Analytical Validation of a Highly Quantitative, Sensitive, Accurate, and Reproducible Assay (HERmark) for the Measurement of HER2 Total Protein and HER2 Homodimers in FFPE Breast Cancer Tumor Specimens

Artificial intelligence for assisted HER2 immunohistochemistry evaluation of breast cancer: A systematic review and meta-analysis

Accurate assessment of HER2 expression in tumor tissue is crucial for determining HER2-targeted treatment options. Nevertheless, pathologists' assessments of HER2 status are less objective than automated, computer-based evaluations. Artificial Intelligence (AI) promises enhanced accuracy and reproducibility in HER2 interpretation. This study aimed to systematically evaluate current AI algorithms for HER2 immunohistochemical diagnosis, offering insights to guide the development of more adaptable algorithms in response to evolving HER2 assessment practices. A comprehensive data search of the PubMed, Embase, Cochrane, and Web of Science databases was conducted using a combination of subject terms and free text. A total of 4994 computational pathology articles published from inception to September 2023 identifying HER2 expression in breast cancer were retrieved. After applying predefined inclusion and exclusion criteria, seven studies were selected. These seven studies comprised 6867 HER2 identification tasks, with two studies employing the HER2-CONNECT algorithm, two using the CNN algorithm, one with the multi-class logistic regression algorithm, and two using the HER2 4B5 algorithm. AI's sensitivity and specificity for distinguishing HER2 0/1+ were 0.98 [0.92-0.99] and 0.92 [0.80-0.97] respectively. For distinguishing HER2 2+, the sensitivity and specificity were 0.78 [0.50-0.92] and 0.98 [0.93-0.99], respectively. For HER2 3+ distinction, AI exhibited a sensitivity of 0.99 [0.98-1.00] and specificity of 0.99 [0.97-1.00]. Furthermore, due to the lack of HER2-targeted therapies for HER2-negative patients in the past, pathologists may have neglected to distinguish between HER2 0 and 1+, leaving room for improvement in the performance of artificial intelligence (AI) in this differentiation. AI excels in automating the assessment of HER2 immunohistochemistry, showing promising results despite slight variations in performance across different HER2 status. While incorporating AI algorithms into the pathology workflow for HER2 assessment poses challenges in standardization, application patterns, and ethical considerations, ongoing advancements suggest its potential as a widely effective tool for pathologists in clinical practice in the near future.

Human Blood Serum Counteracts EGFR/HER2-Targeted Drug Lapatinib Impact on Squamous Carcinoma SK-BR-3 Cell Growth and Gene Expression

Lapatinib is a targeted therapeutic inhibiting HER2 and EGFR proteins. It is used for the therapy of HER2-positive breast cancer, although not all the patients respond to it. Using human blood serum samples from 14 female donors (separately taken or combined), we found that human blood serum dramatically abolishes the lapatinib-mediated inhibition of growth of the human breast squamous carcinoma SK-BR-3 cell line. This antagonism between lapatinib and human serum was associated with cancelation of the drug induced G1/S cell cycle transition arrest. RNA sequencing revealed 308 differentially expressed genes in the presence of lapatinib. Remarkably, when combined with lapatinib, human blood serum showed the capacity of restoring both the rate of cell growth, and the expression of 96.1% of the genes expression of which were altered by the lapatinib treatment alone. Co-administration of EGF with lapatinib also restores the cell growth and cancels alteration of expression of 95.8% of the genes specific to lapatinib treatment of SK-BR-3 cells. Differential gene expression analysis also showed that in the presence of human serum or EGF, lapatinib was unable to inhibit the Toll-Like Receptor signaling pathway and alter expression of genes linked to the Gene Ontology term of Focal adhesion.

Application of quantitative protein mass spectrometric data in the early predictive analysis of membrane-bound target engagement by monoclonal antibodies

Model-informed drug discovery advocates the use of mathematical modeling and simulation for improved efficacy in drug discovery. In the case of monoclonal antibodies (mAbs) against cell membrane antigens, this requires quantitative insight into the target tissue concentration levels. Protein mass spectrometry data are often available but the values are expressed in relative, rather than in molar concentration units that are easier to incorporate into pharmacokinetic models. Here, we present an empirical correlation that converts the parts per million (ppm) concentrations in the PaxDb database to their molar equivalents that are more suitable for pharmacokinetic modeling. We evaluate the insight afforded to target tissue distribution by analyzing the likely tumor-targeting accuracy of mAbs recognizing either epidermal growth factor receptor or its homolog HER2. Surprisingly, the predicted tissue concentrations of both these targets exceed the Kd values of their respective therapeutic mAbs. Physiologically based pharmacokinetic (PBPK) modeling indicates that in these conditions only about 0.05% of the dosed mAb is likely to reach the solid tumor target cells. The rest of the dose is eliminated in healthy tissues via both nonspecific and target-mediated processes. The presented approach allows evaluation of the interplay between the target expression level in different tissues that determines the overall pharmacokinetic properties of the drug and the fraction that reaches the cells of interest. This methodology can help to evaluate the efficacy and safety properties of novel drugs, especially if the off-target cell degradation has cytotoxic outcomes, as in the case of antibody-drug conjugates.

