The Cancer Target Discovery and Development Network at UCSF

加州大学旧金山分校癌症靶标发现和开发网络

• 批准号: 10210200
• 负责人: Sourav Bandyopadhyay
• 金额: $ 102.67万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-10 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10210200
• 关键词: Address; Area; Automobile Driving; CRISPR screen; CRISPR/Cas technology; Cataloging; Cell Communication; Cells; Characteristics; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Critical Pathways; Data; Development; Dominant-Negative Mutation; Drug resistance; Evolution; Fibroblasts; Funding; Gene Combinations; Genes; Genetic; Genetic Epistasis; Genotype; Goals; Growth; Heterogeneity; Human; Individual; Joints; Lesion; Libraries; Link; Maintenance; Malignant Neoplasms; Mammalian Cell; Maps; Mediating; Methodology; Methods; Mining; Mission; Molecular; Molecular Target; Mutation; Neoplasm Metastasis; Oncogenes; Pathway interactions; Patients; Phenotype; Program Development; Protocols documentation; Reagent; Recurrence; Research; Research Project Grants; Resistance; Role; Synthetic Genes; System; Systems Biology; Technology; The Cancer Genome Atlas; Therapeutic; Tissues; Variant; acquired drug resistance; anticancer research; base; cancer cell; cancer genome; cancer initiation; cancer type; cell behavior; cell type; gain of function; gene interaction; genome sequencing; genomic data; high throughput screening; improved; innovation; macrophage; new therapeutic target; novel; novel therapeutics; programs; resistance mechanism; screening; small molecule therapeutics; therapy resistant; tool; tumor; tumor growth; tumor heterogeneity; tumor microenvironment

PROJECT SUMMARY Our general strategy is to take advantage of novel tools and methodologies that we have developed during our first CTD^2 funding period- more specifically pioneering and applying CRISPR based technologies to aid the discovery and characterization of novel cancer targets and their modulators– using innovative high throughput screening methods. Our end goal is to uncover optimal combinations of perturbagens with the potential to eliminate all cancer cells, despite their clonal heterogeneity and environmental context. One goal is to elucidate new molecular targets with the goal to overcome acquired drug resistance. We build upon an exciting system allowing us to quantitate genotypic and phenotypic cell heterogeneity for hundreds of thousands of single cancer cells. We propose a battery of therapeutic small molecule screens to identify candidate driver genes associated with drug resistance and with recurrent mutations from TCGA, TARGET, CGCI, ICGC and related initiatives. The overall goal is to identify synthetic gene combinations necessary for clinical resistance and related to inter- and intra-tumor heterogeneity. We will develop and apply methodologies for the identification of genes influencing heterotypic cell-cell interactions in tumors. Tumor evolution is a challenging area of research, largely due to the complexity of cell types and behaviors. In this aim, high-throughput screens will be performed to identify non-cell autonomous synthetic lethal and synthetic viable interactions relevant to tumor microenvironment interactions. These studies will include primary T-effector/cancer cell interactions to identify new therapeutic targets and cancer associated macrophage and fibroblast/cancer cell screens to identify genes mediating therapeutic resistance. These systems are made possible by using a currently unpublished screening platform that may help to identify genes important for cancer initiation, maintenance, and possibly metastasis. Since we will use primary and cancer tissue, our unique platform will recapitulate as much as possible the characteristics of tumors in patients and address an important challenge in cancer research. We have developed a novel means to establish genetic epistatic interactions in mammalian cells and will expand upon our efforts to generate specific libraries to map the subset of targets identified in the above screens. In this aim, we will address targets and mechanisms by delineating where targets act in the pathway by probing cancer-defining molecular interdependencies, using the novel targets and screening systems described above. The end goal is to uncover the optimal combination of perturbagens with the potential to eliminate all cancer cells, despite their clonal heterogeneity.

