The Novel Roles of MAP Kinase-Interacting Serine/Threonine- Protein Kinase 1 (MNK1) in Melanoma Progression
Bibliographic record
Abstract
In cutaneous melanoma, two of the signaling pathways that are most frequently dysregulated are the MAPK and PI3K-AKT pathways.The most common mutation in cutaneous melanoma is BRAF V600E , which results in 500-fold activation of the MAPK pathway.Studying how the MAPK and PI3K pathways converge and cross-talk can lead us to further understand melanoma progression and develop novel therapeutics.Downstream of the MAPK pathway we find the mitogen-activated protein kinase (MAPK) interacting protein kinases (MNK1/2).MNK1/2 has many roles, but arguably its best studied role is its ability to phosphorylate the eukaryotic translation initiation factor 4E (eIF4E) at serine 209.The phosphorylation of eIF4E on serine 209 leads to the selective translation of pro-tumourigenic and pro-invasive mRNAs, and is thus essential for tumourigenesis and cancer progression.MNK1/2 is known to shuttle into and out of the nucleus, however little is described about the nuclear functions of MNK1.The impact of MNK1 on the regulation of gene transcription, for example, remains unknown.In our research we showed that cells expressing a constitutively active form of MNK1 resulted in an increase in the expression of mRNAs that code for proteins responsible for invasion, tumourigenesis, and proliferation.Conversely, cells devoid of MNK1, generated using CRISPR/Cas9, showed less expression of these same MNK1-regulated target genes.One of the most upregulated genes in cells expressing the constitutively active MNK1, was angiopoetin-like 4 (ANGPTL4).Cells that were devoid of MNK1 expressed less ANGPTL4 than their wild-type counterparts.Overexpression of ANGPTL4 in melanoma cells leads to a more invasive phenotype via the upregulation of matrix metalloproteinases (MMPs).Melanoma cell invasion and MMP9 levels, and activity, were decreased with the knockdown of ANGPTL4.In vivo studies using syngeneic mouse models of melanoma, showed that cells devoid of MNK1 resulted in smaller tumors and a decrease in lung
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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) | 0.001 | 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 | 0.001 |
| 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".