Application of population physiologically based pharmacokinetic modelling to optimize target expression and clearance mechanisms of therapeutic monoclonal antibodies

AIMS

To use population physiologically based pharmacokinetic (PopPBPK) modelling to optimize target expression, kinetics and clearance of HER1/2 directed therapeutic monoclonal antibodies (mAbs). Thus, to propose a general workflow of PopPBPK modelling and its application in clinical pharmacology.

METHODS

Full PBPK model of pertuzumab (PTZ) was developed in patient population using Simcyp V21R1 incorporating mechanistic targeted-mediated drug disposition process by fitting known clinical PK and sparse receptor proteomics data to optimize target expression and kinetics of HER2 receptor. Trastuzumab (TTZ) PBPK modelling was used to validate the optimized HER2 target. Additionally, the simulator was also used to develop a full PBPK model for the HER1-directed mAb cetuximab (CTX) to assess the underlying targeted-mediated drug disposition-independent elimination mechanisms.

RESULTS

HER2 final parameterisation coming from the PBPK modelling of PTZ was successfully cross validated through PBPK modelling of TTZ with average fold error (AFE), absolute AFE and percent prediction error values for area under the concentration-time curve (AUC) and maximum plasma concentration (Cmax ) of 1.13, 1.16 and 16, and 1.01, 1.07 and 7, respectively. CTX PBPK model performance was validated after the incorporation of an additional systemic clearance of 0.033 L/h as AFE and absolute AFE showed an acceptable predictive power of AUC and Cmax with percent prediction error of 13% for AUC and 10% for Cmax .

CONCLUSIONS

Optimisation of both system and drug related parameters were performed through PBPK modelling to improve model performance of therapeutic mAbs (PTZ, TTZ and CTX). General workflow was proposed to develop and apply PopPBPK to support clinical development of mAbs targeting same receptor.

The HER2-low revolution in breast oncology: steps forward and emerging challenges

Approximately half of breast cancers (BCs), historically categorized as human epidermal growth factor receptor 2 (HER2)-negative, have low expression of HER2 defined as an immunohistochemical (IHC) score of 1+ or 2+ with negative in situ hybridization. Retrospective evidence suggest that HER2-low BC does not represent a distinct subtype from a biological and prognostic perspective. Nonetheless, it currently constitutes an essential biomarker to guide treatment selection and its introduction has led to reconsidering the binary classification of HER2 status according to which only patients with HER2-positive BC were thought to derive benefit from anti-HER2 therapies. Trastuzumab deruxtecan has recently been approved by the U.S. Food and Drug Administration for the treatment of patients with HER2-low metastatic BC based on the results of the DESTINY-Breast04 phase III trial, and other antibody-drug conjugates (ADCs) targeting HER2 are showing promising results. Treatment paradigms for both triple-negative and hormone receptor-positive BCs exhibiting HER2-low expression are thus rapidly evolving. Given its therapeutic implications, it is essential to accurately recognize the level of HER2 expression, and the development of more sensitive and reliable methods for HER2 testing and scoring is warranted, especially since the minimum threshold of HER2 expression required for T-DXd efficacy is currently under investigation. Given the signs of activity of T-DXd even in patients with HER2-0 (IHC 0) disease, an evolution in the way we define HER2-low is anticipated. Considering the expansion of the therapeutic armamentarium for BC patients, with several ADCs approaching the clinic, research efforts are needed to clarify whether the expression level of targets can enrich for responders to a given ADC as well as to understand mechanisms of resistance with the goal of optimizing the sequencing of ADCs.

Novel markers in breast pathology

Breast pathology is an ever-expanding database of information which includes markers, or biomarkers, that detect or help treat the disease as prognostic or predictive information. This review focuses on these aspects of biomarkers which are grounded in immunohistochemistry, liquid biopsies and next-generation sequencing.

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.

Water-Dispersible Carboxymethyl Dextran-Coated Melamine Nanoparticles for Biosensing Applications

In this study, we developed a simple method for preparing highly dispersed, stable, and streptavidin (SA)-functionalized carboxymethyl dextran (CMD)-coated melamine nanoparticles (MNPs) in an aqueous buffer at neutral pH. Dynamic light scattering (DLS) revealed the agglomeration of MNPs in an aqueous buffer at neutral pH. When CMD, N-hydroxysuccinimide (NHS), and 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) were simultaneously mixed with the MNPs, CMD was bound to the MNPs, promoting their dispersibility. Preparation of SA-CMD-MNPs was accomplished simply by adding SA solution to the CMD-MNPs. The amount of SA bound to the CMD-MNPs was quantified by the bicinchoninic assay, and the amount of SA molecules bound to each CMD-MNP was 417 ± 4. SA-CMD-MNPs exhibited high dispersity (polydispersity index = 0.058) in a neutral phosphate buffer and maintained it for 182 days with dispersion using a probe sonicator (5 s) before DLS characterization. The performance of the SA-CMD-MNPs in biosensing was evaluated by immunohistochemistry, which revealed that the nanoparticles could specifically stain MCF-7 cells derived from breast cancer cells with low HER2 expression. This study provides an effective method for synthesizing highly dispersible nanoparticles for biosensing.

