The Importance of the Acyltransferase LYCAT on PI3K-Akt Signaling and Cancer Cell Proliferation
Bibliographic record
Abstract
Phosphoinositides (PIPs) play a key role in regulating key cellular functions. PIPs are enriched with a unique acyl profile composed of stearate and arachidonate at the sn-1 and sn-2 positions, respectively, which is governed by phospholipase As and acyltransferases. Specifically, lysocardiolipin acyltransferase (LYCAT) incorporates stearic acid onto the sn-1 position. Previous work found that LYCAT silencing selectively perturbs the levels and localization of phosphatidylinositol-4,5-bisphosphate, an important precursor for phosphatidylinositol-3,4,5- trisphosphate (PIP3). PIP3 recruits and modulates the effector Akt, which promotes and coordinates cell survival and proliferation. Thus, we hypothesized that LYCAT is important in PIP3-Akt signaling and cell proliferation. Our results show that LYCAT silencing suppresses EGF- stimulated phosphorylation of Akt and select downstream substrates. Further, we observed impaired cell proliferation. Overall, our results suggest that the acyl specificity governed by LYCAT may play a significant role in controlling cell signaling and proliferation, which may have consequences for diseases such as cancer.
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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 | 0.000 | 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 | 0.001 | 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".