Abstract 7429: A web-based application to co-register elemental imaging with histopathology to enhance the study of metal bioaccumulation within tumors
Authors: Yunrui Lu, Ramsey Steiner, Serin Han, Matthew Chan, Tracy Punshon, Brian Jackson, Linda Vahdat, Jonathan Marotti, Joshua Levy
Journal: Cancer Research (2024)

Abstract Essential trace elements are crucial in various biological processes, including tumor growth, migration, and metastasis. For instance, copper ions are involved in mitochondrial metabolism, cell proliferation, tumor migration, metastasis and proangiongenic pathways. Localizing where metal ion homeostasis is disrupted is vital for understanding these processes beyond what bulk analysis can reveal. Elemental imaging offers high-resolution, quantifiable multi-elemental distribution maps, providing a more detailed analysis compared to traditional bulk measurements. However, aligning findings with tissue structures identified in histopathological data can be challenging. To address this, we developed a web-based application for the co-registration and analysis of Whole Slide Images (WSI) and elemental imaging data at the cellular level. The application integrates WSI with elemental maps generated by technologies such as ultrafast laser ablation and inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS), as well as a range of other elemental imaging techniques. Hosted by the Biomedical National Elemental Imaging Resource, the current application allows for a streamlined data integration, co-registration, and analysis, including: 1) uploading WSI, elemental maps, and pathologist annotations, 2) automated preprocessing to identify tissue regions, 3) co-registration to merge WSI and elemental maps, 4) custom import, real-time overlay/editing of pathologist annotations transferred from WSI, 5) plotting, statistical tools and 6) data export. This application enables users to compare elemental abundance within/between tissue structures annotated on H&amp;E or immunohistochemical slides. Derived data can pinpoint elements and mixtures whose abundance differs significantly across various pathological conditions. As an initial test, we applied the software on breast HER2/ER/PR tumors, varying in molecular subtype/histology. Preliminary results, using Bayesian lognormal regression models, adjusting for tumor subtypes, indicated a subtype-dependent variation in copper abundance. The relative difference in copper levels between tumor and stromal regions was notably less in HER2 tumors (p=0.026) compared to HR tumors (p&amp;lt;0.0001). Conversely, iron showed a consistently higher abundance in stromal areas across both subtypes (p&amp;lt;0.0001). Future enhancements include improved co-registration capabilities, hotspot analysis, machine learning, mixture effects, and cloud-based architecture. This method uniquely enables integration of elemental data with spatial transcriptomics, mapping gene transcripts on tissue slides. With current ST assays aligned with H&amp;E slides, this tool facilitates co-registration, offering insights into biological pathways affected by metal homeostasis disruptions. Citation Format: Yunrui Lu, Ramsey Steiner, Serin Han, Matthew Chan, Tracy Punshon, Brian Jackson, Linda Vahdat, Jonathan Marotti, Joshua Levy. A web-based application to co-register elemental imaging with histopathology to enhance the study of metal bioaccumulation within tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7429.