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Multiplex immunofluorescence staining and image analysis assay for diffuse large B cell lymphoma

Authors: Lee, Chung Wein; Ren, Yan J.; Marella, Mathieu; Wang, Maria; Hartke, James; Couto, Suzana S.

Online: https://linkinghub.elsevier.com/retrieve/pii/S002217591930287X

Issue: J Immunol Methods. 2020 Mar;478:112714.


With the explosion of immuno-oncology and the approval of many immune checkpoint therapies by regulatory agencies in the last few years, understanding the tumor microenvironment (TME) in the context of patients’ immune status has become essential. Among available immune profiling techniques, multiplex immunofluorescence (mIF) assays offer the unique advantage of preserving the architectural features of the tumor and revealing the spatial relationships between tumor cells and immune cells. A number of mIF and image analysis assays have been described for solid tumors but most are not sufficiently suitable in lymphoma, where the lack of clear tumor-stromal boundaries and high tumor density present significant challenges. Here we describe the development and optimization of a reliable workflow using Akoya Opal staining kits to label and analyze 6 markers per slide in diffuse large B-cell lymphoma (DLBCL) tissue sections. Five panels totaling 30 markers were developed to characterize infiltrating immune cells and relevant check-point proteins such as PD1, PD-L1, ICOS, SIRP-alpha and Lag3 on 70 DLBCL sections. Multiplexed sections were scanned using an Akoya multispectral scanner. An image analysis workflow using InForm and Matlab was developed to overcome challenges inherent to the DLBCL environment. Using the assays and workflows detailed here, we were able to quantify cell densities of subsets of infiltrating immune cells and observe their spatial patterns within the tumors. We highlight heterogeneous distribution of cytotoxic T cells across tumors with similar T cell density to underscores the importance of considering spatial context when studying the effects of immunological therapies in DLBCL.

Keywords: Digital pathology; Image analysis; Immunophenotyping; Lymphoma; Multiplex immunofluorescence; Multispectral imaging.