. During the previous funding periods, our group was the first to determine the sequence of protein coding genes in human cancer and extended this approach to many tumor types. Through this work, we were able to identify candidate genes which had not been previously linked to tumorigenesis, define the basic genomic and neoantigen landscape of common human cancers, and point to pathways that underlie the complex genetic alterations in individual tumor types. More recently, we have identified genomic alterations that are important in the sensitivity and resistance of common targeted therapies as well as immunotherapy. We have pioneered the development of non-invasive circulating tumor DNA approaches to detect and monitor tumors, and have shown that these may be broadly applicable to many cancer patients. These analyses provided new insights into the mechanisms underlying tumorigenesis and have delineated novel avenues for clinical intervention. The recent intersection of cancer genomics with novel immunologic approaches is promising to revolutionize cancer therapeutics. Immune checkpoint inhibitors have demonstrated notable clinical benefit in a variety of tumor types and it is thought that these therapies exert their effects in large part through the immune recognition of mutation associated neoantigens encoded in the genomes of cancer cells. Unfortunately, despite initial successes, a large fraction of patients do not benefit from these treatments or develop resistance after an initial response. Our preliminary data suggest that clinical outcome to immune checkpoint blockade may be determined by the evolving genomic and neoantigen landscape in cancer and that dynamics of the T cell receptor repertoire may be a useful measure of therapeutic outcome. The purpose of this competitive renewal application is to extend our large-scale sequencing efforts to focus on understanding how the evolving genomic and immune landscapes regulate response and resistance to immune checkpoint blockade. First, we propose genome-wide analyses of tumors to examine cancer genome changes under the selective pressure of these therapies. We will develop and utilize computational approaches to predict mutation-associated neoantigens and functionally validate these through novel approaches in patient-specific T cell cultures. Finally, we will develop non-invasive approaches involving circulating tumor DNA and the T cell receptor repertoire to dynamically measure response and resistance to immune checkpoint blockade. The knowledge gained from the studies described in this application will help to broaden our understanding of the underlying mechanisms of response and resistance to immunotherapy. We envision that these analyses will be rapidly translated into the clinical setting, providing new approaches for predicting patient response to current immune-targeted therapies and for development of new treatment strategies.

项目总结