BackgroundThe eligibility of breast cancer patients for human epidermal growth factor receptor 2 (HER2)-directed therapies is determined by the HER2 gene amplification and/or HER2 protein overexpression status of the breast tumor as determined by in situ hybridization (ISH) or immunohistochemistry (IHC), respectively. Our objective was to combine the US Food and Drug Administration (FDA)-approved HER2 & chromosome 17 centromere (CEN17) brightfield ISH (BISH) and HER2 IHC assays into a single automated HER2 gene-protein assay allowing simultaneous detection of all three targets in a single tissue section.MethodsThe HER2 gene-protein assay was optimized using formalin-fixed, paraffin-embedded (FFPE) samples of the xenograft tumors MCF7 [HER2 negative (non-amplified gene, protein negative)] and Calu-3 [HER2 positive (amplified gene, protein positive)]. HER2 IHC was performed using a rabbit monoclonal anti-HER2 antibody (clone 4B5) and a conventional 3,3'-diaminobenzidine IHC detection. The HER2 & CEN17 BISH signals were visualized using horseradish peroxidase-based silver and alkaline phosphatase-based red detection systems, respectively with a cocktail of 2,4-dinitrophenyl-labeled HER2 and digoxigenin-labeled CEN17 probes. The performance of the gene-protein assay on tissue microarray slides containing 189 randomly selected FFPE clinical breast cancer tissue cores was compared to that of the separate HER2 IHC and HER2 & CEN17 BISH assays.ResultsHER2 protein detection was optimal when the HER2 IHC protocol was used before (rather than after) the BISH protocol. The sequential use of HER2 IHC and HER2 & CEN17 BISH detection steps on FFPE xenograft tumor sections appropriately co-localized the HER2 protein, HER2 gene, and CEN17 signals after mitigating the silver background staining by using a naphthol phosphate-containing hybridization buffer for the hybridization step. The HER2 protein and HER2 gene status obtained using the multiplex HER2 gene-protein assay demonstrated high concordance with those obtained using the separate HER2 IHC and HER2 & CEN17 BISH assays, respectively.ConclusionsWe have developed a protocol that allows simultaneous visualization of the HER2 IHC and HER2 & CEN17 BISH targets. This automated protocol facilitated the determination of HER2 protein and HER2 gene status in randomly selected breast cancer samples, particularly in cases that were equivocal or exhibited tumor heterogeneity. The HER2 gene-protein assay produced results virtually equivalent to those of the single FDA-approved HER2 IHC and HER2 & CEN17 BISH assays.Virtual slidesThe virtual slides for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/2041964038705297

Introduction Ki-67 labeling index assessed by immunohistochemical assays has been shown useful in assessing the risk of recurrence for estrogen receptor (ER)-positive HER2-negative breast cancers (BC) and distinguishing Luminal Alike from Luminal B-like tumors. We aimed to assess the performance of the Ventana CONFIRM anti-Ki-67 (30-9) Rabbit Monoclonal Primary Antibody. Methods We constructed a case-cohort design based on a random sample (n = 679) of all patients operated on for a first primary, non-metastatic, ER-positive, HER2-negative BC at the European Institute of Oncology (IEO) Milan, Italy during 1998-2002 and all additional patients (n = 303) operated during the same period, who developed an event (metastasis in distant organs or death due to BC as primary event) and were not included in the previous subset. Multivariable Cox proportional hazards regression with inverse subcohort sampling probability weighting was used to evaluate the risk of event according to Ki-67 (30-9) and derived intrinsic molecular subtype, using previously defined cutoff values, i.e., respectively 14% and 20%. Results Ki-67 was < 14% in 318 patients (32.4%), comprised between 14 and 19% in 245 patients (24.9%) and ≥ 20 in 419 patients (42.7%). At multivariable analysis, the risk of developing distant disease was 1.88 (95% CI 1.20-2.93; P = 0.006) for those with Ki-67 comprised between 14 and 19%, and 3.06 (95% CI 1.93-4.84; P < 0.0001) for those with Ki-67 ≥ 20% compared to those with Ki-67 < 14%. Patients with Luminal B-like BC had an approximate twofold risk of developing distant disease (HR = 1.91; 95% CI 1.35-2.71; P = 0.0003) than patients with Luminal Alike BC defined using Ki-67 (30-9). Conclusions Ki-67 evaluation using the 30-9 rabbit monoclonal primary antibody was able to stratify patients with ERpositive HER2-negative BC into prognostically distinct groups. Ki-67 assessment, with strict adherence to the international recommendations, should be included among the clinically useful biological parameters for the best treatment of patients with BC.

Pathologists have had increasing responsibility for quantitating immunohistochemistry (IHC) biomarkers with the expectation of high between-reader reproducibility due to clinical decision-making especially for patient therapy. Digital imaging-based quantitation of IHC clinical slides offers a potential aid for improvement; however, its clinical adoption is limited potentially due to a conventional field-of-view annotation approach. In this study, we implemented a novel solely morphology-based whole tumor section annotation strategy to maximize image analysis quantitation results between readers. We first compare the field-of-view image analysis annotation approach to digital and manual-based modalities across multiple clinical studies (~120 cases per study) and biomarkers (ER, PR, HER2, Ki-67, and p53 IHC) and then compare a subset of the same cases (~40 cases each from the ER, PR, HER2, and Ki-67 studies) using whole tumor section annotation approach to understand incremental value of all modalities. Between-reader results for each biomarker in relation to conventional scoring modalities showed similar concordance as manual read: ER field-of-view image analysis: 95.3% (95% CI 92.0-98.2%) vs digital read: 92.0% (87.8-95.8%) vs manual read: 94.9% (91.4-97.8%); PR field-of-view image analysis: 94.1% (90.3-97.2%) vs digital read: 94.0% (90.2-97.1%) vs manual read: 94.4% (90.9-97.2%); Ki-67 field-of-view image analysis: 86.8% (82.1-91.4%) vs digital read: 76.6% (70.9-82.2%) vs manual read: 85.6% (80.4-90.4%); p53 field-of-view image analysis: 81.7% (76.4-86.8%) vs digital read: 80.6% (75.0-86.0%) vs manual read: 78.8% (72.2-83.3%); and HER2 field-of-view image analysis: 93.8% (90.0-97.2%) vs digital read: 91.0 (86.6-94.9%) vs manual read: 87.2% (82.1-91.9%). Subset implementation and analysis on the same cases using whole tumor section image analysis approach showed significant improvement between pathologists over field-of-view image analysis and manual read (HER2 100% (97-100%), P=0.013 field-of-view image analysis and 0.013 manual read; Ki-67 100% (96.9-100%), P=0.040 and 0.012; ER 98.3% (94.1-99.5%), p=0.232 and 0.181; and PR 96.6% (91.5-98.7%), p=0.012 and 0.257). Overall, whole tumor section image analysis significantly improves between-pathologist's reproducibility and is the optimal approach for clinical-based image analysis algorithms.

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