Inter-observer reproducibility of HER2 immunohistochemical assessment and concordance with fluorescent in situ hybridization (FISH): pathologist assessment compared to quantitative image analysis

Reproducibility of c-Met Immunohistochemical Scoring (Clone SP44) for Non-Small Cell Lung Cancer Using Conventional Light Microscopy and Whole Slide Imaging

Emerging therapies for non-small cell lung cancer targeting c-Met overexpression have recently demonstrated promising results. However, the evaluation of c-Met expression can be challenging. We aimed to study the inter and intraobserver reproducibility of c-Met expression evaluation. One hundred ten cases with non-small cell lung cancer (40 biopsies and 70 surgical specimens) were retrospectively selected in a single laboratory (LPCE) and evaluated for c-Met expression. Six pathologists (4 seniors and 2 juniors) evaluated the H-score and made a 3-tier classification of c-Met expression for all cases, using conventional light microscopy (CLM) and whole slide imaging (WSI). The interobserver reproducibility with CLM gave global Cohen Kappa coefficients (ƙ) ranging from 0.581 (95% CI: 0.364-0.771) to 0.763 (95% CI: 0.58-0.92) using the c-Met 3-tier classification and H-score, respectively. ƙ was higher for senior pathologists and biopsy samples. The interobserver reproducibility with WSI gave a global ƙ ranging from 0.543 (95% CI: 0.33-0.724) to 0.905 (95% CI: 0.618-1) using the c-Met H-score and 2-tier classification (≥25% 3+), respectively. ƙ for intraobserver reproducibility between CLM and WSI ranged from 0.713 to 0.898 for the c-Met H-score and from 0.600 to 0.779 for the c-Met 3-tier classification. We demonstrated a moderate to excellent interobserver agreement for c-Met expression with a substantial to excellent intraobserver agreement between CLM and WSI, thereby supporting the development of digital pathology. However, some factors (scoring method, type of tissue samples, and expertise level) affect reproducibility. Our findings highlight the importance of establishing a consensus definition and providing further training, particularly for inexperienced pathologists, for c-Met immunohistochemistry assessment in clinical practice.

Associations of stem cell markers CD44, CD24 and ALDH1A1 with mammographic breast density in women with benign breast biopsies

BACKGROUND

We examined associations of CD44, CD24 and ALDH1A1 breast stem cell markers with mammographic breast density (MBD), a well-established breast cancer (BCa) risk factor.

METHODS

We included 218 cancer-free women with biopsy-confirmed benign breast disease within the Nurses' Health Study (NHS) and NHSII. The data on BCa risk factors were obtained from biennial questionnaires. Immunohistochemistry (IHC) was done on tissue microarrays. For each core, the IHC expression was assessed using a semi-automated platform and expressed as percent of positively stained cells for each marker out of the total cell count. MBD was assessed with computer-assisted techniques. Generalised linear regression was used to examine the associations of each marker with square root-transformed percent density (PD), absolute dense and non-dense areas (NDA), adjusted for BCa risk factors.

RESULTS

Stromal CD44 and ALDH1A1 expression was positively associated with PD (≥ 10% vs. <10% β = 0.56, 95% confidence interval [CI] [0.06; 1.07] and β = 0.81 [0.27; 1.34], respectively) and inversely associated with NDA (β per 10% increase = -0.17 [-0.34; -0.01] and β for ≥10% vs. <10% = -1.17 [-2.07; -0.28], respectively). Epithelial CD24 expression was inversely associated with PD (β per 10% increase = -0.14 [-0.28; -0.01]. Stromal and epithelial CD24 expression was positively associated with NDA (β per 10% increase = 0.35 [0.2 × 10-2; 0.70] and β per 10% increase = 0.34 [0.11; 0.57], respectively).

CONCLUSION

Expression of stem cell markers is associated with MBD.

Clinical application of the HM-1000 image processing for HER2 fluorescence in situ hybridization signal quantification in breast cancer

BACKGROUND

Accurate quantification of human epidermal growth factor receptor 2 (HER2) gene amplification is important for predicting treatment response and prognosis in patients with breast cancer. Fluorescence in situ hybridization (FISH) is the gold standard for the diagnosis of HER2 status, particularly in cases with equivocal status on immunohistochemistry (IHC) staining, but has some limitations of non-classical amplifications and such cases are diagnosed basing on additional IHC and FISH. This study investigated the clinical utility of a novel super-resolution fluorescence microscopy technique for the better FISH signal visualization and HER2 FISH classification.

METHODS

Fourteen breast cancer tissue samples were retrospectively collected between September 2018 and February 2022, and FISH HER2 signal quantification was evaluated by determining the HER2/chromosome 17 centromere (CEP17) ratio and the number of HER2 signals per nucleus in super- versus conventional-resolution images.

RESULTS

Super-resolution images maintained the same overall HER2 diagnosis from routine, but HER2 FISH amplification changed negative to monosomy in two cases. Two Letrozole non-response relapses coincided to monosomy samples. The median number of HER2 signals per nucleus was 7.5 in super-resolution images and 4.0 in conventional-resolution images in HER2-positive samples and 2.8 and 2.1 signals per nucleus, respectively, in HER2-negative samples.

CONCLUSIONS

Super-resolution images improved signal visualization, including a significant difference in the number of countable HER2 and CEP17 signals in a single nucleus compared with conventional-resolution images. Increased accuracy of signal quantification by super-resolution microscopy may provide clinicians with more detailed information regarding HER2 FISH status that allows to better FISH classification such as HER2-low samples.

Runx2 heterozygosity alters homeostasis of the periodontal complex

BACKGROUND AND OBJECTIVE

Haploinsufficiency of Runx2 (Runx2+/- ) causes dental anomalies. However, little is known about the involvement of Runx2 in the maintenance of dentin, cementum, and the periodontal ligament (PDL) during adulthood. This study aimed to observe the effects of Runx2+/- on homeostasis of the periodontal complex.

MATERIALS AND METHODS

A total of 14 three-month-old Runx2+/- mice and their wild-type littermates were examined using micro-computed tomography, histology, and immunohistochemistry. Phenotypic alterations in the dentin, cementum, and PDL were characterized and quantified.

RESULTS

Haploinsufficiency of Runx2 caused cellular changes in the PDL space including reduction of cell proliferation and apoptosis, and irregular attachment of the collagen fibers in the PDL space into the cementum. Absence of continuous thickness of cementum was also observed in Runx2+/- mice.

CONCLUSION

Runx2 is critical for cementum integrity and attachment of periodontal fibers. Because of its importance to cementum homeostasis, Runx2 is essential for homeostasis of periodontal complex.

Enhancing the anticancer potential of metformin: fabrication of efficient nanospanlastics, in vitro cytotoxic studies on HEP-2 cells and reactome enhanced pathway analysis

Metformin (MET), an oral antidiabetic drug, was reported to possess promising anticancer effects. We hypothesized that MET encapsulation in unique nanospanlastics would enhance its anticancer potential against HEP-2 cells. Our results showed the successful fabrication of Nano-MET spanlastics (d = 232.10 ± 0.20 nm; PDI = 0.25 ± 0.11; zeta potential = (-) 44.50 ± 0.96; drug content = 99.90 ± 0.11 and entrapment efficiency = 88.01 ± 2.50%). MTT assay revealed the enhanced Nano-MET cytotoxicity over MET with a calculated IC50 of 50 μg/mL and > 500 μg/mL, respectively. Annexin V/PI apoptosis assay showed that Nano-MET significantly decreased the percentage of live cells from 95.49 to 93.70 compared to MET and increased the percentage of cells arrested in the G0/G1 phase by 8.38%. Moreover, Nano-MET downregulated BCL-2 and upregulated BAX protein levels by 1.57 and 1.88 folds, respectively. RT-qPCR revealed that Nano-MET caused a significant 13.75, 4.15, and 2.23-fold increase in caspase-3, -8, and - 9 levels as well as a 100 and 43.47-fold decrease in cyclin D1 and mTOR levels, respectively. The proliferation marker Ki67 immunofluorescent staining revealed a 3-fold decrease in positive cells in Nano-MET compared to the control. Utilizing the combined Pathway-Enrichment Analysis (PEA) and Reactome analysis indicated high enrichment of certain pathways including nucleotides metabolism, Nudix-type hydrolase enzymes, carbon dioxide hydration, hemostasis, and the innate immune system. In summary, our results confirm MET cytotoxicity enhancement by its encapsulation in nanospanlastics. We also highlight, using PEA, that MET can modulate multiple pathways implicated in carcinogenesis.

