Semi-automated imaging system to quantitate estrogen and progesterone receptor immunoreactivity in human breast cancer

Geometric tumor embolic budding characterizes inflammatory breast cancer

PURPOSE

Inflammatory breast cancer (IBC) is characterized by numerous tumor emboli especially within dermal lymphatics. The explanation remains a mystery.

METHODS

This study combines experimental studies with two different IBC xenografts with image algorithmic studies utilizing human tissue microarrays (TMAs) of IBC vs non-IBC cases to support a novel hypothesis to explain IBC's sina qua non signature of florid lymphovascular emboli.

RESULTS

In the human TMAs, compared to tumor features like nuclear grade (size), mitosis and Ki-67 immunoreactivity which show that IBC is only modestly more proliferative with larger nuclei than non-IBC, what really sets IBC apart is the markedly greater number of tumor emboli and distinctly smaller emboli whose numbers indicate geometric or exponential differences between IBC and non-IBC. In the experimental xenograft studies, Mary-X gives rise to tight spheroids in vitro which exhibit dynamic budding into smaller daughter spheroids whereas Karen-X exhibits only loose non-budding aggregates. Furthermore Mary-X emboli also bud dramatically into smaller daughter emboli in vivo. The mechanism that regulates this involves the generation of E-cad/NTF1, a calpain-mediated cleavage 100 kDa product of 120 kDa full length membrane E-cadherin. Inhibiting this calpain-mediated cleavage of E-cadherin by blocking either the calpain site of cleavage (SC) or the site of binding (SB) with specific decapeptides that both penetrate the cell membrane and mimic either the cleavage site or the binding site on E-cadherin, inhibits the generation of E-cad/NTF1 in a dose-dependent manner, reduces spheroid compactness and decreases budding.

CONCLUSION

Since E-cad/NFT1 retains the p120ctn binding site but loses the α-and β-catenin sites, promoting its 360° distribution around the cell's membrane, the vacilating levels of this molecule trigger budding of both the spheroids as well as the emboli. Recurrent and geometric budding of parental emboli into daughter emboli then would account for the plethora of emboli seen in IBC.

Regulation of breast cancer oncogenesis by the cell of origin's differentiation state

Human breast cancer which affects 1/8 women is rare at a cellular level. Even in the setting of germline BRCA1/BRCA2, which is present in all breast cells, solitary cancers or cancers arising at only several foci occur. The overwhelming majority of breast cells (10⁹-10¹² cells) resist transformation. Our hypothesis to explain this rareness of transformation is that mammary oncogenesis is regulated by the cell of origin's critical window of differentiation so that target cells outside of this window cannot transform. Our novel hypothesis differs from both the multi-hit theory of carcinogenesis and the stem/progenitor cell compartmental theory of tumorigenesis and utilizes two well established murine transgenic models of breast oncogenesis, the FVB/N-Tg (MMTV-PyVT)634Mul/J and the FVB-Tg (MMTV-ErbB2) NK1Mul/J. Tail vein fibroblasts from each of these transgenics were used to generate iPSCs. When select clones were injected into cleared mammary fat pads, but not into non-orthotopic sites of background mice, they exhibited mammary ontogenesis and oncogenesis with the expression of their respective transgenes. iPSC clones, when differentiated along different non-mammary lineages in vitro, were also not able to exhibit either mammary ontogenesis or oncogenesis in vivo. Therefore, in vitro and in vivo regulation of differentiation is an important determinant of breast cancer oncogenesis.

Overexpression of collagen type V α1 chain in human breast invasive ductal carcinoma is mediated by TGF-β1

Collagen type V α1 chain (COL5A1) is a minor fibrillar collagen in mammals that co-polymerizes with type I collagen to adjust the diameter of collagen molecules. However, the function of COL5A1 in invasive ductal carcinoma (IDC) of the human breast remains unknown. In the present study, our group examined the expression of COL5A1 in IDC compared with its adjacent normal tissue and fibroadenoma of the breast. COL5A1 was revealed to be overexpressed in IDC compared with benign tumor and adjacent normal control tissues, and was associated with the expression of estrogen receptor and progesterone receptor. No association between COL5A1 expression and tumor size, lymph node metastasis, clinical stage, age, or Her2 expression was identified. High expression of COL5A1 mRNA was associated with distant metastasis free survival in patients with breast cancer. Knockdown of COL5A1 led to a decrease of cell viability, as detected by the WST-1 assay, and an inhibition of migration and invasion, as detected by wound healing and Transwell assays, respectively, in the breast cancer cell line MCF-7. The expression of COL5A1 in MCF-7 cells was downregulated by transforming growth factor (TGF)‑β1, which was abolished in the presence of SB-431542, an inhibitor of TGF-β type I receptor. In conclusion, these data indicated that COL5A1 is overexpressed in IDC and regulated by TGF-β1, suggesting that an increase of COL5A1 reflects tumor progression and may serve as a novel biomarker and therapeutic target for the treatment of breast IDC.

The Assessment of Estrogen Receptor Status and Its Intratumoral Heterogeneity in Patients With Breast Cancer by Using 18F-Fluoroestradiol PET/CT

AIM

The aim of this study was to investigate the clinical value of F-fluoroestradiol (F-FES) PET/CT in the assessment of the estrogen receptor (ER) and its intratumoral heterogeneity in breast cancer patients.

