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Systematic Identification and Pharmacological Targeting of Tumor Dependencies for Precision Cancer Medicine

精准癌症医学中肿瘤依赖性的系统识别和药理学靶向

基本信息

批准号：
10204929
负责人：
ANDREA CALIFANO
金额：
$ 120.19万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2022-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10204929
关键词：
Address Adenocarcinoma Affect Anaplastic Meningioma Area Biochemical Biological Assay Biological Markers Bladder Adenocarcinoma Cancer Model Cancer Patient Categories Cell Communication Cell Line Cells Clinical Clonal Expansion Colon Combined Modality Therapy Complex Data Dependence Disease Resistance Drug Combinations Drug Targeting Drug resistance Engineering Epigenetic Process FDA approved Gastrointestinal Stromal Tumors Genetic Genetic Transcription Glioblastoma Goals Human Immune system In Vitro Individual Investigation Investigational Drugs Lung Adenocarcinoma Maintenance Malignant Neoplasms Malignant neoplasm of prostate Methodology Modeling Molecular Profiling Mutation Network-based Oncogenes Oncology Oncoproteins Organoids Pathway interactions Patients Pharmaceutical Preparations Pharmacodynamics Pharmacology Phase Phenotype Primary Neoplasm Progression-Free Survivals Property Proteins Regulation Relapse Reporter Research Personnel Role Sampling Solid Neoplasm System Testing Therapeutic Universities Validation base candidate identification drug sensitivity falls follow-up immune checkpoint in vivo in vivo Model individual patient inhibitor/antagonist leukemia/lymphoma malignant breast neoplasm molecular marker neoplastic cell new therapeutic target partial response patient biomarkers patient derived xenograft model personalized approach phase 3 study population stratification precision oncology resistance mechanism small molecule inhibitor success targeted cancer therapy targeted treatment therapeutic target transcriptome sequencing tumor tumorigenesis tumorigenic

项目摘要

PROJECT SUMMARY Successful targets for cancer therapy fall in three main categories: oncogenes that elicit tumor-specific essentiality because of their direct role in tumorigenesis (oncogene dependency), proteins that elicit synthetic lethality with specific mutations despite lack of a direct role in tumorigenesis (non-oncogene dependency), and proteins related to the interaction of tumor cells with the immune system (immune-checkpoint dependency). However, given our current understanding of cancer as a complex and highly heterogeneous system, it is difficult to imagine that an individual protein may represent an effective target for all the billions of cells that make up a typical mass. Indeed, while genetic-based targeted therapy and immunoncology hold great promise a majority of patients still does not respond or will eventually relapse with drug resistant tumors, suggesting that the concept of therapeutic targets as single proteins may need to be revisited. To accomplish this goal, we will leverage a highly successful framework developed by our center investigators for the identification and pharmacological targeting of tumor dependencies implemented by the concerted activity of a handful of Master Regulator (MR) proteins within tightly regulated tumor checkpoint modules. Specifically, we will elucidate and experimentally validate MR proteins and associated Tumor Checkpoint modules of rare and incurable malignancies, on an individual patient basis, by performing network-based analysis of tumor samples signatures using regulatory models reverse engineered from primary tumor samples. We will then prioritize a set of FDA approved drugs and late stage investigational drugs in phase II or phase III studies in oncology (oncology drugs) based on their ability to either target essential/synthetic-lethal MRs (OncoTarget) or to reverse the full MR signature of a tumor (OncoTreat). RNASeq profiles of appropriately matched tumor models perturbed with available oncology drugs will be obtained and analyzed to assess the differential tumor checkpoint activity induced by individual drugs and drug combinations, followed by low-throughput studies to elucidate the regulatory basis of their activity. Models – including cell lines, short-term organotypic culture from tumor explants (EXPL), organoids (ORG), and patient derived xenografts (PDX) – will be selected based on MR protein conservation. We will validate these findings as well as overall efficacy of prioritized drugs and combinations, pharmacodynamic properties, biomarker accuracy and sensitivity, and mechanisms of resistance in suitable in vitro and in vivo models. If successful, this would represent the first mechanistic approach for precision cancer medicine, where therapeutic targets, associated inhibitors, and population stratification biomarkers are systematically derived from precise, mechanistic understanding of tumor state regulation and of its drug-induced modulation.

项目总结

项目成果

期刊论文数量（1）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Phase I/II trial of ruxolitinib in combination with trastuzumab in metastatic HER2 positive breast cancer.

DOI：
10.1007/s10549-021-06306-4
发表时间：
2021-08
期刊：
Breast cancer research and treatment
影响因子：
3.8
作者：
Kearney M;Franks L;Lee S;Tiersten A;Makower DF;Cigler T;Mundi P;Chi DC;Goel A;Klein P;Andreopoulou E;Sparano J;Trivedi M;Accordino M;Califano A;Hershman DL;Silva J;Kalinsky K
通讯作者：
Kalinsky K