Diagnostic Role and Prognostic Impact of PSAP Immunohistochemistry: A Tissue Microarray Study on 31,358 Cancer Tissues

Prostate-specific acid phosphatase (PSAP) is a marker for prostate cancer. To assess the specificity and prognostic impact of PSAP, 14,137 samples from 127 different tumor (sub)types, 17,747 prostate cancers, and 76 different normal tissue types were analyzed via immunohistochemistry in a tissue microarray format. In normal tissues, PSAP staining was limited to the prostate epithelial cells. In prostate cancers, PSAP was seen in 100% of Gleason 3 + 3, 95.5% of Gleason 4 + 4, 93.8% of recurrent cancer under androgen deprivation therapy, 91.0% of Gleason 5 + 5, and 31.2% of small cell neuroendocrine cancer. In non-prostatic tumors, PSAP immunostaining was only found in 3.2% of pancreatic neuroendocrine tumors and in 0.8% of diffuse-type gastric adenocarcinomas. In prostate cancer, reduced PSAP staining was strongly linked to an advanced pT stage, a high classical and quantitative Gleason score, lymph node metastasis, high pre-operative PSA levels, early PSA recurrence (p < 0.0001 each), high androgen receptor expression, and TMPRSS2:ERG fusions. A low level of PSAP expression was linked to PSA recurrence independent of pre- and postoperative prognostic markers in ERG-negative cancers. Positive PSAP immunostaining is highly specific for prostate cancer. Reduced PSAP expression is associated with aggressive prostate cancers. These findings make PSAP a candidate marker for prognostic multiparameter panels in ERG-negative prostate cancers.

Deep learning to automatically evaluate HER2 gene amplification status from fluorescence in situ hybridization images

Human epidermal growth factor receptor 2 (HER2) gene amplification helps identify breast cancer patients who may respond to targeted anti-HER2 therapy. This study aims to develop an automated method for quantifying HER2 fluorescence in situ hybridization (FISH) signals and improve the working efficiency of pathologists. An Aitrox artificial intelligence (AI) model based on deep learning was constructed, and a comparison between the AI model and traditional manual counting was performed. In total, 918 FISH images from 320 consecutive invasive breast cancers were analysed and automatically classified into 5 groups according to the 2018 ASCO/CAP guidelines. The overall classification accuracy was 85.33% (157/184) with a mean average precision of 0.735. In Group 5, the most common group, the consistency was as high as 95.90% (117/122), while the consistency was low in the other groups due to the limited number of cases. The causes of this inconsistency, including clustered HER2 signals, coarse CEP17 signals and some section quality problems, were analysed. The developed AI model is a reliable tool for evaluating HER2 amplification statuses, especially for breast cancer in Group 5; additional cases from multiple centres could further improve the accuracy achieved for other groups.

Clinical Trials and Digital Pathology-Toward Quantitative Therapeutic Immunohistochemistry and Tissue Hybridization

This Viewpoint discusses immunohistochemistry and tissue-hybridization-based diagnostics delivery and compares it with digital pathology.

Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors

The expression of human epidermal growth factor receptor 2 (HER2) protein or gene transcripts is critical for therapeutic decision making in breast cancer. We examined the performance of a digitalized and artificial intelligence (AI)-assisted workflow for HER2 status determination in accordance with the American Society of Clinical Oncology (ASCO)/College of Pathologists (CAP) guidelines. Our preliminary cohort consisted of 495 primary breast carcinomas, and our study cohort included 67 primary breast carcinomas and 30 metastatic deposits, which were evaluated for HER2 status by immunohistochemistry (IHC) and in situ hybridization (ISH). Three practicing breast pathologists independently assessed and scored slides, building the ground truth. Following a washout period, pathologists were provided with the results of the AI digital image analysis (DIA) and asked to reassess the slides. Both rounds of assessment from the pathologists were compared to the AI results and ground truth for each slide. We observed an overall HER2 positivity rate of 15% in our study cohort. Moderate agreement (Cohen's κ 0.59) was observed between the ground truth and AI on IHC, with most discrepancies occurring between 0 and 1+ scores. Inter-observer agreement amongst pathologists was substantial (Fleiss´ κ 0.77) and pathologists' agreement with AI scores was 80.6%. Substantial agreement of the AI with the ground truth (Cohen´s κ 0.80) was detected on ISH-stained slides, and the accuracy of AI was similar for the primary and metastatic tumors. We demonstrated the feasibility of a combined HER2 IHC and ISH AI workflow, with a Cohen's κ of 0.94 when assessed in accordance with the ASCO/CAP recommendations.

Reliability of CD44, CD24, and ALDH1A1 immunohistochemical staining: Pathologist assessment compared to quantitative image analysis

Background

The data on the expression of stem cell markers CD44, CD24, and ALDH1A1 in the breast tissue of cancer-free women is very limited and no previous studies have explored the agreement between pathologist and computational assessments of these markers. We compared the immunohistochemical (IHC) expression assessment for CD44, CD24, and ALDH1A1 by an expert pathologist with the automated image analysis results and assessed the homogeneity of the markers across multiple cores pertaining to each woman.

Methods

We included 81 cancer-free women (399 cores) with biopsy-confirmed benign breast disease in the Nurses' Health Study (NHS) and NHSII cohorts. IHC was conducted with commercial antibodies [CD44 (Dako, Santa Clara, CA, USA) 1:25 dilution; CD24 (Invitrogen, Waltham, MA, USA) 1:200 dilution and ALDH1A1 (Abcam, Cambridge, United Kingdom) 1:300 dilution]. For each core, the percent positivity was quantified by the pathologist and Definiens Tissue Studio. Correlations between pathologist and computational scores were evaluated with Spearman correlation (for categorical positivity: 0, >0-<1, 1-10, >10-50, and >50%) and sensitivity/specificity (for binary positivity defined with 1 and 10% cut-offs), using the pathologist scores as the gold standard. Expression homogeneity was examined with intra-class correlation (ICC). Analyses were stratified by core [normal terminal duct-lobular units (TDLUs), benign lesions] and tissue type (epithelium, stroma).

Results

Spearman correlation between pathologist and Definiens ranged between 0.40-0.64 for stroma and 0.66-0.68 for epithelium in normal TDLUs cores and between 0.24-0.60 for stroma and 0.61-0.64 for epithelium in benign lesions. For stroma, sensitivity and specificity ranged between 0.92-0.95 and 0.24-0.60, respectively, with 1% cut-off and between 0.43-0.88 and 0.73-0.85, respectively, with 10% cut-off. For epithelium, 10% cut-off resulted in better estimates for both sensitivity and specificity. ICC between the cores was strongest for CD44 for both stroma and epithelium in normal TDLUs cores and benign lesions (range 0.74-0.80). ICC for CD24 and ALDH1A ranged between 0.42-0.63 and 0.44-0.55, respectively.

