Membrane connectivity estimated by digital image analysis of HER2 immunohistochemistry is concordant with visual scoring and fluorescence in situ hybridization results: algorithm evaluation on breast cancer tissue microarrays

Machine Learning for Digital Scoring of PRMT6 in Immunohistochemical Labeled Lung Cancer

Lung cancer is the leading cause of cancer death in the U.S. Therefore, it is imperative to identify novel biomarkers for the early detection and progression of lung cancer. PRMT6 is associated with poor lung cancer prognosis. However, analyzing PRMT6 expression manually in large samples is time-consuming posing a significant limitation for processing this biomarker. To overcome this issue, we trained and validated an automated method for scoring PRMT6 in lung cancer tissues, which can then be used as the standard method in future larger cohorts to explore population-level associations between PRMT6 expression and sociodemographic/clinicopathologic characteristics. We evaluated the ability of a trained artificial intelligence (AI) algorithm to reproduce the PRMT6 immunoreactive scores obtained by pathologists. Our findings showed that tissue segmentation to cancer vs. non-cancer tissues was the most critical parameter, which required training and adjustment of the algorithm to prevent scoring non-cancer tissues or ignoring relevant cancer cells. The trained algorithm showed a high concordance with pathologists with a correlation coefficient of 0.88. The inter-rater agreement was significant, with an intraclass correlation of 0.95 and a scale reliability coefficient of 0.96. In conclusion, we successfully optimized a machine learning algorithm for scoring PRMT6 expression in lung cancer that matches the degree of accuracy of scoring by pathologists.

Applications of Artificial Intelligence in Breast Pathology

CONTEXT.—

Increasing implementation of whole slide imaging together with digital workflow and advances in computing capacity enable the use of artificial intelligence (AI) in pathology, including breast pathology. Breast pathologists often face a significant workload, with diagnosis complexity, tedious repetitive tasks, and semiquantitative evaluation of biomarkers. Recent advances in developing AI algorithms have provided promising approaches to meet the demand in breast pathology.

OBJECTIVE.—

To provide an updated review of AI in breast pathology. We examined the success and challenges of current and potential AI applications in diagnosing and grading breast carcinomas and other pathologic changes, detecting lymph node metastasis, quantifying breast cancer biomarkers, predicting prognosis and therapy response, and predicting potential molecular changes.

DATA SOURCES.—

We obtained data and information by searching and reviewing literature on AI in breast pathology from PubMed and based our own experience.

CONCLUSIONS.—

With the increasing application in breast pathology, AI not only assists in pathology diagnosis to improve accuracy and reduce pathologists' workload, but also provides new information in predicting prognosis and therapy response.

The Role of Artificial Intelligence in Accurate Interpretation of HER2 Immunohistochemical Scores 0 and 1+ in Breast Cancer

The new human epidermal growth factor receptor (HER)2-targeting antibody-drug conjugate offers the opportunity to treat patients with HER2-low breast cancer. Distinguishing HER2 immunohistochemical (IHC) scores of 0 and 1+ is not only critical but also challenging owing to HER2 heterogeneity and variability of observers. In this study, we aimed to increase the interpretation accuracy and consistency of HER2 IHC 0 and 1+ evaluation through assistance from an artificial intelligence (AI) algorithm. In addition, we examined the value of our AI algorithm in evaluating HER2 IHC scores in tumors with heterogeneity. AI-assisted interpretation consisted of AI algorithms and an augmenting reality module with a microscope. Fifteen pathologists (5 junior, 5 midlevel, and 5 senior) participated in this multi-institutional 2-round ring study that included 246 infiltrating duct carcinoma cases that were not otherwise specified. In round 1, pathologists analyzed 246 HER2 IHC slides by microscope without AI assistance. After a 2-week washout period, the pathologists read the same slides with AI algorithm assistance and rendered the definitive results by adjusting to the AI algorithm. The accuracy of interpretation accuracy with AI assistance (0.93 vs 0.80), thereby the evaluation precision of HER2 0 and the recall of HER2 1+. In addition, the AI algorithm improved the total consistency (intraclass correlation coefficient = 0.542-0.812), especially in HER2 1+ cases. In cases with heterogeneity, accuracy improved significantly (0.68 to 0.89) and to a similar level as in cases without heterogeneity (accuracy, 0.97). Both accuracy and consistency improved more for junior pathologists than those for the midlevel and senior pathologists. To the best of our knowledge, this is the first study to show that the accuracy and consistency of HER2 IHC 0 and 1+ evaluation and the accuracy of HER2 IHC evaluation in breast cancers with heterogeneity can be significantly improved using AI-assisted interpretation.

Digital image analysis and assisted reading of the HER2 score display reduced concordance: pitfalls in the categorisation of HER2-low breast cancer

AIMS

Digital image analysis (DIA) is used increasingly as an assisting tool to evaluate biomarkers, including human epidermal growth factor receptor 2 (HER2) in invasive breast cancer (BC). DIA can assist pathologists in HER2 evaluation by presenting quantitative information about the HER2 staining in APP assisted reading (AR). Concurrently, the HER2-low category (HER2-1+/2+ without HER2 gene amplification) has gained prominence due to newly developed antibody-drug conjugates. However, major inter- and intraobserver variability have been observed for the entity. The present quality assurance study investigated the concordance between DIA and AR in clinical use, especially concerning the HER2-low category.

METHODS AND RESULTS

HER2 immunohistochemistry (IHC) in 761 tumours from 727 patients was evaluated in tissue microarray (TMA) cores by DIA (Visiopharm HER2-CONNECT) and AR. Overall concordance between HER2-scores were 73% (n = 552, weighted-κ: 0.66), and 88% (n = 669, weighted-κ: 0.70), when combining HER2-0/1+. A total of 205 scores were discordant by one category, while four were discordant by two categories. A heterogeneous HER2 pattern was relatively common in the discordant cases and a pitfall in the categorisation of HER2-low BC. AR more commonly reassigned a lower HER2 score (from HER2-1+ to HER2-0) within the HER2-low subgroup (n = 624) compared with DIA.

CONCLUSION

DIA and AR display moderate agreement with heterogeneous and aberrant staining, representing a source of discordance and a pitfall in the evaluation of HER2.

Update on prognostic and predictive biomarkers of breast cancer

Breast cancer represents a heterogeneous group of human cancer at both histological and molecular levels. Estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) are the most commonly used biomarkers in clinical practice for making treatment plans for breast cancer patients by oncologists. Recently, PD-L1 testing plays an important role for immunotherapy for triple-negative breast cancer. With the increased understanding of the molecular characterization of breast cancer and the emergence of novel targeted therapies, more potential biomarkers are needed for the development of more personalized treatments. In this review, we summarized several main prognostic and predictive biomarkers in breast cancer at genomic, transcriptomic and proteomic levels, including hormone receptors, HER2, Ki67, multiple gene expression assays, PD-L1 testing, mismatch repair deficiency/microsatellite instability, tumor mutational burden, PIK3CA, ESR1 andNTRK and briefly introduced the roles of digital imaging analysis in breast biomarker evaluation.

