Abstract 6440: Novel N-myristoyltransferase immunohistochemistry-based predictive and prognostic tests for breast cancer
Bibliographic record
Abstract
Abstract Breast cancer (BC) is the most common cancer worldwide, surpassing lung cancer incidence for the first time in 2020, and is the most common cancer diagnosed in American women. Despite the relative success of endocrine therapies in treating hormone receptor-positive (HR+) BC, de novo and developed resistances to these therapies (endocrine resistance) are still significant concerns. Furthermore, triple-negative breast cancer has a poor prognosis and remains one of the most challenging cancers to treat. We have discovered that the expression and localization of N-myristoyltransferase 2 (NMT2) could be prognostic and predictive markers for metastatic BC. We determined the expression patterns of NMT2 by immunohistochemical (IHC) analyses on primary tumor samples from treatment naïve BC patients. This retrospective study was blinded, and the tumor tissues in duplicate were stained with NMT2 monoclonal/polyclonal antibodies on an autostainer (Leica Bond). Stained slides were scored, and an "H" score representing the intensity and percent positive cells was given to each sample. In a combined cohort of BC represented by ER+, Triple Positive, and Triple Negative (n= 598) cases, we determined the expression and localization of NMT2. The localization pattern of NMT2 turned out to be a significant prognostic and predictive molecular signature. The nuclear localization serves as both prognostic and predictive markers. In a cohort of 447 ER+ BC cases that included 18 triple positive cases, the majority of the cases showed negative staining for nuclear NMT2 (n=394) and positive nuclear staining with differential expression in 53 cases. Whereas, in a cohort of 151 TNBC cases, nuclear NMT2 staining was positive in most cases (n= 116) and negative in 20 cases (undetermined; n= 15). The most important finding was the dichotomy of the nuclear NMT2 staining in predicting treatment response and prognosis. Both high cytoplasmic H score (>180) and positive nuclear staining (>0) predicted significant association with worse clinical outcomes for OS (HR = 1.72, P = .0284, 95% CI 1.06 to 2.81 for cytoplasmic NMT2 and HR = 1.74, P = 0.0006, CI 1.27 to 2.39 for the nuclear NMT2). Nuclear NMT2 status alone predicted a significant association with worse clinical outcomes to RFS (HR = 1.56, P = 0.0027, CI 1.17 to 2.09). The data from our study indicate that NMT2 could be a potential marker for predicting the likelihood of recurrence of BC and become part of routine first-line prognostic and predictive tests. Citation Format: Anuraag Shrivastav, Dean Reddick, Abinash Meher, Shailly Varma Shrivastav, Sahil Mittal, Vijayakrishna K. Gadi, Leigh Murphy. Novel N-myristoyltransferase immunohistochemistry-based predictive and prognostic tests for breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6440.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".