Microarray-Based Determination of Estrogen Receptor, Progesterone Receptor, and HER2 Receptor Status in Breast Cancer

Neoadjuvant Trebananib plus Paclitaxel-based Chemotherapy for Stage II/III Breast Cancer in the Adaptively Randomized I-SPY2 Trial-Efficacy and Biomarker Discovery

PURPOSE

The neutralizing peptibody trebananib prevents angiopoietin-1 and angiopoietin-2 from binding with Tie2 receptors, inhibiting angiogenesis and proliferation. Trebananib was combined with paclitaxel±trastuzumab in the I-SPY2 breast cancer trial.

PATIENTS AND METHODS

I-SPY2, a phase II neoadjuvant trial, adaptively randomizes patients with high-risk, early-stage breast cancer to one of several experimental therapies or control based on receptor subtypes as defined by hormone receptor (HR) and HER2 status and MammaPrint risk (MP1, MP2). The primary endpoint is pathologic complete response (pCR). A therapy "graduates" if/when it achieves 85% Bayesian probability of success in a phase III trial within a given subtype. Patients received weekly paclitaxel (plus trastuzumab if HER2-positive) without (control) or with weekly intravenous trebananib, followed by doxorubicin/cyclophosphamide and surgery. Pathway-specific biomarkers were assessed for response prediction.

RESULTS

There were 134 participants randomized to trebananib and 133 to control. Although trebananib did not graduate in any signature [phase III probabilities: Hazard ratio (HR)-negative (78%), HR-negative/HER2-positive (74%), HR-negative/HER2-negative (77%), and MP2 (79%)], it demonstrated high probability of superior pCR rates over control (92%-99%) among these subtypes. Trebananib improved 3-year event-free survival (HR 0.67), with no significant increase in adverse events. Activation levels of the Tie2 receptor and downstream signaling partners predicted trebananib response in HER2-positive disease; high expression of a CD8 T-cell gene signature predicted response in HR-negative/HER2-negative disease.

CONCLUSIONS

The angiopoietin (Ang)/Tie2 axis inhibitor trebananib combined with standard neoadjuvant therapy increased estimated pCR rates across HR-negative and MP2 subtypes, with probabilities of superiority >90%. Further study of Ang/Tie2 receptor axis inhibitors in validated, biomarker-predicted sensitive subtypes is warranted.

Safety and efficacy of HSP90 inhibitor ganetespib for neoadjuvant treatment of stage II/III breast cancer

HSP90 inhibitors destabilize oncoproteins associated with cell cycle, angiogenesis, RAS-MAPK activity, histone modification, kinases and growth factors. We evaluated the HSP90-inhibitor ganetespib in combination with standard chemotherapy in patients with high-risk early-stage breast cancer. I-SPY2 is a multicenter, phase II adaptively randomized neoadjuvant (NAC) clinical trial enrolling patients with stage II-III breast cancer with tumors 2.5 cm or larger on the basis of hormone receptors (HR), HER2 and Mammaprint status. Multiple novel investigational agents plus standard chemotherapy are evaluated in parallel for the primary endpoint of pathologic complete response (pCR). Patients with HER2-negative breast cancer were eligible for randomization to ganetespib from October 2014 to October 2015. Of 233 women included in the final analysis, 140 were randomized to the standard NAC control; 93 were randomized to receive 150 mg/m2 ganetespib every 3 weeks with weekly paclitaxel over 12 weeks, followed by AC. Arms were balanced for hormone receptor status (51-52% HR-positive). Ganetespib did not graduate in any of the biomarker signatures studied before reaching maximum enrollment. Final estimated pCR rates were 26% vs. 18% HER2-negative, 38% vs. 22% HR-negative/HER2-negative, and 15% vs. 14% HR-positive/HER2-negative for ganetespib vs control, respectively. The predicted probability of success in phase 3 testing was 47% HER2-negative, 72% HR-negative/HER2-negative, and 19% HR-positive/HER2-negative. Ganetespib added to standard therapy is unlikely to yield substantially higher pCR rates in HER2-negative breast cancer compared to standard NAC, and neither HSP90 pathway nor replicative stress expression markers predicted response. HSP90 inhibitors remain of limited clinical interest in breast cancer, potentially in other clinical settings such as HER2-positive disease or in combination with anti-PD1 neoadjuvant chemotherapy in triple negative breast cancer.Trial registration: www.clinicaltrials.gov/ct2/show/NCT01042379.

HER2 mRNA Levels, Estrogen Receptor Activity and Susceptibility to Trastuzumab in Primary Breast Cancer

While the results thus far demonstrate the clinical benefit of trastuzumab in breast cancer (BC), some patients do not respond to this drug. HER2 mRNA, alone or combined with other genes/biomarkers, has been proven to be a powerful predictive marker in several studies. Here, we provide evidence of the association between HER2 mRNA levels and the response to anti-HER2 treatment in HER2-positive BC patients treated with adjuvant trastuzumab and show that this association is independent of estrogen receptor (ER) tumor positivity. While HER2 mRNA expression was significantly correlated with HER2 protein levels in ER-negative tumors, no correlation was found in ER-positive tumors, and HER2 protein expression was not associated with relapse risk. Correlation analyses in the ER-positive subset identified ER activity as the pathway inversely associated with HER2 mRNA. Associations between HER2 levels and oncogene addiction, as well as between HER2 activation and trastuzumab sensitivity, were also observed in vitro in HER2-positive BC cell lines. In ER-positive but not ER-negative BC cells, HER2 transcription was increased by reducing ligand-dependent ER activity or inducing ER degradation. Accordingly, HER2 mRNA levels in patients were found to be inversely correlated with blood levels of estradiol, the natural ligand of ER that induces ER activation. Moreover, low estradiol levels were associated with a lower risk of relapse in HER2-positive BC patients treated with adjuvant trastuzumab. Overall, we found that HER2 mRNA levels, but not protein levels, indicate the HER2 dependency of tumor cells and low estrogen-dependent ER activity in HER2-positive tumors.

How Reliable Are Gene Expression-Based and Immunohistochemical Biomarkers Assessed on a Core-Needle Biopsy? A Study of Paired Core-Needle Biopsies and Surgical Specimens in Early Breast Cancer

In early breast cancer, a preoperative core-needle biopsy (CNB) is vital to confirm the malignancy of suspected lesions and for assessing the expression of treatment predictive and prognostic biomarkers in the tumor to choose the optimal treatments, emphasizing the importance of obtaining reliable results when biomarker status is assessed on a CNB specimen. This study aims to determine the concordance between biomarker status assessed as part of clinical workup on a CNB compared to a medically untreated surgical specimen. Paired CNB and surgical specimens from 259 patients that were part of the SCAN-B cohort were studied. The concordance between immunohistochemical (IHC) and gene expression (GEX) based biomarker status was investigated. Biomarkers of interest included estrogen receptor (ER; specifically, the alpha variant), progesterone receptor (PgR), Ki67, HER2, and tumor molecular subtype. In general, moderate to very good correlation in biomarker status between the paired CNB and surgical specimens was observed for both IHC assessment (83–99% agreement, kappa range 0.474–0.917) and GEX assessment (70–97% agreement, kappa range 0.552–0.800), respectively. However, using IHC, 52% of cases with low Ki67 status in the CNB shifted to high Ki67 status in the surgical specimen (McNemar’s p = 0.011). Similarly, when using GEX, a significant shift from negative to positive ER (47%) and from low to high Ki67 (16%) was observed between the CNB and surgical specimen (McNemar’s p = 0.027 and p = 0.002 respectively). When comparing biomarker status between different techniques (IHC vs. GEX) performed on either CNBs or surgical specimens, the agreement in ER, PgR, and HER2 status was generally over 80% in both CNBs and surgical specimens (kappa range 0.395–0.708), but Ki67 and tumor molecular subtype showed lower concordance levels between IHC and GEX (48–62% agreement, kappa range 0.152–0.398). These results suggest that both the techniques used for collecting tissue samples and analyzing biomarker status have the potential to affect the results of biomarker assessment, potentially also impacting treatment decisions and patient survival outcomes.

