Abstract

Multi-omics profiling by CITE-seq bridges the RNA-protein gap in single-cell analysis but has been largely applied to liquid biopsies. Applying CITE-seq to clinically relevant solid biopsies to characterize healthy tissue and the tumor microenvironment is an essential next step in single-cell translational studies. In this study, gating of cell populations based on their transcriptome signatures for use in cell type-specific ridge plots allowed identification of positive antibody signals and setting of manual thresholds. Next, we compare five skin dissociation protocols by taking into account dissociation efficiency, captured cell type heterogeneity and recovered surface proteome. To assess the effect of enzymatic digestion on transcriptome and epitope expression in immune cell populations, we analyze peripheral blood mononuclear cells (PBMCs) with and without dissociation. To further assess the RNA-protein gap, RNA-protein we perform codetection and correlation analyses on thresholded protein values. Finally, in a proof-of-concept study, using protein abundance analysis on selected surface markers in a cohort of healthy skin, primary, and metastatic melanoma we identify CD56 surface marker expression on metastatic melanoma cells, which was further confirmed by multiplex immunohistochemistry. This work provides practical guidelines for processing and analysis of clinically relevant solid tissue biopsies for biomarker discovery.

CITE-seq analysis in healthy skin, and both primary vs. metastatic melanoma samples suggests practical considerations of different skin dissociation protocols and dynamic thresholding of antibody signals for biomarker discovery.

Details

Title
Dynamic thresholding and tissue dissociation optimization for CITE-seq identifies differential surface protein abundance in metastatic melanoma
Author
Lischetti, Ulrike 1   VIAFID ORCID Logo  ; Tastanova, Aizhan 2   VIAFID ORCID Logo  ; Singer, Franziska 3   VIAFID ORCID Logo  ; Grob, Linda 3   VIAFID ORCID Logo  ; Carrara, Matteo 3 ; Cheng, Phil F. 2 ; Martínez Gómez, Julia M. 2 ; Sella, Federica 2   VIAFID ORCID Logo  ; Haunerdinger, Veronika 2 ; Beisel, Christian 4   VIAFID ORCID Logo  ; Levesque, Mitchell P. 2   VIAFID ORCID Logo 

 Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland (GRID:grid.5801.c) (ISNI:0000 0001 2156 2780); Department of Biomedicine, University Hospital Basel, University of Basel, Basel, Switzerland (GRID:grid.6612.3) (ISNI:0000 0004 1937 0642) 
 Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland (GRID:grid.7400.3) (ISNI:0000 0004 1937 0650) 
 ETH Zurich, NEXUS Personalized Health Technologies, Schlieren, Switzerland (GRID:grid.5801.c) (ISNI:0000 0001 2156 2780); SIB Swiss Institute of Bioinformatics, Zurich, Switzerland (GRID:grid.419765.8) (ISNI:0000 0001 2223 3006) 
 Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland (GRID:grid.5801.c) (ISNI:0000 0001 2156 2780) 
Pages
830
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
23993642
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2848616827
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.