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Enregistrement W4322774598 · doi:10.1158/1538-7445.sabcs22-p4-09-12

Abstract P4-09-12: Baseline and End-of-Treatment Biomarkers in Patients With PIK3CA-Mutated, Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer From BYLieve Study Cohorts A and B

2023· article· en· W4322774598 sur OpenAlexaff
Dejan Juric, Nicholas C. Turner, Sherene Loi, Fabrice André, Stephen Chia, Komal Jhaveri, Patrick Neven, Rebecca Dent, Eva Ciruelos, Mukta Joshi, Estelle Roux, Heather Patino, Murat Akdere, Hope Rugo

Notice bibliographique

RevueCancer Research · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueAdvanced Breast Cancer Therapies
Établissements canadiensBC Cancer Agency
Organismes subventionnairesnon disponible
Mots-clésMedicineFulvestrantInternal medicineOncologyLetrozoleBiomarkerCancerBreast cancerAromatase inhibitorCohortHazard ratioCancer researchEstrogen receptorBiologyConfidence intervalAromataseGenetics

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) is mutated in ~40% of patients (pts) with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2−) advanced breast cancer (ABC). PIK3CA mutations are associated with resistance to endocrine therapy (ET) and worse overall survival. Alpelisib (ALP), an α-selective PI3K inhibitor and degrader, is indicated in combination with fulvestrant (FUL) for pts with PIK3CA-mutated (mut) HR+, HER2− ABC following progression on/after ET-based treatments. In the Phase 2, open-label, 3-cohort, noncomparative BYLieve study, clinical benefit of ALP in combination with ET was observed in the post-cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) setting in pts with PIK3CA-mut, HR+, HER2− ABC. Here we report the results of a biomarker analysis using paired baseline (Cycle 1 Day 1) and end-of-treatment (EOT) circulating tumor DNA (ctDNA) samples from pts in BYLieve Cohorts A and B. Methods: In the BYLieve study, pts with PIK3CA-mut, HR+, HER2− ABC had CDK4/6i + aromatase inhibitor (Cohort A; N=127) or CDK4/6i + FUL (Cohort B; N=126) as treatment immediately prior to receiving ALP + FUL and ALP + letrozole, respectively. In this biomarker analysis, gene alterations were detected in ctDNA at baseline and EOT using next-generation sequencing (PanCancer V2 panel). Pts included in this interim analysis had confirmed PIK3CA mutations and matched baseline/EOT samples with enough sequencing coverage and ctDNA fraction to detect mutations at both time points. ctDNA fractions, tumor mutation burden (TMB) distributions, genomic landscapes, gain/loss of PIK3CA and estrogen receptor 1 (ESR1), chromosome 8/11 amplification profiles, and alterations in PI3K pathway and potential CDK4/6i resistance markers were assessed across time points. Sample sizes were small; results should thus be interpreted with caution. Results: Forty-three pts were included in the Cohort A biomarker population and 40 pts were included in Cohort B. ctDNA fraction was numerically higher at EOT compared with baseline in both cohorts; further analyses will be presented. In Cohort A, no significant differences were observed in TMB at EOT compared with baseline (P=0.21). In Cohort B, TMB was higher at EOT compared with baseline (P=0.053). Chromosome 8/11 amplifications were consistent between baseline and EOT for both cohorts. Small variations were observed in ESR1/PIK3CA mutations between baseline and EOT on both cohorts (Table). The status of potential CDK4/6i resistance markers was relatively unchanged at EOT (Table). Loss-of-function mutations in PTEN, a known PI3K inhibitor resistance marker, increased from 9% at baseline to 14% at EOT in Cohort A and from 12% at baseline to 22% at EOT in Cohort B. Conclusions: Between baseline and EOT, only small variations in gene alterations in PIK3CA-mutated HR+, HER2– ABC were observed in the post-CDK4/6i setting. As the disease progressed, increases in loss-of-function mutations in PTEN at EOT in both Cohorts A and B suggested loss of PTEN in PI3K pathway may drive resistance to ALP. Early intervention with ALP, when the tumor is particularly driven by PIK3CA oncogenic mutations and before it develops more genomic complexity, may potentially provide better clinical outcomes. Table. Gene Alteration Gain/Loss at Baseline/EOT Across Cohorts A and B Citation Format: Dejan Juric, Nicholas Turner, Sherene Loi, Fabrice Andre, Stephen K. Chia, Komal Jhaveri, Patrick Neven, Rebecca Dent, Eva Ciruelos, Mukta Joshi, Estelle Roux, Heather Patino, Murat Akdere, Hope Rugo. Baseline and End-of-Treatment Biomarkers in Patients With PIK3CA-Mutated, Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Advanced Breast Cancer From BYLieve Study Cohorts A and B [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 P4-09-12.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,159
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,035
Tête enseignante GPT0,361
Écart entre enseignants0,326 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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