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.
Dissection of DLBCL Microenvironment Provides a Gene Expression-Based Predictor of Survival Applicable to Formalin-Fixed Paraffin-Embedded Tissue / S. Ciavarella, M.C. Vegliante, M. Fabbri, S. De Summa, F. Melle, G. Motta, V. De Iuliis, G. Opinto, A. Enjuanes, S. Rega, A. Gulino, C. Agostinelli, A. Scattone, S. Tommasi, A. Mangia, F. Mele, G. Simone, A.F. Zito, G. Ingravallo, U. Vitolo, A. Chiappella, C. Tarella, A.M. Gianni, A. Rambaldi, P.L. Zinzani, B. Casadei, E. Derenzini, G. Loseto, A. Pileri, V. Tabanelli, S. Fiori, A. Rivas-Delgado, A. López-Guillermo, T. Venesio, A. Sapino, E. Campo, C. Tripodo, A. Guarini, S.A. Pileri. - In: ANNALS OF ONCOLOGY. - ISSN 0923-7534. - 29:12(2018 Dec), pp. 2363-2370. [10.1093/annonc/mdy450]
Dissection of DLBCL Microenvironment Provides a Gene Expression-Based Predictor of Survival Applicable to Formalin-Fixed Paraffin-Embedded Tissue
C. Tarella;A.M. Gianni;A. Rambaldi;E. Derenzini;
2018
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.File | Dimensione | Formato | |
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