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Record W2954206125 · doi:10.1158/1538-7445.am2019-3046

Abstract 3046: Targeting N-myristoylation in B cell lymphomas as a therapeutic strategy

2019· article· en· W2954206125 on OpenAlexaff
John R. Mackey, Erwan Beauchamp, Megan C. Yap, Aishwarya Iyer, Maneka A. Perinpanayagam, Krista M. Vincent, Abass Al-Momany, Ryan J. Heit, Jacky Y. Sim, Raymond Lai, Weifeng Dong, Manikandan Lakshmanan, Anandhkumar Raju, Vinay Tergaonkar, Soo‐Yong Tan, Soon Thye Lim, Lynne‐Marie Postovit, Kevin D. Read, David W. Gray, Paul G. Wyatt, Luc G. Berthiaume

Bibliographic record

VenueCancer Research · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLymphomaCancer researchB-cell lymphomaCell cultureMyristoylationMedicineBiologyInternal medicineBiochemistryPhosphorylation

Abstract

fetched live from OpenAlex

Abstract Treatment of aggressive lymphoma is toxic, expensive, and a substantial proportion of patients relapse and die. There is an urgent need for more effective treatments. Myristoylation is required for biological activity of >200 intracellular proteins. N-myristoyltransferases (NMTs) transfer the fatty acid myristate to N-terminal glycine residue; there are two isoforms, NMT1 and 2. Since they are critical to intracellular signaling, NMTs are potential anti-cancer targets. We tested a novel potent pan-NMT inhibitor, PCLX-001, in B cell lymphoma cell lines. In vitro assays included cell viability, immunoblotting, and metabolic labeling of lymphoma cell lines. Immunohistochemistry was performed on formalin fixed paraffin embedded lymphoma specimens from patients. In vivo experiments included cell line derived murine xenografts and a patient derived mouse xenograft treated with increasing concentrations of PCLX-001. PCLX-001 selectively killed lymphoma cells, while sparing normal cells in vitro and in 3 mouse xenograft models, eradicating tumors in two of these models including a patient-derived xenograft from a R-CHOP refractory lymphoma patient. While NMT2 is overexpressed in some cancers, loss of NMT2 expression is common in numerous cancers and occurs at the highest prevalence in lymphomas, where it is independently linked to a worse prognosis. This NMT2 suppression occurred through epigenetic mechanisms and may account for lymphoma sensitivity to NMT inhibition. The global myristoylation of lymphoma cell proteins, including that of the protein tyrosine kinase oncogene Src, is profoundly inhibited by PCLX-001. Loss of Src myristoylation is accompanied by loss of Src activity and may account for loss of prosurvival signals causing lymphoma cell death. Targeting NMT2 deficient B cell lymphoma with a pan-NMT inhibitor suppresses the residual NMT1 function provides a novel, selective, and effective therapeutic strategy. Citation Format: John R. Mackey, Erwan Beauchamp, Megan C. Yap, Aishwarya Iyer, Maneka A. Perinpanayagam, Krista M. Vincent, Abass M. Al-Momany, Ryan J. Heit, Jacky Y. Sim, Raymond Lai, Wei-feng Dong, Manikandan Lakshmanan, Anandhkumar Raju, Vinay Tergaonkar, Soo Yong Tan, Soon Thye Lim, Lynne M. Postovit, Kevin D. Read, David W. Gray, Paul G. Wyatt, Luc G. Berthiaume. Targeting N-myristoylation in B cell lymphomas as a therapeutic strategy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3046.

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 score0.003
Threshold uncertainty score0.011

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 communication0.0000.000
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 head0.058
GPT teacher head0.389
Teacher spread0.331 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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