Conclusion

Our findings show that computational assessments for CD44, CD24, and ALDH1A1 exhibit variable correlations with manual assessment. These findings support the use of computational platforms for IHC evaluation of stem cell markers in large-scale epidemiologic studies. Pilot studies maybe also needed to determine appropriate cut-offs for defining staining positivity.

HER2-low breast cancer shows a lower immune response compared to HER2-negative cases

Currently, the human epidermal growth factor receptor 2 (HER2) status of breast cancer is classified dichotomously as negative or positive to select patients for HER2-targeted therapy. However, with the introduction of novel treatment options, it is important to get more insight in the biology of cancers with low HER2 expression. Therefore, we studied several clinicopathologic characteristics in relation to the level of HER2 expression (HER2- versus HER2low). We used a well-documented cohort of breast cancer patients (n = 529), with available tissue microarrays and Affymetrix mRNA expression data. HER2 status was scored as negative (immunohistochemistry 0) or low (immunohistochemistry 1 + or 2 + without amplification). We associated HER2 status with several clinicopathologic characteristics, gene-expression data and survival, stratified for estrogen receptor (ER) status. Overall, breast cancers were scored as HER2- (n = 429) or HER2low (n = 100). Within the ER+ cohort (n = 305), no significant associations were found between the HER2 groups and clinicopathologic features. However, HER2low tumors showed several differentially expressed genes compared to HER2- cases, including genes that are associated with worse outcome and depletion of immunity. In ER- cases (n = 224), HER2low status was significantly associated with increased regional nodal positivity, lower density of tumor infiltrating lymphocyte and a lower protein expression of Ki-67 and EGFR compared to HER2- cases. After multivariate analysis, only density of tumor infiltrating lymphocytes remained significantly associated with HER2low status (P = 0.035). No difference in survival was observed between HER2low and HER2- patients, neither in the ER+ nor ER- cohort. In conclusion, our data suggests that HER2low breast cancer is associated with a lower immune response compared to HER2- breast cancer.

Digital validation of breast biomarkers (ER, PR, AR, and HER2) in cytology specimens using three different scanners

Progression in digital pathology has yielded new opportunities for a remote work environment. We evaluated the utility of digital review of breast cancer immunohistochemical prognostic markers (IHC) using whole slide images (WSI) from formalin fixed paraffin embedded (FFPE) cytology cell block specimens (CB) using three different scanners.CB from 20 patients with breast cancer diagnosis and available IHC were included. Glass slides including 20 Hematoxylin and eosin (H&E), 20 Estrogen Receptor (ER), 20 Progesterone Receptor (PR), 16 Androgen Receptor (AR), and 20 Human Epidermal Growth Factor Receptor 2 (HER2) were scanned on 3 different scanners. Four breast pathologists reviewed the WSI and recorded their semi-quantitative scoring for each marker. Kappa concordance was defined as complete agreement between glass/digital pairs. Discordances between microscopic and digital reads were classified as a major when a clinically relevant change was seen. Minor discordances were defined as differences in scoring percentages/staining pattern that would not have resulted in a clinical implication. Scanner precision was tabulated according to the success rate of each scan on all three scanners.In total, we had 228 paired glass/digital IHC reads on all 3 scanners. There was strong concordance kappa ≥0.85 for all pathologists when comparing paired microscopic/digital reads. Strong concordance (kappa ≥0.86) was also seen when comparing reads between scanners.Twenty-three percent of the WSI required rescanning due to barcode detection failures, 14% due to tissue detection failures, and 2% due to focus issues. Scanner 1 had the best average precision of 92%. HER2 IHC had the lowest intra-scanner precision (64%) among all stains.This study is the first to address the utility of WSI in breast cancer IHC in CB and to validate its reporting using 3 different scanners. Digital images are reliable for breast IHC assessment in CB and offer similar reproducibility to microscope reads.

Her2-Positive Cancers and Antibody-Based Treatment: State of the Art and Future Developments

HER2 positive breast cancer represent about 20% of all breast cancer subtypes and it was considered the subtype with the worst prognosis until the discovery of therapies directed against the HER2 protein. The determination of the status of the HER2 must be very precise and well managed to identify this subtype, and there are very specific and updated guides that allow its characterization to be adjusted. Treatment in local disease has been considerably improved with less aggressive and highly effective approaches and very high cure rates. In metastatic disease, average median survival rates of 5 years have been achieved. New highly active molecules have also been discovered that allow disease control in very complicated situations. This article reviews all these options that can be used for the management of this disease.

The Value of Nomograms in Pre-Operative Prediction of Lymphovascular Invasion in Primary Breast Cancer Undergoing Modified Radical Surgery: Based on Multiparametric Ultrasound and Clinicopathologic Indicators

The purpose of this study was to explore the value of pre-operative prediction of lymphovascular invasion (LVI) in primary breast cancer patients undergoing modified radical mastectomy and to develop a nomogram based on multiparametric ultrasound and clinicopathologic indicators. All patients with primary breast cancer confirmed by pre-operative biopsy underwent B-mode ultrasound and contrast-enhanced ultrasound examinations. Post-operative pathology was used as the gold standard to identify LVI. Lasso regression was used to select predictors most related to LVI. A nomogram was developed to calculate the diagnostic efficacy. We bootstrapped the data for 500 times to perform internal verification, drawing a calibration curve to verify prediction ability. A total of 244 primary breast cancer patients were included. LVI was observed in 77 patients. Ten predictors associated with LVI were selected by Lasso regression. The area under the curve, sensitivity, specificity and accuracy for the nomogram were 0.918, 92.2%, 76.7% and 81.6%, respectively. And the nomogram calibration curve showed good consistency between the predicted probability and the actual probability. The nomogram developed could be used to predict LVI in primary breast cancer patients undergoing modified radical mastectomy and to help in clinical decision-making.

Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology

Tumor stage and grade, visually assessed by pathologists from evaluation of pathology images in conjunction with radiographic imaging techniques, have been linked to outcome, progression, and survival for a number of cancers. The gold standard of staging in oncology has been the TNM (tumor-node-metastasis) staging system. Though histopathological grading has shown prognostic significance, it is subjective and limited by interobserver variability even among experienced surgical pathologists. Recently, artificial intelligence (AI) approaches have been applied to pathology images toward diagnostic-, prognostic-, and treatment prediction-related tasks in cancer. AI approaches have the potential to overcome the limitations of conventional TNM staging and tumor grading approaches, providing a direct prognostic prediction of disease outcome independent of tumor stage and grade. Broadly speaking, these AI approaches involve extracting patterns from images that are then compared against previously defined disease signatures. These patterns are typically categorized as either (1) handcrafted, which involve domain-inspired attributes, such as nuclear shape, or (2) deep learning (DL)-based representations, which tend to be more abstract. DL approaches have particularly gained considerable popularity because of the minimal domain knowledge needed for training, mostly only requiring annotated examples corresponding to the categories of interest. In this article, we discuss AI approaches for digital pathology, especially as they relate to disease prognosis, prediction of genomic and molecular alterations in the tumor, and prediction of treatment response in oncology. We also discuss some of the potential challenges with validation, interpretability, and reimbursement that must be addressed before widespread clinical deployment. The article concludes with a brief discussion of potential future opportunities in the field of AI for digital pathology and oncology.

Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists

CONTEXT.—

Advancements in genomic, computing, and imaging technology have spurred new opportunities to use quantitative image analysis (QIA) for diagnostic testing.

