Current issues in ER and HER2 testing by IHC in breast cancer

DropBlot: single-cell western blotting of chemically fixed cancer cells

Archived patient-derived tissue specimens play a central role in understanding disease and developing therapies. To address specificity and sensitivity shortcomings of existing single-cell resolution proteoform analysis tools, we introduce a hybrid microfluidic platform (DropBlot) designed for proteoform analyses in chemically fixed single cells. DropBlot serially integrates droplet-based encapsulation and lysis of single fixed cells, with on-chip microwell-based antigen retrieval, with single-cell western blotting of target antigens. A water-in-oil droplet formulation withstands the harsh chemical (SDS, 6 M urea) and thermal conditions (98 °C, 1-2 hr) required for effective antigen retrieval, and supports analysis of retrieved protein targets by single-cell electrophoresis. We demonstrate protein-target retrieval from unfixed, paraformaldehyde-fixed (PFA), and methanol-fixed cells. Key protein targets (HER2, GAPDH, EpCAM, Vimentin) retrieved from PFA-fixed cells were resolved and immunoreactive. Relevant to biorepositories, DropBlot profiled targets retrieved from human-derived breast tumor specimens archived for six years, offering a workflow for single-cell protein-biomarker analysis of sparing biospecimens.

A Molecular Typing Method for Invasive Breast Cancer by Serum Raman Spectroscopy

BACKGROUND

The incidence of breast cancer ranks highest among cancers and is exceedingly heterogeneous. Immunohistochemical staining is commonly used clinically to identify the molecular subtype for subsequent treatment and prognosis.

PURPOSE

Raman spectroscopy and support vector machine (SVM) learning algorithm were utilized to identify blood samples from breast cancer patients in order to investigate a novel molecular typing approach.

METHOD

Tumor tissue coarse needle aspiration biopsy samples, and peripheral venous blood samples were gathered from 459 invasive breast cancer patients admitted to the breast department of Sichuan Cancer Hospital between June 2021 and September 2022. Immunohistochemical staining and in situ hybridization were performed on the coarse needle aspiration biopsy tissues to obtain their molecular typing pathological labels, including: 70 cases of Luminal A, 167 cases of Luminal B (HER2-positive), 57 cases of Luminal B (HER2-negative), 84 cases of HER2-positive, and 81 cases of triple-negative. Blood samples were processed to obtained Raman spectra taken for SVM classification models establishment with machine algorithms (using 80% of the sample data as the training set), and then the performance of the SVM classification models was evaluated by the independent validation set (20% of the sample data).

RESULTS

The AUC values of SVM classification models remained above 0.85, demonstrating outstanding model performance and excellent subtype discrimination of breast cancer molecular subtypes.

CONCLUSION

Raman spectroscopy of serum samples can promptly and precisely detect the molecular subtype of invasive breast cancer, which has the potential for clinical value.

Impact of benzo[a]pyrene, PCB153 and sex hormones on human ESC-Derived thyroid follicles using single cell transcriptomics

INTRODUCTION

Endocrine disruptors are compounds of manmade origin able to interfere with the endocrine system and constitute an important environmental concern. Indeed, detrimental effects on thyroid physiology and functioning have been described. Differences exist in the susceptibility of human sexes to the incidence of thyroid disorders, like autoimmune diseases or cancer.

METHODS

To study how different hormonal environments impact the thyroid response to endocrine disruptors, we exposed human embryonic stem cell-derived thyroid organoids to physiological concentrations of sex hormones resembling the serum levels of human females post-ovulation or males of reproductive age for three days. Afterwards, we added 10 µM benzo[a]pyrene or PCB153 for 24 h and analyzed the transcriptome changes via single-cell RNA sequencing with differential gene expression and gene ontology analysis.

RESULTS

The sex hormones receptors genes AR, ESR1, ESR2 and PGR were expressed at low levels. Among the thyroid markers, only TG resulted downregulated by benzo[a]pyrene or benzo[a]pyrene with the "male" hormones mix. Both hormone mixtures and benzo[a]pyrene alone upregulated ribosomal genes and genes involved in oxidative phosphorylation, while their combination decreased the expression compared to benzo[a]pyrene alone. The "male" mix and benzo[a]pyrene, alone or in combination, upregulated genes involved in lipid transport and metabolism (APOA1, APOC3, APOA4, FABP1, FABP2, FABP6). The combination of "male" hormones and benzo[a]pyrene induced also genes involved in inflammation and NFkB targets. Benzo[a]pyrene upregulated CYP1A1, CYP1B1 and NQO1 irrespective of the hormonal context. The induction was stronger in the "female" mix. Benzo[a]pyrene alone upregulated genes involved in cell cycle regulation, response to reactive oxygen species and apoptosis. PCB153 had a modest effect in presence of "male" hormones, while we did not observe any changes with the "female" mix.

CONCLUSION

This work shows how single cell transcriptomics can be applied to selectively study the in vitro effects of endocrine disrupters and their interaction with different hormonal contexts.

High sensitivity saliva-based biosensor in detection of breast cancer biomarkers: HER2 and CA15-3

The prevalence of breast cancer in women underscores the urgent need for innovative and efficient detection methods. This study addresses this imperative by harnessing salivary biomarkers, offering a noninvasive and accessible means of identifying breast cancer. In this study, commercially available disposable based strips similar to the commonly used glucose detection strips were utilized and functionalized to detect breast cancer with biomarkers of HER2 and CA15-3. The results demonstrated limits of detection for these two biomarkers reached as low as 1 fg/ml much lower than those of conventional enzyme-linked immunosorbent assay in the range of 1∼4 ng/ml. By employing a synchronized double-pulse method to apply 10 of 1.2 ms voltage pulses to the electrode of sensing strip and drain electrode of the transistor for amplifying the detected signal, and the detected signal was the average of 10 digital output readings corresponding to those 10 voltage pulses. The sensor sensitivities were achieved approximately 70/dec and 30/dec for HER2 and CA15-3, respectively. Moreover, the efficiency of this novel technique is underscored by its swift testing time of less than 15 ms and its minimal sample requirement of only 3 μl of saliva. The simplicity of operation and the potential for widespread public use in the future position this approach as a transformative tool in the early detection of breast cancer. This research not only provides a crucial advancement in diagnostic methodologies but also holds the promise of revolutionizing public health practices.

Omission of radiation therapy post breast conserving surgery

Radiation therapy (RT) after breast conserving surgery decreases the risks of local recurrence and breast cancer mortality in the multidisciplinary management of patients with breast cancer. However, breast cancer is a heterogeneous disease, and the absolute benefit of post-operative RT in individual patients varies substantially. Clinical trials aiming to identify patients with low-risk early breast cancer in whom post-operative RT may be safely omitted, based on conventional clinical-pathologic variables alone, have not provided sufficiently tailored information on local recurrence risk assessment to guide treatment decisions. The majority of patients with early breast cancer continue to be routinely treated with RT after breast conserving surgery. This approach may represent over-treatment for a substantial proportion of the patients. The clinical impact of genomic signatures on local therapy decisions for early breast cancer has been remarkably modest due to the lack of high-level evidence supporting their clinical validity for assessment of the risk of local recurrence. Efforts to personalise breast cancer care must be supported by high level evidence to enable balanced, informed treatment decisions. These considerations underpin the importance of ongoing biomarker-directed clinical trials to generate the high-level evidence necessary for setting the future standard of care in personalised local therapy for patients with early breast cancer.

Qualification of a multiplexed tissue imaging assay and detection of novel patterns of HER2 heterogeneity in breast cancer

Emerging data suggests that HER2 intratumoral heterogeneity (ITH) is associated with therapy resistance, highlighting the need for new strategies to assess HER2 ITH. A promising approach is leveraging multiplexed tissue analysis techniques such as cyclic immunofluorescence (CyCIF), which enable visualization and quantification of 10-60 antigens at single-cell resolution from individual tissue sections. In this study, we qualified a breast cancer-specific antibody panel, including HER2, ER, and PR, for multiplexed tissue imaging. We then compared the performance of these antibodies against established clinical standards using pixel-, cell- and tissue-level analyses, utilizing 866 tissue cores (representing 294 patients). To ensure reliability, the CyCIF antibodies were qualified against HER2 immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) data from the same samples. Our findings demonstrate the successful qualification of a breast cancer antibody panel for CyCIF, showing high concordance with established clinical antibodies. Subsequently, we employed the qualified antibodies, along with antibodies for CD45, CD68, PD-L1, p53, Ki67, pRB, and AR, to characterize 567 HER2+ invasive breast cancer samples from 189 patients. Through single-cell analysis, we identified four distinct cell clusters within HER2+ breast cancer exhibiting heterogeneous HER2 expression. Furthermore, these clusters displayed variations in ER, PR, p53, AR, and PD-L1 expression. To quantify the extent of heterogeneity, we calculated heterogeneity scores based on the diversity among these clusters. Our analysis revealed expression patterns that are relevant to breast cancer biology, with correlations to HER2 ITH and potential relevance to clinical outcomes.

