Noncanonical protein kinase A activation by oligomerization of regulatory subunits as revealed by inherited Carney complex mutations
Bibliographic record
Abstract
Familial mutations of the protein kinase A (PKA) R1α regulatory subunit lead to a generalized predisposition for a wide range of tumors, from pituitary adenomas to pancreatic and liver cancers, commonly referred to as Carney complex (CNC). CNC mutations are known to cause overactivation of PKA, but the molecular mechanisms underlying such kinase overactivity are not fully understood in the context of the canonical cAMP-dependent activation of PKA. Here, we show that oligomerization-induced sequestration of R1α from the catalytic subunit of PKA (C) is a viable mechanism of PKA activation that can explain the CNC phenotype. Our investigations focus on comparative analyses at the level of structure, unfolding, aggregation, and kinase inhibition profiles of wild-type (wt) PKA R1α, the A211D and G287W CNC mutants, as well as the cognate acrodysostosis type 1 (ACRDYS1) mutations A211T and G287E. The latter exhibit a phenotype opposite to CNC with suboptimal PKA activation compared with wt. Overall, our results show that CNC mutations not only perturb the classical cAMP-dependent allosteric activation pathway of PKA, but also amplify significantly more than the cognate ACRDYS1 mutations nonclassical and previously unappreciated activation pathways, such as oligomerization-induced losses of the PKA R1α inhibitory function.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".