OBJECTIVE.—

To develop evidence-based recommendations to improve accuracy, precision, and reproducibility in the interpretation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) for breast cancer where QIA is used.

DESIGN.—

The College of American Pathologists (CAP) convened a panel of pathologists, histotechnologists, and computer scientists with expertise in image analysis, immunohistochemistry, quality management, and breast pathology to develop recommendations for QIA of HER2 IHC in breast cancer. A systematic review of the literature was conducted to address 5 key questions. Final recommendations were derived from strength of evidence, open comment feedback, expert panel consensus, and advisory panel review.

RESULTS.—

Eleven recommendations were drafted: 7 based on CAP laboratory accreditation requirements and 4 based on expert consensus opinions. A 3-week open comment period received 180 comments from more than 150 participants.

CONCLUSIONS.—

To improve accurate, precise, and reproducible interpretation of HER2 IHC results for breast cancer, QIA and procedures must be validated before implementation, followed by regular maintenance and ongoing evaluation of quality control and quality assurance. HER2 QIA performance, interpretation, and reporting should be supervised by pathologists with expertise in QIA.

Insulin-like growth factor-1 receptor expression in upper tract urothelial carcinoma

Insulin-like growth factor-1 receptor (IGF1R) is a transmembrane tyrosine kinase receptor that plays a crucial role in cell proliferation, growth, differentiation, and apoptosis. IGF1R overexpression has been observed in several cancers, including invasive bladder carcinomas, as a potential prognostic factor. Given known biologic differences between upper and lower urinary tract urothelial carcinoma, we assessed the expression status and prognostic significance of IGF1R in upper tract urothelial carcinoma (UTUC). Two tissue microarrays (TMAs) were built from 99 Japanese patients with non-metastatic UTUC submitted to radical nephroureterectomy between 1997 and 2011. TMAs were constructed with triplicate tumor and paired benign urothelium. Membranous IGF1R staining was evaluated using immunohistochemistry. Two scoring methods were applied (Her2-score and H-score). The highest score was assigned to each tumor. IGF1R positivity was defined as Her2-score ≥ 1+. Association with clinicopathologic parameters and outcome was assessed using hazard ratios (HR) with 95% confidence intervals (CI) and adjusted P values. We found positive IGF1R expression in 70% of UTUC. Outcomes were as follows: tumor recurrence, 33%; tumor progression, 59%; overall mortality, 33%; and cancer-specific mortality, 30%. IGF1R was not associated with any clinicopathologic features. In addition, IGF1R expression was not associated with tumor recurrence (HR = 0.54, CI = 0.25-1.1, P = 0.11), tumor progression (HR = 1.6, CI = 0.8-3.1, P = 0.19), overall mortality (HR = 1.5, CI = 0.68-3.4, P = 0.31), or cancer-specific mortality (HR = 1.6, CI = 0.68-3.8, P = 0.27). Positive IGF1R expression was found in more than two thirds of UTUC. This finding provides a rationale to investigate IGF1R as a potential therapeutic target in UTUC. In contrast to bladder cancer, IGF1R expression in UTUC did not correlate with outcome, further pointing to biologic differences between UTUC and bladder cancer.

A nomogram for individual prediction of vascular invasion in primary breast cancer

OBJECTIVES

To explore the feasibility of preoperative prediction of vascular invasion (VI) in breast cancer patients using nomogram based on multiparametric MRI and pathological reports.

METHODS

We retrospectively collected 200 patients with confirmed breast cancer between January 2016 and January 2018. All patients underwent MRI examinations before the surgery. VI was identified by postoperative pathology. The 200 patients were randomly divided into training (n = 100) and validation datasets (n = 100) at a ratio of 1:1. Least absolute shrinkage and selection operator (LASSO) regression was used to select predictors most associated with VI of breast cancer. A nomogram was constructed to calculate the area under the curve (AUC) of receiver operating characteristics, sensitivity, specificity, accuracy, positive prediction value (PPV) and negative prediction value (NPV). We bootstrapped the data for 2000 times without setting the random seed to obtain corrected results.

RESULTS

VI was observed in 79 patients (39.5%). LASSO selected 10 predictors associated with VI. In the training dataset, the AUC for nomogram was 0.94 (95% confidence interval [CI]: 0.89-0.99, the sensitivity was 78.9% (95%CI: 72.4%-89.1%), the specificity was 95.3% (95%CI: 89.1%-100.0%), the accuracy was 86.0% (95%CI: 82.0%-92.0%), the PPV was 95.7% (95%CI: 90.0%-100.0%), and the NPV was 77.4% (95%CI: 67.8%-87.0%). In the validation dataset, the AUC for nomogram was 0.89 (95%CI: 0.83-0.95), the sensitivity was 70.3% (95%CI: 60.7%-79.2%), the specificity was 88.9% (95%CI: 80.0%-97.1%), the accuracy was 77.0% (95%CI: 70.0%-83.0%), the PPV was 91.8% (95%CI: 85.3%-98.0%), and the NPV was 62.7% (95%CI: 51.7%-74.0%). The nomogram calibration curve shows good agreement between the predicted probability and the actual probability.

CONCLUSION

The proposed nomogram could be used to predict VI in breast cancer patients, which was helpful for clinical decision-making.

Caspase-3, a key apoptotic protein, as a prognostic marker in gastric cancer after curative surgery

BACKGROUND

Caspase-3 acts as a major executioner protein in proteolytic degradation during apoptosis. The role of Caspase-3 in gastric cancer remains controversial.

METHODS

A total of 366 gastric cancer patients who received curative surgery were enrolled. Caspase-3 expression in gastric tumors was examined by immunohistochemical staining. Correlations between Caspase-3 expression and the survival rates and between Caspase-3 expression and the clinicopathological parameters of the gastric cancer patients were analyzed.

RESULTS

The 5-year overall survival rates of gastric cancer patients with and without Caspase-3 expression were 51.2% and 37.3%, respectively (P = 0.030). The 5-year disease-free survival rates of gastric cancer patients with and without Caspase-3 expression were 49.2% and 34.6%, respectively (P = 0.029). Analyses of the clinicopathological features showed that larger tumor size (P = 0.030), more advanced Borrmann type (P = 0.012), more aggressive stromal reaction (P = 0.001), higher classification using Ming's infiltrating histology type (P = 0.018), more lymph node involvement (P = 0.019), and more lymphovascular involvement (P = 0.045) were significantly correlated with a lack of Caspase-3 expression. The multivariate analysis showed that age (P = 0.001), Borrmann classification (P = 0.032), stromal reaction type (P = 0.018), TNM pathological T category (P = 0.002), TNM pathological N category (P < 0.001), and Caspase-3 expression (P = 0.041) were significantly correlated with the overall survival of gastric cancer patients.

CONCLUSION

Caspase-3 expression in gastric cancer patients is related to favorable clinicopathological features and a positive prognosis after curative surgery. Caspase-3 may act as a tumor suppressor in human gastric cancer.

Comparison of visual and automated assessment of HER2 status and their impact on outcome in primary operable invasive ductal breast cancer

AIMS

To compare visual and computerized image analysis of HER2 immunohistochemistry (IHC) with fluorescence in-situ hybridization (FISH) for HER2 status, and to examine the relationships with outcome in patients with primary operable invasive ductal breast cancer.

