Tumor Cell Kill by c-MYC Depletion: Role of MYC-Regulated Genes that Control DNA Double-Strand Break Repair
Bibliographic record
Abstract
MYC regulates a myriad of genes controlling cell proliferation, metabolism, differentiation, and apoptosis. MYC also controls the expression of DNA double-strand break (DSB) repair genes and therefore may be a potential target for anticancer therapy to sensitize cancer cells to DNA damage or prevent genetic instability. In this report, we studied whether MYC binds to DSB repair gene promoters and modulates cell survival in response to DNA-damaging agents. Chromatin immunoprecipitation studies showed that MYC associates with several DSB repair gene promoters including Rad51, Rad51B, Rad51C, XRCC2, Rad50, BRCA1, BRCA2, DNA-PKcs, XRCC4, Ku70, and DNA ligase IV. Endogenous MYC protein expression was associated with increased RAD51 and KU70 protein expression of a panel of cancer cell lines of varying histopathology. Induction of MYC in G(0)-G(1) and S-G(2)-M cells resulted in upregulation of Rad51 gene expression. MYC knockdown using small interfering RNA (siRNA) led to decreased RAD51 expression but minimal effects on homologous recombination based on a flow cytometry direct repeat green fluorescent protein assay. siRNA to MYC resulted in tumor cell kill in DU145 and H1299 cell lines in a manner independent of apoptosis. However, MYC-dependent changes in DSB repair protein expression were not sufficient to sensitize cells to mitomycin C or ionizing radiation, two agents selectively toxic to DSB repair-deficient cells. Our results suggest that anti-MYC agents may target cells to prevent genetic instability but would not lead to differential radiosensitization or chemosensitization.
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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".