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Record 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 on 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

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related gene regulation
Canadian institutionsSpinal Cord Injury BC
Fundersnot available
KeywordsBiologyGerminal centerMutationGermlinePhenotypeDiffuse large B-cell lymphomaSomatic hypermutationB cellGeneticsMissense mutationLymphomaCancer researchGeneImmunologyAntibody

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.205
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2021
Admission routes1
Has abstractyes

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