Breast Cancer Human Epidermal Growth Factor Receptor 2 mRNA Molecular Testing Compared to Immunohistochemistry with Correlation to Neoadjuvant Therapy Response

BACKGROUND: Breast cancer is the most common cancer type among women worldwide. Human epidermal growth factor receptor 2 (HER-2) is amplified in 10–34% of breast carcinomas and offers a therapeutic option from HER2-targeted therapy. Hence, HER2 is tested routinely in all breast cancer patients using immunohistochemistry (IHC) and in situ hybridization. Yet, some pitfalls do exist due to tumoral heterogeneity, inter and intrapersonal variations. mRNA expression assays can provide an alternative method for accurately measuring HER-2 avoiding these limitations. AIM: Comparing results of mRNA gene expression analysis for HER2 with IHC results and correlating it with the therapy response. MATERIALS AND METHODS: One hundred breast cancer core biopsies were tested for HER-2 using IHC and the same blocks were sectioned and tested for mRNA gene expression for HER2 by the Xpert breast cancer STRAT4 device. RESULTS: Concordance rate between mRNA expression and IHC for HER-2 was 93% with Kappa measurement showing perfect agreement (κ = 0.81, 95% CI, p < 0.0005). CONCLUSION: The study reveals high concordance between HER2 measurement using IHC and mRNA analysis. Molecular testing can provide an effective standardized method for HER-2 measurement in breast cancer patients.

Neoadjuvant T-DM1/pertuzumab and paclitaxel/trastuzumab/pertuzumab for HER2+ breast cancer in the adaptively randomized I-SPY2 trial

HER2-targeted therapy dramatically improves outcomes in early breast cancer. Here we report the results of two HER2-targeted combinations in the neoadjuvant I-SPY2 phase 2 adaptive platform trial for early breast cancer at high risk of recurrence: ado-trastuzumab emtansine plus pertuzumab (T-DM1/P) and paclitaxel, trastuzumab and pertuzumab (THP). Eligible women have >2.5 cm clinical stage II/III HER2+ breast cancer, adaptively randomized to T-DM1/P, THP, or a common control arm of paclitaxel/trastuzumab (TH), followed by doxorubicin/cyclophosphamide, then surgery. Both T-DM1/P and THP arms 'graduate' in all subtypes: predicted pCR rates are 63%, 72% and 33% for T-DM1/P (n = 52), THP (n = 45) and TH (n = 31) respectively. Toxicity burden is similar between arms. Degree of HER2 pathway signaling and phosphorylation in pretreatment biopsy specimens are associated with response to both T-DM1/P and THP and can further identify highly responsive HER2+ tumors to HER2-directed therapy. This may help identify patients who can safely de-escalate cytotoxic chemotherapy without compromising excellent outcome.

New Generation of Meso and Antiprogestins (SPRMs) into the Osteoporosis Approach

Receptor activator of nuclear factor κB (RANK) and its ligand (RANKL) play key roles in bone metabolism and the immune system. The RANK/RANKL complex has also been shown to be critical in the formation of mammary epithelia cells. The female hormones estradiol and progesterone closely control the action of RANKL with RANK. Blood concentration of these sex hormones in the postmenopausal period leads to an increase in RANK/RANKL signaling and are a major cause of women's osteoporosis, characterized by altered bone mineralization. Knowledge of the biochemical relationships between hormones and RANK/RANKL signaling provides the opportunity to design novel therapeutic agents to inhibit bone loss, based on the anti-RANKL treatment and inhibition of its interaction with the RANK receptor. The new generation of both anti- and mesoprogestins that inhibit the NF-κB-cyclin D1 axis and blocks the binding of RANKL to RANK can be considered as a potential source of new RANK receptor ligands with anti-RANKL function, which may provide a new perspective into osteoporosis treatment itself as well as limit the osteoporosis rise during breast cancer metastasis to the bone.

Comparison of breast cancer surrogate subtyping using a closed-system RT-qPCR breast cancer assay and immunohistochemistry on 100 core needle biopsies with matching surgical specimens

Background

Routine clinical management of breast cancer (BC) currently depends on surrogate subtypes according to estrogen- (ER) and progesterone (PR) receptor, Ki-67, and HER2-status. However, there has been growing demand for reduced immunohistochemistry (IHC) turnaround times. The Xpert® Breast Cancer STRAT4* Assay (STRAT4)*, a standardized test for ESR1/PGR/MKi67/ERBB2 mRNA biomarker assessment, takes less than 2 hours. Here, we compared the concordance between the STRAT4 and IHC/SISH, thereby evaluating the effect of method choice on surrogate subtype assessment and adjuvant treatment decisions.

Methods

In total, 100 formalin-fixed paraffin-embedded core needle biopsy (CNB) samples and matching surgical specimens for 98 patients with primary invasive BC were evaluated using the STRAT4 assay. The concordance between STRAT4 and IHC was calculated for individual markers for the CNB and surgical specimens. In addition, we investigated whether changes in surrogate BC subtyping based on the STRAT4 results would change adjuvant treatment recommendations.

Results

The overall percent agreement (OPA) between STRAT4 and IHC/SISH ranged between 76 and 99% for the different biomarkers. Concordance for all four biomarkers in the surgical specimens and CNBs was only 66 and 57%, respectively. In total, 74% of surgical specimens were concordant for subtype, regardless of the method used. IHC- and STRAT4-based subtyping for the surgical specimen were shown to be discordant for 25/98 patients and 18/25 patients would theoretically have been recommended a different adjuvant treatment, primarily receiving more chemotherapy and trastuzumab.

Conclusions

A comparison of data from IHC/in situ hybridization and STRAT4 demonstrated that subsequent changes in surrogate subtyping for the surgical specimen may theoretically result in more adjuvant treatment given, primarily with chemotherapy and trastuzumab.

Molecular intrinsic versus clinical subtyping in breast cancer: A comprehensive review

Breast cancer is a heterogeneous disease manifesting diversity at the molecular, histological and clinical level. The development of breast cancer classification was centered on informing clinical decisions. The current approach to the classification of breast cancer, which categorizes this disease into clinical subtypes based on the detection of estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and proliferation marker Ki67, is not ideal. This is manifested as a heterogeneity of therapeutic responses and outcomes within the clinical subtypes. The newer classification model, based on gene expression profiling (intrinsic subtyping) informs about transcriptional responses downstream from IHC single markers, revealing deeper appreciation for the disease heterogeneity and capturing tumor biology in a more comprehensive way than an expression of a single protein or gene alone. While accumulating evidences suggest that intrinsic subtypes provide clinically relevant information beyond clinical surrogates, it is imperative to establish whether the current conventional immunohistochemistry-based clinical subtyping approach could be improved by gene expression profiling and if this approach has a potential to translate into clinical practice.

The mutational landscape of the SCAN-B real-world primary breast cancer transcriptome

Breast cancer is a disease of genomic alterations, of which the panorama of somatic mutations and how these relate to subtypes and therapy response is incompletely understood. Within SCAN‐B (ClinicalTrials.gov: NCT02306096), a prospective study elucidating the transcriptomic profiles for thousands of breast cancers, we developed a RNA‐seq pipeline for detection of SNVs/indels and profiled a real‐world cohort of 3,217 breast tumors. We describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population‐based cohort and relate it to patient survival. We demonstrate that RNA‐seq can be used to call mutations in genes such as PIK3CA,TP53, and ERBB2, as well as the status of molecular pathways and mutational burden, and identify potentially druggable mutations in 86.8% of tumors. To make this rich dataset available for the research community, we developed an open source web application, the SCAN‐B MutationExplorer (http://oncogenomics.bmc.lu.se/MutationExplorer). These results add another dimension to the use of RNA‐seq as a clinical tool, where both gene expression‐ and mutation‐based biomarkers can be interrogated in real‐time within 1 week of tumor sampling.

Clinical Application of Multiple Reaction Monitoring-Mass Spectrometry to Human Epidermal Growth Factor Receptor 2 Measurements as a Potential Diagnostic Tool for Breast Cancer Therapy

Background

Human epidermal growth factor receptor 2 (HER2) is often overexpressed in breast cancer and correlates with a worse prognosis. Thus, the accurate detection of HER2 is crucial for providing the appropriate measures for patients. However, the current techniques used to detect HER2 status, immunohistochemistry and fluorescence in situ hybridization (FISH), have limitations. Specifically, FISH, which is mandatory for arbitrating 2+ cases, is time-consuming and costly. To address this shortcoming, we established a multiple reaction monitoring-mass spectrometry (MRM-MS) assay that improves on existing methods for differentiating HER2 status.

Methods

We quantified HER2 expression levels in 210 breast cancer formalin-fixed paraffin-embedded (FFPE) tissue samples by MRM-MS. We aimed to improve the accuracy and precision of HER2 quantification by simplifying the sample preparation through predicting the number of FFPE slides required to ensure an adequate amount of protein and using the expression levels of an epithelial cell-specific protein as a normalization factor when measuring HER2 expression levels.

