Accounting for the Unique Molecular Landscape of Pediatric Malignancies Improves Target-Agent Pair Identification for Pediatric Precision Oncology
Notice bibliographique
Résumé
Abstract Precision medicine has significant potential to improve therapy options for patients who have exhausted treatment options for their relapsed or refractory cancers. Next-generation sequencing has enabled the detection of genetic abnormalities in individual tumours that bestow sensitivity to selective agents targeting these dysregulated cellular pathways. Several programs have recently launched that utilize sequencing technology to identify patient mutations and match the patients to clinical trials for agents that target the dysregulted pathway. The Pediatric MATCH trial initiated by the National Cancer Institute (NCI) and Children's Oncology Group (COG) exemplifies this approach, but also emphasizes the numerous obstacles involved in molecularly-guided therapies The target and agent prioritization strategy for the Pediatric MATCH trial was recently outlined. It employs an amplicon-based targeted sequencing panel (OCAV3) that was originally developed to capture informative variants for adult tumours, with the current version 3 including a set of pediatric-specific variants. However, the landscape of genomic alterations across pediatric malignancies differs from adult malignancies, which translate to distinct oncogenic drivers. The fundamental differences in the genomic landscapes observed in adult and pediatric malignancies must therefore be considered in the optimization of target identification for precision oncology. We hypothesized that a pediatric-focused targeted sequencing panel (OCCRA) will be more informative than an adult-focused panel (OCAV3) for pediatric malignancies. To compare target-agent pairs identified by OCAV3 and OCCRA, we performed a retrospective analysis of 28 childhood tumour samples, 10 B-ALL, 4 T-ALL, 6 neuroblastomas, and 8 additional solid tumours. For 12 of these tumours, whole genome sequencing (WGS) was performed on matched samples and all sequencing results were filtered for pediatric cancer driver genes. For the 12 samples tested by all three sequencing modalities, we found that the greatest discordance occurred in samples with low (<25%) tumour content. In these samples, however, all three modalities gave highly concordant detection of pediatric driver mutations, indicating the robustness of amplicon-based sequencing. Following the prioritization strategies outlined by the Pediatric MATCH committee, at least one target-agent pair was detected for 16 of 28 samples sequenced by the OCAV3 panel with 23 total agents identified due to multiple variants per sample. Using the OCCRA panel, however, we detected at least one target-agent pair for 19 of 28 samples with 25 total agents. Importantly, a fusion was detected by OCCRA in 3 samples, whereas OCAV3 was unable to detect these fusions due to panel content. Of particular note was the detection of homozygous loss in CDKN2A, which was the most commonly identified target, assigned seven times for OCAV3 and 11 times for OCCRA. Although genomic loss in CDKN2A or CDKN2B is not validated by the manufacturer, orthologous verification through clinical reports and WGS indicates that the OCCRA panel called nine of nine verifiable losses in these genes across the 28 samples. Variants were also detected within targetable pathways currently not included in the Pediatric MATCH trial, such as the JAK/STAT or tyrosine kinase pathways; inclusion of inhibitors targeting these pathways increased the total number of agents to 25 for OCAV3 and 29 for OCCRA. In addition, use of the OCCRA panel enabled detection of potentially targetable cancer driver mutations, including gains in RUNX1, ABL2, or ERBB2 and a SMARCA4 SNV, in several samples for which no established target-agent pairing was assigned. Overall, amplicon-based sequencing was highly reproducible across independent panels, robust to low tumour content, and enabled cost-effective target-agent pairing with short 2-3 day turnaround times. Furthermore the pediatric cancer-specific OCCRA panel improved the identification rate of target-agent pairs and resulted in more frequent matching with multiple agents. Disclosures No relevant conflicts of interest to declare.
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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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,002 | 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 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 ».