At the Icahn Institute for Data Science and Genomic Technology, our cancer genetics research program combines novel genomics technology, molecular biology, and informatics approaches to generate higher resolution cancer data and more sophisticated predictive models directed at guiding more precise targeted therapies and a stronger understanding of cancer evolution.
Cancer remains a complex medical challenge caused by a range of genetic, environmental, lifestyle, and unknown factors that lead to disease. While science continues to make significant advances in understanding how specific cancers evolve, we have learned that individual tumor composition is highly variable. This variation exists across patient populations, but also develops as patients undergo therapy, as individual tumor cells in a patient can become resistant to those treatments.
Analyzing comprehensive phenotypic and genomic data is one way to diagnostically determine and prognostically monitor the variation of an individual’s tumor. By assembling a world-class DNA and RNA sequencing and informatics technology toolbox, we have the unique ability to diagnose and monitor disease progression, as well as discover actionable biomarkers, functional signaling pathways, and potential future therapies using genomic data. As technology progresses, resolution of these genomic data has also increased, facilitating a paradigm shift towards truly personalized therapy in which treatment will be tailored to the patient’s genetic variation in order to understand any altered cellular signaling pathways.
The cancer genomics research program consists of both basic research and applied medical sequencing initiatives. This duality enables scientific discovery, and also permits direct sequencing of cancer patients’ inherited DNA, tumor DNA/RNA, and more recently, unique single cells or circulating cancerous material that comprise heterogeneous tumor tissue. The integration of this genetic data into annotated models significantly increases our understanding of how individual oncogenic cells network, function and respond to therapy. Genetic data is analyzed on an individual basis and also compared to existing databases of phenotypic and genetic information to determine both common and unique potential therapies tailored more closely to the individual patient’s disease, offering a more precise model for treatment. The basic research and discovery of novel therapeutic targets continuously promotes the growth of a stronger database of potential targets. The collection, characterization and of known and novel genetic information drives the development of a more through and comprehensive understanding of how to tackle cancer on an individual basis in the future.
Our Published Research
Clinical Cancer Research
Inhibition of the Nuclear Export Receptor XPO1 as a Therapeutic Target for Platinum-Resistant Ovarian Cancer Read the full study
Development and clinical application of an integrative genomic approach to personalized cancer therapy Read the full study
Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers Read the full study
Characterizing and Overriding the Structural Mechanism of the Quizartinib-Resistant FLT3 "Gatekeeper" F691L Mutation with PLX3397 Read the full study
Validation of ITD mutations in FLT3 as a therapeutic target in human acute myeloid leukaemia Read the full study