Next-Generation Sequencing of Lymphoid Cancers: From Discovery to Clinical Translation
Notice bibliographique
Résumé
Abstract Abstract SCI-12 Since completion of the reference human genome and the introduction of next-generation sequencing (NGS) technologies, a number of key discoveries have significantly added to our understanding of the fundamental biology and mutational landscape of the mature B-cell lymphoid malignancies. By the end of 2012, most mature B-lineage lymphoid cancers will have been sequenced to a reasonable number and depth of coverage to inform on the pattern of recurrent mutations, gene fusions, and other somatic genetic events contributing to the biology. Discerning the important driver mutations from passengers and using filters to decide on what alterations to carry through to functional validation will be critical to informing on the biology in a timely manner. The value of whole genome sequencing with respect to noncoding alterations and discovery has already been realized and will become even more apparent when contrasting these data with the more economical exome-based sequencing strategies. These and related topics will be discussed by Dr. Elaine Mardis in her scientific session presentation. In 2010 we saw these technologies lead to the discovery of recurrent activating (gain-of-function) mutations in EZH2, a histone methyltransferase and member of the polycomb repressor 2 complex that is responsible for laying down repressive chromatin marks by trimethylating H3K27. These mutations were found in follicular lymphoma (FL) and in the germinal center B-cell-like subtype of diffuse large B-cell lymphoma (DLBCL). Subsequent genomic studies uncovered loss-of-function mutations in EZH2 in myeloid tumors, contrasting the very different contributions of one gene in these diverse entities. Studies by Pasqualucci, Morin, and colleagues further expanded the role of histone modification and chromatin remodeling in both FL and DLBCL by implicating recurrent mutations in CREBBP, EP300, MLL2, MEF2B, SETD2, and core histone protein genes, including HIST1H1E, HIST1H1D, HIST1H2AC, and HIST1H2BD. RNA-seq technology was used to uncover novel gene fusions in classical Hodgkin lymphoma and the related entity primary mediastinal large B-cell lymphoma that target CIITA, the master regulator of MHC class II expression. Fusion partners in some of the cases involve the ligands of PD-1 and thus establish immune escape as a key oncogenic driver in some lymphoid malignancies. The application of NGS strategies to chronic lymphocytic leukemia, hairy cell leukemia, mantle cell lymphoma, and lymphoplasmacytic lymphoma has revealed a number of recurrent somatic mutations of key genes, including NOTCH1, MYD88, XPO1, KLHL6, SF3B1, and BRAF (V600E) to name but a few. Validation in extension sets and functional studies will be required to fully understand the contribution of these genetic alterations to lymphoma biology and to know which targets are logically suited to the development of targeted therapies. Last, the deployment of these NGS discoveries into the clinical laboratory may take several forms, including targeted resequencing used for diagnosis and subclassification, assessing clonal dominance for sequencing of therapies in some lymphomas, as well as their use in minimal residual disease detection. Disclosures: No relevant conflicts of interest to declare.
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 | 0,006 | 0,009 |
| 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 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,003 |
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 ».