<i>TRAF3</i> Loss Drives Alternative NF-κB Pathway Activation in Diffuse Large B-Cell Lymphoma
Notice bibliographique
Résumé
Introduction: Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) is a transcription factor family that regulates gene expression programs contributing to inflammation and cell survival. NF-κB signaling occurs via two branches: classical and alternative, and is often enriched in somatic mutations of key pathway members in several lymphoid malignancies. Here, we reveal deregulation and constitutive activation of the alternative NF-κB pathway in a subset of DLBCL patients with recurrent genomic loss of the gene encoding tumor necrosis factor receptor-associated factor 3 (TRAF3), a regulator of the NF-κB signaling pathway. Methods and Results: To uncover novel driver mutations of DLBCL pathogenesis and tumor maintenance, we performed Affymetrix SNP6.0 copy number analysis on 347 de novo DLBCL samples from patients uniformly treated with rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP). We observed frequent, focal genomic loss of chr:14q32.31-32 which included TRAF3 and RCOR1 (7%, 22/313) in the minimally deleted region and an enrichment of activated B-cell-like (ABC) subtype cases over germinal center B-cell-like (GCB) subtype cases, confirming previously published data (Chan et al, Blood 2014). RNAseq of these DLBCL samples revealed a significant reduction of TRAF3 mRNA in chr:14q32.31-32 deleted cases compared to copy number neutral cases (p=0.002). Next, we focused on characterizing the phenotypic consequences of TRAF3 loss in DLBCL. We used CRISPR/Cas9 gene editing to knock out TRAF3 in 2 GCB-DLBCL (DOHH2, OCI-LY1) and 2 ABC-DLBCL (HBL1, OCI-LY3) cell lines. We performed immunoblotting analysis of NF-κB pathway members on cell fractionated samples of TRAF3 knockout cells and found increased levels of the NF-κB inducing kinase NIK (a direct target of TRAF3-mediated ubiquitin-proteasome degradation) and a concomitant increased nuclear translocation of NF-κB transcription factor complex subunits RelB and p52. Proteasome blockade restored RelB cytoplasmic localization and reduced processed p52 protein in TRAF3 knockout GCB-DLBCL lines only, indicating other factors may contribute to alternative NF-κB activation in ABC-DLBCL. Moreover, classical NF-κB activation remained unaffected, highlighting the specific role of TRAF3 regulation on the alternative NF-κB pathway in DLBCL. Consistent with these findings, TRAF3 knockout cells exhibited NF-κB-dependent transcriptional upregulation by luciferase reporter activity and elevated pro-inflammatory cytokine production (IL-6, TNF-β) by Luminex and ELISA. To study transcriptome changes as a result of TRAF3 loss-of-function, we performed RNAseq and differential gene expression analysis on wildtype and TRAF3 knockout DLBCL cell lines as well as primary DLBCL samples (N=347). We found enrichment of NIK and NF-κB associated pathways in TRAF3 deficient DLBCL and uncovered additional enriched gene sets including those involved in cell cycle regulation, cell division and metabolism, suggesting a potential proliferative and survival advantage. Conclusion: Our findings link TRAF3 loss-of-function to clinical and gene expression phenotypes in DLBCL and highlight alternative NF-κB activation as a pathogenically important pathway in both GCB and ABC subtypes. Future studies will be directed towards comprehensive evaluation of NF-κB inhibitors for effective blockade of constitutive alternative NF-κB activation in DLBCL. Disclosures Scott: NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding; Janssen: Consultancy, Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy; Celgene: Consultancy; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding. Steidl:Roche: Consultancy; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Consultancy; Curis Inc: Consultancy; Juno Therapeutics: Consultancy; Bayer: Consultancy; AbbVie: Consultancy.
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 | 0,000 | 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) | 0,002 | 0,000 |
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 ».