Abstract 1076: Sharing data from the Human Tumor Atlas Network through standards, infrastructure, and community engagement
Authors: Ino de Bruijn, Milen Nikolov, Clarisse Lau, Ashley Clayton, David L. Gibbs, Elvira Mitraka, Dar'ya Y. Pozhidayeva, Alex Lash, Selcuk Onur Sumer, Jennifer Altreuter, Kristen Anton, Mialy DeFelice, Xiang Li, Aaron Lisman, William J. Longabaugh, Jeremy Muhlich, Sandro Santagata, Subhiksha Nandakumar, Peter K. Sorger, Christine Suver, Xengie Doan, Justin Guinney, Nikolaus Schultz, Adam J. Taylor, Vésteinn Thorsson, Ethan Cerami, James A. Eddy
Journal: Cancer Research (2025)

Abstract In September 2018, the National Cancer Institute (NCI) launched the first phase of the Human Tumor Atlas Network (HTAN) under the U.S. Cancer Moonshot program with the goal of generating three-dimensional molecular and spatial atlases of diverse human tumors and characterizing crucial transitions in cancer progression and treatment. With over 30 assay types including sequencing, imaging, and spatial transcriptomics spanning 58 cancers across 21 organ types, HTAN has delivered a substantial resource to the broader cancer research community and become the basis for a multitude of publications. Although HTAN is similar to previous large cancer data sharing efforts, new and unique challenges have emerged. First, each HTAN atlas consists of a unique collection of data focused on answering different hypotheses regarding cancer progression. Second, many of the experimental assays used within HTAN—particularly spatial profiling assays—are cutting-edge, requiring their own custom bioinformatics pipelines to perform analyses. Third, HTAN is focused on understanding temporal changes in cancer, and the HTAN data model must therefore be capable of capturing longitudinal clinical/phenotype and profiling data. Fourth, the multi-modal nature of HTAN data requires multiple visualization and data access resources, each of which must be tailored to individual data types or end-users. To address the unique challenges of HTAN data, the network supports a dedicated Data Coordinating Center (DCC) which is currently managed by personnel from four institutions: Dana-Farber Cancer Institute, Sage Bionetworks, Memorial Sloan Kettering Cancer Center, and the Institute for Systems Biology. The DCC develops infrastructure and tools to ingest, curate, explore, and share these data in a findable, accessible, interoperable, and reusable (FAIR) manner. To this end, the DCC manages the HTAN Data Portal, which provides community access to the atlases and enables filtering of released atlas data based on metadata fields, and pointers to data availability. Additionally, the DCC leads community-driven metadata schema development through a Request for Comments (RFC) process. These activities are critical to ensuring that the wealth of data generated by HTAN is available for use by the broader scientific community​. As we transition into the second phase, we describe insights from HTAN phase I, the multiple ways users can access HTAN data and metadata, the associated data standards, the enabling technical infrastructure and governance approaches underlying the DCC, and how community engagement is maintained throughout. Citation Format: Ino de Bruijn, Milen Nikolov, Clarisse Lau, Ashley Clayton, David L. Gibbs, Elvira Mitraka, Dar'ya Y. Pozhidayeva, Alex Lash, Selcuk Onur Sumer, Jennifer Altreuter, Kristen Anton, Mialy DeFelice, Xiang Li, Aaron Lisman, William J. Longabaugh, Jeremy Muhlich, Sandro Santagata, Subhiksha Nandakumar, Peter K. Sorger, Christine Suver, Xengie Doan, Justin Guinney, Nikolaus Schultz, Adam J. Taylor, Vésteinn Thorsson, Ethan Cerami, James A. Eddy. Sharing data from the Human Tumor Atlas Network through standards, infrastructure, and community engagement [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1076.