henhaobio
Sign in

bioRxivCancer Biology

Fully Automated Sequential Immunofluorescence (seqIF) for Hyperplex Spatial Proteomics

F. Rivest, D. Eroglu, B. Pelz, J. Kowal, A. Kehren, M. G. Procopio, P. Bordignon, E. Peres, M. Ammann, E. Dorel, S. Scalmazzi, L. Bruno, M. Ruegg, G. Campargue, G. Casqueiro, L. Arn, J. Fischer, S. Brajkovic, P. Joris, M. Cassano, D. Dupouy

PDFDOIPreprint

Abstract

Tissues are complex environments where different cell types are in constant interaction with each other and with non-cellular components. Preserving the spatial context during proteomics analyses of tissue samples has become an important objective for different applications, one of the most important being the investigation of the tumor microenvironment. Here, we describe a multiplexed protein biomarker detection method on the COMET instrument, coined sequential ImmunoFluorescence (seqIF). The fully automated method uses successive applications of antibody incubation and elution, and in-situ imaging enabled by an integrated microscope and a microfluidic chip that provides optimized optical access to the sample. We show seqIF data on different sample types such as tumor and healthy tissue, including 40-plex on a single tissue section that is obtained in less than 24 hours, using off-the-shelf antibodies. We also present extensive characterization of the developed method, including elution efficiency, epitope stability, repeatability and reproducibility, signal uniformity, and dynamic range, in addition to marker and panel optimization strategies. The streamlined workflow using off-the-shelf antibodies, data quality enabling quantitative downstream analysis, and ease of reaching hyperplex levels make seqIF suitable for immune-oncology research and other disciplines requiring spatial analysis, paving the way for its adoption in clinical settings.

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISMeyer-Bende '26Rajagopalan '20Anderson '25Kohman '20Xiao '24Bolognesi '24
65% semantic matchBioinformatics
Matthias Meyer-Bender, Harald S. Vöhringer, Christina Schniederjohann+21 more·Nature Methods·Jul 24, 2026· 4 citations