背景：儿童胶质瘤（PG）具有高度侵袭性，主要发生在幼儿身上。在儿童胶质瘤中，已观察到Homeobox（HOX）家族基因（HFGs）的异常表达，并与疾病的发展和进展有关。研究发现，某些HOX基因的过度表达或欠表达与胶质瘤的发生和预后有关。这种异常表达可能导致细胞增殖、分化和转移等重要病理过程的失调。本研究旨在提出一种新的与HOX相关的标志物，用于预测PG患者的预后和免疫浸润特征。 方法：利用公开数据库中获得的PGs数据揭示了HFGs的异常表达与PGs预后、肿瘤免疫浸润、临床特征和基因组特征之间的关系。使用共识聚类分析方法，利用HFGs鉴定出异质亚型。然后使用随机森林监督分类算法和最近收缩质心算法在训练集中开发了一个预后标志物。最后，在内部测试集和外部独立队列中验证了该标志物。 结果：首先，我们确定了PGs与正常组织比较时显著差异表达的HFGs。然后，使用HFGs表达谱将PGs患者分为两个异质亚型（HOX-SI和HOX-SII）。与HOX-SI相比，HOX-SII显示出更高的突变总数、较低的免疫浸润水平和较差的预后。然后，根据聚类构建了一个与HOX相关的基因标志物（包括HOXA6，HOXC4，HOXC5，HOXC6和HOXA-AS3），利用随机森林监督分类和最近收缩质心算法进行亚型预测。通过多变量Cox回归分析，该标志物被证实是PGs患者的独立预后因子。 结论：我们的研究提供了一种PGs的预后分类的新方法。研究结果还提示，与HOX相关的标志物是PGs患者诊断和预后的新生物标志物，可更准确地预测生存率。版权所有 © 2023 Zhang, Zhang, Su, Zhang, Liu, Han, Liu and Sun.

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 and is associated with the development and progression of the disease. Studies have found that overexpression or underexpression of certain HOX genes is linked to the occurrence and prognosis of gliomas. This aberrant expression may contribute to the dysregulation of important pathological processes such as cell proliferation, differentiation, and metastasis. This study aimed to propose a novel HOX-related signature to predict patients' prognosis and immune infiltrate characteristics in PGs. Methods: The data of PGs obtained from publicly available databases were utilized to reveal the relationship among abnormal expression of HOX family genes (HFGs), prognosis, tumor immune infiltration, clinical features, and genomic features in PGs. The HFGs were utilized to identify heterogeneous subtypes using consensus clustering. Then random forest-supervised classification algorithm and nearest shrunken centroid algorithm were performed to develop a prognostic signature in the training set. Finally, the signature was validated in an internal testing set and an external independent cohort. Results: Firstly, we identified HFGs significantly differentially expressed in PGs compared to normal tissues. The individuals with PGs were then divided into two heterogeneous subtypes (HOX-SI and HOX-SII) based on HFGs expression profiles. HOX-SII showed higher total mutation counts, lower immune infiltration, and worse prognosis than HOX-SI. Then, we constructed a HOX-related gene signature (including HOXA6, HOXC4, HOXC5, HOXC6, and HOXA-AS3) based on the cluster for subtype prediction utilizing random forest supervised classification and nearest shrunken centroid algorithm. The signature was revealed to be an independent prognostic factor for patients with PGs by multivariable Cox regression analysis. Conclusion: Our study provides a novel method for the prognosis classification of PGs. The findings also suggest that the HOX-related signature is a new biomarker for the diagnosis and prognosis of patients with PGs, allowing for more accurate survival prediction.Copyright © 2023 Zhang, Zhang, Su, Zhang, Liu, Han, Liu and Sun.