MYC Rules: Leading Glutamine Metabolism toward a Distinct Cancer Cell Phenotype
Bibliographic record
Abstract
Metabolic reprogramming and deregulated cellular energetics are hallmarks of cancer. The aberrant metabolism of cancer cells is thought to be the product of differential oncogene activation and tumor suppressor gene inactivation. MYC is one of the most important oncogenic drivers, its activation being reported in a variety of cancer types and sub-types, among which are the most prevalent and aggressive of all malignancies. This review aims to offer a comprehensive overview and highlight the importance of the c-Myc transcription factor on the regulation of metabolic pathways, in particular that of glutamine and glutaminolysis. Glutamine can be extensively metabolized into a variety of substrates and be integrated in a complex metabolic network inside the cell, from energy metabolism to nucleotide and non-essential amino acid synthesis. Together, understanding metabolic reprogramming and its underlying genetic makeup, such as MYC activation, allows for a better understanding of the cancer cell phenotype and thus of the potential vulnerabilities of cancers from a metabolic standpoint.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".