Building a spatial transcriptomics infrastructure for isoform profiling in aging pre-neoplastic tissues

项目总结/摘要 衰老是癌症的最大危险因素，但尚不清楚哪些与年龄相关的细胞和分子事件 驱动癌症的发生空间转录组学方法正在彻底改变我们对癌症的理解 通过揭示组织形态学背景下的表达模式，研究其启动、进展和耐药性。 然而，这些方法尚未应用于衰老驱动的癌症的跨学科生物学， 尽管组织内和微环境进化可能介导衰老表型。此外，委员会认为， 目前的大多数单细胞空间项目是基于3 ′短读RNA测序（RNA-seq）， 因此缺乏检测全长剪接同种型的能力，这种同种型经常在肿瘤中观察到， 已知影响肿瘤起始和治疗反应。我们和其他人的工作显示， 在人类肿瘤中，包括乳腺癌中，选择性RNA剪接的改变， 使用长读序测序（LR-seq）在人乳腺肿瘤中检测到的同种型被RNA-seq遗漏， 不存在于参考转录组中。此外，我们已经因果关系地将特异性剪接的上调 在体外和体内研究中， 乳腺上皮细胞中癌症相关基因的同种型。总之，这些结果表明， 剪接是随着年龄增长而引发肿瘤的关键机制，空间LR-seq方法 需要解决这些机制。然而，衡量、量化、 和可视化的组织内全长同种型的表达是缺乏的。基础设施的这一差距阻碍了 领域的能力，以确定细胞群体表达年龄依赖性亚型，如何影响这些亚型癌症 例如通过受体-配体相互作用的变化而引发。为了解决这些基础设施和 知识的差距，我们将首先发展的方法，地图和分析全长RNA异构体空间 在组织切片内（R21相，Aim 1）。这些工具将LR-seq和空间转录组学融合在一起， 该方法适用于所有样本类型，因此将对研究界具有广泛的可持续效用。 然后，我们将应用这些技术来生成健康人中全长RNA异构体的空间图。 乳腺组织和肿瘤在老化过程中（R33阶段，目标2和3）。最后，我们将发展数据共享 以及用于空间异构体表达的可视化工具，以使其他人能够通过网络资源挖掘我们的数据 (R33阶段，目标4）。为了实现这些目标，该项目将利用互补和跨学科的 Anczukow实验室在选择性剪接和乳腺癌方面的专长，以及Chuang实验室在系统生物学方面的专长 和空间转录组学分析。为响应NOT-CA-22-002，NCI参加PAR-20的通知- 070，该项目将提供一个空间转录基础设施的异构体分析和一个关键的 跨学科的数据资源，供衰老和癌症研究人员了解剪接在组织衰老中的作用 和肿瘤发生，从而推进癌症早期检测、干预和预防的方法。

PROJECT SUMMARY/ABSTRACT Aging is the greatest risk factor for cancer, but it is not known which age-dependent cellular and molecular events drive cancer initiation. Spatial transcriptomic approaches are revolutionizing our understanding of cancer initiation, progression, and drug resistance by revealing expression patterns with tissue morphological context. However, these approaches have not yet been applied to the interdisciplinary biology of aging-driven cancers, despite the likelihood that intratissue and microenvironmental evolution mediate the aging phenotype. Moreover, the majority of current single cell spatial projects are based on 3' short read RNA-sequencing (RNA-seq) and therefore lack the ability to detect full-length spliced isoforms, which are frequently observed in tumors and are known to impact tumor initiation and treatment response. Work from us and others has revealed widespread alterations in alternative RNA splicing in human tumors, including in breast cancer, and that half of all spliced isoforms detected in human breast tumors using long-read sequencing (LR-seq) are missed by RNA-seq and absent from reference transcriptomes. In addition, we have causally linked the upregulation of specific splicing factors with breast tumor initiation both in vitro and in vivo and identified age-dependent changes in spliced isoforms in cancer-associated genes in mammary epithelial cells. Together, these results suggest that alternative splicing is a critical mechanism underlying tumor initiation with age, and that spatial LR-seq approaches are required to resolve these mechanisms. However, standardized approaches and resources to measure, quantify, and visualize expression of full-length isoforms within tissues are lacking. This gap in infrastructure impedes the field's ability to identify cell populations that express age-dependent isoforms, how such isoforms impact cancer initiation for example through changes in receptor-ligand interactions. To address these infrastructure and knowledge gaps, we will first develop approaches to map and analyze full-length RNA isoforms spatially within tissue sections (R21 phase, Aim 1). These tools, which merge LR-seq and spatial transcriptomics, will be applicable across sample types and will therefore be of broad, sustainable utility to the research community. We will then apply these technologies to generate a spatial map of full-length RNA isoforms in healthy breast tissues and tumors during aging (R33 phase, Aims 2 and 3). Finally, we will develop data sharing and visualization tools for spatial isoform expression to enable others to mine our data via a web resource (R33 phase, Aim 4). To achieve these goals, this project will leverage the complementary and interdisciplinary expertise of the Anczukow lab in alternative splicing and breast cancer, and of the Chuang lab in systems biology and spatial transcriptomics analysis. In response to NOT-CA-22-002, Notice of NCI's Participation in PAR-20- 070, this project will deliver a spatial transcriptomic infrastructure for isoform profiling and a critical interdisciplinary data resource for aging and cancer researchers to understand the role of splicing in tissue aging and oncogenesis, thereby advancing approaches for cancer early detection, intervention, and prevention.