Employing Pd nanoparticles decorated on halloysite nanotube/carbon composite for electrochemical aptasensing of HER2 in breast cancer patients

An effective biosensing platform is described based on halloysite nanotube/carbon composite decorated with Pd nanoparticles (HNT/C@Pd NPs). A novel electrochemical aptasensor was designed using the proposed nano-platform to determine human epidermal growth factor receptor 2 (HER2), a breast cancer biomarker. Inherently, aptasensing interfaces provide high sensitivity and selectivity for tumor markers owing to the high specific surface area of HNT/C and good conductivity stems from deposition of Pd NPs into HNT/C composite. With a correlation coefficient of 0.996, the electrochemical aptasensor demonstrated a wide linear range from 0.03 ng/mL to 9 ng/mL. The limit of detection (LOD) of the established assay was 8 pg/mL based on S/N = 3 method. Further, the designed biosensor demonstrated acceptable selectivity, good reproducibility, and high stability. The applicability of the impedimetric sensor in human serum samples was also examined and compared to enzyme-linked immunosorbent assay (ELISA) assay (p-value >0.05). Based on the results, it was found that the proposed methodology can be used in quantification of breast cancer markers for early diagnosis and treatment.

DropBlot: single-cell western blotting of chemically fixed cancer cells

To further realize proteomics of archived tissues for translational research, we introduce a hybrid microfluidic platform for high-specificity, high-sensitivity protein detection from individual chemically fixed cells. To streamline processing-to-analysis workflows and minimize signal loss, DropBlot serially integrates sample preparation using droplet-based antigen retrieval from single fixed cells with unified analysis-on-a-chip comprising microwell-based antigen extraction followed by chip-based single-cell western blotting. A water-in-oil droplet formulation proves robust to the harsh chemical (SDS, 6M urea) and thermal conditions (98°C, 1-2 hr.) required for sufficient antigen retrieval, and the electromechanical conditions required for electrotransfer of retrieved antigen from microwell-encapsulated droplets to single-cell electrophoresis. Protein-target retrieval was demonstrated for unfixed, paraformaldehyde-(PFA), and methanol-fixed cells. We observed higher protein electrophoresis separation resolution from PFA-fixed cells with sufficient immunoreactivity confirmed for key targets (HER2, GAPDH, EpCAM, Vimentin) from both fixation chemistries. Multiple forms of EpCAM and Vimentin were detected, a hallmark strength of western-blot analysis. DropBlot of PFA-fixed human-derived breast tumor specimens (n = 5) showed antigen retrieval from cells archived frozen for 6 yrs. DropBlot could provide a precision integrated workflow for single-cell resolution protein-biomarker mining of precious biospecimen repositories.

Automated Classification of Breast Cancer Across the Spectrum of ERBB2 Expression Focusing on Heterogeneous Tumors With Low Human Epidermal Growth Factor Receptor 2 Expression

PURPOSE

Although pharmaceutical companies conduct clinical trials of novel human epidermal growth factor receptor 2 (HER2)-low-directed drugs, diagnosing HER2-low cancer by immunohistochemistry (IHC) and in situ hybridization (ISH) remains challenging. This study investigates the performance of first-in-kind computerized intelligence to classify samples across gene expression levels and differentiate HER2-low tumors.

MATERIALS AND METHODS

We classified 251 samples: 142 primary invasive breast cancers (IBCs), 75 ductal carcinomas in situ (DCIS), and 34 mammaplasties (reference) using mRNA expression data from the QuantiGene Plex 2.0 assay. We used g3mclass probabilistic software to assess the number of classes in the assay data, the mean and the variance in each class, diagnostic cutoffs, and the prevalence of each class in the study population.

RESULTS

HER2-low (IHC score of 1+ or 2+/ISH-) accounted for 31% of IBC. First, we discovered that HER2-low tumors were represented by cases with normal ERBB2 transcript levels that were expected to produce physiologic levels of HER2 (70%) and cases with abnormally upregulated unamplified ERBB2 (30%). We termed the latter cancers ERBB2-up as they do not meet the standard definitions for ERBB2 overexpression and amplification. Second, HER2-low IBC classified as ERBB2-up had not only abnormally increased luminal growth and adhesion markers (ERBB2, ESR1, PGR, IGF1R, VAV2, VAV3, KRT8, CDH1) but also downregulated myoepithelial marker (KRT5). The vascularization (RAP1 and C3G), immune cell infiltration (VAV1), and mesenchymal transition (CDH2) markers were dysregulated. Finally, in the independent cohort of DCIS, 40% of HER2-low DCIS shared similar traits with HER2-low IBC except for rare downregulation of KRT5 and no change in C3G, VAV1, and CDH2.

CONCLUSION

We demonstrated how innovative bioinformatic tools could help diagnose cancer across the spectrum of ERBB2 expression to aid decision making for HER2-low.

ELISA-like QDB method to meet the emerging need of Her2 assessment for breast cancer patients

Inherent issues of subjectivity and inconsistency have long plagued immunohistochemistry (IHC)-based Her2 assessment, leading to the repeated issuance of guidelines by the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) for its standardization for breast cancer patients. Yet, all these efforts may prove insufficient with the advent of Trastuzumab deruxtecan (T-Dxd), a drug with the promise to expand to tumors traditionally defined as Her2 negative (Her2-). In this study, we attempted to address these issues by exploring an ELISA-like quantitative dot blot (QDB) method as an alternative to IHC. The QDB method has been used to measure multiple protein biomarkers including ER, PR, Ki67, and cyclin D1 in breast cancer specimens. Using an independent cohort (cohort 2) of breast cancer formalin-fixed paraffin-embedded (FFPE) specimens, we validated cutoffs developed in cohort 1 (Yu et al., Scientific Reports 2020 10:10502) with overall 100% specificity (95% CI: 100-100) and 97.56% sensitivity (95% CI: 92.68-100) in cohort 2 against standard practice with the dichotomized absolutely quantitated values. Using the limit of detection (LOD) of the QDB method as the putative cutoff point, tumors with no Her2 expression were identified with the number comparable to those of IHC 0. Our results support further evaluation of the QDB method as an alternative to IHC to meet the emerging need of identifying tumors with low Her2 expression (Her2-low) in daily clinical practice.

In Situ Proximity Ligation Assay to Visualize Protein-Protein Interactions in Tumor Specimens

Protein-protein interactions (PPI) are the basis of various biological phenomena, such as intracellular signal transduction, gene transcription, and metabolism. PPI are also considered to be involved in the pathogenesis and development of various diseases, including cancer. PPI phenomenon and their functions have been elucidated by gene transfection and molecular detection technologies. On the other hand, in histopathological analysis, although immunohistochemical analyses provide information pertaining to protein expression and their localization in pathophysiological tissues, it has been difficult to visualize the PPI of these proteins. An in situ proximity ligation assay (PLA) was developed as a microscopic visualization technique for PPI in formalin-fixed, paraffin-embedded (FFPE) tissues as well as in cultured cells and frozen tissues. PLA using histopathological specimens enables cohort studies of PPI, which can clarify the significance of PPI in pathology. We have previously shown the dimerization pattern of estrogen receptors and significance of HER2-binding proteins using breast cancer FFPE tissues. In this chapter, we describe a methodology for the visualization of PPI using PLA in pathological specimens.

