SYST-28 FUNCTIONAL MAPPING REVEALS WIDESPREAD REMODELLING AND A NOVEL TARGETABLE PTP4A2-ROBO1 SIGNALING AXIS AT GLIOBLASTOMA RECURRENCE
Bibliographic record
Abstract
Abstract Resistance to genotoxic therapies and tumor recurrence are hallmarks of glioblastoma (GBM), an aggressive brain tumor. Here, we explore the functional drivers of post-treatment recurrent GBM. By conducting genome-wide CRISPR-Cas9 screens in patient-derived GBM models, we uncover distinct genetic dependencies in recurrent tumor cells that were absent in their patient-matched primary predecessors, accompanied by increased mutational burden and differential transcript and protein expression. These analyses map a multilayered genetic response to drive tumor recurrence, identifying protein tyrosine phosphatase 4A2 (PTP4A2) as a novel modulator of self-renewal, proliferation and tumorigenicity at GBM recurrence. Mechanistically, genetic perturbation or small molecule inhibition of PTP4A2 represses axon guidance activity through a dephosphorylation axis with roundabout guidance receptor 1 (ROBO1), exploiting a functional dependency on ROBO signaling. Roundabout guidance receptor 1 (ROBO1) protein is involved in axonal guidance during neurodevelopment and aberrant ROBO1 signaling axis is associated with higher tumorigenicity in GBM. ROBO1 was highly expressed on the surface of malignant and treatment-refractory brain tumor initiating cells (BTICs) in rGBM, brain metastasis (BM) and medulloblastoma (MB). Importantly, engineered anti-ROBO1 single-domain antibodies also mimic the effects of PTP4A2 inhibition. We therefore developed and validated second-generation CAR-T cells against ROBO1, which demonstrated upregulation of activation markers, enhanced cytokine release, markedly increased proliferation, and induction of potent and specific tumor cell death compared to untransduced cells in all the three brain cancers. These findings were further validated in vivo in rGBM, MB and BM models, where ROBO1 CAR-T cells showed significant reduction in tumor burden and increase in survival of treated mice. We conclude that functional reprogramming drives tumorigenicity and dependence on a multi-targetable PTP4A2-ROBO1 signaling axis at GBM recurrence.
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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".