Abstract 7381: Mathematical modeling and validation of mechanistic target of rapamycin and N-myristoyltransferase signaling pathways in breast cancer
Bibliographic record
Abstract
Abstract Hormone receptor-positive (HR+) breast cancer (BC) makes up approximately 65% of all breast cancers diagnosed. The prognosis for early-stage disease is excellent with mainstay endocrine therapy (ET). Despite the effectiveness of standard ET, as many as 41% of HR+ early-stage BC diagnosed women will experience distant recurrence. The resistance to endocrine therapy and recurrence is partly attributed to the activation of the insulin pathway and the independence of HR+ BC cells on the ER pathway for their growth. Earlier, we demonstrated the crosstalk between insulin/mTOR and ER pathways. N-myristoyltransferase (NMT) exists in humans in two paralogues (NMT1 and NMT2) that catalyze myristoylation reaction. Recent studies from our laboratory demonstrated that NMTs are downstream targets of insulin and ER pathways. In this study, we have designed mathematical models using differential equations to study the activation of the insulin pathway and its effect on NMT. The mathematical modeling incorporated the partition of cellular organelles and the sequential flow of information with cascades of equations representing signaling reactions. The activated mathematical model was designed by activating the insulin receptor (IR) or insulin-like growth factor receptor (IGF1R) and compared with the control model. The mathematical models were validated by wet lab experiments. The HR+ BC cells (MCF7) were treated with insulin or IGF1 for short term and long term. The expression patterns of NMT1, NMT2, and mTOR were determined by cell fractionation and western blot analysis. The results revealed the correlation between the differential expression patterns of NMTs and the proliferation of MCF7 cells when the insulin pathway was activated by insulin or IGF. The mathematical modeling was validated by simulations and data fittings. The results demonstrated that differential equation-based mathematical modeling could predict the NMT-related oncogenic changes in HR+ BC cells. Citation Format: Abinash Meher, Shailly Varma Shrivastav, Anouska Agarwal, Sheen Dube, Stephanie Portet, Anuraag Shrivastav. Mathematical modeling and validation of mechanistic target of rapamycin and N-myristoyltransferase signaling pathways in 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 7381.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".