Abstract A087: Spatial RNA-seq reveals intratumor heterogeneity and transcriptional substructure in a diverse cohort of high-grade ovarian cancers
Authors: Gibbs Lee D. , Williams Stephen R. , Weisenfeld Neil I. , Bassiouni Rania , Delaney Nigel F. , Da Silva Diane , Yin Yifeng , Rotimi Solomon , Chew Jennifer , Frey Meghan , Qian Jing , Miller Heather , Murderspach Laila , McEachron Troy , Craig David , Roman Lynda WOptional , Carpten John D. 
Published: September 2020

Abstract
Introduction: Differences in tumor heterogeneity, particularly the tumor microenvironment have not yet been explored as potential molecular features underlying cancer disparities. Molecular profiling of bulk tissue specimens using methods such as whole-transcriptome sequencing are limited in their ability to resolve fine grain molecular signatures and hinder our utility to dissect underlying biology of individual tumors. Although informatics approaches are available that attempt to disentangle tissue heterogeneity from bulk tumor data, emerging spatial whole transcriptome sequencing technologies allows a more precise delineation of cellular and molecular substructure in a comprehensive unbiased way. Here we present an investigation whole-transcriptome spatial sequencing in a diverse cohort of ovarian cancer cases. Methods: Three serial 5-micron frozen sections were placed on proprietary 10x Genomics Spatial Transcriptomics (ST) slides and processed using manufacturer specifications. Libraries were sequenced on the Illumina NovaSeq 6000 system and data was processed using the 10X Genomics analytical tools. ST data from each section was analyzed to create spatially defined cellular clusters at 100-micron resolution. Results: ST revealed cellular heterogeneity across the entirety of the tumor microenvironment in an anatomically resolved manner. Bioinformatic tools and molecular pathways to infer tumor purity were used to annotate tumor, immune, and stromal substructures. These data also revealed clear transcriptional substructure in some tumors, where different tumor regions were defined by unique gene sets associated with different molecular processes known to be related to tumorigenesis. Further, we observed clear transcriptional substructure in some tumors, where different tumor regions were enriched with molecular pathways that are associated with tumorigenesis (i.e., DNA Damage Response, and Protein Translation pathways), regions defined by immune infiltration (i.e. CD8+ T cells, T regulatory cells, Macrophages, and B cells), and molecular pathways that are associated with inflammatory signalling (i.e. complement, IL2, IL-10, and IL6 signaling pathways). Conclusion: These approaches highlight the power of spatial whole-transcriptomic approaches in solid tumor studies to help unravel the complexity of heterogeneous cancers and provide a comprehensive characterization of transcriptional substructure within a single tissue section.
Citation Format: Lee D. Gibbs, Stephen R. Williams, Neil I. Weisenfeld, Rania Bassiouni, Nigel F. Delaney, Diane Da Silva, Yifeng Yin, Solomon Rotimi, Jennifer Chew, Meghan Frey, Jing Qian, Heather Miller, Laila Murderspach, Troy McEachron, David Craig, Lynda WOptional Roman, John D. Carpten. Spatial RNA-seq reveals intratumor heterogeneity and transcriptional substructure in a diverse cohort of high-grade ovarian cancers [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr A087.