Imagine high-risk neuroblastoma as a treacherous maze, with tumor cells hiding around every corner. Scientists embarked on a mission to find a guide through this maze by identifying specific genes that can predict prognosis in high-risk neuroblastoma (HRNB) patients. They collected extensive multi-omics datasets, including gene expression and DNA methylation data, from HRNB patients and used sophisticated analytics to uncover a signature of six malignant cell marker genes. These genes, MAPT, C1QTNF4, MEG3, NPW, RAMP1, and CDT1, were found to be crucial in predicting patient survival. In fact, they could divide patients into ultra-high-risk and common-high-risk groups, with the ultra-high-risk group having significantly worse overall survival. The researchers then validated their findings in an independent dataset, further confirming the reliability of their prognostic model. Additionally, they discovered that the dysregulation of metabolic processes and an immunosuppressive microenvironment could contribute to the poor prognosis observed in the ultra-high-risk group. This groundbreaking study not only provides valuable insights into the development of personalized monitoring strategies for HRNB patients but also opens up new avenues for treatment options.

BackgroundNeuroblastoma is the most common extracranial solid tumor of childhood, arising from the sympathetic nervous system. High-risk neuroblastoma (HRNB) remains a major therapeutic challenge with low survival rates despite the intensification of therapy. This study aimed to develop a malignant-cell marker gene signature (MMGS) that might serve as a prognostic indicator in HRNB patients.MethodsMulti-omics datasets, including mRNA expression (single-cell and bulk), DNA methylation, and clinical information of HRNB patients, were used to identify prognostic malignant cell marker genes. MMGS was established by univariate Cox analysis, LASSO, and stepwise multivariable Cox regression analysis. Kaplan–Meier (KM) curve and time-dependent receiver operating characteristic curve (tROC) were used to evaluate the prognostic value and performance of MMGS, respectively. MMGS further verified its reliability and accuracy in the independent validation set. Finally, the characteristics of functional enrichment, tumor immune features, and inflammatory activity between different MMGS risk groups were also investigated.ResultsWe constructed a prognostic model consisting of six malignant cell maker genes (MAPT, C1QTNF4, MEG3, NPW, RAMP1, and CDT1), which stratified patients into ultra-high-risk (UHR) and common-high-risk (CHR) group. Patients in the UHR group had significantly worse overall survival (OS) than those in the CHR group. MMGS was verified as an independent predictor for the OS of HRNB patients. The area under the curve (AUC) values of MMGS at 1-, 3-, and 5-year were 0.78, 0.693, and 0.618, respectively. Notably, functional enrichment, tumor immune features, and inflammatory activity analyses preliminarily indicated that the poor prognosis in the UHR group might result from the dysregulation of the metabolic process and immunosuppressive microenvironment.ConclusionThis study established a novel six-malignant cell maker gene prognostic model that can be used to predict the prognosis of HRNB patients, which may provide new insight for the treatment and personalized monitoring of HRNB patients.

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