University Health Network
Project Term: July 1, 2019 - June 30, 2022
A proportion of follicular lymphoma patients will experience early treatment failure and premature death. We will delineate the molecular features that underlie treatment failure from a recent randomized trial (BIONIC) & Canadian cohort via 3 aims: 1) confirm the prognostic significance of prior reported biomarkers (eg, m7-FLIPI, etc); 2) establish the genetic taxonomy of FL via integrated genomic analyses and consensus clustering; and 3) determine the prognostic value of circulating tumor DNA.
Follicular lymphoma is the 2nd most common lymphoma type diagnosed in the US. Despite recent advances, follicular lymphoma remains largely incurable and the vast majority of patients experience progression. Some patients may remain free of disease for 10 years or longer following initial treatment and have a favorable outlook, while others may experience early disease progression and are at risk of dying prematurely from lymphoma. Thus, despite all follicular lymphoma patients being diagnosed with the same lymphoma type, their outcomes are extremely variable. At the same time, an increasing number of treatment options are becoming available, but we are currently unable to tailor treatment to each individual patient’s lymphoma, for two reasons: 1) we are unable to accurately predict risk of progression before starting treatment; 2) we do not understand what patients would benefit more from one treatment compared to another. Herein, we propose to solve these two deficiencies in order to improve outcomes for follicular lymphoma patients via enhanced precision diagnostics of tumor genetics that will lead to more individualized therapy. We will harness large cohorts of follicular lymphoma samples, accrued within clinical trials and existing repositories. As recent technological advances allow us to study perturbations of all genes within lymphoma biopsies, we have the unprecedented opportunity to link this knowledge to patient outcomes. In a first part of this project, we will examine whether existing tests allow us to identify those patients who are at increased risk of experiencing lymphoma progression. We will then aim to identify patterns that are currently hidden, but that can be uncovered using unbiased, cutting edge tools. Such patterns will reveal that not all follicular lymphoma patients have the same disease, but that they can be grouped based on gene perturbations. These subtypes of follicular lymphoma are expected to be associated with distinct risk of progression and susceptibility to specific treatments. Lastly, we will study whether we can identify gene perturbations in blood draws, foregoing the need for invasive biopsies altogether, and whether this information predicts patient outcomes. Our project has important implications for the treatment of follicular lymphoma patients. The accurate prediction of progression and identification of novel subtypes will allow to adjust our treatment approach for each individual patient. By identification of the mechanisms underlying poor outcome at the time of diagnosis (i.e. pre-treatment), we can propose more individualized therapeutic recommendations for patients who were previously thought to be at high risk, thereby circumventing adverse outcome. Altogether, this project’s results will be significant because they will represent a critical step towards enhanced precision medicine for follicular lymphoma patients and are expected to significantly improve individualized patient care.