HDAC8 Activates AKT through Upregulating PLCB1 and Suppressing DESC1 Expression in MEK1/2 Inhibition-Resistant Cells
Bibliographic record
Abstract
Inhibition of the RAF-MEK1/2-ERK signaling pathway is an ideal strategy for treating cancers with NRAS or BRAF mutations. However, the development of resistance due to incomplete inhibition of the pathway and activation of compensatory cell proliferation pathways is a major impediment of the targeted therapy. The anthrax lethal toxin (LT), which cleaves and inactivates MEKs, is a modifiable biomolecule that can be delivered selectively to tumor cells and potently kills various tumor cells. However, resistance to LT and the mechanism involved are yet to be explored. Here, we show that LT, through inhibiting MEK1/2-ERK activation, inhibits the proliferation of cancer cells with NRAS/BRAF mutations. Among them, the human colorectal tumor HT-29 and murine melanoma B16-BL6 cells developed resistance to LT in 2 to 3 days of treatment. These resistant cells activated AKT through a histone deacetylase (HDAC) 8-dependent pathway. Using an Affymetrix microarray, followed by qPCR validation, we identified that the differential expression of the phospholipase C-β1 (PLCB1) and squamous cell carcinoma-1 (DESC1) played an important role in HDAC8-mediated AKT activation and resistance to MEK1/2-ERK inhibition. By using inhibitors, small interference RNAs and/or expression vectors, we found that the inhibition of HDAC8 suppressed PLCB1 expression and induced DESC1 expression in the resistant cells, which led to the inhibition of AKT and re-sensitization to LT and MEK1/2 inhibition. These results suggest that targeting PLCB1 and DESC1 is a novel strategy for inhibiting the resistance to MEK1/2 inhibition.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".