N-myristoyltransferase proteins in breast cancer: prognostic relevance and validation as a new drug target
Bibliographic record
Abstract
PURPOSE: N-myristoyltransferases 1 and 2 (NMT1 and NMT2) catalyze the addition of 14-carbon fatty acids to the N-terminus of proteins. Myristoylation regulates numerous membrane-bound signal transduction pathways important in cancer biology and the pan-NMT inhibitor PCLX-001 is approaching clinical development as a cancer therapy. The tissue distribution, relative abundances, and prognostic value of the two human NMTs remain poorly understood. METHODS: We generated and validated mutually exclusive monoclonal antibodies (mAbs) specific to human NMT1 and NMT2. These mAbs were used to perform immunohistochemical analysis of the abundance and distribution of NMT1 and NMT2 in normal breast epithelial samples and a large cohort of primary breast adenocarcinomas from the BCIRG001 clinical trial (n = 706). RESULTS: NMT1 protein was readily quantified in normal and most transformed breast epithelial tissue and was associated with higher overall histologic grade, higher Ki67, and lower hormone receptor expression. While NMT2 protein was readily detected in normal breast epithelial tissue, it was undetectable in the majority of breast cancers. Detectable NMT2 protein correlated with significantly poorer overall survival (hazard ratio 1.36; P = 0.029) and worse biological features including younger age, higher histologic grade, lower hormone receptor expression, higher Ki67, and p53 positivity. Treatment of cultured breast cancer cells with PCLX-001 reduced cell viability in vitro. Daily oral administration of PCLX-001 to immunodeficient mice bearing human MDA-MB-231 breast cancer xenografts produced significant dose-dependent tumor growth inhibition in vivo. CONCLUSIONS: These results support further evaluation of NMT immunohistochemistry for patient selection and clinical trials of NMT inhibition in breast cancer patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".