Abstract P2-09-10: Comprehensive gene expression biomarker analysis of CDK 4/6 and endocrine pathways from the PALOMA-2 study
Bibliographic record
Abstract
Abstract Background: Palbociclib (P) is a potent, oral, highly selective, inhibitor of cyclin-dependent kinase (CDK) 4 and 6. In the Phase 3 PALOMA-2 study, P in combination with letrozole (L) demonstrated a significant improvement in progression-free survival (PFS) versus placebo (PBO) plus L. To further explore predictive markers for sensitivity and resistance to CDK4/6-based therapy or endocrine therapy (ET) alone, we performed a large gene expression analysis of baseline tumor tissues using mature PFS data with extended follow-up. Methods: Postmenopausal women (N=666) with no prior systemic therapy for ER+/HER2- ABC were randomized 2:1 to P+L or PBO+L until disease progression, death, unacceptable toxicity, or consent withdrawal. All patients provided tumor tissues to participate in the study. 455 of 666 intent-to-treat (ITT) patients had tumor tissue appropriate for gene expression evaluation (303 [68%] P+L arm and 152 [68%] PBO+L arm). EdgeSeq Oncology Biomarker Panel (HTG Molecular Diagnostics; Tucson, AZ) was used for mRNA profiling, assessing 2534 genes involved in a variety of cancer-related pathways. Using systematic and unsupervised approaches, gene expression levels were interrogated for identification of potential genes and/or pathways associated with a treatment effect of P+L compared with PBO+L. Results: With median follow-up of 38 months, mPFS of P+L vs L + PBO was 27.6 mos vs 14.5 mos (HR=0.563 [p<0.000001] in ITT). PFS in the biomarker-assessed group was similar. Using a supervised approach, expression of genes involved in the Cyclin D-CDK4/6-RB pathway were analyzed. This demonstrated that patients receiving P+L had a consistent benefit similar to the ITT population irrespective of various expression levels of CCND1, CCNE1/2, CDK2/4/6, RB1, and CDKN2A. These results are consistent with findings from previous IHC data (CCND1, RB, p16). Unsupervised analysis revealed that tumors with higher levels of growth factor receptors (eg. FGFR2 FDR 0.032, interaction p=0.056 and ERBB3 FDR 0.221, interaction p=0.043,) were associated with greater sensitivity to P+L vs L alone. Using parallel gene signature-based analyses, tumors with higher expression of a growth factor signature had longer PFS in the P+L arm. In addition, higher CDK4 expression was identified as a resistance marker for PBO+L arm (FDR 0.095, interaction p=0.016). Gene expression-based molecular subtyping demonstrated that both luminal A and B subtypes benefited equally from P+L vs PBO+L. Patients with lower level of tumor PD-1 expression showed more benefit from P+L (FDR 0.099, interaction p=0.021). Conclusion: These results confirm efficacy of palbociclib + letrozole in ER+/HER2- breast cancer, and support the use of ER+ as a biomarker for sensitivity to CDK 4/6 inhibition. Expression levels (whether high or low) of genes in the Cyclin D-CDK4/6-RB pathway did not correlate with benefit from palbociclib + letrozole. These data provide evidence that the interplay between steroid hormone and peptide growth factor signaling in ER+ breast cancer drives dependence on CDK 4/6 and benefit from CDK 4/6 inhibition with palbociclib. These data can be used to guide additional therapeutic opportunities in ER+/HER2- ABC. Sponsor: Pfizer Citation Format: Finn RS, Liu Y, Martin M, Rugo HS, Dieras V, Im S-A, Gelmon K, Harbeck N, Zhu Z, Lu D, Gauthier E, Bartlett CH, Slamon DJ. Comprehensive gene expression biomarker analysis of CDK 4/6 and endocrine pathways from the PALOMA-2 study [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-09-10.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".