METHODS

Forty-six female patients (50 lesions) with histologically confirmed invasive breast cancer who underwent both F-FES and F-FDG PET/CT in our center were retrospectively included. All the patients enrolled were scheduled to undergo biopsy. The F-FES and FDG uptakes were compared with pathological features (tumor size, ER, progesterone receptor, human epidermal growth factor receptor 2, and Ki67%). The optimal threshold to discriminate ER-positive and ER-negative lesions was determined by receiver operating characteristic curve analysis. Furthermore, we observed the intratumoral heterogeneity by a heterogeneity index (SUVmax/SUVmean) and compared the results with the Chang-Gung Image Texture Analysis.

RESULTS

There was good agreement between F-FES uptake and ER, progesterone receptor, and human epidermal growth factor receptor 2 expression (P < 0.001), and the use of SUVmean instead of SUVmax can provide a slightly better correlation. The optimal threshold for F-FES PET/CT to discriminate between ER-positive and ER-negative lesions, as determined by receiver operating characteristic curve analysis, was an SUVmax of 1.82 (sensitivity = 88.2% and specificity = 87.5%) and SUVmean of 1.21 (sensitivity = 85.3% and specificity = 93.7). Our simplified heterogeneity index-FES can easily observe ER heterogeneity. In addition, our results suggested that recurrent/metastatic patients and lesions located other than breast might have greater heterogeneity.

CONCLUSIONS

F-FES PET/CT is a feasible, noninvasive method for assessing ER expression in breast cancer patients. Because intratumoral heterogeneity exists, F-FES PET/CT might better reflect the ER expression, especially in metastatic patients after treatment, thus assisting in making individualized treatment decisions.

A preliminary study of 18F-FES PET/CT in predicting metastatic breast cancer in patients receiving docetaxel or fulvestrant with docetaxel

The present explorative study was initiated to evaluate the clinical value of ¹⁸F-FES PET/CT in monitoring the change of estrogen receptor (ER) expression and potential predictive value in metastatic breast cancer patients. Twenty-two pathology-confirmed breast cancer patients were prospectively enrolled and randomly divided into two groups (T: docetaxel, n = 14 and TF: docetaxel + fulvestrant, n = 8). The percentage of patients without disease progression after 12 months (PFS > 12 months) was 62.5% in group TF compared with 21.4% in group T (P = 0.08). According to ¹⁸F-FES PET/CT scans, the SUVmax (maximum standard uptake value) of all the metastatic lesions decreased in group TF after 2 cycles of treatment (6 weeks ± 3 days). However, 6 of 9 patients in group T had at least one lesion with higher post-treatment SUVmax. There was a significant difference in the reduction of ER expression between these two groups (P = 0.028). In group TF, the patients with PFS > 12 months had significantly greater SUVmax changes of ¹⁸F-FES than those with PFS < 12 months (PFS > 12 months: 91.0 ± 12.0% versus PFS < 12 months: 20.7 ± 16.2%; t = −4.64, P = 0.01). Our preliminary study showed that ¹⁸F-FES PET/CT, as a noninvasive method to monitor ER expression, could be utilized to predict prognosis based on changes in SUVmax.

AutoIHC-scoring: a machine learning framework for automated Allred scoring of molecular expression in ER- and PR-stained breast cancer tissue

In prognostic evaluation of breast cancer Immunohistochemical (IHC) markers namely, oestrogen receptor (ER) and progesterone receptor (PR) are widely used. The expert pathologist investigates qualitatively the stained tissue slide under microscope to provide the Allred score; which is clinically used for therapeutic decision making. Such qualitative judgment is time-consuming, tedious and more often suffers from interobserver variability. As a result, it leads to imprecise IHC score for ER and PR. To overcome this, there is an urgent need of developing a reliable and efficient IHC quantifier for high throughput decision making. In view of this, our study aims at developing an automated IHC profiler for quantitative assessment of ER and PR molecular expression from stained tissue images. We propose here to use CMYK colour space for positively and negatively stained cell extraction for proportion score. Also colour features are used for quantitative assessment of intensity scoring among the positively stained cells. Five different machine learning models namely artificial neural network, Naïve Bayes, K-nearest neighbours, decision tree and random forest are considered for learning the colour features using average red, green and blue pixel values of positively stained cell patches. Fifty cases of ER- and PR-stained tissues have been evaluated for validation with the expert pathologist's score. All five models perform adequately where random forest shows the best correlation with the expert's score (Pearson's correlation coefficient = 0.9192). In the proposed approach the average variation of diaminobenzidine (DAB) to nuclear area from the expert's score is found to be 7.58%, as compared to 27.83% for state-of-the-art ImmunoRatio software.

Computer-based image analysis in breast pathology

Whole slide imaging (WSI) has the potential to be utilized in telepathology, teleconsultation, quality assurance, clinical education, and digital image analysis to aid pathologists. In this paper, the potential added benefits of computer-assisted image analysis in breast pathology are reviewed and discussed. One of the major advantages of WSI systems is the possibility of doing computer-based image analysis on the digital slides. The purpose of computer-assisted analysis of breast virtual slides can be (i) segmentation of desired regions or objects such as diagnostically relevant areas, epithelial nuclei, lymphocyte cells, tubules, and mitotic figures, (ii) classification of breast slides based on breast cancer (BCa) grades, the invasive potential of tumors, or cancer subtypes, (iii) prognosis of BCa, or (iv) immunohistochemical quantification. While encouraging results have been achieved in this area, further progress is still required to make computer-based image analysis of breast virtual slides acceptable for clinical practice.