Targeted Approaches to HER2-Low Breast Cancer: Current Practice and Future Directions

Simple Summary

HER2-low breast cancer (BC) accounts for more than half of breast cancer patients. Anti-HER2 therapy has been ineffective in HER2-low BC, for which palliative chemotherapy is the main treatment modality. The definitive efficacy of T-Dxd in HER2-low BC breaks previous treatment strategies, which will redefine HER2-low and thus reshape anti-HER2 therapy. This review summarizes detection technologies and novel agents for HER2-low BC, and explores their possible role in future clinics, to provide ideas for the diagnosis and treatment of HER2-low BC.

Abstract

HER2-low breast cancer (BC) has a poor prognosis, making the development of more suitable treatment an unmet clinical need. While chemotherapy is the main method of treatment for HER2-low BC, not all patients benefit from it. Antineoplastic therapy without chemotherapy has shown promise in clinical trials and is being explored further. As quantitative detection techniques become more advanced, they assist in better defining the expression level of HER2 and in guiding the development of targeted therapies, which include directly targeting HER2 receptors on the cell surface, targeting HER2-related intracellular signaling pathways and targeting the immune microenvironment. A new anti-HER2 antibody-drug conjugate called T-DM1 has been successfully tested and found to be highly effective in clinical trials. With this progress, it could eventually be transformed from a disease without a defined therapeutic target into a disease with a defined therapeutic molecular target. Furthermore, efforts are being made to compare the sequencing and combination of chemotherapy, endocrine therapy, and HER2-targeted therapy to improve prognosis to customize the subtype of HER2 low expression precision treatment regimens. In this review, we summarize the current and upcoming treatment strategies, to achieve accurate management of HER2-low BC.

HER2-low-positive breast cancer: evolution from primary tumor to residual disease after neoadjuvant treatment

Approximately a half of breast tumors classified as HER2-negative exhibit HER2-low-positive expression. We recently described a high instability of HER2-low-positive expression from primary breast cancer (BC) to relapse. Previous studies reporting discordance in HER2 status between baseline biopsy and residual disease (RD) in patients undergoing neoadjuvant treatment did not include the HER2-low-positive category. The aim of this study is to track the evolution of HER2-low-positive expression from primary BC to RD after neoadjuvant treatment. Patients undergoing neoadjuvant treatment with available baseline tumor tissue and matched samples of RD (in case of no pCR) were included. HER2-negative cases were sub-classified as HER2-0 or HER2-low-positive (IHC 1+ or 2+ and ISH negative). Four-hundred forty-six patients were included. Primary BC phenotype was: HR-positive/HER2-negative 23.5%, triple-negative (TN) 35%, HER2-positive 41.5%. HER2-low-positive cases were 55.6% of the HER2-negative cohort and were significantly enriched in the HR-positive/HER2-negative vs. TN subgroup (68.6% vs. 46.8%, p = 0.001 χ2 test). In all, 35.3% of non-pCR patients (n = 291) had a HER2-low-positive expression on RD. The overall rate of HER2 expression discordance was 26.4%, mostly driven by HER2-negative cases converting either from (14.8%) or to (8.9%) HER2-low-positive phenotype. Among HR-positive/HER2-negative patients with HER2-low-positive expression on RD, 32.0% and 57.1% had an estimated high risk of relapse according to the residual proliferative cancer burden and CPS-EG score, respectively. In conclusion, HER2-low-positive expression showed high instability from primary BC to RD after neoadjuvant treatment. HER2-low-positive expression on RD may guide personalized adjuvant treatment for high-risk patients in the context of clinical trials with novel anti-HER2 antibody-drug conjugates.

Evolution of HER2-low expression from primary to recurrent breast cancer

About a half of HER2-negative breast cancer (BC) show HER2-low expression that can be targeted by new antibody-drug conjugates. The main aim of this study is to describe the evolution of HER2 expression from primary BC to relapse by including HER2-low category in both primary and recurrent BC samples. Patients with matched primary and relapse BC samples were included. HER2 was evaluated according to ASCO/CAP recommendations in place at the time of diagnosis. A cutoff of >10% cells staining for HER2-positivity was applied. HER2-negative cases were sub-classified as HER2-low (IHC = 1 + /2+ and ISH not amplified), or HER2-0 (IHC-0). 547 patients were included. The proportion of HER2-low cases was 34.2% on the primary tumor and 37.3% on the relapse samples. Among HER2-negative cases, HER2-low status was more frequent in HR-positive vs triple-negative tumors (47.3% vs 35.4% on primary tumor samples, 53.8% vs 36.2% on relapse samples). The overall rate of HER2 discordance was 38.0%, mostly represented by HER2-0 switching to HER2-low (15%) and HER2-low switching to HER2-0 (14%). Among patients with a primary HER2-negative tumor, the rate of HER2 discordance was higher in HR-positive/HER2-negative vs triple-negative cases (45.5% vs 36.7% p = 0.170). This difference was mostly driven by cases switching from HER2-0 to HER2-low. HER2-low expression is highly unstable during disease evolution. Relapse biopsy in case of a primary HER2-0 tumor may open new therapeutic opportunities in a relevant proportion of patients.

Quantification of HER1, HER2 and HER3 by time-resolved Förster resonance energy transfer in FFPE triple-negative breast cancer samples

Background

Triple-negative breast cancer (TNBC) has a worse prognosis compared with other breast cancer subtypes, and biomarkers to identify patients at high risk of recurrence are needed. Here, we investigated the expression of human epidermal receptor (HER) family members in TNBC and evaluated their potential as biomarkers of recurrence.

