Abstract A007: Picturing progression: A new role of whole slide imaging in comprehensive clinical genomic datasets
Authors: Elizabeth G. Sweeney, Yawei J. Wang, Jacob Picard, Jim Abraham, Eghbal Amidi, Michael R. Rossi, Sergey Klimov, Claudio D'Ambrosio, Ming Chen, Jeff Elton, George Sledge
Journal: Cancer Research (2024)

Abstract Introduction: Real world data is needed to understand cancer evolution based on changing standards of care. While Next Generation Sequencing (NGS) is the preferred standard for confirmatory testing of mutational status, its use varies tremendously across settings and countries, with the most influential variable being cost. In this research, we examined the utility of Whole Slide Images (WSI) as a discrete data type to predict mutational and other statuses to inform assessments of clinical progression. This could include initial mutational status or the evolution of resistance to a specific treatment and the emergence of a new driver mutation. Experimental Procedures: We have curated datasets from 4000 NSCLC and 2000 CRC patients with clinically tested WES, WTS and WSI tumors with deeply curated longitudinal clinical electronic medical records were compiled through a partnership between ConcertAI and Caris Life Science. This de-identified clinical dataset is drawn from a diverse range of U.S. community and academic oncology practices. The practice patterns reflect the real-world variability of treatment and utilization of molecular testing. Additional stratification was performed based on lines of therapy and evidence of clinical progression for patients with information available. Results: Features from whole slide H&amp;E images were extracted and compared between subcohorts of interest. We demonstrated the correlation of the WSI features with TMB, MSI-H, molecular variants, differential gene expression and PD-L1 IHC of these cohorts within the context human interpretable features (HIFs) of whole slide images. Conclusion: The availability of whole slide images (WSI) is a dimensionality requirement for real world longitudinal comprehensive clinical datasets. Digital images should be considered as a key deliverable of clinical genomic datasets and have the potential to inform treatment selection and outcomes. In settings where NGS is not the standard of care, WSI could be used to predict the value of a test for treatment decisions or determination of prospective clinical trial eligibility. Where the cost of NGS is fundamentally prohibitive, such as less developed economies, WSI is a much lower cost modality that could have very high utility in guiding treatment decisions with better predicted outcomes. In all cases WSI imaging could be used to assess potential status or acquired resistance and the evolution of a new driver mutation. All critical in the decision to continue or discontinue a specific treatment. Citation Format: Elizabeth G. Sweeney, Yawei J. Wang, Jacob Picard, Jim Abraham, Eghbal Amidi, Michael R. Rossi, Sergey Klimov, Claudio D'Ambrosio, Ming Chen, Jeff Elton, George Sledge. Picturing progression: A new role of whole slide imaging in comprehensive clinical genomic datasets [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A007.