Elucidating and Targeting tumor dependencies and drug resistance determinants at the single cell level

癌症靶点分为两大类：癌蛋白，由于其在肿瘤中的直接作用而诱导肿瘤的必要性 肿瘤形成或肿瘤维持(癌基因依赖性)和引起合成致死性的蛋白质 癌基因突变，但本身不突变(非癌基因依赖)。不幸的是，克隆人 选择和固有的癌细胞可塑性-以及癌细胞经历适应和 在治疗后重新编程到耐药状态-目前正在挑战 单个蛋白质作为整个肿瘤的有效治疗靶点--特别是如果从 大块组织分析。事实上，尽管取得了一些成功，但只有5%-11%的癌症患者受益于 靶向治疗，基于无进展的生存，通常没有实质性的总体生存差异； 免疫疗法前景看好，但也会出现选择性反应和复发。为了应对这些挑战，我们的 提案将研究一类更普遍的实现的突变不可知性、非癌基因依赖 通过严格自动调节的一组主调节蛋白(MR)，我们称之为肿瘤检查点(TC) 模块。我们已经证明，MR蛋白通过以下方式机械地实现肿瘤细胞的转录状态 引导突变和异常信号在其上游通路中的作用。因此，在上下文中 作为一种转录上不同的肿瘤亚型，它们在很大程度上代表着突变不可知的依赖关系。我们的 因此，提案将集中于MRS和TC-模块的阐明和药理学靶向 单细胞水平，在分子上不同但共存的肿瘤亚群中。这将导致设计 成功的联合治疗方法，并将有助于阐明和药理靶向机制 耐药和细胞适应的问题。为了实现这些目标，我们将扩展一个非常成功的网络- 基于我们的CTD2中心开发的框架，用于阐明、验证和药理学靶向 MR蛋白质和TC模块。事实上，我们已经证明了这种新的基因或药物靶向 一类肿瘤依赖可导致TC模块活性崩溃并导致肿瘤活力丧失 多种恶性肿瘤，从胶质母细胞瘤、神经母细胞瘤、神经内分泌肿瘤到前列腺癌 和乳房腺癌，以及其他许多疾病。特别是，对25个TCGA队列的分析确定了112个 转录上不同的肿瘤亚型，每一种都受不同亚型特异的TC模块调控，该模块 不受患者特定突变的影响。这些方法尤其适用于罕见的、具有侵略性的 肿瘤--包括几种儿科恶性肿瘤--队列大小可能太小，不能支持相关研究 分析。关键的是，这些研究已经导致了两个NY/CA Dpt的发展。卫生部批准，CLIA- 符合测试，OncoTarget和OncoTreat，他们的预测已经刺激了几个临床试验。这些 将扩展方法以阐明TC模块依赖关系并开发药物敏感性生物标记物 在单细胞水平上。

Cancer targets fall into two major categories: oncoproteins that elicit tumor essentiality due to their direct role in tumorigenesis or tumor maintenance (oncogene dependencies) and proteins that elicit synthetic lethality with oncogene mutations but are not themselves mutated (non-oncogene dependencies). Unfortunately, clonal selection and inherent cancer cell plasticity—as well as the ability of cancer cells to undergo adaptation and reprogramming to drug resistant states, following treatment—are currently challenging the concept of individual proteins as effective therapeutic targets for an entire tumor mass—especially if identified from bulk tissue analyses. Indeed, despite several successes, only 5% – 11% of cancer patients benefit from targeted therapy, based on progression free survival, often with no substantial overall survival differences; while promising, immune therapy is also subject to selective response and relapse. To address these challenges, our proposal will study a more universal class of mutation-agnostic, non-oncogene dependencies implemented by tightly-autoregulated sets of Master Regulator (MR) proteins that we have called Tumor Checkpoint (TC) modules. We have shown that MR proteins mechanistically implement a tumor cell’s transcriptional state by canalizing the effect of mutations and aberrant signals in their upstream pathways. As such, within the context of a transcriptionally-distinct tumor subtype, they represent largely mutation-agnostic dependencies. Our proposal will thus focus on the elucidation and pharmacological targeting of MRs and TC-modules at the single cell level, within molecularly distinct, yet co-existing tumor subpopulations. This will lead to design of successful combination therapy approaches and will help elucidate and pharmacologically target mechanisms of drug resistance and cell adaptation. To accomplish these goals, we will extend a highly successful, network- based framework developed by our CTD2 Center, for the elucidation, validation, and pharmacological targeting of MR proteins and TC-modules. Indeed, we have shown that genetic or pharmacological targeting of this new class of tumor dependencies can induce collapse of TC-module activity and induce loss of tumor viability in a wide range of malignancies, ranging from glioblastoma, neuroblastoma, and neuroendocrine tumors, to prostate and breast adenocarcinoma, among many others. In particular, analysis of 25 TCGA cohorts has identified 112 transcriptionally distinct tumor subtypes, each one regulated by a distinct subtype-specific TC-module, which was independent of patient-specific mutations. These methodologies are especially relevant in rare, aggressive tumors—including several pediatric malignancies—where cohort size may be too small to support correlative analyses. Critically, these studies have led to the development of two NY/CA Dpt. of Health approved, CLIA- compliant tests, OncoTarget and OncoTreat, whose predictions have spurred several clinical trials. These approaches will be extended to elucidate TC-module dependencies and to develop drug sensitivity biomarkers at the single cell level.