HER2 classification in breast cancer cells: A new explainable machine learning application for immunohistochemistry

The immunohistochemical (IHC) evaluation of epidermal growth factor 2 (HER2) for the diagnosis of breast cancer is still qualitative with a high degree of inter-observer variability, and thus requires the incorporation of complementary techniques such as fluorescent in situ hybridization (FISH) to resolve the diagnosis. Implementing automatic algorithms to classify IHC biomarkers is crucial for typifying the tumor and deciding on therapy for each patient with better performance. The present study aims to demonstrate that, using an explainable Machine Learning (ML) model for the classification of HER2 photomicrographs, it is possible to determine criteria to improve the value of IHC analysis. We trained a logistic regression-based supervised ML model with 393 IHC microscopy images from 131 patients, to discriminate between upregulated and normal expression of the HER2 protein. Pathologists' diagnoses (IHC only) vs. the final diagnosis complemented with FISH (IHC + FISH) were used as training outputs. Basic performance metrics and receiver operating characteristic curve analysis were used together with an explainability algorithm based on Shapley Additive exPlanations (SHAP) values to understand training differences. The model could discriminate amplified IHC from normal expression with better performance when the training output was the IHC + FISH final diagnosis (IHC vs. IHC + FISH: area under the curve, 0.94 vs. 0.81). This may be explained by the increased analytical impact of the membrane distribution criteria over the global intensity of the signal, according to SHAP value interpretation. The classification model improved its performance when the training input was the final diagnosis, downplaying the weighting of the intensity of the IHC signal, suggesting that to improve pathological diagnosis before FISH consultation, it is necessary to emphasize subcellular patterns of staining.

Breast Cancer Dataset, Classification and Detection Using Deep Learning

Incorporating scientific research into clinical practice via clinical informatics, which includes genomics, proteomics, bioinformatics, and biostatistics, improves patients' treatment. Computational pathology is a growing subspecialty with the potential to integrate whole slide images, multi-omics data, and health informatics. Pathology and laboratory medicine are critical to diagnosing cancer. This work will review existing computational and digital pathology methods for breast cancer diagnosis with a special focus on deep learning. The paper starts by reviewing public datasets related to breast cancer diagnosis. Additionally, existing deep learning methods for breast cancer diagnosis are reviewed. The publicly available code repositories are introduced as well. The paper is closed by highlighting challenges and future works for deep learning-based diagnosis.

Deep oncopanel sequencing reveals within block position-dependent quality degradation in FFPE processed samples

BACKGROUND

Clinical laboratories routinely use formalin-fixed paraffin-embedded (FFPE) tissue or cell block cytology samples in oncology panel sequencing to identify mutations that can predict patient response to targeted therapy. To understand the technical error due to FFPE processing, a robustly characterized diploid cell line was used to create FFPE samples with four different pre-tissue processing formalin fixation times. A total of 96 FFPE sections were then distributed to different laboratories for targeted sequencing analysis by four oncopanels, and variants resulting from technical error were identified.

RESULTS

Tissue sections that fail more frequently show low cellularity, lower than recommended library preparation DNA input, or target sequencing depth. Importantly, sections from block surfaces are more likely to show FFPE-specific errors, akin to "edge effects" seen in histology, while the inner samples display no quality degradation related to fixation time.

CONCLUSIONS

To assure reliable results, we recommend avoiding the block surface portion and restricting mutation detection to genomic regions of high confidence.

L’intelligence artificielle pourrait-elle intervenir dans l’aide au diagnostic des cancers du sein ? – L’exemple de HER2

HER2 is an important prognostic and predictive biomarker in breast cancer. Its detection makes it possible to define which patients will benefit from a targeted treatment. While assessment of HER2 status by immunohistochemistry in positive vs negative categories is well implemented and reproducible, the introduction of a new "HER2-low" category could raise some concerns about its scoring and reproducibility. We herein described the current HER2 testing methods and the application of innovative machine learning techniques to improve these determinations, as well as the main challenges and opportunities related to the implementation of digital pathology in the up-and-coming AI era.

Associations between the Levels of Estradiol-, Progesterone-, and Testosterone-Sensitive MiRNAs and Main Clinicopathologic Features of Breast Cancer

Despite the existing advances in the diagnosis and treatment of breast cancer (BC), the search for markers associated with the clinicopathological features of BC is still in demand. MiRNAs (miRs) have potential as markers, since a change in the miRNA expression profile accompanies the initiation and progression of malignant diseases. The receptors for estrogen, androgen, and progesterone (ER, AR, and PR) play an important role in breast carcinogenesis. Therefore, to search for miRNAs that may function as markers in BC, using bioinformatic analysis and the literature data, we selected 13 miRNAs whose promoter regions contain binding sites for ER or AR, or putative binding sites for ER, AR, and PR. We quantified their expression in MCF-7 cells treated with estradiol, progesterone, or testosterone. The levels of miRNAs sensitive to one or more of these hormones were quantified in BC samples (n = 196). We discovered that high expression levels of miR-190b in breast tumor tissue indicate a positive ER status, and miR-423 and miR-200b levels differ between patients with and without HER2 amplification. The miR-193b, -423, -190a, -324, and -200b levels were associated with tumor size or lymph node status in BC patients, but the presence of these associations depended on the status and expression level of ER, PR, HER2, and Ki-67. We also found that miR-21 expression depends on HER2 expression in ER- and/or PR-positive BC. The levels of miRNA were significantly different between HER2 0 and HER2 1+ tumors (p = 0.027), and between HER2 0 and HER2 2+, 3+ tumors (p = 0.005).

ESR1 PvuII polymorphism: from risk factor to prognostic and predictive factor of the success of primary systemic therapy in advanced breast cancer

BACKGROUND

The ESR1 gene encodes Estrogen Receptor alpha (ERα), which plays a role in the tumourigenesis of breast cancer. A single nucleotide polymorphism (SNP) in intron 1 of this gene called ESR1 PvuII (rs2234693) has been reported to increase the risk of breast cancer. This study aimed to investigate the ESR1 PvuII polymorphism as a prognostic and predictive factor guiding the choice of therapy for advanced breast cancer.

METHODS

This retrospective study was conducted in 104 advanced breast cancer patients at Dharmais Cancer Hospital from 2011 to 2018. The ESR1 PvuII polymorphism was analysed by Sanger sequencing of DNA from primary breast tumour samples.

RESULTS

The percentages of patients with ESR1 PvuII genotypes TT, TC, and CC were 42.3, 39.4, and 18.3%, respectively. Looking at prognosis, patients with ESR1 PvuII TC + CC had shorter overall survival than those with the TT genotype [HR = 1.79; 95% CI 1.05-3.04; p = 0.032]. As a predictive marker, TC + CC was associated with shorter survival (p = 0.041), but TC + CC patients on primary hormonal therapy had a median overall survival longer than TC + CC patients on primary chemotherapy (1072 vs 599 days).

CONCLUSION

The ESR1 PvuII TC + CC genotypes confer poor prognosis in advanced breast cancer, but these genotypes could be regarded as a good predictor of the therapeutic effect of hormonal treatment.

Functional Significance of Selective Expression of ERα and ERβ in Mammary Gland Organ Culture

Thoracic pair of mammary glands from steroid hormone-pretreated mice respond to hormones structurally and functionally in organ culture. A short exposure of glands for 24 h to 7,12 Dimethylbenz(a)anthracene (DMBA) during a 24-day culture period induced alveolar or ductal lesions. Methods: To differentiate the functional significance of ERα and ERβ, we employed estrogen receptor (ER) knockout mice. We compared the effects of DMBA on the development of preneoplastic lesions in the glands in the absence of ERα (αERKO) and ERβ (βERKO) using an MMOC protocol. Glands were also subjected to microarray analyses. We showed that estradiol can be replaced by EGF for pretreatment of mice. The carcinogen-induced lesions developed under both steroids and EGF pretreatment protocols. The glands from αERKO did not develop any lesions, whereas in βERKO mice in which ERα is intact, mammary alveolar lesions developed. Comparison of microarrays of control, αERKO and βERKO mice showed that ERα was largely responsible for proliferation and the MAP kinase pathways, whereas ERβ regulated steroid metabolism-related genes. The results indicate that ERα is essential for the development of precancerous lesions. Both subtypes, ERα and Erβ, differentially regulated gene expression in mammary glands in organ cultures.

