Targeting cell regulatory states to complement MEK/autophagy inhibition in pancreatic cancer

摘要 胰腺导管腺癌(PDAC)的特点是对基因毒性具有广泛的、原发的耐药性。 化疗、靶向治疗和免疫治疗。PDAC的唯一致癌基因是KRAS，它 在95%的病例中发生了突变。不幸的是，在PDAC中发现的特定突变KRAS等位基因的抑制剂是 目前还不能用于临床，所有针对下游效应器通路的尝试都受到了 反馈环和其他阻力机制。 我们的合作者的工作发现，抑制MEK通路，一个关键的KRAS效应器，会导致 自噬的代偿性上调，这是一种生存途径。联合应用MEK和自噬抑制 在模型中显示在降低PDAC细胞系的活力和导致肿瘤反应方面具有协同作用 来自人类患者的系统和个人病例报告。然而，只有一小部分患者有反应 对早期临床试验中的MEK/自噬抑制剂。在有反应的人中，大多数肿瘤在一年内进展 几个月了。然而，这可能是第一个没有遗传毒性药物的有效方案的例子。 已发表的在PDAC中MEK和自噬抑制剂之间协同作用的机制并不容易 解释耐药性迅速出现的原因，不能解释恶性细胞内的异质性 上皮室，并且没有解决肿瘤间质在治疗反应中的作用。这个 该提案的总体目标是采用整体方法来了解细胞对MEK/自噬的反应 通过研究治疗对肿瘤中每种细胞类型的影响来抑制。我们将通过表演来实现这一点 单细胞RNA测序和数据分析使用单细胞调控网络分析-AN 先进的计算框架，旨在系统地测量每个转录的活动 每个单独的单元格中的因素。这一创新的新方法使我们能够识别特定的细胞 研究治疗影响的亚型，并快速确定观察到反应的机制驱动因素。我们会 将这种方法应用于来自四个不同模型系统的肿瘤样本：基因工程(KPC)小鼠， 人患者来源的异种移植(PDX)、患者来源的肿瘤“外植体”模型(新鲜培养的完整组织 切片)，以及在PDAC患者中抑制MEK/自噬的积极临床试验的样本。 在人类细胞系、人PDAC外植体和KPC小鼠肿瘤中的大量初步数据 证明抑制MEK/自噬主要影响三种主要细胞类型的特定亚群： 上皮细胞、成纤维细胞和巨噬细胞/单核细胞。我们的三个目标将研究其影响和机制 MEK/自噬抑制在每种细胞类型中的作用，目的是注释表型，了解是否 影响是细胞自主的，决定了驱动治疗反应的转录因子，了解 对剩余细胞的影响，并确定新的治疗组合以增强抗癌效果。

Abstract Pancreatic ductal adenocarcinoma (PDAC) is characterized by its broad, primary resistance to genotoxic chemotherapy, targeted therapy, and immunotherapy. The singular driving oncogene of PDAC is KRAS, which is mutated in 95% of cases. Unfortunately, inhibitors of the specific mutant KRAS alleles found in PDAC are not yet clinically available, and all attempts to target downstream effector pathways have been stymied by feedback loops and other resistance mechanisms. Work from our collaborators found that inhibition of the MEK pathway, a key KRAS effector, results in compensatory upregulation of autophagy, a survival pathway. Combination MEK and autophagy inhibition was shown to have synergistic effects in reducing viability of PDAC cell lines and led to tumor responses in model systems and individual case reports from human patients. However, only a subset of patients have responded to MEK/autophagy inhibitors in early clinical trials. Among those who respond, most tumors progress within a few months. Nevertheless, this is potentially the first example of an active regimen lacking genotoxic agents. Published mechanisms for the synergy between MEK and autophagy inhibitors in PDAC do not readily explain the rapid emergence of resistance, do not account for cellular heterogeneity within the malignant epithelial compartment, and do not address the role of the tumor stroma in the response to therapy. The overall goal of this proposal is take a holistic approach to understanding cellular responses to MEK/autophagy inhibition by studying the effects of treatment on every cell type in the tumor. We will do this by performing single cell RNA sequencing and analyzing the data using single cell regulatory network analysis – an advanced computational framework designed to systematically measure the activity of every transcription factor in each individual cell. This innovative new approach enables us both to identify specific cellular subtypes impacted by treatment, and to rapidly identify the mechanistic drivers of observed responses. We will deploy this approach on tumor samples from four different model systems: genetically engineered (KPC) mice, human patient derived xenografts (PDXs), patient-derived tumor “explant” models (freshly cultured intact tissue slices), and samples from an active clinical trial of MEK/autophagy inhibition in PDAC patients. Extensive preliminary data in human cell lines, human PDAC explants, and KPC mouse tumors demonstrate that MEK/autophagy inhibition primarily impacts specific subsets of three major cell types: epithelial cells, fibroblasts, and macrophage/monocytes. Our three aims will study the effects and mechanisms of MEK/autophagy inhibition in each cell type, with the goals of annotating phenotypes, learning whether effects are cell autonomous, determining the transcription factors driving treatment response, understanding impacts on the remaining cells, and identifying new therapeutic combinations to potentiate anticancer effects.