<i>CCNE1</i> and <i>PLK1</i> Mediate Resistance to Palbociclib in HR+/HER2− Metastatic Breast Cancer
Bibliographic record
Abstract
PURPOSE: In hormone receptor-positive (HR+)/HER2- metastatic breast cancer (MBC), it is imperative to identify patients who respond poorly to cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) and to discover therapeutic targets to reverse this resistance. Non-luminal breast cancer subtype and high levels of CCNE1 are candidate biomarkers in this setting, but further validation is needed. EXPERIMENTAL DESIGN: We performed mRNA gene expression profiling and correlation with progression-free survival (PFS) on 455 tumor samples included in the phase III PEARL study, which assigned patients with HR+/HER2- MBC to receive palbociclib+endocrine therapy (ET) versus capecitabine. Estrogen receptor-positive (ER+)/HER2- breast cancer cell lines were used to generate and characterize resistance to palbociclib+ET. RESULTS: Non-luminal subtype was more prevalent in metastatic (14%) than in primary tumor samples (4%). Patients with non-luminal tumors had median PFS of 2.4 months with palbociclib+ET and 9.3 months with capecitabine; HR 4.16, adjusted P value < 0.0001. Tumors with high CCNE1 expression (above median) also had worse median PFS with palbociclib+ET (6.2 months) than with capecitabine (9.3 months); HR 1.55, adjusted P value = 0.0036. In patients refractory to palbociclib+ET (PFS in the lower quartile), we found higher levels of Polo-like kinase 1 (PLK1). In an independent data set (PALOMA3), tumors with high PLK1 show worse median PFS than those with low PLK1 expression under palbociclib+ET treatment. In ER+/HER2- cell line models, we show that PLK1 inhibition reverses resistance to palbociclib+ET. CONCLUSIONS: We confirm the association of non-luminal subtype and CCNE1 with resistance to CDK4/6i+ET in HR+ MBC. High levels of PLK1 mRNA identify patients with poor response to palbociclib, suggesting PLK1 could also play a role in the setting of resistance to CDK4/6i.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".