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