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Enregistrement W4415506104 · doi:10.2147/ott.s537253

Evaluating the Prognostic Value of a Pan-Cancer Circulating Tumor DNA Next-Generation Sequencing Panel in Advanced Cancer Patients

2025· article· en· W4415506104 sur OpenAlex
Jaewoong Lee, Jang Ho Cho, Seungok Lee, Hoon Seok Kim, Seung Jung Han, Younmu Jung, Myungshin Kim

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Notice bibliographique

RevueOncoTargets and Therapy · 2025
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueCancer Genomics and Diagnostics
Établissements canadiensNexen (Canada)
Organismes subventionnairesIncheon St. Mary's Hospital, Catholic University of Korea
Mots-clésCirculating tumor DNACirculating tumor cellLiquid biopsyDiseaseValue (mathematics)DNA sequencingBiomarkerPredictive value

Résumé

récupéré en direct d'OpenAlex

Purpose: This study aimed to evaluate the clinical utility of a pan-cancer circulating tumor DNA (ctDNA) next-generation sequencing (NGS) panel for predicting treatment response and progression-free survival (PFS) in patients with advanced solid tumors. Patients and Methods: A total of 41 patients with advanced solid tumors, including gastric cancer (n=13), non-small cell lung cancer (n=10), head and neck cancer (n=9), esophageal cancer (n=7), breast cancer (n=1), and colon cancer (n=1), were prospectively enrolled and included in the analysis. ctDNA was analyzed at three time points: pretreatment (41 patients), post-treatment evaluation (37 patients), and follow-up (18 patients). Results: Among 41 patients analyzed at pretreatment, 35 (85.4%) exhibited tier 1 or 2 somatic variants in ctDNA, with TP53 being the most frequently mutated gene. At the post-treatment evaluation, ctDNA was assessed in 37 patients (3 with rapid deterioration and 1 lost to follow-up were not evaluable). Newly emerging variants after treatment were strongly associated with poor clinical outcomes. Consistent with the Kaplan–Meier analysis, Cox proportional hazards regression confirmed that post-treatment ctDNA positivity was significantly associated with inferior PFS (HR 10.5, 95% CI 1.4– 80.0, P=0.024). At follow-up, 18 patients were evaluable, while the others were not due to follow-up loss, rapid deterioration, or study termination. ctDNA positivity at post-treatment evaluation was significantly associated with shorter PFS (median PFS, 5.0 months [95% CI: 2.0– 12.0] vs not reached; HR, 4.87; 95% CI: 1.69– 14.09; P = 0.0035). Conclusion: Longitudinal monitoring of ctDNA using a pan-cancer NGS panel provides meaningful prognostic information in patients with advanced cancers. Post-treatment ctDNA dynamics may better reflect disease progression than baseline ctDNA status alone, highlighting the need for further validation in larger cohorts, particularly in gastric, lung, head and neck, and esophageal cancers. Plain Language Summary: Cancer cells can release small fragments of their DNA into the bloodstream, known as circulating tumor DNA (ctDNA). These fragments can be detected through a blood test, often called a “liquid biopsy.” By monitoring changes in ctDNA over time, doctors can better understand how a patient’s cancer is responding to treatment. In this study, we analyzed blood samples from 41 patients with advanced cancers, including stomach, lung, and esophageal cancers. Using a genetic test called next-generation sequencing (NGS), we examined cancer-related DNA changes at three time points: before treatment, after the first round of treatment, and during follow-up care. We then assessed how these changes related to the time patients lived without their cancer worsening, a measure known as progression-free survival (PFS). We found that over 85% of patients had significant cancer-related DNA changes before starting treatment. After treatment, many patients developed new mutations, which were associated with shorter PFS. In contrast, patients without new ctDNA changes after treatment generally had better outcomes. These results suggest that ctDNA monitoring after treatment may provide better information about a patient’s status than testing before treatment alone. Ongoing blood-based monitoring could help guide future treatment decisions. However, larger studies are needed to validate these findings. Keywords: circulating tumor DNA, next-generation sequencing, liquid biopsy, prognostic biomarker, longitudinal monitoring

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.

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 candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,371
Score d'incertitude au seuil0,426

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
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)0,0000,000

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 Opus0,064
Tête enseignante GPT0,335
Écart entre enseignants0,271 · 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