Breast Cancer Consensus Subtypes: A system for subtyping breast cancer tumors based on gene expression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Breast cancer is heterogeneous in prognoses and drug responses. To organize breast cancers by gene expression independent of statistical methodology, we identified the Breast Cancer Consensus Subtypes (BCCS) as the consensus groupings of six different subtyping methods. Our classification software identified seven BCCS subtypes in a study cohort of publicly available data (n = 5950) including METABRIC, TCGA-BRCA, and data assayed by Affymetrix arrays. All samples were fresh-frozen from primary tumors. The estrogen receptor-positive (ER+) BCCS subtypes were: PCS1 (18%) good prognosis, stromal infiltration; PCS2 (15%) poor prognosis, highly proliferative; PCS3 (13%) poor prognosis, highly proliferative, activated IFN-gamma signaling, cytotoxic lymphocyte infiltration, high tumor mutation burden; PCS4 (18%) good prognosis, hormone response genes highly expressed. The ER- BCCS subtypes were: NCS1 (11%) basal; NCS2 (10%) elevated androgen response; NCS3 (5%) cytotoxic lymphocyte infiltration; unclassified tumors (9%). HER2+ tumors were heterogeneous with respect to BCCS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it