Microarray-based copy number analysis of neurofibromatosis type-1 (NF1)-associated malignant peripheral nerve sheath tumors reveals a role for Rho-GTPase pathway genes in NF1 tumorigenesis
Bibliographic record
Abstract
Neurofibromatosis type-1 (NF1) is associated with the growth of benign and malignant tumors. Approximately 15% of NF1 patients develop malignant peripheral nerve sheath tumors (MPNSTs), underlining the need to identify specific diagnostic/prognostic biomarkers associated with MPNST development. The Affymetrix Genome-Wide Human single-nucleotide polymorphism (SNP) Array 6.0 was used to perform SNP genotyping and copy number alteration (CNA), loss-of-heterozygosity (LOH), and copy number neutral-LOH (CNN-LOH) analyses of DNA isolated from 15 MPNSTs, five benign plexiform neurofibromas (PNFs), and patient-matched lymphocyte DNAs. MPNSTs exhibited high-level CNN-LOH, with recurrent changes occurring in MPNSTs but not PNFs. CNN-LOH was evident in MPNSTs but occurred less frequently than genomic deletions. CNAs involving the ITGB8, PDGFA, Ras-related C3 botulinum toxin substrate 1 (RAC1) (7p21-p22), PDGFRL (8p22-p21.3), and matrix metallopeptidase 12 (MMP12) (11q22.3) genes were specific to MPNSTs. Pathway analysis revealed the MPNST-specific amplification of seven Rho-GTPase pathway genes and several cytoskeletal remodeling/cell adhesion genes. In knockdown experiments employing short-hairpin RAC1, ROCK2, PTK2, and LIMK1 RNAs to transfect both control and MPNST-derived cell lines, cell adhesion was significantly increased in the MPNST cell lines, whereas wound healing, cell migration, and invasiveness were reduced, consistent with a role for these Rho-GTPase pathway genes in MPNST development and metastasis. These results suggest new targets for therapeutic intervention in relation to MPNSTs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".