56 Quantitative evaluation of the tissue micro-environment by high-resolution 17-plex immunofluorescence reveals distinct cell populations

病理 激光捕获显微切割 CD8型 CD38 生物 医学 免疫系统 免疫学 川地34 细胞生物学 干细胞 生物化学 基因 基因表达
作者
Kyla Teplitz,Daniel Campton,Erin McCarty,Jeremy Cooper,Anne Hellebust,Donald M. Allen,Kimberly Collins,Kate Lillard,Eric Kaldjian,Tad George
出处
期刊: 卷期号:: A64-A64
标识
DOI:10.1136/jitc-2021-sitc2021.056
摘要

Background

Inflammatory tumor micro-environments contain cells of various types and sub-types. The composition and spatial location of the cell populations reflects the host reaction to the inflammatory stimulus and increasingly is understood to influence responsiveness to tumor immunotherapies. Multiplexed imaging technologies allow identification of cell types and states within the spatial context of tissue architecture. We present here a prototype workflow that combines rapid high-resolution, whole-slide highly multiplexed immunofluorescence imaging with advanced image analysis tools for 1) segmenting tissues, cells, and quantifying cellular phenotypes based on multiple markers and 2) determining regional densities and proximity between cells. We apply the workflow to comparative assessment of three lymphoid tissues: tonsil (follicular hyperplasia); lymph node (quiescence); lymphoma (architectural effacement).

Methods

Formalin-fixed, paraffin-embedded 5 micron sections of tonsil, lymph node and chronic lymphocytic leukemia/small lymphocytic lymphoma were deparaffinized, subjected to alkaline pH epitope retrieval, and then manually stained with a 17-plex panel including CD45 (leukocytes); CD20 (B cells); CD3d, CD4, CD8 (T cells); FOXP3 (T reg cells); CD68, CD163 (macrophages); CD45RO (activated cells); PD-L1, PD-1 (checkpoint markers); CD31 (vascular and lymphatic endothelial cells); cytokeratin, E-cadherin (epithelial cells); PCNA, Ki-67 (proliferating cells); and a nuclear dye. Stained slides were coverslipped and imaged on the Orion Instrument (RareCyte) generating .ome tiff image files. The HighPlex FL module of the HALO image analysis platform from Indica Labs with embedded HALO AI performed nuclear and cell segmentation, nuclear phenotyping, and user-defined thresholds were applied to each of the biomarkers to define positivity for the appropriate subcellular localization (nuclear, cytoplasmic, and/or membrane) for phenotypic analysis. H & E images from either the same or serial sections were integrated with the multiplex images using the HALO Serial Stain module.

Results

Regional masks that were defined by predominance of B-cells (CD20) or T-cells (CD3d) matched known lymphoid micro-anatomy of follicles and inter-follicular cortex respectively. Within the regions, populations and sub-populations of B-cells, T-cells, macrophages and vessels were measured, and their densities calculated and compared between tissues. Rare cell types of potential importance in immuno-oncology were investigated. The results demonstrate differences between the tissues at a phenotypic level that correspond to the morphologic differences seen by light microscopy.

Conclusions

Orion imaging combined with HALO image analysis provides a powerful and intuitive workflow for visualization and quantification of distinct microenvironment populations for use in translational and clinical research.

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