A Genomic Framework for Molecular Risk Prediction & Individualized Lymphoma Therapy

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PROJECT SUMMARY/ABSTRACT PIs: Ash Alizadeh, M.D./Ph.D. & Maximilian Diehn, M.D./Ph.D. For patients with Diffuse large B-cell lymphoma (DLBCL), the most common lymphoma subtype, curative outcomes are common. Unfortunately, despite many large clinical trials, survival has not significantly improved over the last 15 years and nearly a third of patients continue to succumb to this disease. For these patients, effective strategies to predict early treatment failures have been elusive. Our long-term goal is to study the ability of baseline and dynamic risk factors, including genetic mutations and circulating tumor DNA (ctDNA), to accurately predict treatment outcomes in DLBCL patients. Our central hypothesis is that novel biomarkers of cancer risk, such as detection of ctDNA and detailed genetic profiling, can be used for early detection of residual disease, to identify dynamic changes that anticipate treatment failure, and to provide early surrogate endpoints for future clinical trials. We will test our hypothesis via three specific aims: (1) To build an accurate and dynamic predictor of survival for patients newly diagnosed with DLBCL, (2) To test the validity and utility of this predictor in a large multi-institutional cohort of patients from around the globe, and (3) To assess the ability of this dynamic risk assessment tool to serve as an early surrogate endpoint in prospective clinical trials. We will apply our novel approach in both the frontline and relapse/refractory setting and to a variety of treatment types including immunochemotherapy, an antibody-drug conjugate and Chimeric Antigen Receptor (CAR) T cells. If successful, our project will lead to novel ways to select better therapies for patients at highest risk of failure. Our innovative approach, in which we will employ novel, blood-based methods for tumor genotyping and disease monitoring that were developed by our group, will lay the foundation for studies aimed at reducing risk of treatment failure in DLBCL patients. Demonstrating that this approach can serve as a robust, early surrogate endpoint for patients with aggressive lymphomas would be transformative for future trial design and for rapid evaluation of novel, personalized treatment approaches in patients at highest risk for recurrence. Our work will serve as proof-of-principle for an approach that could also be applied to other cancer types.