Quantitative Image Analysis as an Adjunct to Manual Scoring of ER, PgR, and HER2 in Invasive Breast Carcinoma

OBJECTIVES

Biomarker expression evaluation for estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor 2 (HER2) is an essential prognostic and predictive parameter for breast cancer and critical for guiding hormonal and neoadjuvant therapy. This study compared quantitative image analysis (QIA) with pathologists' scoring for ER, PgR, and HER2.

METHODS

A retrospective analysis was undertaken of 1,367 invasive breast carcinomas, including all histopathology subtypes, for which ER, PgR, and HER2 were analyzed by manual scoring and QIA. The resulting scores were compared, and in a subset of HER2 cases (n = 373, 26%), scores were correlated with available fluorescence in situ hybridization (FISH) results.

RESULTS

Concordance between QIA and manual scores for ER, PgR, and HER2 was 93%, 96%, and 90%, respectively. Discordant cases had low positive scores (1%-10%) for ER (n = 33), were due to nonrepresentative region selection (eg, ductal carcinoma in situ) or tumor heterogeneity for PgR (n = 43), and were of one-step difference (negative to equivocal, equivocal to positive, or vice versa) for HER2 (n = 90). Among HER2 cases where FISH results were available, only four (1.0%) showed discordant QIA and FISH results.

CONCLUSIONS

QIA is a computer-aided diagnostic support tool for pathologists. It significantly improves ER, PgR, and HER2 scoring standardization. QIA demonstrated excellent concordance with pathologists' scores. To avoid pitfalls, pathologist oversight of representative region selection is recommended.

Intratumoral Heterogeneity and Immune Response Indicators to Predict Overall Survival in a Retrospective Study of HER2-Borderline (IHC 2+) Breast Cancer Patients

Breast cancer (BC) categorized as human epidermal growth factor receptor 2 (HER2) borderline [2+ by immunohistochemistry (IHC 2+)] presents challenges for the testing, frequently obscured by intratumoral heterogeneity (ITH). This leads to difficulties in therapy decisions. We aimed to establish prognostic models of overall survival (OS) of these patients, which take into account spatial aspects of ITH and tumor microenvironment by using hexagonal tiling analytics of digital image analysis (DIA). In particular, we assessed the prognostic value of Immunogradient indicators at the tumor–stroma interface zone (IZ) as a feature of antitumor immune response. Surgical excision samples stained for estrogen receptor (ER), progesterone receptor (PR), Ki67, HER2, and CD8 from 275 patients with HER2 IHC 2+ invasive ductal BC were used in the study. DIA outputs were subsampled by HexT for ITH quantification and tumor microenvironment extraction for Immunogradient indicators. Multiple Cox regression revealed HER2 membrane completeness (HER2 MC) (HR: 0.18, p = 0.0007), its spatial entropy (HR: 0.37, p = 0.0341), and ER contrast (HR: 0.21, p = 0.0449) as independent predictors of better OS, with worse OS predicted by pT status (HR: 6.04, p = 0.0014) in the HER2 non-amplified patients. In the HER2-amplified patients, HER2 MC contrast (HR: 0.35, p = 0.0367) and CEP17 copy number (HR: 0.19, p = 0.0035) were independent predictors of better OS along with worse OS predicted by pN status (HR: 4.75, p = 0.0018). In the non-amplified tumors, three Immunogradient indicators provided the independent prognostic value: CD8 density in the tumor aspect of the IZ and CD8 center of mass were associated with better OS (HR: 0.23, p = 0.0079 and 0.14, p = 0.0014, respectively), and CD8 density variance along the tumor edge predicted worse OS (HR: 9.45, p = 0.0002). Combining these three computational indicators of the CD8 cell spatial distribution within the tumor microenvironment augmented prognostic stratification of the patients. In the HER2-amplified group, CD8 cell density in the tumor aspect of the IZ was the only independent immune response feature to predict better OS (HR: 0.22, p = 0.0047). In conclusion, we present novel prognostic models, based on computational ITH and Immunogradient indicators of the IHC biomarkers, in HER2 IHC 2+ BC patients.

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.

Using Delaunay triangulation to sample whole-specimen color from digital images

Color variation is one of the most obvious examples of variation in nature, but biologically meaningful quantification and interpretation of variation in color and complex patterns are challenging. Many current methods for assessing variation in color patterns classify color patterns using categorical measures and provide aggregate measures that ignore spatial pattern, or both, losing potentially important aspects of color pattern.Here, we present Colormesh, a novel method for analyzing complex color patterns that offers unique capabilities. Our approach is based on unsupervised color quantification combined with geometric morphometrics to identify regions of putative spatial homology across samples, from histology sections to whole organisms. Colormesh quantifies color at individual sampling points across the whole sample.We demonstrate the utility of Colormesh using digital images of Trinidadian guppies (Poecilia reticulata), for which the evolution of color has been frequently studied. Guppies have repeatedly evolved in response to ecological differences between up- and downstream locations in Trinidadian rivers, resulting in extensive parallel evolution of many phenotypes. Previous studies have, for example, compared the area and quantity of discrete color (e.g., area of orange, number of black spots) between these up- and downstream locations neglecting spatial placement of these areas. Using the Colormesh pipeline, we show that patterns of whole-animal color variation do not match expectations suggested by previous work.Colormesh can be deployed to address a much wider range of questions about color pattern variation than previous approaches. Colormesh is thus especially suited for analyses that seek to identify the biologically important aspects of color pattern when there are multiple competing hypotheses or even no a priori hypotheses at all.

Quantitative Image Analysis for Tissue Biomarker Use: A White Paper From the Digital Pathology Association

Tissue biomarkers have been of increasing utility for scientific research, diagnosing disease, and treatment response prediction. There has been a steady shift away from qualitative assessment toward providing more quantitative scores for these biomarkers. The application of quantitative image analysis has thus become an indispensable tool for in-depth tissue biomarker interrogation in these contexts. This white paper reviews current technologies being employed for quantitative image analysis, their application and pitfalls, regulatory framework demands, and guidelines established for promoting their safe adoption in clinical practice.