High specific activity is not optimal: 18 F-fluoroestradio positron emission tomography-computed tomography results in a breast cancer xenograft

The purpose of the preliminary study was to investigate whether high specific activity (SA) of ¹⁸ F-fluoroestradiol was optimal in breast cancer diagnosis. Imaging at variable SA was conducted in a ZR-75-1 xenograft model of estrogen-receptor positive human breast cancer in 6 mice. The region of interest was manually drawn, and the percent of injected dose per gram of the tumor and muscle in the regions of interest were recorded. Tumor-to-muscle ratio (T/M) was calculated and compared in each group with different SAs. In addition, the correlation between blood estradiol and sex hormone-binding globulin and the value of T/M were also analyzed. The value of T/M increased initially with the rise of SA and it reached the peak at SA of 1.6 Ci/μmol. After that, the value fell down sharply and remained stable from SA of 3.1 Ci/μmol. The value of T/M was highest at SA of 1.6 Ci/μmol (P < .001). Additionally, the blood levels of estradiol and sex hormone-binding globulin showed no correlation with the value of T/M (P > .05). High SA of ¹⁸ F-fluoroestradiol leads to low T/M results in breast cancer xenograft models. We should control SA in a reasonable range to obtain high-quality images.

The preliminary study of 16α-[18F]fluoroestradiol PET/CT in assisting the individualized treatment decisions of breast cancer patients

Objective

To evaluate the clinical value of 16α-[18F]fluoroestradiol (18F-FES) PET/CT in assisting the individualized treatment decisions of breast cancer patients.

Methods

Thirty-three breast cancer patients, who underwent both 18F-FES and 18F-FDG PET/CT from July 2010 to March 2013 in our center, were enrolled in this preliminary study. All the patients used 18F-FES PET/CT as a diagnostic tool with a clinical dilemma. We used the maximum Standardized Uptake Value (SUVmax) to quantify ER expression and a cutoff value of 1.5 to dichotomize results into ER positive and negative lesions. All patients were clinically followed up at least 6 months.

Results

In evaluating equivocal lesions on conventional work-up group (n = 4), three lung lesions and another iliac lesion were enrolled. As for three lung lesions, 18F-FES PET/CT showed one lesion with high uptake, which suggested it was an ER positive metastasis. The other two lesions were 18F-FES negative, which meant an ER negative metastasis or secondary primary tumor. Additionally, one iliac lesion was detected by MRI. 18F-FDG uptake was high at the suspected lesion, whereas 18F-FES uptake was absent; In predicting origin of metastasis group (n = 2), two breast cancer patients had secondary primary tumors were collected. They were 18F-FES negative, which showed low possibility of metastasis from breast cancer and they were all confirmed by biopsy. In detecting ER status in metastasis group (n = 27), 18F-FES PET/CT showed increased 18F-FES uptake in all metastatic lesions in 11 patients; absent in all lesions in 13 patients; and the remaining 3 patients had both 18F-FES positive and negative lesions. Totally, on the basis of the 18F-FES PET/CT results, we found changes in the treatment plans in 16 patients (48.5%, 16/33).

Conclusions

18F-FES PET/CT could assess the entire tumor volume receptor status; therefore, it may be used to assist the individualized treatment decisions of breast cancer patients.

Visual and automated assessment of matrix metalloproteinase-14 tissue expression for the evaluation of ovarian cancer prognosis

The purpose of this study was to evaluate whether the membrane type 1 matrix metalloproteinase-14 (or MT1-MMP) tissue expression, as assessed visually on digital slides and by digital image analysis, could predict outcomes in women with ovarian carcinoma. Tissue microarrays from a cohort of 211 ovarian carcinoma women who underwent a debulking surgery between 1993 and 2006 at the CHU de Québec (Canada) were immunostained for matrix metalloproteinase-14. The percentage of MMP-14 staining was assessed visually and with the Calopix software. Progression was evaluated using the CA-125 and/or the RECIST criteria according to the GCIG criteria. Dates of death were obtained by record linkage with the Québec mortality files. Adjusted hazard ratios of death and progression with their 95% confidence intervals were estimated using the Cox model. Comparisons between the two modalities of MMP-14 assessment were done using the box plots and the Kruskal-Wallis test. The highest levels of MMP-14 immunostaining were associated with nonserous histology, early FIGO stage, and low preoperative CA-125 levels (P<0.05). In bivariate analyses, the higher level of MMP-14 expression (>40% of MMP-14-positive cells) was inversely associated with progression using visual assessment (hazard ratio=0.39; 95% confidence interval: 0.18-0.82). A similar association was observed with the highest quartile of MMP-14-positive area assessed by digital image analysis (hazard ratio=0.48; 95% confidence interval: 0.28-0.82). After adjustment for standard prognostic factors, these associations were no longer significant in the ovarian carcinoma cohort. However, in women with serous carcinoma, the highest quartile of MMP-14-positive area was associated with progression (adjusted hazard ratio=0.48; 95% confidence interval: 0.24-0.99). There was no association with overall survival. The digital image analysis of MMP-14-positive area matched the visual assessment using three categories (>40% vs 21-40 vs <20%). Higher levels of MMP-14 immunostaining were associated with standard factors of better ovarian carcinoma prognosis. In women with serous carcinoma, high expression of MMP-14 was associated with lower progression.