Methods

We developed Time Resolved-Förster Resonance Energy Transfer (TR-FRET) assays to quantify HER1, HER2 and HER3 in formalin-fixed paraffin-embedded (FFPE) tumour tissues. After assessing the performance and precision of our assays, we quantified HER protein expression in 51 TNBC specimens, and investigated the association of their expression with relapse-free survival.

Results

The assays were quantitative, accurate, and robust. In TNBC specimens, HER1 levels ranged from ≈4000 to more than 2 million receptors per cell, whereas HER2 levels varied from ≈1000 to 60,000 receptors per cell. HER3 expression was very low (less than 5500 receptors per cell in all samples). Moderate HER2 expression was significantly associated with higher risk of recurrence (HR = 3.93; P = 0.003).

Conclusions

Our TR-FRET assays accurately quantify HER1, HER2 and HER3 in FFPE breast tumour specimens. Moderate HER2 expression may represent a novel prognostic marker in patients with TNBC.

A novel detection methodology for HER2 protein quantitation in formalin-fixed, paraffin embedded clinical samples using fluorescent nanoparticles: an analytical and clinical validation study

BACKGROUND

Clinical assays for the assessment of the human epidermal growth factor receptor-2 (HER2) status in breast cancer include immunohistochemistry (IHC) and in situ hybridization (ISH), both of which have limitations. Recent studies have suggested that a more quantitative approach to the measurement of HER2 protein expression may improve specificity in selecting patients for HER-2 targeted therapy. In the current study, we have used HER2 expression in breast cancer cell lines and clinical samples as a model to explore the potential utility of a novel immunodetection technique, using streptavidin coated Phosphor Integrated Dot fluorescent nanoparticles (PID), which can be quantitatively measured using computer analysis.

METHODS

The expression of HER2 protein in cell lines was evaluated with antibody-binding capacity using fluorescence-activated cell sorting (FACS) for comparison with PID measurements to test for correlations with existing quantitative protein analysis methodologies. Various other analytic validation tests were also performed, including accuracy, precision, sensitivity, robustness and reproducibility. A methods comparison study investigated correlations between PID versus IHC and ISH in clinical samples. Lastly, we measured HER2 protein expression using PID in the pretreatment biopsies from 34 HER2-positive carcinomas that had undergone neoadjuvant trastuzumab-based chemotherapy.

RESULTS

In the analytic validation, PID HER2 measurements showed a strong linear correlation with FACS analysis in breast cell lines, and demonstrated significant correlations with all aspects of precision, sensitivity, robustness and reproducibility. PID also showed strong correlations with conventional HER2 testing methodologies (IHC and ISH). In the neoadjuvant study, patients with a pathologic complete response (pCR) had a significantly higher PID score compared with patients who did not achieve a pCR (p = 0.011), and was significantly correlated to residual cancer burden (RCB) class (p = 0.026, R² = 0.9975).

CONCLUSIONS

Analytic testing of PID showed that it may be a viable testing methodology that could offer advantages over other experimental or conventional biomarker diagnostic methodologies. Our data also suggests that PID quantitation of HER2 protein may offer an improvement over conventional HER2 testing in the selection of patients who will be the most likely to benefit from HER2-targeted therapy. Further studies with a larger cohort are warranted.

Breast carcinomas with low amplified/equivocal HER2 by Ish: potential supporting role of multiplex ligation-dependent probe amplification

BACKGROUND

This is a retrospective cross sectional study aimed to verify whether Multiplex Ligation-dependent Probe Amplification (MLPA), a quantitative molecular assay, may represent a valuable reflex test in breast cancer with equivocal HER2 expression by immunohistochemistry and HER2 gene signals/nucleus (s/n) ranging between 4.0 and 5.9 by in situ hybridization.

METHODS

A series of 170 breast carcinomas scored as 2+ for HER2 expression by immunohistochemistry, were selected from our files and analyzed in parallel by silver in situ hybridization and by MLPA. According to ASCO-CAP 2013 guidelines, 54/170 tumors, displaying 4.0-5.9 HER2 gene s/n, were defined as low amplified (ratio ≥ 2) or equivocal (ratio < 2) on the basis of centromere enumeration probe 17 (CEP17) status. An independent set of 108 score 2+ breast cancers represented the external validation set. Concordance between the two techniques was assessed through the use of Cohen's K statistic.

RESULTS

A concordance rate of 78.2% (Cohen's K statistic: 0,548 95% CI:[0,419-0,677]) between in situ hybridization and MLPA was found in the whole series of 170 cases and of 55.5% (Cohen's K statistic: -0,043 95% CI:[-0,271-0,184]) in the 54 tumors presenting 4.0-5.9 HER2 gene s/n. By MLPA, we found HER2 amplification or gain in 14% of the 21 BC presenting a disomic status and in 18% of the 33 BC presenting a CEP17 > 2.0. These data were further confirmed in the external validation set. Interestingly, the 54 low amplified/equivocal breast carcinomas presented a frequency of hormonal receptor positivity significantly higher than that observed in the amplified tumors and similar to the non-amplified one (p = 0.016 for estrogen receptor and p = 0.001 for progesterone receptor).

