EPCO-02. MOLECULAR CHARACTERIZATION OF TWO NOVEL MPNST SUBGROUPS IDENTIFIES THERAPEUTIC OPPORTUNITIES
Bibliographic record
Abstract
Abstract Malignant peripheral nerve sheath tumors (MPNSTs) are highly aggressive Schwann-cell derived sarcomas. These tumors are resistant to all current therapies, with exception to gross total surgical resection, and unresectable or metastatic tumors are considered incurable. Our understanding of the molecular alterations driving malignant transformation is limited, and to date, targeted therapies have proven ineffective. In this study, we leverage multi-platform genomic and epigenomic profiling of human MPNSTs and neurofibromas to identify targetable molecular pathways that lead to malignant transformation. Unsupervised consensus hierarchical clustering of the top 20K most variable methylated probes yielded seven stable and robust subgroups that are clinically relevant. The high-grade MPNSTs formed two distinct methylation-based clusters (MPNST-G1 and MPNST-G2). MPNST-G1 had worse prognosis compared to MPNST-G2 (0.6 years versus 1.4 years, p < 0.05). PTCH1 loss or SMO gain was prevalent in MPNST-G1 compared to MPNST-G2 (75% vs 12.5%, p < 0.05). In addition, MPNST-G1 harbored PTCH1 CpG island promoter hypermethylation in (87.5% vs 12.5%, p < 0.001). Transcriptome profiling recapitulated the two distinct MPNST subgroups. We next demonstrated that that RB1 signaling pathways are aberrant in both MPNST-G1 and MPNST-G2. However, SHH pathway activation is observed in MPNST-G1, while WNT/CCND1/ ß-catenin pathway activation is observed in MPNST-G2. Network-based drug-disease proximity analysis identified SMO inhibitors as a potential FDA approved drug as a potential targeted therapy. To determine if SHH pathway activation is sufficient for malignant transformation, we knocked out PTCH1 in immortalized neurofibroma cells lines. In 3 different cell lines with PTCH1 knockout, we observed induction of a malignant phenotype, with increased cellular proliferation and invasion. Most importantly, in-vitro and in-vivo models confirm that targeting the SHH pathway, with sonidegib, was effective in inhibiting tumor growth proving SMO inhibition to be a novel therapeutic option in these lethal cancers.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".