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1.
Ann Oncol ; 29(12): 2363-2370, 2018 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-30307529

RESUMO

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.


Assuntos
Linfoma Difuso de Grandes Células B/mortalidade , Transcriptoma/genética , Microambiente Tumoral/genética , Adulto , Idoso , Algoritmos , Biópsia , Análise por Conglomerados , Estudos de Coortes , Biologia Computacional , Conjuntos de Dados como Assunto , Feminino , Perfilação da Expressão Gênica/métodos , Humanos , Linfoma Difuso de Grandes Células B/genética , Linfoma Difuso de Grandes Células B/patologia , Masculino , Pessoa de Meia-Idade , Inclusão em Parafina , Valor Preditivo dos Testes , Prognóstico , Intervalo Livre de Progressão , Ensaios Clínicos Controlados Aleatórios como Assunto , Reprodutibilidade dos Testes , Análise de Sobrevida , Adulto Jovem
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