IntroductionAccurate assessment of estrogen receptor (ER), progesterone receptor (PR), and Ki-67 is essential in the histopathologic diagnostics of breast cancer. Commercially available image analysis systems are usually bundled with dedicated analysis hardware and, to our knowledge, no easily installable, free software for immunostained slide scoring has been described. In this study, we describe a free, Internet-based web application for quantitative image analysis of ER, PR, and Ki-67 immunohistochemistry in breast cancer tissue sections.MethodsThe application, named ImmunoRatio, calculates the percentage of positively stained nuclear area (labeling index) by using a color deconvolution algorithm for separating the staining components (diaminobenzidine and hematoxylin) and adaptive thresholding for nuclear area segmentation. ImmunoRatio was calibrated using cell counts defined visually as the gold standard (training set, n = 50). Validation was done using a separate set of 50 ER, PR, and Ki-67 stained slides (test set, n = 50). In addition, Ki-67 labeling indexes determined by ImmunoRatio were studied for their prognostic value in a retrospective cohort of 123 breast cancer patients.ResultsThe labeling indexes by calibrated ImmunoRatio analyses correlated well with those defined visually in the test set (correlation coefficient r = 0.98). Using the median Ki-67 labeling index (20%) as a cutoff, a hazard ratio of 2.2 was obtained in the survival analysis (n = 123, P = 0.01). ImmunoRatio was shown to adapt to various staining protocols, microscope setups, digital camera models, and image acquisition settings. The application can be used directly with web browsers running on modern operating systems (e.g., Microsoft Windows, Linux distributions, and Mac OS). No software downloads or installations are required. ImmunoRatio is open source software, and the web application is publicly accessible on our website.ConclusionsWe anticipate that free web applications, such as ImmunoRatio, will make the quantitative image analysis of ER, PR, and Ki-67 easy and straightforward in the diagnostic assessment of breast cancer specimens.

Bone morphogenetic proteins (BMP) are extracellular signaling molecules that belong to the transforming growth factor β (TGFβ) superfamily. Bone morphogenetic proteins have diverse roles during development where they regulate proliferation, differentiation, and apoptosis in many different cell types by modulating the transcription of specific target genes. BMPs have also been implicated in both promotion and inhibition of cancer progression. We have recently shown that BMP4 is commonly expressed in breast cancer but its functional significance has not been previously explored. Our data demonstrate that in all nine breast cancer cell lines studied, BMP4 treatment leads to a dramatic growth suppression as a result of the induction of G1 arrest of the cell cycle. At the same time, BMP4 stimulates cell migration and invasion in a subset of these breast cancer cell lines. The BMP4-induced phenotypic changes were mediated through the activation of the canonical SMAD signaling pathway whereas no activation of MAP-kinases ERK1/2 or p38 was detected. Our results thus implicate that BMP4 is an important regulator of key phenotypic characteristics of cancer cells, cell growth, cell migration, and invasion, and that, similar to TGFβ, it possesses both tumor suppressive and oncogenic properties in breast cancer.

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We anticipate that publicly available web applications, such as ImmunoMembrane, will accelerate the adoption of automated image analysis in clinical diagnostics of HER2 IHC. ImmunoMembrane is freely accessible at: http://jvsmicroscope.uta.fi/immunomembrane/.

Evaluation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) is subject to interobserver variation and lack of reproducibility. Digital image analysis (DIA) has been shown to improve the consistency and accuracy of the evaluation and its use is encouraged in current testing guidelines. We studied whether digital image analysis using a free software application (ImmunoMembrane) can assist in interpreting HER2 IHC in equivocal 2+ cases. We also compared digital photomicrographs with whole-slide images (WSI) as material for ImmunoMembrane DIA. We stained 750 surgical resection specimens of invasive breast cancers immunohistochemically for HER2 and analysed staining with ImmunoMembrane. The ImmunoMembrane DIA scores were compared with the originally responsible pathologists' visual scores, a researcher's visual scores and in situ hybridisation (ISH) results. The originally responsible pathologists reported 9.1 % positive 3+ IHC scores, for the researcher this was 8.4 % and for ImmunoMembrane 9.5 %. Equivocal 2+ scores were 34 % for the pathologists, 43.7 % for the researcher and 10.1 % for ImmunoMembrane. Negative 0/1+ scores were 57.6 % for the pathologists, 46.8 % for the researcher and 80.8 % for ImmunoMembrane. There were six false positive cases, which were classified as 3+ by ImmunoMembrane and negative by ISH. Six cases were false negative defined as 0/1+ by IHC and positive by ISH. ImmunoMembrane DIA using digital photomicrographs and WSI showed almost perfect agreement. In conclusion, digital image analysis by ImmunoMembrane can help to resolve a majority of equivocal 2+ cases in HER2 IHC, which reduces the need for ISH testing.