PM-13 * IDENTIFICATION OF THERAPEUTIC TARGETS IN AN INTRACRANIAL XENOGRAFT MODEL OF PITUITARY ADENOMA
Bibliographic record
Abstract
INTRODUCTION: Pituitary adenomas (PA) are common brain tumors whose pathogenesis is not well understood. Fibroblast growth factor receptor 4 (FGFR4) is a transmembrane kinasewhich can harbor a single nucleotide polymorphism (SNP) substituting a glycine (G388) with an arginine (R388) residue. This SNP is associated with aggressive behavior in some cancer types, including PA. There are currently limited options for this PA. Furthermore, no robust in vivo PA models harboring the FGFR4 SNP exist. Therefore, the aim of our study was to establish an intracranial xenograft model of PA and use this model to identify the mTOR inhibitor, RAD001, as a novel therapy. METHODS: We generated stable cell lines to harbour the SNPs, by using mammosomatotroph cells and transfecting with either FGFR4-G388 or FGFR4-R388. We generated intracranial xenograft models by implanting these stable cell lines either in the pituitary fossa or frontal intraperanchyma of NODSCID mice. We used longitudinal MRI imaging to study imaging characteristics, tumor volumes and growth rates of these tumours. Tumors were treated with RAD001. Histological analysis was conducted ascertain the hormone profile (growth hormone and prolactin) and mTOR pathway signalling in FGFR4-G388 and FGFR4-R388 tumors in response to RAD001. RESULTS: Tumor growth was significantly slower in R388 and G388 compared to empty vector control (pc-DNA) tumors following mTOR inhibition. Histologically, we found that the FGFR4-G388 tumors express predominately prolactin, while FGFR4-R388 tumors express growth hormone, with no change in hormone profile in response to RAD001. With respect to the mTOR pathway, an upregulation was observed as demonstrated by increased p-s6 and p-4EBP1 expression which were subsequently decreased in R388 tumors following mTOR inhibition. CONCLUSION: Our study identifies increased mTOR signalling may explain differences in tumor growth and hormone production in this prolactin/growth hormone secreting PA. mTOR inhibition may be a promising treatment option for PA tumors harboring alterations the FGFR4 allele.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".