权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Oncogenic mechanisms, molecular stratification and therapeutic targets of brain tumors

脑肿瘤的致癌机制、分子分层和治疗靶点

基本信息

批准号：
10493186
负责人：
Antonio Iavarone
金额：
$ 12.52万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-24 至 2022-09-26
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10493186
关键词：
Biological Brain Neoplasms Cancer Model Cancer Patient Cells Classification Clinical Research Computer Analysis Dependence Development Dissection Gene Proteins Genomics Glioblastoma Goals Human Individual Investigation Laboratories Malignant Glioma Malignant Neoplasms Modeling Molecular Motion Oncogenes Oncogenic Outcome Pathogenesis Pathway interactions Patients Phenotype Plant Roots Proteomics Research Resistance Route Solid Neoplasm Stratification Subgroup Testing Therapeutic Tissues Treatment Failure Universities Validation Work base cancer genome cancer heterogeneity computerized tools design drug sensitivity high throughput technology in vitro Model in vivo innovation neoplastic cell new technology new therapeutic target novel operation personalized therapeutic programs targeted treatment therapeutic target tool transcriptomics tumor

项目摘要

Abstract The work to be pursued in this application will continue and expand the program pioneered by Dr. Iavarone to combine innovative computational tools and state-of-the-art experimental cancer models in vitro and in vivo to identify homogeneous subgroups of cancer patients in order to dissect the pathogenesis of cancer and design tailored and fully validated personalized therapeutic approaches. The application is focused on glioblastoma multiforme, one of the most lethal forms of human cancer. The investigation of glioblastoma has represented a long-standing effort of Dr. Iavarone’s laboratory, which in recent work has produced novel targeted therapeutic opportunities currently being tested in clinical studies. The proposal will also benefit from the organizational contexts recently set in motion by the large network operations coordinated by the PI. The research plan is articulated around the development of a novel and integrated computational-experimental framework for: i) the identification of homogeneous groups of tumors sharing activation of the same biological pathways; ii) the study of cancer heterogeneity at the single cell level to accurately inform tumor classifications; iii) the therapeutic prediction emerging from the identification of driver modules and synthetic lethal relationships of malignant glioma. We will develop and apply novel technologies for high-throughput transcriptomic and proteomic analysis of individual cells within malignant glioma tissues. These approaches, which we have pioneered in our laboratory at Columbia University during the last few years, will serve as the basis for the multifaceted computational analysis that will extract genes and proteins responsible for the phenotypic state of individual cells. Experimental validations will be selectively applied to the novel and most exciting molecular pathways and will be performed by our laboratory that has an array of experimental tools and sequence-annotated patient-derived models to pursue each individual question. As for the selection of oncogene-dependent and independent vulnerabilities identified by our previous work, the ability of our studies to identify novel driver phenotypes and master regulators of individual tumor cells will be geared towards routing the new mechanisms into pathway-based synthetic lethality that will inform specific drug sensitivities. The successful outcome of this proposal is an integrated computational-experimental pipeline that will be able to mechanistically identify the determinants of tumor genomes and phenotypes of solid tumors. This information will be of invaluable significance to decipher evolving tumor dependencies and provide the most accurate therapeutic predictions.

摘要