Circulating tumor cells enumeration and characterization in patients with lung cancer treated with immunotherapy.
Notice bibliographique
Résumé
e15030 Background: Programmed death-ligand 1 (PD-L1) is a predictive biomarker for immunotherapy in the treatment of non-small cell lung cancer (NSCLC). Assessing PD-L1 expression from the tumor specimen can be challenging because of tissue accessibility, heterogeneity, and dynamic changes in PD-L1 expression that may impact the status of PD-L1 during disease evolution and treatment. Hence, assessing PD-L1 status from archival tumor might not reflect its actual state on the tumor and having a real-time assessment of its expression with the use of non-invasive techniques such circulating tumor cells (CTCs) is useful. Methods: We conducted a single centre prospective study to detect CTCs in the blood of patients with stage III-IV NSCLC treated with immunotherapy using the standard CellSearch technology for CTC enumeration and the Epic Sciences technology for CTCs enumeration and assessment of PD-L1 protein expression on CTCs. CTCs were detected at baseline before treatment initiation and after 2 cycles of treatment. Study endpoints included CTCs detection and concordance between the 2 technologies, PD-L1 expression assessment on CTCs with the Epic Sciences technology, and concordance with tissue-based expression. Comparisons were made using Pearson correlation coefficient (PCC) and intraclass correlation coefficient (ICC) for count data and percentage of perfect agreement. Results: Between 2019 and 2022, 48 patients treated with immunotherapy were enrolled in the study. The mean ± standard deviation (SD) age was 66.8 ± 10.3 years, 63% were females, 42% received combination chemotherapy and immunotherapy, and 44% had adenocarcinoma histology. The tissue PD-L1 expression was high (≥50%), intermediate (1-49%), and low (<1%) in 36%, 31% and 33% of patients respectively. The mean ± SD baseline CTCs count per 7.5ml was 1.97 ± 4 with CellSearch and 1.38 ± 2.72 per ml with Epic Sciences. After 2 treatment cycles, 22% and 41% of patients had an increase in their CTCs count with CellSearch and Epic Sciences, respectively and 30% and 29% had a decrease in their CTCs. The PCC and ICC for baseline CTCs detected by CellSearch and Epic Sciences were 0.72 and 0.61, respectively and for CTCs detected after 2 cycles of treatment by the 2 technologies were -0.16 and 0.45 respectively. One patient had PD-L1 expression on their CTCs with the Epic Sciences technology and there was no association between the PD-L1 expression on CTCs and on matched tissue samples. Conclusions: This study showed a moderate to strong correlation between the 2 technologies for baseline CTCs detection and moderate to poor correlation for CTCs detection after 2 cycles of therapy. No association was found between CTCs and tissue PD-L1 expression. Future work needs to further investigate the role of PD-L1 expression on CTCs.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,000 | 0,000 |
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.
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 tête enseignante, 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 ».