Abstract PD5-08: The human tumor atlas network (HTAN) breast pre cancer atlas: A multi-omic integrative analysis of ductal carcinoma in situ (DCIS) and correlation with clinical outcomes
Authors: Shelley Hwang, Siri H Strand, Belen Rivero, Lorraine King, Tyler Risom, Bryan Harmon, Fergus Couch, Kristalyn Gallagher, Mark Kilgore, Shi Wei, Angela DeMichele, Tari King, Priscilla McAuliffe, Julie Nangia, Ana Maria Storniolo, Alastair Thompson, Gaorav Gupta, Joanna Lee, Jennifer Tseng, Robyn Burns, ChunFang Zhu, Magda Matusiak, Shirley X Zhu, Jason Wang, Jose Seoane, Jen Tappenden, Daisy Ding, Dadong Zhang, Jingqin Luo, Sujay Vennam, Sushama Varma, Lunden Simpson, Luis Cisneros, Timmothy Hardman, Lauren Anderson, Cody Straub, Sucheta Srivastava, Deb J Veis, Christina Curtis, Rob Tibshirani, Robert Michael Angelo, Allison Hall, Kouros Owzar, Kornelia Polyak, Carlo Maley, Jeff Marks, Graham Colditz, Robert B West
Journal: Cancer Research (2021)

Abstract Introduction. As nonobligate precursors of invasive disease, pre-cancers provide a unique vantage point from which to study the molecular pathways and evolutionary dynamics that lead to the development of life-threatening cancers. Ductal carcinoma in situ (DCIS) is the most commonly diagnosed precursor of breast cancer, with variable propensity for invasive progression. In order to address the problems of over- and under-treatment, we performed a multimodal, integrated profile of DCIS with clinical outcomes with which to develop and validate predictors of invasive progression. Methods. We present observations on DNA, RNA, and protein expression on two independent patient cohorts of DCIS, diagnosed from 1981 to 2014, from the Translational Breast Cancer Research Consortium (TBCRC 038) and the Washington University Repository of Archival Human Breast Tissue (RAHBT). Patients initially diagnosed with DCIS, with either DCIS or invasive recurrence (cases; mean follow up 5.8 years) were matched to those without recurrence (controls; mean follow up 10.3 years), based upon age at diagnosis and year of diagnosis. Results. We present genomic and cellular changes that correlate with both disease states and patient outcomes in DCIS. DCIS can be clustered by classification systems developed for IBC. Specific immune cell types and pathways correlate with longitudinal outcome. Luminal cell adhesion and metabolism pathways are upregulated in controls and cases, respectively. Highly multiplexed ion beam imaging (MIBI) was used to validate RNA seq findings, and to provide single cell-level spatial context for molecular alterations.Conclusion. We have performed an integrated multi-omic analysis of DCIS and associated tumor micorenvironment. Our multi-scale approach employs in situ methods to generate a spatially resolved atlas of breast precancers where different modalities can be directly compared to each other, and correlated with conventional pathology findings and clinical outcome. The PreCancer Atlas represents a complex multi-modal database for DCIS study, whose design allows for future discovery and hypothesis generation. Table 1. Breast Pre-cancer Atlas Multi-scale Characterization AssaysAssayScaleType of DataIntegration and validation with other assaysRNA-seq (Single duct, single cell, TME)Cell, duct, organ, normal tissue1. Whole transcriptome gene expression profiling per single duct (also enabling CNV and cell type prediction)2. Whole transcriptome gene expression profiling per single duct1. Prediction of CNV confirmed by DNA-seq (single duct) and FISH (single cell)2. Prediction of cell type composition (Cibersort) confirmed by multiplex IHC and multicolor flow cytometryLow-pass whole genome DNA-seqDuct and adjacent normalCNV profiling per single ductAnalysis of CNV supported by RNA-seq (single duct) and MIBI (single cell)Whole genome sequencingDuct and adjacent normalMutation status per single ductMutational analysis confirmed by RNA-seqMultiplex IHC (MIBI &amp; Cyclic multicolor)Cell1. Cell type2. Proteomic analysisAnalysis of cell type supported by RNA-seq of ducts (Cibersort) and single cellsH&amp;E MorphometricsCell, duct, organSpatial location of cell types, organization of ductsAnalysis of H&amp;E images correlated with FISH data Citation Format: Shelley Hwang, Siri H Strand, Belen Rivero, Lorraine King, Tyler Risom, Bryan Harmon, Fergus Couch, Kristalyn Gallagher, Mark Kilgore, Shi Wei, Angela DeMichele, Tari King, Priscilla McAuliffe, Julie Nangia, Ana Maria Storniolo, Alastair Thompson, Gaorav Gupta, Joanna Lee, Jennifer Tseng, Robyn Burns, ChunFang Zhu, Magda Matusiak, Shirley X Zhu, Jason Wang, Jose Seoane, Jen Tappenden, Daisy Ding, Dadong Zhang, Jingqin Luo, Sujay Vennam, Sushama Varma, Lunden Simpson, Luis Cisneros, Timmothy Hardman, Lauren Anderson, Cody Straub, Sucheta Srivastava, Deb J Veis, Christina Curtis, Rob Tibshirani, Robert Michael Angelo, Allison Hall, Kouros Owzar, Kornelia Polyak, Carlo Maley, Jeff Marks, Graham Colditz, Robert B West. The human tumor atlas network (HTAN) breast pre cancer atlas: A multi-omic integrative analysis of ductal carcinoma in situ (DCIS) and correlation with clinical outcomes [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PD5-08.