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Enregistrement W4220719444 · doi:10.1158/1538-7445.sabcs21-pd2-05

Abstract PD2-05: Genomic profiling of PAM50-based intrinsic subtypes in HR+/HER2- advanced breast cancer (ABC) across the MONALEESA (ML) studies

2022· article· en· W4220719444 sur OpenAlexaff
Aleix Prat, Nadia Solovieff, Faye Su, Aditya Bardia, Patrick Neven, Gabriel N. Hortobágyi, Debu Tripathy, Stephen Chia, Dennis Slamon, Yen‐Shen Lu, Tetiana Taran, Agnes Lteif, Carlos L. Arteaga, Fabrice André

Notice bibliographique

RevueCancer Research · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueAdvanced Breast Cancer Therapies
Établissements canadiensBC Cancer Agency
Organismes subventionnairesnon disponible
Mots-clésIndelMedicineOncologyFalse discovery rateExact testInternal medicineBreast cancerLogistic regressionMultiple comparisons problemGeneCancerBioinformaticsBiologyGeneticsSingle-nucleotide polymorphismGenotype

Résumé

récupéré en direct d'OpenAlex

Abstract Background: In the ML program, PAM50-based intrinsic subtypes (ie, luminal A [LumA], luminal B [LumB], HER2 enriched [HER2E], and basal-like [Basal]) were found to be prognostic and predictive of ribociclib benefit in ABC (Prat et al. J Clin Oncol. 2021). While ribocliclib demonstrated benefit in all subtypes (except Basal, with a limited sample size), LumB and HER2E derived the largest benefit. However, DNA features of the intrinsic subtypes in the advanced setting remain unknown. Here, we report the results of genomic profiling of baseline circulating tumor DNA (ctDNA) by PAM50-based intrinsic subtypes across ML studies. Methods: A total of 883 of 2066 patients recruited in the ML-2, -3, and -7 phase 3 trials had both tumor intrinsic subtype and plasma ctDNA next-generation sequencing (NGS)-based data obtained at baseline (ie, before starting treatment). The NGS-based panel targeted exonic regions in approximately 550 genes sequenced on an Illumina HiSeq instrument. A total of 130 patients had the normal-like subtype and were excluded from further analyses. For genes altered in > 5% of patients, we assessed the differences in frequency across intrinsic subtypes. Genetic alterations included mutations, indels, and copy number alterations. For each gene, a Fisher exact test was used to test for differences in frequency across the subtypes. A false discovery rate (FDR) correction was used to adjust for multiple testing. For genes with FDR < 0.10, a logistic regression model was used to quantify the relationship between subtypes and alteration status. Also, we evaluated differences across subtypes for tumor mutational burden (TMB) using analysis of variance and for ctDNA fraction using a Kruskal-Wallis test. Results: Overall, gene amplifications were more frequent in the LumB, HER2E, and Basal subtypes. CCND1 (and genes FGF3/4/19 found in the same amplicon) was more frequently altered in HER2E (14.6%) and LumB (14.3%) than in the LumA (4.8%) subtype. Similarly, FGFR1 and MYC were more frequently altered in HER2E (13% and 9.8%), Basal (12.5% and 12.5%), and LumB (8.6% and 10%) than in the LumA (3.3% and 2.3%) subtype. PIK3CA alterations, including hotspot somatic mutations, were less frequent in Basal (12.5%) than in the LumB (27.6%), LumA (33.8%), and HER2E (37.4%) subtypes. In contrast, TP53 alterations were more frequent in Basal (66.7%) and HER2E (29.3%) than in the LumB (16.2%) and LumA (12.4%) subtypes. ERBB2 alterations (n = 25) were found in the LumA, LumB, and HER2E subtypes at similar frequencies (3%-4%). ESR1 did not show any significant difference across subtypes. TMB did not differ by subtype (P = .20), even when a TMB cutoff ≥ 10 was used (P = .23). Finally, ctDNA fraction differed across subtypes (P < .001), being significantly higher in the LumB (P < .001) and HER2E (P < .001) than in the LumA subtype. Conclusions: This is the first combined report of ctDNA NGS profiling and intrinsic molecular subtype in ABC. Differences in tumor DNA profiles were observed across PAM50 subtypes, with a trend for higher copy number alterations in HER2E and LumB than in the LumA subtype. LumA and Basal subtypes were found to have the most distinct genomic features. The Basal subtype is known to be similar to triple-negative BC from a clinical and biological perspective, which may explain the limited activity of ribociclib in this subgroup, as shown previously (Prat et al. J Clin Oncol. 2021). The pronounced activity of ribociclib in HER2E and LumB subtypes, which are enriched with somatic alterations associated with endocrine therapy resistance and tend to have a worse prognosis, warrants further investigation. Citation Format: Aleix Prat, Nadia Solovieff, Faye Su, Aditya Bardia, Patrick Neven, Gabriel N. Hortobagyi, Debu Tripathy, Stephen Chia, Dennis Slamon, Yen-Shen Lu, Tetiana Taran, Agnes Lteif, Carlos L. Arteaga, Fabrice André. Genomic profiling of PAM50-based intrinsic subtypes in HR+/HER2- advanced breast cancer (ABC) across the MONALEESA (ML) studies [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD2-05.

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)0,002
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,644
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,002
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 Opus0,086
Tête enseignante GPT0,445
Écart entre enseignants0,359 · 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

Citations3
Publié2022
Routes d'admission1
Résumé présentoui

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