DEPTOR Tyrosine Phosphorylation: A Novel Molecular Switch Involved in mTOR Activity
Bibliographic record
Abstract
Dysregulated mTOR (mechanistic Target Of Rapamycin) is a potent tumor growth inducer known to promote cancer cell proliferation and survival. Its activity can be regulated by numerous factors composing the PTEN/PI3K/AKT canonical pathway, which are often mutated in cancer. However, in a subset of cancer showing a constitutively activated mTOR, there is no alteration within the canonical activation pathway, suggesting different activation mechanism. We previously discovered several post‐translational modifications (PTMs) on DEP domain‐containing mTOR‐interacting protein (DEPTOR), an endogenous regulator of the two mTOR complexes (mTORC1 and mTORC2). Still, the mechanism by which these PTMs regulate DEPTOR ability to shut down mTOR complexes remains ill‐defined. Studies have only shown that DEPTOR is phosphorylated on serine (S286/287/291/293/299) under high energy level condition, leading to its degradation by the ubiquitin/proteasome system. Unlike this irreversible regulatory mechanism, we have recently identified another PTM, a tyrosine phosphorylation that affects DEPTOR inhibitory functions. We found that phosphorylation of DEPTOR tyrosine 289 increase its stability, while promoting DEPTOR dissociation from mTORC1&2, leading to a rapid and sustain increase in mTORC1&2 activity. To identify the upstream signaling pathway causing tyrosine 289 phosphorylation, we performed mass spectrometry analysis, as well as a small drug screening of different tyrosine kinase inhibitors. Using these combined methods, we identify Syk (Spleen tyrosine kinase), whose expression levels correlate with levels of tyrosine 289 phosphorylation. We also found that Syk‐induced phosphorylation of DEPTOR was regulated by the EphB2 receptor. Our findings uncovered a new mechanism regulating mTOR activity, which explains the increased mTOR activity in cancer with unaffected PTEN/PI3K/AKT regulatory pathways. Better understanding of this mTOR/DEPTOR regulatory pathway could allow the development of a new therapeutic approach to inhibit mTOR associated cancer progression.
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 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 | 0.000 | 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) | 0.001 | 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".