Can positron emission tomography/computed tomography with the dual tracers fluorine-18 fluoroestradiol and fluorodeoxyglucose predict neoadjuvant chemotherapy response of breast cancer?--A pilot study

OBJECTIVE

To assess the clinical value of dual tracers Positron emission tomography/computed tomography (PET/CT) (18)F-fluoroestradiol ((18)F-FES) and (18)F-fluorodeoxyglucose ((18)F-FDG) in predicting neoadjuvant chemotherapy response (NAC) of breast cancer.

METHODS

Eighteen consecutive patients with newly diagnosed, non-inflammatory, stage II and III breast cancer undergoing NAC were included. Before chemotherapy, they underwent both (18)F-FES and (18)F-FDG PET/CT scans. Surgery was performed after three to six cycles of chemotherapy. Tumor response was graded and divided into two groups: the responders and non-responders. We used the maximum standardized uptake value (SUVmax) to qualify each primary lesion.

RESULTS

Pathologic analysis revealed 10 patients were responders while the other 8 patients were non-responders. There was no statistical difference of SUVmax-FDG and tumor size between these two groups (P>0.05). On the contrary, SUVmax-FES was lower in responders (1.75±0.66 versus 4.42±1.14; U=5, P=0.002); and SUVmax-FES/FDG also showed great value in predicting outcome (0.16±0.06 versus 0.54±0.22; U=5, P=0.002).

CONCLUSIONS

Our study showed (18)F-FES PET/CT might be feasible to predict response of NAC. However, whether the use of dual tracers (18)F-FES and (18)F-FDG has complementary value should be further studied.

Software-automated counting of Ki-67 proliferation index correlates with pathologic grade and disease progression of follicular lymphomas

OBJECTIVES

To examine the accuracy of software-assisted measurement of the Ki-67 proliferation index (PI) and its correlation with the grade and clinical progression of follicular lymphoma (FL).

METHODS

High-power field equivalents were extracted from H&E- and Ki-67-immunostained slides of FL, and a nuclear quantitation algorithm was used to calculate a PI. Representative fields were manually counted for validation with close agreement.

RESULTS

The PI was significantly higher in World Health Organization grade 3 FL than grade 1 to 2 FL. Disease progression, as defined by subsequent treatment with radiation or cytotoxic chemotherapy, was also significantly associated with elevated PI but not pathologic grade.

CONCLUSIONS

These data show that software-automated quantitation of Ki-67 can provide both a useful adjunct to pathologic grade in FL and improved prognostic information for patients.

Systematic review on hormone receptor testing in breast cancer

Assessment of hormone receptors (estrogen and progesterone) helps to direct therapy for women with breast cancer. Immunohistochemistry is most commonly used to assess hormone receptor status and it is essential that these tests are performed accurately and reliably within and across laboratories. The overall purpose of this guideline is to improve the quality and accuracy of hormone receptor testing and its utility as a prognostic and predictive marker for invasive and in situ breast cancer. Medline, EMBASE, the Cochrane Database of Systematic Reviews, and abstracts from the San Antonio Breast Cancer Symposium were searched. An environmental scan of the internet and of international guideline developers and key organizations was performed. Preanalytic elements such as the collection, fixation, and storage of samples, and analytic elements such as selection of antibodies and scoring methods that seem to offer the best results for immunohistochemical assessment of hormone receptors are presented. Proficiency testing or quality assurance of immunohistochemistry is described.

Cancer care Ontario guideline recommendations for hormone receptor testing in breast cancer

Hormone receptor testing (oestrogen and progesterone) in breast cancer at the time of primary diagnosis is used to guide treatment decisions. Accurate and standardised testing methods are critical to ensure the proper classification of the patient's hormone receptor status. Recommendations were developed to improve the quality and accuracy of hormone receptor testing based on a systematic review conducted jointly by the American Society of Clinical Oncology/College of American Pathologists and Cancer Care Ontario's Program in Evidence-Based Care. Evidence-based recommendations were formulated to set standards for optimising immunohistochemistry in assessing hormone receptor status, as well as assuring quality and proficiency between and within laboratories. A formal external review was conducted to validate the relevance of these recommendations. It is anticipated that widespread adoption of these guidelines will further improve the accuracy of hormone receptor testing in Canada.

Identification of prognostic biomarkers for glioblastomas using protein expression profiling

A set of proteins reflecting the prognosis of patients have clinical significance since they could be utilized as predictive biomarkers and/or potential therapeutic targets. With the aim of finding novel diagnostic and prognostic markers for glioblastoma (GBM), a tissue microarray (TMA) library consisting of 62 GBMs and 28 GBM-associated normal spots was constructed. Immunohistochemistry against 78 GBM-associated proteins was performed. Expression levels of each protein for each patient were analyzed using an image analysis program and converted to H-score [summation of the intensity grade of staining (0-3) multiplied by the percentage of positive cells corresponding to each grade]. Based on H-score and hierarchical clustering methods, we divided the GBMs into two groups (n=19 and 37) that had significantly different survival lengths (p<0.05). In the two groups, expression of nine proteins (survivin, cyclin E, DCC, TGF-β, CDC25B, histone H1, p-EGFR, p-VEGFR2/3, p16) was significantly changed (q<0.05). Prognosis-predicting potential of these proteins were validated with another independent library of 82 GBM TMAs and a public GBM DNA microarray dataset. In addition, we determined 32 aberrant or mislocalized subcellular protein expression patterns in GBMs compared with relatively normal brain tissues, which could be useful for diagnostic biomarkers of GBM. We therefore suggest that these proteins can be used as predictive biomarkers and/or potential therapeutic targets for GBM.

