Illuminating luminal B: QSOX1 as a subtype-specific biomarker
Bibliographic record
Abstract
Breast cancer is a complex and heterogeneous disease that affects about one out of every eight women. In the last decade, several advancements have been made that have increased our understanding of breast cancer and have allowed us to more accurately diagnose and treat this disease in a more targeted manner. For example, gene expression profiling enabled the classification of breast cancers into four main subtypes - basal-like, HER2+ (human epidermal growth factor receptor 2-positive), luminal A and luminal B - and this classification is used to direct the use of targeted therapies such as tamoxifen or trastuzumab. The luminal subtypes are generally characterized as being estrogen receptor-positive and targetable with anti-hormone therapies. However, whereas luminal A cancers have a good prognosis, luminal B cancers are associated with early relapse following endocrine therapy and a prognosis that is similar to that of the aggressive basal subtype. It is thus imperative that luminal B cancers be better characterized so that therapeutic targets and biomarkers for this disease type can be realized. In the previous issue of Breast Cancer Research, Katchman and colleagues address this need by demonstrating that quiescin sulfydryl oxidase 1 (QSOX1), a secreted enzyme involved in post-translational modifications, is associated with poor prognosis in patients with luminal B breast cancer. The authors further determined that this protein promotes breast cancer proliferation and invasion. Collectively, these studies suggest that QSOX1 is a predictive biomarker for luminal cancers and that it may be a useful target for elusive luminal B disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".