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Record W2531891923 · doi:10.1182/blood.v116.21.632.632

Recurrent DNA Mutations In Non-Hodgkin Lymphomas Reveal Candidate Therapeutic Targets

2010· article· en· W2531891923 on OpenAlexaff
Andrew J. Mungall, Ryan D. Morin, Jianghong An, Oleksandr Yakovenko, Merrill Boyle, Nathalie A. Johnson, Bruce W. Woolcock, Stephen Leach, Michael Mayo, María Méndez-Lago, Sarah Munro, Thomas Zeng, Yongjun Zhao, Martin Hirst, Robert A. Holt, Richard A. Moore, Jacqueline E. Schein, Randy D. Gascoyne, Douglas E. Horsman, Joseph M. Connors, Steven J.M. Jones, Marco A. Marra

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsBiologyLymphomaGerminal centerKRASCancer researchDiffuse large B-cell lymphomaTranscriptomeComputational biologyB cellGeneGeneticsMutationImmunologyAntibodyGene expression

Abstract

fetched live from OpenAlex

Abstract Abstract 632 Introduction: Non-Hodgkin lymphomas (NHL) are the most common type of lymphoma and can be broadly classified as indolent (slow-growing) diseases, progressing over many years; and aggressive (fast-growing) diseases, which progress rapidly. The latter class includes diffuse large B-cell lymphoma (DLBCL), which accounts for approximately 30% of all NHL diagnoses. Three DLBCL subtypes have been identified based on gene expression profiling, namely: germinal center B-cell (GCB), activated B-cell (ABC) and primary mediastinal B-cell lymphoma (PMBCL). These subtypes show substantial differences in response to treatment and ultimate disease outcome, suggesting that molecular subtyping is an important prognostic indicator and that each subtype may benefit from a distinct treatment regimen. Despite recent advances in cancer genomics revealing molecular and mutational differences between these subtypes, further studies focused on the common NHL subtypes are required to identify critical players in the pathogenesis of DLBCL that may be targeted by pharmacological intervention to improve patient outcome. Methods: Using ultra-high throughput whole genome shotgun sequencing (WGSS) and whole transcriptome shotgun sequencing (WTSS/RNA-seq) we have discovered protein-coding mutations in NHL genomes. With a focus on recurrent and likely gain-of-function mutations we have established procedures to model the three-dimensional structures of mutant proteins and using a computational “molecular docking” pipeline have identified candidate molecules with specificity for the mutant protein. These small molecule compounds are acquired and tested in cell proliferation assays against a suite of DLBCL cell lines characterized for target mutations. Results: Mutations affecting a single key tyrosine in the catalytic site of enhancer of zeste, homolog 2 (EZH2), a member of the Polycomb-group family involved in transcriptional repression were identified (Morin, R. et al. 2010 Nature Genetics 42(2):181-5). This mutation, in a gene previously unknown to be mutated in cancer, is restricted to the GCB subtype of lymphomas and is highly prevalent in patient samples and DLBCL cell lines. Mutations have also been observed in other proteins involved in epigenetic regulation and thus afford potentially novel therapeutic targets. In proof-of-principle experiments small molecule inhibitors were identified using molecular docking approaches to target the effect of EZH2 mutations in both mutant and wild-type DLBCL cell lines. We identified and imported 96 compounds from the Developmental Therapeutic Program NCI/NIH repository. These compounds were tested in alamarBlue cell proliferation assays revealing three with activity at 10uM concentration in EZH2 mutant but not wild-type cells. Computational optimization of these compounds is underway to identify related compounds with improved activities at reduced concentrations. Conclusions: High-throughput sequencing platforms have enabled the identification of recurrent, non-synonymous protein mutations in tumor genomes and transcriptomes. Such a catalogue of mutations provides new avenues of exploration for targeted therapy including small molecule inhibitors. Despite intensive efforts launched in recent years to determine the crystal structure for every human protein, many (including EZH2) do not currently have three dimensional structures. This poses a challenge to novel drug discovery but can be overcome using homology modeling and/or targeting other members of a pathway. Our observations also demonstrate the importance of epigenetic regulation in NHL tumorigenesis and thus provide potential new therapeutic targets. 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.242
Teacher spread0.236 · 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 designObservational
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
Published2010
Admission routes1
Has abstractyes

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