High-throughput profiling of tissue and tissue model microarrays: Combined transmitted light and 3-color fluorescence digital pathology

For many years pathologists have used Hematoxylin and Eosin (H&E), single marker immunohistochemistry (IHC) and in situ hybridization with manual analysis by microscopy or at best simple digital imaging. There is a growing trend to update pathology to a digital workflow to improve objectivity and productivity, as has been done in radiology. There is also a need for tissue-based multivariate biomarker assays to improve the accuracy of diagnostic, prognostic, and predictive testing. Multivariate tests are not compatible with the traditional single marker, manual analysis pathology methods but instead require a digital platform with brightfield and fluorescence imaging, quantitative image analysis, and informatics. Here we describe the use of the Hamamatsu NanoZoomer Digital Pathology slide scanner with HCImage software for combined brightfield and multiplexed fluorescence biomarker analysis and highlight its applications in biomarker research and pathology testing. This combined approach will be an important aid to pathologists in making critical diagnoses.

Image analysis tools for evaluation of microscopic views of immunohistochemically stained specimen in medical research-a review

The aim of this study is to review the methods being used for image analysis of microscopic views of immunohistochemically stained specimen in medical research. The solutions available range from general purpose software to commercial packages. Many studies have developed their own custom written programs based on some general purpose software available. Many groups have reported development of computer aided image analysis programs aiming at obtaining faster, simpler and cheaper solutions. Image analysis tools namely Aperio, Lucia, Metaview, Metamorph, ImageJ, Scion, Adobe Photoshop, Image Pro Plus are also used for evaluation of expressions using immunohistochemical staining. An overview of such methods used for image analysis is provided in this paper. This study concludes that there is good scope for development of freely available software for staining intensity quantification, which a medical researcher could easily use without requiring high level computer skills.

Image analysis tools for evaluation of microscopic views of immunohistochemically stained specimen in medical research-a review

The aim of this study is to review the methods being used for image analysis of microscopic views of immunohistochemically stained specimen in medical research. The solutions available range from general purpose software to commercial packages. Many studies have developed their own custom written programs based on some general purpose software available. Many groups have reported development of computer aided image analysis programs aiming at obtaining faster, simpler and cheaper solutions. Image analysis tools namely Aperio, Lucia, Metaview, Metamorph, ImageJ, Scion, Adobe Photoshop, Image Pro Plus are also used for evaluation of expressions using immunohistochemical staining. An overview of such methods used for image analysis is provided in this paper. This study concludes that there is good scope for development of freely available software for staining intensity quantification, which a medical researcher could easily use without requiring high level computer skills.

Automation of immunohistochemical evaluation in breast cancer using image analysis

AIM: To automate breast cancer diagnosis and to study the inter-observer and intra-observer variations in the manual evaluations.

METHODS: Breast tissue specimens from sixty cases were stained separately for estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor-2 (HER-2/neu). All cases were assessed by manual grading as well as image analysis. The manual grading was performed by an experienced expert pathologist. To study inter-observer and intra-observer variations, we obtained readings from another pathologist as the second observer from a different laboratory who has a little less experience than the first observer. We also took a second reading from the second observer to study intra-observer variations. Image analysis was carried out using in-house developed software (TissueQuant). A comparison of the results from image analysis and manual scoring of ER, PR and HER-2/neu was also carried out.

RESULTS: The performance of the automated analysis in the case of ER, PR and HER-2/neu expressions was compared with the manual evaluations. The performance of the automated system was found to correlate well with the manual evaluations. The inter-observer variations were measured using Spearman correlation coefficient r and 95% confidence interval. In the case of ER expression, Spearman correlation r = 0.53, in the case of PR expression, r = 0.63, and in the case of HER-2/neu expression, r = 0.68. Similarly, intra-observer variations were also measured. In the case of ER, PR and HER-2/neu expressions, r = 0.46, 0.66 and 0.70, respectively.

CONCLUSION: The automation of breast cancer diagnosis from immunohistochemically stained specimens is very useful for providing objective and repeatable evaluations.

Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer

Background

The immunohistochemical detection of estrogen (ER) and progesterone (PR) receptors in breast cancer is routinely used for prognostic and predictive testing. Whole slide digitalization supported by dedicated software tools allows quantization of the image objects (e.g. cell membrane, nuclei) and an unbiased analysis of immunostaining results. Validation studies of image analysis applications for the detection of ER and PR in breast cancer specimens provided strong concordance between the pathologist's manual assessment of slides and scoring performed using different software applications.

Methods

The effectiveness of two connected semi-automated image analysis software (NuclearQuant v. 1.13 application for Pannoramic™ Viewer v. 1.14) for determination of ER and PR status in formalin-fixed paraffin embedded breast cancer specimens immunostained with the automated Leica Bond Max system was studied. First the detection algorithm was calibrated to the scores provided an independent assessors (pathologist), using selected areas from 38 small digital slides (created from 16 cases) containing a mean number of 195 cells. Each cell was manually marked and scored according to the Allred-system combining frequency and intensity scores. The performance of the calibrated algorithm was tested on 16 cases (14 invasive ductal carcinoma, 2 invasive lobular carcinoma) against the pathologist's manual scoring of digital slides.

