Differential BACH1 Expression in Basal-like Breast Tumors of Black Women Identified via Immunohistochemistry
Bibliographic record
Abstract
BACH1 has been identified as a functional regulator of cancer metastasis and metabolic signaling in breast cancer cells. However, the clinical relevance of BACH1 expression in breast tumors remains poorly understood. Using a tissue microarray from a cohort of 130 patients, we assessed the expression of BACH1 and its known target gene, MCT1 (encoded by SLC16A1), through immunohistochemistry (IHC). The expression data were then analyzed in relation to clinical variables, including breast cancer subtypes, tissue types, tumor size and grade, patient racial background, and age group. We found positive associations between BACH1 expression and tumor size, tumor grade, and the basal-like subtype. Importantly, BACH1 expression was significantly higher in tumors from Black women compared to those from White women, as well as in the basal-like subtype of breast tumors from Black women. Additionally, a positive correlation was observed between BACH1 and MCT1 IHC scores in tumors from Black women, while a weak association was noted in tumors from White women. Our study provides compelling evidence that BACH1 expression is evident based on the race and subtypes of breast cancer patients.
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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 | 0.000 |
| 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) | 0.001 | 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".