Digital scoring of EpCAM and slug expression as prognostic markers in head and neck squamous cell carcinomas

Head and neck squamous cell carcinomas (HNSCCs) have poor clinical outcome owing to therapy resistance and frequent recurrences that are among others attributable to tumor cells in partial epithelial‐to‐mesenchymal transition (pEMT). We compared side‐by‐side software‐based and visual quantification of immunohistochemistry (IHC) staining of epithelial marker EpCAM and EMT regulator Slug in n = 102 primary HNSCC to assess optimal analysis protocols. IHC scores incorporated expression levels and percentages of positive cells. Digital and visual evaluation of membrane‐associated EpCAM yielded correlating scorings, whereas visual evaluation of nuclear Slug resulted in significantly higher overall scores. Multivariable Cox proportional hazard analysis defined the median EpCAM expression levels resulting from visual quantification as an independent prognostic factor of overall survival. Slug expression levels resulting from digital quantification were an independent prognostic factor of recurrence‐free survival, locoregional recurrence‐free survival, and disease‐specific survival. Hence, we propose to use visual assessment for the membrane‐associated EpCAM protein, whereas nuclear protein Slug assessment was more accurate following digital measurement.

Accuracy of Digital Image Analysis (DIA) of Borderline Human Epidermal Growth Factor Receptor (HER2) Immunohistochemistry in Invasive Ductal Carcinoma

Background: Digital image analysis (DIA), used to extract information from pathology slides, provides better precision and no limitation regarding different interpretations by observers. Objectives: The present study aimed at evaluating the accuracy of DIA in the interpretation of borderline (2+) human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) slides of invasive ductal carcinoma of the breast. Methods: Sixty pathology samples with invasive ductal carcinoma of the breast were extracted based on HER2 (2+) and their fluorescence in situ hybridization (FISH), and chromogenic in situ hybridization (CISH) responses (as reference standard). The slides were digitized and, then, two pathologists examined the slides and documented diagnosis. DIA was performed by a free web application. Results: Totally, 307 digital images with 298 megabytes volume were extracted. The accuracy, sensitivity, and specificity values of DIA were 86 %, 46.1 %, and 97.8 %, respectively, with 8 false-negative cases. There was moderate agreement between the pathologist 1 (kappa = 0.42) and pathologist 2 (kappa = 0.41) with DIA. Conclusions: DIA had good accuracy and could be used for the interpretation of borderline HER2 IHC method in invasive ductal carcinoma.

Color standardization and optimization in whole slide imaging

Whole slide imaging (WSI) has various uses, including the development of decision support systems, image analysis, education, conferences, and remote diagnostics. It is also used to develop artificial intelligence using machine learning methods. In the clinical setting, however, many issues have hindered the implementation of WSI. These issues are becoming more important as WSI is gaining wider use in clinical practice, particularly with the implementation of artificial intelligence in pathological diagnosis. One of the most important issues is the standardization of color for WSI, which is an important component of digital pathology. In this paper, we review the major factors of color variation and how to evaluate and modify color variation to establish color standardization. There are five major reasons for color variation, which include specimen thickness, staining, scanner, viewer, and display. Recognizing that the color is not standardized is the first step towards standardization, and it is difficult to ascertain whether the appropriate color of the WSI is displayed at the reviewers' end.

A Validation Study of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry Digital Imaging Analysis and its Correlation with Human Epidermal Growth Factor Receptor 2 Fluorescence In situ Hybridization Results in Breast Carcinoma

Background:

The Visiopharm human epidermal growth factor receptor 2 (HER2) digital imaging analysis (DIA) algorithm assesses digitized HER2 immunohistochemistry (IHC) by measuring cell membrane connectivity. We aimed to validate this algorithm for clinical use by comparing with pathologists’ scoring and correlating with HER2 fluorescence in situ hybridization (FISH) results.

Materials and Methods:

The study cohort consisted of 612 consecutive invasive breast carcinoma specimens including 395 biopsies and 217 resections. HER2 IHC slides were scanned using Philips IntelliSite Scanners, and the digital images were analyzed using Visiopharm HER2-CONNECT App to obtain the connectivity values (0–1) and scores (0, 1+, 2+, and 3+). HER2 DIA scores were compared with Pathologists’ manual scores, and HER2 connectivity values were correlated with HER2 FISH results.

Results:

The concordance between HER2 DIA scores and pathologists’ scores was 87.3% (534/612). All discordant cases (n = 78) were only one-step discordant (negative to equivocal, equivocal to positive, or vice versa). Five cases (0.8%) showed discordant HER2 IHC DIA and HER2 FISH results, but all these cases had relatively low HER2 copy numbers (between 4 and 6). HER2 IHC connectivity showed significantly better correlation with HER2 copy number than HER2/CEP17 ratio.

Conclusions:

HER2 IHC DIA demonstrates excellent concordance with pathologists’ scores and accurately discriminates between HER2 FISH positive and negative cases. HER2 IHC connectivity has better correlation with HER2 copy number than HER2/CEP17 ratio, suggesting HER2 copy number may be more important in predicting HER2 protein expression, and response to anti-HER2-targeted therapy.

Quantitative digital imaging analysis of HER2 immunohistochemistry predicts the response to anti-HER2 neoadjuvant chemotherapy in HER2-positive breast carcinoma

PURPOSE

Patients with HER2-positive breast cancer commonly receive anti-HER2 neoadjuvant chemotherapy and pathologic complete response (pCR) can be achieved in up to half of the patients. HER2 protein expression detected by immunohistochemistry (IHC) can be quantified using digital imaging analysis (DIA) as a value of membranous connectivity. We aimed to investigate the association HER2 IHC DIA quantitative results with response to anti-HER2 neoadjuvant chemotherapy.

METHODS

Digitized HER2 IHC whole slide images were analyzed using Visiopharm HER2-CONNECT to obtain quantitative HER2 membranous connectivity from a cohort of 153 HER2+ invasive breast carcinoma cases treated with anti-HER2 neoadjuvant chemotherapy (NAC). HER2 connectivity and other factors including age, histologic grade, ER, PR, and HER2 fluorescence in situ hybridization (FISH) were analyzed for association with the response to anti-HER2 NAC.

RESULTS

Eighty-three cases (54.2%) had pCR, while 70 (45.8%) showed residual tumor. Younger age, negative ER/PR, higher HER2 DIA connectivity, higher HER2 FISH ratio and copy number were significantly associated with pCR in univariate analysis. Multivariate analysis demonstrated only age, HER2 DIA connectivity, PR negativity, and HER2 copy number was significantly associated with pCR, whereas HER2 DIA connectivity had the strongest association.

CONCLUSIONS

HER2 IHC DIA connectivity is the most important factor predicting pCR to anti-HER2 neoadjuvant chemotherapy in patients with HER2-positive breast cancer.

Digital Microscopy, Image Analysis, and Virtual Slide Repository

Advancements in technology and digitization have ushered in novel ways of enhancing tissue-based research via digital microscopy and image analysis. Whole slide imaging scanners enable digitization of histology slides to be stored in virtual slide repositories and to be viewed via computers instead of microscopes. Easier and faster sharing of histologic images for teaching and consultation, improved storage and preservation of quality of stained slides, and annotation of features of interest in the digital slides are just a few of the advantages of this technology. Combined with the development of software for digital image analysis, digital slides further pave the way for the development of tools that extract quantitative data from tissue-based studies. This review introduces digital microscopy and pathology, and addresses technical and scientific considerations in slide scanning, quantitative image analysis, and slide repositories. It also highlights the current state of the technology and factors that need to be taken into account to insure optimal utility, including preanalytical considerations and the importance of involving a pathologist in all major steps along the digital microscopy and pathology workflow.

