BackgroundGene 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 methodsHere, 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.ConclusionsOur 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.

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Induction of apoptosis seems to be a key function in maintaining normal cell growth by exerting negative controls on cell proliferation and suppressing tumorigenesis. The adenovirus E1A oncogene shows both cell cycle progression and apoptotic functions. To understand the mechanism of E1A-induced apoptosis, the apoptotic function of E1A 13S was investigated in p53-null cells. We show here that E1A is sufficient by itself to induce substantial apoptosis independent of p53 and other adenoviral genes. The apoptotic function of E1A is accompanied by processing of caspase-3 and cleavage of poly(ADP-ribose)-polymerase. Cell death is significantly blocked by the caspase inhibitor zVAD-fmk and when coexpressed with E1B19K, Bcl-2 or the retinoblastoma protein (RB). Analyses of E1A mutants indicated that the apoptotic activity of E1A correlates closely with the ability to bind the key regulators of E2F1-induced apoptosis, p300 and RB. Finally, in vivo relevance of down-modulation of p53-independent apoptosis for efficient transformation is demon-