Identification of KvLQT1 K+ channels as new regulators of non-small cell lung cancer cell proliferation and migration
Bibliographic record
Abstract
K+ channels, which are overexpressed in several cancers, have been identified as regulators of cell proliferation and migration, key processes in cancer development/propagation. Their role in lung cancer has not been studied extensively; but we showed previously that KvLQT1 channels are involved in cell migration, proliferation and repair of normal lung epithelial cells. We now investigated the role of these channels in lung cancer cell lines and their expression levels in human lung adenocarcinoma (AD) tissues. First, we observed that the wound-healing rates of A549 lung adenocarcinoma cell monolayers were reduced by clofilium and chromanol or after silencing with KvLQT1-specific siRNA. Dose-dependent decrease of A549 cell growth and cell accumulation in G0/G1 phase were seen after KvLQT1 inhibition. Clofilium also affected 2D and 3D migration of A549 cells. Similarly, H460 cell growth, migration and wound healing were diminished by this drug. Because K+ channel overexpression has been encountered in some cancers, we assessed KvLQT1 expression levels in tumor tissues from patients with lung AD. KvLQT1 protein expression in tumor samples was increased by 1.5- to 7-fold, compared to paired non-neoplastic tissues, in 17 of 26 patients. In summary, our data reveal that KvLQT1 channel blockade efficiently reduces A549 and H460 cell proliferation and migration. Moreover, KvLQT1 overexpression in AD samples suggests that it could be a potential therapeutic target in lung cancer.
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 | 0.000 |
| 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".