Prognostic role of PD-L1/PD-1 expression in B-Cell Lymphomas

Fabienne McClanahan, from the Barts Cancer Institute at the Queen Mary University of London, UK, and colleagues recently published in Haematologica a systematic review of the published data available on Programed Cell Death-Ligand 1/Programmed Cell Death-1 (PD-L1/PD-1) expression and their prognostic value. They only included studies of patients with either DLBCL, HL, FL, CLL or PMBCL, where the expression of PD-L1/PD-1 was quantified in tumor cells or components of the tumor microenvironment via immunohistochemistry or flow cytometry.

Highlights:

DLBCL:

• Expression of PD-L1 is heterogeneous
• Molecular subtype and EBV status can affect PD-L1 expression
• Higher PD-L1 expression significantly associated with inferior OS and higher B symptoms

FL:

• Expression of PD-L1 is largely absent

CLL:

• Expression of PD-L1 is higher in lymph nodes and peripheral blood cells in patients with poorer survival
• Results highly conflicting and small sample size

HL and PMBCL:

• Strong PD-L1 and PD-L2 expression in malignancies
• PD-L1+PD-1 co-expression shown to be an independent prognostic risk factor
• Significantly lower OS and DFS in patients with PD-L1+PD-1 co-expressing vs non-co-expressing

The authors concluded by stating that their review shows that PD-L1/PD-1 expression is clinically important, and the function this interaction plays is an essential part of B-Cell Lymphoma biology. Furthermore, they state that outcome of patients with high PD-L1/PD-1 expression is dictated by additional contributory components. Finally, the authors propose that a consistent assessment and interpretation of PD-L1/PD-1 expression should be adopted in ongoing clinical trials of checkpoint inhibitors in order to better categorize the prognostic value of PD-L1/PD-1.

Abstract: Therapeutic strategies targeting the programmed cell death-ligand 1/programmed cell death-1 pathway have shown significant responses and good tolerability in solid malignancies. Although preclinical studies suggest that inhibiting programmed cell death-ligand 1/programmed cell death-1 interactions might also be highly effective in hematological malignancies, remarkably few clinical trials have been published. Determining patients who will benefit most from programmed cell death-ligand 1/programmed cell death-1-directed immunotherapy and whether programmed cell death-ligand 1/programmed cell death-1 are adequate prognostic markers becomes an increasingly important clinical question, especially as aberrant programmed cell death-ligand 1/programmed cell death-1 expression are key mediators of impaired anti-tumor immune responses in a range of B-cell lymphomas. Herein, we systematically review the published literature on the expression and prognostic value of programmed cell death-ligand 1/programmed cell death-1 in these patients and identify considerable differences in expression patterns, distribution and numbers of programmed cell death-ligand 1+/programmed cell death-1+cells, both between and within lymphoma subtypes, which is reflected in conflicting findings regarding the prognostic value of programmed cell death-ligand 1+/programmed cell death-1+ cells. This can be partly explained by differences in methodologies (techniques, protocols, cutoff values) and definitions of positivity. Moreover, lymphomagenesis, disease progression, and prognosis appear to be determined not only by the presence, numbers and distribution of specific subtypes of T cells, but also by other cells and additional immune checkpoints. Collectively, our findings indicate that programmed cell death-ligand 1/programmed cell death-1 interactions play an essential role in B-cell lymphoma biology and are of clinical importance, but that the overall outcome is determined by additional components. To categorize the exact prognostic value of programmed cell death-ligand 1/programmed cell death-1 expressing cells and cell types, efforts should be made to harmonize their assessment and interpretation, optimally within ongoing clinical immune checkpoint inhibitor trials, and to identify and validate novel high-throughput platforms.