Abstract P3-11-03: Validation of CIN4 in the DBCG 89D clinical cohort
Bibliographic record
Abstract
Abstract Background: Chromosome instability (CIN) in solid tumours is associated with poor prognosis and results in numerical and structural chromosomal aberrations. Our group previously have developed the CIN signatures and have demonstrated the CIN signatures as prognostic biomarkers in breast cancer cohorts. Furthermore, our work in the BR9601 and MA.5 clinical cohorts CIN4 provided level IIB evidence that CIN4 was predictive of anthracycline sensitivity. An analysis of the DBCG 89D clinical trial was now performed to validate the role of CIN gene expression signatures as a marker of anthracycline sensitivity. Methods: RNA was extracted from patients in DBCG 89D clinical trial analysed through NanoString technology. The prognostic and predictive values of the signatures on distant relapse-free survival (DRFS) were explored using Cox proportional hazard models. Multivariate models included menopausal status, tumour size, nodal status, ER and Her2 status, histological type and grade, and treatment regimen. Results: All of the 594 samples available from the DBCG 89D we successfully analysed. CIN25 and CIN70 gene expression signatures did not associate with any of the clinicopathological characteristics tested. In addition, CIN25 and CIN70 were not prognostic or predictive of distant relapse free or breast cancer specific survival in this clinical cohort. Low CIN4 score was associated with ER negativity (p=0.02), HER2 normal expression (p<0.05). Conclusion: In this study we demonstrated that CIN4 was associated with aggressive disease. We were however in DBCG 89D unable to validate the predictive value of CIN4 concerning anthracycline sensitivity. Citation Format: Spears M, Jensen M-B, Lyttle N, Liao L, Laenkholm A-V, Ejitlertsen B, Bartlett JM. Validation of CIN4 in the DBCG 89D clinical cohort [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-11-03.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".