METHODS AND RESULTS

Tissue microarrays for 431 breast cancer patients were used to compare different approaches to the assessment of HER2 status. The cores were scored visually and with the Slidepath Tissue IA system, using the NICE-approved scoring system for the HercepTest, as well as by FISH. The agreement between visual and image analysis of HER2 IHC was excellent [interclass correlation coefficient (ICCC) = 0.95, rs = 0.90, r = 0.91, k = 0.81, and P < 0.001]. The agreement of HER2 FISH with visual and image analysis of HER2 IHC was also excellent (ICCC = 0.95 and ICCC = 0.92, respectively). Univariate survival analysis showed equivalent associations of visual and image analysis of HER2 and HER2 FISH with both recurrence-free survival (all P < 0.01) and cancer-specific survival (all P < 0.05) in patients with invasive ductal breast cancer.

CONCLUSION

Computerized image analysis of HER2 IHC gives results comparable to those obtained with visual assessment, with possible advantages in diagnostic pathology.

Commentary

Historically, pathologists perform manual evaluation of H&E- or immunohistochemically-stained slides, which can be subjective, inconsistent, and, at best, semiquantitative. As the complexity of staining and demand for increased precision of manual evaluation increase, the pathologist’s assessment will include automated analyses (i.e., “digital pathology”) to increase the accuracy, efficiency, and speed of diagnosis and hypothesis testing and as an important biomedical research and diagnostic tool. This commentary introduces the many roles for pathologists in designing and conducting high-throughput digital image analysis. Pathology review is central to the entire course of a digital pathology study, including experimental design, sample quality verification, specimen annotation, analytical algorithm development, and report preparation. The pathologist performs these roles by reviewing work undertaken by technicians and scientists with training and expertise in image analysis instruments and software. These roles require regular, face-to-face interactions between team members and the lead pathologist. Traditional pathology training is suitable preparation for entry-level participation on image analysis teams. The future of pathology is very exciting, with the expanding utilization of digital image analysis set to expand pathology roles in research and drug development with increasing and new career opportunities for pathologists.

Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor β2 immunohistochemistry in prostate cancer

Background

Digital image analysis offers advantages over traditional pathologist visual scoring of immunohistochemistry, although few studies examining the correlation and reproducibility of these methods have been performed in prostate cancer. We evaluated the correlation between digital image analysis (continuous variable data) and pathologist visual scoring (quasi-continuous variable data), reproducibility of each method, and association of digital image analysis methods with outcomes using prostate cancer tissue microarrays (TMAs) stained for estrogen receptor-β2 (ERβ2).

Methods

Prostate cancer TMAs were digitized and evaluated by pathologist visual scoring versus digital image analysis for ERβ2 staining within tumor epithelium. Two independent analysis runs were performed to evaluate reproducibility. Image analysis data were evaluated for associations with recurrence-free survival and disease specific survival following radical prostatectomy.

Results

We observed weak/moderate Spearman correlation between digital image analysis and pathologist visual scores of tumor nuclei (Analysis Run A: 0.42, Analysis Run B: 0.41), and moderate/strong correlation between digital image analysis and pathologist visual scores of tumor cytoplasm (Analysis Run A: 0.70, Analysis Run B: 0.69). For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99). Further, ERβ2 staining was significantly associated with increased risk of prostate cancer-specific mortality (PCSM) when quantified by cytoplasmic digital image analysis (HR 2.16, 95 % CI 1.02–4.57, p = 0.045), nuclear image analysis (HR 2.67, 95 % CI 1.20–5.96, p = 0.016), and total malignant epithelial area analysis (HR 5.10, 95 % CI 1.70–15.34, p = 0.004). After adjusting for clinicopathologic factors, only total malignant epithelial area ERβ2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37–12.15, p = 0.012).

Conclusions

Digital methods of immunohistochemical quantification are more reproducible than pathologist visual scoring in prostate cancer, suggesting that digital methods are preferable and especially warranted for studies involving large sample sizes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13000-016-0511-5) contains supplementary material, which is available to authorized users.

Validation of the IHC4 Breast Cancer Prognostic Algorithm Using Multiple Approaches on the Multinational TEAM Clinical Trial

CONTEXT

Hormone receptors HER2/neu and Ki-67 are markers of residual risk in early breast cancer. An algorithm (IHC4) combining these markers may provide additional information on residual risk of recurrence in patients treated with hormone therapy.

OBJECTIVE

To independently validate the IHC4 algorithm in the multinational Tamoxifen Versus Exemestane Adjuvant Multicenter Trial (TEAM) cohort, originally developed on the trans-ATAC (Arimidex, Tamoxifen, Alone or in Combination Trial) cohort, by comparing 2 methodologies.

DESIGN

The IHC4 biomarker expression was quantified on TEAM cohort samples (n = 2919) by using 2 independent methodologies (conventional 3,3'-diaminobezidine [DAB] immunohistochemistry with image analysis and standardized quantitative immunofluorescence [QIF] by AQUA technology). The IHC4 scores were calculated by using the same previously established coefficients and then compared with recurrence-free and distant recurrence-free survival, using multivariate Cox proportional hazards modeling.

RESULTS

The QIF model was highly significant for prediction of residual risk (P < .001), with continuous model scores showing a hazard ratio (HR) of 1.012 (95% confidence interval [95% CI]: 1.010-1.014), which was significantly higher than that for the DAB model (HR: 1.008, 95% CI: 1.006-1.009); P < .001). Each model added significant prognostic value in addition to recognized clinical prognostic factors, including nodal status, in multivariate analyses. Quantitative immunofluorescence, however, showed more accuracy with respect to overall residual risk assessment than the DAB model.

CONCLUSIONS

The use of the IHC4 algorithm was validated on the TEAM trial for predicting residual risk in patients with breast cancer. These data support the use of the IHC4 algorithm clinically, but quantitative and standardized approaches need to be used.

Free digital image analysis software helps to resolve equivocal scores in HER2 immunohistochemistry

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.

Epidermal growth factor receptor immunohistochemistry: new opportunities in metastatic colorectal cancer

The treatment of cancer is becoming more precise, targeting specific oncogenic drivers with targeted molecular therapies. The epidermal growth factor receptor has been found to be over-expressed in a multitude of solid tumours. Immunohistochemistry is widely used in the fields of diagnostic and personalised medicine to localise and visualise disease specific proteins. To date the clinical utility of epidermal growth factor receptor immunohistochemistry in determining monoclonal antibody efficacy has remained somewhat inconclusive. The lack of an agreed reproducible scoring criteria for epidermal growth factor receptor immunohistochemistry has, in various clinical trials yielded conflicting results as to the use of epidermal growth factor receptor immunohistochemistry assay as a companion diagnostic. This has resulted in this test being removed from the licence for the drug panitumumab and not performed in clinical practice for cetuximab. In this review we explore the reasons behind this with a particular emphasis on colorectal cancer, and to suggest a way of resolving the situation through improving the precision of epidermal growth factor receptor immunohistochemistry with quantitative image analysis of digitised images complemented with companion molecular morphological techniques such as in situ hybridisation and section based gene mutation analysis.

Comparative study between quantitative digital image analysis and fluorescence in situ hybridization of breast cancer equivocal human epidermal growth factor receptors 2 score 2(+) cases

Background:

Optimization of workflow for breast cancer samples with equivocal human epidermal growth factor receptors 2 (HER2)/neu score 2⁺ results in routine practice, remains to be a central focus of the on-going efforts to assess HER2 status. According to the College of American Pathologists/American Society of Clinical Oncology guidelines equivocal HER2/neu score 2⁺ cases are subject for further testing, usually by fluorescence in situ hybridization (FISH) investigations. It still remains on open question, whether quantitative digital image analysis of HER2 immunohistochemistry (IHC) stained slides can assist in further refining the HER2 score 2⁺.

Aim of this Work:

To assess utility of quantitative digital analysis of IHC stained slides and compare its performance to FISH in cases of breast cancer with equivocal HER2 score 2⁺.

