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Personalized cancer models to discover and develop new therapeutic targets.

个性化癌症模型以发现和开发新的治疗靶点。

基本信息

批准号：
10228567
负责人：
CHRISTOPHER J KEMP
金额：
$ 47.03万
依托单位：
FRED HUTCHINSON CANCER RESEARCH CENTER
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：
2017-09-14 至 2022-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10228567
关键词：
Address Affect Autologous Biochemical Bioinformatics Biological Assay Biological Markers Biology Biopsy Cancer Biology Cancer Model Cell Culture Techniques Cells Clinical Clinical Oncology Clinical Trials Clustered Regularly Interspaced Short Palindromic Repeats Complex Computational Biology DNA sequencing Data Development Drug Combinations Drug Targeting Drug resistance Event Future Gene Targeting Genes Genetic Genetic Heterogeneity Genome Genomics Genotype Goals Head and Neck Squamous Cell Carcinoma Human Immunotherapeutic agent KRAS2 gene Knock-out Lethal Genes Malignant Neoplasms Malignant neoplasm of ovary Methods Modeling Molecular Mutate Mutation Neoadjuvant Therapy Oncogenes Oncology Operative Surgical Procedures Organoids Outcome Outcomes Research Patient Representative Patients Pharmaceutical Preparations Phenotype Physiological Predictive Value Research Personnel Resistance Resistance development Screening Result Small Interfering RNA Solid Neoplasm Surgical Oncology System TP53 gene Test Result Testing Therapeutic Agents Translations Tumor-Derived Validation Visualization Work cancer cell cancer genomics cancer type drug candidate drug development drug discovery drug efficacy druggable target exhaustion gene function genomic aberrations genomic data high throughput screening inhibitor/antagonist innovation insight molecular subtypes mouse model mutant neoplastic cell new therapeutic target novel novel strategies novel therapeutics patient derived xenograft model population based pre-clinical precision medicine precision oncology preclinical development predictive modeling response screening small hairpin RNA small molecule inhibitor standard of care statistics success targeted agent targeted cancer therapy targeted treatment tool tumor tumor heterogeneity

项目摘要

PROJECT SUMMARY/ABSTRACT The wealth of data on the genomics of cancer provides a great opportunity to develop more effective targeted therapies. However, many commonly mutated cancer genes resist efforts to target with drugs, genetic heterogeneity of tumors confounds choice or efficacy of drugs, and development of resistance to commonly used therapies is common, leaving few alternatives. New approaches are needed to address these challenges. Exploiting cellular vulnerabilities generated as a result of mutations in commonly mutated genes, e.g. synthetic lethality, is a promising approach, as illustrated by the recent approval of the PARP inhibitor olaparib in ovarian cancer. We have developed and optimized a synthetic lethal discovery platform that entails high throughput screening to identify novel targets in patient-derived cancer cell cultures and isogenic cell systems. Integration of functional screen results with both patient specific (N of 1) and population-based genomic data is used to prioritize targets useful to the greatest number of patients and in the most appropriate genomic and molecular contexts. Prioritized targets undergo exhaustive confirmation and orthogonal validation in physiologically-relevant settings including genomically characterized patient-derived cell cultures, organoids and patient derived xenograft (PDX) models. Synthetic lethal genes identified with our platform are conserved across species, have been confirmed as candidate drug targets across multiple human cancer types and have led to an investigator initiated clinical trial, illustrating the translational utility of our platform. The outcome of this proposal will be novel validated targets and therapeutic strategies to several human cancer types including those resistant to standard of care agents and a deeper understanding of the biology of several major cancer genes.

项目总结/文摘