Results

To assess the correlation between MRM-MS and IHC/FISH data, HER2 quantitative data from MRM-MS were divided by the expression levels of junctional adhesion molecule A, an epithelial cell-specific protein, prior to statistical analysis. The normalized HER2 amounts distinguished between HER2 2+/FISH-negative and 2+/FISH-positive groups (AUROC = 0.908), which could not be differentiated by IHC. In addition, all HER2 status were discriminated by MRM-MS.

Conclusions

This MRM-MS assay yields more accurate HER2 expression levels relative to immunohistochemistry and should help to guide clinicians toward the proper treatment for breast cancer patients, based on their HER2 expression.

Controlling technical variation amongst 6693 patient microarrays of the randomized MINDACT trial

Gene expression data obtained in large studies hold great promises for discovering disease signatures or subtypes through data analysis. It is also prone to technical variation, whose removal is essential to avoid spurious discoveries. Because this variation is not always known and can be confounded with biological signals, its removal is a challenging task. Here we provide a step-wise procedure and comprehensive analysis of the MINDACT microarray dataset. The MINDACT trial enrolled 6693 breast cancer patients and prospectively validated the gene expression signature MammaPrint for outcome prediction. The study also yielded a full-transcriptome microarray for each tumor. We show for the first time in such a large dataset how technical variation can be removed while retaining expected biological signals. Because of its unprecedented size, we hope the resulting adjusted dataset will be an invaluable tool to discover or test gene expression signatures and to advance our understanding of breast cancer.

Effect of Pembrolizumab Plus Neoadjuvant Chemotherapy on Pathologic Complete Response in Women With Early-Stage Breast Cancer: An Analysis of the Ongoing Phase 2 Adaptively Randomized I-SPY2 Trial

Importance

Approximately 25% of patients with early-stage breast cancer who receive (neo)adjuvant chemotherapy experience a recurrence within 5 years. Improvements in therapy are greatly needed.

Objective

To determine if pembrolizumab plus neoadjuvant chemotherapy (NACT) in early-stage breast cancer is likely to be successful in a 300-patient, confirmatory randomized phase 3 neoadjuvant clinical trial.

Design, Setting, and Participants

The I-SPY2 study is an ongoing open-label, multicenter, adaptively randomized phase 2 platform trial for high-risk, stage II/III breast cancer, evaluating multiple investigational arms in parallel. Standard NACT serves as the common control arm; investigational agent(s) are added to this backbone. Patients with ERBB2 (formerly HER2)-negative breast cancer were eligible for randomization to pembrolizumab between November 2015 and November 2016.

Interventions

Participants were randomized to receive taxane- and anthracycline-based NACT with or without pembrolizumab, followed by definitive surgery.

Main Outcomes and Measures

The primary end point was pathologic complete response (pCR). Secondary end points were residual cancer burden (RCB) and 3-year event-free and distant recurrence-free survival. Investigational arms graduated when demonstrating an 85% predictive probability of success in a hypothetical confirmatory phase 3 trial.

Results

Of the 250 women included in the final analysis, 181 were randomized to the standard NACT control group (median [range] age, 47 [24.77] years). Sixty-nine women (median [range] age, 50 [27-71] years) were randomized to 4 cycles of pembrolizumab in combination with weekly paclitaxel followed by AC; 40 hormone receptor (HR)-positive and 29 triple-negative. Pembrolizumab graduated in all 3 biomarker signatures studied. Final estimated pCR rates, evaluated in March 2017, were 44% vs 17%, 30% vs 13%, and 60% vs 22% for pembrolizumab vs control in the ERBB2-negative, HR-positive/ERBB2-negative, and triple-negative cohorts, respectively. Pembrolizumab shifted the RCB distribution to a lower disease burden for each cohort evaluated. Adverse events included immune-related endocrinopathies, notably thyroid abnormalities (13.0%) and adrenal insufficiency (8.7%). Achieving a pCR appeared predictive of long-term outcome, where patients with pCR following pembrolizumab plus chemotherapy had high event-free survival rates (93% at 3 years with 2.8 years' median follow-up).

Conclusions and Relevance

When added to standard neoadjuvant chemotherapy, pembrolizumab more than doubled the estimated pCR rates for both HR-positive/ERBB2-negative and triple-negative breast cancer, indicating that checkpoint blockade in women with early-stage, high-risk, ERBB2-negative breast cancer is highly likely to succeed in a phase 3 trial. Pembrolizumab was the first of 10 agents to graduate in the HR-positive/ERBB2-negative signature.

Trial Registration

ClinicalTrials.gov Identifier: NCT01042379.

Deep learned tissue "fingerprints" classify breast cancers by ER/PR/Her2 status from H&E images

Because histologic types are subjective and difficult to reproduce between pathologists, tissue morphology often takes a back seat to molecular testing for the selection of breast cancer treatments. This work explores whether a deep-learning algorithm can learn objective histologic H&E features that predict the clinical subtypes of breast cancer, as assessed by immunostaining for estrogen, progesterone, and Her2 receptors (ER/PR/Her2). Translating deep learning to this and related problems in histopathology presents a challenge due to the lack of large, well-annotated data sets, which are typically required for the algorithms to learn statistically significant discriminatory patterns. To overcome this limitation, we introduce the concept of “tissue fingerprints,” which leverages large, unannotated datasets in a label-free manner to learn H&E features that can distinguish one patient from another. The hypothesis is that training the algorithm to learn the morphological differences between patients will implicitly teach it about the biologic variation between them. Following this training internship, we used the features the network learned, which we call “fingerprints,” to predict ER, PR, and Her2 status in two datasets. Despite the discovery dataset being relatively small by the standards of the machine learning community (n = 939), fingerprints enabled the determination of ER, PR, and Her2 status from whole slide H&E images with 0.89 AUC (ER), 0.81 AUC (PR), and 0.79 AUC (Her2) on a large, independent test set (n = 2531). Tissue fingerprints are concise but meaningful histopathologic image representations that capture biological information and may enable machine learning algorithms that go beyond the traditional ER/PR/Her2 clinical groupings by directly predicting theragnosis.

Microfluidic-based immunohistochemistry for breast cancer diagnosis: a comparative clinical study

Breast cancer is a highly heterogeneous disease. The efficacy of tailored therapeutic strategies relies on the precise detection of diagnostic biomarkers by immunohistochemistry (IHC). Therefore, considering the increasing incidence of breast cancer cases, a concomitantly time-efficient and accurate diagnosis is clinically highly relevant. Microfluidics is a promising innovative technology in the field of tissue diagnostic, enabling for rapid, reliable, and automated immunostaining. We previously reported the microfluidic-based HER2 (human epidermal growth factor receptor 2) detection in breast carcinomas to greatly correlate with the HER2 gene amplification level. Here, we aimed to develop a panel of microfluidic-based IHC protocols for prognostic and therapeutic markers routinely assessed for breast cancer diagnosis, namely HER2, estrogen/progesterone receptor (ER/PR), and Ki67 proliferation factor. The microfluidic IHC protocol for each marker was optimized to reach high staining quality comparable to the standard procedure, while concomitantly shortening the staining time to 16 min-excluding deparaffinization and antigen retrieval step-with a turnaround time reduction up to 7 folds. Comparison of the diagnostic score on 50 formaldehyde-fixed paraffin-embedded breast tumor resections by microfluidic versus standard staining showed high concordance (overall agreement: HER2 94%, ER 95.9%, PR 93.6%, Ki67 93.7%) and strong correlation (ρ coefficient: ER 0.89, PR 0.88, Ki67 0.87; p < 0.0001) for all the analyzed markers. Importantly, HER2 genetic reflex test for all discordant cases confirmed the scores obtained by the microfluidic technique. Overall, the microfluidic-based IHC represents a clinically validated equivalent approach to the standard chromogenic staining for rapid, accurate, and automated breast cancer diagnosis.

