Allyl isothiocyanate regulates lysine acetylation and methylation marks in an experimental model of malignant melanoma
Bibliographic record
Abstract
OBJECTIVE(S): Isothiocyanates (ITCs) are biologically active plant secondary metabolites capable of mediating various biological effects including modulation of the epigenome. Our aim was to characterize the effect of allyl isothiocyanate (AITC) on lysine acetylation and methylation marks as a potential epigenetic-induced anti-melanoma strategy. METHODS: Our malignant melanoma model consisted of (1) human (A375) and murine (B16-F10) malignant melanoma as well as of human; (2) brain (VMM1) and lymph node (Hs 294T) metastatic melanoma; (3) non-melanoma epidermoid carcinoma (A431) and (4) immortalized keratinocyte (HaCaT) cells subjected to AITC. Cell viability, histone deacetylases (HDACs) and acetyltransferases (HATs) activities were evaluated by the Alamar blue, Epigenase HDAC Activity/Inhibition and EpiQuik HAT Activity/Inhibition assay kits, respectively, while their expression levels together with those of lysine acetylation and methylation marks by western immunoblotting. Finally, apoptotic gene expression was assessed by an RT-PCR-based gene expression profiling methodology. RESULTS: AITC reduces cell viability, decreases HDACs and HATs activities and causes changes in protein expression levels of various HDACs, HATs, and histone methyl transferases (HMTs) all of which have a profound effect on specific lysine acetylation and methylation marks. Moreover, AITC regulates the expression of a number of genes participating in various apoptotic cascades thus indicating its involvement in apoptotic induction. CONCLUSIONS: AITC exerts a potent epigenetic effect suggesting its potential involvement as a promising epigenetic-induced bioactive for the treatment of malignant melanoma.
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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 | 0.000 | 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".