Abstract Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogenous disease almost invariably treated with combinatorial chemoimmunotherapy resulting in a ~65% cure rate in first line. Further improvement of treatment outcome relies on elucidating the biology that underlies the clinical behavior of this heterogenous disease. Transcriptomic and genetic characterization of DLBCL have increased our understanding of its pathogenesis and provided potential novel therapeutic targets. Over the past few years, the role of the microenvironment in DLBCL biology has been increasingly recognized. A guiding framework is necessary to effectively and safely translate research evidence into clinical practice. Towards this goal, we characterized the DLBCL microenvironment based on the transcriptional footprint of microenvironment cells and processes in a large cohort of patients. We first developed transcriptional signatures reflecting distinct cellular subtypes of the microenvironment, biologic processes, and canonical signaling pathway activation. We then used these signatures to virtually reconstruct the lymphoma microenvironment (LME) by applying an unsupervised community detection algorithm in 4,656 DLBCL cases. As a result, we described four classes of LMEs that reflect distinct enrichment of associated signatures. 1. “Germinal center-like” (GC-like) due to the presence of signatures from cell types commonly found in germinal centers including follicular dendritic cells, lymphatic endothelial cells, total T cells, and several CD4+ T-cell subpopulations. 2. “Mesenchymal” (MS) for the abundance of signatures from stromal cells such as cancer-associated fibroblasts, fibroblastic reticular cells, vascular endothelial cells, and extracellular matrix pathways. The MS-LME class was enriched in mutations affecting antigen presentation. These lymphomas also presented with high activity of the TGFB/SMAD and HIF pathways, previously associated with favorable prognosis in DLBCL. 3. “Inflammatory” (IN) for the presence of signatures from macrophages, neutrophils, NK cells, and cytotoxic T cells. The IN-LME class was enriched for immune suppressive/pro-lymphoma cytokines, expression of the immune checkpoint molecules PD-L1 and IDO1, and higher activity of the NF-kB, JAK/STAT, and TNF signaling pathways. 4. A “depleted” (DP) form that, contrasting with the other LMEs, was characterized by an overall lower presence of microenvironment-derived signatures. We analyzed the association of LME classes with overall survival (OS) and progression-free survival (PFS) in patient cohorts of, respectively, 2,646 and 2,189 DLBCLs treated with rituximab-based chemoimmunotherapy. Analysis of OS by LME indicated significant differences in prognosis from better to poor as follows: GC-like, MS (p =0.03, vs. GC-like), IN (p = 0.006, vs. MS), and DP (p = 0.008, vs. IN) LMEs, whereas GC-like and MS have similarly favorable PFS curves (p = 0.9) followed by IN (p < 0.01) and DP (p = 0.03, vs. IN), which presented with the poorest PFS. In multivariate Cox-proportional hazard analysis controlled for C.O.O. and I.P.I., the LME subtypes remained informative with GC-like and MS LMEs associated with better outcome. When segregated by C.O.O., the DP-LME retained the poorest OS and PFS in both C.O.O. subtypes. However, in ABC-DLBCL, the LME with the best PFS and OS was MS, and in GCB-DLBCL, the best LME was GC-like, suggesting that the biologic impact of the microenvironment may be different depending on the lymphoma subtype. DHL and high-grade lymphomas (HGL) modified their outcome when LME was considered. DHL/HGL with the favorable prognosis LMEs GC-like and MS had significantly better PFS and OS than DHL/HGL with the unfavorable prognosis LMEs IN and DP. DLBCLs with a DP-LME were characterized by a minimal presence of LME signatures and tumor cells exhibited higher clonality, were enriched for mutations affecting TP53 and cell proliferation genes, as well as presented higher levels of aberrant hypermethylation of immune-related and TGFB/SMAD1 genes. Preclinical murine models and patient data demonstrated that some of these features can be pharmacologically reversed with hypomethylating agents, indicating that cytosine methylation patterning of lymphoma cells may contribute to a depleted LME. In summary, we categorized the DLBCL LME into four major transcriptionally defined subtypes with distinct biologic properties and clinical behavior, which complement genetically defined subtypes of DLBCL in guiding the development of rational therapeutic approaches for these patients. Citation Format: Leandro Cerchietti. Microenvironmental signatures reveal biologic and clinical subtypes of diffuse large B-cell lymphoma [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr IA05.