Abstract B036: Integrating gene expression evaluation in molecular diagnostics for pediatric AML molecular classification
Notice bibliographique
Résumé
Abstract Next generation sequencing (NGS) based molecular profiling has been proven to be robust and reliable in detecting most biological attributes in acute myeloid leukemia (AML). Targeted NGS testing on genomic DNA for SNVs/Indels and on RNA for oncogenic gene fusions are commonly performed in molecular diagnostics laboratories. With the initial clinical molecular diagnostic framework established in our institution, we used whole genome and whole transcriptome sequencing (WGS and WTS) to evaluate SNVs/Indels, structural variations (SVs) and copy number variations (CNVs) in pediatric and adolescent AMLs. In addition, gene expression was assessed using WTS data to evaluate the possible pathogenicity of variants identified through DNA sequencing. In the 154 AML cases analyzed, WGS revealed recurrent AML oncogenic fusions in 88, all of which were confirmed to be in-frame fusion transcripts by WTS. AML-defining SNVs/Indels and internal tandem duplications were detected by WGS in 45 cases with supporting evidence from WTS. WGS revealed potential enhancer hijacking fusions in 10 cases (MECOM-r in 6, HOXA-r in 2 and BCL11B::TLX3 in 2). Among them, increased expression of the oncogene of interest was verified by WTS in 8 cases (6 MECOM-r and 2 HOXA-r). In the remaining two cases (FAB classification of AML M0 and M1, respectively) for which WGS suggested an SV of BCL11B::TLX3, expression of TLX3 was barely detectable and expression of BCL11B was not increased. Furthermore, global gene expression profiling did not cluster these cases within any known AML molecular categories. Together, the gene expression data of the two cases was not consistent with an SV leading to aberrant TLX3 or BCL11B activation, resulting in the final classification of AML, NOS. Among the 7 cases that initially could not be molecularly classified based on sequence variants only, gene expression assessment helped elucidate the AML class-defining genetic driver in one case. While no apparently known genetic driver was detected by WGS and WTS analyses, an acquired heterozygous frameshift variant in the N-terminal transcription activation domain of CEBPA (35% variant allele frequency, VAF) was found. Notably, the same variant in CEBPA was observed in WTS at 97% VAF, indicating the exclusive expression of the mutant allele in the tumor. Furthermore, global gene expression profiling demonstrated the same characteristic expression profile as seen in CEBPA double mutants (CEBPA-dm). Together, the gene expression assessment obtained from WTS provided an essential tool to classify this case to the molecular subgroup of CEBPA-dm. In this study, gene expression obtained from WTS was used to complement WGS, providing gene/allele-specific expression and global gene expression profiling, to verify the possible pathogenicity of sequence variants identified through DNA sequencing. We demonstrated that molecular classification of AML can be further improved using a diagnostic framework of WGS and WTS as well as integrating gene expression evaluation to complement sequence variants analysis. Citation Format: Lu Wang, Rebecca Voss, Victor Pastor Loyola, Maria F. Cardenas, Jing Ma, Priya Kumar, Mark R. Wilkinson, David A. Wheeler, Jeffery M. Klco. Integrating gene expression evaluation in molecular diagnostics for pediatric AML molecular classification [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 B036.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 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) | 0,003 | 0,002 |
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 ».