Materials and Methods:

Fifteen specimens (previously diagnosed as breast cancer and was evaluated as HER 2^- score 2⁺) represented the study population. Contemporary new cuts were prepared for re-evaluation of HER2 immunohistochemical studies and FISH examination. All the cases were digitally scanned by iScan (Produced by BioImagene [Now Roche-Ventana]). The IHC signals of HER2 were measured using an automated image analyzing system (MECES, www.Diagnomx.eu/meces). Finally, a comparative study was done between the results of the FISH and the quantitative analysis of the virtual slides.

Results:

Three out of the 15 cases with equivocal HER2 score 2⁺, turned out to be positive (3⁺) by quantitative digital analysis, and 12 were found to be negative in FISH too. Two of these three positive cases proved to be positive with FISH, and only one was negative.

Conclusions:

Quantitative digital analysis is highly sensitive and relatively specific when compared to FISH in detecting HER2/neu overexpression. Therefore, it represents a potential reliable substitute for FISH in breast cancer cases, which desire further refinement of equivocal IHC results.

Whole slide imaging for human epidermal growth factor receptor 2 immunohistochemistry interpretation: Accuracy, Precision, and reproducibility studies for digital manual and paired glass slide manual interpretation

Background:

The use of digital whole slide imaging for human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) could create improvements in workflow and performance, allowing for central archiving of specimens, distributed and remote interpretation, and the potential for additional computerized automation.

Procedures:

The accuracy, precision, and reproducibility of manual digital interpretation for HER2 IHC were determined by comparison to manual glass slide interpretation. Inter- and intra-pathologist reproducibility and precision between the glass slide and digital interpretations of HER2 IHC were determined in 5 studies using DAKO HercepTest-stained breast cancer slides with the Philips Digital Pathology System. In 2 inter-method studies, 3 pathologists interpreted glass and digital slides in sequence or in random order with a minimum of 7 days as a washout period. These studies also measured inter-observer reproducibility and precision. Another two studies measured intra-pathologist reproducibility on cases read 10 times by glass and digital methods. One additional study evaluated the effects of adding IHC control slides with each run, using 1 pathologist interpreting glass and digital slides randomized from the sets above along with appropriate controls for each slide in the set.

Results:

The overall results show that there is no statistical difference between the variance of performance when comparing glass and digital HER2 interpretations; and there were no effects noted when control tissues were evaluated in conjunction with the test slides.

Conclusions:

The results show that there is an equivalence of result when interpreting HER2 IHC slides in breast cancer by either glass slides or digital images. Digital interpretation can therefore be safely and effectively used for this purpose.

Assessing fibrinogen extravasation into Alzheimer's disease brain using high-content screening of brain tissue microarrays

BACKGROUND

Tissue microarrays are commonly used to evaluate disease pathology however methods to automate and quantify pathological changes are limited.

NEW METHOD

This article demonstrates the utility of the VSlide scanner (MetaSystems) for automated image acquisition from immunolabelled tissue microarray slides, and subsequent automated image analysis with MetaXpress (Molecular Devices) software to obtain objective, efficient and reproducible data from immunolabelled tissue microarray sections.

RESULTS

Significant increases in fibrinogen immunolabelling were observed in 29 Alzheimer's disease cases compared to 28 control cases analysed from a single tissue microarray slide. Western blot analysis also demonstrated significant increases in fibrinogen immunolabelling in 6 Alzheimer's cases compared to 6 control cases. The observed changes were also validated with gold standard blinded manual H-scoring.

COMPARISON WITH EXISTING METHOD

VSlide Metafer software offers a 'tissue microarray acquisition' plugin for easy mapping of tissue cores with their original position on the tissue microarray map. High resolution VSlide images are compatible with MetaXpress image analysis software. This article details the coupling of these two technologies to accurately and reproducibly analyse immunolabelled tissue microarrays within minutes, compared to the gold standard method of manual counting using H-scores which is significantly slower and prone to inter-observer variation.

CONCLUSIONS

Here, we couple brain tissue microarray technology with high-content screening and automated image analysis as a powerful way to address bottle necks in data generation and improve throughput, as well as sensitivity to study biological/pathological changes in brain disease.

Breast cancer histopathology image analysis: a review

This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients.

Human epidermal growth factor receptor 2 testing in primary breast cancer in the era of standardized testing: a Canadian prospective study

PURPOSE

Therapies that target overexpression of human epidermal growth factor receptor 2 (HER2) rely on accurate and timely assessment of all patients with new diagnoses. This study examines HER2 testing of primary breast cancer tissue when performed with immunohistochemistry (IHC) and additional in situ hybridization (ISH) for negative cases (IHC 0/1+). The analysis focuses on the rate of false-negative HER2 tests, defined as IHC 0/1+ with an ISH ratio ≥ 2.0, in eight pathology centers across Canada.

PATIENTS AND METHODS

Whole sections of surgical resections or tissue microarrays (TMAs) from invasive breast carcinoma tissue were tested by both IHC and ISH using standardized local methods. Samples were scored by the local breast pathologist, and consecutive HER2-negative IHC results (IHC 0/1+) were compared with the corresponding fluorescence or silver ISH result.

RESULTS

Overall, 711 surgical excisions of primary breast cancer were analyzed by IHC and ISH; HER2 and chromosome 17 centromere (CEP17) counts were available in all cases. The overall rate of false-negative samples was 0.84% (six of 711 samples). Interpretable IHC and ISH scores were available in 1,212 cases from TMAs, and the overall rate of false-negative cases was 1.6% (16 of 978 cases).

CONCLUSION

Our observation confirms that IHC is an adequate test to predict negative HER2 status in primary breast cancer in surgical excision specimens, even when different antibodies and IHC platforms are used. The study supports the American Society of Clinical Oncology/College of American Pathologists and Canadian testing algorithms of using IHC followed by ISH for equivocal cases.

Image analysis of immunohistochemistry is superior to visual scoring as shown for patient outcome of esophageal adenocarcinoma

Quantification of protein expression based on immunohistochemistry (IHC) is an important step in clinical diagnoses and translational tissue-based research. Manual scoring systems are used in order to evaluate protein expression based on staining intensities and distribution patterns. However, visual scoring remains an inherently subjective approach. The aim of our study was to explore whether digital image analysis proves to be an alternative or even superior tool to quantify expression of membrane-bound proteins. We analyzed five membrane-binding biomarkers (HER2, EGFR, pEGFR, β-catenin, and E-cadherin) and performed IHC on tumor tissue microarrays from 153 esophageal adenocarcinomas patients from a single center study. The tissue cores were scored visually applying an established routine scoring system as well as by using digital image analysis obtaining a continuous spectrum of average staining intensity. Subsequently, we compared both assessments by survival analysis as an end point. There were no significant correlations with patient survival using visual scoring of β-catenin, E-cadherin, pEGFR, or HER2. In contrast, the results for digital image analysis approach indicated that there were significant associations with disease-free survival for β-catenin, E-cadherin, pEGFR, and HER2 (P = 0.0125, P = 0.0014, P = 0.0299, and P = 0.0096, respectively). For EGFR, there was a greater association with patient survival when digital image analysis was used compared to when visual scoring was (visual: P = 0.0045, image analysis: P < 0.0001). The results of this study indicated that digital image analysis was superior to visual scoring. Digital image analysis is more sensitive and, therefore, better able to detect biological differences within the tissues with greater accuracy. This increased sensitivity improves the quality of quantification.

