Activation of TRPM7 by naltriben enhances migration and invasion of glioblastoma cells
Bibliographic record
Abstract
// Raymond Wong 1, 2 , Ekaterina Turlova 1, 2 , Zhong-Ping Feng 2 , James T. Rutka 1 , Hong-Shuo Sun 1, 2, 3, 4 1 Department of Surgery, Faculty of Medicine, University of Toronto, Toronto, Canada 2 Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Canada 3 Department of Pharmacology, Faculty of Medicine, University of Toronto, Toronto, Canada 4 Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada Correspondence to: Hong-Shuo Sun, email: hss.sun@utoronto.ca Keywords: glioblastoma, U87, TRPM7, naltriben, migration Received: August 31, 2016 Accepted: December 26, 2016 Published: January 04, 2017 ABSTRACT Glioblastoma (GBM), the most common and aggressive brain tumor in the central nervous system, remains a lethal diagnosis with a median survival of < 15 months. Aberrant expression of the TRPM7 channel has been linked to GBM functions. In this study, using the human GBM cell line U87, we evaluated the TRPM7 activator naltriben on GBM viability, migration, and invasiveness. First, using the whole-cell patch-clamp technique, we showed that naltriben enhanced the endogenous TRPM7-like current in U87 cells. In addition, with Fura-2 Ca 2+ imaging, we observed robust Ca 2+ influx following naltriben application. Naltriben significantly enhanced U87 cell migration and invasion (assessed with scratch wound assays, Matrigel invasion experiments, and MMP-2 protein expression), but not viability and proliferation (evaluated with MTT assays). Using Western immunoblots, we also detected the protein levels of p-Akt/t-Akt, and p-ERK1|2/t-ERK1|2. We found that naltriben enhanced the MAPK/ERK signaling pathway, but not the PI3k/Akt pathway. Therefore, potentiated TRPM7 activity contributes to the devastating migratory and invasive characteristics of GBM.
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 | 0.001 |
| 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".