HER-2 gene amplification in circulating tumor cells (CTCs): Concordance with amplification status in primary breast cancers and metastatic lesions
Bibliographic record
Abstract
e12006 Background: Recent studies have suggested a significant incidence (10%-30%) of discordance in HER-2 expression between metastatic lesions and the primary breast cancer (BC) which can result in inappropriate treatment recommendations. Biopsies of recurrent BC can aid in determining the expression but are often painful, costly, or cause delays in therapy. We initiated a study with the objective to determine and compare the molecular characteristics of the primary tumor, CTCs and metastases to assess whether the assessment of HER-2 gene amplification status in CTCs by FISH analysis could be used to determine treatment. Methods: After consent, patients with metastatic BC were enrolled, peripheral blood was collected (5 cc-10 cc), metastases were biopsied and HER-2 expression was determined. Blood samples were used for the CTC assay. We performed the CTC enrichment assay using a combination of anti CK and anti-EpCAM. The criteria for CTCs were: positive for cytokeratins 8, 18, 19, positive for DAPI and negative for CD45. Slides were scanned for CTCs using the Ariol system. When a CTC was identified the slide was reused for HER-2 FISH staining using the PathVysion HER-2 DNA Probe Kit. Initial attempts of FISH on CTCs took 48 hours to complete; to hasten the process, the second scan for FISH was done only on selected areas and the images for CTCs and FISH analysis were fused to obtain FISH images on a specific CTCs resulting in a 1 hour process. Results: To date 58 samples were collected, 40 of which had CTCs. At present, biopsies are being assessed and compared to the primary lesion in the initial 20 cases. Conclusions: FISH analysis of CTCs is a feasible technique and may be used to assess the specific molecular characteristics of breast cancer. Whether their HER-2 status reflects the metastatic or primary tumor is still unclear but is being determined and may have useful clinical application. No significant financial relationships to disclose.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".