Is Carboxypeptidase B1 a Prognostic Marker for Ductal Carcinoma In Situ?
Bibliographic record
Abstract
Ductal carcinoma in situ (DCIS) is considered a non-obligatory precursor for invasive ductal carcinoma (IDC). Around 70% of women with atypical ductal hyperplasia (ADH) undergo unnecessary surgery due to the difficulty in differentiating ADH from low-grade DCIS. If untreated, 14–60% of DCIS progress to IDC, highlighting the importance of identifying a DCIS gene signature. Human transcriptome data of breast tissue samples representing each step of BC progression were analyzed and high expression of carboxypeptidase B1 (CPB1) expression strongly correlated with DCIS. This was confirmed by quantitative PCR in breast tissue samples and cell lines model. High CPB1 expression correlated with better survival outcome, and mRNA level was highest in DCIS than DCIS adjacent to IDC and IDC. Moreover, loss of CPB1 in a DCIS cell line led to invasive properties associated with activation of HIF1α, FN1, STAT3 and SPP1 and downregulation of SFRP1 and OS9. The expression of CPB1 could predict 90.1% of DCIS in a cohort consisting of DCIS and IDC. We identified CPB1, a biomarker that helps differentiate DCIS from ADH or IDC and in predicting if a DCIS is likely to progress to IDC, thereby helping clinicians in their decisions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".