Targeting HER2 protein in individual cells using ICP-MS detection and its potential as prognostic and predictive breast cancer biomarker

The human epidermal growth factor receptor 2 (HER2) is a transmembrane protein that has become one of the most specific prognostic and predictive biomarker of breast cancer. Its early detection is key for optimizing the patient clinical outcome. This work is focused on the detection of HER2 in individual cells using an antibody containing lutetium (Lu) as reporter group that is monitored by introducing the individual cells into the inductively coupled plasma mass spectrometer (ICP-MS). This Lu-containing antibody probe is used to label different breast cancer cell lines considered HER2 negative (MDA-MB-231) and positive (SKBR-3 and BT-474). Optimizations regarding the amount of the probe necessary to ensure complete labelling reactions are conducted in the different cell models. Concentrations in the range of 0.006 fg Lu/cell and 0.030 fg Lu/cell could be found in the HER2 negative and HER2 positive cells, respectively. In addition, the selectivity of the labelling reaction is tested by using two different metal-containing antibody probes for HER2 (containing Lu) and for transferrin receptor 1 (containing Nd), respectively, within the same cell population. Finally, the methodology is applied to the targeting of HER2 positive cells in complex cell mixtures containing variable amounts of BT-474 and MDA-MB-231 cells. The obtained results showed the excellent capabilities of the proposed strategy to discriminate among cell populations. This finding could help for scoring HER2 positive tumors improving existing technologies.

The expression and clinical significance of ERβ/ERα in ovarian cancer: can we predict the effectiveness of platinum plus taxane therapy?

Estrogens play an extremely important role in regulating the proliferation of ovarian cancer. The estrogen receptor alpha (ERα) stimulates cell growth, whereas ERβ can be attributed to tumor suppressors. The study aims to assess the relationship between the expression of estrogen receptors in tumors and the efficacy of front-line platinum plus taxane chemotherapy in ovarian cancer patients.

MATERIALS AND METHODS

ERα and ERβ tumor expression was evaluated quantitatively by flow cytometry in a narrowly defined group (31 patients): stage III high-grade serous ovarian carcinoma (HGSOC), suboptimal surgical cytoreduction, front-line platinum plus taxane chemotherapy (front-line, six cycles).

RESULTS

The median of progression-free survival (PFS) was 2 times greater (18 vs 8 months, p = 0.04) and the recurrence risk (HR) was 2.2 times (95 % CI: 1.1-6.2, p = 0.04) lower in the group with high (in more than 40% of the cells) vs low level of ERβ tumor expression. The statistically significant difference between PFS in the groups with high vs low tumor ERα expression was not revealed.

CONCLUSION

A high level of ERβ and not ERα expression can predict the efficacy of front-line platinum plus taxane chemotherapy in stage III HGSOC patients. The status of estrogen receptor beta can be considered as one of the possible predictors for evaluating the effectiveness of ovarian cancer therapy.

Cellphone enabled point-of-care assessment of breast tumor cytology and molecular HER2 expression from fine-needle aspirates

Management of breast cancer in limited-resource settings is hindered by a lack of low-cost, logistically sustainable approaches toward molecular and cellular diagnostic pathology services that are needed to guide therapy. To address these limitations, we have developed a multimodal cellphone-based platform—the EpiView-D4—that can evaluate both cellular morphology and molecular expression of clinically relevant biomarkers directly from fine-needle aspiration (FNA) of breast tissue specimens within 1 h. The EpiView-D4 is comprised of two components: (1) an immunodiagnostic chip built upon a “non-fouling” polymer brush-coating (the “D4”) which quantifies expression of protein biomarkers directly from crude cell lysates, and (2) a custom cellphone-based optical microscope (“EpiView”) designed for imaging cytology preparations and D4 assay readout. As a proof-of-concept, we used the EpiView-D4 for assessment of human epidermal growth factor receptor-2 (HER2) expression and validated the performance using cancer cell lines, animal models, and human tissue specimens. We found that FNA cytology specimens (prepared in less than 5 min with rapid staining kits) imaged by the EpiView-D4 were adequate for assessment of lesional cellularity and tumor content. We also found our device could reliably distinguish between HER2 expression levels across multiple different cell lines and animal xenografts. In a pilot study with human tissue (n = 19), we were able to accurately categorize HER2-negative and HER2-positve tumors from FNA specimens. Taken together, the EpiView-D4 offers a promising alternative to invasive—and often unavailable—pathology services and may enable the democratization of effective breast cancer management in limited-resource settings.

Transferred-tissue Microarray for Fluorescence In Situ Hybridization Test for Human Epidermal Growth Factor Receptor 2 in Breast Cancer

CONTEXT

Human epidermal growth factor receptor 2 (HER2) status of breast carcinomas is usually determined by immunohistochemical (IHC) staining and, if the IHC results are equivocal, in situ hybridization (ISH). Multiple ISH tests are sometimes required for multiple primary or metastatic tumors. A method for multiplex ISH test on tissues from multiple blocks is helpful in these situations.

OBJECT

To evaluate the clinical application of transferred-tissue microarray (TTM) followed by a dual-probe HER2 fluorescence in situ hybridization (FISH).

DESIGN

A 3×3 TTM technique was successfully established using 152 invasive mammary carcinoma tissue fragments. To evaluate detection of HER2 positive tumors, this cohort was enriched with tumors with IHC scores of 2 and 3.

RESULTS

The HER2 FISH analyses revealed that all transferred-tissue fragments were adequate for determining HER2 amplification. Tissue loss was minimal and had no major adverse effects on interpretation of the test results. Of the 81 tumors with IHC scores of 3, 72 (88.8%) were positive for HER2 FISH. The remaining tumors were negative for HER2 FISH in both TTM and reflex whole tissue section. Finally, FISH results for tumors with IHC scores of 2 were compared between TTM and whole tissue section. Concordance was high in overall positivity/negativity (100%), HER2 copy number (97.5%), and HER2/CEP17 ratio (100%).

CONCLUSIONS

This novel technique is a reliable option for performing multiple HER2 FISH tests simultaneously in clinical and research-oriented settings with less tissue damage compared with conventional tissue microarray techniques.

Whole-Genome Sequencing of Common Salivary Gland Carcinomas: Subtype-Restricted and Shared Genetic Alterations

PURPOSE

Salivary gland carcinomas (SGCs) are pathologically classified into several widely diverse subtypes, of which adenoid cystic carcinoma (ACC), mucoepidermoid carcinoma (MEC), and salivary duct carcinoma (SDC) are the most commonly encountered. A comparative genetic analysis of these subtypes provides detailed information on the genetic alterations that are associated with their tumorigenesis and may lead to the identification of biomarkers to guide tumor-specific clinical trials.

EXPERIMENTAL DESIGN

Whole-genome sequencing of 58 common SGCs (20 ACCs, 20 SDCs, and 18 MECs) was performed to catalog structural variations, copy number, rearrangements, and driver mutations. Data were bioinformatically analyzed and correlated with clinicopathologic parameters, and selected targets were validated.

RESULTS

Novel and recurrent type-specific and shared genetic alterations were identified within and among 3 subtypes. Mutually exclusive canonical fusion and nonfusion genomic alterations were identified in both ACC and MEC. In ACCs, loss of chromosome 12q was dominant in MYB or MYBL1 fusion-positive tumors and mutations of NOTCH pathway were more common in these fusion negatives. In MECs, CRTC1-MAML2 fusion-positive tumors showed frequent BAP1 mutation, and tumors lacking this fusion were enriched with LRFN1 mutation. SDCs displayed considerable genetic instability, lacked recurrent chromosomal rearrangements, and demonstrated nonoverlapping TP53 mutation and ERBB2 amplification in a subset of tumors. Limited genetic alterations, including focal amplifications of 8q21-q23, were shared by all subtypes and were associated with poor survival.

CONCLUSIONS

This study delineates type-specific and shared genetic alterations that are associated with early phenotypic commitment and the biologic progression of common SGCs. These alterations, upon validation, could serve as biomarkers in tumor-specific clinical trials.

Thyroglobulin as a negative marker for malignancy in canine and human breast tumors

Canine mammary gland tumors (CMTs) are the most common tumor type in female dogs. This study evaluated the expression pattern and role of thyroglobulin (Tg) in CMT and in human breast cancer (HBC). CMT samples were subjected to fine-needle aspiration, primary cell culture, and histopathology. The expression level of Tg was higher in benign CMT than in malignant CMT (mCMT) primary cells, particularly in the epithelial lineage. Moreover, treatment with Tg enhanced the sensitivity of doxorubicin in mCMT epithelial cells and mitigated proinflammatory response by increasing nuclear factor erythroid 2-related factor 2 (Nrf2). The proximal region of the Tg promoter was hypermethylated in mCMT epithelial cells, silencing Tg expression with concurrent downregulation of Nrf2-mediated antioxidant signaling. An identical pattern of Tg expression was observed in cytological and tissue samples. Tissue microarray analysis showed that Tg was highly expressed in normal and benign tissues when compared with their malignant counterparts, which was diminished along with higher histological grades. The survival rate was significantly higher in HBC patients with high Tg expression than those with low Tg expression. This study also showed that the progression of HBC is accompanied by the reduction of Tg expression along with augmentation of proinflammatory signaling. Our data suggested that Tg could be a negative indicator of malignancy in canine and human breast neoplasia.

