Abstract 4158: Cell lines as quality controls for Quantitative Continuous Scoring (QCS) of IHC stained samples

Abstract Background: Effectively measuring therapeutic target expression is critical in oncology for precise and accurate patient selection. Target expression is often measured by immunohistochemistry (IHC) using visual pathology scoring; however, digital pathology-based Quantitative Continuous Scoring (QCS) has emerged as a more precise and accurate alternative1. Given that IHC assays and whole slide image (WSI) scanners have known variability, we designed a proof-of-concept study to evaluate the applicability of using cell lines as quality controls for QCS scoring of IHC stained samples. Methods: A panel of cell lines (N=10) were selected to represent a broad range of target expression and cultured as cell pellets into a Formalin-Fixed Paraffin Embedded (FFPE) Cell Micro Array (CMA) for downstream IHC analysis with QCS. The CMA was sectioned (4 µm) and stained with a target antibody according to standard protocols. The stained slides were scanned at 40x, and images were analyzed using a trained QCS deep-learning based QCS model that quantifies membrane staining intensity (SI). Results: Cell line controls showed highly consistent QCS staining intensity (SI) scores through the entire CMA block (n=40 sections). SI from triplicates run on the same day were compared among each other or across days with a coefficient of variation (CV) <10% for each cell line, demonstrating a high level of precision and reproducibility through the entire cell line pellet. Additionally, cell density was also consistent throughout the FFPE block. Moreover, we observed highly significant correlation (R=0.98) between QCS SI and mass-spectrometry results, thus demonstrating specificity for assessing target expression in cell lines. Finally, early experiments with contrived assay variability showed the ability of cell lines to track the 32% contrived variability observed in tissue and correct that variability to 7%, thus supporting the use of cell lines to potentially improve IHC/QCS precision and reproducibility. Conclusion: These data support the feasibility of using cell lines as qualitative controls for QCS scoring of IHC stained samples. Given that heterogeneity of expression is not a significant factor like it is in tissue, cell lines provide consistent expression throughout the entire block with a high degree of precision and reproducibility. These data thus support the potential for integrating cell line controls into the quality assurance pipeline for QCS-based IHC measurements in the laboratory setting. Further, cell line quality controls could also be used for bridging and comparability, thus enabling efficient and robust development of QCS assays.1 Kapil et al. “HER2 quantitative continuous scoring for accurate patient selection in HER2 negative trastuzumab deruxtecan treated breast cancer”. Nature Sci Rep. 2024 May 27;14(1):12129. Citation Format: Ana Hidalgo-Sastre, Tze Heng Tan, Nicolas Giraldo, Nathalie Harder, Sophia Varriano, Andrew Kunihiro, Guenter Schmidt, Hadassah Sade, Yeoun Jin Kim, Marlon Rebelatto, Mark Gustavson. Cell lines as quality controls for Quantitative Continuous Scoring (QCS) of IHC stained samples [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 4158.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-4158
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 4158: Cell lines as quality controls for Quantitative Continuous Scoring (QCS) of IHC stained samples

Hadassah Sade, Tze Heng Tan, Yeoun Jin Kim, Sophia Varriano et al.
Cancer Research
Cell Image Analysis Techniques
article

Abstract 4158: Cell lines as quality controls for Quantitative Continuous Scoring (QCS) of IHC stained samples

Hadassah Sade, Tze Heng Tan, Yeoun Jin Kim, Sophia Varriano, A. Kunihiro, Nicolás A. Giraldo, Nathalie Harder, Guenter Schmidt, Marlon C. Rebelatto, M. Gustavson, Ana Hidalgo-Sastre
article en

Abstract

Abstract Background: Effectively measuring therapeutic target expression is critical in oncology for precise and accurate patient selection. Target expression is often measured by immunohistochemistry (IHC) using visual pathology scoring; however, digital pathology-based Quantitative Continuous Scoring (QCS) has emerged as a more precise and accurate alternative1. Given that IHC assays and whole slide image (WSI) scanners have known variability, we designed a proof-of-concept study to evaluate the applicability of using cell lines as quality controls for QCS scoring of IHC stained samples. Methods: A panel of cell lines (N=10) were selected to represent a broad range of target expression and cultured as cell pellets into a Formalin-Fixed Paraffin Embedded (FFPE) Cell Micro Array (CMA) for downstream IHC analysis with QCS. The CMA was sectioned (4 µm) and stained with a target antibody according to standard protocols. The stained slides were scanned at 40x, and images were analyzed using a trained QCS deep-learning based QCS model that quantifies membrane staining intensity (SI). Results: Cell line controls showed highly consistent QCS staining intensity (SI) scores through the entire CMA block (n=40 sections). SI from triplicates run on the same day were compared among each other or across days with a coefficient of variation (CV) <10% for each cell line, demonstrating a high level of precision and reproducibility through the entire cell line pellet. Additionally, cell density was also consistent throughout the FFPE block. Moreover, we observed highly significant correlation (R=0.98) between QCS SI and mass-spectrometry results, thus demonstrating specificity for assessing target expression in cell lines. Finally, early experiments with contrived assay variability showed the ability of cell lines to track the 32% contrived variability observed in tissue and correct that variability to 7%, thus supporting the use of cell lines to potentially improve IHC/QCS precision and reproducibility. Conclusion: These data support the feasibility of using cell lines as qualitative controls for QCS scoring of IHC stained samples. Given that heterogeneity of expression is not a significant factor like it is in tissue, cell lines provide consistent expression throughout the entire block with a high degree of precision and reproducibility. These data thus support the potential for integrating cell line controls into the quality assurance pipeline for QCS-based IHC measurements in the laboratory setting. Further, cell line quality controls could also be used for bridging and comparability, thus enabling efficient and robust development of QCS assays.1 Kapil et al. “HER2 quantitative continuous scoring for accurate patient selection in HER2 negative trastuzumab deruxtecan treated breast cancer”. Nature Sci Rep. 2024 May 27;14(1):12129. Citation Format: Ana Hidalgo-Sastre, Tze Heng Tan, Nicolas Giraldo, Nathalie Harder, Sophia Varriano, Andrew Kunihiro, Guenter Schmidt, Hadassah Sade, Yeoun Jin Kim, Marlon Rebelatto, Mark Gustavson. Cell lines as quality controls for Quantitative Continuous Scoring (QCS) of IHC stained samples [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 4158.

Cancer ResearchVol. 86(7_Supplement)
AstraZeneca (Japan) (JP), AstraZeneca (Spain) (ES), AstraZeneca (Germany) (DE)
Openalex Percentile: Top 27%
Cell Image Analysis Techniques
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.