Abstract 2679: Immuno-oncology panel optimization for imaging mass cytometry and digital image analysis of tumor tissues

Abstract

Abstract Introduction: Imaging mass cytometry (IMC) enables highly multiplexed assessment of more than 30 proteins at a time for the quantification of cell phenotypes within the tumor microenvironment of formaldehyde fixed-paraffin embedded (FFPE) tumor tissue. This methodology provides a deep understanding of the immune-contexture while preserving their spatial information in regards to malignant cells. We report a detailed workflow for optimization of a 27-plex immune-oncology (IO) panel, immune-phenotyping, and spatial analysis of tumor tissue. Methods: IO-panel includes 27 antibodies targeting lymphoid (CD3e, CD4, CD8a, CD19, CD45RO, LAG3, ICOS, Granzyme-B), myeloid (CD11b, CD14, CD33, CD68, CSF1R, IDO-1), immune-regulatory (HLA-DR, OX-40, VISTA, TIM-3, CD73, B7-H3), epithelial (Cytokeratin), proliferative (Ki-67), and constitutive (GAPDH, NaKATPase, Vimentin, aSMA, Histone H3) markers that were selected by singlet automated chromogenic immunohistochemistry (IHC) staining. BSA-free formulation from the same clones of antibodies were isotope-metal conjugated and manual indirect immunofluorescence (IF) staining was used to confirm the stability of metal-tagged antibodies. The optimization by singlet-IF and multiplexed-IMC staining was performed with normal and malignant tissues (4mm core TMA with tonsil, placenta, prostate, breast carcinoma, ovarian carcinoma, and endometrioid carcinoma tissues). All images from IHC (HALO software), indirect IF (InForm software), and IMC (MCD viewer software) slides were evaluated by two pathologists. Cell densities and spatial analysis of a breast carcinoma core was performed using HALO software. Results: All antibodies included in the panel were individually optimized by IHC under the same protocol conditions. A significant correlation of optimal antibody concentrations where observed across the different staining techniques (IHC vs IF, r=0.51; IHC vs IMC, r= 0.54; IF vs IMC, r=0.992; all p values <0.01). The breast carcinoma core (total area=0.308mm2) was segmented into epithelial (area=0.216 mm2) and stroma (area=0.092mm2) compartments by digital image analysis. Individual cell segmentation was obtained with based on iridium nuclei signal (total cells=2420). Automated immune-phenotyping showed 20 different cell phenotypes with a predominance of malignant cells expressing B7-H3 (120.1 cells/mm2) and T-lymphocytes expressing LAG3 (3.2 cells/mm2). The average distance between proliferative cytotoxic T-lymphocytes to malignant cells (MCs) was higher when MCs were proliferating (22.94 μm, and 55.4 μm, respectively). Conclusions: IMC is a powerful platform for highly multiplexed detection of protein and cell phenotypes quantification in FFPE samples. Our developed IMC panel and digital image analysis of tissues allow the quantification of immune cells and spatial analysis of the tumor tissue microenvironment. Citation Format: Pedro Rocha, Luisa Solis, Edwin Parra, Ou Shi, Barbara Mino, Vidya C. Sinha, Amanda Rinkenbaugh, Auriole Tamegnon, Mak Duncan, Wei Lu, Mei Jiang, Lakshimi Kakarala, Jared K. Burks, Helen Piwnica-Worms, Cara Haymacker, Michael Teztlaff, Ignacio Wistuba, Alejandro Francisco-Cruz. Immuno-oncology panel optimization for imaging mass cytometry and digital image analysis of tumor tissues [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 2679.