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Enregistrement W3213874179 · doi:10.1182/blood-2021-149921

<i>BTG1</i> Mutation Promotes Aggressive Lymphoma Development By Lowering the Threshold to MYC Activation and Generating "Super-Competitor" B Cells

2021· article· en· W3213874179 sur OpenAlexaff
Coraline Mlynarczyk, Matthew Teater, Juhee Pae, Theinmozhi Arulraj, Christopher R. Chin, Ling Wang, Jonatan Ersching, Ekaterina D. Kots, Amy Chadburn, Ersilia Barin, Hui Xian Poh, Hannah M. Isles, Chen Zhengming, Hao Shen, Arnab Bandyopadhyay, Kenneth B. Hoehn, Diu Nguyen, Ashley S. Doane, Huimin Geng, Muhammad Hassan Rehman, Jonah Melnick, Wyatt Morgan, Olivier Elemento, Michael G. Kharas, David W. Scott, Samie R. Jaffrey, Michael Meyer‐Hermann, George Khelashvili, Gabriel D. Victora, Ari Melnick

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueCancer-related gene regulation
Établissements canadiensSpinal Cord Injury BC
Organismes subventionnairesnon disponible
Mots-clésBiologyGerminal centerMutationGermlinePhenotypeDiffuse large B-cell lymphomaSomatic hypermutationB cellGeneticsMissense mutationLymphomaCancer researchGeneImmunologyAntibody

Résumé

récupéré en direct d'OpenAlex

Abstract Somatic missense mutations of BTG1 are exclusive to germinal center (GC)-derived B cell lymphomas (~12% of DLBCLs) and are most prevalent in ABC-DLBCL (p=0.0184 vs GCB-DLBCL), particularly in the MCD/cluster 5 subtype, which features extranodal dissemination and unfavorable outcome. However, the relevance, mechanism of action and biological contribution of BTG1 mutations have not been studied. Using a rigorous genomic covariate analysis, we identified BTG1 mutations as a top genetic driver in DLBCL. Furthermore, molecular dynamics simulations indicated that BTG1 recurrent mutations, including the most frequent Q36H, disrupted the protein structure, with likely deleterious functional consequences. To investigate the effect of BTG1 mutation in GC B cells, we generated a conditional Btg1Q36H knock in mouse crossed to the B cell specific Cd19Cre line. Surprisingly, there was no apparent phenotype in GC B cells or other B cell populations. However, placing Btg1 Q36H and WT GC B cells in competition within the same mouse through adoptive transfer revealed a dramatic competitive advantage of Btg1 Q36H cells, virtually taking over the GC reaction. To gain further insight into this striking fitness advantage, we performed RNAseq in Btg1 Q36H GCs, which showed marked enrichment for genes induced in positively selected GC B cells, including MYC targets and biosynthetic pathways. The same genes were also enriched in BTG1 mutant DLBCL patients in 2 independent cohorts. Furthermore, Btg1 Q36H GC B cells displayed greater RNA content and cell size, reflecting increased fitness. Positive selection normally triggers a brief Myc pulse in GC B cells. We therefore crossed our Btg1Q36H mice to the MycGFPprotein fusion reporter and observed higher proportion of Myc GFP+ cells in Btg1 Q36H GCs. For mechanistic studies, we generated isogenic BTG1 Q36H or BTG1 WT human DLBCL cell lines. BTG1 Q36H cells exhibited enrichment for the same positively selected GC B and MYC target genes, as well as greater RNA content and cell size. BTG1 family members were suggested to interact with RNA. Performing RNA-immunoprecipitation, we discovered that ~800 transcripts associated with BTG1 WT, but not BTG1 Q36H. Notably, these corresponded to the same positively selected GC B and MYC target genes, including MYC itself. BTG1 was shown to regulate mRNA stability in other cell types. However, BTG1 Q36H did not alter MYC mRNA stability and instead facilitated MYC protein synthesis, thus disrupting a novel GC context-specific checkpoint mechanism, whereby BTG1 normally attenuates spurious MYC translation to tightly restrict fitness potential. In GC B cells, Myc induction coincides with S phase entry, but G2/M progression requires re-entry into the proliferative dark zone. To characterize GC dynamics in vivo, we performed targeted single cell RNAseq in competing Btg1 Q36H and WT GC B cells and noted earlier and higher proportion of positively selected Btg1 Q36H GC B cells having committed to G2/M and the proliferative program. We confirmed faster S phase completion in competing Btg1 Q36H GC B cells by in vivo EdU/BrdU labelling and greater re-entry into the proliferative dark zone by in vivo antigen delivery to synchronize GC B cells at the time of positive selection. Given that MCD-DLBCLs express high levels of BCL2, we crossed our Btg1Q36H mice to the VavP-Bcl2 model. As compared to VavP-Bcl2, VavP-Bcl2+Btg1 Q36H mice displayed shorter survival (p=0.0005), earlier onset of lymphoma, dysplastic B cell infiltration into non lymphoid organs and they contained highly mutated, selected and clonal tumor B cells. Moribund VavP-Bcl2+Btg1 Q36H mice uniquely featured sheets of large, immunoblastic lymphoma cells, characteristic of ABC-DLBCLs. Most notably, examining ABC-DLBCLs from 5 independent cohorts showed inferior clinical outcome for BTG1 mutant patients (p=0.0011) and independent association of BTG1 mutation with inferior overall survival by multivariable Cox regression (p=0.0190). Collectively, we find that BTG1 mutations mediate lymphomagenesis through an entirely novel mechanism of action that recapitulates the embryonic MYC-dependent "super-competitive" phenotype originally described in Drosophila imaginal disc cells. In the GC, "super-competition" is provided by BTG1 mutation via a subtle acceleration of MYC induction and GC dynamics, conferring dramatic fitness and the potential to transform into aggressive lymphomas. Disclosures Hoehn: Prellis Biologics: Consultancy. Elemento: Janssen: Research Funding; Freenome: Consultancy, Other: Current equity holder in a privately-held company; Volastra Therapeutics: Consultancy, Other: Current equity holder, Research Funding; Owkin: Consultancy, Other: Current equity holder; Champions Oncology: Consultancy; One Three Biotech: Consultancy, Other: Current equity holder; Eli Lilly: Research Funding; AstraZeneca: Research Funding; Johnson and Johnson: Research Funding. Scott: NanoString Technologies: Patents &amp; Royalties: Patent describing measuring the proliferation signature in MCL using gene expression profiling.; BC Cancer: Patents &amp; Royalties: Patent describing assigning DLBCL COO by gene expression profiling--licensed to NanoString Technologies. Patent describing measuring the proliferation signature in MCL using gene expression profiling. ; AstraZeneca: Consultancy; Abbvie: Consultancy; Celgene: Consultancy; Incyte: Consultancy; Janssen: Consultancy, Research Funding; Rich/Genentech: Research Funding. Melnick: Constellation: Consultancy; Epizyme: Consultancy; Daiichi Sankyo: Research Funding; Sanofi: Research Funding; Janssen Pharmaceuticals: Research Funding; KDAC Pharma: Membership on an entity's Board of Directors or advisory committees.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,424

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,005
Tête enseignante GPT0,205
Écart entre enseignants0,200 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2021
Routes d'admission1
Résumé présentoui

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