Identification and validation of a novel HOX-related classifier signature for predicting prognosis and immune microenvironment in pediatric gliomas

Background: Pediatric gliomas (PGs) are highly aggressive and predominantly occur in young children. In pediatric gliomas, abnormal expression of Homeobox (HOX) family genes (HFGs) has been observed is associated with the development progression disease. Studies have found that overexpression or underexpression certain HOX linked to occurrence prognosis gliomas. This aberrant may contribute dysregulation important pathological processes such as cell proliferation, differentiation, metastasis. study aimed propose a novel HOX-related signature predict patients’ immune infiltrate characteristics PGs. Methods: The data PGs obtained from publicly available databases were utilized reveal relationship among (HFGs), prognosis, tumor infiltration, clinical features, genomic features HFGs identify heterogeneous subtypes using consensus clustering. Then random forest-supervised classification algorithm nearest shrunken centroid performed develop prognostic training set. Finally, was validated an internal testing set external independent cohort. Results: Firstly, we identified significantly differentially expressed compared normal tissues. individuals then divided into two (HOX-SI HOX-SII) based on profiles. HOX-SII showed higher total mutation counts, lower worse than HOX-SI. Then, constructed gene (including HOXA6 , HOXC4 HOXC5 HOXC6 HOXA-AS3 ) cluster for subtype prediction utilizing forest supervised algorithm. revealed be factor patients by multivariable Cox regression analysis. Conclusion: Our provides method findings also suggest new biomarker diagnosis PGs, allowing more accurate survival prediction.