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Record W2809959753 · doi:10.1158/1538-7445.am2018-4437

Abstract 4437: Down-modulation of ADAR1-mediated GLI1 editing alters extracellular and immune response genes in multiple myeloma

2018· article· en· W2809959753 on OpenAlexaff
Leslie Crews, Elisa Lazzari, Phoebe Mondala, Nathaniel P. Delos Santos, Amber Miller, Gabriel Pineda, Qingfei Jiang, Anusha-Preethi Ganesan, Christina Wu, Caitlin Costello, Mark D. Minden, Raffaella Chiaramonte, A. Keith Stewart, Catriona Jamieson

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsRNA editingBiologySmall hairpin RNACancer researchGene knockdownMolecular biologyRNAGeneticsCell cultureGene

Abstract

fetched live from OpenAlex

Abstract Introduction: Representing 10% of hematologic malignancies, multiple myeloma (MM) is typified by clonal plasma cell proliferation in the bone marrow (BM) and may progress to therapy-resistant plasma cell leukemia (PCL). Despite many novel therapies, relapse rates remain high as a result of malignant regeneration (self-renewal) of MM cells in inflammatory microenvironments. In addition to recurrent DNA mutations and epigenetic deregulation, inflammatory cytokine-responsive adenosine deaminase associated with RNA (ADAR1)-mediated adenosine to inosine (A-to-I) RNA editing has emerged as a key driver of cancer relapse and progression. In MM, copy number amplification of chromosome 1q21, which contains both ADAR1 and interleukin-6 receptor (IL-6R) gene loci, portends a poor prognosis. Thus, we hypothesized that ADAR1 copy number amplification combined with inflammatory cytokine activation of ADAR1 stimulates malignant regeneration of MM and therapeutic resistance. Methods and Results: Analysis of MMRF CoMMpass RNA sequencing (RNA-seq) data revealed that high ADAR1 expression (n=162 patients) correlated with significantly reduced progression-free and overall survival compared with a low ADAR1 subset (n=159 patients). In contrast to lentiviral ADAR1 shRNA knockdown and overexpression of an editase defective ADAR1 mutant (ADAR1E912A), lentiviral wild-type ADAR1 overexpression enhanced editing of GLI1, a Hedgehog (Hh) pathway transcriptional activator and self-renewal agonist. Editing of GLI1 transcripts enhanced GLI transcriptional activity in luciferase reporter assays, and promoted lenalidomide resistance in vitro. Finally, lentiviral shRNA ADAR1 knockdown reduced regeneration of high-risk MM in humanized serial transplantation mouse models, indicative of reduced malignant self-renewal capacity. Whole-transcriptome RNA-sequencing of primary samples after lentiviral shRNA knockdown of ADAR1 revealed specific modulation of extracellular and immune response genes, while overexpression of wild-type versus edited GLI1 elicited distinct gene expression changes in human myeloma cells analyzed using NanoString nCounter assays. These data demonstrate that ADAR1 promotes malignant self-renewal of MM and, if selectively inhibited, may prevent progression and relapse through modulation of extracellular and immune response genes. Conclusions: Deregulated RNA editing, driven by aberrant ADAR1 activation, represents a unique source of transcriptomic and proteomic diversity, resulting in self-renewal of MM cells in inflammatory microenvironments. In summary, both genetic (1q21 amplification) and microenvironmental factors (inflammatory cytokines, IMiDs) combine to drive GLI1-dependent malignant regeneration in MM. Thus, ADAR1 represents both a vital prognostic biomarker and therapeutic target in MM. Citation Format: Leslie A. Crews, Elisa Lazzari, Phoebe K. Mondala, Nathaniel Delos Santos, Amber Miller, Gabriel Pineda, Qingfei Jiang, Anusha-Preethi Ganesan, Christina Wu, Caitlin Costello, Mark Minden, Raffaella Chiaramonte, A. Keith Stewart, Catriona H. M. Jamieson. Down-modulation of ADAR1-mediated GLI1 editing alters extracellular and immune response genes in multiple myeloma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4437.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.038
GPT teacher head0.349
Teacher spread0.311 · 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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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