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Clonal drivers of resistance to immune checkpoint blockade in liver malignancies

肝脏恶性肿瘤抵抗免疫检查点阻断的克隆驱动因素

基本信息

批准号：
10357211
负责人：
Giannicola Genovese
金额：
$ 22.72万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-01-12 至 2023-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10357211
关键词：
Address Advanced Malignant Neoplasm Architecture Automobile Driving Bar Codes Behavior Biological CRISPR/Cas technology Cancer Biology Cancer Etiology Cancer Model Cancer Patient Cells Cessation of life Clinical Clonal Evolution Clonal Expansion Clustered Regularly Interspaced Short Palindromic Repeats Cytotoxic Chemotherapy Development Disease Disease Progression Ecosystem Epigenetic Process Epithelial Event Experimental Models Fishes Fluorescence Funding Generations Genetic Genetically Engineered Mouse Genomics Hepatobiliary Heterogeneity Human Human Characteristics Immune Immune Evasion Immune response Immunocompetent Immunomodulators Immunotherapy Kidney Knowledge Libraries Light Malignant - descriptor Malignant Neoplasms Malignant neoplasm of liver Metabolic Methods Mission Molecular Molecular Genetics Mosaicism Mus Nature Nivolumab Oncologist Outcome Pathologic Patients Phase Population Recovery Recurrence Recurrent disease Reporter Research Research Design Resistance Sampling Signal Transduction Sorting - Cell Movement Suicide Technology Therapeutic Transplantation Tumor-Derived United States National Institutes of Health Validation adaptive immune response base cancer cell cancer therapy cancer type checkpoint modulation chemotherapy design experience human disease immune checkpoint immune checkpoint blockade liver cancer model mortality multiple omics new technology novel patient subsets pressure response targeted treatment therapy resistant tool tumor weapons

项目摘要

PROJECT SUMMARY Background and relevance to NIH mission. Immune checkpoint blockade based therapy has quickly become the treatment paradigm for several advanced cancer including liver malignancies providing the clinical oncologist with a formidable weapon to achieve dramatic and durable tumor response. The widespread clinical use of modulators of the immune checkpoint, however, has clearly shown that a subset of patients are intrinsically poorly responsive to such treatments, while others might develop recurrent disease after an initial response. While this phenomenon is widely recognized the mechanisms underlying intrinsic and acquired resistance to immune therapy are still poorly understood, posing an urgent need for the development of novel technological tools to study and predict which clones within a tumor will likely drive recurrence. Research design. To investigate the cancer cell intrinsic mechanisms of adaptation and the tumor clonal dynamics in response to immune-checkpoint blockade in an autochthonous experimental model of cancer we will barcode somatic mosaic GEM models of liver cancer to look into the clonal drivers of resistance to immune- checkpoint blockade leveraging a CRISPR-Cas9 based clonal recovery method. Methods. We have generated somatic mosaic cancer models which faithfully recapitulate the biological behavior, the genomic complexity and functional heterogeneity of human disease. To investigate the clonal response to immune therapy malignant cells will be transduced with a dual reporter/suicide cassette barcoded lentiviral library that enables the precise recovery and expansion of any given barcoded clone by using a CRISPR/Cas9 based “fishing” method. These novel technology will be instrumental in the isolation and characterization of those clones/malignant cell populations that are intrinsically prone to evade the immune response or that stochastically acquire the ability to evade the adaptive immune response in the context of immune competent models of cancer. Genetic, molecular and metabolic characterization of such populations will shed light on the mechanisms driving the evasion from immune checkpoint blockade. Ultimately, we will gain fundamental information about clonal dynamics during disease progression in renal malignancies, in addition, by enabling the recovery of single clones and the generation of clonal avatars, this approach would help understanding the relative contribution of intrinsic cell plasticity vs. stochastic genetic events in driving disease recurrence. The technology would eventually demonstrate broader applications in the field of cancer biology and provide novel knowledge and valuable research tools to tackle different cancer types, particularly those characterized by a poor response to immune checkpoints modulation.

项目总结