Characterization of the apoptotic response of human leukemia cells to organosulfur compounds
Bibliographic record
Abstract
BACKGROUND: Novel therapeutic agents that selectively induce tumor cell death are urgently needed in the clinical management of cancers. Such agents would constitute effective adjuvant approaches to traditional chemotherapy regimens. Organosulfur compounds (OSCs), such as diallyl disulfide, have demonstrated anti-proliferative effects on cancer cells. We have previously shown that synthesized relatives of dysoxysulfone, a natural OSC derived from the Fijian medicinal plant, Dysoxylum richi, possess tumor-specific antiproliferative effects and are thus promising lead candidates. METHODS: Because our structure-activity analyses showed that regions flanking the disulfide bond mediated specificity, we synthesized 18 novel OSCs by structural modification of the most promising dysoxysulfone derivatives. These compounds were tested for anti-proliferative and apoptotic activity in both normal and leukemic cells. RESULTS: Six OSCs exhibited tumor-specific killing, having no effect on normal bone marrow, and are thus candidates for future toxicity studies. We then employed mRNA expression profiling to characterize the mechanisms by which different OSCs induce apoptosis. Using Gene Ontology analysis we show that each OSC altered a unique set of pathways, and that these differences could be partially rationalized from a transcription factor binding site analysis. For example, five compounds altered genes with a large enrichment of p53 binding sites in their promoter regions (p < 0.0001). CONCLUSIONS: Taken together, these data establish OSCs derivatized from dysoxysulfone as a novel group of compounds for development as anti-cancer agents.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".