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Checkpoint protein expression in the tumor microenvironment defines the outcome of classical Hodgkin lymphoma patients

Kristiina Karihtala, Suvi‐Katri Leivonen, Marja‐Liisa Karjalainen‐Lindsberg, Fong Chun Chan, Christian Steidl, Teijo Pellinen, Sirpa Leppä

2021Blood Advances22 citationsDOIOpen Access PDF

Abstract

Emerging evidence indicates a major impact for the tumor microenvironment (TME) and immune escape in the pathogenesis and clinical course of classical Hodgkin lymphoma (cHL). We used gene expression profiling (n = 88), CIBERSORT, and multiplex immunohistochemistry (n = 131) to characterize the immunoprofile of cHL TME and correlated the findings with survival. Gene expression analysis divided tumors into subgroups with T cell-inflamed and -noninflamed TME. Several macrophage-related genes were upregulated in samples with the non-T cell-inflamed TME, and based on the immune cell proportions, the samples clustered according to the content of T cells and macrophages. A cluster with high proportions of checkpoint protein (programmed cell death protein 1, PD-1 ligands, indoleamine 2,3 dioxygenase 1, lymphocyte-activation gene 3, and T-cell immunoglobulin and mucin domain containing protein 3) positive immune cells translated to unfavorable overall survival (OS) (5-year OS 76% vs 96%; P = .010) and remained an independent prognostic factor for OS in multivariable analysis (HR, 4.34; 95% CI, 1.05-17.91; P = .043). cHL samples with high proportions of checkpoint proteins overexpressed genes coding for cytolytic factors, proposing paradoxically that they were immunologically active. This checkpoint molecule gene signature translated to inferior survival in a validation cohort of 290 diagnostic cHL samples (P < .001) and in an expansion cohort of 84 cHL relapse samples (P = .048). Our findings demonstrate the impact of T cell- and macrophage-mediated checkpoint system on the survival of patients with cHL.

Topics & Concepts

Classical Hodgkin lymphomaTumor microenvironmentLymphomaProtein expressionOutcome (game theory)Cancer researchHodgkin lymphomaOncologyExpression (computer science)MedicineInternal medicineBiologyTumor cellsComputer scienceGeneticsGeneMathematical economicsMathematicsProgramming languageLymphoma Diagnosis and TreatmentCancer Immunotherapy and BiomarkersCancer Genomics and Diagnostics