CONCLUSIONS

To avoid to offer patients an ineffective therapy, HER2 status should be studied more thoroughly in low amplified and equivocal cases which can have lower response rates and shorter time to progression to trastuzumab. In this context, our data indicate that MLPA may be a reliable, objective supporting test in selecting HER2 positive breast cancer patients.

Role of HER2-Related Biomarkers (HER2, p95HER2, HER3, PTEN, and PIK3CA) in the Efficacy of Lapatinib plus Capecitabine in HER2-Positive Advanced Breast Cancer Refractory to Trastuzumab

OBJECTIVE

The aim of this study was to investigate the correlation between human epidermal growth factor receptor 2 (HER2)-related biomarkers and the treatment outcomes using lapatinib plus capecitabine (LC) and to evaluate the influence of the estrogen receptor (ER) status in trastuzumab-refractory HER2-positive advanced breast cancer.

METHOD

Eighty patients were enrolled in this study. Total HER2, p95HER2, and total HER3 expression were quantified using the VeraTag assays. PTEN (phosphatase and tensin homolog) and p95 expression was evaluated using immunohistochemistry and PIK3CA mutation using direct sequencing.

RESULTS

The response rate to LC was 30%, clinical benefit rate was 51.3%, and the median progression-free survival (PFS) was 174.5 days. ER negativity significantly correlated with higher HER2 and p95HER2. The lower HER2 and PIK3CA mutations were often observed in the nonresponders. A high p95HER2 expression correlated with longer PFS especially in the high HER2- and ER-positive cases. Patients without the PIK3CA mutation showed longer PFS in the same subset. Overall survival after LC significantly correlated with the number of recurrence organs.

CONCLUSION

LC therapy is effective in trastuzumab-refractory HER2-positive breast cancer. Moreover, the biomarker expression differed depending on ER status, and a high p95HER2 expression and wild-type PIK3CA gene correlated with longer PFS especially in the ER-positive cases.

Population PBPK modelling of trastuzumab: a framework for quantifying and predicting inter-individual variability

In this work we proposed a population physiologically-based pharmacokinetic (popPBPK) framework for quantifying and predicting inter-individual pharmacokinetic variability using the anti-HER2 monoclonal antibody (mAb) trastuzumab as an example. First, a PBPK model was developed to account for the possible mechanistic sources of variability. Within the model, five key factors that contribute to variability were identified and the nature of their contribution was quantified with local and global sensitivity analyses. The five key factors were the concentration of membrane-bound HER2 ([Formula: see text]), the convective flow rate of mAb through vascular pores ([Formula: see text]), the endocytic transport rate of mAb through vascular endothelium ([Formula: see text]), the degradation rate of mAb-HER2 complexes ([Formula: see text]) and the concentration of shed HER2 extracellular domain in circulation ([Formula: see text]). [Formula: see text] was the most important parameter governing trastuzumab distribution into tissues and primarily affected variability in the first 500 h post-administration. [Formula: see text] was the most significant contributor to variability in clearance. These findings were used together with population generation methods to accurately predict the observed variability in four experimental trials with trastuzumab. To explore anthropometric sources of variability, virtual populations were created to represent participants in the four experimental trials. Using populations with only their expected anthropometric diversity resulted in under-prediction of the observed inter-individual variability. Adapting the populations to include literature-based variability around the five key parameters enabled accurate predictions of the variability in the four trials. The successful application of this framework demonstrates the utility of popPBPK methods to understand the mechanistic underpinnings of pharmacokinetic variability.

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.

Quantitative measurement of HER2 expression in breast cancers: comparison with 'real-world' routine HER2 testing in a multicenter Collaborative Biomarker Study and correlation with overall survival

Introduction

Accurate assessment of HER2 status is critical in determining appropriate therapy for breast cancer patients but the best HER2 testing methodology has yet to be defined. In this study, we compared quantitative HER2 expression by the HERmark™ Breast Cancer Assay (HERmark) with routine HER2 testing by immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH), and correlated HER2 results with overall survival (OS) of breast cancer patients in a multicenter Collaborative Biomarker Study (CBS).

Methods

Two hundred and thirty-two formalin-fixed, paraffin-embedded breast cancer tissues and local laboratory HER2 testing results were provided by 11 CBS sites. HERmark assay and central laboratory HER2 IHC retesting were retrospectively performed in a blinded fashion. HER2 results by all testing methods were obtained in 192 cases.

Results

HERmark yielded a continuum of total HER2 expression (H2T) ranging from 0.3 to 403 RF/mm² (approximately 3 logs). The distribution of H2T levels correlated significantly (P <0.0001) with all routine HER2 testing results. The concordance of positive and negative values (equivocal cases excluded) between HERmark and routine HER2 testing was 84% for local IHC, 96% for central IHC, 85% for local FISH, and 84% for local HER2 status. OS analysis revealed a significant correlation of shorter OS with HER2 positivity by local IHC (HR = 2.6, P = 0.016), central IHC (HR = 3.2, P = 0.015), and HERmark (HR = 5.1, P <0.0001) in this cohort of patients most of whom received no HER2-targeted therapy. The OS curve of discordant low (HER2 positive but H2T low, 10% of all cases) was aligned with concordant negative (HER2 negative and H2T low, HR = 1.9, P = 0.444), but showed a significantly longer OS than concordant positive (HER2 positive and H2T high, HR = 0.31, P = 0.024). Conversely, the OS curve of discordant high (HER2 negative but H2T high, 9% of all cases) was aligned with concordant positive (HR = 0.41, P = 0.105), but showed a significantly shorter OS than concordant negative (HR = 41, P <0.0001).

