Abstract A022: Synthetic lethality of <i>ERBB2</i> and <i>CCND1</i> in breast cancer at scale
Notice bibliographique
Résumé
Abstract Introduction: Synthetically lethal mutations offer unique molecular targets for oncologic therapy. At scale, synthetic lethality (SL) is observed when alterations to one gene alone do not correspond with worse overall survival (OS), but simultaneous expression with another gene does correspond with worse OS. Mutually exclusive gene expression is not a requirement for SL. Existing breast cancer (BC) literature suggests synthetic lethality between CKS1B and PLK1, as well as BRCA1/BRCA2 and PARP1. Unaltered RB1 and altered CCND1 are also known to exhibit SL in the HER2-deficient environment of triple-negative BC. CCND1 and ERBB2 are typically amplified in invasive ductal carcinoma, with ERBB2 amplifications correlating to larger tumor size. This relationship is not observed in invasive lobular carcinoma, although expression of E2F1, a downstream transcription factor of CCND1, is inversely correlated with tumor grade. Methods: Our in silico approach investigated SL between ERBB2 and CCND1 in breast invasive carcinoma without distinction to lobular or ductal origin (TCGA, PanCancer Atlas 2018). We identified 17 genes of interest based on molecular alterations present in >10% of the sample (n=1084) and common mentions in BC literature. SL was determined if alterations to one gene alone did not significantly worsen OS, while alterations to two genes corresponded with worse OS. Results: Twenty-three SL interactions were observed. CCND1 and ERBB2 were selected because neither gene significantly worsened OS alone (p=0.915 & p=0.0951 respectively). However, patients with alterations to both genes had significantly worse OS compared to those with alterations to one gene alone. CCND1 and ERBB2 alterations were present in 14.9% and 13.7% of the sample, respectively. HR=2.568 (p=0.0138) for SL patients compared to those with CCND1 alterations alone; HR=2.244 (p=0.0497) for SL patients compared to those with ERBB2 alterations alone. Mutual exclusivity was not significantly observed (p=0.084). Multivariate analysis was performed using Cox regression models; neither age (older or younger than 55 years) nor race (White, Black, Asian) confounded our results due to p>0.05. Conclusion: Our findings support potential therapeutic use of CCND1 targets in HER2+ BC, specifically for patients with SL between CCND1 and ERBB2. These include PLK1 inhibitors, commonly used in estrogen receptor-positive patients with CDK4/6 inhibitor resistance, along with HER2 inhibitors. A combination of MAP2K and PIK3CA inhibitors should also be investigated in HER2+ BC patients with CCND1 amplification, since HER2+ colorectal cancer patients have been demonstrated to fare better with this treatment. Citation Format: Rishi Nair, Evan P. White, Roy Khalife, Anthony M. Magliocco. Synthetic lethality of ERBB2 and CCND1 in breast cancer at scale [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr A022.
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 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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».