Genomic dissection of tumor heterogeneity and progression

该项目的第一个目标是使用单细胞测序来了解儿童实体肿瘤中存在的细胞类型和细胞间异质性的复杂性。在这项工作中，我们专注于生成NF1患者肿瘤中存在的细胞的全面基因表达谱。迄今为止，我们收集并分析了丛状神经纤维瘤（PN）、非典型神经纤维瘤（AN）和恶性周围神经鞘肿瘤（MPNST）的手术标本。在过去的一年里，我们对来自12例NF1神经肿瘤患者的350,000个单细胞进行了高基因覆盖率测序，包括组织学验证的PN， ANF和MPNST。我们迄今为止生成的最大数据集包括PN和ANF的单细胞测序。从这些实验中，我们捕捉到这些肿瘤内细胞异质性的景观。在PNs中，我们已经确定了至少21种独特的细胞群，包括各种基质细胞和免疫细胞类型。这个丰富的数据集详细介绍了这些群体的转录谱，并突出了已知和新的细胞类型。按照相同的程序，我们从3个MPNST肿瘤和10个PDX MPNST模型的300,000个细胞中生成了scRNAseq数据。该项目的重要发现是组成肿瘤簇的多个转录不同的细胞簇以及大量免疫抑制巨噬细胞。目前，我们正在使用这个数据集来描述这些肿瘤中大量的细胞间相互作用，以剖析潜在的肿瘤特异性脆弱性。鉴于很难从实体瘤患者获得多个连续活检标本，在过去的一年里，我们开展了一个项目，测定细胞游离DNA，以评估NF1患者的疾病状态。在这项工作中，我们开发了一种将低通全基因组测序与选定基因的NF1特异性靶向捕获深度测序相结合的检测方法。目前，我们正在使用积极招募的临床试验SARC031 （NCT03433183）“MEK抑制剂Selumetinib （AZD6244）与mTOR抑制剂西罗莫司联合治疗MPNST患者”收集的样本评估我们的检测值。将循环肿瘤DNA中观察到的变化与再分期成像中观察到的变化联系起来的初步研究正在进行中。后续研究将循环肿瘤DNA与治疗中肿瘤活检配对，观察循环肿瘤DNA整体基因组变化的相关性和描述，以发现肿瘤进化的机制。这项工作的第二个目标是开发与单细胞测序相结合的新型条形码策略，可用于临床前模型系统，以模拟肿瘤细胞的耐药性和存活。单细胞测序有能力同时剖析数千个细胞的基因表达谱，但在选择性压力下追踪细胞群体的能力有限。在今年，我们完成了试点实验，突出了在我们的实验系统中添加一个功能的必要性，该功能可以随着时间的推移跟踪特定的细胞并进行复制。为了做到这一点，我们将一个独特的序列“DNA条形码”整合到细胞池中的每个细胞中（在10个单独的池中有超过1000万个独特的条形码）。重要的是，我们的载体产生一个聚腺苷化表达基因，与单细胞RNA测序方法捕获兼容。已经完成的实验表明，随着时间的推移和细胞群的扩增，我们能够在scRNAseq数据中检测到表达的DNA条形码。目前的实验采用单细胞条形码策略来了解异质肿瘤细胞对拓扑异构酶抑制剂和小分子靶向表观遗传修饰剂的反应。我们预计，这将使个体存活细胞的表达谱的识别和新的治疗靶点的定义。

The first aim of this project is to use single cell sequencing to understand the complexities of cell types and cell to cell heterogeneity that is present within pediatric solid tumors. In this work, we are focusing on generating comprehensive gene expression profiling of the cells present within tumors that occur in patients with NF1. To date we have collected and analyzed surgical specimens from Plexiform Neurofibromas (PN), Atypical Neurofibromas (AN) and Malignant Peripheral Nerve Sheath Tumors (MPNST). Over the past year, we have generated high gene coverage sequencing on 350,000 single cells from 12 patients with NF1 nerve tumors including histologically validated PN, ANF and MPNST. Our largest dataset generated to date includes single-cell sequencing of PN and ANF. From these experiments, we capture the landscape of cellular heterogeneity within these tumors. Within PNs we have identified at least 21 unique cell populations including a variety of stromal and immune cell types. This rich dataset details the transcriptional profile of each of these populations and highlights both known and novel cell types. Following the same procedure, we have generated scRNAseq data from 300,000 cells from three MPNST tumors and 10 PDX MPNST models. Important findings from this project are multiple clusters of transcriptionally distinct cells that compose the tumor cluster as well as a large population of immune suppressive macrophages. Currently, we are using this dataset to describe the multitude of cell to cell interactions within these tumors to dissect potential tumor specific vulnerabilities. Given the difficulty in obtaining multiple sequential biopsy specimens from patients with solid tumors, in the past year we have undertaken a project to assay cell free DNA to assess disease status in NF1 patients. In this work we have developed an assay that marries low pass whole genome sequencing with NF1 specific targeted capture deep sequencing of selected genes. Currently we are evaluating our assays value using samples collected on the actively enrolling clinical trial SARC031 (NCT03433183) "MEK Inhibitor Selumetinib (AZD6244) in Combination with the mTOR Inhibitor Sirolimus for Patients With MPNST". Initial studies correlating the changes observed in the circulating tumor DNA with the changes observed on re-staging imaging are underway. Secondary efforts will pair the circulating tumor DNA with an on-treatment tumor biopsy to observe correlation and description of the global genomic changes in the circulating tumor DNA to discover mechanisms of tumor evolution. The second aim of this work is to develop novel barcoding strategies married with single cell sequencing that can be used in preclinical model systems to model tumor cell resistance and survival. Single cell sequencing has the ability to dissect the gene expression profile of thousands of cells in parallel but is limited in its ability to track populations of cells under a selective pressure. Within the current year we completed pilot experiments that highlighted the need to add a feature to our experimental system which enabled tracking a particular cell over time and as it replicated. To accomplish this, we have incorporated a unique sequence "DNA barcode" into each cell within a pool of cells (greater than 10 million unique barcodes in 10 separate pools). Importantly, our vector generates a polyadenylated expressed gene that is compatible with capture using single cell RNA sequencing methods. Experiments have been completed which demonstrated that we are able to detect the expressed DNA barcodes within the scRNAseq data over time and with cell population expansion. Current experiments are employing the single cell barcoding strategy to understand the heterogenous tumor cell responses to topoisomerase inhibitors and small molecules targeting epigenetic modifiers. We anticipate that this will enable discernment of the expression profiles of individual surviving cells and definition of new therapeutic targets.