Digital Quantification of Membrane DAB Immunohistochemical Staining in FFPE Cervical Cancer Tissues Using an Open-Source CellProfiler Pipeline.

Immunohistochemistry (IHC) is a highly specific and widely used laboratory technique for assessing protein localization and expression in tissue samples. Interpretation of 3,3' diamino benzidine (DAB)-based IHC is often based on observer-dependent manual scoring or traditional imaging software, which may show variability in DAB staining quantification. Furthermore, conventional image analysis tools often face limitations in precisely defining cell boundaries and quantifying membrane-specific signals. In this study, we present a standardized image analysis workflow using CellProfiler, an open-source software for image analysis for the quantification of membrane staining intensity in IHC images captured from slides prepared using formalin-fixed paraffin-embedded (FFPE) human cervical cancer tissue sections. The image analysis workflow was demonstrated using ASCT2 (SLC1A5), a membrane-localized amino acid transporter, as a representative biomarker for membrane-associated protein expression. This protocol involves image preprocessing, object identification, segmentation, and intensity measurement modules to distinguish cell membranes from cytoplasmic regions, enabling automated quantification of membrane intensity signals. The CellProfiler pipeline demonstrated improved accuracy in cell boundary identification and quantification of membrane-specific staining intensity. This is a rapid quantification process, since processing of each image only takes a few seconds; therefore, the analysis for 100 images can be performed within 10-15 min. This segmentation and quantification strategy is applicable to other membrane-based biomarkers after appropriate optimization of segmentation parameters. Following further minor modifications to the object identification modules, this pipeline can be used to detect and quantify cytoplasm- or nuclei-localized DAB-IHC markers across different tissue types. Overall, this protocol provides a standardized, user-friendly, and reproducible workflow for quantitative IHC image analysis that can be broadly applied to the study of protein biomarkers of different localizations, such as nuclei, cytoplasm, and cell membranes from different tissue types. Key features • Quantification of membrane-specific staining intensity in immunohistochemistry (IHC) images using a customized CellProfiler analysis pipeline. • Accurate delineation of cell boundaries, allowing separation of membrane and cytoplasmic signal regions. • Reproducible stepwise workflow adaptable to multiple tissue types and membrane protein biomarkers. • Applicability to studies of membrane-localized biomarkers, such as ASCT2, in cancer research.