CSIG-02. SHH PATHWAY ACTIVATION DRIVES NEURAL CREST CELL SIGNATURE IN A SUBGROUP OF MPNSTS
Bibliographic record
Abstract
Abstract INTRODUCTION Neurofibromatosis Type 1 is hereditary tumor predisposition syndrome that results in the development of innumerable nerve sheath tumors that fall within the spectrum of benign, premalignant and malignant lesions. Our previous work has demonstrated that SHH pathway activation drives malignant transformation in a subset of malignant peripheral nerve sheath tumors (MPNSTs). Here, we demonstrate that SHH pathway activation induces a neural crest cell-like state in a subset of MPNSTs. METHODS We performed single nuclear RNA sequencing on 6 tumors (5 MPNSTS and 1 atypical neurofibroma). We performed in vitro experiments to assess the correlation between SHH pathway activation and neural crest signatures. We inhibited SHH pathway with sonidegib, a SMO inhibitor, in MPNST cell lines and performed RT-PCR to assess markers of neural crest cell signatures. In addition, we assessed cellular viability with treatment. RESULTS We observed that cells that express SMO at high levels, with SHH pathway activation, express neural crest cell makers. Single cell trajectory analysis further demonstrates a pseudotemporal continuum from atypical neurofibromas (Schwann cells), MPNSTs (Schwann cell precursor cells) and other MPNSTs (neural crest cells), which supports that these tumors fall along the developmental trajectory of neural crest cell lineage. SHH pathway activity was high in S462TY MPNST cell line and low in STS-26T MPNST cell line. S462TY also demonstrated prominent elevation in expression of neural crest cell markers TWIST1, SOX9, SNAI2, OTX2, PAX4 and PAX6 . We found that treatment with sonidegib treatment attenuates the expression of neural crest cell signatures. Finally, inhibiting SHH pathway activation reduced cellular viability in MPNST cell lines. CONCLUSION SHH pathway activation drives dedifferentiation into a neural crest cell-like state in a subset of MPNSTs. We confirm that inhibiting SHH pathway activity in a subset of MPNSTS prevent growth and malignant progression, providing a rational for future clinical trials.
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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) | 0.002 | 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".