• Researcher Profile

    Dana H. Gabuzda, MD

    Dana H. Gabuzda, MD
    Professor of Neurology, Harvard Medical School

    Office phone: 617-632-2154
    Fax: 617-632-4338
    Email: dana_gabuzda@dfci.harvard.edu
    Website: Gabuzda Lab Website

    Preferred contact method: office phone

    Research Department

    Cancer Immunology and Virology

    Area of Research

    HIV Molecular Biology and Pathogenesis

    Dana-Farber Cancer Institute
    450 Brookline Avenue
    CLS 1010
    Boston, MA 02215


    Dr. Gabuzda received her MD from Harvard Medical School in 1983 and did her postgraduate training in internal medicine and neurology at Massachusetts General Hospital. After completing research fellowships at Johns Hopkins University and DFCI, she joined the DFCI faculty in 1991. She is primarily involved in basic laboratory research on HIV replication and disease mechanisms in AIDS.


    HIV Molecular Biology and Pathogenesis

    The Gabuzda lab uses genetic, biochemical, metabolomic, systems biology, and computational approaches to study HIV infection and comorbidities including cancer. Research interests include understanding viral, host, and environmental factors that determine clinical outcomes, therapeutic responses, and accelerated aging. Current projects include studies on:

    • 1) virus-host interactions during HIV replication and pathogenesis that impact immune control, inflammation, metabolic disorders, and comorbidities

    • 2) role of exosomes in cell-cell communication, immune regulation, stress responses, and disease pathophysiology

    • 3) mechanisms involved in HIV-associated neurological disorders and accelerated aging

    • 4) cancer risk and etiologies in aging populations with HIV

    The lab is proficient at bioinformatic, computational, and systems biology approaches including generation, analysis, interpretation, and visualization of large data sets, big data handling, and using bioinformatic software and R programs for data integration, network prediction, pathway analysis, and modeling. The lab also uses machine learning and other computational approaches to model longitudinal trajectories and identify new predictors of clinical outcomes. The long-term goal is gaining multidisciplinary knowledge that leads to progress in personalized medicine for HIV-infected and aging populations.

    Complete Publications List: http://www.ncbi.nlm.nih.gov/sites/myncbi/dana.gabuzda.1/collections/47703338/public/


    • Chettimada, Sukrutha, PhD
    • Dutta, Anuprya, PhD
    • Guha, Debjani, PhD
    • Mukerji, Shibani, MD, PhD
    • Solomon, Isaac, MD, PhD
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