Dissection of DLBCL microenvironment provides a gene expression-based predictor of survival applicable to formalin-fixed paraffin-embedded tissue. (11th October 2018)

• Record Type: Journal Article
• Authors: Ciavarella, S; Vegliante, M C; Fabbri, M; De Summa, S; Melle, F; Motta, G; De Iuliis, V; Opinto, G; Enjuanes, A; Rega, S; Gulino, A; Agostinelli, C; Scattone, A; Tommasi, S; Mangia, A; Mele, F; Simone, G; Zito, A F; Ingravallo, G; Vitolo, U; Chiappella, A; Tarella, C; Gianni, A M; Rambaldi, A; Zinzani, P L; Casadei, B; Derenzini, E; Loseto, G; Pileri, A; Tabanelli, V; Fiori, S; Rivas-Delgado, A; López-Guillermo, A; Venesio, T; Sapino, A; Campo, E; Tripodo, C; Guarini, A; Pileri, S A;
• Is Part Of: Annals of oncology. Volume 29:Number 12(2018)
• Page Start: 2363
• Page End: 2370
• Publication Date: 2018-10-11
• Subjects: DLBCL -- microenvironment -- deconvolution -- cell-of-origin -- digital expression analysis -- prognosticators; Oncology -- Periodicals; 616.992
• DOI: 10.1093/annonc/mdy450
• Languages: English
• ISSNs: 0923-7534

Abstract

Abstract: Background: Gene 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 methods: Here, 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. Conclusions: Our 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.