Browsing by Author "Cerami, Ethan"

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    Interactive or static reports to guide clinical interpretation of cancer genomics.
    (Journal of the American Medical Informatics Association : JAMIA, 2018-05) Gray, Stacy W; Gagan, Jeffrey; Cerami, Ethan; Cronin, Angel M; Uno, Hajime; Oliver, Nelly; Lowenstein, Carol; Lederman, Ruth; Revette, Anna; Suarez, Aaron; Lee, Charlotte; Bryan, Jordan; Sholl, Lynette; Van Allen, Eliezer M

    Objective

    Misinterpretation of complex genomic data presents a major challenge in the implementation of precision oncology. We sought to determine whether interactive genomic reports with embedded clinician education and optimized data visualization improved genomic data interpretation.

    Materials and methods

    We conducted a randomized, vignette-based survey study to determine whether exposure to interactive reports for a somatic gene panel, as compared to static reports, improves physicians' genomic comprehension and report-related satisfaction (overall scores calculated across 3 vignettes, range 0-18 and 1-4, respectively, higher score corresponding with improved endpoints).

    Results

    One hundred and five physicians at a tertiary cancer center participated (29% participation rate): 67% medical, 20% pediatric, 7% radiation, and 7% surgical oncology; 37% female. Prior to viewing the case-based vignettes, 34% of the physicians reported difficulty making treatment recommendations based on the standard static report. After vignette/report exposure, physicians' overall comprehension scores did not differ by report type (mean score: interactive 11.6 vs static 10.5, difference = 1.1, 95% CI, -0.3, 2.5, P = .13). However, physicians exposed to the interactive report were more likely to correctly assess sequencing quality (P < .001) and understand when reports needed to be interpreted with caution (eg, low tumor purity; P = .02). Overall satisfaction scores were higher in the interactive group (mean score 2.5 vs 2.1, difference = 0.4, 95% CI, 0.2-0.7, P = .001).

    Discussion and conclusion

    Interactive genomic reports may improve physicians' ability to accurately assess genomic data and increase report-related satisfaction. Additional research in users' genomic needs and efforts to integrate interactive reports into electronic health records may facilitate the implementation of precision oncology.
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    The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution.
    (Cell, 2020-04) Rozenblatt-Rosen, Orit; Regev, Aviv; Oberdoerffer, Philipp; Nawy, Tal; Hupalowska, Anna; Rood, Jennifer E; Ashenberg, Orr; Cerami, Ethan; Coffey, Robert J; Demir, Emek; Ding, Li; Esplin, Edward D; Ford, James M; Goecks, Jeremy; Ghosh, Sharmistha; Gray, Joe W; Guinney, Justin; Hanlon, Sean E; Hughes, Shannon K; Hwang, E Shelley; Iacobuzio-Donahue, Christine A; Jané-Valbuena, Judit; Johnson, Bruce E; Lau, Ken S; Lively, Tracy; Mazzilli, Sarah A; Pe'er, Dana; Santagata, Sandro; Shalek, Alex K; Schapiro, Denis; Snyder, Michael P; Sorger, Peter K; Spira, Avrum E; Srivastava, Sudhir; Tan, Kai; West, Robert B; Williams, Elizabeth H; Human Tumor Atlas Network
    Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.