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Enregistrement W4322774011 · doi:10.1158/1538-7445.sabcs22-her2-06

Abstract HER2-06: HER2-06 Outcome analysis of HER2-zero or HER2-low hormone receptor-positive (HR+) breast cancer patients - characterization of the molecular phenotype in combination with molecular subtyping

2023· article· en· W4322774011 sur OpenAlexaff
Carsten Denkert, Michael Untch, Hervé Bonnefoi, Erik S. Knudsen, Seock‐Ah Im, Angela DeMichele, Agnieszka K. Witkiewicz, Laura van ‘t Veer, Sung‐Bae Kim, Harry D. Bear, Nicole McCarthy, Karen Gelmon, Frederik Marmé, José Á. García-Sáenz, Nicholas Turner, Federico Rojo, Martin Filipits, Lesley‐Ann Martin, Peter A. Fasching, Christian Schem, Catherine M. Kelly, Toralf Reimer, Masakazu Toi, Hope Rugo, Michael Gnant, Andreas Makris, Yuan Liu, Karsten E. Weber, Sivaramakrishna Rachakonda, Sibylle Loibl

Notice bibliographique

RevueCancer Research · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueAdvanced Breast Cancer Therapies
Établissements canadiensBC Cancer Agency
Organismes subventionnairesnon disponible
Mots-clésBreast cancerMedicineOncologyInternal medicineCancerNeoadjuvant therapyBiomarkerHormone receptorStage (stratigraphy)TrastuzumabBiopsyPathologyBiology

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Breast cancer with low HER2 expression (HER2-low) is of high clinical relevance because of new therapeutic options with antibody-drug conjugates. We have recently shown in a large cohort from neoadjuvant clinical trials that HER2-low breast cancer has different molecular characteristics as well as different clinical outcomes compared to HER2-zero. Considering the positive correlation between HER2-low expression and hormone receptor positivity observed consistently in many investigations, we have extended our analysis to HR+ tumors from the post-neoadjuvant PenelopeB trial. In PenelopeB, patients with HR+ breast cancer and residual disease after neoadjuvant chemotherapy (NACT) were randomized to post-neoadjuvant palbociclib versus placebo in addition to endocrine therapy. We evaluated the molecular phenotype and clinical outcomes of HER2-low compared to HER2-zero patients. Methods: A total of 1250 patients were randomized, HER2 status was available for 1151 tumors from pretherapeutic core biopsy, determined mainly by local pathology, and from 1213 tumors from the post-NACT sample, determined as part of central pathology. For 1119 patients a paired HER2-status was both available. HER2-zero was defined as IHC0 and HER2-low-positive was defined as IHC1+ or IHC2+/ISH-. Gene expression analysis of 2549 genes using the HTG oncology biomarker panel was performed in 620 pretherapeutic biopsies and 780 post-NACT residual tumor samples, with 539 paired gene expression samples. Breast cancer subtypes were determined using the AIMS approach. Results: In pretherapeutic biopsies, 695 tumors (60%) were HER2-low and 457 (40%) were HER2-zero. A HER2-low status in the biopsy was significantly linked to improved iDFS (HR 0.76 (0.60-0.96; p=0.02). In residual tumors, 632 tumors (60%) were HER2-low and 581 (40%) were HER2-zero, without any prognostic impact of HER2 low status. In addition, a shift of HER2-low-status comparing core biopsy and residual tumor was observed in 415 (37%) of 1119 tumors. 161 (14%) had a shift from HER2-zero to HER2-low and 254 (23%) shifted from HER2-low to HER2-zero. A shift from HER2-zero to HER2-low in the post-NACT samples was significantly linked to reduced iDFS (HR 1.43 [95%CI 1.01-2.01]), p=0.04), compared to HER2-low group, while a shift from HER2-low to HER2-zero was associated with better iDFS compared to HER2-zero group, although not statistically significant (p=0.17). We did not observe a significant correlation of HER2-low status and AIMS molecular subtypes. In particular, the HER2-enriched (HER2E) subtype was assigned to only 4.3% of HER2-zero and 3.1% of HER2-low tumors. Significant iDFS differences were observed for HER2-low-status in combination with AIMS subtypes (lumB/basal/HER2E vs. lumA/normL; overall p-value < 0.0001) for both pretherapeutic biopsies and residual tumor. Patients with post-NACT HER2-low tumors had an improved survival in the subgroups of aggressive AIMS subtypes (lumB/basal/HER2E), but not in the less aggressive AIMs subtypes (lumA/normL), with a positive test for interaction (p=0.02). For the pre-NACT samples a similar, but non-significant trend was observed. We evaluated a total of 620 core biopsies for differences in gene expression comparing HER2-low and HER2-zero tumors. A total of 417 genes were statistically significantly different, but in a hierarchical clustering there was no clear separation of HER2-low and HER2-zero tumors. Conclusions: In the PenelopeB cohort of HR+ tumors, a HER2-low status in pretherapeutic core biopsies is related to improved disease-free survival, especially for those tumors that have a more aggressive intrinsic subtype. A shift of HER2-low status was observed before and after chemotherapy, indicating an adaptation of the pathway activity to therapy-induced stress, which might become relevant for future diagnostic and therapeutic approaches. Citation Format: Carsten Denkert, Miguel Martín, Michael Untch, Hervé R. Bonnefoi, Erik S. Knudsen, Seock-Ah Im, Angela DeMichele, Agnieszka Witkiewicz, Laura Van ’t Veer, Sung-Bae Kim, Harry D. Bear, Nicole McCarthy, Karen Gelmon, Frederik Marmé, José Ángel García-Sáenz, Nicholas Turner, Federico Rojo, Martin Filipits, Lesley-Ann Martin, Peter A. Fasching, Christian Schem, Catherine M. Kelly, Toralf Reimer, Masakazu Toi, Hope Rugo, Michael Gnant, Andreas Makris, Yuan Liu, Karsten Weber, Sivaramakrishna Rachakonda, Sibylle Loibl. HER2-06 Outcome analysis of HER2-zero or HER2-low hormone receptor-positive (HR+) breast cancer patients - characterization of the molecular phenotype in combination with molecular subtyping [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 HER2-06.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,005
Score d'incertitude au seuil0,016

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

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 Opus0,027
Tête enseignante GPT0,353
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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations5
Publié2023
Routes d'admission1
Résumé présentoui

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