Modulating PKCα Activity to Target Wnt/β-Catenin Signaling in Colon Cancer
Bibliographic record
Abstract
Inactivating mutations of the tumor suppressor Adenomatosis Polyposis Coli (APC), which are found in familial adenomatosis polyposis and in 80% of sporadic colorectal cancers (CRC), result in constitutive activation of the Wnt/β-catenin pathway and tumor development in the intestine. These mutations disconnect the Wnt/β-catenin pathway from its Wnt extracellular signal by inactivating the APC/GSK3-β/axin destruction complex of β-catenin. This results in sustained nuclear accumulation of β-catenin, followed by β-catenin-dependent co-transcriptional activation of Wnt/β-catenin target genes. Thus, mechanisms acting downstream of APC, such as those controlling β-catenin stability and/or co-transcriptional activity, are attractive targets for CRC treatment. Protein Kinase C-α (PKCα) phosphorylates the orphan receptor RORα that then inhibits β-catenin co-transcriptional activity. PKCα also phosphorylates β-catenin, leading to its degradation by the proteasome. Here, using both in vitro (DLD-1 cells) and in vivo (C57BL/6J mice) PKCα knock-in models, we investigated whether enhancing PKCα function could be beneficial in CRC treatment. We found that PKCα is infrequently mutated in CRC samples, and that inducing PKCα function is not deleterious for the normal intestinal epithelium. Conversely, di-terpene ester-induced PKCα activity triggers CRC cell death. Together, these data indicate that PKCα is a relevant drug target for CRC treatment.
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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) | 0.000 | 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) | 0.000 | 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".