PCA-PAM50 improves consistency between breast cancer intrinsic and clinical subtyping reclassifying a subset of luminal A tumors as luminal B

The PAM50 classifier is widely used for breast tumor intrinsic subtyping based on gene expression. Clinical subtyping, however, is based on immunohistochemistry assays of 3–4 biomarkers. Subtype calls by these two methods do not completely match even on comparable subtypes. Nevertheless, the estrogen receptor (ER)-balanced subset for gene-centering in PAM50 subtyping, is selected based on clinical ER status. Here we present a new method called Principle Component Analysis-based iterative PAM50 subtyping (PCA-PAM50) to perform intrinsic subtyping in ER status unbalanced cohorts. This method leverages PCA and iterative PAM50 calls to derive the gene expression-based ER status and a subsequent ER-balanced subset for gene centering. Applying PCA-PAM50 to three different breast cancer study cohorts, we observed improved consistency (by 6–9.3%) between intrinsic and clinical subtyping for all three cohorts. Particularly, a more aggressive subset of luminal A (LA) tumors as evidenced by higher MKI67 gene expression and worse patient survival outcomes, were reclassified as luminal B (LB) increasing the LB subtype consistency with IHC by 25–49%. In conclusion, we show that PCA-PAM50 enhances the consistency of breast cancer intrinsic and clinical subtyping by reclassifying an aggressive subset of LA tumors into LB. PCA-PAM50 code is available at ftp://ftp.wriwindber.org/.

Gaussian Mixture Models for Probabilistic Classification of Breast Cancer

In the era of omics-driven research, it remains a common dilemma to stratify individual patients based on the molecular characteristics of their tumors. To improve molecular stratification of patients with breast cancer, we developed the Gaussian mixture model (GMM)-based classifier. This probabilistic classifier was built on mRNA expression data from more than 300 clinical samples of breast cancer and healthy tissue and was validated on datasets of ESR1, PGR, and ERBB2, which encode standard clinical markers and therapeutic targets. To demonstrate how a GMM approach could be exploited for multiclass classification using data from a candidate marker, we analyzed the insulin-like growth factor I receptor (IGF1R), a promising target, but a marker of uncertain importance in breast cancer. The GMM defined subclasses with downregulated (40%), unchanged (39%), upregulated (19%), and overexpressed (2%) IGF1R levels; inter- and intrapatient analyses of IGF1R transcript and protein levels supported these predictions. Overexpressed IGF1R was observed in a small percentage of tumors. Samples with unchanged and upregulated IGF1R were differentiated tumors, and downregulation of IGF1R correlated with poorly differentiated, high-risk hormone receptor-negative and HER2-positive tumors. A similar correlation was found in the independent cohort of carcinoma in situ, suggesting that loss or low expression of IGF1R is a marker of aggressiveness in subsets of preinvasive and invasive breast cancer. These results demonstrate the importance of probabilistic modeling that delves deeper into molecular data and aims to improve diagnostic classification, prognostic assessment, and treatment selection. SIGNIFICANCE: A GMM classifier demonstrates potential use for clinical validation of markers and determination of target populations, particularly when availability of specimens for marker development is low.

Clinical validation of Ki67 by quantitative reverse transcription-polymerase chain reaction (RT-PCR) in HR+/HER2- early breast cancer

Objective: To evaluate the clinical value of Ki67 by RT-PCR, we investigated the concordance of Ki67 expression by IHC and by RT-PCR, and assessed their prognostic value in HR+/HER2- early breast cancer.

Methods: 1259 HR+/HER2- early breast cancer patients treated at Ruijin Hospital with recurrence score were retrospectively recruited. RT-PCR assay measurement of Ki67 was conducted by 21-gene expression assay and compared with IHC measurement of Ki67 using chi-square tests. X-tile program was used to determine the optimal cutoff point for Ki67 by RT-PCR. Survival analyses were performed by Kaplan-Meier analysis and log-rank tests, and hazard ratios were derived from the Cox proportional hazards model.

Results: Ki67 by RT-PCR had a weak positive correlation with Ki67 by IHC. Pathology, grade and Ki67 expression by IHC were significantly related to the concordance between two assays, and most discordance cases were seen in patients with Ki67 ranging from 10 to 29. The estimated 3-year DFS was 96.0% in low, and 92.5% in high expression group of Ki67 by IHC, 97.0% in low and 90.4% in high expression group of Ki67 by RT-PCR. Univariate and multivariate analysis in the whole population indicated that only Ki67 by RT-PCR—but not intrinsic subtype or recurrence score—was an independent factor for DFS.

Conclusions: Ki67 assessed by RT-PCR assay was weakly correlated to Ki67 by IHC. Using 5.68 as cutoff point, Ki67 by RT-PCR had shown potential as a prognostic biomarker in HR+/HER2- early breast cancer.

CYP2D6*3 (A2549del), *4 (G1846A), *10 (C100T) and *17 (C1023T) genetic polymorphisms in Iranian breast cancer patients treated with adjuvant tamoxifen

There is controversy regarding the efficacy of tamoxifen in breast cancer patients who are carriers of cytochrome P450 2D6 (CYP2D6) gene polymorphisms. Poor metabolizer genotypes may not fully convert tamoxifen to its active metabolite endoxifen and thus have less exposure to anti-estrogen therapy. The present study was conducted to identify the prevalence of CYP2D6 genotypes among Iranian breast cancer patients. A total of 84 estrogen receptor-positive breast cancer patients treated at a referral center in the north of Iran were examined. A peripheral blood sample was obtained from each patient to determine the presence of *3, *4, *10 and *17 single nucleotide polymorphisms of the CYP2D6 gene by polymerase chain reaction-based restriction fragment-length polymorphism analysis. Of the four genotypes assessed, CYP2D6*4 was the most common variant and was identified in 41 (48.8%) patients as heterozygous (G/A) and 3 (3.6%) as homozygous (A/A) alleles. CYP2D6*10 heterozygous mutated alleles (C/T) were also a common genotype that presented in 22 (26.2%) of the study subjects. Variant *17 was less common and was detected only as heterozygous (C/T) in 3 patients (3.6%). No CYP2D6*3 heterozygous or homozygous mutated alleles were observed. In conclusion, the frequency of the CYP2D6 nonfunctional alleles *4 and *10 appeared relatively high in Iranian patients with hormone-sensitive breast cancer. This finding may affect the selection of an optimal hormone therapy, as patients with low CYP2D6 pathway activity may not sufficiently convert tamoxifen to its active metabolite endoxifen.

Clinical and molecular aspects of breast cancer: Targets and therapies

Breast Cancer is a complex disease characterized by the occurrence of multiple molecular alterations. Currently, some molecular markers are in use for breast cancer diagnostic, prognostic, and predictive purposes. Thus, genetic signatures are available for improving the decision-making. The biomarkers are also essential as therapeutic approaches, but many questions remain due to the lack of efficacy on breast cancer treatment, mainly for triple-negative breast cancer subtype. Since the genetic profile of breast cancer can also be related to different ethnic groups and geographic areas, the reference populations of the genetic assays and clinical trials need to include a broader population beyond the European and North American patients. In this review, we analyzed the current and potential molecular markers that could help to improve the strategies for breast cancer therapy.

Concordance between Immunohistochemistry and Microarray Gene Expression Profiling for Estrogen Receptor, Progesterone Receptor, and HER2 Receptor Statuses in Breast Cancer Patients in Lebanon

Introduction

Accurate evaluation of estrogen and progesterone receptors and HER2 is critical when diagnosing invasive breast cancer for optimal treatment. The current evaluation method is via immunohistochemistry (IHC). In this paper, we compared results of ER, PR, and HER2 from microarray gene expression to IHC in 81 fresh breast cancer specimens.

Methods

Gene expression profiling was performed using the GeneChip Human Genome U133 Plus 2.0 arrays (Affymetrix Inc). Immunohistochemical staining for estrogen receptor, progesterone receptor, and HER2 status was performed using standard methods at a CAP-accredited pathology laboratory. Concordance rates, agreement measures, and kappa scores were calculated for both methods.

Results

For ER, Kappa score was 0.918 (95% CI, 0.77.3-1.000) and concordance rate was 97.5% (95% CI, 91.4%-99.7%). For PR, Kappa score was 0.652 (95% CI, 0.405-0.849) and concordance rate was 86.4% (95% CI, 77%-93%). For HER2, Kappa score was 0.709 (95% CI, 0.428-0.916) and concordance rate was 97.5% (95% CI, 91.4%-99.7%).

Conclusion

Our results are in line with the available evidence with the concordance rate being the lowest for the progesterone receptor. In general, microarray gene expression and IHC proved to have high concordance rates. Several factors can increase the discordance rate such as differences in sample processing.

Clinical Value of RNA Sequencing-Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network-Breast Initiative

Purpose

In early breast cancer (BC), five conventional biomarkers-estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), Ki67, and Nottingham histologic grade (NHG)-are used to determine prognosis and treatment. We aimed to develop classifiers for these biomarkers that were based on tumor mRNA sequencing (RNA-seq), compare classification performance, and test whether such predictors could add value for risk stratification.