Reverse-phase protein microarray highlights HER2 signaling activation in immunohistochemistry/FISH/HER2-negative breast cancers

EVALUATION OF: Wulfkuhle JD, Berg D, Wolff C et al. Molecular analysis of HER2 signaling in human breast cancer by functional protein pathway activation mapping. Clin. Cancer Res. 18(23), 6426-6435 (2012). Exhaustive characterization and mapping of pivotal molecules and downstream effectors deregulated in breast cancer is of fundamental clinical value to define the most effective therapy. Wulfkuhle et al. applied reverse-phase protein microarray, a highly sensitive immunoassay able to perform quantitative and multiplexed analysis of total and/or modified cellular proteins, to assess protein levels and activation/phosphorylation status of the HER family (EGFR, HER2, HER3) and downstream signaling molecules in HER2(+) and HER2(-) breast cancers. The research was performed using laser capture microdissected tumor epithelial cells from frozen samples and formalin-fixed paraffin embedded specimens, which were also analyzed by immunohistochemistry (IHC) and FISH. This study identified a subgroup of IHC/FISH/HER2(-) patients with HER2 activation/phosphorylation levels comparable with those obtained from IHC/FISH/HER2(+) tumors. HER2 signaling activation was independent from total HER2 expression and involved HER3 and EGFR activation. These findings indicate that molecular characterization by reverse-phase protein microarray of HER2 and its partners/effectors in the signaling cascade enables the identification of a subgroup of IHC/FISH/HER2(-) patients showing HER2 signaling activation. These patients, currently excluded from targeted therapy administration, could potentially benefit from this and it could improve prognosis and survival.

Differences in estrogen and progesterone receptor expression in endometrial polyps and atrophic endometrium of postmenopausal women with and without exposure to tamoxifen

Postmenopausal women who use tamoxifen present with an increased incidence of endometrial alterations, such as polyps and hyperplasia, in addition to a higher risk of malignant endometrial neoplasms. Among these endometrial changes, polyps are the most common, with a pathogenesis associated with hormonal influence. The objective of this study was to compare the expression of estrogen receptors (ERs) and progesterone receptors (PRs) in endometrial polyps from tamoxifen users with that in endometrial polyps and the atrophic endometrium of postmenopausal tamoxifen non-users. Among women undergoing surgical hysteroscopy, 84 tamoxifen users with benign endometrial polyps were selected. This group was compared to 84 samples of atrophic endometrium and to 252 benign polyps from postmenopausal women who were not treated with tamoxifen. The expression of ER/PR was assessed by immunohistochemical analysis, according to the percentage of stained cells, intensity of nuclear staining and final score. The polyps from tamoxifen users exhibited a higher expression of ER and PR in the glandular epithelium and stroma compared to the atrophic endometrium (P<0.0001). Compared to the polyps from women not treated with tamoxifen, tamoxifen users exhibited a higher PR expression in the epithelium (P=0.0014) and stroma (P=0.0056), with no difference in the expression of ER. In conclusion, endometrial polyps frequently exhibit an increase in ER expression, regardless of tamoxifen use. High levels of PR expression appear to be consistent with the estrogen agonist effects of tamoxifen.

Single-cell quantitative HER2 measurement identifies heterogeneity and distinct subgroups within traditionally defined HER2-positive patients

Human epidermal growth factor receptor 2 (HER2) is an important biomarker for breast and gastric cancer prognosis and patient treatment decisions. HER2 positivity, as defined by IHC or fluorescent in situ hybridization testing, remains an imprecise predictor of patient response to HER2-targeted therapies. Challenges to correct HER2 assessment and patient stratification include intratumoral heterogeneity, lack of quantitative and/or objective assays, and differences between measuring HER2 amplification at the protein versus gene level. We developed a novel immunofluorescence method for quantitation of HER2 protein expression at the single-cell level on FFPE patient samples. Our assay uses automated image analysis to identify and classify tumor versus non-tumor cells, as well as quantitate the HER2 staining for each tumor cell. The HER2 staining level is converted to HER2 protein expression using a standard cell pellet array stained in parallel with the tissue sample. This approach allows assessment of HER2 expression and heterogeneity within a tissue section at the single-cell level. By using this assay, we identified distinct subgroups of HER2 heterogeneity within traditional definitions of HER2 positivity in both breast and gastric cancers. Quantitative assessment of intratumoral HER2 heterogeneity may offer an opportunity to improve the identification of patients likely to respond to HER2-targeted therapies. The broad applicability of the assay was demonstrated by measuring HER2 expression profiles on multiple tumor types, and on normal and diseased heart tissues.

Astronomical algorithms for automated analysis of tissue protein expression in breast cancer

BACKGROUND

High-throughput evaluation of tissue biomarkers in oncology has been greatly accelerated by the widespread use of tissue microarrays (TMAs) and immunohistochemistry. Although TMAs have the potential to facilitate protein expression profiling on a scale to rival experiments of tumour transcriptomes, the bottleneck and imprecision of manually scoring TMAs has impeded progress.

METHODS

We report image analysis algorithms adapted from astronomy for the precise automated analysis of IHC in all subcellular compartments. The power of this technique is demonstrated using over 2000 breast tumours and comparing quantitative automated scores against manual assessment by pathologists.

RESULTS

All continuous automated scores showed good correlation with their corresponding ordinal manual scores. For oestrogen receptor (ER), the correlation was 0.82, P<0.0001, for BCL2 0.72, P<0.0001 and for HER2 0.62, P<0.0001. Automated scores showed excellent concordance with manual scores for the unsupervised assignment of cases to 'positive' or 'negative' categories with agreement rates of up to 96%.

CONCLUSION

The adaptation of astronomical algorithms coupled with their application to large annotated study cohorts, constitutes a powerful tool for the realisation of the enormous potential of digital pathology.

Targeting the HGF/c-MET pathway in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a significant cause of cancer-related morbidity and mortality worldwide. Despite improvements in local therapies, including surgical resection, liver transplantation, and transarterial embolization, the prognosis remains poor for the majority of patients who develop recurrence or present with advanced disease. Systemic therapy with the tyrosine kinase inhibitor sorafenib represents a milestone in advanced HCC but provides a limited survival benefit. Ongoing efforts to study hepatocarcinogenesis have identified an important role for c-MET signaling in the promotion of tumor growth, angiogenesis, and metastasis. In this review, we summarize the preclinical data from human tissue, cell lines, and animal models that implicate c-MET in the pathogenesis of HCC. We also evaluate potential biomarkers that may estimate prognosis or predict response to c-MET inhibitors for more rational clinical trial design. Finally, we discuss the latest clinical trials of c-MET inhibitors in advanced HCC.

Automated Quantitative Analysis of p53, Cyclin D1, Ki67 and pERK Expression in Breast Carcinoma Does Not Differ from Expert Pathologist Scoring and Correlates with Clinico-Pathological Characteristics

There is critical need for improved biomarker assessment platforms which integrate traditional pathological parameters (TNM stage, grade and ER/PR/HER2 status) with molecular profiling, to better define prognostic subgroups or systemic treatment response. One roadblock is the lack of semi-quantitative methods which reliably measure biomarker expression. Our study assesses reliability of automated immunohistochemistry (IHC) scoring compared to manual scoring of five selected biomarkers in a tissue microarray (TMA) of 63 human breast cancer cases, and correlates these markers with clinico-pathological data. TMA slides were scanned into an Ariol Imaging System, and histologic (H) scores (% positive tumor area x staining intensity 0–3) were calculated using trained algorithms. H scores for all five biomarkers concurred with pathologists’ scores, based on Pearson correlation coefficients (0.80–0.90) for continuous data and Kappa statistics (0.55–0.92) for positive vs. negative stain. Using continuous data, significant association of pERK expression with absence of LVI (p = 0.005) and lymph node negativity (p = 0.002) was observed. p53 over-expression, characteristic of dysfunctional p53 in cancer, and Ki67 were associated with high grade (p = 0.032 and 0.0007, respectively). Cyclin D1 correlated inversely with ER/PR/HER2-ve (triple negative) tumors (p = 0.0002). Thus automated quantitation of immunostaining concurs with pathologists’ scoring, and provides meaningful associations with clinico-pathological data.

