SGPath Annual Meeting

Background:   Deciphering the tissue architecture is emerging as a crucial step to better understand tissue biology and harness it in a future therapeutic intervention [PMID:32377572]. Newly developed protocols allow detection of dozens of biomarkers simultaneously [PMID:35714588;35132261]. However, fresh frozen sections (FS) analyses remain challenging as harsh procedures used in manual protocols are detrimental to tissue morphology and limit the use of this application [PMID:34811556]. Furthermore, manual protocols are laborious and time-consuming, allowing to process a limited number of samples.  Here, we describe the capability to perform automated hyperplex assays for up to 32 biomarkers on FS as a cogent case combining staining quality with tissue preservation.   

Methods:  COMET™ platform automates sequential immunofluorescence (seqIF™) assays based on an iterative series of fast tissue staining, imaging, and antibody elution cycles. FS tissue of human and murine origins were fixed and permeabilized prior to staining protocols. Up to 32 biomarkers were detected on a single tissue slide. To assess the tissue morphology preservation, standard hematoxylin and eosin (H&E) staining was performed on FS freshly processed or post-seqIF™.   

Results:  Murine tissues were stained with panels of up to 6 proteins showing an accurate detection of both immune and organ-specific biomarkers. For a deep characterization of human lung cancer, 32 biomarkers were simultaneously detected on a single FS with optimal staining and a total procedure time of 23 hours. An H&E staining performed on the slide retrieved from the platform after the seqIF™ showed excellent preservation of the tissue architecture in comparison with an unprocessed FS slide.   

Conclusion: This work demonstrates the feasibility of performing automated hyper-plex assays on a variety of delicate frozen samples with high-quality results.  With this new toolbox, we aim to support and hasten discovery studies across multiple research fields by overcoming current limitations in spatial biology.