Methods

In total, 3,678 patients with BC were studied. For 405 tumors, a comprehensive multi-rater histopathologic evaluation was performed. Using RNA-seq data, single-gene classifiers and multigene classifiers (MGCs) were trained on consensus histopathology labels. Trained classifiers were tested on a prospective population-based series of 3,273 BCs that included a median follow-up of 52 months (Sweden Cancerome Analysis Network-Breast [SCAN-B], ClinicalTrials.gov identifier: NCT02306096), and results were evaluated by agreement statistics and Kaplan-Meier and Cox survival analyses.

Results

Pathologist concordance was high for ER, PgR, and HER2 (average κ, 0.920, 0.891, and 0.899, respectively) but moderate for Ki67 and NHG (average κ, 0.734 and 0.581). Concordance between RNA-seq classifiers and histopathology for the independent cohort of 3,273 was similar to interpathologist concordance. Patients with discordant classifications, predicted as hormone responsive by histopathology but non-hormone responsive by MGC, had significantly inferior overall survival compared with patients who had concordant results. This extended to patients who received no adjuvant therapy (hazard ratio [HR], 3.19; 95% CI, 1.19 to 8.57), or endocrine therapy alone (HR, 2.64; 95% CI, 1.55 to 4.51). For cases identified as hormone responsive by histopathology and who received endocrine therapy alone, the MGC hormone-responsive classifier remained significant after multivariable adjustment (HR, 2.45; 95% CI, 1.39 to 4.34).

Conclusion

Classification error rates for RNA-seq-based classifiers for the five key BC biomarkers generally were equivalent to conventional histopathology. However, RNA-seq classifiers provided added clinical value in particular for tumors determined by histopathology to be hormone responsive but by RNA-seq to be hormone insensitive.

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.

Comparison of risk classification between EndoPredict and MammaPrint in ER-positive/HER2-negative primary invasive breast cancer

PURPOSE

To compare the concordance in risk classification between the EndoPredict and the MammaPrint scores obtained for the same cancer samples on 40 estrogen-receptor positive/HER2-negative breast carcinomas.

METHODS

Formalin-fixed, paraffin-embedded invasive breast carcinoma tissues that were previously analyzed with MammaPrint as part of routine care of the patients, and were classified as high-risk (20 patients) and low-risk (20 patients), were selected to be analyzed by the EndoPredict assay, a second generation gene expression test that combines expression of 8 genes (EP score) with two clinicopathological variables (tumor size and nodal status, EPclin score).

RESULTS

The EP score classified 15 patients as low-risk and 25 patients as high-risk. EPclin re-classified 5 of the 25 EP high-risk patients into low-risk, resulting in a total of 20 high-risk and 20 low-risk tumors. EP score and MammaPrint score were significantly correlated (p = 0.008). Twelve of 20 samples classified as low-risk by MammaPrint were also low-risk by EP score (60%). 17 of 20 MammaPrint high-risk tumors were also high-risk by EP score. The overall concordance between EP score and MammaPrint was 72.5% (κ = 0.45, (95% CI, 0.182 to 0.718)). EPclin score also correlated with MammaPrint results (p = 0.004). Discrepancies between both tests occurred in 10 cases: 5 MammaPrint low-risk patients were classified as EPclin high-risk and 5 high-risk MammaPrint were classified as low-risk by EPclin and overall concordance of 75% (κ = 0.5, (95% CI, 0.232 to 0.768)).

CONCLUSIONS

This pilot study demonstrates a limited concordance between MammaPrint and EndoPredict. Differences in results could be explained by the inclusion of different gene sets in each platform, the use of different methodology, and the inclusion of clinicopathological parameters, such as tumor size and nodal status, in the EndoPredict test.

[Validation and clinical application of MammaPrint® in patients with breast cancer]

BACKGROUND

In recent years, advances in molecular biology have resulted in innovations in breast cancer diagnostics and therapeutics. The development of genomics has revolutionized our understanding of this disease. MammaPrint^® was developed as a diagnostic tool to predict risk of breast cancer recurrence using the expression of 70 genes altering the clinicopathologic paradigm of selection of patients for adjuvant cytotoxic chemotherapy.

MATERIALS AND METHODS

A study of stage i-ii breast cancer patients on whom the MammaPrint^® genomic assay was performed.

RESULTS

The use of the MammaPrint^® assay was a decisive factor for the recommendation of adjuvant treatment with chemotherapy and/or hormone therapy in patients with high risk for relapse. In our group, the patients with low-risk have not presented local or systemic recurrences DISCUSSION: The determination of the genetic characteristics and its alterations in breast cancer, is fundamentally important for a better identification of risk, as well as a better selection of cancer therapy.

CONCLUSION

MammaPrint^® is an effective study to determine risk of recurrence of in early stage breast cancer.

Prognostic Value of MammaPrint® in Invasive Lobular Breast Cancer

BACKGROUND

MammaPrint® is a microarray-based gene expression test cleared by the US Food and Drug Administration to assess recurrence risk in early-stage breast cancer, aimed to guide physicians in making neoadjuvant and adjuvant treatment decisions. The increase in the incidence of invasive lobular carcinomas (ILCs) over the past decades and the modest representation of ILC in the MammaPrint development data set calls for a stratified survival analysis dedicated to this specific subgroup.

STUDY AIM

The current study aimed to validate the prognostic value of the MammaPrint test for breast cancer patients with early-stage ILCs.

MATERIALS AND METHODS

Univariate and multivariate survival associations for overall survival (OS), distant metastasis-free interval (DMFI), and distant metastasis-free survival (DMFS) were studied in a study population of 217 early-stage ILC breast cancer patients from five different clinical studies.

RESULTS AND DISCUSSION

A significant association between MammaPrint High Risk and poor clinical outcome was shown for OS, DMFI, and DMFS. A subanalysis was performed on the lymph node-negative study population. In the lymph node-negative study population, we report an up to 11 times higher change in the diagnosis of an event in the MammaPrint High Risk group. For DMFI, the reported hazard ratio is 11.1 (95% confidence interval = 2.3-53.0).

CONCLUSION

Study results validate MammaPrint as an independent factor for breast cancer patients with early-stage invasive lobular breast cancer. Hazard ratios up to 11 in multivariate analyses emphasize the independent value of MammaPrint, specifically in lymph node-negative ILC breast cancers.

Multimodal Assessment of Estrogen Receptor mRNA Profiles to Quantify Estrogen Pathway Activity in Breast Tumors

BACKGROUND

Molecular markers have transformed our understanding of the heterogeneity of breast cancer and have allowed the identification of genomic profiles of estrogen receptor (ER)-α signaling. However, our understanding of the transcriptional profiles of ER signaling remains inadequate. Therefore, we sought to identify the genomic indicators of ER pathway activity that could supplement traditional immunohistochemical (IHC) assessments of ER status to better understand ER signaling in the breast tumors of individual patients.

MATERIALS AND METHODS

We reduced ESR1 (gene encoding the ER-α protein) mRNA levels using small interfering RNA in ER⁺ MCF7 breast cancer cells and assayed for transcriptional changes using Affymetrix HG U133 Plus 2.0 arrays. We also compared 1034 ER⁺ and ER^- breast tumors from publicly available microarray data. The principal components of ER activity generated from these analyses and from other published estrogen signatures were compared with ESR1 expression, ER-α IHC, and patient survival.

RESULTS

Genes differentially expressed in both analyses were associated with ER-α IHC and ESR1 mRNA expression. They were also significantly enriched for estrogen-driven molecular pathways associated with ESR1, cyclin D1 (CCND1), MYC (v-myc avian myelocytomatosis viral oncogene homolog), and NFKB (nuclear factor kappa B). Despite their differing constituent genes, the principal components generated from these new analyses and from previously published ER-associated gene lists were all associated with each other and with the survival of patients with breast cancer treated with endocrine therapies.

CONCLUSION

A biomarker of ER-α pathway activity, generated using ESR1-responsive mRNAs in MCF7 cells, when used alongside ER-α IHC and ESR1 mRNA expression, could provide a method for further stratification of patients and add insight into ER pathway activity in these patients.

