Abstract 7662: A high-throughput, automated, and reproducible mIF workflow for spatial biology enabled by ZEISS slide stream and Vizgen’s InSituPlex® assays.

Abstract Multiplex immunofluorescence (mIF) has become a cornerstone technique in spatial biology for investigating the tumor microenvironment. Despite its widespread use, existing mIF workflows are often hindered by variability in image acquisition and dependence on labor-intensive manual steps. To overcome these limitations, we developed a fully integrated, high-throughput spatial biology workflow combining the highly standardized and automated ZEISS spatial biology platform with Vizgen’s pre-optimized InSituPlex assay. Together, these deliver high-throughput, fully automated, and reproducible biomarker detection across a broad dynamic range, enhancing both efficiency and scalability. To validate these claims, we conducted a multisite verification study. A 4-plex OmniVUE panel including CD3, Ki67, Granzyme-B and CK/Sox10 was utilized to stain multiple tissue indications on formalin-fixed paraffin-embedded (FFPE) sections. On all sites, the slides underwent the same predefined and automated routine for staining using Leica Bond RX instruments and imaging using ZEISS Axioscan 7 spatial biology slide scanners. Acquired images were seamlessly uploaded to Mindpeak and analyzed with integrated STARVUE algorithms optimized for Vizgen InSituPlex assays imaged on Axioscan scanners, providing quantitative analysis for densities and fluorescence intensities of positive cells. Analysis of the results demonstrated excellent concordance between sites, confirming the precision and accuracy of the combined workflow across multiple operators and instruments. Qualitatively, staining was highly comparable across all sites, and the limited variations in fluorescence signal and background did not affect the accuracy of the STARVUE™ AI algorithms. Quantitatively, the presented workflow exhibits high reproducibility and repeatability of results across locations, providing a reliable solution for translational research with amplified speed and quality of data generation. As a result, it offers significant potential to advance spatial biology from translational research to clinical applications Citation Format: Cassandra Kysilovsky, Kevin Hwang, Susanne Pfeifenbring, Michael Downing, Sherry Derakhshani, Moritz Widmaier, Jiang He, Angela Vasaturo. A high-throughput, automated, and reproducible mIF workflow for spatial biology enabled by ZEISS slide stream and Vizgen’s InSituPlex® assays [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7662.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-7662
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 7662: A high-throughput, automated, and reproducible mIF workflow for spatial biology enabled by ZEISS slide stream and Vizgen’s InSituPlex® assays.

Moritz Widmaier, Susanne Pfeifenbring, Cassandra Kysilovsky, Angela Vasaturo et al.
Cancer Research
Single-cell and spatial transcriptomics
article

Abstract 7662: A high-throughput, automated, and reproducible mIF workflow for spatial biology enabled by ZEISS slide stream and Vizgen’s InSituPlex® assays.

Moritz Widmaier, Susanne Pfeifenbring, Cassandra Kysilovsky, Angela Vasaturo, Kevin Hwang, Sherry Derakhshani, Jiang He, Michael Downing
article en

Abstract

Abstract Multiplex immunofluorescence (mIF) has become a cornerstone technique in spatial biology for investigating the tumor microenvironment. Despite its widespread use, existing mIF workflows are often hindered by variability in image acquisition and dependence on labor-intensive manual steps. To overcome these limitations, we developed a fully integrated, high-throughput spatial biology workflow combining the highly standardized and automated ZEISS spatial biology platform with Vizgen’s pre-optimized InSituPlex assay. Together, these deliver high-throughput, fully automated, and reproducible biomarker detection across a broad dynamic range, enhancing both efficiency and scalability. To validate these claims, we conducted a multisite verification study. A 4-plex OmniVUE panel including CD3, Ki67, Granzyme-B and CK/Sox10 was utilized to stain multiple tissue indications on formalin-fixed paraffin-embedded (FFPE) sections. On all sites, the slides underwent the same predefined and automated routine for staining using Leica Bond RX instruments and imaging using ZEISS Axioscan 7 spatial biology slide scanners. Acquired images were seamlessly uploaded to Mindpeak and analyzed with integrated STARVUE algorithms optimized for Vizgen InSituPlex assays imaged on Axioscan scanners, providing quantitative analysis for densities and fluorescence intensities of positive cells. Analysis of the results demonstrated excellent concordance between sites, confirming the precision and accuracy of the combined workflow across multiple operators and instruments. Qualitatively, staining was highly comparable across all sites, and the limited variations in fluorescence signal and background did not affect the accuracy of the STARVUE™ AI algorithms. Quantitatively, the presented workflow exhibits high reproducibility and repeatability of results across locations, providing a reliable solution for translational research with amplified speed and quality of data generation. As a result, it offers significant potential to advance spatial biology from translational research to clinical applications Citation Format: Cassandra Kysilovsky, Kevin Hwang, Susanne Pfeifenbring, Michael Downing, Sherry Derakhshani, Moritz Widmaier, Jiang He, Angela Vasaturo. A high-throughput, automated, and reproducible mIF workflow for spatial biology enabled by ZEISS slide stream and Vizgen’s InSituPlex® assays [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 7662.

Cancer ResearchVol. 86(7_Supplement)
Carl Zeiss (Germany) (DE)
Decent work and economic growth
Openalex Percentile: Top 30%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.