PROJECT SUMMARY Diffuse Large B-Cell Lymphoma (DLBCL) is the most common form of Non-Hodgkin Lymphoma (NHL). DLBCL tumors are highly heterogeneous and molecular profiling has revealed 100s of mutations that can be clustered into five distinct prognostically relevant sub-groups, however biomarkers that include TME elements have not been developed. In our parent R01, we hypothesized that successful development of next generation immune targeting therapies for lymphoma will require spatially resolved, highly multiplexed single cell based biomarkers of TME composition and structure. For that project we proposed to perform imaging mass cytometry analysis (IMC) on over 2000 cases of aggressive B cell lymphoma with the following aims: Specific Aim 1: Validate spatially-derived protein biomarkers of DLBCL outcomes (n=830 patients). Specific Aim 2: Analyze the single cell topology of histologically diverse aggressive B cell lymphomas (n=1380) to identify shared TME based biomarkers across all aggressive B cell lymphoma. Specific Aim 3: Determine which TME elements modulate chemoresistance and mediate response to immune therapies in lymphoma through in vitro and in vitro model systems. A significant limitation of Aim 3 was that it relied on a single syngeneic model system, A20, that does not represent that genetic diversity or complexity seen in DLBCL. This was due to a major gap in the field as model systems that represent the five genetic sub-groups have not been developed. In this revision, we propose a new Aim, Revision Aim 4, where we will apply the IMAT supported technology Mosaic Analysis by Dual Recombinase-mediated cassette exchange (MADR) to rapidly develop complex genetic models of DLBCL that recapitulate the genetic diversity seen in human disease. This will allow us to perform functional validation of the spatial biomarkers we identify in Aims 1 and 2 of the parent grant in the context of each specific mutational subtype. This will significantly enhance the impact of the original grant and be the first application of MADR technology in a hematologic cancer. Once established these MADR derived mouse models will enable testing of targeted therapies in each genetic sub-group, which is currently not possible with the currently available pre-clinical models.