Pooled ctDNA analysis of MONALEESA phase III advanced breast cancer trials
Bibliographic record
Abstract
BACKGROUND: The phase III MONALEESA trials tested the efficacy and safety of the cyclin-dependent kinase (CDK)4/6 inhibitor ribociclib with different endocrine therapy partners as first- or second-line treatment of hormone receptor-positive/human epidermal growth factor receptor 2-negative advanced breast cancer (ABC). Using the largest pooled biomarker dataset of the CDK4/6 inhibitor ribociclib in ABC to date, we identified potential biomarkers of response to ribociclib. PATIENTS AND METHODS: Baseline circulating tumour DNA from patients in the MONALEESA trials was assessed using next-generation sequencing. An analysis of correlation between gene alteration status and progression-free survival (PFS) was carried out to identify potential biomarkers of response to ribociclib. RESULTS: Multiple frequently altered genes were identified. Alterations in ERBB2, FAT3, FRS2, MDM2, SFRP1, and ZNF217 were associated with a greater PFS benefit with ribociclib versus placebo. Patients with high tumour mutational burden (TMB) and with ANO1, CDKN2A/2B/2C, and RB1 alterations exhibited decreased sensitivity to ribociclib versus placebo. CONCLUSIONS: Although exploratory, these results provide insight into alterations associated with the improved response to ribociclib treatment and may inform treatment sequencing in patients with actionable alterations following progression on CDK4/6 inhibitors. Validation of potential biomarkers identified here and development of prospective trials testing their clinical utility are warranted. GOV IDENTIFIERS: NCT01958021, NCT02422615, NCT02278120.
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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 | 0.021 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".