Abstract P2-10-04: Targeted sequencing in early breast cancer: Identification of novel candidate mutations predictive of anthracycline benefit
Notice bibliographique
Résumé
Abstract Background The use of chemotherapies such as anthracyclines and taxanes have improved overall and disease free survival in breast cancer. For all patients, anthracyclines can have significant toxicities including cardiotoxicity and leukemia. It is therefore essential to select the subset of patients who will receive the optimal overall benefit from anthracycline therapy and to identify molecular pathways driving resistance. To fully understand the impact of mutations in the context of current breast cancer therapy, requires a comprehensive mapping of key molecular events in the context of treatment. We sequenced 101 genes, that were prioritized based on not only gene frequency, but also taking into account the importance of amino acid substitution, type of mutation and network connectivity, in 692 primary tumours to both identify driver genes and pathway cassettes and to understand their clinical significance in response to anthracycline treatment. Methods We performed targeted sequencing in patients from the BR9601 (n=374) and CCTG MA.5 (n=703) clinical trials. The BR9601 and MA.5 clinical trials examined the effectiveness of combination chemotherapy consisting of CMF (cyclophosphamide, methotrexate and 5-fluorouracil) with or without epirubicin. DNA was extracted, samples were sequenced using AmpliSeq Technology adapted to Illumina and somatic mutations were called using a novel mutation calling pipeline (ISOWN). A priori analyses were performed using distant recurrence free survival (DRFS) as the primary endpoint. Results: In 692 successfully analysed samples 509 (73.6%) samples exhibited at least one single nucleotide mutation (range 0-54). 94/101 genes were mutated in at least one patient. Only variants in PIK3CA, TP53, CDH1, TLE6, MLL3 and USH2A were detected in 5% or more of samples. TSC22D1, RB1 and ZNF565 were associated with increased risk of distant relapse in multivariate analyses corrected for clinic-pathological variables. No single genes were predictive of anthracycline treatment compared to CMF in multivariate analyses corrected for clinic-pathological variables. Signaling cassettes/modules were designed based on the pathway database, Reactome. Within the signaling cassettes one module was predictive of anthracycline failure. Patients with one or more mutations in this module had an increased risk of distant relapse (HR 0.52, 95% CI 0.29-0.95, p=0.034) when treated with an anthracycline containing chemotherapy regimen compared to CMF (HR 1.34 95% CI 1.05-1.72, p=0.019). Conclusions: We successfully performed a signaling pathway-based targeted sequencing analysis within predefined signaling modules. We identified a single signaling cassette linked to anthracycline resistance in early breast cancer. However, further work to validate this study in a separate clinical trial is warranted. Citation Format: Spears M, Kalatskaya I, Trinh QM, Liao L, Chong TM, Crozier C, Dion D, Heisler L, Timms L, Stein LD, Pritchard KI, Levine MN, Shepherd L, Twelves CJ, Bartlett JMS. Targeted sequencing in early breast cancer: Identification of novel candidate mutations predictive of anthracycline benefit [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 P2-10-04.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».