Abstract PD17-06: Immunohistochemical markers and determinants of clinical response in the Penelope-B trial
Notice bibliographique
Résumé
Abstract Background: The Penelope-B trial did not show improvement in invasive disease-free survival (iDFS) with the addition of palbociclib to endocrine therapy (ET) in patients with high-risk early breast cancer (BC) after neoadjuvant chemotherapy (NACT). Biomarkers may be able to identify subgroups of patients deriving benefit from Palbociclib and guide future studies. Estrogen-receptor (ER), progesterone-receptor (PgR) and Ki-67 might be helpful in identifying patients benefiting from palbociclib. Concordantly, tumors with elevated expression of Cyclin D1 and phosphorylated retinoblastoma protein (phospho-RB) may harbor more dependency on CDK4/6 and thus higher sensitivity to palbociclib. Methods: The percentage of positive ER and PgR cells and Ki-67 assessed in surgical specimens after NACT were combined to obtain the immunohistochemical score 3 (IHC3, Cuzick et al JCO 2011, low vs high based on the median IHC3 value). Cyclin D1 and phospho-RB Ser 807/811 immunoreactive (phospho-RB) scores were analyzed in residual tumors after NACT (range 0-12 each). Proportional hazard regression model was used to assess the predictive and prognostic value of IHC3 and treatment on iDFS. Subgroup analysis was performed according to BC intrinsic subtypes (luminal-A/normal-like, luminal-B/HER2-enriched/basal) and HER2-status (HER2 0, HER2 low). Cox/Fine-Gray regression was used to define the predictive and prognostic value of CyclinD1 (≤1, >1), phospho-RB (≤2, >2) as dichotomized and continuous variables on iDFS, distant DFS (DDFS), locoregional invasive recurrence-free interval (LRRFI) and overall survival (OS). Multivariate analyses (MVA) were adjusted for age (≤50 vs >50), Ki-67 (≤15 vs >15), region (non-Asian vs Asian), ypN (ypN0-1 vs ypN2-3), risk status (CPS-EG=2 ypN+ vs ≥3), cT (cT1-2 vs cT3-4), ypT (ypT0-2 vs ypT3-4), and grade (G1-2 vs G3). The MVA for IHC3 includes all the covariates above except Ki-67. p< 0.05 was defined as statistically significant. Results: Data for ER, PgR, Ki-67, HER2, Cyclin D1 and phospho-RB were available for 1250 patients. Overall, 98.9% of the patients had ER+ tumors, 75.0% PgR+, 52.2% had HER2 low, 25.5% Ki-67>15, 50% had IHC3 score higher than median, 93.9% had Cyclin D1 >1, 57.8% had phospho-RB >2. Patients with IHC3 score high had a worse iDFS compared to patients with IHC3 score low (MVA HR 2.28 95%CI (1.78-2.91), p< 0.0001). Patients with luminal-A/normal-like tumors and IHC3 low had an improved iDFS with the addition of palbociclib to ET (MVA HR 0.35 95%CI (0.14-0.90), test for interaction p=0.01). No difference was observed according to HER2 status. Cyclin D1>1 has no predictive value but is prognostic for better iDFS (MVA HR 0.62 95%CI (0.41-0.94), p=0.023), LRRFI (MVA HR 0.30 95%CI (0.15-0.63), p=0.001) and OS (MVA HR 0.50 95%CI (0.28-0.89), p=0.019). Similar results were obtained when Cyclin D1 was analysed as a continuous variable. Phospho-RB had neither predictive nor prognostic value. Phospho-RB highly correlates with Ki-67 (p< 0.001, Spearman correlation 0.248). Conclusions: Patients with high Cyclin D1 expression had a favorable prognosis independent of treatment arm, but patients with luminal-A/normal-like tumors and IHC3 low after NACT had an improved outcome when receiving palbociclib in addition to adjuvant ET. Theses exploratory studies suggest specific signatures/phenotypes could predict benefit from Palbociclib in high-risk early breast cancer. Citation Format: Erik S. Knudsen, Sivaramakrishna Rachakonda, Frederik Marmé, Miguel Martín, Michael Untch, Hervé R. Bonnefoi, Wolfgang D. Schmitt, Sung-Bae Kim, Harry D. Bear, Agnieszka Witkiewicz, Seock-Ah Im, Angela DeMichele, Laura Van’t Veer, Nicole McCarthy, Bruno V. Sinn, Karen Gelmon, José Ángel García-Sáenz, Catherine M. Kelly, Toralf Reimer, Nicholas Turner, Federico Rojo, Martin Filipits, Peter A. Fasching, Christian Schem, Lesley-Ann Martin, Yuan Liu, Masakazu Toi, Hope Rugo, Michael Gnant, Andreas Makris, Jenny Furlanetto, Karsten Weber, Carsten Denkert, Sibylle Loibl. Immunohistochemical markers and determinants of clinical response in the Penelope-B trial [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD17-06.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».