Activating Transcription Factor 3 regulates in part the enhanced tumour cell cytotoxicity of the histone deacetylase inhibitor M344 and cisplatin in combination
Bibliographic record
Abstract
BACKGROUND: Activating Transcription Factor (ATF) 3 is a key regulator of the cellular integrated stress response whose expression has also been correlated with pro-apoptotic activities in tumour cell models. Combination treatments with chemotherapeutic drugs, such as cisplatin, and histone deacetylase (HDAC) inhibitors have been demonstrated to enhance tumour cell cytotoxicity. We recently demonstrated a role for ATF3 in regulating cisplatin-induced apoptosis and others have shown that HDAC inhibition can also induce cellular stress. In this study, we evaluated the role of ATF3 in regulating the co-operative cytotoxicity of cisplatin in combination with an HDAC inhibitor. RESULTS: The HDAC inhibitor M344 induced ATF3 expression at the protein and mRNA level in a panel of human derived cancer cell lines as determined by Western blot and quantitative RT-PCR analyses. Combination treatment with M344 and cisplatin lead to increased induction of ATF3 compared with cisplatin alone. Utilizing the MTT cell viability assay, M344 treatments also enhanced the cytotoxic effects of cisplatin in these cancer cell lines. The mechanism of ATF3 induction by M344 was found to be independent of MAPKinase pathways and dependent on ATF4, a known regulator of ATF3 expression. ATF4 heterozygote (+/-) and knock out (-/-) mouse embryonic fibroblast (MEF) as well as chromatin immunoprecipitation (ChIP) assays were utilized in determining the mechanistic induction of ATF3 by M344. We also demonstrated that ATF3 regulates the enhanced cytotoxicity of M344 in combination with cisplatin as evidenced by attenuation of cytotoxicity in shRNAs targeting ATF3 expressing cells. CONCLUSION: This study identifies the pro-apoptotic factor, ATF3 as a novel target of M344, as well as a mediator of the co-operative effects of cisplatin and M344 induced tumour cell cytotoxicity.
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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) | 0.002 | 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".