Characterization of the phototoxicity, chemigenetic profile, and mutational signatures of the chemotherapeutic CX-5461 in <i>Caenorhabditis elegans</i>
Bibliographic record
Abstract
ABSTRACT New anti-cancer therapeutics require extensive in vivo characterization to identify endogenous and exogenous factors affecting efficacy, to measure toxicity and mutagenicity, and to determine genotypes resulting in therapeutic sensitivity or resistance. We used Caenorhabditis elegans as a platform with which to characterize properties of anti-cancer therapeutic agents in vivo . We generated a map of chemigenetic interactions between DNA damage response mutants and common DNA damaging agents. We used this map to investigate the properties of the new anti-cancer therapeutic CX-5461. We phenocopied the photoreactivity observed in CX-5461 clinical trials and found that CX-5461 generates reactive oxygen species when exposed to UVA radiation. We demonstrated that CX-5461 is a mutator, resulting in both large copy number variations and a high frequency of single nucleotide variations (SNVs). CX-5461-induced SNVs exhibited a distinct mutational signature. Consistent with the wide range of CX-5461-induced mutation types, we found that multiple repair pathways were needed for CX-5461 tolerance. Together, the data from C. elegans demonstrate that CX-5461 is a multimodal DNA damaging agent with strong similarity to ellipticines, a class of antineoplastic agents, and to anthracycline-based chemotherapeutics.
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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 | 0.000 |
| 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".