99P Exploratory analysis of differential gene expression (DGE) and non-negative matrix factorisation (NMF) clustering in KATHERINE: Adjuvant trastuzumab emtansine (T-DM1) vs trastuzumab (H) in patients with HER2-positive residual invasive breast cancer after neoadjuvant treatment (NAT)
Bibliographic record
Abstract
This exploratory biomarker analysis aimed to identify prognostic gene sets in the. T-DM1 and H arms of the phase III KATHERINE study (NCT01772472). RNA sequencing was performed on post-NAT surgical samples. Genes and pathways associated with prognosis were identified using DGE, comparing pts with invasive disease-free survival (iDFS) events with censored pts at a 3-year cut-off, and gene set enrichment analysis (GSEA), using Hallmark, KEGG, xCell, and selected signatures. NMF was used to identify transcriptional subgroups; their association with iDFS was assessed by Cox regression. Association analyses were adjusted for tumour content (TC) and stratification factors. Eight hundred and fifteen samples were included in the analysis. GSEA showed that cell cycle, oxidative phosphorylation and DNA repair gene sets were associated with poor prognosis in both arms; in the H arm, metabolism-related signatures were associated with poor prognosis while immune signatures were associated with good prognosis; and in the T-DM1 arm, apoptosis and epithelial mesenchymal (EM) transition (EMT) gene sets and fibroblast, stroma and endothelial cell scores were associated with good prognosis. Trends were seen for poor prognosis with malignant-specific EM signatures in both arms. NMF clusters are described in the table. Table: 99PCluster, % prevalenceGene and signature expression, TC and association with prognosisiDFS hazard ratio,T-DM1 vs. H (95% confidence interval)CL1, 24.0%Cell cycle and DNA repair-related genes. High TC, higher HER2 and lower ESR1 levels vs. other clusters, poorest prognosis0.42 (0.24, 0.75)CL2, 8.3%Metabolism signatures and keratinisation-related genes0.58 (0.16, 2.19)CL3, 40.6%Focal adhesion, TGFβ, Wnt β catenin, EMT and extracellular matrix-related genes. Low TC, best prognosis0.25 (0.11, 0.57)CL4, 18.5%Oestrogen- and cilium assembly-related genes. High TC, highest ESR1 expression0.49 (0.22, 1.08)CL5, 8.5%Immune-related genes0.65 (0.18, 2.38) Open table in a new tab . Both DGE and NMF approaches identified cell cycle pathway-related and DNA repair genes as associated with poor prognosis in both arms. Stromal genes and high stromal content were associated with good prognosis. The advantage of T-DM1 over H was seen across all NMF clusters.
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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) | 0.001 | 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 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".