Bibliographic record
Abstract
PIK3CA, the gene for the lipid kinase p110α is one of the most frequently mutated oncogenes across all types of cancer. p110α is an enzyme that catalyzes the formation of phosphatidylinositol 3, 4, 5 Triphosphate (PIP 3 ). PIP 3 recruits effector proteins which regulate growth, proliferation and motility. Due to this role as a master cell regulator, the activity of p110α is maintained in an inactive confirmation and is only activated downstream of Receptor Tyrosine Kinases (RTKs) and RAS family of GTPases. p110α is maintained in an inactive confirmation through interactions with its regulatory subunit as well as inhibitory contacts with the C‐terminus. However, oncogenic mutations in p110α breaks these inhibitory interactions and drives hyperactivity without the need for activation signals leading to uncontrolled cell growth. We provide molecular insights into the regulation of oncogenic mutants of p110α using Hydrogen‐Deuterium Exchange Mass Spectrometry (HDX‐MS). HDX‐MS reveals the dynamic changes between the natural cytosolic state and fully‐active membrane bound states of the enzyme. We find unique molecular mechanisms regulating how mutants at the c‐terminus activate lipid kinase activity (H1047R, M1043L, G1049R and N1068KLKR). Using extensive biophysical tools, biochemical assays, and MD simulations, we have tested the oncogenic potential of these mutations. Our results elucidates a unifying theory towards the regulation of PI3Kα and how oncogenic mutations drive hyperactivity. This will aid in understanding the regulation of PI3Kα and in developing isoform specific inhibitors.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".