Recurrent DNA Mutations In Non-Hodgkin Lymphomas Reveal Candidate Therapeutic Targets
Notice bibliographique
Résumé
Abstract Abstract 632 Introduction: Non-Hodgkin lymphomas (NHL) are the most common type of lymphoma and can be broadly classified as indolent (slow-growing) diseases, progressing over many years; and aggressive (fast-growing) diseases, which progress rapidly. The latter class includes diffuse large B-cell lymphoma (DLBCL), which accounts for approximately 30% of all NHL diagnoses. Three DLBCL subtypes have been identified based on gene expression profiling, namely: germinal center B-cell (GCB), activated B-cell (ABC) and primary mediastinal B-cell lymphoma (PMBCL). These subtypes show substantial differences in response to treatment and ultimate disease outcome, suggesting that molecular subtyping is an important prognostic indicator and that each subtype may benefit from a distinct treatment regimen. Despite recent advances in cancer genomics revealing molecular and mutational differences between these subtypes, further studies focused on the common NHL subtypes are required to identify critical players in the pathogenesis of DLBCL that may be targeted by pharmacological intervention to improve patient outcome. Methods: Using ultra-high throughput whole genome shotgun sequencing (WGSS) and whole transcriptome shotgun sequencing (WTSS/RNA-seq) we have discovered protein-coding mutations in NHL genomes. With a focus on recurrent and likely gain-of-function mutations we have established procedures to model the three-dimensional structures of mutant proteins and using a computational “molecular docking” pipeline have identified candidate molecules with specificity for the mutant protein. These small molecule compounds are acquired and tested in cell proliferation assays against a suite of DLBCL cell lines characterized for target mutations. Results: Mutations affecting a single key tyrosine in the catalytic site of enhancer of zeste, homolog 2 (EZH2), a member of the Polycomb-group family involved in transcriptional repression were identified (Morin, R. et al. 2010 Nature Genetics 42(2):181-5). This mutation, in a gene previously unknown to be mutated in cancer, is restricted to the GCB subtype of lymphomas and is highly prevalent in patient samples and DLBCL cell lines. Mutations have also been observed in other proteins involved in epigenetic regulation and thus afford potentially novel therapeutic targets. In proof-of-principle experiments small molecule inhibitors were identified using molecular docking approaches to target the effect of EZH2 mutations in both mutant and wild-type DLBCL cell lines. We identified and imported 96 compounds from the Developmental Therapeutic Program NCI/NIH repository. These compounds were tested in alamarBlue cell proliferation assays revealing three with activity at 10uM concentration in EZH2 mutant but not wild-type cells. Computational optimization of these compounds is underway to identify related compounds with improved activities at reduced concentrations. Conclusions: High-throughput sequencing platforms have enabled the identification of recurrent, non-synonymous protein mutations in tumor genomes and transcriptomes. Such a catalogue of mutations provides new avenues of exploration for targeted therapy including small molecule inhibitors. Despite intensive efforts launched in recent years to determine the crystal structure for every human protein, many (including EZH2) do not currently have three dimensional structures. This poses a challenge to novel drug discovery but can be overcome using homology modeling and/or targeting other members of a pathway. Our observations also demonstrate the importance of epigenetic regulation in NHL tumorigenesis and thus provide potential new therapeutic targets. 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».