Conclusions

Quantitative HER2 measurement by HERmark is highly sensitive, accurately quantifies HER2 protein expression and correlates well with routine HER2 testing. When HERmark and local HER2 results were discordant, HERmark more accurately predicted overall survival.

HER family kinase domain mutations promote tumor progression and can predict response to treatment in human breast cancer

Resistance to HER2-targeted therapies remains a major obstacle in the treatment of HER2-overexpressing breast cancer. Understanding the molecular pathways that contribute to the development of drug resistance is needed to improve the clinical utility of novel agents, and to predict the success of targeted personalized therapy based on tumor-specific mutations. Little is known about the clinical significance of HER family mutations in breast cancer. Because mutations within HER1/EGFR are predictive of response to tyrosine kinase inhibitors (TKI) in lung cancer, we investigated whether mutations in HER family kinase domains are predictive of response to targeted therapy in HER2-overexpressing breast cancer. We sequenced the HER family kinase domains from 76 HER2-overexpressing invasive carcinomas and identified 12 missense variants. Patients whose tumors carried any of these mutations did not respond to HER2 directed therapy in the metastatic setting. We developed mutant cell lines and used structural analyses to determine whether changes in protein conformation could explain the lack of response to therapy. We also functionally studied all HER2 mutants and showed that they conferred an aggressive phenotype and altered effects of the TKI lapatinib. Our data demonstrate that mutations in the finely tuned HER kinase domains play a critical function in breast cancer progression and may serve as prognostic and predictive markers.

c-erbB-2 as a possible target for the use of magnetic nanoparticles in breast cancer cells

Breast cancer (BC) is the most frequent malignancy among women worldwide and has been associated with high mortality because of the late treatment of the disease. Our group has proposed a selective ablation of breast cancer cells by the use of magnetic fields assisted by magnetic nanoparticles. The principle is to increase the conductivity of tumoral tissue by the use of a bioconjugated "nanoparticle-antibody" that recognizes specific antigens on the surface of the cancer cells. The aim of this study was to evaluate the c-erbB-2 antigen in breast cancer cells of type BT-474, MCF-7, and MDA-MB-231 as a possible target for the use of magnetic nanoparticles coupled to a specific Monoclonal Antibody (Mab). Quantitative real-time polymerase chain reaction and flow cytometry were used to estimate the relative expressions of the c-erbB-2 gene and the c-erbB-2 antigen in the cell lines, respectively. A covalent union of magnetic nanoparticles to anti c-erbB-2 Mab was used to develop the bioconjugate. Fluorescence microscopy was used to determine the cells that were tagged by the bioconjugate. The results show a well-differentiated relative expression of c-erbB-2 in the studied cell lines and are qualitatively in agreement with the fluorescent marking by the magnetic nanoparticles. The selected breast cancer cells appear to be suitable for experimental evaluation of selective targeting by magnetic nanoparticles.

HER3, p95HER2, and HER2 protein expression levels define multiple subtypes of HER2-positive metastatic breast cancer

Trastuzumab is effective in the treatment of HER2/neu over-expressing breast cancer, but not all patients benefit from it. In vitro data suggest a role for HER3 in the initiation of signaling activity involving the AKT–mTOR pathway leading to trastuzumab insensitivity. We sought to investigate the potential of HER3 alone and in the context of p95HER2 (p95), a trastuzumab resistance marker, as biomarkers of trastuzumab escape. Using the VeraTag® assay platform, we developed a dual antibody proximity-based assay for the precise quantitation of HER3 total protein (H3T) from formalin-fixed paraffin-embedded (FFPE) breast tumors. We then measured H3T in 89 patients with metastatic breast cancer treated with trastuzumab-based therapy, and correlated the results with progression-free survival and overall survival using Kaplan–Meier and decision tree analyses that also included HER2 total (H2T) and p95 expression levels. Within the sub-population of patients that over-expressed HER2, high levels of HER3 and/or p95 protein expression were significantly associated with poor clinical outcomes on trastuzumab-based therapy. Based on quantitative H3T, p95, and H2T measurements, multiple subtypes of HER2-positive breast cancer were identified that differ in their outcome following trastuzumab therapy. These data suggest that HER3 and p95 are informative biomarkers of clinical outcomes on trastuzumab therapy, and that multiple subtypes of HER2-positive breast cancer may be defined by quantitative measurements of H3T, p95, and H2T.

Quantitative measurements of tumoral p95HER2 protein expression in metastatic breast cancer patients treated with trastuzumab: independent validation of the p95HER2 clinical cutoff

PURPOSE

P95HER2 (p95) is a truncated form of the HER2, which lacks the trastuzumab-binding site and contains a hyperactive kinase domain. Previously, an optimal clinical cutoff of p95 expression for progression-free survival (PFS) and overall survival (OS) was defined using a quantitative VeraTag assay (Monogram Biosciences) in a training set of trastuzumab-treated metastatic breast cancer (MBC) patients.

