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      Digital quantification of somatostatin receptor subtype 2a immunostaining: a validation study

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          Abstract

          Objective

          The aim of this study was to develop an open-source and reproducible digital quantitative analysis (DIA) of somatostatin receptor subtype 2a (SST 2) staining in formalin-fixed paraffin-embedded tissues of pancreatic neuroendocrine tumors (panNETs) and growth hormone (GH)-secreting pituitary adenomas (GHomas).

          Design

          SST 2 immunostaining of 18 panNETs and 39 GHomas was assessed using a novel DIA protocol and compared with a widely used semi-quantitative immunoreactivity score (IRS).

          Methods

          The DIA software calculates the staining intensity/area and the percentage of positive cells (%PC). Four representative images were selected for each sample by two independent selectors (S 1 and S 2), with the analysis performed by two independent analyzers (A 1 and A 2). Agreement between observers was calculated using the concordance correlation coefficient (CCC).

          Results

          In panNETs, the CCC ranged 0.935–0.977 for intensity/area and 0.942–0.983 for %PC. In GHomas, the CCC ranged 0.963–0.997 for intensity/area and 0.979–0.990 for %PC. In both panNETs and GHomas, the DIA staining intensity was strongly correlated with the IRS (Spearman rho: 0.916–0.969, P < 0.001), as well as the DIA %PC with the IRS %PC (Spearman rh: 0.826–0.881, P < 0.001). In GHomas, the biochemical response to somatostatin receptor ligands correlated with SST 2 expression, evaluated both as DIA intensity/area (Spearman rho: −0.448 to −0.527, P = 0.007–0.004) and DIA %PC (Spearman rho: −0.558 to −0.644, P ≤ 0.001).

          Conclusions

          The DIA has an excellent inter-observer agreement and showed a strong correlation with the widely used semi-quantitative IRS. The DIA protocol is an open-source, highly reproducible tool and provides a reliable quantitative evaluation of SST 2 immunohistochemistry.

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          Most cited references32

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          Is Open Access

          CellProfiler 4: improvements in speed, utility and usability

          Background Imaging data contains a substantial amount of information which can be difficult to evaluate by eye. With the expansion of high throughput microscopy methodologies producing increasingly large datasets, automated and objective analysis of the resulting images is essential to effectively extract biological information from this data. CellProfiler is a free, open source image analysis program which enables researchers to generate modular pipelines with which to process microscopy images into interpretable measurements. Results Herein we describe CellProfiler 4, a new version of this software with expanded functionality. Based on user feedback, we have made several user interface refinements to improve the usability of the software. We introduced new modules to expand the capabilities of the software. We also evaluated performance and made targeted optimizations to reduce the time and cost associated with running common large-scale analysis pipelines. Conclusions CellProfiler 4 provides significantly improved performance in complex workflows compared to previous versions. This release will ensure that researchers will have continued access to CellProfiler’s powerful computational tools in the coming years. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04344-9.
            • Record: found
            • Abstract: not found
            • Article: not found

            [Recommendation for uniform definition of an immunoreactive score (IRS) for immunohistochemical estrogen receptor detection (ER-ICA) in breast cancer tissue].

              • Record: found
              • Abstract: not found
              • Article: not found

              Gastroenteropancreatic neuroendocrine neoplasms: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up

                Author and article information

                Journal
                Eur J Endocrinol
                Eur J Endocrinol
                EJE
                European Journal of Endocrinology
                Bioscientifica Ltd (Bristol )
                0804-4643
                1479-683X
                30 June 2022
                01 September 2022
                : 187
                : 3
                : 399-411
                Affiliations
                [1 ]Division of Endocrinology , Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
                [2 ]Endocrinology Unit , Department of Internal Medicine and Medical Specialties, School of Medical and Pharmaceutical Sciences, University of Genova, Genova, Italy
                [3 ]Department of Pathology , Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands
                [4 ]Endocrinology Unit , IRCCS Ospedale Policlinico San Martino, Genova, Italy
                Author notes
                Correspondence should be addressed to L J Hofland; Email: l.hofland@ 123456erasmusmc.nl

                *(F Gatto and L J Hofland contributed equally as senior authors)

                Author information
                http://orcid.org/0000-0003-4974-2075
                http://orcid.org/0000-0002-4897-2197
                Article
                EJE-22-0339
                10.1530/EJE-22-0339
                9346267
                35895707
                fba8e544-83f4-48e5-bdcd-b26cf20b564d
                © The authors

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 27 April 2022
                : 30 June 2022
                Categories
                Original Research

                Endocrinology & Diabetes
                Endocrinology & Diabetes

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