Genomic alterations in primary breast cancers compared with their sentinel and more distal lymph node metastases: An aCGH study
Bibliographic record
Abstract
Metastatic potential of breast cancer may be associated with specific genomic alterations and the earliest metastases are likely to be found in the sentinel lymph nodes (SLN). Using array comparative genomic hybridization (aCGH), we compared the genomes of primary breast invasive duct carcinomas (IDCs), their sentinel and more distal lymph node metastases, and IDCs without nodal metastasis. Thirty-three samples from 22 patients with IDC were subjected to aCGH: 8 IDC samples from patients without lymph node metastasis, 11 IDCs associated with SLN metastases out of which 7 had paired samples of metastases, and 14 samples of lymph node metastases out of which 8 were sentinel-distal pairs from 4 patients. aCGH data were analyzed by correlation of genomic profiles, cluster analysis, segmentation, and peak identification. Quantitative real-time PCR was used for data validation. We observed high genomic similarity between primary tumors and their nodal metastases as well as between metastases to the sentinel and distal lymph nodes. Several recurrent alterations were detected preferentially in IDC associated with SLN metastases compared to IDCs without metastasis. Amplification within the 17q24.1-24.2(59.96-62.76 Mb) region was associated with presence of sentinel or distal lymph node metastases; larger tumor size and higher histological grade. In our samples, there were genomic events associated with metastatic progression, which could be detected in both primary tumors and LN metastases. Gain on 17q24.1-24.2 is a candidate region for further testing as a predictor of nodal metastasis.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".