The enzyme L-isoaspartyl (D-aspartyl) methyltransferase promotes migration and invasion in human U-87 MG and U-251 MG glioblastoma cell lines
Bibliographic record
Abstract
The protein L-isoaspartyl (D-aspartyl) methyltransferase (PIMT) recognizes abnormal L-isoaspartyl and D-aspartyl residues in proteins. Among examined tissues, PIMT shows the highest level in the brain. The U-87 MG cell line is a commonly used cellular model to study the most frequent brain tumor, glioblastoma. Previously, we reported that PIMT amount increased when U-87 MG cells were detached from the extracellular matrix. Recently, we also showed that PIMT possessed pro-angiogenic properties. Together, these PIMT features led us to postulate that PIMT could play a critical role in glioblastoma growth. Here, we investigate PIMT role in U-87 MG cell viability, adhesion, migration, invasion, and colony formation and in the reorganization of the actin and tubulin cytoskeleton. PIMT inhibition by siRNA significantly reduced in vitro cell migration and invasion in various assays, including wound-healing assay, Boyden chambers coated with gelatin and Matrigel invasion assay. Conversely, in stably transfected U-87 MG cells overexpressing wild-type PIMT, cell migration, invasive capacity and colony formation significantly increased. However, in stably transfected cells with the gene encoding for mutated PIMT(D83V), despite of its overexpression, migration and invasion remained similar to those observed in control cells. In all these conditions, cell viability was unaffected. Importantly, overexpressed wild-type PIMT and mutated PIMT(D83V) have opposite effects on the organization of microtubules and actin cytoskeleton and thus on morphology of U-87 cells. These data highlighted the importance of PIMT level and its catalytic activity in migration and invasion of U-87 glioma cells and its possible contribution in cancer invasion during glioma growth.
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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".