The promises and challenges of using gene mutations for patient stratification in follicular lymphoma.

Follicular lymphoma (FL) is a clinically and molecularly highly heterogeneous disease. Most patients achieve long-lasting remissions and have excellent overall survival (OS) with current treatment. However, ∼20% of patients have early progression of disease and short OS. At present, therapies are not guided by individual risk or disease biology. Reliable tools for patient stratification are urgently needed to avoid overtreatment of low-risk patients and to prioritize alternative approaches in high-risk patients. A rapidly expanding repertoire of promising therapeutic options is available for clinical evaluation; however, the numbers of patients with FL and the resources to conduct adequately powered trials are limited. Recent studies have shown that gene mutations can serve as prognostic and/or predictive biomarkers, in particular when integrated into composite risk models. Before translating these findings into routine clinical practice, however, several challenges loom. We review aspects of "clinicogenetic" risk model development and validation that apply to FL and more generally to other cancers. Finally, we propose a crowdsourcing effort that could expedite the development, validation, refinement, and selection of risk models. A new era of collaboration and harmonization is required if we hope to transition from empiric selection of therapeutics to risk-based, biology-guided treatment of patients with FL.