Quantitative comparison of immunohistochemical staining measured by digital image analysis versus pathologist visual scoring

Abstract

Immunohistochemical (IHC) assays performed on formalin-fixed paraffin-embedded (FFPE) tissue sections traditionally have been semi-quantified by pathologist visual scoring of staining. IHC is useful for validating biomarkers discovered through genomics methods as large clinical repositories of FFPE specimens support the construction of tissue microarrays (TMAs) for high throughput studies. Due to the ubiquitous availability of IHC techniques in clinical laboratories, validated IHC biomarkers may be translated readily into clinical use. However, the method of pathologist semi-quantification is costly, inherently subjective, and produces ordinal rather than continuous variable data. Computer-aided analysis of digitized whole slide images may overcome these limitations. Using TMAs representing 215 ovarian serous carcinoma specimens stained for S100A1, we assessed the degree to which data obtained using computer-aided methods correlated with data obtained by pathologist visual scoring. To evaluate computer-aided image classification, IHC staining within pathologist annotated and software-classified areas of carcinoma were compared for each case. Two metrics for IHC staining were used: the percentage of carcinoma with S100A1 staining (%Pos), and the product of the staining intensity (optical density [OD] of staining) multiplied by the percentage of carcinoma with S100A1 staining (OD*%Pos). A comparison of the IHC staining data obtained from manual annotations and software-derived annotations showed strong agreement, indicating that software efficiently classifies carcinomatous areas within IHC slide images. Comparisons of IHC intensity data derived using pixel analysis software versus pathologist visual scoring demonstrated high Spearman correlations of 0.88 for %Pos (p < 0.0001) and 0.90 for OD*%Pos (p < 0.0001). This study demonstrated that computer-aided methods to classify image areas of interest (e.g., carcinomatous areas of tissue specimens) and quantify IHC staining intensity within those areas can produce highly similar data to visual evaluation by a pathologist.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1649068103671302

State-of-the-art FISHing: automated analysis of cytogenetic aberrations in interphase nuclei

Interphase fluorescence in situ hybridization (i-FISH) is a powerful tool for visualizing various molecular targets in non-dividing cells. Manual scoring of i-FISH signals is a labor intensive, time-consuming, and error-prone process liable to subjective interpretation. Automated evaluation of signal patterns provides the opportunity to overcome these difficulties. The first report on automated i-FISH analysis has been published 20 years ago and since then several applications have been introduced in the fields of oncology, and prenatal and fertility screening. In this article, we provide an insight into the automated i-FISH analysis including its course, brief history, clinical applications, and advantages and challenges. The lack of guidelines for describing new automated i-FISH methods hampers the precise comparison of performance of various applications published, thus, we make a proposal for a panel of parameters essential to introduce and standardize new applications and reproduce previously described technologies.

'Genetic heterogeneity' in HER2/neu testing by fluorescence in situ hybridization: a study of 2,522 cases

Amplification for the ERBB2 oncogene encoding the HER2/neu protein (HER2) is of predictive and prognostic importance in breast carcinoma. Fluorescence in situ hybridization (FISH) is a widely accepted method for determining HER2 amplification status. A HER2-amplified tumor is defined as having a ratio of HER2 signals to chromosome 17 centromeric probe signals (HER2/CEP17 ratio) exceeding 2.2. However, the presence of scattered cells demonstrating HER2 amplification is of unclear significance. A 2009 panel guideline defined a tumor with 'genetic heterogeneity' as having at least 5% but fewer than 50% of (non-clustered) tumor nuclei with a ratio >2.2. The study objective was to examine the statistical distribution of breast tumors tested by FISH for HER2 amplification, after implementation of this 2009 guideline. We identified 2522 consecutive breast carcinoma cases (2009-2011) tested for HER2 amplification. All cases were tested by FISH using a standard clinical protocol, adhering to established guidelines. For each case, data on cell counts were retrieved electronically. Each tumor was compared with a theoretical normal distribution by quantile-quantile analysis. Of 2522 FISH tests for HER2, 1900 (75%) were non-amplified, 394 (16%) were amplified, and 228 (9%) were HER2-equivocal. A total of 666 (26%) had 'genetic heterogeneity.' Among these 'genetically heterogeneous' cases, the ratio was non-amplified in 430 (64.5%), amplified in 24 (4%), and equivocal in 212 (31.5%). The amplified subpopulation in 'genetically heterogeneous' tumors was larger if the overall ratio was close to 2.2. However, the percentage of nuclei >2.2 in a 'genetically heterogeneous' tumor was not informative of the underlying tumor-cell distribution. We conclude that the proportion of HER2-amplified nuclei within a tumor does not contribute information independent of the actual HER2/CEP17 ratio. Reassessment of the definition of 'genetic heterogeneity' in HER2 testing is warranted.

Applications of 'TissueQuant'- a color intensity quantification tool for medical research

This paper demonstrates the use of TissueQuant - an image analysis tool for quantification of color intensities which was developed for use in medical research where the stained biological specimen such as tissue or antigen needs to be quantified. TissueQuant provides facilities for user interaction to choose and quantify the color of interest and its shades. Gaussian weighting functions are used to provide a color score which quantifies how close the shade is to the user specified reference color. We describe two studies in medical research which use TissueQuant for quantification. The first study evaluated the effect of petroleum-ether extract of Cissus quadrangularis (CQ) on osteoporotic rats. It was found that the analysis results correlated well with the manual evaluation, p < 0.001. The second study evaluated the nerve morphometry and it was found that the adipose and non adipose tissue content was maximum in radial nerve among the five nerves studied.

Utility of multispectral imaging in automated quantitative scoring of immunohistochemistry

BACKGROUND

Automated scanning devices and image analysis software provide a means to overcome the limitations of manual semiquantitative scoring of immunohistochemistry. Common drawbacks to automated imaging systems include an inability to classify tissue type and an inability to segregate cytoplasmic and nuclear staining.

METHODS

Immunohistochemistry for the membranous marker α-catenin, the cytoplasmic marker stathmin and the nuclear marker Ki-67 was performed on tissue microarrays (TMA) of archival formalin-fixed paraffin-embedded tissue comprising 471 (α-catenin and stathmin) and 511 (Ki-67) cases of prostate adenocarcinoma. These TMA were quantitatively analysed using two commercially available automated image analysers, the Ariol SL-50 system and the Nuance system from CRi. Both systems use brightfield microscopy for automated, unbiased and standardised quantification of immunohistochemistry, while the Nuance system has spectral deconvolution capabilities.

RESULTS

Overall concordance between scores from both systems was excellent (r=0.90; 0.83-0.95). The software associated with the multispectral imager allowed accurate automated classification of tissue type into epithelial glandular structures and stroma, and a single-step segmentation of staining into cytoplasmic or nuclear compartments allowing independent evaluation of these areas. The Nuance system, however, was not able to distinguish reliably between tumour and non-tumour tissue. In addition, variance in the labour and time required for analysis between the two systems was also noted.

CONCLUSION

Despite limitations, this study suggests some beneficial role for the use of a multispectral imaging system in automated analysis of immunohistochemistry.