Somatic CRISPR tumorigenesis and multiomic analysis reveal a pentose phosphate pathway disruption vulnerability in MPNSTs
Bibliographic record
Abstract
Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive and chemo-resistant sarcomas with poor survival rates. Loss of CDKN2A or P53 following NF1 disruption is a key event in MPNST development. Here, we used CRISPR-Cas9 somatic tumorigenesis in mice to identify transcriptomic and metabolomic features distinguishing CDKN2A - versus P53 -deleted MPNSTs. Convergent, multiomic analyses revealed that CDKN2A -deleted MPNSTs are especially dependent on the pentose phosphate pathway (PPP) and NADPH metabolism for growth and viability. Disruption of glucose-6-phosphate dehydrogenase (G6PD), the PPP rate-limiting enzyme, slowed CDKN2A -deleted MPNST growth and sensitized MPNSTs to standard-of-care chemotherapy. Knockdown of the redox-regulated transcription factor NRF2 slowed MPNST growth and decreased G6PD transcription. Analysis of patient MPNSTs identified a NRF2 gene signature correlating with tumor transformation. Furthermore, G6PD and NRF2 expression in PanCancer TCGA samples correlates with patient survival. This work identifies NRF2-PPP dependency as a targetable vulnerability in these difficult-to-treat MPNSTs, particularly in the NF1/CDKN2A -deleted majority.
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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) | 0.001 | 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 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".