EXPERIMENTAL DESIGN

In the current study, the predictive value of the p95 VeraTag assay cutoff established in the training set was retrospectively validated for PFS and OS in an independent series of 240 trastuzumab-treated MBC patients from multiple institutions.

RESULTS

In the subset of 190 tumors assessed as HER2-total (H2T)-positive using the quantitative HERmark assay (Monogram Biosciences), p95 VeraTag values above the predefined cutoff correlated with shorter PFS (HR = 1.43; P = 0.039) and shorter OS (HR = 1.94; P = 0.0055) where both outcomes were stratified by hormone receptor status and tumor grade. High p95 expression correlated with shorter PFS (HR = 2.41; P = 0.0003) and OS (HR = 2.57; P = 0.0025) in the hormone receptor-positive subgroup of patients (N = 78), but not in the hormone receptor-negative group. In contrast with the quantitative p95 VeraTag measurements, p95 immunohistochemical expression using the same antibody was not significantly correlated with outcomes.

CONCLUSIONS

The consistency in the p95 VeraTag cutoff across different cohorts of patients with MBC treated with trastuzumab justifies additional studies using blinded analyses in larger series of patients.

Expression of c-erbB-2 in breast cancer cell lines as experimental receptor of magnetic nanoparticles

High mortality in breast cancer is associated to a late diagnosis and therapy of the disease. Our research group is working on the development of an innovative technology to promote selective ablation of breast cancer in early stages by the use of high frequency magnetic fields assisted by magnetic nanoparticles. The concept behind the technical proposal is to increase the electrical conductivity of tumoral tissue by the use of bioconjugated "magnetic nanoparticle-monoclonal antibody". Is expected that bioconjugated recognizes specific genes on the surface of cancer cells. The aim of this study was to evaluate the expression of the c-erbB-2 gene and c-erbB-2 antigen in breast cancer cells type BT-474, MCF-7 and MDA-MB-231, as previous step to propose the c-erbB-2 protein as receptor of magnetic nanoparticles. The results suggest that the elected breast cancer cell lines show well-differentiated relative expression of the elected gen and antigen, and sems suitable for experimental evaluation of selective targeting by magnetic nanoparticles.

Correlation of HER2, p95HER2 and HER3 expression and treatment outcome of lapatinib plus capecitabine in her2-positive metastatic breast cancer

BACKGROUND

Lapatinib plus capecitabine is an effective treatment option for trastuzumab-refractory HER2-positive metastatic breast cancer. We have investigated the correlation between quantitative measures of HER2, p95HER2, and HER3 and treatment outcomes using lapatinib and capecitabine.

METHODS

Total HER2 (H2T), p95HER2 (p95), and total HER3 (H3T) expression were quantified in formalin-fixed paraffin-embedded samples using the VeraTag assays. Patients received lapatinib and capecitabine treatment following trastuzumab failure according to the Lapatinib Expanded Access Program. The association between the protein expression levels and clinical outcomes was analyzed.

RESULTS

A total of 52 patients were evaluable. H2T level was significantly higher in responders (median 93.49 in partial response, 47.66 in stable disease, and 17.27 in progressive disease; p = 0.020). Longer time-to-progression (TTP) was observed in patients with high H2T [p = 0.018, median 5.2 months in high (>14.95) vs. 1.8 in low (<14.95)] and high H3T [p = 0.017, median 5.0 months in high (>0.605) vs. 2.2 in low (<0.605)]. Patients having both high H2T and high H3T had significantly longer TTP [adjusted hazard ratio (HR) 0.38 (95% CI 0.20-0.73), p = 0.004] and overall survival [adjusted HR 0.46 (95% CI 0.24-0.89), p = 0.020]. No significant association between p95 and response or survival was observed.

CONCLUSIONS

These data suggest a correlation between high HER2 and high HER3 expression and treatment outcome, while no significant difference was observed between clinical outcome and p95 expression level in this cohort of HER2-positive, trastuzumab-refractory metastatic breast cancer patients treated with lapatinib and capecitabine.

Correlation between quantitative HER-2 protein expression and risk for brain metastases in HER-2+ advanced breast cancer patients receiving trastuzumab-containing therapy

BACKGROUND

Patients with human epidermal growth factor receptor (HER)-2+ breast cancer are at particularly high risk for brain metastases; however, the biological basis is not fully understood. Using a novel HER-2 assay, we investigated the correlation between quantitative HER-2 expression in primary breast cancers and the time to brain metastasis (TTBM) in HER-2+ advanced breast cancer patients treated with trastuzumab.

METHODS

The study group included 142 consecutive patients who were administered trastuzumab-based therapy for HER-2+ metastatic breast cancer. HER-2/neu gene copy number was quantified as the HER-2/centromeric probe for chromosome 17 (CEP17) ratio by central laboratory fluorescence in situ hybridization (FISH). HER-2 protein was quantified as total HER-2 protein expression (H2T) by the HERmark® assay (Monogram Biosciences, Inc., South San Francisco, CA) in formalin-fixed, paraffin-embedded tumor samples. HER-2 variables were correlated with clinical features and TTBM was measured from the initiation of trastuzumab-containing therapy.

