Involvement of KCNQ1 K+ channels in cell volume regulation in human mammary epithelial cells
Bibliographic record
Abstract
Transepithelial ion transport across mammary epithelial cells underlies milk secretion and breast cyst formation. However, little is known about the molecular nature of the K+ channels involved. We have investigated the location and functionality of the KCNQ1 K+ channel in the mammary epithelial cell line MCF‐7. Using RT‐PCR, we determined that KCNQ1, as well as its accessory subunits KCNE1‐3, were present in MCF‐7 cells. KCNQ1 protein expression was confirmed by Western blotting and immunolocalization with confocal microscopy. When cells were cultured as a polarized monolayer, KCNQ1 was located in the apical membrane. We next investigated the potential role this channel may play in the regulatory volume decrease (RVD) of these cells. Switching from an isotonic to a hypotonic solution resulted in an initial cell swelling, followed by an RVD response. This could be inhibited by the KCNQ1 inhibitors chromonol 293B and XE991, and also when a dominant‐negative N‐terminus truncated KCNQ1 isoform was transfected into MCF‐7 cells. Since MCF‐7 cells are also known to express hIK (KCNN4) and BK (KCNMA1) channels, implicated in the RVD response in other cell types, we additionally investigated the ability of MCF‐7 cells to RVD in the presence of clotrimazole and charybdotoxin. Neither agent inhibited the RVD in these cells. Finally, whole cell recordings from baby hamster kidney cells expressing KCNQ1 and the accessory subunit KCNE3 revealed a volume‐sensitive K+ current, which was inhibited by 293B. These data suggest that KCNQ1 may play important physiological roles in the mammary epithelium, potentially mediating apical K+ secretion and well as being critically involved in the regulation of cell volume. Supported by the Canadian Breast Cancer Foundation, Atlantic Chapter.
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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".