PGDS, A Novel Technique Combining Chromogenic In Situ Hybridization and Immunohistochemistry for the Assessment of ErbB2 (HER2/neu) Status in Breast Cancer
Bibliographic record
Abstract
Given the important prognostic and predictive utility of v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 (ErbB2) [human epidermal growth factor receptor-2 (HER2/neu)] in breast cancer, it is recommended that ErbB2 testing be performed on all invasive breast cancers at the time of diagnosis. A consensus, however, has not yet been reached as to the optimal method of evaluating ErbB2 status. Immunohistochemistry to detect protein overexpression and fluorescence in situ hybridization (FISH) to detect ErbB2 gene amplification are the most frequently used methods. As no one detection method fulfills all necessary requirements of reliability, reproducibility, and ease of use, we developed a novel approach in the form of a simple assay we refer to as protein and gene double staining (PGDS) which simultaneously evaluates protein overexpression and gene amplification by combining immunohistochemistry with chromogenic in situ hybridization (CISH). A total of 134 invasive breast carcinomas, including 81 cases with a full-face section and 53 cases included in a tissue microarray (TMA), were assessed by PGDS, and the results were correlated with ErbB2 gene amplification status as determined by FISH. ErbB2 gene copy number determined by CISH analysis in the PGDS assay showed excellent concordance with that of FISH (correlation coefficient 0.82; P<0.001 with full-face section cases, and 0.98; P<0.001 with cases in a TMA). The overall concordance rate for gene amplification status between PGDS and FISH was 90.12% in cases with a full-face section and 92.45% with TMA cases. Perfect correlation was seen between the PGDS assay and FISH in cases that were considered either nonamplified or highly amplified by the dual assay. Of the 17 cases that showed low amplification by PGDS, 5 were classified as nonamplified by FISH. Correction for chromosome 17 copy number in the FISH assessment contributed to the discordance between CISH and FISH results. This newly developed PGDS method represents a novel approach to ErbB2 status determination that combines the assessment of both protein overexpression and gene amplification in one simple assay. It is likely that this assay will aid in immunohistochemical calibration and will also increase the sensitivity and specificity of ErbB2 testing.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".