CK8/18 expression, the basal phenotype, and family history in identifying <i>BRCA1</i>‐associated breast cancer in the Ontario site of the Breast Cancer Family Registry
Bibliographic record
Abstract
BACKGROUND: BRCA1-associated breast cancer had been shown to be morphologically and genetically distinct from sporadic cancers. The aim of this study was to determine the association of CK8/18 with BRCA1-associated tumors and if, by using CK8/18 and basal biomarkers in conjunction with morphologic features and family history characteristics, the specificity of the BRCA1-associated tumor profile in a pathologically well-characterized cohort would be improved. METHODS: Fifty-eight patients with known BRCA1 germline mutations and 221 control (familial non-BRCA) patients were selected from the Ontario Familial Breast Cancer Registry. From this database, information on family history and morphologic features was abstracted. Tissue microarrays were constructed and immunohistochemistry to determine expression of several biomarkers was performed. After a logistic regression fit, a best-subsets variable-selection procedure using model performance and predictive ability measures was applied to find a best predictor to distinguish BRCA1-associated tumors from non-BRCA associated tumors. RESULTS: BRCA1-associated tumors differed significantly from control tumors in terms of morphology, family history, and biomarker profile. CK8/18 was highly significantly associated with BRCA1 tumors. Consistently, BRCA1 cancers showed low levels of CK8/18 compared to non-BRCA tumors, whether they were basal-like or not. A combination of 7 factors, including CK8/18 and family history, best predicted the BRCA1-associated cancers. CONCLUSIONS: CK8/18 expression was independently associated with BRCA1-associated breast cancers. Reduced CK8/18 expression in conjunction with the basal-like phenotype and family history may have improved the ability to identify which tumors were likely to be associated with a BRCA1 germline mutation and thereby help streamline genetic testing.
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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 | 0.002 |
| 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) | 0.001 | 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".