Notice bibliographique
Résumé
Abstract The complexity of gene expression regulation is the result of a composite interplay between promoters, enhancers and other cis-acting regulatory elements bound by transcription factors (TFs) that controls the transcriptional activity of genes. Primary tumor cells, in comparison to their healthy counterparts, are known to display altered enhancer repertoires that are associated with tumor-specific transcription. Large groups of transcriptional enhancers cluster together to form super-enhancers (SEs). These elements have been shown to control genes that are important for maintaining cell identity but are also frequently associated with oncogenes as well as translocations that result in aberrant gene expression in cancer. Immunoglobulin (IGH, IGL, IGK) and non-immunoglobulin (PVT1, FAM46C, DUSP22, etc.) enhancers hijacking by variable genes (MYC, MAF, CCND1/2/3, MMSET, IRF4) is a recognized oncogenic driver event in multiple myeloma (MM). However, the identity of the TFs or transcriptional regulatory complexes binding and regulating the activity of these enhancers remains to be fully elucidated and may yield valuable therapeutic targets. In this regard, the bromodomain and extra-terminal (BET) inhibitors have emerged as promising molecules for the treatment of hematologic malignancies. BET family proteins are chromatin adaptors, functionally linked to important pathways for cellular viability and cancer signaling. In particular, BRD4 has a direct role in the transcription regulation of different genes involved in the cell cycle progression and cellular viability. The BET inhibitor JQ1 selectively inhibits BRD4 by competitively binding to the acetyl-lysine recognition pocket of BET bromodomains from chromatin leading to the inhibition of MYC transcription in a dose- and time-dependent manner. Thus, BRD4 has been recently described as a therapeutic target for MM, among other hematologic diseases. Constitutive activation of MYC signaling is detected in more than 60% of patient-derived MM cells and can be involved in the pathogenesis of MM through different mechanisms. One of the most common somatic genomic aberrations in early and late-stage MM is rearrangement or translocation of MYC. Regardless of whether MYC rearrangements occur at early or late stages of MM pathogenesis, MYC rearrangements may provide one of several critical events contributing to increased autonomy and a more aggressive phenotype. Moreover promiscuous rearrangements of the MYC locus are known to hijack enhancers and super-enhancers to dysregulate MYC expression in MM and are involved in its pathogenesis. The development of the immunomodulatory drugs (IMiDs) has contributed significantly to improve the outcomes of MM patients. They possess pleiotropic anti-MM properties and through CRBN binding they induce Ikaros and Aiolos ubiquitylation and proteasomal degradation with an ensuing transcriptional repression of MYC and IRF4, two essential factors for myeloma cells survival. However, is not clear how IKZF1/IKZF3 regulate MYC transcription and how myeloma cells acquire resistance to IMIDs, "beyond CRBN". In addition, acquired resistance to IMIDs and the loss of the transcriptional repression of MYC are nearly universal and occur in spite of sustained IKZF1/3 degradation suggesting that transcriptional rewiring may be sustaining hijacked enhancers activity and transcription of driver oncogenes. In this contest we have recently demonstrated that IMiDs are repressors of IKZF1/3-depedent oncogenic enhancers. Transcriptional plasticity with expression of extra-lineage TFs such as the ETS family member ETV4 sustains oncogenic enhancers in MM overcoming IKAROS and AIOLOS dependency and promoting IMiDs resistance. Therefore defining TFs occupancy and their circuitry at enhancers identifies "non-canonical" (aberrant) myeloma TFs dependency that may be linked to potential therapeutic targets. Disclosures Neri: Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria.
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 | 0,000 | 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) | 0,007 | 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 ».