CAXII Is a Surrogate Marker for Luminal Breast Tumors Regulated by ER and GATA3
Bibliographic record
Abstract
Estrogen receptor alpha (ERα) expression in ~2/3 breast tumors selects patients for hormonal therapies. Tumors negative for ERα but positive for the progesterone receptor (PR, encoded by PGR) have also been candidates for ER-targeting therapies, as PR expression may reflect undetected ER activity. Conversely, PR− status in ER+ tumors predicts a worse therapeutic response. Our analysis of breast tumor transcriptome datasets, however, revealed that in tumors with lower PGR expression, the clinical PR status does not correlate accurately with the expression of ESR1 or of ER target genes, including PGR itself. We identified carbonic anhydrase 12 (CA12) as an estrogen target gene better correlated with ESR1 than PGR, reflecting CA12 regulation by both ERα and the luminal factor and upstream ESR1 regulator GATA3. Immunostaining supported strong positive correlations at the protein level with ERα and GATA3 in a cohort of 118 tumors. Most ER+PR− tumors expressed CAXII at levels similar to those of ER+PR+ tumors, consistent with observations in tumor transcriptome datasets and with active estrogenic signaling in some ER+PR− breast cancer cell lines. The few ER−PR+ tumors did not express CAXII or the other luminal markers FOXA1 and GATA3. Overall, CAXII is a luminal marker that can help interpret ER status in single ER/PR positive tumors.
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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 | 0.000 |
| 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".