Adaptive Randomization of Veliparib-Carboplatin Treatment in Breast Cancer

BACKGROUND

The genetic and clinical heterogeneity of breast cancer makes the identification of effective therapies challenging. We designed I-SPY 2, a phase 2, multicenter, adaptively randomized trial to screen multiple experimental regimens in combination with standard neoadjuvant chemotherapy for breast cancer. The goal is to match experimental regimens with responding cancer subtypes. We report results for veliparib, a poly(ADP-ribose) polymerase (PARP) inhibitor, combined with carboplatin.

METHODS

In this ongoing trial, women are eligible for participation if they have stage II or III breast cancer with a tumor 2.5 cm or larger in diameter; cancers are categorized into eight biomarker subtypes on the basis of status with regard to human epidermal growth factor receptor 2 (HER2), hormone receptors, and a 70-gene assay. Patients undergo adaptive randomization within each biomarker subtype to receive regimens that have better performance than the standard therapy. Regimens are evaluated within 10 biomarker signatures (i.e., prospectively defined combinations of biomarker subtypes). Veliparib-carboplatin plus standard therapy was considered for HER2-negative tumors and was therefore evaluated in 3 signatures. The primary end point is pathological complete response. Tumor volume changes measured by magnetic resonance imaging during treatment are used to predict whether a patient will have a pathological complete response. Regimens move on from phase 2 if and when they have a high Bayesian predictive probability of success in a subsequent phase 3 neoadjuvant trial within the biomarker signature in which they performed well.

RESULTS

With regard to triple-negative breast cancer, veliparib-carboplatin had an 88% predicted probability of success in a phase 3 trial. A total of 72 patients were randomly assigned to receive veliparib-carboplatin, and 44 patients were concurrently assigned to receive control therapy; at the completion of chemotherapy, the estimated rates of pathological complete response in the triple-negative population were 51% (95% Bayesian probability interval [PI], 36 to 66%) in the veliparib-carboplatin group versus 26% (95% PI, 9 to 43%) in the control group. The toxicity of veliparib-carboplatin was greater than that of the control.

CONCLUSIONS

The process used in our trial showed that veliparib-carboplatin added to standard therapy resulted in higher rates of pathological complete response than standard therapy alone specifically in triple-negative breast cancer. (Funded by the QuantumLeap Healthcare Collaborative and others; I-SPY 2 TRIAL ClinicalTrials.gov number, NCT01042379.).

Adaptive Randomization of Neratinib in Early Breast Cancer

BACKGROUND

The heterogeneity of breast cancer makes identifying effective therapies challenging. The I-SPY 2 trial, a multicenter, adaptive phase 2 trial of neoadjuvant therapy for high-risk clinical stage II or III breast cancer, evaluated multiple new agents added to standard chemotherapy to assess the effects on rates of pathological complete response (i.e., absence of residual cancer in the breast or lymph nodes at the time of surgery).

METHODS

We used adaptive randomization to compare standard neoadjuvant chemotherapy plus the tyrosine kinase inhibitor neratinib with control. Eligible women were categorized according to eight biomarker subtypes on the basis of human epidermal growth factor receptor 2 (HER2) status, hormone-receptor status, and risk according to a 70-gene profile. Neratinib was evaluated against control with regard to 10 biomarker signatures (prospectively defined combinations of subtypes). The primary end point was pathological complete response. Volume changes on serial magnetic resonance imaging were used to assess the likelihood of such a response in each patient. Adaptive assignment to experimental groups within each disease subtype was based on Bayesian probabilities of the superiority of the treatment over control. Enrollment in the experimental group was stopped when the 85% Bayesian predictive probability of success in a confirmatory phase 3 trial of neoadjuvant therapy reached a prespecified threshold for any biomarker signature ("graduation"). Enrollment was stopped for futility if the probability fell to below 10% for every biomarker signature.

RESULTS

Neratinib reached the prespecified efficacy threshold with regard to the HER2-positive, hormone-receptor-negative signature. Among patients with HER2-positive, hormone-receptor-negative cancer, the mean estimated rate of pathological complete response was 56% (95% Bayesian probability interval [PI], 37 to 73%) among 115 patients in the neratinib group, as compared with 33% among 78 controls (95% PI, 11 to 54%). The final predictive probability of success in phase 3 testing was 79%.

CONCLUSIONS

Neratinib added to standard therapy was highly likely to result in higher rates of pathological complete response than standard chemotherapy with trastuzumab among patients with HER2-positive, hormone-receptor-negative breast cancer. (Funded by QuantumLeap Healthcare Collaborative and others; I-SPY 2 TRIAL ClinicalTrials.gov number, NCT01042379.).

Pattern of HER-2 Gene Amplification and Protein Expression in Benign, Borderline, and Malignant Ovarian Serous and Mucinous Neoplasms

Amplification of HER-2 gene and overexpression of HER-2 receptor play a significant role in the progression of a number of malignancies such as breast cancer. Trastuzumab (anti-HER-2 therapeutic agent) has been used successfully in treatment of breast cancer. The aim of this study was to assess the pattern of HER-2 gene amplification and of HER-2 receptor expression in a spectrum of serous and mucinous ovarian tumors to determine whether HER-2 is altered in these neoplasms similar to that occurring in breast cancer. Formalin-fixed paraffin-embedded microarray tissue sections from 212 specimens were stained with HER-2 antibody using immunohistochemistry and with anti-HER-2 DNA probe using chromogenic in situ hybridization. Specimens consisted of 65 benign tumors (50 serous and 15 mucinous), 26 borderline (13 serous and 13 mucinous), 73 malignant tumors (53 serous carcinoma and 20 mucinous carcinoma), 18 metastatic deposits (13 serous and 5 mucinous), in addition to 30 normal tissues (16 ovarian surface and 14 normal fallopian tube). HER-2 protein-positive expression was not detected in the normal or the benign tissues. Borderline neoplasms showed positive staining, but no overexpression. HER-2 overexpression was seen only in 4 carcinoma specimens: 1/53 (1.8%) primary serous carcinomas and 3/20 (15%) primary mucinous carcinomas. HER-2 gene amplification was seen in 4 specimens: 2 primary mucinous carcinomas and 2 malignant deposits of these 2 mucinous carcinomas. In conclusion, alteration of HER-2 was not detected in ovarian serous neoplasms; however, in mucinous carcinoma, HER-2 amplification and overexpression occur.

Estrogen-Receptor, Progesterone-Receptor and HER2 Status Determination in Invasive Breast Cancer. Concordance between Immuno-Histochemistry and MapQuant™ Microarray Based Assay

Background

Hormone receptor status and HER2 status are of critical interest in determining the prognosis of breast cancer patients. Their status is routinely assessed by immunohistochemistry (IHC). However, it is subject to intra-laboratory and inter-laboratory variability. The aim of our study was to compare the estrogen receptor, progesterone receptor and HER2 status as determined by the MapQuant™ test to the routine immuno-histochemical tests in early stage invasive breast cancer in a large comprehensive cancer center.

Patients and Methods

We retrospectively studied 163 invasive early-stage breast carcinoma with standard IHC status. The genomic status was determined using the MapQuant™ test providing the genomic grade index.

Results

We found only 4 tumours out of 161 (2.5%) with discrepant IHC and genomic results concerning ER status. The concordance rate between the two methods was 97.5% and the Cohen’s Kappa coefficient was 0.89.

Comparison between the MapQuant™ PR status and the PR IHC status gave more discrepancies. The concordance rate between the two methods was 91.4% and the Cohen’s Kappa coefficient was 0.74.

The HER2 MapQuant™ test was classified as « undetermined » in 2 out of 163 cases (1.2%). One HER2 IHC-negative tumour was found positive with a high HER2 MapQuant™ genomic score. The concordance rate between the two methods was 99.3% and the Cohen’s Kappa coefficient was 0.86.

Conclusion

Our results show that the MapQuant™ assay, based on mRNA expression assay, provides an objective and quantitative assessment of Estrogen receptor, Progesterone receptor and HER2 status in invasive breast cancer.

