Claudin 1 Expression Levels Affect miRNA Dynamics in Human Basal-Like Breast Cancer Cells
Bibliographic record
Abstract
Deemed a putative tumor suppressor in breast cancer, the tight junction protein claudin 1 has now been shown to be highly expressed in the basal-like molecular subtype. Moreover, recent in vitro studies show that claudin 1 can regulate breast cancer cell motility and proliferation. Herein, we investigated whether microRNA (miRNA) dysregulation is associated with alterations in the level of claudin 1. Using next-generation sequencing (NGS), we identified seven miRNAs (miR-9-5p, miR-9-3p, let-7c, miR-127-3p, miR-99a-5p, miR-129-5p, and miR-146a-5p) that were deregulated as a consequence of claudin 1 overexpression in the MDA-MB231 human breast cancer (HBC) cell line. Most of these miRNAs have been associated with tumor suppression in a variety of cancers, including breast cancer. Moreover, through gene expression profiling analysis, we identified epithelial-mesenchymal transition-related genes, including platelet-derived growth factor receptor-beta (PDGFRB) and cadherin 1 (CDH1, E cadherin), whose downregulation correlated with claudin 1 overexpression. Collectively, we show for the first time that in HBC, claudin 1 can alter the dynamics of a number of miRNAs involved in tumor progression. Our data suggest that the dysregulated expression of these miRNAs, in conjunction with the high claudin 1 levels, could serve as a useful biomarker that identifies a subset of tumors within the poorly characterized basal-like subtype of breast cancer. Further studies are warranted to determine the role of these miRNAs in facilitating the function of claudin 1 in 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".