Microglandular adenosis or microglandular adenoma? A molecular genetic analysis of a case associated with atypia and invasive carcinoma
Bibliographic record
Abstract
AIMS: Microglandular adenosis (MGA) is a rare breast lesion, which has long been considered to be hyperplastic. However, atypical forms of MGA (AMGA) and invasive carcinomas arising in the background of MGA are recorded. Recent studies have suggested that MGA may be a non-obligate precursor of invasive carcinomas that are negative for hormone receptors and lack HER-2 overexpression (triple-negative phenotype). The aim of this study was to determine whether MGA is clonal and whether it harbours chromosomal aberrations similar to those found in matched invasive ductal carcinoma of no special type (IDC-NST). METHODS AND RESULTS: We report on a case comprising MGA, AMGA and a high-grade IDC-NST. The three components were separately microdissected and subjected to genetic analysis with high-resolution microarray comparative genomic hybridisation. Identical genetic changes were detected in all components with subsequent acquisition of additional genetic aberrations in the invasive component, suggesting that MGA was the substrate for the development of the invasive carcinoma. Immunohistochemistry revealed concordant profiles across all components, characterized by triple-negative phenotype and variable positivity for basal markers. CONCLUSIONS: Similar to adenomas, MGA is, at least in some cases, a clonal lesion and may be a non-obligate precursor of a subgroup of high-grade triple-negative and basal-like breast carcinomas.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".