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The Role of UBR5 Mutations in the Pathogenesis of Mantle CELL Lymphoma

2016· article· en· W2740436806 on OpenAlexaff
Olga A. Kutovaya, Stacy Hung, Hughes Christopher, Randy D. Gascoyne, Gregg B. Morin, Christian Steidl

Bibliographic record

VenueBlood · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsBiologyImmunoprecipitationMutantMantle cell lymphomaCancer researchUbiquitin ligaseMutationProteomeMolecular biologyGeneticsGeneUbiquitinLymphomaImmunology

Abstract

fetched live from OpenAlex

Abstract Intro: Mantle cell lymphoma (MCL) accounts for 6% of non-Hodgkin lymphomas and represents a particularly challenging disease with patient outcomes inferior to most other lymphoma subtypes. Using targeted capture sequencing of MCL biopsy samples, we recently reported frequent mutations (18%) in UBR5, a gene encoding an E3 ubiquitin-protein ligase that has not been previously implicated in lymphomagenesis. All mutations were clustered within 100bp in or around exon 58 of UBR5 and truncate the reading frame or change a key lysine residue. These mutations are predicted to result in the loss of the conserved cysteine residue in the HECT-domain, which is responsible for binding the ubiquitin co-factor. The recurrence and clustering of UBR5 mutations suggest their critical pathogenic involvement in a subgroup of MCL that might be therapeutically targetable. The aim of this study is to determine UBR5 mutation-associated proteome changes and altered cell signaling. Methods: As seen in MCL patients, mutations in exon 58 of UBR5 were introduced to three MCL cell lines (Granta-519, Jeko-1, and Mino) using the CRISPR-Cas9 genome engineering tool. First, mass spectrometry-based immunoprecipitation proteomics (IP-MS) was employed to identify differences in UBR5 interacting partners between UBR5 mutant and wildtype (WT) cells. Candidate UBR5 interacting proteins were validated by flow cytometry, western blotting, co-immunoprecipitation, and immunofluorescence. Next, global proteomes of UBR5 mutants and WT were analyzed by Tandem Mass Tag (TMT)-based mass spectrometry quantification to identify proteins with differential expression due to the UBR5 mutations. Results: The IP-MS analysis of WT vs UBR5 mutants revealed histone and cell cycle control proteins as candidate differential UBR5 interacting proteins (p<0.05). Particularly, histones H1, H4, and H2AFX, as well as the cell cycle genes CDC5L, BUB3, MAP4, RAD50 and CDK11B were identified as candidate UBR5 interacting partners. The global proteome analysis identified a set of differentially expressed genes (mutant vs wt; p<0.05) that are common among the MCL cell lines with the same direction of change. Gene ontology analysis of this set revealed DNA damage response, chromosome organization, and cell cycle response pathways as the predominant pathways affected. Moreover, our preliminary functional studies indicate constitutive phosphorylation of H2AFX in UBR5 mutants vs WT in line with the role of UBR5 in DNA damage response. Conclusions: Our results are consistent with UBR5 functioning as a key regulator of cell signalling and strongly suggest UBR5 as a novel regulator of histone modifications and DNA damage response. These findings provide an experimentally valid platform for further functional investigation and testing of target therapies for MCL harbouring UBR5 mutations. Disclosures No relevant conflicts of interest to declare.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.203
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), 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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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