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Record W3083557162 · doi:10.1158/1538-7445.am2020-1782

Abstract 1782: N-myristoyltransferase proteins in breast cancer: Prognostic relevance and validation as a new drug target

2020· article· en· W3083557162 on OpenAlexaff
John R. Mackey, Justine Lai, Utkarsh Chauhan, Weifeng Dong, Darryl Glubrect, Sunita Ghosh, Gilbert Bigras, Raymond Lai, Luc G. Berthiaume

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBreast cancerImmunohistochemistryCancerBiologyAntibodyCancer researchApoptosisMonoclonal antibodyHazard ratioInternal medicineOncologyMedicineImmunologyBiochemistry

Abstract

fetched live from OpenAlex

Abstract N-myristoyltransferases (NMTs) catalyze the addition of 14-carbon fatty acids to the N-terminus of proteins. This activity regulates numerous membrane-bound signal transduction pathways important in cancer biology, and the pan-NMT inhibitor PCLX-001 is in clinical development as a cancer therapy. The physiologic distribution and relative contributions of the two human NMTs, NMT1 and NMT2, remain poorly understood as previous studies used polyclonal antibodies with potential cross-reactivity. We generated and validated mutually exclusive monoclonal antibodies (mAbs) specific to the human isotypes of NMT1 and NMT2. These mAbs were used to perform an immunohistochemical (IHC) analysis of the abundance and distribution of NMT1 and NMT2 in normal human breast epithelial samples and a large (n=703) cohort of primary breast adenocarcinomas from the BCIRG001 study. While NMT1 protein was readily identifiable in most normal and transformed breast epithelial tissue, NMT1 abundance was associated with higher overall histologic grade, higher Ki67, and lower hormone expression. While NMT2 protein was readily detected in normal breast epithelial tissue, NMT2 protein was undetectable in the majority of malignant breast cancers, but detectable NMT2 protein correlated with significantly poorer overall survival outcomes (hazard ratio for death 1.36; p < 0.029) and significantly worse biological features including younger age, higher histologic grade, lower hormone receptor expression, higher Ki67, and p53 positivity. NMT status was unrelated to HER2 status. NMT1 and NMT2 protein abundances were positively correlated with each other. Treatment of cultured breast cancer cells with the pan-NMT inhibitor PCLX-001 reduced cell viability in vitro. Daily oral administration of PCLX-001 to immunodeficient mice bearing human MDA-MB-231 breast cancer xenografts induced significant dose-dependent tumor growth inhibition in vivo. These results support the further evaluation of NMT immunohistochemistry for selection of patients for NMT inhibitor therapy, and clinical trials of NMT inhibition in breast cancer patients. Citation Format: John R. Mackey, Justine Lai, Utkarsh Chauhan, Wei-Feng Dong, Darryl Glubrect, Sunita Ghosh, Gilbert Bigras, Raymond Lai, Luc G. Berthiaume. N-myristoyltransferase proteins in breast cancer: Prognostic relevance and validation as a new drug target [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1782.

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)0.001
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.039
GPT teacher head0.370
Teacher spread0.330 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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