Results

The detection was calibrated to 87 percent object detection agreement and almost perfect Total Score agreement (Cohen's kappa 0.859, quadratic weighted kappa 0.986) from slight or moderate agreement at the start of the study, using the un-calibrated algorithm. The performance of the application was tested against the pathologist's manual scoring of digital slides on 53 regions of interest of 16 ER and PR slides covering all positivity ranges, and the quadratic weighted kappa provided almost perfect agreement (κ = 0.981) among the two scoring schemes.

Conclusions

NuclearQuant v. 1.13 application for Pannoramic™ Viewer v. 1.14 software application proved to be a reliable image analysis tool for pathologists testing ER and PR status in breast cancer.

JPEG2000 for automated quantification of immunohistochemically stained cell nuclei: a comparative study with standard JPEG format

The Joint Photographic Experts Group (JPEG) standard format is one of the most widely used in image compression technologies. More recently, JPEG2000 format has emerged as a state-of-the-art technology that provides substantial improvements in picture quality at higher compression ratios. However, there has been no attempt to date to determine which of the two compression formats produces less variability in the automated evaluation of immunohistochemically stained digital images in agreement with their compression rates and complexity degrees. The evaluation of Ki67 and FOXP3 immunohistochemical nuclear markers was performed in a total of 329 digital images: 47 were captured in uncompressed Tagged Image File Format (TIFF), 141 were converted to three JPEG compressed formats (47 each with 1:3, 1:23 and 1:46 compression) and 141 were converted to three JPEG2000 compressed formats (47 each with 1:3, 1:23 and 1:46 compression). The count differences between images in TIFF versus JPEG formats were compared with those obtained between images in TIFF versus JPEG2000 formats at the three levels of compression. It was found that, using JPEG2000 compression, the results of the stained nuclei count are close enough to the results obtained with uncompressed images, especially in highly complex images at minimum and medium compression. Otherwise, in images of low complexity, JPEG and JPEG2000 had similar count efficiency to that of the original TIFF images at all compression levels. These data suggest that JPEG2000 could give rise to an efficient means of storage, reducing file size and storage capacity, without compromise on the immunohistochemical analytical quality.

Comparison of evaluations of hormone receptors in breast carcinoma by image-analysis using three automated immunohistochemical stainings

The aim of this study was to compare the results of immunohistochemistry (IHC) assays evaluated by human examiners with the results evaluated by computerized image analysis, and to compare the computerized image analysis results among three automated IHC assays, namely the BioGenex, Dako and Ventana assays. All slides were semiquantitatively evaluated according to the Allred score and J-score by human examiners. The images were analyzed using MacSCOPE version 2.6 for Macintosh according to the H-score and the percentage of positive-stained nuclei per area of carcinoma cells (PP) irrespective of the intensity of the stained nuclei. The H-score for the estrogen receptor (ER) was significantly correlated with the Allred score (P<0.0001) and the PP for the ER was significantly correlated with the J-score (P<0.0001), suggesting that the image analysis used in the present study is a useful method for the evaluation of ER status. Several discrepancies were identified between the Allred score and H-score and between the PP and J-score due to the positive-stained cytoplasm area of carcinoma cells and/ or the positive-stained nuclei area of non-carcinoma cells, including benign epithelial cells, lymphocytes and stromal cells. Accordingly, advances in the algorithm of the digitized analyzing system is necessary.

Datamining approach for automation of diagnosis of breast cancer in immunohistochemically stained tissue microarray images

Cancer of the breast is the second most common human neoplasm, accounting for approximately one quarter of all cancers in females after cervical carcinoma. Estrogen receptor (ER), Progesteron receptor and human epidermal growth factor receptor (HER-2/neu) expressions play an important role in diagnosis and prognosis of breast carcinoma. Tissue microarray (TMA) technique is a high throughput technique which provides a standardized set of images which are uniformly stained, facilitating effective automation of the evaluation of the specimen images. TMA technique is widely used to evaluate hormone expression for diagnosis of breast cancer. If one considers the time taken for each of the steps in the tissue microarray process workflow, it can be observed that the maximum amount of time is taken by the analysis step. Hence, automated analysis will significantly reduce the overall time required to complete the study. Many tools are available for automated digital acquisition of images of the spots from the microarray slide. Each of these images needs to be evaluated by a pathologist to assign a score based on the staining intensity to represent the hormone expression, to classify them into negative or positive cases. Our work aims to develop a system for automated evaluation of sets of images generated through tissue microarray technique, representing the ER expression images and HER-2/neu expression images. Our study is based on the Tissue Microarray Database portal of Stanford university at http://tma.stanford.edu/cgi-bin/cx?n=her1, which has made huge number of images available to researchers. We used 171 images corresponding to ER expression and 214 images corresponding to HER-2/neu expression of breast carcinoma. Out of the 171 images corresponding to ER expression, 104 were negative and 67 were representing positive cases. Out of the 214 images corresponding to HER-2/neu expression, 112 were negative and 102 were representing positive cases. Our method has 92.31% sensitivity and 93.18% specificity for ER expression image classification and 96.67% sensitivity and 88.24% specificity for HER-2/neu expression image classification.

