The long-term prognostic and predictive capacity of cyclin D1 gene amplification in 2305 breast tumours
Bibliographic record
Abstract
BACKGROUND: Use of cyclin D1 (CCND1) gene amplification as a breast cancer biomarker has been hampered by conflicting assessments of the relationship between cyclin D1 protein levels and patient survival. Here, we aimed to clarify its prognostic and treatment predictive potential through comprehensive long-term survival analyses. METHODS: CCND1 amplification was assessed using SNP arrays from two cohorts of 1965 and 340 patients with matching gene expression array and clinical follow-up data of over 15 years. Kaplan-Meier and multivariable Cox regression analyses were used to determine survival differences between CCND1 amplified vs. non-amplified tumours in clinically relevant patient sets, within PAM50 subtypes and within treatment-specific subgroups. Boxplots and differential gene expression analyses were performed to assess differences between amplified vs. non-amplified tumours within PAM50 subtypes. RESULTS: When combining both cohorts, worse survival was found for patients with CCND1-amplified tumours in luminal A (HR = 1.68; 95% CI, 1.15-2.46), luminal B (1.37; 1.01-1.86) and ER+/LN-/HER2- (1.66; 1.14-2.41) subgroups. In gene expression analysis, CCND1-amplified luminal A tumours showed increased proliferation (P < 0.001) and decreased progesterone (P = 0.002) levels along with a large overlap in differentially expressed genes when comparing luminal A and B-amplified vs. non-amplified tumours. CONCLUSIONS: Our results indicate that CCND1 amplification is associated with worse 15-year survival in ER+/LN-/HER2-, luminal A and luminal B patients. Moreover, luminal A CCND1-amplified tumours display gene expression changes consistent with a more aggressive phenotype. These novel findings highlight the potential of CCND1 to identify patients that could benefit from long-term treatment strategies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".