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. VitoloA. Chiappella, C. Tarella, A.M. Gianni, A. Rambaldi, P.L. Zinzani, B. Casadei, E. Derenzini, G. Loseto, A. Pileri, V. Tabanelli, Stefano Fiori, A. Rivas-Delgado, A. López-Guillermo, T. Venesio, A. Sapino, E. Campo, C. Tripodo, A. Guarini, S.A. Pileri

Research output: Contribution to journalArticle

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.
Original languageEnglish
Pages (from-to)2363-2370
Number of pages8
JournalAnnals of oncology : official journal of the European Society for Medical Oncology
Volume29
Issue number12
DOIs
Publication statusPublished - 2018

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Cellular Microenvironment
Paraffin
Formaldehyde
Dissection
B-Lymphocytes
Gene Expression
Tumor Microenvironment
Survival
Genes
Myofibroblasts
Lymphoma, Large B-Cell, Diffuse
Gene Expression Profiling
Cluster Analysis
Proportional Hazards Models
Computer Simulation
Dendritic Cells
Disease-Free Survival
Extracellular Matrix
Cell Biology
Clinical Trials

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Dissection of DLBCL microenvironment provides a gene expression-based predictor of survival applicable to formalin-fixed paraffin-embedded tissue. / 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, Stefano; Rivas-Delgado, A.; López-Guillermo, A.; Venesio, T.; Sapino, A.; Campo, E.; Tripodo, C.; Guarini, A.; Pileri, S.A.

In: Annals of oncology : official journal of the European Society for Medical Oncology, Vol. 29, No. 12, 2018, p. 2363-2370.

Research output: Contribution to journalArticle

Ciavarella, S, Vegliante, MC, 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, AF, Ingravallo, G, Vitolo, U, Chiappella, A, Tarella, C, Gianni, AM, Rambaldi, A, Zinzani, PL, 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, SA 2018, 'Dissection of DLBCL microenvironment provides a gene expression-based predictor of survival applicable to formalin-fixed paraffin-embedded tissue', Annals of oncology : official journal of the European Society for Medical Oncology, vol. 29, no. 12, pp. 2363-2370. https://doi.org/10.1093/annonc/mdy450
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, Stefano ; Rivas-Delgado, A. ; López-Guillermo, A. ; Venesio, T. ; Sapino, A. ; Campo, E. ; Tripodo, C. ; Guarini, A. ; Pileri, S.A. / Dissection of DLBCL microenvironment provides a gene expression-based predictor of survival applicable to formalin-fixed paraffin-embedded tissue. In: Annals of oncology : official journal of the European Society for Medical Oncology. 2018 ; Vol. 29, No. 12. pp. 2363-2370.
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title = "Dissection of DLBCL microenvironment provides a gene expression-based predictor of survival applicable to formalin-fixed paraffin-embedded tissue",
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.",
author = "S. Ciavarella and M.C. Vegliante and M. Fabbri and {De Summa}, S. and F. Melle and G. Motta and {De Iuliis}, V. and G. Opinto and A. Enjuanes and S. Rega and A. Gulino and C. Agostinelli and A. Scattone and S. Tommasi and A. Mangia and F. Mele and G. Simone and A.F. Zito and G. Ingravallo and U. Vitolo and A. Chiappella and C. Tarella and A.M. Gianni and A. Rambaldi and P.L. Zinzani and B. Casadei and E. Derenzini and G. Loseto and A. Pileri and V. Tabanelli and Stefano Fiori and A. Rivas-Delgado and A. L{\'o}pez-Guillermo and T. Venesio and A. Sapino and E. Campo and C. Tripodo and A. Guarini and S.A. Pileri",
note = "Cited By :1 Export Date: 5 February 2019",
year = "2018",
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TY - JOUR

T1 - Dissection of DLBCL microenvironment provides a gene expression-based predictor of survival applicable to formalin-fixed paraffin-embedded tissue

AU - Ciavarella, S.

AU - Vegliante, M.C.

AU - Fabbri, M.

AU - De Summa, S.

AU - Melle, F.

AU - Motta, G.

AU - De Iuliis, V.

AU - Opinto, G.

AU - Enjuanes, A.

AU - Rega, S.

AU - Gulino, A.

AU - Agostinelli, C.

AU - Scattone, A.

AU - Tommasi, S.

AU - Mangia, A.

AU - Mele, F.

AU - Simone, G.

AU - Zito, A.F.

AU - Ingravallo, G.

AU - Vitolo, U.

AU - Chiappella, A.

AU - Tarella, C.

AU - Gianni, A.M.

AU - Rambaldi, A.

AU - Zinzani, P.L.

AU - Casadei, B.

AU - Derenzini, E.

AU - Loseto, G.

AU - Pileri, A.

AU - Tabanelli, V.

AU - Fiori, Stefano

AU - Rivas-Delgado, A.

AU - López-Guillermo, A.

AU - Venesio, T.

AU - Sapino, A.

AU - Campo, E.

AU - Tripodo, C.

AU - Guarini, A.

AU - Pileri, S.A.

N1 - Cited By :1 Export Date: 5 February 2019

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

U2 - 10.1093/annonc/mdy450

DO - 10.1093/annonc/mdy450

M3 - Article

VL - 29

SP - 2363

EP - 2370

JO - Annals of Oncology

JF - Annals of Oncology

SN - 0923-7534

IS - 12

ER -