Genomic Differences Between Pure Ductal Carcinoma <i>In Situ</i> of the Breast and that Associated with Invasive Disease: a Calibrated aCGH Study
Bibliographic record
Abstract
PURPOSE: In the quest for new targets, genomes of ductal carcinoma in situ (DCIS) and infiltrating duct carcinoma (IDC) have been compared previously; however, genomic alterations associated with cancer progression were difficult to identify. We hypothesized that significant events can be detected by comparing lesions with a broader range of behavior: from pure DCIS to IDC associated with lymph node metastasis. EXPERIMENTAL DESIGN: Array comparative genomic hybridization, calibrated by self-self hybridization tests, was used to study 6 cases of pure DCIS and 17 cases of DCIS paired with IDC where 8 tumors had spread to the local lymph nodes. RESULTS: Pure DCIS exhibited a marginally higher degree of genomic complexity than DCIS and IDC components of invasive tumors. The latter two showed similarity between tumors and between components of the same tumor with several regions detected preferentially compared with pure DCIS. IDC associated with lymph node metastases showed similarity of genomic profiles as a group. Gain on 17q22-24.2 was associated with higher histologic grade, large IDC size, lymphatic/vascular invasion, and lymph node metastasis (P < 0.05). CONCLUSIONS: Our findings suggest that DCIS and IDC are associated with specific genomic events. DCIS associated with IDC is genomically similar to the invasive component and therefore may represent either a clone with high invasive potential or invasive cancer spreading through the ducts. Specifically, gain on 17q22-24.2 is a candidate region for further testing as a predictor of invasion when detected in DCIS and predictor of nodal metastasis when detected in DCIS or IDC.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".