Deciphering heritability, plasticity and differentiation trajectories in gliomas via single-cell multi-omics

摘要 癌症的进化构成了有效治疗的首要障碍，促使恶性细胞适应 并战胜心理治疗。弥漫性胶质瘤说明了癌症进化的困境：尽管 治疗后，该病总会复发。最近的单细胞RNA测序(ScRNAseq)分析 SUVà实验室中的胶质瘤表明，定义了细胞状态、发育等级和 可塑性促进了胶质瘤的生长、进化和对治疗的抵抗。然而，这提高了 胶质瘤细胞状态决定因素的关键问题。我们假设遗传、表观遗传 微环境决定因素支配着驱动细胞关键状态的生物学 胶质瘤及其可塑性，呼吁建立一个癌症进化的综合模型，包括 所有肿瘤内可遗传变异的来源。为了应对这一挑战，兰道实验室 开发了新的多模式单细胞测序技术，使直接整合成为可能 跨越细胞间变异的遗传、表观遗传和转录维度，并已应用于 以研究血液系统恶性肿瘤的克隆进化。在这笔R01联合PI合作赠款中，我们 寻求将这种多层单细胞方法应用于人类胶质瘤，以确定细胞 表型可塑性和克隆进化使肿瘤细胞适应。具体地说，我们将：定义内部 和胶质瘤细胞状态的外在决定因素(AIM1)，映射了 胶质瘤细胞状态程序(AIM2)，并重建胶质瘤的高分辨率谱系历史 单细胞用于测量细胞状态的遗传性和可塑性(Aim3)。总而言之，这项研究 Proposal寻求开创表观遗传同一性与遗传和转录的综合分析 系统剖析胶质瘤分化和分化的细胞状态驱动因素的信息 进化论。

Abstract Cancer evolution constitutes a foremost obstacle to effective treatment, driving malignant cells to adapt and overcome therapy. Diffuse glioma illustrates the quandary of cancer evolution: despite maximal treatment, the disease invariably recurs. Recent single-cell RNA-sequencing (scRNAseq) profiling of gliomas in the Suvà laboratory showed that defined cellular states, developmental hierarchies and plasticity coordinate to fuel glioma growth, evolution and resistance to therapy. However, this raises the critical question of the determinants of glioma cell states. We hypothesize that genetic, epigenetic and micro-environmental determinants govern the biology of key cellular states that drive gliomas and their plasticity, calling for an integrative model of cancer evolution, encompassing all sources of intra-tumoral heritable variations. To address this challenge, the Landau laboratory developed novel multi-modality single-cell sequencing technologies that enable direct integration across genetic, epigenetic, and transcriptional dimensions of cell-to-cell variation, and have applied them to study clonal evolution in hematological malignancies. In this R01 co-PI collaborative grant, we seek to apply this multi-layered single-cell approach to human gliomas in order to define how cellular phenotypic plasticity and clonal evolution enable tumor cell fitness. Specifically, we will: define intrinsic and extrinsic determinants of cellular states in glioma (aim1), map the epigenetic encoding of cell state programs in glioma (aim2), and reconstruct high-resolution lineage histories of glioma single-cells to measure the heritability and plasticity of cell states (aim3). Altogether, this research proposal seeks to pioneer the integrative analysis of epigenetic identity with genetic and transcriptional information to systematically dissect drivers of cellular states that underlie glioma differentiation and evolution.