DNA Copy Number Gains of TCF4 (E2-2) Are Associated with Poor Outcome in Diffuse Large B-Cell Lymphoma
Notice bibliographique
Résumé
Abstract The development of B-cells is a complex process that proceeds through multiple stages and is regulated by a hierarchy of transcription factors and other physiologic signals. Each unique B-cell malignancy can be aligned with a 'normal counterpart' at one or more of these discrete developmental stages. However, with the exception of translocations of transcription factor genes, the genetic basis for this is not well defined. We performed an analysis of high-resolution single nucleotide polymorphism (SNP) microarrays from 694 diffuse large B-cell (DLBCL) tumors to identify significant somatic copy number alterations (SCNA). Through integrative analysis of 249 tumors with matched gene expression profiling (GEP) data, we identified the likely targets of these alterations and found that genes that were targeted by DNA copy number gain were significantly enriched for DNA binding activity and transcription factor function. We extended upon this observation by analyzing SNP microarray data of a further 2,716 tumors from 7 additional subtypes of B-cell malignancy. Through this analysis, we identified patterns of transcription factor alterations that aligned with the differentiation state of the 'normal B-cell counterpart' of each malignancy. This provides evidence that SCNA of B-cell transcription factors may underlie the differentiation state of B-cell malignancies. DLBCL can be divided into two subtypes based upon gene expression profiles that align with either the germinal center B-cell differentiation state (GCB-like) or a post-GCB activated B-cell state (ABC-like). Having observed an enrichment for transcription factor SCNAs in DLBCL, and an alignment between transcription factor alterations and differentiation states in other B-cell malignancies, we hypothesized that SCNAs of transcription factors may also underlie the etiology of these molecular subtypes. By testing for associations between SCNAs and cell of origin subtype, we identified three co-segregating DNA copy number gains that were significantly enriched in the ABC-like subtype. These included gains of the BCL6 and SPIB genes that have been previously observed to be associated with the ABC-like subtype. In addition, we found gains of the TCF4 (E2-2) gene to be significantly enriched in ABC-like tumors. In line with this, TCF4 alterations were significantly associated with reduced overall survival in cohorts of patients treated with either CHOP (n=232, P=0.009) or R-CHOP (n=197, P=0.041). B-cell receptor (BCR) signaling is a key survival pathway in ABC-like DLBCL, and the TCF4 gene has a defined role in promoting the expression of immunoglobulin (Ig) genes that encode the B-cell receptor (BCR). The analysis of paired SCNA and GEP data revealed a significantly higher expression of Ig genes in tumors with TCF4 DNA copy number gain compared to those without, suggesting that normal BCR expression may be deregulated by this genetic alteration. In addition, chromatin-immunoprecipitation sequencing (ChIP-seq) for TCF4 in ABC-like DLBCL cell lines also revealed binding of TCF4 to an Ig gene enhancer region. As BCR signaling can be altered by somatic mutations in the CARD11, CD79B and MYD88 genes, we evaluated the relative representation of these mutations and TCF4 DNA copy number gains using targeted deep sequencing of 124 DLBCL tumors. This revealed that TCF4 DNA copy number gains largely mutually excluded CARD11 mutations, but significantly co-segregated with both MYD88 (FDR=0.005) and CD79B (FDR=0.053) mutations. In addition, we observed significant co-segregation between CD79B and MYD88 mutations (FDR<0.001). This is particularly notable due to the preliminary associations between combined CD79B and MYD88 mutation status and response to an inhibitor of BCR signaling, Ibrutinib. Together these data highlight an association between SCNA of B-cell transcription factors and the differentiation state of the 'normal counterpart' of the respective malignant B-cell. In line with this, we show that DNA copy number gains of the TCF4 transcription factor are associated with the ABC-like subtype of DLBCL, significantly worse overall survival, and increased Ig expression. These characteristics, in addition to the co-association between TCF4 DNA copy number gains and somatic mutations of CD79B and MYD88, suggest that TCF4 may be an important modifier of BCR signaling and contribute to the etiology of ABC-like DLBCL. Disclosures Rosenquist: Gilead Sciences: Speakers Bureau. Lunning:TG Therapeutics: Consultancy; AbbVie: Consultancy; Gilead: Consultancy; Bristol-Myer-Squibb: Consultancy; Juno: Consultancy; Genentech: Consultancy; Spectrum: Consultancy; Celgene: Consultancy; Pharmacyclics: Consultancy. Rodig:Bristol-Myers Squibb: Honoraria, Research Funding; Perkin Elmer: Membership on an entity's Board of Directors or advisory committees. Levy:Kite Pharma: Consultancy; Five Prime Therapeutics: Consultancy; Innate Pharma: Consultancy; Beigene: Consultancy; Corvus: Consultancy; Dynavax: Research Funding; Pharmacyclics: Research Funding.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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) | 0,001 | 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 ».