Functional Genomic Discovery of Pathway Targeted and Immune Modulatory Therapeutic Combinations in Hematologic Malignancies

血液系统恶性肿瘤中通路靶向和免疫调节治疗组合的功能基因组发现

• 批准号: 10238859
• 负责人: BRIAN J DRUKER
• 金额: $ 100.48万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10238859
• 关键词: Acute; Acute Myelocytic Leukemia; Aftercare; Algorithms; Area; Automobile Driving; Biological; Biological Assay; CRISPR screen; Cell physiology; Cells; Characteristics; Chemicals; Chronic Lymphocytic Leukemia; Clinical; Clinical Trials; Clustered Regularly Interspaced Short Palindromic Repeats; Combined Modality Therapy; Computational algorithm; Computer Analysis; Cytometry; Data; Data Set; Disease; Drug Combinations; Drug resistance; Foundations; Future; Gene Expression; Genes; Genetic; Genomics; Genotype; Goals; Hematologic Neoplasms; Hematology; Immune; Immune Targeting; Immunologics; Immunomodulators; Immunophenotyping; Knowledge; Laboratories; Leadership; Libraries; Malignant Neoplasms; Molecular; Myelogenous; Pathway interactions; Patients; Pharmaceutical Preparations; Pharmacogenomics; Phenotype; Physiological; Preclinical Testing; Process; Quantum Dots; RNA; Research; Residual state; Resistance; Resistance development; Resources; Sampling; Screening procedure; System; Techniques; Testing; Therapeutic; Translating; Update; Validation; base; cancer genomics; chemotherapy; cohort; computer framework; computerized tools; data resource; design; drug development; drug sensitivity; drug testing; exome; experimental study; functional genomics; gene function; genetic profiling; genome-wide; genomic data; high throughput screening; immune checkpoint; improved; inhibitor/antagonist; interest; large datasets; large scale data; leukemia; miniaturize; novel; novel drug combination; novel therapeutics; predictive marker; programs; prospective; response; screening; small molecule; small molecule inhibitor; targeted agent; targeted biomarker; targeted treatment; transcriptome sequencing; treatment strategy; tumor

PROJECT SUMMARY Targeted therapies have been a recent focus of drug development for acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL), but the majority of patients eventually develop resistance even to these new drugs. There is thus an urgent need to better understand the pathways underlying drug resistance to identify novel drugs or combinations of drugs that can effectively inhibit these pathways. Through our leadership of the Beat AML program as well as other programs in our laboratories oriented towards CLL, we are amassing a large cohort of patient samples with corresponding genomic, functional, clinical and immune annotation. We are developing novel computational tools to extract useful conclusions from these large datasets. The overall goals of this proposal are to leverage our existing cohorts, high-throughput screening tools, and datasets for prediction and pre-clinical testing of novel drug combinations that will eventually be translated into clinical trials. The specific aims of this project are to: (1) use genome-wide CRISPR screening and mass cytometry to create a discovery resource of genomic and immune profiles of 500 primary samples from leukemia patients; (2) develop an integrated computational framework (called PRECEPTS) to infer the cellular processes driving resistance to perturbagens and predict combination targets that can overcome resistance; (3) identify synergistic drug combinations by combining ex vivo testing of single drugs with CRISPR/Cas synthetic lethality screening with genes prioritized by computational prediction, and identify resistance pathways by using RNAseq to profile any residual resistant cells; and (4) use the data from (3) to identify and test drug combinations. This proposed project will contribute to all 3 areas of research interest for the CTD2 by improving our understanding of the molecular processes underlying drug sensitivity and resistance in leukemias, developing algorithms to predict markers and targets in these processes, and identifying drugs and/or combinations that will maximize drug sensitivity and minimize resistance. The proposed studies have direct translational relevance in selecting novel treatment strategies for clinical trials, and will benefit the CTD2 by generating large-scale data sets and providing novel computational tools that can be applied to future studies and expanded beyond leukemias.

项目总结

项目成果

Immunomodulatory effects of pevonedistat, a NEDD8-activating enzyme inhibitor, in chronic lymphocytic leukemia-derived T cells.

• DOI: 10.1038/s41375-020-0794-0
• 发表时间: 2021-01
• 期刊: Leukemia
• 影响因子: 11.4
• 作者: Best S;Lam V;Liu T;Bruss N;Kittai A;Danilova OV;Murray S;Berger A;Pennock ND;Lind EF;Danilov AV
• 通讯作者: Danilov AV