p75 neurotrophin receptor-mediated metabolic regulation in glioblastoma cells
Bibliographic record
Abstract
The most common and deadly primary brain cancer, glioblastoma (GBM), spreads easily throughout the brain and is resistant to standard treatments. Interaction between the cellular protein, p75 neurotrophin receptor (p75NTR), and its binding partner, PDLIM1, plays an important role in mediating cell motility. Preliminary data showed that p75NTR expression in invasive tumor cells accompanies a shift in cellular metabolism from glucose consumption (glycolysis) to glutamine (glutaminolysis). This study investigated the role of the p75NTR-PDLIM1 signaling axis in cellular metabolism and therapeutic resistance. Human U87 GBM cells that expressed p75NTR (i.e. invasive), or expressed p75NTR proteins that were crippled for their ability to bind PDLIM1 were cultured under glucose- or glutamine-deficient conditions and assessed for their effects on cell survival and metabolic activity. Pharmacologically available metabolic inhibitors (BPTES, a glutaminolysis inhibitor, and DCA, a glycolysis inhibitor) were also assessed for their effects in these cell lines. Both types of p75NTR-mutant cell lines showed decreased mitochondrial activity in glucose-deficient conditions, compared to invasive cells, which showed decreased mitochondrial activity in glutamine-deficient conditions. Furthermore, p75NTR-mutant cell lines showed decreased mitochondrial activity when treated with DCA, whereas invasive cells showed decreased mitochondrial activity when treated with BPTES. These data suggest that p75NTR-PDLIM1 signaling axis is involved in switching cellular metabolism from glycolysis to glutaminolysis in invasive U87 cells. Future treatments that target this metabolic shift may improve outcomes for patients. Further research is needed to investigate the impact of nutrient-starvation and treatment conditions on cell viability and in patient-derived brain tumor initiating cells. * Indicates faculty mentor
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".