Assessment of automated image analysis of breast cancer tissue microarrays for epidemiologic studies

BACKGROUND

A major challenge in studies of etiologic heterogeneity in breast cancer has been the limited throughput, accuracy, and reproducibility of measuring tissue markers. Computerized image analysis systems may help address these concerns, but published reports of their use are limited. We assessed agreement between automated and pathologist scores of a diverse set of immunohistochemical assays done on breast cancer tissue microarrays (TMA).

METHODS

TMAs of 440 breast cancers previously stained for estrogen receptor (ER)-alpha, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), ER-beta, and aromatase were independently scored by two pathologists and three automated systems (TMALab II, TMAx, and Ariol). Agreement between automated and pathologist scores of negative/positive was measured using the area under the receiver operating characteristics curve (AUC) and weighted kappa statistics for categorical scores. We also investigated the correlation between immunohistochemical scores and mRNA expression levels.

RESULTS

Agreement between pathologist and automated negative/positive and categorical scores was excellent for ER-alpha and PR (AUC range = 0.98-0.99; kappa range = 0.86-0.91). Lower levels of agreement were seen for ER-beta categorical scores (AUC = 0.99-1.0; kappa = 0.80-0.86) and both negative/positive and categorical scores for aromatase (AUC = 0.85-0.96; kappa = 0.41-0.67) and HER2 (AUC = 0.94-0.97; kappa = 0.53-0.72). For ER-alpha and PR, there was a strong correlation between mRNA levels and automated (rho = 0.67-0.74) and pathologist immunohistochemical scores (rho = 0.67-0.77). HER2 mRNA levels were more strongly correlated with pathologist (rho = 0.63) than automated immunohistochemical scores (rho = 0.41-0.49).

CONCLUSIONS

Automated analysis of immunohistochemical markers is a promising approach for scoring large numbers of breast cancer tissues in epidemiologic investigations. This would facilitate studies of etiologic heterogeneity, which ultimately may allow improved risk prediction and better prevention approaches.

Use and validation of epithelial recognition and fields of view algorithms on virtual slides to guide TMA construction

While tissue microarrays (TMAs) are a form of high-throughput screening, they presently still require manual construction and interpretation. Because of predicted increasing demand for TMAs, we investigated whether their construction could be automated. We created both epithelial recognition algorithms (ERAs) and field of view (FOV) algorithms that could analyze virtual slides and select the areas of highest cancer cell density in the tissue block for coring (algorithmic TMA) and compared these to the cores manually selected (manual TMA) from the same tissue blocks. We also constructed TMAs with TMAker, a robot guided by these algorithms (robotic TMA). We compared each of these TMAs to each other. Our imaging algorithms produced a grid of hundreds of FOVs, identified cancer cells in a stroma background and calculated the epithelial percentage (cancer cell density) in each FOV. Those with the highest percentages guided core selection and TMA construction. Algorithmic TMA and robotic TMA were overall approximately 50% greater in cancer cell density compared with Manual TMA. These observations held for breast, colon, and lung cancer TMAs. Our digital image algorithms were effective in automating TMA construction.

ERalpha signaling through slug regulates E-cadherin and EMT. Oncogene. 2010;29:1451-1462. [PMID: 20101232 DOI: 10.1038/onc.2009.433]

The ERalpha signaling pathway is one of the most important and most studied pathways in human breast cancer, yet numerous questions still exist such as how hormonally responsive cancers progress to a more aggressive and hormonally independent phenotype. We have noted that human breast cancers exhibit a strong direct correlation between ERalpha and E-cadherin expression by immunohistochemistry, suggesting that ERalpha signaling might regulate E-cadherin and implying that this regulation might influence epithelial-mesenchymal transition (EMT) and tumor progression. To investigate this hypothesis and the mechanisms behind it, we studied the effects of ERalpha signaling in ERalpha-transfected ERalpha-negative breast carcinoma cell lines, the MDA-MB-468 and the MDA-MB-231 and the effects of ERalpha knockdown in naturally expressing ERalpha-positive lines, MCF-7 and T47D. When ERalpha was overexpressed in the ERalpha-negative lines, 17beta-estradiol (E2) decreased slug and increased E-cadherin. Clones maximally exhibiting these changes grew more in clumps and became less invasive in Matrigel. When ERalpha was knocked down in the ERalpha-positive lines, slug increased, E-cadherin decreased, cells became spindly and exhibited increased Matrigel invasion. ERalpha signaling decreased slug expression by two different mechanisms: directly, by repression of slug transcription by the formation of a corepressor complex of ligand-activated ERalpha, HDAC inhibitor (HDAC1), and nuclear receptor corepressor (N-CoR) that bound the slug promoter in three half-site estrogen response elements (EREs); indirectly by phosphorylation and inactivation of GSK-3beta through phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt). The GSK-3beta inactivation, in turn, repressed slug expression and increased E-cadherin. In human breast cancer cases, there was a strong inverse correlation between slug and ERalpha and E-cadherin immunoreactivity. Our findings indicate that ERalpha signaling through slug regulates E-cadherin and EMT.