Discordant assessment of tumor biomarkers by histopathological and molecular assays in the EORTC randomized controlled 10041/BIG 03-04 MINDACT trial breast cancer : Intratumoral heterogeneity and DCIS or normal tissue components are unlikely to be the cause of discordance

Accurate identification of breast cancer patients most likely to benefit from adjuvant systemic therapies is crucial. Better understanding of differences between methods can lead to an improved ER, PgR, and HER-2 assessment. The purpose of this preplanned translational research is to investigate the correlation of central IHC/FISH assessments with microarray mRNA readouts of ER, PgR, and HER-2 status in the MINDACT trial and to determine if any discordance could be attributed to intratumoral heterogeneity or the DCIS and normal tissue components in the specimens. MINDACT is an international, prospective, randomized, phase III trial investigating the clinical utility of MammaPrint in selecting patients with early breast cancer for adjuvant chemotherapy (n = 6694 patients). Gene-expression data were obtained by TargetPrint; IHC and/or FISH were assessed centrally (n = 5788; 86 %). Macroscopic and microscopic evaluation of centrally submitted FFPE blocks identified 1427 cases for which the very same sample was submitted for gene-expression analysis. TargetPrint ER had a positive agreement of 98 %, and a negative agreement of 95 % with central pathology. Corresponding figures for PgR were 85 and 94 % and for HER-2 72 and 99 %. Agreement of mRNA versus central protein was not different when the same or a different portion of the tumor tissue was analyzed or when DCIS and/or normal tissue was included in the sample subjected to mRNA assays. This is the first large analysis to assess the discordance rate between protein and mRNA analysis of breast cancer markers, and to look into intratumoral heterogeneity, DCIS, or normal tissue components as a potential cause of discordance. The observed difference between mRNA and protein assessment for PgR and HER-2 needs further research; the present analysis does not support intratumoral heterogeneity or the DCIS and normal tissue components being likely causes of the discordance.

BRCA1-like signature in triple negative breast cancer: Molecular and clinical characterization reveals subgroups with therapeutic potential

Triple negative (TN) breast cancers make up some 15% of all breast cancers. Approximately 10-15% are mutant for the tumor suppressor, BRCA1. BRCA1 is required for homologous recombination-mediated DNA repair and deficiency results in genomic instability. BRCA1-mutated tumors have a specific pattern of genomic copy number aberrations that can be used to classify tumors as BRCA1-like or non-BRCA1-like. BRCA1 mutation, promoter methylation, BRCA1-like status and genome-wide expression data was determined for 112 TN breast cancer samples with long-term follow-up. Mutation status for 21 known DNA repair genes and PIK3CA was assessed. Gene expression and mutation frequency in BRCA1-like and non-BRCA1-like tumors were compared. Multivariate survival analysis was performed using the Cox proportional hazards model. BRCA1 germline mutation was identified in 10% of patients and 15% of tumors were BRCA1 promoter methylated. Fifty-five percent of tumors classified as BRCA1-like. The functions of genes significantly up-regulated in BRCA1-like tumors included cell cycle and DNA recombination and repair. TP53 was found to be frequently mutated in BRCA1-like (P < 0.05), while PIK3CA was frequently mutated in non-BRCA1-like tumors (P < 0.05). A significant association with worse prognosis was evident for patients with BRCA1-like tumors (adjusted HR = 3.32, 95% CI = 1.30-8.48, P = 0.01). TN tumors can be further divided into two major subgroups, BRCA1-like and non-BRCA1-like with different mutation and expression patterns and prognoses. Based on these molecular patterns, subgroups may be more sensitive to specific targeted agents such as PI3K or PARP inhibitors.

HER2 testing and its predictive utility in anti-HER2 breast cancer therapy

Breast cancer treatment is dependent on accurate pathologic diagnosis. HER2 testing is now universally recommended as part of evaluation of invasive breast cancer. HER2 testing is available via various slide and non-slide based assays, and interpretation of results continues to evolve. Herein we review these testing modalities and their incorporation into the 2013 ASCO/CAP guidelines. Once accurate HER2 status has been established the proper treatment based on recent clinical trials can be instituted.

Long non-coding RNA expression profiles predict metastasis in lymph node-negative breast cancer independently of traditional prognostic markers

INTRODUCTION

Patients with clinically and pathologically similar breast tumors often have very different outcomes and treatment responses. Current prognostic markers allocate the majority of breast cancer patients to the high-risk group, yielding high sensitivities in expense of specificities below 20%, leading to considerable overtreatment, especially in lymph node-negative patients. Seventy percent would be cured by surgery and radiotherapy alone in this group. Thus, precise and early indicators of metastasis are highly desirable to reduce overtreatment. Previous prognostic RNA-profiling studies have only focused on the protein-coding part of the genome, however the human genome contains thousands of long non-coding RNAs (lncRNAs) and this unexplored field possesses large potential for identification of novel prognostic markers.

METHODS

We evaluated lncRNA microarray data from 164 primary breast tumors from adjuvant naïve patients with a mean follow-up of 18 years. Eighty two patients who developed detectable distant metastasis were compared to 82 patients where no metastases were diagnosed. For validation, we determined the prognostic value of the lncRNA profiles by comparing the ability of the profiles to predict metastasis in two additional, previously-published, cohorts.

RESULTS

We showed that lncRNA profiles could distinguish metastatic patients from non-metastatic patients with sensitivities above 90% and specificities of 64-65%. Furthermore; classifications were independent of traditional prognostic markers and time to metastasis.

CONCLUSIONS

To our knowledge, this is the first study investigating the prognostic potential of lncRNA profiles. Our study suggest that lncRNA profiles provide additional prognostic information and may contribute to the identification of early breast cancer patients eligible for adjuvant therapy, as well as early breast cancer patients that could avoid unnecessary systemic adjuvant therapy. This study emphasizes the potential role of lncRNAs in breast cancer prognosis.

Quantification of HER family receptors in breast cancer

The clinical success of trastuzumab in breast cancer taught us that appropriate tumor evaluation is mandatory for the correct identification of patients eligible for targeted therapies. Although HER2 protein expression by immunohistochemistry (IHC) and gene amplification by fluorescence in situ hybridization (FISH) assays are routinely used to select patients to receive trastuzumab, both assays only partially predict response to the drug. In the case of epidermal growth factor receptor (EGFR), the link between the presence of the receptor or its amplification and response to anti-EGFR therapies could not be demonstrated. Even less is known for HER3 and HER4, mainly due to lack of robust and validated assays detecting these proteins. It is becoming evident that, besides FISH and IHC, we need better assays to quantify HER receptors and categorize the patients for individualized treatments. Here, we present the current available methodologies to measure HER family receptors and discuss the clinical implications of target quantification.

Transfer of clinically relevant gene expression signatures in breast cancer: from Affymetrix microarray to Illumina RNA-Sequencing technology

Background

Microarrays have revolutionized breast cancer (BC) research by enabling studies of gene expression on a transcriptome-wide scale. Recently, RNA-Sequencing (RNA-Seq) has emerged as an alternative for precise readouts of the transcriptome. To date, no study has compared the ability of the two technologies to quantify clinically relevant individual genes and microarray-derived gene expression signatures (GES) in a set of BC samples encompassing the known molecular BC’s subtypes. To accomplish this, the RNA from 57 BCs representing the four main molecular subtypes (triple negative, HER2 positive, luminal A, luminal B), was profiled with Affymetrix HG-U133 Plus 2.0 chips and sequenced using the Illumina HiSeq 2000 platform. The correlations of three clinically relevant BC genes, six molecular subtype classifiers, and a selection of 21 GES were evaluated.

Results

16,097 genes common to the two platforms were retained for downstream analysis. Gene-wise comparison of microarray and RNA-Seq data revealed that 52% had a Spearman’s correlation coefficient greater than 0.7 with highly correlated genes displaying significantly higher expression levels. We found excellent correlation between microarray and RNA-Seq for the estrogen receptor (ER; r_s = 0.973; 95% CI: 0.971-0.975), progesterone receptor (PgR; r_s = 0.95; 0.947-0.954), and human epidermal growth factor receptor 2 (HER2; r_s = 0.918; 0.912-0.923), while a few discordances between ER and PgR quantified by immunohistochemistry and RNA-Seq/microarray were observed. All the subtype classifiers evaluated agreed well (Cohen’s kappa coefficients >0.8) and all the proliferation-based GES showed excellent Spearman correlations between microarray and RNA-Seq (all r_s >0.965). Immune-, stroma- and pathway-based GES showed a lower correlation relative to prognostic signatures (all r_s >0.6).

Conclusions

To our knowledge, this is the first study to report a systematic comparison of RNA-Seq to microarray for the evaluation of single genes and GES clinically relevant to BC. According to our results, the vast majority of single gene biomarkers and well-established GES can be reliably evaluated using the RNA-Seq technology.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1008) contains supplementary material, which is available to authorized users.