What is the added value of digital image analysis of HER2 immunohistochemistry in breast cancer in clinical practice? A study with multiple platforms

AIMS

We aimed to compare digital image analysis (DIA) of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) in breast cancer by two platforms: (i) to validate DIA against standard diagnostics; and (ii) to evaluate the added value of DIA in clinical practice.

METHODS AND RESULTS

HER2 IHC and in-situ hybridisation (ISH) were performed on 152 consecutive invasive breast carcinomas. IHC scores were determined with DIA using two independent platforms. Manual scoring was performed by two independent observers. HER2 status was considered positive in 3+ and ISH-positive 2+ cases. HER2 status using DIA was compared to HER2 status with standard diagnostics (manual scoring with ISH in 2+ cases). Interplatform agreement of IHC scores was 'moderate' (linear weighted κ = 0.58), agreement between manual scoring and platform A was 'moderate' (κ = 0.60) and between manual scoring and platform B 'almost perfect' (κ = 0.85). Compared to manual scoring, DIA resulted in a reduction of 2+ cases from 17.1 to 1.3% with platform A and from 17.1 to 15.8% with platform B. However, compared to standard diagnostics, there were three false-negative cases with DIA using platform A [81.3% sensitivity, 100% specificity, 100% positive predictive value (PPV), 97.8% negative predictive value (NPV)]. Sensitivity, specificity, PPV and NPV were 100% with DIA using platform B.

CONCLUSIONS

DIA of HER2 IHC is a valid tool in determining HER2 status in breast carcinoma. Algorithms in different platforms can behave differently, and optimal calibration is essential. In clinical practice, DIA offers an objective alternative to manual scoring, but a reduction in 2+ cases could result in loss of sensitivity.

Clinicopathologic and prognostic significance of VEGF, JAK2 and STAT3 in patients with nasopharyngeal carcinoma

Background

The aim of the study was to investigate the effect associated with the protein expression of VEGF, JAK2 and STAT3 on the clinicopathologic characteristics and prognosis in the development and progression of nasopharyngeal carcinoma (NPC).

Methods

Fifty NPC patients in addition to 20 patients with chronic nasopharyngitis (CNP) were recruited for the purposes of the study. Western blotting and immunohistochemistry methods were employed to evaluate the protein expressions of JAK2, STAT3 and VEGF in the NPC and CNP tissues, with their respective correlations with the clinicopathologic characteristics of NPC patients subsequently analyzed. Spearman’s rank correlation coefficient and Kaplan–Meier method were conducted to evaluate the respective correlations of JAK2, STAT3 and VEGF with NPC as well as the survival rates of patients with NPC. Cox regression analyses was performed in determine the prognostic NPC factors.

Results

Compared with the CNP tissues, the NPC tissues exhibited elevated levels of JAK2, STAT3 and VEGF which were subsequently determined to share a positive correlation with T stages, lymph node metastasis (LNM), N stages and clinical stages, while a negative correlation with survival rates were observed in the NPC patients. Positive correlations between the expressions of JAK2, STAT3 and VEGF were detected among the NPC tissues. NPC patients survival time with negative expressions of JAK2, STAT3 and VEGF were observed to be longer than that of NPC patients with positive expressions of JAK2, STAT3 and VEGF. T stage, LNM, N stage, clinical stage. The expressions of JAK2, STAT3 and VEGF were discovered to be independent risk factors associated with the prognosis of patients with NPC.

Conclusion

The results obtained from the present study support the notion that higher expressions of JAK2, STAT3 and VEGF may be correlated with the clinicopathologic characteristics and prognosis of patients suffering from NPC.

Physical basis of the 'magnification rule' for standardized Immunohistochemical scoring of HER2 in breast and gastric cancer

Background

Detection of HER2/neu receptor overexpression and/or amplification is a prerequisite for efficient anti-HER2 treatment of breast and gastric carcinomas. Immunohistochemistry (IHC) of the HER2 protein is the most common screening test, thus precise and reproducible IHC-scoring is of utmost importance. Interobserver variance still is a problem; in particular in gastric carcinomas the reliable differentiation of IHC scores 2+ and 1+ is challenging.

Herein we describe the physical basis of what we called the ‘magnification rule’: Different microscope objectives are employed to reproducibly subdivide the continuous spectrum of IHC staining intensities into distinct categories (1+, 2+, 3+).

Methods

HER2-IHC was performed on 120 breast cancer biopsy specimens (n = 40 per category). Width and color-intensity of membranous DAB chromogen precipitates were measured by whole-slide scanning and digital morphometry. Image-analysis data were related to semi-quantitative manual scoring according to the magnification rule and to the optical properties of the employed microscope objectives.

Results

The semi-quantitative manual HER2-IHC scores are correlated to color-intensity measured by image-analysis and to the width of DAB-precipitates. The mean widths ±standard deviations of precipitates were: IHC-score 1+, 0.64 ± 0.1 μm; score 2+, 1.0 ± 0.23 μm; score 3+, 2.14 ± 0.4 μm. The width of precipitates per category matched the optical resolution of the employed microscope objective lenses: Approximately 0.4 μm (40×), 1.0 μm (10×) and 2.0 μm (5×).

Conclusions

Perceived intensity, width of the DAB chromogen precipitate, and absolute color-intensity determined by image-analysis are linked. These interrelations form the physical basis of the ‘magnification rule’: 2+ precipitates are too narrow to be observed with 5× microscope objectives, 1+ precipitates are too narrow for 10× objectives. Thus, the rule uses the optical resolution windows of standard diagnostic microscope objectives to derive the width of the DAB-precipitates. The width is in turn correlated with color-intensity. Hereby, the more or less subjective estimation of IHC scores based only on the staining-intensity is replaced by a quasi-morphometric measurement. The principle seems universally applicable to immunohistochemical stainings of membrane-bound biomarkers that require an intensity-dependent scoring.

Electronic supplementary material

The online version of this article (10.1186/s13000-018-0696-x) contains supplementary material, which is available to authorized users.

Digital image analysis of HER2 immunohistochemistry in gastric- and oesophageal adenocarcinoma: a validation study on biopsies and surgical specimens

AIMS

To test the validity of diagnostics incorporating digital image analysis (DIA) for human epidermal growth factor 2 (HER2) immunohistochemistry (IHC) in gastro-oesophageal adenocarcinomas, as an alternative to current standard diagnostics using manual scoring.

