Real-time PCR complements immunohistochemistry in the determination of HER-2/neu status in breast cancer
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Bibliographic record
Abstract
BACKGROUND: The clinical benefit of determining the status of HER-2/neu amplification in breast cancer patients is well accepted. Although immunohistochemistry (IHC) is the most frequently used method to assess the over-expression of HER-2 protein, fluorescent in-situ hybridization (FISH) is recognized as the "gold standard" for the determining of HER-2/neu status. The greatest discordance between the two methods occurs among breast tumors that receive an indeterminate IHC score of 2+. More recently, a real-time polymerase chain reaction (PCR) assay using the LightCycler(R) has been developed for quantifying HER-2/neu gene amplification. In this study, we evaluated the sensitivity and specificity of a commercially available LightCycler assay as it compares to FISH. To determine whether this assay provides an accurate alternative for the determination of HER-2/neu status, we focused primarily on tumors that were deemed indeterminate or borderline status by IHC. METHODS: Thirty-nine breast tumors receiving an IHC score of 2+ were evaluated by both FISH and LightCycler(R) technologies in order to determine whether quantitative real-time PCR provides an accurate alternative for the determination of HER-2/neu status. RESULTS: We found a high concordance (92%) between FISH and real-time PCR results. We also observed that 10% of these tumors were positive for gene amplification by both FISH and real-time PCR. CONCLUSION: The data show that the results obtained for the gene amplification of HER-2/neu by real-time PCR on the LightCycler instrument is comparable to results obtained by FISH. These results therefore suggest that real-time PCR analysis, using the LightCycler, is a viable alternative to FISH for reassessing breast tumors which receive an IHC score of 2+, and that a combined IHC and real-time PCR approach for the determination of HER-2 status in breast cancer patients may be an effective and efficient strategy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it