项目概要 我们的总体策略是利用我们在开发过程中开发的新颖工具和方法。 第一个 CTD^2 资助期 - 更具体地说，开拓和应用基于 CRISPR 的技术来帮助 使用创新的高通量发现和表征新的癌症靶点及其调节剂 我们的最终目标是发现具有潜力的扰动因素的最佳组合。 消除所有癌细胞，尽管它们具有克隆异质性和环境背景。 我们的目标之一是阐明新的分子靶标，以克服获得性耐药性。 令人兴奋的系统使我们能够定量数百个细胞的基因型和表型细胞异质性 我们提出了一系列治疗性小分子筛选来识别数千个单个癌细胞。 与耐药性和来自 TCGA、TARGET 的反复突变相关的驱动候选基因 CGCI、ICGC 和相关举措的总体目标是确定必要的合成基因组合。 临床耐药性与肿瘤间和肿瘤内的异质性有关。 我们将开发并应用方法来鉴定影响异型细胞的基因 肿瘤进化是一个具有挑战性的研究领域，很大程度上是由于细胞的复杂性。 为此，将进行高通量筛选来识别非细胞自主性。 与肿瘤微环境相互作用相关的合成致死和合成可行相互作用。 研究将包括初级 T 效应器/癌细胞相互作用，以确定新的治疗靶点和癌症 相关的巨噬细胞和成纤维细胞/癌细胞筛选，以确定介导治疗耐药性的基因。 这些系统是通过使用当前未发布的筛选平台而实现的，该平台可能有助于 确定癌症发生、维持和可能转移的重要基因，因为我们将使用原发基因。 和癌症组织，我们独特的平台将尽可能地重现肿瘤的特征 患者并解决癌症研究中的一个重要挑战。 我们开发了一种在哺乳动物细胞中建立遗传上位相互作用的新方法，并将 扩大我们的努力，生成特定的库来映射上述确定的目标子集 为了实现这一目标，我们将通过描述目标在路径中的作用位置来解决目标和机制。 通过探索癌症定义分子的相互依赖性，使用新的靶标和筛选系统 如上所述，最终的最佳目标是发现具有潜力的扰动因素的组合。 消除所有癌细胞，尽管它们具有克隆异质性。

项目成果

Drug-tolerant persister cancer cells are vulnerable to GPX4 inhibition.

耐药性持续癌细胞很容易受到 GPX4 抑制的影响。

• 发表时间: 2017
• 影响因子: 64.8
• 作者: Hangauer, Matthew J;Viswanathan, Vasanthi S;Ryan, Matthew J;Bole, Dhruv;Eaton, John K;Matov, Alexandre;Galeas, Jacqueline;Dhruv, Harshil D;Berens, Michael E;Schreiber, Stuart L;McCormick, Frank;McManus, Michael T
• 通讯作者: McManus, Michael T

Examining the evidence for extracellular RNA function in mammals.

检查哺乳动物细胞外 RNA 功能的证据。

• 发表时间: 2021
• 作者: Gruner, Hannah N;McManus, Michael T
• 通讯作者: McManus, Michael T

miR-200 deficiency promotes lung cancer metastasis by activating Notch signaling in cancer-associated fibroblasts.

miR-200 缺陷通过激活癌症相关成纤维细胞中的 Notch 信号传导促进肺癌转移。

• 发表时间: 2021
• 影响因子: 10.5
• 作者: Xue, Bin;Chuang, Chen;Prosser, Haydn M;Fuziwara, Cesar Seigi;Chan, Claudia;Sahasrabudhe, Neil;Kühn, Maximilian;Wu, Yalei;Chen, Jingqi;Biton, Anne;Chen, Caifu;Wilkinson, John Erby;McManus, Michael T;Bradley, Allan;Winslow, Monte M;Su, Bo
• 通讯作者: Su, Bo

A Single-Chain Photoswitchable CRISPR-Cas9 Architecture for Light-Inducible Gene Editing and Transcription.

用于光诱导基因编辑和转录的单链光开关 CRISPR-Cas9 架构。

• 发表时间: 2018
• 影响因子: 4
• 作者: Zhou, Xin X;Zou, Xinzhi;Chung, Hokyung K;Gao, Yuchen;Liu, Yanxia;Qi, Lei S;Lin, Michael Z
• 通讯作者: Lin, Michael Z

A Quantitative Chemotherapy Genetic Interaction Map Reveals Factors Associated with PARP Inhibitor Resistance.

定量化疗基因相互作用图揭示了与 PARP 抑制剂耐药性相关的因素。

• 发表时间: 2018-04-17
• 影响因子: 8.8
• 作者: Hu, Hsien;Zhao, Xin;Kaushik, Swati;Robillard, Lilliane;Barthelet, Antoine;Lin, Kevin K;Shah, Khyati N;Simmons, Andy D;Raponi, Mitch;Harding, Thomas C;Bandyopadhyay, Sourav
• 通讯作者: Bandyopadhyay, Sourav