Abstract P5-07-07: Fluorescence quantitative image analysis of HER2 evaluation against current clinical HER2 assays in breast cancer testing
Bibliographic record
Abstract
Abstract BACKGROUND: Presently, therapy for treatment of breast cancer is based on the evaluation of formalin fixed, paraffin embedded (FFPE) pathological specimens using a combination of immunohistochemistry (IHC) and gene copy assessment by in-situ hybridization (-ISH) techniques, following current testing guidelines from the American Society of Clinical Oncology (ASCO) and the College of American Pathologists (CAP). Patients with specimens found to have marked overexpression and amplification of the human epidermal receptor 2 (HER2) are approved for treatment with trastuzumab. While IHC and –ISH assays represent the current clinical standard, these assays are subject to pre-analytical variation, which could lead to false negative results. There are novel laboratory technologies which may improve the accuracy of HER2 measurements and lead to improved patient selection for therapy. AIM: In this comparative study, we assessed the utility of testing HER2 expression by the fluorescence IHC using AQUA® - a novel computer assisted platform to enable quantitative assessment of protein expression in FFPE tissue specimens – against current clinical assays (IHC and –ISH). METHODS: Local cases from 2008-2010 clinically evaluated for HER2 were identified for further pathological review. FFPE tissue specimens were retrieved from a total of 207 cases with sufficient tumor present, and placed into a tissue microarray (TMA). TMA sections underwent assessment for IHC HER2 (Clone 4B5, Ventana), HER2/Chromosome 17 gene copy number (Inform HER2 dual-ISH DNA Probe Cocktail Assay, Ventana), and fluorescence IHC (Clone SP3, Thermo Fisher). RESULTS: HER2 results were available for 142 patients for IHC, and 134 patients for dual–ISH and fluorescence IHC. A comparison of the current clinical methods revealed 11 discordant cases. The average median fluorescence IHC cytoplasmic HER2 expression (cAQUA) was found to be 225.65, (70.65-419.95). HER2 cAQUA was strongly correlated with dual-ISH, and cases with low level amplification had low cAQUA expression. There were cases having high cAQUA expression that did not show amplification by dual-ISH. Only a few amplfied cases demonstrated low cAQUA expression. Dichotomizing cAQUA at the 256 showed an improvement of the receiver operating characteristic compared to the clinical HER2 IHC assay (cAQUA=0.903, p<0.001; IHC=0.833, p=0.006). CONCLUSIONS: Measurement of HER2 expression using human interpretation can be imprecise as there is still some discordance between HER2 IHC and dual-ISH assays. Evaluation of HER2 protein expression using the novel AQUA assay showed correlation with IHC and dual-ISH, and AQUA may present a more precise way to quantify HER2 protein expression. HER2 cAQUA used a different antibody clone than the clinical IHC assay; however, previous studies have shown strong correlation between these two antibodies. The AQUA assay may identify a previously unrecognized group of breast cancers with elevated HER2 expression. The significance of this finding requires further investigation, particularly in regards with cAQUA HER2 serving as a marker for response to anti-HER2 therapy. Citation Format: Kornaga EN, Feng X, Klimowicz AC, Dean ML, Guggisberg N, Morris DG, Magliocco AM. Fluorescence quantitative image analysis of HER2 evaluation against current clinical HER2 assays in breast cancer testing. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-07-07.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".