Interactive flow cytometry analysis software allows users to make binary decisions on immunomarker status of single cells through arbitrary placement of one- and two- dimensional gates. However, manual gating through a point-and-click graphical user interface (GUI) is impractical for large datasets. Here we describe SYLARAS, a suite of experimental and computational tools for the systematic and chronological evaluation of lymphoid tissue architecture. SYLARAS takes multiplex single-cell data as input, bins cells in n-dimensional orthant space, and returns schematized summary statistics on immunophenotypes of interest. We programmatically curated data on 33 immunophenotypes constituting primary and secondary lymphoid tissue of immunocompetent mice bearing syngeneic, orthotopic glioblastoma (GBM) at 3 stages of tumor growth. SYLARAS permitted the discovery of tumor-induced immune signatures whose divergence from mock engrafted, age-matched controls was quantified and statistically analyzed. By integrating information on peripheral immune composition with the levels of 111 blood cytokines of the same mice, we uncovered novel cell types, cytokines, and correlation networks perturbed by the mouse GL261 glioma model. SYLARAS facilitates the discovery of immune regulatory mechanisms and their response to therapy and is broadly applicable to the fields of immuno-oncology, autoimmunity, and infectious disease.

Citation Format: Gregory J. Baker, Sucheendra K. Palaniappan, Jodene K. Moore, Stephanie H. Davis, Peter K. Sorger. Systemic lymphoid architecture response assessment (SYLARAS): Application to system-wide immunophenotyping of glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5670.