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Enregistrement W4396591390 · doi:10.1158/1538-7445.sabcs23-po4-15-01

Abstract PO4-15-01: A multi-center prospective cohort study to evaluate the presence of circulating tumor cells using the Epic Sciences platform among women with metastatic breast cancer

2024· article· en· W4396591390 sur OpenAlexaffabout
Katarzyna J. Jerzak, Pamela J. Goodwin, Marguerite Ennis, Christine Brezden‐Masley, Nathaniel Bouganim, Mark Basik, Arushi Jain, Giuseppe Di, Rick Wenstrup, N Hartmann, Megan Slade, Ana Elisa Lohmann

Notice bibliographique

RevueCancer Research · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueCancer Cells and Metastasis
Établissements canadiensLondon Health Sciences CentreJewish General HospitalSunnybrook Health Science CentreMcGill University Health CentreUniversity of TorontoHealth Sciences CentreMount Sinai Hospital
Organismes subventionnairesnon disponible
Mots-clésEPICMedicineCancerEuropean Prospective Investigation into Cancer and NutritionProspective cohort studyCirculating tumor cellOncologyBreast cancerInternal medicineMetastatic breast cancerCenter (category theory)CohortMetastasis

Résumé

récupéré en direct d'OpenAlex

Abstract Background: The presence of tumor cells (or their components) in the blood of women with a history of early breast cancer has the potential to herald the development of metastatic recurrence at its earliest stages. Such early detection could potentially lead to novel prevention strategies, but it requires a sensitive assay. Objective: To use the Epic Sciences platform to detect and enumerate CTCs in blood samples from patients with an established diagnosis of metastatic breast cancer (MBC), prior to initiation of 1st line systemic therapy in the metastatic setting. Methods: We conducted a multi-center prospective cohort study to evaluate the presence of CTCs using the Epic Sciences platform among patients with a new diagnosis of MBC. Men or women age 18 to 85 were included, irrespective of breast cancer subtype. Patients with a prior or concurrent malignancy whose natural history or treatment had the potential to interfere with the detection of MBC in a liquid biopsy were excluded. A one-time blood draw was performed before patients received any local or systemic therapy in the metastatic setting. In addition, those with recurrent disease must have been off any systemic adjuvant therapy for ≥3 weeks prior to blood collection. Two 5 mL blood samples were obtained for CTC identification and enumeration. CTC identification was based on immunofluorescence analysis using Epic Sciences platform as previously described (Ueno et al 2017). The presence of CTCs was correlated with clinical and pathological features, which were abstracted from medical records and pathology reports. The association between the presence of CTCs and clinical/pathologic characteristics was tested using Fisher’s exact test for categorical variables and t-test or Wilcoxon rank sum tests for numerical variables. All analyses were performed using the R software package. Results: 100 patients were recruited between February 2021 and January 2023 at five academic oncology centres in Ontario and Quebec, Canada. 95 patients had evaluable blood for analysis and 5 did not due to blood age and/or insufficient blood volume. Six patients were excluded after providing a blood sample because tissue biopsy ultimately revealed a 2nd primary tumor (n=4) or benign tissue (n=2). Hence, 89 patients with a clinical diagnosis of MBC and with evaluable blood for CTC analyses were ultimately included in our cohort. The average age of patients was 61 years. Most patients (n=49, 55%) had a prior history of early breast cancer, 38 (43%) had de-novo metastatic disease and prior breast cancer history was unknown for 2 patients. 50 (66%) of patients had visceral metastatic disease. The most common sites of metastases included bone (62%), lung (30%), liver (29%) and lymph nodes (17%). 63 of 89 patients (71%) had detectable CTCs at baseline, prior to any local or systemic treatment in the metastatic setting. The median number of detectable CTCs per 5mL sample was 2 (IQR 8.5) and the range was 0 – 12,798. Twenty nine of 89 (33%) patients had 5 or more CTCs detected per 5ml blood. The proportion of patients with detectable CTCs was numerically highest (n=39/51, 76%) among patients with hormone receptor (HR)+/HER2-ve breast cancer, followed by HER2+ (n=16/22, 73%) and triple negative (n=8/13, 62%) disease. Associations between CTC detection with prior history of early breast cancer, sites of metastatic disease and disease burden will also be presented. Conclusions: Approximately 3 in 4 women with newly diagnosed metastatic breast cancer have detectable CTCs using the Epic Sciences platform prior to initiation of first line systemic therapy. CTCs may be a promising tool for the monitoring of breast cancer recurrence and will be investigated in an ongoing Canadian prospective observational study that aims to elucidate biomarkers of late breast cancer recurrence. Citation Format: Katarzyna Jerzak, Pamela Goodwin, Marguerite Ennis, Christine Brezden-Masley, Nathaniel Bouganim, Mark Basik, Arushi Jain, Giuseppe Di Caro, Rick Wenstrup, Nadine Hartmann, Megan Slade, Ana Elisa Lohmann. A multi-center prospective cohort study to evaluate the presence of circulating tumor cells using the Epic Sciences platform among women with metastatic breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-15-01.

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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,007

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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.

Tête enseignante Opus0,134
Tête enseignante GPT0,446
Écart entre enseignants0,312 · 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

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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