Hitting back at lymphoma: How do modern diagnostics identify high-risk diffuse large B-cell lymphoma subsets and alter treatment?

Abstract

Diffuse large B-cell lymphoma (DLBCL) is a clinically and biologically heterogeneous disease. Diagnostic tools in the clinic can now identify distinct subsets characterized by unique molecular features, which are increasingly transforming how these patients are managed. Activated B-cell-like DLBCL is characterized by NF-κB activation and chronic B-cell receptor signaling and may be targeted with lenalidomide or ibrutinib in the relapsed setting. Germinal center-like DLBCL is enriched for activating EZH2 mutations, and encouraging activity has been observed for the EZH2 inhibitor tazemetostat, which now has a fast-track US Food and Drug Administration designation. Double-hit lymphoma is a high-grade B-cell lymphoma characterized by translocations of MYC and BCL2 and/or BCL6 and carries a poor prognosis. Intensive chemoimmunotherapy strategies appear to be superior to standard R-CHOP (rituximab combined with cyclophosphamide, doxorubicin, vincristine, and prednisone) as initial therapy, and anti-CD19 chimeric antigen receptor T cells are inducing remission in patients with relapsed/refractory disease who previously had few available options. Primary mediastinal (thymic) large B-cell lymphoma is a molecularly distinct large-cell lymphoma with clinical and molecular features that overlap with those of classical Hodgkin lymphoma. R-CHOP has been associated with an unacceptably high rate of primary treatment failure in this young population, whereas dose-adjusted EPOCH-R (etoposide, prednisone, vincristine, cyclophosphamide, and doxorubicin plus rituximab) produces durable remissions without the need for radiotherapy in most patients. For relapsed/refractory disease, immune checkpoint inhibitors targeting PD-1 have shown promising activity in chemotherapy-refractory disease, as have anti-CD19 chimeric antigen receptor T cells. Additional therapeutic targets, including JAK2, continue to be evaluated. The identification of discrete biological subsets is steadily moving us away from a "one-size-fits-all" approach in DLBCL.