Hormone Receptors and Her-2/neu Overexpression in Breast Carcinomas in Patients of West African Origin Seen at Lagos State University Teaching Hospital, Nigeria

Breast carcinoma is a disease of utmost concern to the individual, family, and society at large. The current trend in the management of breast carcinoma also involves hormonal therapy. Consequently, the hormone expression of the tumor in the individual involved must be known if he or she is to benefit from such therapy. This is a prospective study of estrogen and progesterone receptors as well as Her-2/neu overexpression in all breast carcinomas seen at the Lagos State University Teaching Hospital, Ikeja, Nigeria, between April, 1, 2016, and September, 30, 2018. The total number of cases analyzed during the period under study was 107, comprising 105 women and 2 men with an age range of 26 to 88 years and a mean age of 52 ± 13 years. The tumors fell into histologic grade II (71.0%) and grade III (29.0%). They expressed ER, PR, and Her-2/neu positivity in 42.1%, 33.6%, and 30.8% of the cases, respectively. Triple-negative breast cancer was 35.5%. Male breast cancers presented as invasive ductal carcinoma and exhibit similar staining pattern as the female breast cancer. In conclusion, this study shows that breast carcinomas occurred predominantly in females of younger age and present with tumors, most of which were of high grade and exhibit triple negativity. This observation is relevant to any therapeutic decisions and management of these patients. Improvement in breast carcinoma screening programs so that the disease can be detected early is also advocated.

Global Protease Activity Profiling Identifies HER2-Driven Proteolysis in Breast Cancer

Differential expression of extracellular proteases and endogenous protease inhibitors has been associated with distinct molecular subtypes of breast cancer. However, due to the tight post-translational regulation of protease activity, protease expression-level data alone are not sufficient to understand the role of proteases in malignant transformation. Therefore, we hypothesized that global profiles of extracellular protease activity could more completely reflect differences observed at the transcriptional level in breast cancer and that subtype-associated protease activity may be leveraged to identify specific proteases that play a functional role in cancer signaling. Here, we used a global peptide library-based approach to profile the activities of proteases within distinct breast cancer subtypes. Analysis of 3651 total peptide cleavages from a panel of well-characterized breast cancer cell lines demonstrated differences in proteolytic signatures between cell lines. Cell line clustering based on protease cleavages within the peptide library expanded upon the expected classification derived from transcriptional profiling. An isogenic cell line model developed to further interrogate proteolysis in the HER2 subtype revealed a proteolytic signature consistent with activation of TGF-β signaling. Specifically, we determined that a metalloprotease involved in TGF-β signaling, BMP1, was upregulated at both the protein (2-fold, P = 0.001) and activity (P = 0.0599) levels. Inhibition of BMP1 and HER2 suppressed invasion of HER2-expressing cells by 35% (P < 0.0001), compared to 15% (P = 0.0086) observed in cells where only HER2 was inhibited. In summary, through global identification of extracellular proteolysis in breast cancer cell lines, we demonstrate subtype-specific differences in protease activity and elucidate proteolysis associated with HER2-mediated signaling.

High Intrinsic Expression of P-glycoprotein and Breast Cancer Resistance Protein in Canine Mammary Carcinomas Regardless of Immunophenotype and Outcome

P-glycoprotein (P-gp) and breast cancer resistance protein (BCRP) are major actors in multidrug resistance (MDR) phenomenon in both human and canine mammary carcinomas (CMCs). The aim of this study was to investigate an association between the intrinsic expression of P-gp and BCRP compared to the immunophenotypes and outcome in CMCs. Fifty CMCs were evaluated at immunohistochemistry (IHC) for P-gp, BCRP, Estrogen receptor alpha (ER), Progesterone receptors (PR), Human Epidermal Growth Factor Receptor type 2 (HER2), basal cytokeratins 5/6 (CK5/6), Epidermal Growth Factor Receptor 1 (EGFR), and Ki67 proliferation index. P-gp and BCRP positive cases were, respectively, 52% and 74.5%, with a significantly higher expression of BCRP than P-gp. Five immunophenotypes were defined in 37 out of 50 CMCs: 9 (24.3%) Luminal A, 5 (13.5%) Luminal B, 9 (24.3%) HER2 overexpressing, 9 (24.3%) Triple-negative basal-like, and 5 (13.5%) Triple-negative non-basal-like. In all CMCs at least one marker was expressed. Follow-up data were available for 25 animals. The average cancer-specific survival was 739 ± 444 days. A number of CMCs bear a high expression of P-gp and BCRP but no significant association was found between their expression and the immunophenotypes, Ki67 index, the histological grade, and tumor-related death.

Systematic review and meta-analysis of breast cancer brain metastasis and primary tumor receptor expression discordance

Background

Change in hormone receptor (estrogen [ER] and progesterone [PR]) and/or human epidermal growth factor receptor type 2 (HER2) status during the evolutionary course of metastatic breast cancer and the effect of tumor classification subtype switching remain understudied and underappreciated in brain metastasis patients.

Methods

Using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, a systematic review of series published prior to April 2020 obtained from the Medline database of biopsied or resected breast cancer brain metastasis (BCBM) was performed. Weighted random effects models were used to calculate pooled estimates.

Results

15 full-text articles were included with receptor expression analyses on 1373 patients who underwent biopsy or resection of at least one intracranial lesion to compare to the primary tumor. Primary tumor receptor expression immunophenotypes were 45.0% ER+, 41.0% ER−, 31.0% PR+, 51.0% PR−, 35% HER2+, and 47.0% HER2−. Corresponding BCBM immunophenotypes were 19.0% ER+, 31.0% ER−, 13.0% PR+, 40.0% PR−, 21.0% HER2+, and 26.0% HER2−. On primary/BCBM comparison, 540 patients (42.6%) exhibited discordance in any receptor with 17.0% (95% CI: 13.0%–23.0%) discordant on ER, 23.0% (95% CI: 18.0%–30.0%) discordant on PR, and 12.0% (95% CI: 8.0%–16.0%) discordant on HER2 status. The most common receptor conversions found in BCBM were ER loss 11.0% (95% CI: 8.0%–16.0%), PR loss 15.0% (95% CI: 11.0%–21.0%), and HER2 gain 9.0% (95% CI: 7.0%–11.0%).

Conclusions

BCBM exhibits significant receptor expression discordance in comparison to primary tumors in approximately 40% of patients. Classification patterns need to be analyzed to determine factors predictive of BCBM/primary tumor discordance. Overall, tumor subtype switching and its effect on clinical management remains underappreciated.

Deep learning-enabled breast cancer hormonal receptor status determination from base-level H&E stains

For newly diagnosed breast cancer, estrogen receptor status (ERS) is a key molecular marker used for prognosis and treatment decisions. During clinical management, ERS is determined by pathologists from immunohistochemistry (IHC) staining of biopsied tissue for the targeted receptor, which highlights the presence of cellular surface antigens. This is an expensive, time-consuming process which introduces discordance in results due to variability in IHC preparation and pathologist subjectivity. In contrast, hematoxylin and eosin (H&E) staining—which highlights cellular morphology—is quick, less expensive, and less variable in preparation. Here we show that machine learning can determine molecular marker status, as assessed by hormone receptors, directly from cellular morphology. We develop a multiple instance learning-based deep neural network that determines ERS from H&E-stained whole slide images (WSI). Our algorithm—trained strictly with WSI-level annotations—is accurate on a varied, multi-country dataset of 3,474 patients, achieving an area under the curve (AUC) of 0.92 for sensitivity and specificity. Our approach has the potential to augment clinicians’ capabilities in cancer prognosis and theragnosis by harnessing biological signals imperceptible to the human eye.

