阐明ecDNA在儿童髓母细胞瘤治疗耐药和免疫逃逸中的作用

PurposeExtrachromosomal DNA (ecDNA) has been identified as a key driver of cancer evolution and poor clinical prognosis, with emerging research describing its utility for risk stratification. Coupled with current investigations in immunotherapy-based strategies for pediatric medulloblastoma (MBL), we conducted a data-driven pathway analysis to elicit the mechanisms by which ecDNA oncogenes might be implicated in disease pathogenesis. These insights could inform robust molecular subtyping for improved understanding and outcomes in MBL. IntroductionThere are four major molecular subtypes of MBL: WNT, G4, SHH, and G3, in order of best to worst prognosis. While greater ecDNA counts have been reported to be associated with worse outcomes, we qualitatively evaluated the pathways involved, with a focus on immune evasion and drug resistance. Within the Childhood Cancer Data Initiative (CCDI) database, oncogenes amplified on ecDNA are denoted as either canonical or non-canonical, with the former referring to established drivers of malignant transformation through dysregulated pathways in apoptosis, cell proliferation, etc. Compared to these well-established direct drivers of oncogenesis, we hypothesized that “non-canonical” oncogenes may serve as an undertapped source of pharmacological insights. MethodsPatient cohorts were generated using the CCDI database by filtering MBL subclasses for cases with both available survival data and ecDNA presence: SHH (n=33 patients; 787 unique genes on ecDNA); G3 (n=19; 161); G4 (n=25; 291); WNT (n=0; 0). Genes identified in more than three patients per subtype were selected for our pathway analysis. ResultsWhile ecDNA genes were often related to cell cycle dynamics and adhesion proteins, a primarily non-canonical subset is involved in immune dysregulation through various mechanisms. For SHH patients, GLI2 (n=6 patients) upregulates Wnt signaling, reducing natural killer (NK) and CD8+ T cell activity. In G3 patients, both RAD21 and UTP23 (n=3) are implicated in immune evasion, the former by inhibiting interferon signaling and CD8+ T cell function and the latter through reduced dendritic cell activity. In the G4 subclass, NBAS (n=5) is associated with reduced NK cell function and immunodeficiency disorders, while high CDK6 (n=4) is correlated with T cell suppression. Meanwhile, FZD1 (n=4) promotes Wnt signaling-based chemoresistance, and FAM49A (n=3) is a negative regulator of T cell activation. Although these genes have been previously shown to confer worse prognosis across other cancer types, their role in mediating MBL outcomes has not been established. ConclusionThere are no approved immunotherapeutic strategies for pediatric MBL, despite evidence of immunomodulatory mechanisms. Our preliminary computational results provide guidance to developing ecDNA screenings that could inform personalized therapies and redefine the standard of care.