Evaluation of cell-line-derived xenograft tumours as controls for immunohistochemical testing for ER and PR
Bibliographic record
Abstract
Quality control (QC) for immunohistochemistry (IHC) analysis routinely incorporates archived specimens for on-slide control material. We have assessed the utility of cell-line-derived xenograft (CDX) tumours for QC in breast estrogen receptor (ER) and progesterone receptor (PR) biomarker testing. Immunoblot and IHC analyses were used to select cell lines with different steady-state levels of ER and PR expression. CDX tumours all demonstrated consistent and comparable expression of ER and PR with corresponding cell lines from which they were derived. Three pathologists experienced in breast biomarker reporting scored tumours from different locations on mammary fat pads to determine reproducibility. Tumours from different locations were consistently scored as identical, and the CDX tumours representing different levels of biomarker expression were similar to patient-derived controls. Pathologists could not consistently distinguish CDX tumours from patient-derived controls, suggesting that within the appropriate quality management setting, CDX tumours may serve as control material for reporting purposes.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".