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-miRNA prognostic model to predict the overall survival of neuroblastoma patients for early diagnosis. A total of 205 DE miRNAs were screened using RNA sequencing data from GSE121513. Lasso Cox regression analysis generated a 16-miRNA 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, and hsa-miR-9star. The concordance index of multivariate Cox regression analysis was 0.9, and the area under the curve (AUC) values of 3-year and 5-year survival were 0.92 and 0.943, respectively. The mechanism was further investigated using the TCGA 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-cell proportion and higher SPTA1 expressions were related to a better prognosis. Our study demonstrated that the miRNA signature may be useful in prognosis prediction and management improvement.
Keywords:
bioinformatic analysis; miRNA; neuroblastoma; overall survival; prognostic model.