METHODS AND RESULTS

We included 319 consecutive gastro-oesophageal adenocarcinomas (232 biopsies and 87 surgical specimens). DIA was applied to determine HER2 IHC classification, using both standard breast cancer (BC) and modified gastro-oesophageal cancer (GEC) cut-offs. Consensus manual scores were established by four independent observers. Chromogenic in-situ hybridization (CISH) was performed on all 2+ cases by manual scoring, DIA or both. HER2 status was considered positive in 3+ and CISH-positive 2+ cases. Overall agreement between DIA and consensus manual scores was 76.5% (weighted κ = 0.66, BC cut-offs) and 85.6% (weighted κ = 0.80, GEC cut-offs). Agreement was similar for biopsies and surgical specimens. All disagreement occurred in the manual IHC equivocal cases. DIA resulted in a reduction of 2+ cases: 75.8% with BC cut-offs and 46.5% with GEC cut-offs. HER2 status was positive in 48 cases (15%) with standard diagnostics and DIA using GEC cut-offs, and 46 cases (14.4%) using BC cut-offs (all with CISH in 2+ cases). Considering standard diagnostics as a reference, DIA showed 93.8% sensitivity and 99.6% specificity (BC cut-offs) or 97.9% sensitivity and 99.6% specificity (GEC cut-offs).

CONCLUSIONS

DIA is a reliable and feasible alternative to manual HER2 IHC scoring in gastro-oesophageal adenocarcinoma, both in biopsies and surgical specimens, leading to a reduction of 2+ cases for which subsequent ISH testing is required.

Impact of Altering Various Image Parameters on Human Epidermal Growth Factor Receptor 2 Image Analysis Data Quality

Introduction:

The quality of data obtained from image analysis can be directly affected by several preanalytical (e.g., staining, image acquisition), analytical (e.g., algorithm, region of interest [ROI]), and postanalytical (e.g., computer processing) variables. Whole-slide scanners generate digital images that may vary depending on the type of scanner and device settings. Our goal was to evaluate the impact of altering brightness, contrast, compression, and blurring on image analysis data quality.

Methods:

Slides from 55 patients with invasive breast carcinoma were digitized to include a spectrum of human epidermal growth factor receptor 2 (HER2) scores analyzed with Visiopharm (30 cases with score 0, 10 with 1+, 5 with 2+, and 10 with 3+). For all images, an ROI was selected and four parameters (brightness, contrast, JPEG2000 compression, out-of-focus blurring) then serially adjusted. HER2 scores were obtained for each altered image.

Results:

HER2 scores decreased with increased illumination, higher compression ratios, and increased blurring. HER2 scores increased with greater contrast. Cases with HER2 score 0 were least affected by image adjustments.

Conclusion:

This experiment shows that variations in image brightness, contrast, compression, and blurring can have major influences on image analysis results. Such changes can result in under- or over-scoring with image algorithms. Standardization of image analysis is recommended to minimize the undesirable impact such variations may have on data output.

Colour in digital pathology: a review

Colour is central to the practice of pathology because of the use of coloured histochemical and immunohistochemical stains to visualize tissue features. Our reliance upon histochemical stains and light microscopy has evolved alongside a wide variation in slide colour, with little investigation into the implications of colour variation. However, the introduction of the digital microscope and whole-slide imaging has highlighted the need for further understanding and control of colour. This is because the digitization process itself introduces further colour variation which may affect diagnosis, and image analysis algorithms often use colour or intensity measures to detect or measure tissue features. The US Food and Drug Administration have released recent guidance stating the need to develop a method of controlling colour reproduction throughout the digitization process in whole-slide imaging for primary diagnostic use. This comprehensive review introduces applied basic colour physics and colour interpretation by the human visual system, before discussing the importance of colour in pathology. The process of colour calibration and its application to pathology are also included, as well as a summary of the current guidelines and recommendations regarding colour in digital pathology.

Expression and prognostic impact of matrix metalloproteinase-2 (MMP-2) in astrocytomas

Astrocytomas are the most frequent primary brain tumors in adults, and despite aggressive treatment patients often experience recurrence. Survival decreases with increasing tumor grade, and especially patients with grade IV glioblastoma have poor prognosis due to the aggressive character of this tumor. Matrix metalloproteinase-2 (MMP-2) is an extracellular matrix degrading enzyme which has been shown to play important roles in different cancers. The aim of this study was to investigate the expression and prognostic potential of MMP-2 in astrocytomas. Tissue samples from 89 patients diagnosed with diffuse astrocytoma, anaplastic astrocytoma and glioblastoma were stained immunohistochemically using a monoclonal MMP-2 antibody. The MMP-2 intensity in cytoplasm/membrane was quantified by a trained software-based classifier using systematic random sampling in 10% of the tumor area. We found MMP-2 expression in tumor cells and blood vessels. Measurements of MMP-2 intensity increased with tumor grade, and MMP-2 expression was found to be significantly higher in glioblastomas compared to normal brain tissue (p<0.001), diffuse astrocytomas (p<0.001) and anaplastic astrocytomas (p<0.05). MMP-2 expression was associated with shorter overall survival in patients with grade II-IV astrocytic tumors (HR 1.60; 95% CI 1.03–2.48; p = 0.036). In glioblastoma, high MMP-2 was associated with poorer prognosis in patients who survived longer than 8.5 months independent of age and gender (HR 2.27; 95% CI 1.07–4.81; p = 0.033). We found a positive correlation between MMP-2 and tissue inhibitor of metalloproteinases-1 (TIMP-1), and combined MMP-2 and TIMP-1 had stronger prognostic value than MMP-2 alone also when adjusting for age and gender (HR 2.78; 95% CI 1.30–5.92; p = 0.008). These findings were validated in bioinformatics databases. In conclusion, this study indicates that MMP-2 is associated with aggressiveness in astrocytomas and may hold an unfavorable prognostic value in patients with glioblastoma.

A novel quantitative immunohistochemistry method for precise protein measurements directly in formalin-fixed, paraffin-embedded specimens: analytical performance measuring HER2

In clinical routine pathology today, detection of protein in intact formalin-fixed, paraffin-embedded tissue is limited to immunohistochemistry, which is semi-quantitative. This study presents a new and reliable quantitative immunohistochemistry method, qIHC, based on a novel amplification system that enables quantification of protein directly in formalin-fixed, paraffin-embedded tissue by counting of dots. The qIHC technology can be combined with standard immunohistochemistry, and assessed using standard bright-field microscopy or image analysis. The objective was to study analytical performance of the qIHC method. qIHC was tested under requirements for an analytical quantitative test, and compared with ELISA and flow cytometry for quantitative protein measurements. Human epidermal growth factor receptor 2 (HER2) protein expression was measured in five different cell lines with HER2 expression from undetectable with immunohistochemistry to strong positive staining (IHC 3+). Repeatability, reproducibility, robustness, linearity, dynamic range, sensitivity, and quantification limits were evaluated. Reproducibility and robustness were assessed in a setup to resemble daily work in a laboratory using a commercial immunohistochemistry platform. In addition, qIHC was correlated to standard HER2 immunohistochemistry in 44 breast cancer specimens. For all evaluated parameters, qIHC performance was either comparable or better than the reference methods. Furthermore, qIHC has a lower limit of detection than both immunohistochemistry and the ELISA reference method, and demonstrated ability to measure HER2 accurately and precise within a large dynamic range. In conclusion, the results show that qIHC provides a sensitive, quantitative, accurate, and robust assay for measurement of protein expression in formalin-fixed, paraffin-embedded cell lines, and tissue.

