Claudin 1 Is Highly Upregulated by PKC in MCF7 Human Breast Cancer Cells and Correlates Positively with PKCε in Patient Biopsies
Bibliographic record
Abstract
Recent studies provide compelling evidence to suggest that the tight junction protein claudin 1, aberrantly expressed in several cancer types, plays an important role in cancer progression. Dysregulation of claudin 1 has been shown to induce epithelial mesenchymal transition (EMT). Furthermore, activation of the ERK signaling pathway by protein kinase C (PKC) was shown to be necessary for EMT induction. Whether PKC is involved in regulating breast cancer progression has not been addressed. The PKC activator 12-O-tetradecanoylphorbol 13-acetate (TPA) was used to investigate the effect of PKC activity on claudin 1 transcription and protein levels, subcellular distribution, and alterations in EMT markers in human breast cancer (HBC) cell lines. As well, tissue microarray analysis (TMA) of a large cohort of invasive HBC biopsies was conducted to investigate correlations between claudin 1 and PKC isomers. TPA upregulated claudin 1 levels in all HBC cell lines analyzed. In particular, a high induction of claudin 1 protein was observed in the MCF7 cell line. TPA treatment also led to an accumulation of claudin 1 in the cytoplasm. Additionally, we demonstrated that the upregulation of claudin 1 was through the ERK signaling pathway. In patient biopsies, we identified a significant positive correlation between claudin 1, PKCα, and PKCε in ER+ tumors. A similar correlation between claudin 1 and PKCε was identified in ER- tumors, and high PKCε was associated with shorter disease-free survival. Collectively, these studies demonstrate that claudin 1 and the ERK signaling pathway are important players in HBC progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".