iAtlas Tour of Modules Immune Checkpoint Inhibitor Trials Meet the Team CRI iAtlas is made possible through collaboration between the Cancer Research Institute (cancerresearch.org), Sage Bionetworks (sagebionetworks.org), the Institute for Systems Biology (isbscience.org), and the Vincent Lab (unclineberger.org/vincentlab) at the UNC Lineberger Comprehensive Cancer Center. Our team combines expertise in software design and engineering, bioinformatics, computational biology, immuno-oncology and immunogenomics. David L. Gibbs, Carolina Heimann, Andrew E. Lamb, Dante Bortone, Thomas Yu, Brad Macdonald, Milen Nikolov, Adam J. Taylor, Amy Heiser, Steven P. Vensko II, Susheel Varma, Vesteinn Thorsson, Benjamin G. Vincent Accelerating cancer immunotherapy research with the CRI iAtlas data resource and web portal New IO Data Types CRI iAtlas is grateful for support from the Cancer Research Institute. All references cited here are listed, along with a PDF version of this poster, in Figshare at https://doi.org/10.6084/m9.ﬁgshare.26932027 Immune Landscape of Cancer Amy Heiser Milen Nikolov Thomas Yu Immuno-oncology (IO) is one of the most promising areas of cancer research, with IO-based treatments demonstrating high efﬁcacy within certain cancer types and subsets of patients. The Cancer Research Institute (CRI) iAtlas1 (cri-iatlas.org) is a platform for interactive IO data exploration and discovery, originating in a pan-cancer working group study by the Cancer Genome Atlas (TCGA)2, exploring the relationship between tumors and the immune microenvironment and its impact on patient outcomes. iAtlas provides topic-oriented analysis modules using the R/Shiny4 framework, each generating visualizations and statistics for studying interactions between tumors and the immune microenvironment. Using single cell data we have three new modules, UMAP, Immune Features, and Immunomodulators. Vésteinn Þórsson David Gibbs Carolina Heimann Andrew Lamb Benjamin Vincent We continue to expand the breadth of data in iAtlas, including newly published ICI trials with accompanying outcome data, as well as large-scale cancer -omics datasets such as the Human Tumor Atlas Network11. Dante Bortone Steven Vensko Models and notebooks We aim to make iAtlas a platform that both democratizes analysis for IO researchers and enables contributions from tool developers or data scientists. Everything we build is intended to follow FAIR principles, to advance and accelerate discovery in combating cancer. Expanding iAtlas functionality. Examples of newer modules include (above) a Cytoscape6-powered module showing how receptor-ligand interactions mediate interactions among tumor and immune cells and right iAtlas development has been generously supported by CRI since 2017 iAtlas analysis modules. (left) Interactivity enables users to explore different views or “drill down” into results. (right) List for either large-scale genomics datasets or harmonized ICI study data are driven by ﬂexible features for cohort selection. iAtlas is working hard to ramp up new data ingestion! Among the various data types we host, we've added single cell RNA-seq, with a focus on immuno-oncology studies. In our beta version (in test now), we have six new data sets that come from the Human Tumor Atlas Network (HTAN) and other public resources. Acknowledgement, References & Contact (Above) For ICI datasets with DNA- and RNA-seq data available, the Vincent Lab has developed a workﬂow (using Nextﬂow DSL2) to predict tumor antigens derived from a comprehensive set of genomic sources. The Landscape of Effective Neoantigens Software (LENS)21 workﬂow provides a portable and reproducible process for deriving these data for use in translational applications. In the TCGA study3, we identiﬁed six immune subtypes—associated with differences in somatic aberrations, microenvironment, and survival—that span cancer types and molecular subtypes. For each sample, we characterized the tumor microenvironment in terms of