HER2 aberrations and heterogeneity in cancers of the digestive system: Implications for pathologists and gastroenterologists

Management of cancers of the digestive system has progressed rapidly into the molecular era. Despite the significant recent achievements in the diagnosis and treatment of these patients, the number of deaths for these tumors has currently plateaued. Many investigations have assessed the role of HER2 in tumors of the digestive system in both prognostic and therapeutic settings, with heterogeneous results. Novel testing and treatment guidelines are emerging, in particular in gastric and colorectal cancers. However, further advances are needed. In this review we provide a comprehensive overview of the current state-of-knowledge of HER2 alterations in the most common tumors of the digestive system and discuss the operational implications of HER2 testing.

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.

Digital image analysis outperforms manual biomarker assessment in breast cancer

In the spectrum of breast cancers, categorization according to the four gene expression-based subtypes 'Luminal A,' 'Luminal B,' 'HER2-enriched,' and 'Basal-like' is the method of choice for prognostic and predictive value. As gene expression assays are not yet universally available, routine immunohistochemical stains act as surrogate markers for these subtypes. Thus, congruence of surrogate markers and gene expression tests is of utmost importance. In this study, 3 cohorts of primary breast cancer specimens (total n=436) with up to 28 years of survival data were scored for Ki67, ER, PR, and HER2 status manually and by digital image analysis (DIA). The results were then compared for sensitivity and specificity for the Luminal B subtype, concordance to PAM50 assays in subtype classification and prognostic power. The DIA system used was the Visiopharm Integrator System. DIA outperformed manual scoring in terms of sensitivity and specificity for the Luminal B subtype, widely considered the most challenging distinction in surrogate subclassification, and produced slightly better concordance and Cohen's κ agreement with PAM50 gene expression assays. Manual biomarker scores and DIA essentially matched each other for Cox regression hazard ratios for all-cause mortality. When the Nottingham combined histologic grade (Elston-Ellis) was used as a prognostic surrogate, stronger Spearman's rank-order correlations were produced by DIA. Prognostic value of Ki67 scores in terms of likelihood ratio χ(2) (LR χ(2)) was higher for DIA that also added significantly more prognostic information to the manual scores (LR-Δχ(2)). In conclusion, the system for DIA evaluated here was in most aspects a superior alternative to manual biomarker scoring. It also has the potential to reduce time consumption for pathologists, as many of the steps in the workflow are either automatic or feasible to manage without pathological expertise.

Analysis of new bone, cartilage, and fibrosis tissue in healing murine allografts using whole slide imaging and a new automated histomorphometric algorithm

Histomorphometric analysis of histologic sections of normal and diseased bone samples, such as healing allografts and fractures, is widely used in bone research. However, the utility of traditional semi-automated methods is limited because they are labor-intensive and can have high interobserver variability depending upon the parameters being assessed, and primary data cannot be re-analyzed automatically. Automated histomorphometry has long been recognized as a solution for these issues, and recently has become more feasible with the development of digital whole slide imaging and computerized image analysis systems that can interact with digital slides. Here, we describe the development and validation of an automated application (algorithm) using Visiopharm’s image analysis system to quantify newly formed bone, cartilage, and fibrous tissue in healing murine femoral allografts in high-quality digital images of H&E/alcian blue-stained decalcified histologic sections. To validate this algorithm, we compared the results obtained independently using OsteoMeasure^TM and Visiopharm image analysis systems. The intraclass correlation coefficient between Visiopharm and OsteoMeasure was very close to one for all tissue elements tested, indicating nearly perfect reproducibility across methods. This new algorithm represents an accurate and labor-efficient method to quantify bone, cartilage, and fibrous tissue in healing mouse allografts.

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.

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.

High agreement between whole slide imaging and optical microscopy for assessment of HER2 expression in breast cancer: whole slide imaging for the assessment of HER2 expression

Whole slide imaging (WSI) technology has been used for training, teaching, researching, and remote consultation. Few studies compared HER2 expression using optical microscopy (OM) and WSI evaluations in breast carcinomas. However, no consensus has been achieved comparing both assessments.

MATERIAL AND METHODS

Sections from tissue microarray containing 200 preselected invasive breast carcinomas were submitted to immunohistochemistry applying three anti-HER2 antibodies (HercepTest™, CB11, SP3) and in situ hybridization (DDISH). Slides were evaluated using OM and WSI (Pannoramic MIDI and Viewer, 3DHISTECH). Sensitivity and specificity were calculated comparing the anti-HER2 antibodies and DDISH.

RESULTS

WSI and OM HER2 evaluations agreement was considered good (SP3, k=0.80) to very good (CB11 and HercepTest™, k=0.81). WSI evaluation led to higher sensitivity (ranging from 100 of SP3 and HercepTest™ to 97 of CB11) and lower specificity (ranging from 86.4 of SP3 to 89.4 of HercepTest™) compared to OM evaluation (sensitivity ranged from 92.1 of CB11 to 98 of SP3 and specificity ranged from 95.2 of SP3 and HercepTest™ to 97.1 of CB11 and SP3).

CONCLUSION

High agreement was achieved between WSI and OM evaluations. All three antibodies were highly sensitive and specific using both evaluations. WSI can be considered a useful tool for HER2 immunohistochemical assessment.

