Genomic Alterations in Sporadic Synchronous Primary Breast Cancer Using Array and Metaphase Comparative Genomic Hybridization
Bibliographic record
Abstract
Synchronous primary breast cancer describes the occurrence of multiple tumors affecting one or both breasts at initial diagnosis. This provides a unique opportunity to identify tissue-specific genomic markers that characterize each tumor while controlling for the individual genetic background of a patient. The aim of this study was to examine the genomic alterations and degree of similarity between synchronous cancers. Using metaphase comparative genomic hybridization and array comparative genomic hybridization (aCGH), the genomic alterations of 23 synchronous breast cancers from 10 patients were examined at both chromosomal and gene levels. Synchronous breast cancers, when compared to their matched counterparts, were found to have a common core set of genetic alterations, with additional unique changes present in each. They also frequently exhibited features distinct from the more usual solitary primary breast cancers. The most frequent genomic alterations included chromosomal gains of 1q, 3p, 4q, and 8q, and losses of 11q, 12q, 16q, and 17p. aCGH identified copy number amplification in regions that are present in all 23 tumor samples, including 1p31.3-1p32.3 harboring JAK1. Our findings suggest that synchronous primary breast cancers represent a unique type of breast cancer and, at least in some instances, one tumor may give rise to the other.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".