A functional genomics approach to determine the mechanism of cellular response to new anti-cancer drugs

 描述（由申请人提供）：原理和背景：细胞毒性和靶向药物是癌症治疗的关键组成部分。对于某些癌症，如睾丸癌和某些血癌，化疗治愈了大多数患者。尽管这些选择的成功，内在和获得性耐药性仍然是一个主要的临床问题。由于基因组学革命，我们对癌症中常见的基因组改变的理解现在相当广泛。观察性癌症基因组学为初治和复发肿瘤开辟了一个潜在治疗靶点的世界。现在必须确定药物目标的优先次序，并查明和阻断耐药性的途径。基因组学识别癌症中的驱动突变，使我们能够创造新的靶向药物，尽管单一药物靶向治疗最终往往会失败，因为一部分肿瘤细胞会逃逸。此外，有许多对癌细胞存活和药物反应至关重要的基因从未发生突变。理解癌症治疗中的这种“非癌基因成瘾”是至关重要的。我们需要更好的方法来功能性地绘制癌细胞对抗癌药物的反应和耐药性，以开发阻止癌细胞逃避治疗的合理方法。在Weissman实验室，我创造了新的功能基因组学工具来探索癌症治疗中的药物反应。使用CRISPR效应蛋白Cas9（dCas 9）的核酸酶-酶解形式，我们可以将转录激活子（CRISPRa）或阻遏子（CRISPRi）结构域靶向特定的DNA序列，以稳健且特异性地控制由人类基因组编码的单个转录物的表达。我们已经生成了基因组规模的CRISPRi/a文库，并表明当组合CRISPRi/a筛选时，可以更完整地了解控制细胞生长，分化和对毒素的反应的过程。目的：我建议使用我们的CRISPRi/a功能基因组平台来研究癌症治疗中的药物反应。为了完善我们的功能基因组工具集，我还提议开发一个CRISPRi/一个遗传相互作用（GI）作图平台。GI图谱是鉴定合成-致死基因对的有力方法，这些基因对是癌症治疗中的理想药物靶点。我建议进行一段时间的指导培训，以应用我们新的CRISPR功能基因组学平台来确定细胞对新型抗癌药物的反应机制，并学习如何构建和分析GI图谱。我的主要导师，乔纳森·韦斯曼，是遗传相互作用图谱的世界级专家，他的实验室是我学习技术和分析技能的完美场所，我需要成功地实现这一目标。我选择使用CRISPRi/a来表征HSP 70抑制剂和K-Ras（G12 C）抑制剂，这两种新的令人兴奋的抗癌药物是由我的共同导师Jason Gestwicki和Kevan Shokat创造的。我在加州大学旧金山分校的一个社区工作，在研究蛋白质伴侣和Ras方面有着深厚而成功的历史。我的共同导师都是抗癌药物设计原理的化学家，他们对我进行了一段时间的培训，这将使我能够使用我们的CRISPR功能基因组学平台作为研究抗癌药物的工具。这项工作将作为使用CRISPRi/a研究癌症中癌基因（Ras）和非癌基因（蛋白质伴侣）成瘾的通用模板。为了实现这些目标，我提出了以下具体目标：（1）确定细胞对HSP 70伴侣抑制剂的反应机制（2）确定细胞对K-Ras（G12 C）抑制剂的反应机制（3）实现CRISPRi/a遗传相互作用（GI）作图平台。在追求这些目标的过程中，我将获得知识基础，分析技能和独特的视角，以开始我作为癌症生物学家的独立研究生涯。

 DESCRIPTION (provided by applicant): Rationale and Background: Cytotoxic and targeted agents are a critical component of cancer therapy. For some cancers, such as testicular cancer and certain blood cancers, chemotherapy cures most patients. Despite these select successes, intrinsic and acquired drug resistance remains a major clinical problem. Due to the genomics revolution, our understanding of the common genomic alterations in cancer is now quite extensive. Observational cancer genomics has opened up a world of potential therapeutic targets in naïve and relapsed tumors. There is now an imperative to prioritize drug targets and to map and block routes of drug resistance. Genomics identifies driver mutations in cancer enabling us to create new-targeted drugs, although single agent targeted therapies frequently eventually fail because a subset of tumor cells escape. Additionally, there are many genes critical for cancer cell survival and drug response that are never mutated. Understanding such "non-oncogene addictions" in cancer therapy is critical. We need better ways of functionally mapping out cancer cell response and resistance to anti-cancer drugs in order to develop rational ways of blocking cancer cell escape from therapy. In the Weissman lab, I have created new functional genomics tools to explore drug response in cancer therapy. Using a nuclease-inactivate form of the CRISPR effector protein Cas9 (dCas9), we can target transcription activator (CRISPRa) or repressor (CRISPRi) domains to specific DNA sequences to robustly and specifically control expression of individual transcripts encoded by the human genome. We have generated genome-scale CRISPRi/a libraries and shown that when combined CRISPRi/a screens yield a more complete view of processes controlling cell growth, differentiation, and response to toxins. Objective: I am proposing to use our CRISPRi/a functional genomic platform to study drug response in cancer therapy. To complete our functional genomic toolset, I am also proposing to develop a CRISPRi/a genetic-interaction (GI) mapping platform. GI maps are a powerful method of identifying synthetic-lethal gene pairs, which are ideal drug targets in cancer therapy. I propose a period of mentored training to apply our new CRISPR functional genomics platform to determine mechanisms of cellular response to new classes of anti-cancer drugs and crucially to learn how to construct and analyze a GI map. My primary mentor, Jonathan Weissman, is a world expert in genetic- interaction mapping and his lab is the perfect place for me to learn the technical and analytical skills I need to be successful in this aim. I have chosen to use CRISPRi/a to characterize HSP70 inhibitors and K-Ras(G12C) inhibitors, two new exciting classes of anti-cancer drugs that were created by my co-mentors Jason Gestwicki and Kevan Shokat. I am embedded in a community at UCSF with a deep and successful history of studying protein chaperones and Ras. A period of training by my co-mentors who are both chemists in principles of anti-cancer drug design will uniquely enable me to use our CRISPR functional genomics platform as a tool for studying anti-cancer drugs. This work will serve as a general template for using CRISPRi/a to study oncogene (Ras) and non- oncogene (protein chaperones) addictions in cancer. To achieve these goals, I propose the following specific aims: (1) Determine the mechanism of cellular responses to HSP70 chaperone inhibitors (2) Determine the mechanism of cellular response to K-Ras(G12C) inhibitors (3) Implement a CRISPRi/a genetic-interaction (GI) mapping platform. In pursuit of these aims, I will acquire the knowledge base, analytical skills and unique perspective to launch my independent research career as a cancer biologist.