Clinical implementations of spatial transcriptomics in tumors

摘要 肿瘤存在于一个复杂的多细胞生态系统中，包括恶性和非恶性肿瘤。 恶性细胞，其中相互作用的细胞和分子在空间和时间上组织起来。的 这些细胞的多样性及其相互作用影响癌症进展和药物反应， 耐药性，并为更精确的诊断和治疗提供了机会。在这 建议，我们将开发Slide-seq，一种新的空间转录组学方法，成为一种高水平的 高分辨率空间基因组学平台，通过一套强大的 协议、管道和计算算法。我们的工具将允许病理学家 使用标准设备在临床上对广泛的肿瘤标本进行Slide-seq， 最低限度的训练。我们新颖的计算管道将允许无缝集成， 肿瘤的分子、细胞和组织学理解： 在复杂的肿瘤环境中定位细胞类型， 由病理学驱动的基因表达模式，以及细胞小生境的组织。 应用这些方法将彻底改变我们发现肿瘤空间变化的能力， 在疾病进展和治疗过程中的分子组织，提供新的生物标志物， 诊断学和药理学，并强调新的治疗途径。

Abstract Tumors reside within a complex multicellular ecosystem comprised of malignant and non- malignant cells, where interacting cells and molecules are organized in space and time. The diversity of these cells and their interactions affect cancer progression and drug response and resistance, and present opportunities for more precise diagnostics and therapeutics. In this proposal, we will develop Slide-seq, a novel spatial transcriptomic method, into a high- resolution spatial genomics platform for cancer precision medicine through a set of robust protocols, pipelines and computational algorithms. Our tools will allow pathologists to apply Slide-seq on a broad range of tumor specimens in the clinic with standard equipment and minimal training. Our novel computational pipelines will allow the seamless integration of molecular, cellular and histological understanding in tumors: they will enable the spatial localization of cell types within complex tumor environments, the identification of spatially varying gene expression patterns driven by pathology, as well as the organization of cellular niches. Applying these approaches will revolutionize our ability to discover changes in tumor spatial and molecular organization during disease progression and treatment, provide new biomarkers for diagnostics and prognostics, and highlight new therapeutic avenues.