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

癌症靶点分为两大类：由于其直接作用而引起肿瘤本质的癌蛋白， 肿瘤发生或肿瘤维持（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（非癌基因依赖性）。不幸的是，克隆 选择和固有的癌细胞可塑性-以及癌细胞进行适应和 在治疗后重新编程为耐药状态，目前正在挑战 单个蛋白质作为整个肿瘤块的有效治疗靶点-特别是如果从 大量组织分析。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，基于无进展生存期，通常没有实质性的总生存期差异; 尽管免疫疗法很有前途，但它也存在选择性反应和复发的问题。为了应对这些挑战，我们 一项提案将研究一个更普遍的类突变不可知，非癌基因的依赖性实现 由我们称为肿瘤检查点（TC）的主调节器（MR）蛋白质紧密自动调节 模块。我们已经表明，MR蛋白机械地实现肿瘤细胞的转录状态， 在其上游通路中疏导突变和异常信号的影响。因此，在这方面， 在转录上不同的肿瘤亚型中，它们在很大程度上代表了突变不可知的依赖性。我们 因此，该提案将侧重于MR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内。这将导致设计 成功的联合治疗方法，并将有助于阐明和验证目标机制 抗药性和细胞适应性的过程。为了实现这些目标，我们将扩大一个非常成功的网络- 由我们的CTD 2中心开发的基于框架，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，这种新的基因或药理学靶向 一类肿瘤依赖性可以诱导TC-模块活性的崩溃，并诱导肿瘤活力的丧失， 广泛的恶性肿瘤，从胶质母细胞瘤、神经母细胞瘤和神经内分泌肿瘤到前列腺 和乳腺癌等。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，每一种都由不同的亚型特异性TC模块调节， 与患者特异性突变无关。这些方法尤其适用于罕见的、侵袭性的、 肿瘤-包括几种儿科恶性肿瘤-队列规模可能太小，无法支持相关性 分析。重要的是，这些研究导致了两个纽约/加州Dpt的发展。卫生部批准，CLIA- 符合标准的测试，OncoTarget和OncoTreat，其预测已经刺激了几项临床试验。这些 方法将扩展到阐明TC-模块依赖性和开发药物敏感性生物标志物 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.