Dissecting and Modeling Evolution of Inter- and Intra-tumoral Heterogeneity in High-Risk Diffuse Large B-cell Lymphoma

点击翻译按钮获取中文摘要

Diffuse large B-cell lymphoma is the most common form of aggressive lymph node cancer and relapsed and refractory diffuse large B-cell lymphoma (rrDLBCL) is a fatal disease with the majority of patients dying from their disease. Mechanistically this is fueled by an understudied intertumoral and intratumoral heterogeneity. Our groups dissected intertumor heterogeneity of de novo DLBCL (Chapuy et al Nat. Med. 2018) and started to explore intratumoral heterogeneity (ITH) in a pilot series of DLBCL samples, suggesting that lymphoma subpopulation of the same patients have a differential response to treatments (Roider et al. Nat. Cell Biol. 2020). Notably, C3 and C5 DLBCL subtypes are high-risk DLBCL subtypes in which, however, not all patients exhibit a dismal outcome. Here, we aim to understand this ITH and will capitalize on our previous findings and leverage a readily available unique resource of clinically annotated single-cell suspensions of primary and rrDLBCL samples, established technologies and deep modeling expertise and propose: 1) To perform an integrative multi-omics analysis to dissect the intracellular heterogeneity of genetic and TME factors in genetically high-risk C3 and C5 DLBCLs employing state-of-the-art bulk and single-cell technologies; 2) To define and model biologically relevant clonal and subclonal genetic determinants of intratumoral heterogeneity in genetically engineered cell line models and our established ex vivo LN model following exposure to targeted and classical chemotherapy agents; and, 3) To perform spatial analyses of the most parsimonious actionable signatures and to validate them in large clinically annotated lymphoma cohorts. Importantly, we propose not only to employ static multi-omics technologies, but also link the signatures to dynamic drug responses and functional measurements such as the apoptotic potential. Capitalizing on our longstanding expertise, we will also model how the dissected ITH contributes to treatment failure in high-risk C3 and C5 DLBCLs to eventually find novel avenues to target treatment failure and/or develop robust biomarkers to predict treatment failure. Notably, all data will be shared in an existing easy-to-use and yet unpublished interactive data portal, making it a unique repository for the lymphoma community.