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Systems approaches to understanding the relationships between genotype, signaling, and therapeutic efficacy

了解基因型、信号传导和治疗功效之间关系的系统方法

基本信息

批准号：
9904544
负责人：
Wilhelm Haas
金额：
$ 77.01万
依托单位：
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
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：
2017-04-05 至 2022-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9904544
关键词：
Address Affect Algorithms Attention Biological Markers Biology Cancer Patient Cells Colon Colorectal Colorectal Cancer Communities Complex Computer Analysis Computer Models Computing Methodologies Cues Cytometry Cytostatics Data Epidermal Growth Factor Receptor Epigenetic Process Event Exposure to FDA approved Failure Fuzzy Logic Genes Genetic Genetically Engineered Mouse Genotype Goals Heterogeneity Human Human Cell Line Hyperactive behavior Individual KRAS2 gene Knowledge Least-Squares Analysis Lung MAP3K1 gene MEK inhibition MEKs Malignant Neoplasms Mass Spectrum Analysis Measurement Measures Molecular Movement Mutate Mutation Oncogenic Oncoproteins Output Pancreas Pathway interactions Patients Phosphotransferases Physicians Prize Proteome Proteomics Regimen Research Resistance Sampling Signal Pathway Signal Transduction System Systems Biology TP53 gene Testing Therapeutic Therapeutic Studies Therapy trial Time Tissues Treatment Efficacy Tumor Suppressor Genes Work Xenograft procedure antibody inhibitor base cancer cell cancer therapy combinatorial conventional therapy cytotoxic design effective therapy experimental study forest individual patient inhibitor/antagonist insight kinase inhibitor multidimensional data mutant personalized medicine personalized therapeutic phosphoproteomics pre-clinical pre-clinical therapy precision medicine precision oncology prospective response small molecule stem success targeted treatment therapeutic candidate therapy resistant treatment response tumor

项目摘要

Project Summary/Abstract The promise of precision medicine is that a physician can tailor a therapeutic regimen to suit each individual patient. In the case of cancer, this means a personalized therapeutic strategy based on the molecular features of an individual's cancer. But while successes in precision medicine have garnered significant attention in recent years, precision medicine has not made an impact for the vast majority of cancer patients. Our overarching goal is to use proteomics and systems biology to understand the relationships between cancer genotype and therapeutic response, with the long-term goal of expanding the prospects of precision medicine. Our study focuses primary on cancers expressing mutant forms of K-Ras, the most commonly mutated oncoprotein in cancer and one of the best biomarkers for the failure of a cancer to respond to therapy. Using a variety of experimental and computational approaches, this project will address three key questions related to K-Ras and the promise of precision medicine. First, we will exploit a relatively rare circumstance in which colorectal cancers expressing a specific mutant form of K-Ras are uniquely sensitive to inhibition of the MEK kinase. We will use mass spectrometry and computational modeling to determine why cancers expressing K-RasG12D and K-RasA146T are differentially sensitive to inhibition of MEK. Next, we will address the limitation of univariate genetic prediction of therapeutic efficacy by determining how genetic and epigenetic factors interact to establish network signaling state. We will use mass cytometry and computational modeling to explore how signaling downstream of mutant K-Ras is affected by cellular lineage and by secondary mutations in oncogenes and tumor suppressor genes. Finally, we will move beyond genotype as a predictor of therapeutic efficacy by developing an algorithm to predict sensitivity to kinase inhibition based on phospho-proteomic measurements. We will validate the computational approach via preclinical therapeutics studies in patient-derived xenografts. Altogether these studies will utilize state-of-the-art experimental and computational approaches to make personalized medicine a realistic goal for patients suffering from K-Ras mutant cancer.

项目总结/文摘