Preclinical <i>in vivo</i> evaluation of rapamycin in human malignant peripheral nerve sheath explant xenograft
Bibliographic record
Abstract
Neurofibromatosis type 1 (NF1) patients are prone to the development of malignant tumors, the most common being Malignant Peripheral Nerve Sheath Tumor (MPNST). NF1-MPNST patients have an overall poor survival due to systemic metastasis. Currently, the management of MPNSTs includes surgery and radiation; however, conventional chemotherapy is not very effective, underscoring the need for effective biologically-targeted therapies. Recently, the NF1 gene product, neurofibromin, was shown to negatively regulate the phosphoinositide-3-kinase (PI3K)/Protein Kinase-B (Akt)/mammalian Target Of Rapamycin (mTOR) pathway, with loss of neurofibromin expression in established human MPNST cell lines associated with high levels of mTOR activity. We developed and characterized a human NF1-MPNST explant grown subcutaneously in NOD-SCID mice, to evaluate the effect of the mTOR inhibitor rapamycin. We demonstrate that rapamycin significantly inhibited human NF1-MPNST mTOR pathway activation and explant growth in vivo at doses as low as 1.0 mg/kg/day, without systemic toxicities. While rapamycin was effective at reducing NF1-MPNST proliferation and angiogenesis, with decreased CyclinD1 and VEGF respectively, there was no increase in tumor apoptosis. Rapamycin effectively decreased activation of S6 downstream of mTOR, but there was accompanied increased Akt activation. This study demonstrates the therapeutic potential and limitations of rapamycin in NF1-associated, and likely sporadic, MPNSTs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".