Role of non-mutational mechanisms in cancer cell drug resistance
Bibliographic record
Abstract
3211 Many chemotherapy regiments are used effectively to treat breast cancer; however, breast cancer cells often become resistant to the drugs, which usually leads to a relapse and worsening of prognosis. The acquisition of drug resistance is a major clinical obstacle to the successful treatment of breast cancer. The causes of cancer-specific drug resistance are currently believed to be linked to: (i) random drug-induced mutational events (genetic hypothesis), (ii) drug-induced non-mutational alterations of gene function (epigenetic hypothesis), and/or (iii) drug-induced karyotypic changes (karyotypic hypothesis). In the present study, we examined the role of non-mutational mechanisms in the development of a multidrug-resistant phenotype of MCF-7 human breast cancer cells induced by doxorubicin (DOX) and cisplatin (cisDDP), two chemotherapeutic drugs with different modes of action. Both of the drug-resistant cell lines were characterized by extensive alterations in gene-specific cytosine methylation, as indicated by the appearance of a number of differentially methylated DNA genes. A detailed analysis of hypo- and hypermethylated DNA sequences revealed that in addition to specific alterations induced by each of the drugs, the acquisition of the drug-resistant phenotype of MCF-7 cells to DOX and cisDDP was characterized by three common features: dysfunction of genes involved in estrogen metabolism (sulfatase 2 and estrogen receptor α), apoptosis (p53, p73, α-tubulin, BCL2-antagonist of cell death, tissue transglutaminase 2, and forkhead box protein K1), and cell-cell contact (leptin, stromal cell derived factor receptor 1, activin A receptor, and E-cadherin). The analysis also showed that two opposing hypo- and hypermethylation processes may enhance and complement each other in the disruption of these pathways. Another non-mutational mechanism of gene expression control is mediated via the function of small regulatory RNAs, particularly microRNAs (miRNAs). How these miRNAs might be involved in cancer cell drug resistance remains largely unexplored. MCF-7/DOX cells exhibited a considerable dysregulation of the miRNAome profile. In addition, miR-451 was found to regulate the expression of the multidrug resistance 1 (mdr1) gene. More importantly, transfection of the MCF-7/DOX resistant cells with miR-451 resulted in an increased sensitivity of cells to DOX. These results provide evidence that non-mutational mechanisms are an important feature of cancer cells with the acquired drug-resistant phenotype and may be a crucial contributing factor to its development. Furthermore, the potential reversibility of these alterations may have significant implications for novel therapeutic strategies to overcome cancer cell resistance.
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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".