Browsing by Author "Elmarakeby, Haitham"

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    Integrating molecular profiles into clinical frameworks through the Molecular Oncology Almanac to prospectively guide precision oncology
    (Springer Nature, 2021) Reardon, Brendan; Moore, Nathanael D.; Moore, Nicholas S.; Kofman, Eric; AlDubayan, Saud H.; Cheung, Alexander T.M.; Conway, Jake; Elmarakeby, Haitham; Imamovic, Alma; Kamran, Sophia C.; Keenan, Tanya; Keliher, Daniel; Konieczkowski, David J.; Liu, David; Mouw, Kent W.; Park, Jihye; Vokes, Natalie I.; Dietlein, Felix; Van Allen, Eliezer M.; Medicine, School of Medicine
    Tumor molecular profiling of single gene-variant ('first-order') genomic alterations informs potential therapeutic approaches. Interactions between such first-order events and global molecular features (for example, mutational signatures) are increasingly associated with clinical outcomes, but these 'second-order' alterations are not yet accounted for in clinical interpretation algorithms and knowledge bases. We introduce the Molecular Oncology Almanac (MOAlmanac), a paired clinical interpretation algorithm and knowledge base to enable integrative interpretation of multimodal genomic data for point-of-care decision making and translational-hypothesis generation. We benchmarked MOAlmanac to a first-order interpretation method across multiple retrospective cohorts and observed an increased number of clinical hypotheses from evaluation of molecular features and profile-to-cell line matchmaking. When applied to a prospective precision oncology trial cohort, MOAlmanac nominated a median of two therapies per patient and identified therapeutic strategies administered in 47% of patients. Overall, we present an open-source computational method for integrative clinical interpretation of individualized molecular profiles.