Determination of estrogen receptor status (ERS) in breast cancer tissue requires immunohistochemistry, which is sensitive to the vagaries of sample processing and the subjectivity of pathologists. Here the authors present a deep learning model that determines ERS from H&E stained tissue, which could improve oncology decisions in under-resourced settings.

Triple-Negative Breast Cancer Comparison With Canine Mammary Tumors From Light Microscopy to Molecular Pathology

Many similar characteristics in human and dog cancers including, spontaneous development, clinical presentation, tumor heterogeneity, disease progression, and response to standard therapies have promoted the approval of this comparative model as an alternative to mice. Breast cancer represents the second most frequent neoplasm in humans after lung cancer. Triple-negative breast cancers (TNBC) constitute around 15% of all cases of breast cancer and do not express estrogen receptor (ER), progesterone receptor (PR), and do not overexpress human epidermal growth factor receptor 2 (HER2). As a result, they do not benefit from hormonal or trastuzumab-based therapy. Patients with TNBC have worse overall survival than patients with non-TNBC. Lehmann and collaborators described six different molecular subtypes of TNBC which further demonstrated its transcriptional heterogeneity. This six TNBC subtype classification has therapeutic implications. Breast cancer is the second most frequent neoplasm in sexually intact female dogs after skin cancer. Canine mammary tumors are a naturally occurring heterogeneous group of cancers that have several features in common with human breast cancer (HBC). These similarities include etiology, signaling pathway activation, and histological classification. Molecularly CMTs are more like TNBCs, and therefore dogs are powerful spontaneous models of cancer to test new therapeutic approaches, particularly for human TNBCs. More malignant tumors of the breast are more often ER and PR negative in both humans and dogs. Promising breast cancer biomarkers in both humans and canines are cancer-associated stroma (CAS), circulating tumor cells and tumor DNA (ctDNA), exosomes and miRNAs, and metabolites.

Breast cancer, screening and diagnostic tools: All you need to know

Breast cancer is one of the most frequent malignancies among women worldwide. Methods for screening and diagnosis allow health care professionals to provide personalized treatments that improve the outcome and survival. Scientists and physicians are working side-by-side to develop evidence-based guidelines and equipment to detect cancer earlier. However, the lack of comprehensive interdisciplinary information and understanding between biomedical, medical, and technology professionals makes innovation of new screening and diagnosis tools difficult. This critical review gathers, for the first time, information concerning normal breast and cancer biology, established and emerging methods for screening and diagnosis, staging and grading, molecular and genetic biomarkers. Our purpose is to address key interdisciplinary information about these methods for physicians and scientists. Only the multidisciplinary interaction and communication between scientists, health care professionals, technical experts and patients will lead to the development of better detection tools and methods for an improved screening and early diagnosis.

Evaluating Estrogen Receptor Immunohistochemistry on Cell Blocks From Breast Cancer Patients in a Low-Resource Setting

CONTEXT.—

Breast cancer biomarker assessment is critical in determining treatment and prognosis. In Tanzania, immunohistochemistry (IHC) is limited to surgical specimens and core biopsies. However, performing IHC on fine-needle aspiration biopsy cell blocks would offer numerous advantages.

OBJECTIVE.—

To compare the performance between estrogen receptor (ER) IHC performed at Muhimbili National Hospital (MNH) in Tanzania and ER IHC performed at University of California, San Francisco (UCSF), to demonstrate feasibility of performing IHC using cell blocks in Tanzania.

DESIGN.—

Patients with breast masses were recruited prospectively from the fine-needle aspiration biopsy clinic at MNH. Estrogen receptor IHC results on cell blocks, performed at both MNH and UCSF, and corresponding tissue blocks, performed at MNH, were compared to determine concordance.

RESULTS.—

Eighty-six cell blocks were evaluated by ER IHC at MNH, with 41 of 86 (47.7%) positive and 45 of 86 (52.3%) negative. Among 65 UCSF and MNH cell block pairs, overall ER IHC concordance was 93.8% (61 of 65) and positive concordance was 93.5% (29 of 31) (κ = 0.88, P > .99). Among 43 paired UCSF cell blocks and MNH tissue blocks, overall ER IHC concordance was 88.3% (38 of 43) and positive concordance was 90.5% (19 of 21) (κ = 0.77, P > .99). We compared 62 MNH cell block and tissue block pairs. Overall ER IHC concordance was 90.3% and positive concordance was 87.9% (κ = 0.81, P = .69).

CONCLUSIONS.—

Pairwise comparisons between ER IHC at MNH, on cell blocks and tissue blocks, with ER IHC at UCSF on cell blocks showed excellent concordance. We demonstrate that ER IHC on fine-needle aspiration biopsy specimens can be implemented in resource-constrained settings.

ERH overexpression is associated with decreased cell migration and invasion and a good prognosis in gastric cancer

Background

The enhancer of rudimentary homolog (ERH) protein is implicated in transcriptional regulation, cell cycle progression, and malignancy. We previously conducted a proteomics analysis using gastric cancer (GC) tissues and identified ERH as a biomarker candidate. The aim of this study was to investigate whether ERH may be useful as a prognostic marker for GC.

Methods

Surgically resected GC tissue specimens were obtained from 327 patients who underwent gastrectomy at Gyeongsang National University Hospital. Immunohistochemistry (IHC) was used to validate ERH as a prognostic marker in these tissues. SNU601 and MKN74 cells with siRNA-mediated knockdown of ERH expression and ERH-overexpressing SNU601 and MKN74 knock-in cells were used for analysis of ERH function.

Results

ERH was overexpressed in stomach cancer tissues compared with normal tissues according to proteomics analysis (n=29, P<0.01) of patient samples. Based on IHC, patients with tumors overexpressing ERH had lower T stage and lower TNM stage classifications, lower cancer recurrence rates and longer survival times than did patients with tumors showing low expression of ERH (P=0.04). In vitro, forced expression of ERH significantly decreased GC cell migration and invasion, and depletion of ERH triggered GC cell migration and invasion but had no effect on proliferation in vitro.

Conclusions

The findings from the present study show that ERH is associated with decreased cancer cell migration and invasion, suggesting that overexpression of ERH may serve as a marker of good prognosis for patients with GC.

A new approach to epithelial-mesenchymal transition diagnostics in epithelial tumors: double immunofluorescent staining and flow cytometry

A new method of double immunofluorescent staining for flow cytometry has been created to evaluate quantitative expression of mesenchymal protein vimentin only in epithelial cells of a solid tumor that is a mix of different origin cells. De novo vimentin expression is strongly associated with epithelial-mesenchymal transition and therefore is a metastatic potential marker of epithelial tumor cells. In comparison with semiquantitative available methods, the proposed one has several advantages, such as the accurate measurement of the marker's expression, and minimization of spatial and temporal tumor heterogeneity. Clinical validation of the method has revealed inverse correlation between the quantitative index of epithelial-mesenchymal transition level and progression-free survival using Kaplan-Meier curves and the COX proportional hazards ratio in 32 ovarian cancer patients.

Developing a routine lab test for absolute quantification of HER2 in FFPE breast cancer tissues using Quantitative Dot Blot (QDB) method

Developing immunoassay for absolute quantitation of protein biomarkers in Formalin Fixed Paraffin Embedded (FFPE) samples promises improved objectivity, consistency and accuracy in daily clinical practice. The feasibility of Quantitative Dot Blot (QDB) method for this purpose was explored in this study. We were able to measure HER2 protein levels using 0.5 µg/sample total protein lysate extracted from 2 × 5 µm FFPE slices absolutely and quantitatively using QDB method in 332 breast cancer FFPE samples. HER2 levels measured using two clinically validated antibodies for immunohistochemistry respectively were highly correlated (r = 0.963). We also achieved area under the curve (AUC) at 0.9998 ± 0.0002 (p < 0.0001, n = 224) with IHC analysis, and 0.9942 ± 0.0031 (p < 0.0001, n = 319) with combined results from IHC and Fluorescence in situ hybridization (FISH) analyses when analyzed with Receiver Operative Characteristics analysis (ROC) respectively. When the results were converted dichotomously with optimized cutoffs from ROC analyses, we achieved 99.5% concordance with IHC; and 96.9% with combined results from both IHC and FISH analyses. Therefore, we were able to demonstrate QDB method as the first immunoassay platform for absolute quantitation of protein biomarkers in FFPE samples to meet the need of daily clinical practice, especially for local laboratories or laboratories in developing countries.

