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.
Subject(s)
Lymphoma, Large B-Cell, Diffuse/mortality , Transcriptome/genetics , Tumor Microenvironment/genetics , Adult , Aged , Algorithms , Biopsy , Cluster Analysis , Cohort Studies , Computational Biology , Datasets as Topic , Female , Gene Expression Profiling/methods , Humans , Lymphoma, Large B-Cell, Diffuse/genetics , Lymphoma, Large B-Cell, Diffuse/pathology , Male , Middle Aged , Paraffin Embedding , Predictive Value of Tests , Prognosis , Progression-Free Survival , Randomized Controlled Trials as Topic , Reproducibility of Results , Survival Analysis , Young AdultABSTRACT
Peripheral T-cell lymphomas not otherwise specified (PTCLs/NOS) are rare and aggressive tumours whose molecular pathogenesis and diagnosis are still challenging. The microRNA (miRNA) profile of 23 PTCLs/NOS was generated and compared with that of normal T-lymphocytes (CD4+, CD8+, naive, activated). The differentially expressed miRNA signature was compared with the gene expression profile (GEP) of the same neoplasms. The obtained gene patterns were tested in an independent cohort of PTCLs/NOS. The miRNA profile of PTCLs/NOS then was compared with that of 10 angioimmunoblastic T-cell lymphomas (AITLs), 6 anaplastic large-cell lymphomas (ALCLs)/ALK+ and 6 ALCLs/ALK-. Differentially expressed miRNAs were validated in an independent set of 20 PTCLs/NOS, 20 AITLs, 19 ALCLs/ALK- and 15 ALCLs/ALK+. Two hundred and thirty-six miRNAs were found to differentiate PTCLs/NOS from activated T-lymphocytes. To assess which miRNAs impacted on GEP, a multistep analysis was performed, which identified all miRNAs inversely correlated to different potential target genes. One of the most discriminant miRNAs was selected and its expression was found to affect the global GEP of the tumours. Moreover, two sets of miRNAs were identified distinguishing PTCL/NOS from AITL and ALCL/ALK-, respectively. The diagnostic accuracy of this tool was very high (83.54%) and its prognostic value validated.
Subject(s)
Gene Expression Regulation, Neoplastic , Lymphoma, T-Cell, Peripheral/diagnosis , Lymphoma, T-Cell, Peripheral/metabolism , MicroRNAs/biosynthesis , RNA, Neoplasm/biosynthesis , Female , Gene Expression Profiling/methods , Humans , Lymphoma, T-Cell, Peripheral/genetics , Male , MicroRNAs/genetics , Oligonucleotide Array Sequence Analysis/methods , RNA, Neoplasm/geneticsABSTRACT
Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare disease of controversial origin recently recognized as a neoplasm deriving from plasmacytoid dendritic cells (pDCs). Nevertheless, it remains an orphan tumor with obscure biology and dismal prognosis. To better understand the pathobiology of BPDCN and discover new targets for effective therapies, the gene expression profile (GEP) of 25 BPDCN samples was analyzed and compared with that of pDCs, their postulated normal counterpart. Validation was performed by immunohistochemistry (IHC), whereas functional experiments were carried out ex vivo. For the first time at the molecular level, we definitely recognized the cellular derivation of BPDCN that proved to originate from the myeloid lineage and in particular, from resting pDCs. Furthermore, thanks to an integrated bioinformatic approach we discovered aberrant activation of the NF-kB pathway and suggested it as a novel therapeutic target. We tested the efficacy of anti-NF-kB-treatment on the BPDCN cell line CAL-1, and successfully demonstrated by GEP and IHC the molecular shutoff of the NF-kB pathway. In conclusion, we identified a molecular signature representative of the transcriptional abnormalities of BPDCN and developed a cellular model proposing a novel therapeutic approach in the setting of this otherwise incurable disease.
