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Improvement of Opal Multiplex Immunofluorescence Workflow for Human Tissue Sections.

ABSTRACT: The Opal multiplex technique is an established methodology for the detection of multiple biomarkers in one section. The protocol encompasses iterative single stainings and heating-mediated removal of the primary and secondary antibodies after each staining round, leaving untouched the Opal fluorophores which are deposited onto the antigen of interest. According to our experience, repetitive heating of skin sections often results in tissue damage, indicating an urgent need for milder alternatives to strip immunoglobulins. In this study, we demonstrate that considerable heating-related damage was found not only in skin but also in tissues of different origin, mostly characterized by low cell density. Importantly, the morphology remained fully intact when sections were repetitively exposed to β-mercaptoethanol-containing stripping buffer instead of multiple heating cycles. However, target epitopes appeared sensitive at a differential degree to multiple treatments with stripping buffer, as shown by loss in staining intensity, but in all cases, the staining intensity could be restored by increment of the primary antibody concentrations. Application of β-mercaptoethanol-containing stripping buffer instead of heating for antibody removal markedly improved the quality of the Opal multiplex technique, as a substantial higher number of differently colored cells could be visualized within a well-conserved morphological context.

SUBMITTER: Willemsen M

PROVIDER: S-EPMC8091416 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:A robust understanding of the tumor immune environment has important implications for cancer diagnosis, prognosis, research, and immunotherapy. Traditionally, immunohistochemistry (IHC) has been regarded as the standard method for detecting proteins in situ, but this technique allows for the evaluation of only one cell marker per tissue sample at a time. However, multiplexed imaging technologies enable the multiparametric analysis of a tissue section at the same time. Also, through the curation of specific antibody panels, these technologies enable researchers to study the cell subpopulations within a single immunological cell group. Thus, multiplexed imaging gives investigators the opportunity to better understand tumor cells, immune cells, and the interactions between them. In the multiplexed imaging technology workflow, once the protocol for a tumor immune micro environment study has been defined, histological slides are digitized to produce high-resolution images in which regions of interest are selected for the interrogation of simultaneously expressed immunomarkers (including those co-expressed by the same cell) by using an image analysis software and algorithm. Most currently available image analysis software packages use similar machine learning approaches in which tissue segmentation first defines the different components that make up the regions of interest and cell segmentation, then defines the different parameters, such as the nucleus and cytoplasm, that the software must utilize to segment single cells. Image analysis tools have driven dramatic evolution in the field of digital pathology over the past several decades and provided the data necessary for translational research and the discovery of new therapeutic targets. The next step in the growth of digital pathology is optimization and standardization of the different tasks in cancer research, including image analysis algorithm creation, to increase the amount of data generated and their accuracy in a short time as described herein. The aim of this review is to describe this process, including an image analysis algorithm creation for multiplex immunofluorescence analysis, as an essential part of the optimization and standardization of the different processes in cancer research, to increase the amount of data generated and their accuracy in a short time.

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Improvement of Opal Multiplex Immunofluorescence Workflow for Human Tissue Sections.

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