Correlation of contrast-enhanced ultrasound features with prognostic factors in invasive ductal carcinomas of the breast

OBJECTIVES

To correlate contrast-enhanced ultrasound (CEUS) features with pathological prognostic factors of breast invasive ductal carcinomas (IDCs).

METHODS

169 patients who were admitted to our hospital with confirmed IDCs diagnosed between August 2017 and June 2019 were selected. CEUS indicators included the time of contrast agent entered the lesion, the degree of enhancement, the boundary of the lesion, whether there was perfusion defect and nourishing blood vessels, and etc. These parameters correlated with traditional prognostic factors (tumour size, histological grade, axillary lymph node status) and immunohistochemical biomarkers (ER, PR, c-erbB-2, Ki-67, and TOPO-II).

RESULTS

Perfusion defects after enhancement were predictive factors of PR negative expression (r = - 0.318, OR = 0.239) and TOPO-II overexpression (r = 0.284, OR = 3.577). Centripetal enhancement was negatively correlated with ER expression (r = - 0.350, OR = 0.246). The lesions with a larger range after enhancement than the conventional ultrasound had a higher histological grade (r = 0.215). Perfusion defects were positively correlated with lymph node metastasis (r = 0.221) and negatively correlated with the expression of ER and PR (r = - 0.342, r = - 0.318).

CONCLUSIONS

Contrast-enhanced ultrasound features of IDCs have a certain correlation with pathological prognostic factors, which is conducive in assessing the prognosis of these patients.

Triple Negative Breast Cancer Detection Using LC-MS/MS Lipidomic Profiling

Breast cancer (BC) is a heterogeneous malignancy that is responsible for a great portion of female cancer cases and cancer-related deaths in the United States. In comparison to other major BC subtypes, triple negative breast cancer (TNBC) presents with a relatively low survival rate and a high rate of metastasis. This has led to a strong, though largely unmet, need for more sensitive and specific methods of early-stage TNBC (ES-TNBC) detection to combat its high-grade pathology and relatively low survival rate. The current study employs a liquid chromatography-tandem mass spectrometry assay capable of targeted, highly specific, and sensitive detection of lipids to propose two diagnostic biomarker panels for TNBC/ES-TNBC. Using this approach, 110 lipids were reliably detected in 166 human plasma samples, 45 controls, and 121 BC (96 non-TNBC and 25 TNBC) subjects. Univariate and multivariate analyses allowed the construction and application of a 19-lipid biomarker panel capable of distinguishing TNBC (and ES-TNBC) from controls, as well as a 5-lipid biomarker panel capable of differentiating TNBC from non-TNBC and ES-TNBC from ES-non-TNBC. Receiver operating characteristic curves with notable classification performances were generated from the biomarker panels according to their orthogonal partial least-squares discrimination analysis models. TNBC was distinguished from controls with an area under the receiving operating characteristic curve (AUROC) = 0.93, sensitivity = 0.96, and specificity = 0.76 and ES-TNBC from controls with an AUROC = 0.96, sensitivity = 0.95, and specificity = 0.89. TNBC was differentiated from non-TNBC with an AUROC = 0.88, sensitivity = 0.88, and specificity = 0.79 and ES-TNBC from ES-non-TNBC with an AUROC = 0.95, sensitivity = 0.95, and specificity = 0.87. A pathway enrichment analysis between TNBC and controls also revealed significant disturbances in choline metabolism, sphingolipid signaling, and glycerophospholipid metabolism. To the best of our knowledge, this is the first study to propose a diagnostic lipid biomarker panel for TNBC detection. All raw mass spectrometry data have been deposited to MassIVE (dataset identifier MSV000085324).

Predicting Effects of Clinicopathological Variables on Her2 Gene Amplification by Chromogenic in situ Hybridization (CISH) in IHC Her2 (2+) Breast Cancer Patients; A Study from Iran

Background & Objective

The her2 amplification plays an important role in breast cancer management. Therefore, there is a need for using supplementary molecular methods in IHC equivocal cases. Present study has been conducted to determine the effects of clinicopathological variables on her2 gene amplification by chromogenic in situ hybridization (CISH) in IHC Her2 (2+) breast cancer individuals.

Methods

A cross-sectional study was conducted in Zaferanyeh Laboratory collaborated with Shahid Beheshti University of Medical Sciences (Tehran-Iran; 2015-2018). All pathological data related invasive breast cancer patients with equivocal IHC results were included. CISH method was performed as a supplementary technique. The associations between histopathologic variables, status of Ki-67 index, progesterone and estrogen receptors (PR & ER) with her2 amplification by CISH were investigated and analyzed. The level of significance was considered as P-value < 0.05.

Results

Totally, 239 patients with mean age of 53.2 years were studied. CISH identified her2 gene amplification in 51 subjects (21.3%). The type of tumor (invasive ductal carcinoma), the tumor grade, and the value of Ki-67 index were directly correlated with her2 amplification. Significant negative associations were also observed between CISH results and ER and PR expression.

Conclusion

As her2 gene amplification was identified in 21.3% of invasive breast cancer patients with equivocal IHC results, it is supposed that applying CISH method may consider as a potentially valuable supplementary method. Results have also shown that higher grades of tumor, invasive ductal carcinoma, absences of hormone receptors and high Ki-67 index significantly correlated with the her2 amplification.

Association between low estrogen receptor positive breast cancer and staining performance

Estrogen receptor (ER) expression in breast carcinomas, determined by immunohistochemistry, indicates statistically significant benefit to endocrine therapy in patients with tumors expressing ER in ≥1% of tumor cells. Rare cases with low ER expression (1-10%) lead to the dilemma of treating these tumors as ER positive or negative. We hypothesize that low ER positive result from poor staining performance and that we may detect this artefact by assessing the average dynamic range of normal ducts adjacent to low ER positive tumors. Using quantitative tools, we compare the dynamic range of normal background ER expression in patients with low (1-10%) ER tumors to dynamic range of ER expression in normal epithelium from control patient populations, to determine if low ER cases are accompanied by decreased dynamic range. Low ER cases were infrequent (1% of invasive breast carcinomas). Twenty-one cases with low ER staining and two control cohorts, including a tissue microarray (TMA) of 10 benign breast sections and a group of 34 control breast carcinomas (reported as ER negative or >10% ER positive) with normal background epithelium, were digitally scanned. QuPath was utilized to quantify ER staining for each cell as the mean optical density of nuclear DAB staining. The dynamic range of ER expression in normal epithelium surrounding low ER tumors was significantly lower (range 2-240, median 16.5) than that of the benign epithelium in the control tumors (range 3-475, median 30.8; p < 0.001) and benign TMA sections (range 38-212, median 114; p < 0.001) suggesting inconsistent stainer performance.

Droplet digital polymerase chain reaction offers an improvisation over conventional immunohistochemistry and fluorescent in situ hybridization for ascertaining Her2 status of breast cancer

Background

Droplet digital polymerase chain reaction (DDPCR) is a recent modality for detecting Her2 expression which is quantitative, cheaper, easier to standardize, and free from interobserver variation.

Purpose

The purpose of this study is to incorporate DDPCR in the current diagnostic paradigm with clinical benefit.

Materials and Methods

Fifty-four consecutive patients were tested by immunohistochemistry (IHC), fluorescent in situ hybridization (FISH), and DDPCR. With FISH result as gold standard, receiver operating characteristic curves for DDPCR ratio were analyzed to label Her2-negative, equivocal, and positive cases as DDPCR score 1, 2, and 3, respectively. Proportion of patients labeled unequivocally as Her2 positive or negative was defined to have "clinically benefitted" from the test. Drawing parallel to inter-relationships between DDPCR, IHC, and FISH in the test cohort, four diagnostic pathways were defined - (1) initial IHC followed by FISH, (2) initial DDPCR followed by FISH, (3) initial IHC followed by DDPCR followed by FISH, and (4) initial DDPCR followed by IHC followed by FISH.

Results

Clinical benefit of DDPCR as an initial test in the test cohort was 57%, while it was 65% if used as a second-line test among those with an initial inconclusive IHC result. Sensitivity analysis in the simulation cohort revealed that if DDPCR cost was ≤0.6 times the cost of IHC, then a three-step pathway with DDPCR upfront would near certainly prove most cost beneficial. If DDPCR cost was >0.6 but ≤2 times the cost of IHC, then a three-step pathway with DDPCR as second-line test had a higher probability to prove most cost beneficial. If DDPCR cost was >2 times the cost of IHC, then conventional pathway had a higher probability to prove most cost-effective.