Identification by digital immunohistochemistry of intratumoral changes of immune infiltrates after vaccine in the absence of modifications of PBMC immune cell subsets

Preclinical studies have demonstrated that the combination of systemic subcutaneous (s.c.) vaccination with intratumoral (i.t.) vaccination was superior in the induction of antitumor activity vs. vaccination with either route alone. A subsequent phase I study employing i.t.-s.c. vaccination was carried out in men with locally recurrent or progressive prostate cancer. rF-PSA-TRICOM (PROSTVAC) vaccine was administered intraprostatically and rV-PSA-TRICOM followed by rF-PSA-TRICOM vaccine was administered systemically. In that study no dose limiting toxicities were observed, 19/21 patients had stable or improved prostate-specific antigen (PSA) values and tumor-infiltrating lymphocytes (TILs) increased in post- vs. pre-treatment tumor biopsies, analyzed employing conventional immunohistochemistry (IHC). In the studies reported here, 31 phenotypes of peripheral blood mononuclear cells (PBMCs) were analyzed prevaccination and postvaccination as well as the functions of PBMC regulatory T cells (Tregs) and natural killer cells. A trend was observed in decreases in serum PSA with the reduction of circulating Tregs postvaccination. Digital IHC was employed prevaccination and postvaccination to measure CD4 and CD8 TILs, as well as Treg TILs by conventional IHC. Few correlations were observed with CD4, CD8 or Treg in TILs vs. PBMCs. However, patients with lower levels of CD4 TILs prevaccination showed the greatest increases in CD4 TILs postvaccine, while Treg TILs decreased postvaccine. There was also a strong correlation between decreases in serum PSA and increases in CD8 TILs postvaccine. These studies provide additional rationale for the use of i.t.-s.c. vaccinations and demonstrate a noncoordinate expression of specific immune subsets in PBMCs vs. tumor.

Effects of pretreatment on the denaturation and fragmentation of genomic DNA for DNA hybridization

DNA hybridization is an important step for a number of bioassays such as fluorescence in situ hybridization, microarrays, as well as the NanoGene assay. Denaturation and fragmentation of genomic DNA are two critical pretreatments for DNA hybridization. However, no thorough and systematic characterization on denaturation and fragmentation has been carried out for the NanoGene assay so far. In this study, we investigated the denaturation and fragmentation of the bacterial gDNA with physical treatments (i.e., heating and sonication) and chemical treatments (i.e., dimethyl sulfoxide). First of all, a simple approach for indicating the denaturation fraction was developed based on the absorbance difference (i.e., hyperchromic effect) between the double-stranded DNA and single-stranded DNA fragments. Then the denaturation capabilities of the treatments to the gDNA were elucidated, followed by the examination of the possible renaturation over time. The fragmentation of the gDNA by each treatment was also investigated. Based on denaturation efficiency, minimum renaturation tendency, and fragmentation, the sonication method was found to be the best among the six methods. We further demonstrated that the sonication method produced the best result among the treatments examined for the DNA hybridization in the NanoGene assay.

Differing deregulation of HER2 in primary gastric cancer and synchronous related metastatic lymph nodes

BACKGROUND

The aim of this study was to investigate how differences in expression of HER2 between primary gastric cancers (PGCs) and their corresponding metastatic lymph nodes (LMNs) might affect its potential as a prognostic indicator in treatments including anti-HER2 agents.

METHODS

The analysis was conducted in 102 patients who underwent surgical resection for primary gastric cancers (PGCs; adenocarcinoma, intestinal type) with synchronous LNMs. HER2 gene status and protein expression were investigated by immunohistochemistry (IHC) in all patients; fluorescence in situ hybridization (FISH) was performed in 22 patients. The correlation between HER2 gene status in PGCs and their LNMs was evaluated.

RESULTS

Positive HER2 expression as detected by IHC + FISH was observed in 27/102 PGC samples (26.5%) and 29/102 LNM samples (28.4%). HER2 amplification status in 102 paired PGC and LNM samples as evaluated by FISH + IHC was concordant in 92 patients (90.2%), 69 (67.6%) were unamplified and 23/102 (22.5%) were amplified at both sites, and discordant in 10 patients (9.8%), 4 (3.9%) were positive for PGC and negative for LNM, while 6 (5.9%) were positive for LNM and negative for PGC. The results of FISH + IHC showed very strong concordance in HER2 status between the PGC and LNM groups (k = 0.754).

CONCLUSION

The high concordance between HER2 results for PGCs and their LNMs indicates that assessment of HER2 status in the primary cancer alone is a reliable basis for deciding treatment with anti-HER2 agents in patients with LNMs from gastric adenocarcinoma.

VIRTUAL SLIDES

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/9365749431029643.

Podocalyxin-like protein expression in primary colorectal cancer and synchronous lymph node metastases

Aims

Previous studies have shown that membranous expression of podocalyxin-like protein (PODXL) is associated with poor prognosis in colorectal cancer (CRC). In this study, we compared PODXL expression in primary CRC and synchronous lymph node metastases. We further analyzed whether its expression changed in rectal tumours after neoadjuvant radiation therapy.

Methods and results

The studied cohort consists of 73 consecutive patients from the South-Swedish Colorectal Cancer Biobank. Immunohistochemical PODXL expression was examined on full-face sections from all primary tumours and all 140 available lymph node metastases from 31 cases. Membranous PODXL expression was denoted in 18/73 (24,7%) primary tumours, with a high concordance between primary and metastatic lesions. While all negative primary tumours had negative metastases, some PODXL positive primaries had a varying proportion of positive and negative metastatic lymph nodes. PODXL expression was also found to be mainly unaltered in pre- and post-irradiation surgically resected tumour specimens in rectal cancer patients (n=16).

Conclusions

The findings in this study suggest that analysis of PODXL expression in the primary tumour is sufficient for its use as a prognostic and treatment predictive biomarker in CRC, also in patients with metastatic disease.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/9014177329634352

A comparison between manual and automated evaluations of tissue microarray patterns of protein expression

Tissue microarray technology enables us to evaluate the pattern of protein expression in large numbers of samples. However, manual data acquisition and analysis still represent a challenge because they are subjective and time-consuming. Automated analysis may thus increase the speed and reproducibility of evaluation. However, the reliability of automated analysis systems should be independently evaluated. Herein, the expression of phosphorylated AKT and mTOR was determined by ScanScope XT (Aperio; Vista, CA) and ACIS III (Dako; Glostrup, Denmark) and compared with the manual analysis by two observers. The percentage of labeled pixels or nuclei analysis had a good correlation between human observers and automated systems (κ = 0.855 and 0.879 for ScanScope vs. observers and κ = 0.765 and 0.793 for ACIS III vs. observers). The intensity of labeling determined by ScanScope was also correlated with that found by the human observers (correlation index of 0.946 and 0.851 for pAKT and 0.851 and 0.875 for pmTOR). However, the correlation between ACIS III and human observation varied for labeling intensity and was considered poor in some cases (correlation index of 0.718 and 0.680 for pAKT and 0.223 and 0.225 for pmTOR). Thus, the percentage of positive pixels or nuclei determination was satisfactorily performed by both systems; however, labeling intensity was better identified by ScanScope XT.

Immunohistochemical analysis of medullary breast carcinoma autoantigens in different histological types of breast carcinomas

BACKGROUND

On the past decade a plethora of investigations were directed on identification of molecules involved in breast tumorogenesis, which could represent a powerful tool for monitoring, diagnostics and treatment of this disease. In current study we analyzed six previously identified medullary breast carcinoma autoantigens including LGALS3BP, RAD50, FAM50A, RBPJ, PABPC4, LRRFIP1 with cancer restricted serological profile in different histological types of breast cancer.

