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745 High throughput tissue imaging and phenotyping by streamlined 8-plex staining and analysis of complex TMA samples
  1. Amanda Bares1,
  2. Marie Cumberbatch2,
  3. Lorcan Sherry3,
  4. Christopher Womack2,
  5. Milan Bhagat2,
  6. Angela Vasaturo1 and
  7. Mael Manesse1
  1. 1Ultivue, Inc, Cambridge, MA, USA
  2. 2TriStar Technology Group, LLC, Washington DC, DC, USA
  3. 3OracleBio, North Lanarkshire, UK


Conclusions In this study, we highlighted the benefits of using a combination of well-characterized TMAs, a fast, optimized 8-plex mIHC protocol, and a detailed analysis pipeline to characterize the immune-response in a broad range of cancer types and samples, leading to a better understanding of the TME as well as a streamlined workflow for further translational studies.

Results Immune cell counts and phenotypes were identified using automated analysis for cores within the tumor and within the tumor margin using a panel characterizing a range of immune cell populations, and compared across each tissue type. Deep phenotyping was performed for each core to identify unique profiles for each tissue type, with a workflow optimized for high-throughput analysis of rich-content TMAs.

Methods Each slide comprised 144 cores (1 mm) and included duplicate cores for each case (1 from invasive margin; 1 from tumor center) from 11 different tumor types including breast cancer (ER+, Her2+, TNBC), NSCLC (squamous, adenocarcinoma), SCLC, CRC, pancreatic, gastric, hepatic and esophageal cancers. TMA sections were stained using the UltiMapper I/O Immuno8 panel, which includes markers for CD3, CD4, CD8, FOXP3, CD68, PD-1, PD-L1, and a pan-CK/SOX10 cocktail as a tumor indicator. The stained TMAs were scanned at 20X magnification on a fluorescence whole slide scanner. To provide accurate marker colocalization data, marker images were aligned using the UltiStacker software, using the nuclear counterstain images as references from multiple rounds of imaging. Image analysis was performed using Visiopharm software and generated total and negative cell phenotype counts, cell density in tumor and stroma, as well as spatial interactions maps in each of the 288 cores in the TMA set.

Background Multiplex immunohistochemistry (mIHC) and associated data analysis methods are rapidly becoming invaluable tools to improve our understanding of the complex tumor micro-environment (TME) and accelerate the discovery of novel immunotherapy targets. These techniques can enable the accurate phenotyping of the immune response and checkpoint expression in the spatial context of the tumor. The goal of this study was to identify the populations of immune cells (T-cytotoxic, T-helper, T-reg, and macrophages), their functional status, as well as their interactions with the tumor, in a range of samples and indications using a carefully designed multi-tumor Tissue Micro-Array (TMA) set of 2 slides from TriStar.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:

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