Requirements for the valid quantification of immunostains on tissue microarray materials using image analysis

Antibody-based proteomics applied to tissue microarray (TMA) technology provides a very efficient means of visualizing and locating antigen expression in large collections of normal and pathological tissue samples. To characterize antigen expression on TMAs, the use of image analysis methods avoids the effects of human subjectivity evidenced in manual microscopical analysis. Thus, these methods have the potential to significantly enhance both precision and reproducibility. Although some commercial systems include tools for the quantitative evaluation of immunohistochemistry-stained images, there exists no clear agreement on best practices to allow for correct and reproducible quantification results. Our study focuses on practical aspects regarding (i) image acquisition (ii) segmentation of staining and counterstaining areas and (iii) extraction of quantitative features. We illustrate our findings using a commercial system to quantify different immunohistochemistry markers targeting proteins with different expression patterns (cytoplasmic, nuclear or membranous) in colon cancer or brain tumor TMAs. Our investigations led us to identify several steps that we consider essential for standardizing computer-assisted immunostaining quantification experiments. In addition, we propose a data normalization process based on reference materials to be able to compare measurements between studies involving different TMAs. In conclusion, we recommend certain critical prerequisites that commercial or in-house systems should satisfy in order to permit valid immunostaining quantification.

Tissue Microarray: A rapidly evolving diagnostic and research tool

Tissue microarray is a recent innovation in the field of pathology. A microarray contains many small representative tissue samples from hundreds of different cases assembled on a single histologic slide, and therefore allows high throughput analysis of multiple specimens at the same time. Tissue microarrays are paraffin blocks produced by extracting cylindrical tissue cores from different paraffin donor blocks and re-embedding these into a single recipient (microarray) block at defined array coordinates. Using this technique, up to 1000 or more tissue samples can be arrayed into a single paraffin block. It can permit simultaneous analysis of molecular targets at the DNA, mRNA, and protein levels under identical, standardized conditions on a single glass slide, and also provide maximal preservation and use of limited and irreplaceable archival tissue samples. This versatile technique, in which data analysis is automated, facilitates retrospective and prospective human tissue studies. It is a practical and effective tool for high-throughput molecular analysis of tissues that is helping to identify new diagnostic and prognostic markers and targets in human cancers, and has a range of potential applications in basic research, prognostic oncology and drug discovery. This article summarizes the technical aspects of tissue microarray construction and sectioning, advantages, application, and limitations.

Virtual slide telepathology workstation of the future: lessons learned from teleradiology

The clinical reading environment for the 21st century pathologist looks very different than it did even a few short years ago. Glass slides are quickly being replaced by digital "virtual slides," and the traditional light microscope is being replaced by the computer display. There are numerous questions that arise however when deciding exactly what this new digital display viewing environment will be like. Choosing a workstation for daily use in the interpretation of digital pathology images can be a very daunting task. Radiology went digital nearly 20 years ago and faced many of the same challenges so there are lessons to be learned from these experiences. One major lesson is that there is no "one size fits all" workstation so users must consider a variety of factors when choosing a workstation. In this article, we summarize some of the potentially critical elements in a pathology workstation and the characteristics one should be aware of and look for in the selection of one. Issues pertaining to both hardware and software aspects of medical workstations will be reviewed particularly as they may impact the interpretation process.

Tissue Microarray: A rapidly evolving diagnostic and research tool

Tissue microarray is a recent innovation in the field of pathology. A microarray contains many small representative tissue samples from hundreds of different cases assembled on a single histologic slide, and therefore allows high throughput analysis of multiple specimens at the same time. Tissue microarrays are paraffin blocks produced by extracting cylindrical tissue cores from different paraffin donor blocks and re-embedding these into a single recipient (microarray) block at defined array coordinates. Using this technique, up to 1000 or more tissue samples can be arrayed into a single paraffin block. It can permit simultaneous analysis of molecular targets at the DNA, mRNA, and protein levels under identical, standardized conditions on a single glass slide, and also provide maximal preservation and use of limited and irreplaceable archival tissue samples. This versatile technique, in which data analysis is automated, facilitates retrospective and prospective human tissue studies. It is a practical and effective tool for high-throughput molecular analysis of tissues that is helping to identify new diagnostic and prognostic markers and targets in human cancers, and has a range of potential applications in basic research, prognostic oncology and drug discovery. This article summarizes the technical aspects of tissue microarray construction and sectioning, advantages, application, and limitations.

Disruption in the expression and immunolocalisation of steroid receptors and steroidogenic enzymes in letrozole-induced polycystic ovaries in rat

The objective of the present study was to characterise the expression and tissue distribution of steroid receptors (oestrogen receptor-α and –β (ERα, ERβ), androgen receptor (AR) and progesterone receptor (PR)) and steroidogenic enzymes (P450 aromatase (P450arom), 3β-hydroxysteroid dehydrogenase (3β-HSD) and steroidogenic acute regulatory protein (StAR)) in letrozole-induced polycystic ovaries of rats. Changes in serum hormone levels, protein expression in whole ovaries by western blot analysis and protein localisation by immunohistochemistry were determined in female rats treated with the aromatase inhibitor letrozole and compared with controls in proestrous and diestrous rats. Increases in the serum LH, FSH and testosterone concentrations were observed in letrozole-treated rats whereas serum oestradiol and progesterone levels were reduced. Protein expression as analysed by western immunoblot was consistent with the immunohistochemical data. Letrozole treatment induced an increase in the expression of AR, StAR and 3β-HSD and a decrease in ERβ. ERα, PR and P450arom showed partial changes in relation to some cycle stages. These results indicate that cystogenesis in this experimental model is characterised by changes in steroid receptors and steroidogenic enzyme expression that may be essential to proper ovarian functioning and are in agreement with similar changes observed in women with PCOS.