Genomic instability and histone H3 phosphorylation induction by the Ras‐mitogen activated protein kinase pathway in pancreatic cancer cells
Bibliographic record
Abstract
Activating mutations in K-Ras occur in most pancreatic cancers. We investigated whether genetic changes (K-Ras mutations) in human pancreatic cancer cell lines altered genomic instability and epigenetic events responding to Ras-mitogen activated protein kinase (MAPK) signaling by characterizing 3 human pancreatic cancer cells lines with and without activating mutations in K-Ras. Activation of the Ras-MAPK pathway results in the stimulation of the histone H3 kinase, mitogen and stress activated kinase (MSK) 1, and increased phosphorylation of histone H3 at serine 10 (H3 S10ph). MSK1 and H3 S10ph have roles in neoplastic transformation. We demonstrate that the presence of a K-Ras mutation did not correlate with elevated chromosomal aberrations or increased genomic instability. Although the levels of the epidermal growth factor receptors and MSK were similar, the Ras-MAPK pathway was differentially induced by phorbol esters (12-O tetradecanoylphorbol-13-acetate) or epidermal growth factor, with the response of this signaling pathway being cell-type specific. This response corresponded downstream at the level of chromatin where stimuli-induced elevation of H3 S10ph typically paralleled the increase in phospho-extracellular signal regulated kinase 1/2. Our results present evidence that nonclonal chromosomal aberrations and epigenetic programming responding to stimulation of the Ras-MAPK pathway may be better markers for cancer progression than the upstream mutated oncogenes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".