Conclusion

Incorporating DDPCR in the current clinical diagnostic paradigm has the potential to improve its cost-effectiveness and benefit.

Aberrant methylation of yes-associated protein (YAP1) as a potential biomarker in breast cancer

Background

Breast cancer (BC) represents the most prevalent malignancy among women, and it is characterized by high mortality especially in late stages. BC tumorigenesis was linked to epigenetic alterations namely methylation. Yes-associated protein (YAP1) is the leading downstream effector of the Hippo pathway. It may enhance or inhibit oncogenesis based on the tissue involved.

Aim

This case-control study aimed to analyze the methylation degree of promoter region of YAP1 gene in BC patients by applying methylation-specific polymerase chain reaction (MSP) analysis.

Methods

Genomic deoxyribonucleic acid (DNA) was isolated from 50 paired tumor and adjacent noncancerous breast tissue samples and subjected to bisulfite conversion. Methylation condition of YAP1 gene was studied by MSP and evaluated as a possible biomarker for diagnosing BC and its differentiation from corresponding normal tissues. We also correlated the aberrant methylation with clinicopathological criteria.

Results

Increased methylation of the YAP1 gene promoter region in BC tumor tissue was detected in 68% of the studied BC tissue samples. There was a significant change in the frequency of YAP1 methylated genotype between breast tumor tissues compared to that in adjacent non-cancerous tissue (p < 0.001). YAP1 can discriminate early from late-stage BC with a sensitivity of 96.88% and specificity of 83.33%.

Conclusions

Gene analysis of YAP1 using conventional MSP in tissue specimens can be considered a possible biomarker to distinguish BC from normal breast tissue as well as between early- and late-stage BC.

Therapeutic applications of multifunctional nanozymes

Nanozymes, which are functional nanomaterials with enzyme-like characteristics, have emerged as a highly-stable and low-cost alternative to natural enzymes. Apart from overcoming the limitations of natural enzymes (e.g., high cost, low stability or complex production), nanozymes are also equipped with the unique intrinsic properties of nanomaterials such as magnetism, luminescence or near infrared absorbance. Therefore, the development of nanozymes exhibiting additional functions to their catalytic activity has opened up new opportunities and applications within the biomedical field. To highlight the progress in the field, this review summarizes the novel applications of multifunctional nanozymes in various biomedical-related fields ranging from cancer diagnosis, cancer and antibacterial therapy to regenerative medicine. Future challenges and perspectives that may advance nanozyme research are also discussed at the end of the review.

Suboptimal concordance in testing and retesting results of triple-negative breast carcinoma cases among laboratories: one institution experience

Background

Triple-negative breast carcinoma (TNBC) patients do not benefit from hormone- or human epidermal growth factor receptor 2- (HER2-) targeted therapies. Accurate testing is pivotal for these patients.

Methods

TNBC cases that were retested at our institution during a 3-year period were evaluated for concordance rates in estrogen (ER) and progesterone (PR) receptor and HER2 results.

Results

We found 19 (22%) discrepancies (13 major/6 minor) among 86 cases. Minor discrepancies were in HER2 changes by immunohistochemistry, and all cases were demonstrated to be negative by and dual in situ hybridization. All major discrepancies were in ER/PR expression changes. In only 2 cases the treatment changed based on repeated results and/or patient history.

Conclusions

Discrepancies in prognostic/predictive testing continue to be frequent despite rigorous regulations. However, since for the majority of patients in our setting, the treatment plan did not change, reflex retesting for TNBC has been deemed unnecessary in our institution.

Artificial Intelligence Algorithms to Assess Hormonal Status From Tissue Microarrays in Patients With Breast Cancer

IMPORTANCE

Immunohistochemistry (IHC) is the most widely used assay for identification of molecular biomarkers. However, IHC is time consuming and costly, depends on tissue-handling protocols, and relies on pathologists' subjective interpretation. Image analysis by machine learning is gaining ground for various applications in pathology but has not been proposed to replace chemical-based assays for molecular detection.

OBJECTIVE

To assess the prediction feasibility of molecular expression of biomarkers in cancer tissues, relying only on tissue architecture as seen in digitized hematoxylin-eosin (H&E)-stained specimens.

DESIGN, SETTING, AND PARTICIPANTS

This single-institution retrospective diagnostic study assessed the breast cancer tissue microarrays library of patients from Vancouver General Hospital, British Columbia, Canada. The study and analysis were conducted from July 1, 2015, through July 1, 2018. A machine learning method, termed morphological-based molecular profiling (MBMP), was developed. Logistic regression was used to explore correlations between histomorphology and biomarker expression, and a deep convolutional neural network was used to predict the biomarker expression in examined tissues.

MAIN OUTCOMES AND MEASURES

Positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristics curve measures of MBMP for assessment of molecular biomarkers.

RESULTS

The database consisted of 20 600 digitized, publicly available H&E-stained sections of 5356 patients with breast cancer from 2 cohorts. The median age at diagnosis was 61 years for cohort 1 (412 patients) and 62 years for cohort 2 (4944 patients), and the median follow-up was 12.0 years and 12.4 years, respectively. Tissue histomorphology was significantly correlated with the molecular expression of all 19 biomarkers assayed, including estrogen receptor (ER), progesterone receptor (PR), and ERBB2 (formerly HER2). Expression of ER was predicted for 105 of 207 validation patients in cohort 1 (50.7%) and 1059 of 2046 validation patients in cohort 2 (51.8%), with PPVs of 97% and 98%, respectively, NPVs of 68% and 76%, respectively, and accuracy of 91% and 92%, respectively, which were noninferior to traditional IHC (PPV, 91%-98%; NPV, 51%-78%; and accuracy, 81%-90%). Diagnostic accuracy improved given more data. Morphological analysis of patients with ER-negative/PR-positive status by IHC revealed resemblance to patients with ER-positive status (Bhattacharyya distance, 0.03) and not those with ER-negative/PR-negative status (Bhattacharyya distance, 0.25). This suggests a false-negative IHC finding and warrants antihormonal therapy for these patients.

CONCLUSIONS AND RELEVANCE

For at least half of the patients in this study, MBMP appeared to predict biomarker expression with noninferiority to IHC. Results suggest that prediction accuracy is likely to improve as data used for training expand. Morphological-based molecular profiling could be used as a general approach for mass-scale molecular profiling based on digitized H&E-stained images, allowing quick, accurate, and inexpensive methods for simultaneous profiling of multiple biomarkers in cancer tissues.

The Impact of Partial Weak Staining in Normal Breast Epithelium on the Reliability of Immunohistochemistry Results in HercepTest-positive Breast Cancer

INTRODUCTION

Although normal epithelial cells do not show human epidermal growth factor receptor-2 (HER2) gene amplification and should lack membrane staining by HER2 immunohistochemistry (IHC), HER2 staining in benign breast epithelium is occasionally encountered. The significance of this occurrence has not yet been adequately studied, and its associated American Society of Clinical Oncology/College of American Pathologists recommendations are vague. Our objective is to assess the correlation between HER2 IHC 3+ breast cancer cases with normal epithelium staining (NES) and their corresponding fluorescence in situ hybridization (FISH) results, and to suggest recommendations for interpretation.

MATERIALS AND METHODS

A total of 154 breast cancer cases with HER2 IHC 3+ were reviewed. NES, along with other clinicopathologic characteristics, were recorded. NES was scored as present or absent. All study cases were sent for FISH testing. All cases, and particularly those that showed false positivity for IHC (positive IHC, negative FISH) were examined for NES.

RESULTS

Of the 154 cases, 146 cases were FISH-positive (94.8%) and 2 failed FISH testing (1.3%). Conversely, 22% (34/154) of the cases showed NES for HER2. Of these 34 cases, 23 (67%) were FISH-amplified, 9 (26%) were FISH not amplified, and 2 failed FISH testing. Notably, all of the false-positive (FISH-negative) breast cancer cases showed some degree of positivity in normal breast epithelium.

CONCLUSIONS

Our findings, though descriptive, show a very strong association between NES and false-positive HER2 IHC. This confirms the need to carefully evaluate IHC-positive breast cancers for NES, and to have a low threshold for confirmatory testing by FISH.