Abstract 4260: Clinical testing and implementation of the TruSight Myeloid Next Generation Sequencing (NGS) panel for identification of clinically relevant variants in hematological malignancies
Notice bibliographique
Résumé
Abstract Recent cancer genome profiling studies have increased our understanding of the somatic mutation landscape of myeloid malignancies. A number of genes and variants are known to have prognostic/predictive utility in several myeloid malignancies, allowing for more accurate stratification, and enhanced patient management. This has led to consideration of NGS for detection of somatic mutations in myeloid malignancies in the clinical diagnostic setting, to supplant single-gene molecular testing assays in current use. Building on our prior work establishing a novel mass spectrometry-based high throughput mutation detection assay for hematologic malignancies, we investigated the application of NGS to myeloid malignancy diagnostics. To do this, we validated the Illumina TruSight Myeloid Sequencing Panel (54 genes, 568 amplicons) on 71 acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasm (MPN) patient samples, alongside relevant controls. NGS Libraries were prepared using standard protocols, and sequencing performed on the Illumina MiSeq platform. Concordance among NGS calls, single gene tests, and Sanger verification was tested as part of the clinical validation process. Analysis of 41 cases tested in our previously developed mass spectrometry assay indicated 100% concordance (70/70) for reportable variants mutually covered in both assays. Single nucleotide variations detectable in lab-standard single gene assays were all found by NGS (100% concordance). 58/71 (82%) cases had at least one additional potentially clinically relevant variant that would not have been identified in the existing assay (mean 1.95 additional variants/case; range 1-9). Additionally, we determined that AMLs carrying IDH1, IDH2 or TET2 mutations had a higher mutation burden (mean 4.6 mutations/case, range 2-7), compared to AMLs wild-type for these three genes (mean 3.1 mutations/case, range 2-4; p = 0.008). Clinically relevant insertions (up to 33 bp) and deletions (up to 52 bp) associated with AML and MPN, including FLT3 ITD and CALR deletions, were detected in known positive cases. In these cases, our analysis was supplemented with a custom bioinformatics algorithm allowing for alignment against an artificial reference sequence to detect larger indels. Due to low coverage of the clinically actionable CEBPA, we supplemented the NGS assay with Sanger sequencing for this locus. Therefore, we report the validation of an NGS panel for high throughput detection of mutations in myeloid malignancies, and the development of a wet-bench and informatics workflow enabling maximal information benefit in the diagnostic setting. This pipeline allows the detection of variants that impact diagnosis and patient management, with significantly improved information benefit over current tests. Citation Format: Mariam Thomas, Mahadeo Sukhai, Tong Zhang, Djamel Harbi, Justin De Souza, Katherine MacDonald, Trevor Pugh, Mark Minden, Andre Schuh, Tracy L. Stockley, Suzanne Kamel-Reid. Clinical testing and implementation of the TruSight Myeloid Next Generation Sequencing (NGS) panel for identification of clinically relevant variants in hematological malignancies. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4260. doi:10.1158/1538-7445.AM2015-4260
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 | 0,007 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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.
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 ».