AUTHOR=Wang Jiepin , Xiao Dong , Wang Junxiang 

TITLE=A 16-miRNA Prognostic Model to Predict Overall Survival in Neuroblastoma

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.827842

DOI=10.3389/fgene.2022.827842

ISSN=1664-8021

ABSTRACT=Neuroblastoma is the most malignant childhood tumor. The outcome of neuroblastoma is hard to predict due to the limitation of prognostic markers. In our study, we constructed a 16 miRNAs prognostic model to predict the overall survival of neuroblastoma patients at early diagnosis. A total of 205 DE miRNAs were screened using RNA sequencing data from GSE121513. Lasso-Cox regression analysis generated a 16 miRNAs signature consisting of hsa-let-7c, hsa -miR-135a, hsa -miR-137, hsa -miR-146a, hsa -miR-149, hsa -miR-15a, hsa -miR-195, hsa -miR-197, hsa -miR-200c, hsa -miR-204, hsa -miR-302a, hsa -miR-331, hsa -miR-345, hsa -miR-383, hsa -miR-93, hsa -miR-9star. The Concordance index of multivariate Cox regression analysis was 0.9 and the area under curve (AUC) of 3-year and 5-year survival were 0.92 and 0.943. The mechanism was further investigated using the TCGA dataset and GSE90689 datasets. Two miRNA-gene interaction networks were constructed among DEGs from two datasets. Functional analysis revealed that immune-related processes were involved in the initiation and metastasis of neuroblastoma. CIBERSORT and survival analysis suggested that lower CD8 T cells proportion and higher SPTA1 expression were related to a better prognosis. Our study demonstrated that miRNA signature may be useful in prognosis prediction and management improvement.