Nocodazole-induced p53-dependent c-Jun N-terminal Kinase Activation Reduces Apoptosis in Human Colon Carcinoma HCT116 Cells
Bibliographic record
Abstract
Microtubule-interfering agents are widely used in cancer chemotherapy, and prognostic results vary significantly from tumor to tumor, depending on the p53 status. In preliminary experiments, we compared the expression and phosphorylation profiles of more than 100 protein kinases and protein phosphatases in human colorectal carcinoma cell line HCT116 between p53+/+ and p53-/- cells in response to short term nocodazole treatment through application of Kinetworks immunoblotting screens. Among the proteins tracked, the regulation of the phosphorylation of c-Jun N-terminal kinase (JNK)1/2 at Thr-183/Tyr-185 was the major difference between p53+/+ and p53-/- cells. With the loss of the p53 gene, the levels of phosphorylation of Ser-63 of c-Jun and Thr-183/Tyr-185 of JNK1/2 in p53-/- cells did not increase as markedly as in p53+/+ cells in response to a 1-h treatment with nocodazole or other microtubule-disrupting drugs such as vinblastine and colchicine. Similar observations were also made in MCF-7 and A549 tumor cells, which were rendered p53-deficient by E6 oncoprotein expression. However, arsenate-induced JNK activation in p53-/- cells was preserved. Inhibition of p53 expression by its antisense oligonucleotide also attenuated nocodazole-induced JNK activation in p53+/+ cells. Surprisingly, cotransfection of p53+/+ cells with dominant negative mutants of JNK isoforms and treatment of p53+/+ cells with the JNK inhibitor SP600125 actually further enhanced apoptosis in p53+/+ cells by up to 2-fold in response to nocodazole. These findings indicate that inhibition of p53-mediated JNK1/2 activity in certain tumor cells could serve to enhance the apoptosis-inducing actions of cancer chemotherapeutic agents that disrupt mitotic spindle function.
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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) | 0.000 | 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 | 0.001 |
| 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".