METHODS

Semi-quantitative immunohistochemical analysis of 20 tissue samples including medullary breast carcinoma, invasive ductal carcinoma, invasive lobular carcinoma and non-cancerous tissues obtained from patients with fibrocystic disease (each of five) was performed using specifically generated polyclonal antibodies. Differences in expression patterns were evaluated considering percent of positively stained cells, insensitivity of staining and subcellular localization in cells of all tissue samples.

RESULTS

All 6 antigens predominantly expressed in the most cells of all histological types of breast tumors and non-cancerous tissues with slight differences in intensity of staining and subcellular localization. The most significant differences in expression pattern were revealed for RAD50 and LGALS3BP in different histological types of breast cancer and for PABPC4 and FAM50A antigens in immune cells infiltrating breast tumors.

CONCLUSIONS

This pilot study made possible to select 4 antigens LGALS3BP, RAD50, PABPC4, and FAM50A as promising candidates for more comprehensive research as potential molecular markers for breast cancer diagnostics and therapy.

VIRTUAL SLIDES

The virtual slides' for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1860649350796892.

Immunohistochemical characterization of neoplastic cells of breast origin

Background

After skin cancer, breast cancer is the most common malignancy in women. Tumors of unknown origin account for 5-15% of malignant neoplasms, with 1.5% being breast cancer. An immunohistochemical panel with conventional and newer markers, such as mammaglobin, was selected for the detection of neoplastic cells of breast origin. The specific objectives are: 1) to determine the sensitivity and specificity of the panel, with a special emphasis on the inclusion of the mammaglobin marker, and 2) to compare immunohistochemistry performed on whole tissue sections and on Tissue Micro-Array.

Methods

Twenty-nine metastatic breast tumors were included and assumed as tumors of unknown origin. Other 48 biopsies of diverse tissues were selected and assumed as negative controls. Tissue Micro-Array was performed. Immunohistochemistry for mammaglobin, gross cystic disease fluid protein-15, estrogen receptor, progesterone receptor and cytokeratin 7 was done.

Results

Mammaglobin positive staining was observed in 10/29 cases, in 13/29 cases for gross cystic disease fluid protein-15, in 20/29 cases for estrogen receptor, in 9/29 cases for progesterone receptor, and in 25/29 cases for cytokeratin 7. Among the negative controls, mammaglobin was positive in 2/48, and gross cystic disease fluid protein-15 in 4/48.

Conclusions

The inclusion of MAG antibody in the immunohistochemical panel for the detection of tumors of unknown origin contributed to the detection of metastasis of breast cancer. The diagnostic strategy with the highest positive predictive value (88%) included hormone receptors and mammaglobin in serial manner.

Virtual slides

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1366310812718988

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

Introduction of virtual microscopy in routine surgical pathology--a hypothesis and personal view from Europe

The technology of whole image acquisition from histological glass slides (Virtual slides, (VS)) and its associated software such as image storage, viewers, and virtual microscopy (VM), has matured in the recent years. There is an ongoing discussion whether to introduce VM into routine diagnostic surgical pathology (tissue-based diagnosis) or not, and if these are to be introduced how best to do this. The discussion also centres around how to substantially define the mandatory standards and working conditions related to introducing VM. This article briefly describes some hypotheses alongside our perspective and that of several of our European colleagues who have experienced VS and VM either in research or routine praxis. After consideration of the different opinions and published data the following statements can be derived: 1. Experiences from static and remote telepathology as well as from daily routine diagnoses, confirm that VM is a diagnostic tool that can be handled with the same diagnostic accuracy as conventional microscopy; at least no statistically significant differences (p > 0.05) exist. 2. VM possesses several practical advantages in comparison to conventional microscopy; such as digital image storage and retrieval and contemporary display of multiple images (acquired from different stains, and/or different cases). 3. VM enables fast and efficient feedback between the pathologist and the laboratory in terms of ordered additional stains, automated access to the latest research for references, and fast consultation with outstanding telepathology experts. 4. Industry has already invested “big money” into this technology which certainly will be of influence in its future development. The main constraints against VM include the questionable reimbursement of the initial investment, the missing direct and short term financial benefit, and the loss of potential biological identity between the patient and the examined tissue. This article tries to analyze and evaluate the factors that influence the implementation of VM into routine tissue-based diagnosis, for example in combination with predictive diagnosis. It focuses on describing the advantages of modern and innovative electronically based communication technology.

Immunohistochemistry profiles of breast ductal carcinoma: factor analysis of digital image analysis data

BACKGROUND

Molecular studies of breast cancer revealed biological heterogeneity of the disease and opened new perspectives for personalized therapy. While multiple gene expression-based systems have been developed, current clinical practice is largely based upon conventional clinical and pathologic criteria. This gap may be filled by development of combined multi-IHC indices to characterize biological and clinical behaviour of the tumours. Digital image analysis (DA) with multivariate statistics of the data opens new opportunities in this field.

METHODS

Tissue microarrays of 109 patients with breast ductal carcinoma were stained for a set of 10 IHC markers (ER, PR, HER2, Ki67, AR, BCL2, HIF-1α, SATB1, p53, and p16). Aperio imaging platform with the Genie, Nuclear and Membrane algorithms were used for the DA. Factor analysis of the DA data was performed in the whole group and hormone receptor (HR) positive subgroup of the patients (n = 85).

RESULTS

Major factor potentially reflecting aggressive disease behaviour (i-Grade) was extracted, characterized by opposite loadings of ER/PR/AR/BCL2 and Ki67/HIF-1α. The i-Grade factor scores revealed bimodal distribution and were strongly associated with higher Nottingham histological grade (G) and more aggressive intrinsic subtypes. In HR-positive tumours, the aggressiveness of the tumour was best defined by positive Ki67 and negative ER loadings. High Ki67/ER factor scores were strongly associated with the higher G and Luminal B types, but also were detected in a set of G1 and Luminal A cases, potentially indicating high risk patients in these categories. Inverse relation between HER2 and PR expression was found in the HR-positive tumours pointing at differential information conveyed by the ER and PR expression. SATB1 along with HIF-1α reflected the second major factor of variation in our patients; in the HR-positive group they were inversely associated with the HR and BCL2 expression and represented the major factor of variation. Finally, we confirmed high expression levels of p16 in Triple-negative tumours.

CONCLUSION

Factor analysis of multiple IHC biomarkers measured by automated DA is an efficient exploratory tool clarifying complex interdependencies in the breast ductal carcinoma IHC profiles and informative value of single IHC markers. Integrated IHC indices may provide additional risk stratifications for the currently used grading systems and prove to be useful in clinical outcome studies.

VIRTUAL SLIDES

The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1512077125668949.