The Effect of Aflatoxin B1 on Tumor-Related Genes and Phenotypic Characters of MCF7 and MCF10A Cells
Bibliographic record
Abstract
The fungal toxin aflatoxin B1 (AB1) and its reactive intermediate, aflatoxin B1-8, 9 epoxide, could cause liver cancer by inducing DNA adducts. AB1 exposure can induce changes in the expression of several cancer-related genes. In this study, the effect of AB1 exposure on breast cancer MCF7 and normal breast MCF10A cell lines at the phenotypic and epigenetic levels was investigated to evaluate its potential in increasing the risk of breast cancer development. We hypothesized that, even at low concentrations, AB1 can cause changes in the expression of important genes involved in four pathways, i.e., p53, cancer, cell cycle, and apoptosis. The transcriptomic levels of BRCA1, BRCA2, p53, HER1, HER2, cMyc, BCL2, MCL1, CCND1, WNT3A, MAPK1, MAPK3, DAPK1, Casp8, and Casp9 were determined in MCF7 and MCF10A cells. Our results illustrate that treating both cells with AB1 induced cytotoxicity and apoptosis with reduction in cell viability in a concentration-dependent manner. Additionally, AB1 reduced reactive oxygen species levels. Phenotypically, AB1 caused cell-cycle arrest at G1, hypertrophy, and increased cell migration rates. There were changes in the expression levels of several tumor-related genes, which are known to contribute to activating cancer pathways. The effects of AB1 on the phenotype and epigenetics of both MCF7 and MCF10A cells associated with cancer development observed in this study suggest that AB1 is a potential risk factor for developing breast cancer.
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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".