Abstract P4-10-29: Identifying novel molecular markers of response to trastuzumab in metastatic breast cancer
Notice bibliographique
Résumé
Abstract Background: The survival of women with HER2+ metastatic breast cancer (MBC) has improved with the introduction of the anti-HER2 antibody trastuzumab, but responses vary greatly among individuals. A predictive signature of response (and lack thereof) to trastuzumab may help personalize therapy for women with HER2+ MBC and enable the discovery of new “druggable” targets. Methods: In this retrospective cohort study, 256 patients with HER2+ MBC at the Sunnybrook Odette Cancer Centre were identified sequentially from January 1999 to December 2013 using the Cancer Care Ontario Registry. In total, 53 patients (21%) had archived metastatic tissue available for analysis, 29 (55%) of whom had samples obtained <3 years prior to the initiation of trastuzumab. Nanostring molecular testing was used to measure the expression of commonly known oncogenes and gene signatures using the Nanostring technologies nCounter Analysis System TM (Seattle, Washington, USA). Descriptive statistics were used to summarize patient results and prognostic scores. Patients were categorized into short-term survivors (died within 12 months) and long-term survivors (survived >30 months after starting trastuzumab). Results were compared between these two groups of patients using a Fisher’s exact test (dichotomous groups) and Wilcoxon rank sum tests (continuous scores). Univariable Cox regression models were evaluated using all patients, to evaluate if risk scores were prognostic of overall survival (OS). Statistical significance was set at the p=0.05 level and all tests were two-sided. Results: The median patient age was 60 years (interquartile range 53-65 years), 24% (n=7) had de-novo MBC and the majority of patients (52%) had ER or PR positive tumors. Among 29 included patients, the median OS was 23.4 months (95%CI 10.3-34.3 months); 10 patients died within 12 months and 10 patients survived >30 months after starting trastuzumab-based therapy. A median of 155 days (range 4-812) elapsed between metastatic biopsy and initiation of trastuzumab. The distribution of the Prosigna ROR Score, Basal Cor, HER2 Cor, Luminal A Cor, Luminal B Cor, Mammaprint Subtype/Risk Group, Oncotype Risk Score/Risk Group, IHC4 mRNA Risk Group and GGI Risk Score/Risk Group did not differ between the short- and long-term survivors. However, the Mammaprint Predictor Score was significantly higher [mean 0.34 (std 5.50) versus -4.95 (std 5.24), p=0.033] and the IHC4 Risk Score was significantly lower among long-term as compared to short-term survivors [mean 99.3 (std 67.1) versus 160.3 (std 40.9), p=0.044]. The association between molecular gene signatures and OS are described in Table 1. Conclusion: Several gene signatures were associated with OS in this exploratory analysis of women with HER2+ MBC who received trastuzumab-based therapy. The Mammaprint Predictor and the IHC4 Risk Scores differed among short- versus long-term survivors, warranting validation in an independent dataset. Table 1. Univariable Survival Results (n=29)ComparatorHR (95% CI)p-valueProsigna ROR Score/ 10 units1.23 (0.92, 1.65)0.17ProsignaHER2 vs Other1.25 (0.50, 3.13)0.64Basal Cor/ unit3.61 (1.10, 11.78)0.034Her2 Cor/ unit0.99 (0.15, 6.40)0.99Luminal A Cor/ unit0.22 (0.05, 0.95)0.042Luminal B Cor/ unit0.26 (0.06, 1.06)0.060Mammaprint Predictor Score/ unit1.10 (1.02, 1.19)0.015Mammaprint SubtypeHER2 vs Other0.85 (0.37, 2.00)0.72Mammaprint RiskHigh vs Low4.20 (1.37, 12.86)0.012Oncotype Risk Score/ 10 units1.27 (0.95, 1.70)0.11Oncotype Risk GroupHigh vs Intermediate4.83 (0.60, 39.07)0.14IHC4 Risk Score/ 10 units1.09 (1.00, 1.18)0.046IHC4 mRNA Risk GroupHigh vs Intermediate4.83 (0.60, 39.07)0.14GGI Risk Score/ 10 units1.63 (1.02, 2.61)0.043GGI Risk GroupHigh vs Low5.14 (1.13, 23.51)0.035 Citation Format: Katarzyna Joanna Jerzak, Danielle N Desautels, Phillip S Blanchette, Jane Bayani, Sharon Nofech-Mozes, Martin J Yaffe, Gregory Pond, Kathleen I Pritchard, John MS Bartlett. Identifying novel molecular markers of response to trastuzumab in metastatic breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-29.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 tête enseignante, 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 ».