Breast cancer prognostic biomarker using attractor metagenes and the FGD3-SUSD3 metagene

BACKGROUND

The winning model of the Sage Bionetworks/DREAM Breast Cancer Prognosis Challenge made use of several molecular features, called attractor metagenes, as well as another metagene defined by the average expression level of the two genes FGD3 and SUSD3. This is a follow-up study toward developing a breast cancer prognostic test derived from and improving upon that model.

METHODS

We designed a feature selector facility calculating the prognostic scores of combinations of features, including those that we had used earlier, as well as those used in existing breast cancer biomarker assays, identifying the optimal selection of features for the test.

RESULTS

The resulting test, called BCAM (Breast Cancer Attractor Metagenes), is universally applicable to all clinical subtypes and stages of breast cancer and does not make any use of breast cancer molecular subtype or hormonal status information, none of which provided additional prognostic value. BCAM is composed of several molecular features: the breast cancer-specific FGD3-SUSD3 metagene, four attractor metagenes present in multiple cancer types (CIN, MES, LYM, and END), three additional individual genes (CD68, DNAJB9, and CXCL12), tumor size, and the number of positive lymph nodes.

CONCLUSIONS

Our analysis leads to the unexpected and remarkable suggestion that ER, PR, and HER2 status, or molecular subtype classification, do not provide additional prognostic value when the values of the FGD3-SUSD3 and attractor metagenes are taken into consideration.

IMPACT

Our results suggest that BCAM's prognostic predictions show potential to outperform those resulting from existing breast cancer biomarker assays.

High concordance of protein (by IHC), gene (by FISH; HER2 only), and microarray readout (by TargetPrint) of ER, PgR, and HER2: results from the EORTC 10041/BIG 03-04 MINDACT trial

BACKGROUND

To investigate the correlation of TargetPrint with local and central immunohistochemistry/fluorescence in situ hybridization assessment of estrogen (ER), progesterone (PgR), and human epidermal growth factor receptor 2 (HER2) in the first 800 patients enrolled in the MINDACT trial.

PATIENTS AND METHODS

Data from local (N = 800) and central (N = 626) assessments of receptor status were collected and compared with TargetPrint results.

RESULTS

For ER, the positive agreement (the percentage of central pathology positive assessments that were also TargetPrint/local laboratory positive) for TargetPrint in comparison to centralized assessment was 98% with a negative agreement (the percentage of central pathology negative assessments that were also TargetPrint/local laboratory negative) of 96%. For PgR, the positive agreement was 83% with a negative agreement of 92%. For HER2, the positive agreement was 75% with a negative agreement of 99%. Even though the local assessment showed higher positive agreement for PgR (89%) and higher positive agreement for HER2 (85%), the range of discordant local versus central assessments were as high as 6.7% for ER, 12.9% for PgR, and 4.3% for HER2.

CONCLUSION

TargetPrint and local assessment of ER, PgR, and HER2 show high concordance with central assessment in the first 800 MINDACT patients. However, there are concerns about the higher discordance rates for some local sites. TargetPrint can improve the reliability of hormone receptor and HER2 testing for those centers with a lower rate of concordance with the reference laboratory, with the limitation of a positive agreement of 75% for HER2. TargetPrint consequently has important implications for treatment decisions in clinical practice and is a reliable alternative to local assessment for ER.

CLINICAL TRIALS NUMBER

NCT00433589.

Study assessing the quality of quantification of estrogen receptor protein expression by immunohistochemistry and gene expression in breast cancer

Although immunohistochemistry (IHC) is a widely used technique to classify tumors in ER-positive versus ER-negative ones, interlab variabilities can occur. This study aims to investigate the influences of preanalytical and analytical factors on IHC results. For this purpose, the different steps of the preparation of IHC sections and scoring procedures were compared between two participating laboratories and a central lab. There was a significant positive correlation between the IHC results of the participating laboratories and those of the central lab (correlation coefficient > 0.600; P<0.05). Nevertheless, some discordant cases for immunostaining (5.3% for ER and 5.6% for PR) and for scoring (10.5% for PR) occur at site 1. Comparing IHC results with ESR1 gene expression results revealed a significant positive correlation (correlation coefficients > 0.769; P<0.05). PCR results of ER target genes showed some heterogeneity in the ER-signalling pathway. These results suggest that differences in the IHC procedure between these laboratories did not have a big influence on the end result. Nevertheless, discordant cases caused by preanalytical and analytical lab-specific procedures have been identified.

Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update

PURPOSE

To update the American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guideline recommendations for human epidermal growth factor receptor 2 (HER2) testing in breast cancer to improve the accuracy of HER2 testing and its utility as a predictive marker in invasive breast cancer.

METHODS

ASCO/CAP convened an Update Committee that included coauthors of the 2007 guideline to conduct a systematic literature review and update recommendations for optimal HER2 testing.

RESULTS

The Update Committee identified criteria and areas requiring clarification to improve the accuracy of HER2 testing by immunohistochemistry (IHC) or in situ hybridization (ISH). The guideline was reviewed and approved by both organizations.

RECOMMENDATIONS

The Update Committee recommends that HER2 status (HER2 negative or positive) be determined in all patients with invasive (early stage or recurrence) breast cancer on the basis of one or more HER2 test results (negative, equivocal, or positive). Testing criteria define HER2-positive status when (on observing within an area of tumor that amounts to >10% of contiguous and homogeneous tumor cells) there is evidence of protein overexpression (IHC) or gene amplification (HER2 copy number or HER2/CEP17 ratio by ISH based on counting at least 20 cells within the area). If results are equivocal (revised criteria), reflex testing should be performed using an alternative assay (IHC or ISH). Repeat testing should be considered if results seem discordant with other histopathologic findings. Laboratories should demonstrate high concordance with a validated HER2 test on a sufficiently large and representative set of specimens. Testing must be performed in a laboratory accredited by CAP or another accrediting entity. The Update Committee urges providers and health systems to cooperate to ensure the highest quality testing.

Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update

PURPOSE

To update the American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guideline recommendations for human epidermal growth factor receptor 2 (HER2) testing in breast cancer to improve the accuracy of HER2 testing and its utility as a predictive marker in invasive breast cancer.

METHODS

ASCO/CAP convened an Update Committee that included coauthors of the 2007 guideline to conduct a systematic literature review and update recommendations for optimal HER2 testing.

RESULTS

The Update Committee identified criteria and areas requiring clarification to improve the accuracy of HER2 testing by immunohistochemistry (IHC) or in situ hybridization (ISH). The guideline was reviewed and approved by both organizations.

RECOMMENDATIONS

The Update Committee recommends that HER2 status (HER2 negative or positive) be determined in all patients with invasive (early stage or recurrence) breast cancer on the basis of one or more HER2 test results (negative, equivocal, or positive). Testing criteria define HER2-positive status when (on observing within an area of tumor that amounts to > 10% of contiguous and homogeneous tumor cells) there is evidence of protein overexpression (IHC) or gene amplification (HER2 copy number or HER2/CEP17 ratio by ISH based on counting at least 20 cells within the area). If results are equivocal (revised criteria), reflex testing should be performed using an alternative assay (IHC or ISH). Repeat testing should be considered if results seem discordant with other histopathologic findings. Laboratories should demonstrate high concordance with a validated HER2 test on a sufficiently large and representative set of specimens. Testing must be performed in a laboratory accredited by CAP or another accrediting entity. The Update Committee urges providers and health systems to cooperate to ensure the highest quality testing. This guideline was developed through a collaboration between the American Society of Clinical Oncology and the College of American Pathologists and has been published jointly by invitation and consent in both Journal of Clinical Oncology and the Archives of Pathology & Laboratory Medicine.

Improving Pathological Assessment of Breast Cancer by Employing Array-Based Transcriptome Analysis

Breast cancer research has paved the way of personalized oncology with the introduction of hormonal therapy and the measurement of estrogen receptor as the first widely accepted clinical biomarker. The expression of another receptor—HER2/ERBB2/neu—was initially a sign of worse prognosis, but targeted therapy has granted improved outcome for these patients so that today HER2 positive patients have better prognosis than HER2 negative patients. Later, the introduction of multigene assays provided the pathologists with an unbiased assessment of the tumors’ molecular fingerprint. The recent FDA approval of complete microarray pipelines has opened new possibilities for the objective classification of breast cancer samples. Here we review the applications of microarrays for determining ER and HER2 status, molecular subtypes as well as predicting prognosis and grade for breast cancer patients. An open question remains the role of single genes within such signatures. Openly available microarray datasets enable the execution of an independent cross-validation of new marker and signature candidates. In summary, we review the current state regarding clinical applications of microarrays in breast cancer molecular pathology.