Abstract 1557: Landscape of tumor cell states and cellular ecosystems in diffuse large B cell lymphoma

Abstract The tumor microenvironment (TME) plays critical roles in cancer development, tumor progression, and susceptibility to therapy. However, the phenotypic states and interaction patterns of its underlying cell types remain poorly understood. To address this challenge, we developed a new computational framework, EcoTyper, for large-scale dissection of cell states and cellular communities (i.e., ecosystems) from tumor genomic profiles. EcoTyper integrates single-cell RNA sequencing (scRNA-seq) with CIBERSORTx, an algorithm for bulk RNA-seq deconvolution (Newman et al., Nat Biotechnol, 2019), to identify and validate cellular states and ecosystems that reflect fundamental distinctions in TME biology. Here we applied EcoTyper to diffuse large B cell lymphoma (DLBCL), an aggressive B cell malignancy with clinically distinct molecular subtypes and several immunologically-active therapies. We sought to determine whether EcoTyper could reveal novel biological variation in the DLBCL TME linked to tumor subtypes and genotypes, therapeutic responses, and clinical outcomes. We applied our approach to define transcriptional states from 13 cell types, including malignant, immune, and stromal cells, in over 1,500 DLBCL tumors. Remarkably, nearly all cell states identified by EcoTyper were validated in independent scRNA-seq and bulk RNA-seq datasets. Moreover, many cells states reflected novel phenotypic groupings, and the majority showed strong associations with overall survival, specific mutational profiles, and tumor molecular subtypes. Additionally, by identifying DLBCL tumors with similar communities of cellular states, we defined novel cellular ecosystems, or “ecotypes”, with distinct biological characteristics and clinical outcomes. Several ecotypes showed significant enrichments in canonical or novel tumor genotypes, suggesting an evolutionary interplay between the tumor and host TME. In summary, we developed a novel computational framework to dissect the TME at scale and present the most comprehensive atlas to date of cell states and cellular communities in DLBCL. Our approach is extensible to nearly any cancer type and may lead to the development of novel diagnostics and individualized immunotherapies. Citation Format: Chloe B. Steen, Bogdan Luca, Mohammad S. Esfahani, Barzin Y. Nabet, Brian Sworder, Farshad Farshidfar, David Kurtz, Chih Long Liu, Ranjana H. Advani, Yasodha Natkunam, June H. Myklebust, Maximilian Diehn, Andrew Gentles, Ash Alizadeh, Aaron M. Newman. Landscape of tumor cell states and cellular ecosystems in diffuse large B cell lymphoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1557.