RESULTS

A higher H2T level (continuous variable) was correlated with shorter TTBM, whereas HER-2 amplification by FISH and a continuous HER-2/CEP17 ratio were not predictive (p = .013, .28, and .25, respectively). In the subset of patients that was centrally determined by FISH to be HER-2+, an above-the-median H2T level was significantly associated with a shorter TTBM (hazard ratio, [HR], 2.4; p = .005), whereas this was not true for the median HER-2/CEP17 ratio by FISH (p = .4). Correlation between a continuous H2T level and TTBM was confirmed on multivariate analysis (HR, 3.3; p = .024).

CONCLUSIONS

These data reveal a strong relationship between the quantitative HER-2 protein expression level and the risk for brain relapse in HER-2+ advanced breast cancer patients. Consequently, quantitative assessment of HER-2 protein expression may inform and facilitate refinements in therapeutic treatment strategies for selected subpopulations of patients in this group.

Quantitative assays for the measurement of HER1-HER2 heterodimerization and phosphorylation in cell lines and breast tumors: applications for diagnostics and targeted drug mechanism of action

Introduction

Ligand-bound and phosphorylated ErbB/HER heterodimers are potent signaling forms of this receptor family, and quantitative measurements of these active receptors may be predictive of patient response to targeted therapies. Using VeraTag™ technology, we developed and characterized quantitative assays measuring epidermal growth factor (EGF)-dependent increases in activated HER receptors in tumor cell line lysates and formalin-fixed, paraffin-embedded (FFPE) tumor sections. We demonstrated the ability of the assays to quantitatively measure changes in activated HER1 and HER2 receptor levels in cell lines following treatment with 2C4, erlotinib, and lapatinib. We utilized these assays to determine the prevalence and distribution of activated HER1, HER2, and HER1-HER2 heterodimers in 43 HER2-positive breast tumors.

Methods

Assays for activated HER1 and HER2 receptors in FFPE and cell lysate formats were developed using VeraTag™ technology, which requires the proximity of an antibody pair for light-dependent release of a fluorescently labeled tag, followed by capillary electrophoresis-based quantitation.

Results

Ligand-dependent and independent HER1-HER2 heterodimer levels measured by lysate and FFPE VeraTag™ assays trended with HER1 and HER2 expression levels in tumor cell lines, which was confirmed by co-immunoprecipitation. The formation of EGF-dependent HER1-HER2 heterodimers were inhibited by the HER2-targeted monoclonal antibody 2C4 and stabilized by the HER1 tyrosine kinase inhibitor (TKI) erlotinib. EGF-dependent HER1 and HER2 phosphorylation was inhibited by lapatinib and erlotinib. Further, we observed that dominant receptor signaling patterns may switch between HER1-HER1 and HER1-HER2, depending on drug mechanism of action and relative levels of HER receptors. In FFPE breast tumors that expressed both HER1 and HER2, HER1-HER2 heterodimers were detected in 25 to 50% of tumors, depending on detection method. The levels of activated phospho-HER1-HER2 heterodimers correlated with HER1 or HER2 levels in an analysis of 43 HER2-positive breast tumors.

Conclusions

VeraTag™ lysate assays can be used as a tool for understanding the mechanism of action of targeted HER-family inhibitors in the preclinical setting, while VeraTag™ FFPE assays of activated HER receptors combined with total HER2 measurements (HERmark^®) in tumor samples may provide a more accurate prediction of clinical response to both HER1 and HER2 targeted therapies.

Detection of hepatocyte growth factor (HGF) ligand-c-MET receptor activation in formalin-fixed paraffin embedded specimens by a novel proximity assay

Aberrant activation of membrane receptors frequently occurs in human carcinomas. Detection of phosphorylated receptors is commonly used as an indicator of receptor activation in formalin-fixed paraffin embedded (FFPE) tumor specimens. FFPE is a standard method of specimen preparation used in the histological analysis of solid tumors. Due to variability in FFPE preparations and the labile nature of protein phosphorylation, measurements of phospho-proteins are unreliable and create ambiguities in clinical interpretation. Here, we describe an alternative, novel approach to measure receptor activation by detecting and quantifying ligand-receptor complexes in FFPE specimens. We used hepatocyte growth factor (HGF)-c-MET as our model ligand-receptor system. HGF is the only known ligand of the c-MET tyrosine kinase receptor and HGF binding triggers c-MET phosphorylation. Novel antibody proximity-based assays were developed and used to detect and quantify total c-MET, total HGF, and HGF-c-MET ligand-receptor interactions in FFPE cell line and tumor tissue. In glioma cells, autocrine activation of c-MET by HGF-c-MET increased basal levels of c-MET phosphorylation at tyrosine (Tyr) 1003. Furthermore, HGF-c-MET activation in glioma cell lines was verified by Surface Protein-Protein Interaction by Crosslinking ELISA (SPPICE) assay in corresponding soluble cell lysates. Finally, we profiled levels ofc-MET, HGF, and HGF-c-MET complexes in FFPE specimens of human Non-Small Cell Lung Cancer (NSCLC), Gastric Cancer, Head and Neck Squamous Cell, and Head and Neck Non-Squamous Cell carcinomas. This report describes a novel approach for the detection and quantification of ligand-receptor interactions that can be widely applied to measure receptor activation in FFPE preclinical models and archived FFPE human tissue specimens.