Ependymomas (EPN) are rare central nervous system tumors that account for approximately 10% of intracranial tumors in children and 4% in adults. Despite their clinical and molecular heterogeneity, spanning supratentorial, posterior fossa, and spinal subtypes, treatment remains limited to surgery and radiotherapy, with chemotherapy offering minimal benefit. Here, we performed transcriptomic analysis of 370 human ependymoma samples and identified two distinct molecular subgroups: EPN-E1 and EPN-E2. The EPN-E1 cluster is enriched for supratentorial tumors harboring ZFTA-RELA fusions (ZFTA-RELA(fus)), which occur in over 70% of cases and are associated with poor prognosis. To identify targeted therapies for this aggressive subtype, we validated a ZFTA-RELA(fus) mouse model that recapitulates the human EPN-E1 transcriptome and used it for target discovery. Through Kinome Regularization, a machine learning-driven polypharmacology approach, we identified MERTK as a critical regulator of tumor cell viability. Genetic depletion or pharmacologic inhibition of Mertk reduced cell growth ex vivo, and treatment with a clinical-grade MERTK inhibitor significantly suppressed tumor proliferation in vivo. Both human EPN-E1 tumors and ZFTA-RELA(fus) mouse tumors exhibited elevated expression of MERTK and its ligand GAS6, and MERTK inhibition led to suppression of pro-survival signaling pathways including MEK/ERK (Mitogen-Activated Protein Kinase Kinase/Extracellular Signal-Regulated Kinase) and PI3K/AKT (Phosphoinositide 3-Kinase/Protein Kinase B). Notably, over 80% of genes upregulated in ZFTA-RELA(fus) tumors were downregulated following MERTK inhibition, indicating a strong dependency on this pathway for tumor maintenance. These findings define a signaling vulnerability in ZFTA-RELA-driven ependymomas and support the clinical development of MERTK-targeted therapies for patients with the high-risk EPN-E1 subtype.
A systems approach identifies MERTK as a therapeutic vulnerability in ZFTA-RELA-driven ependymomas.
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作者:Chan Marina, Zhu Songli, Russell Zachary R, Arora Sonali, Arakaki Aleena K S, Vaz Joel M, Kumasaka Deby, Szulzewsky Frank, Michealraj Antony, Holland Eric C, Gujral Taranjit S
| 期刊: | Proceedings of the National Academy of Sciences of the United States of America | 影响因子: | 9.100 |
| 时间: | 2026 | 起止号: | 2026 Feb 17; 123(7):e2514518123 |
| doi: | 10.1073/pnas.2514518123 | ||
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