BackgroundGene expression profiling (GEP) studies recognized a prognostic role for tumor microenvironment (TME) in diffuse large B-cell lymphoma (DLBCL), but the routinely adoption of prognostic stromal signatures remains limited.Patients and methodsHere, we applied the computational method CIBERSORT to generate a 1028-gene matrix incorporating signatures of 17 immune and stromal cytotypes. Then, we carried out a deconvolution on publicly available GEP data of 482 untreated DLBCLs to reveal associations between clinical outcomes and proportions of putative tumor-infiltrating cell types. Forty-five genes related to peculiar prognostic cytotypes were selected and their expression digitally quantified by NanoString technology on a validation set of 175 formalin-fixed, paraffin-embedded DLBCLs from two randomized trials. Data from an unsupervised clustering analysis were used to build a model of clustering assignment, whose prognostic value was also assessed on an independent cohort of 40 cases. All tissue samples consisted of pretreatment biopsies of advanced-stage DLBCLs treated by comparable R-CHOP/R-CHOP-like regimens.Results In silico analysis demonstrated that higher proportion of myofibroblasts (MFs), dendritic cells, and CD4+ T cells correlated with better outcomes and the expression of genes in our panel is associated with a risk of overall and progression-free survival. In a multivariate Cox model, the microenvironment genes retained high prognostic performance independently of the cell-of-origin (COO), and integration of the two prognosticators (COO + TME) improved survival prediction in both validation set and independent cohort. Moreover, the major contribution of MF-related genes to the panel and Gene Set Enrichment Analysis suggested a strong influence of extracellular matrix determinants in DLBCL biology.ConclusionsOur study identified new prognostic categories of DLBCL, providing an easy-to-apply gene panel that powerfully predicts patients’ survival. Moreover, owing to its relationship with specific stromal and immune components, the panel may acquire a predictive relevance in clinical trials exploring new drugs with known impact on TME.

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Summary We applied digital spatial profiling for 87 immune and stromal genes to lymph node germinal center (GC) dark- and light-zone (DZ/LZ) regions of interest to obtain a differential signature of these two distinct microenvironments. The spatially resolved 53-genes signature, comprising key genes of the DZ mutational machinery and LZ immune and mesenchymal milieu, was applied to the transcriptomes of 543 GC-related diffuse large B cell lymphomas and double-hit (DH) lymphomas. According to the DZ/LZ signature, the GC-related lymphomas were sub-classified into two clusters. The subgroups differed in the distribution of DH cases and survival, with most DH displaying a distinct DZ-like profile. The clustering analysis was also performed using a 25-genes signature composed of genes positively enriched in the non-B, stromal sub-compartments, for the first time achieving DZ/LZ discrimination based on stromal/immune features. The report offers new insight into the GC microenvironment, hinting at a DZ microenvironment of origin in DH lymphomas.