Abstract IA010: Opportunities and challenges for liquid biopsies in pediatric oncology
Notice bibliographique
Résumé
Abstract Understanding the molecular mechanisms underlying tumour progression and resistance to treatment is crucial to the development of new treatment approaches. In high risk pediatric cancers, somatic DNA alterations such as genomic amplifications, copy number alterations, translocations or mutations play an important role as molecular diagnostic, prognostic and predictive biomarkers. However it is now known that in many high risk pediatric cancers, clonal evolution most likely plays an important role in tumor progression and treatment resistance. Circulating tumour DNA, a fraction of cell free DNA can be readily isolated from plasma and now provides an important tool and surrogate for tumor molecular analyses at diagnosis, during treatment and follow-up. At diagnosis, the prospective clinical trials MICCHADO (NCT03496402) enrolled 599 patients, including high-risk pediatric cancer (Neuroblastoma, Rhabdomyosarcoma, Ewing sarcoma, other high-risk cancers). Whole -Exome-Sequencing (WES) was performed on tumor, germline DNA and cfDNA extracted from plasma at diagnosis, during treatment and follow up. Whereas all cfDNA samples obtained at follow-up in patients without evidence of disease revealed no or few tumor cell-specific SNVs, cfDNA samples obtained at relapse harbored additional, new relapse-specific SNVs in all cases, targeting genes of interest. Deep sequencing capture techniques enable to develop models of clonal evolution. In pediatric embryonal brain tumours, ctDNA isolated from CSF enables detection of tumor cell specific genetic alterations with a high sensitivity. At relapse, ctDNA studies can provide complementary information to molecular analyses of tumour samples performed within programs such as MAPPYACTS (NCT02613962), with 76% of actionable alterations detected in tumor also identified in ctDNA, while also highlighting the importance of spatial heterogeneity. MONALISA, a SIOPEN pragmatic clinical trial to MOnitor NeuroblastomA relapse with LIquid biopsy Sensitive Analysis aims to establish liquid biopsies as standard-of-care to monitor relapsed/refractory neuroblastoma. Reliable, early assessment of molecular progression or relapse determined by mRNA and/or ctDNA analysis is the main aim of this randomized clinical trial. ctDNA also enables to infer expression profiles. Gene expression levels are reflected by nucleosome positioning, and differences in nucleosome organization at transcription start sites (TSS) lead to differential clipping of fragments upon ctDNA release and distinct nucleosome footprints depending on the expression of a given gene in the originating cells. Altogether the presence of tumor genetic and epigenetic abnormalities in ctDNA can be documented in most patients with high risk pediatric cancer and frequently suggest spatial and temporal heterogeneity. Sequential studies will further elucidate mechanisms of clonal evolution, tumor progression and therapy resistance. Thus, sequential studies based on liquid biopsies are now integrated into the development and optimization of targeted treatment strategies. Citation Format: Gudrun Schleiermacher. Opportunities and challenges for liquid biopsies in pediatric oncology [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr IA010.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,015 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,010 |
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 source (Gemma direct ou Codex distillé), 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 ».