Original Article
A 4-miRNA signature act as a novel prognostic biomarker in patients with Sarcoma
Abstract
Background: A sarcoma is a rare form of cancer that can develop throughout the body and has a poor prognosis. Micro RNA may be used as molecular markers in sarcoma patients to predict patient outcomes.
Methods: In this study, miRNA expression data of sarcoma tissues samples were downloaded from The Cancer Genome Atlas (TCGA) database. The univariable cox regression and log likelihood were performed to screen the miRNAs related with prognosis. The Cox proportional hazard regression model was used to establish a multi-gene prognostic model based on the expression value of the miRNAs. The survival curve was created by the KM method. The interaction network and function annotation of the target genes were analyzed to investigate the mechanism of the key miRNAs.
Results: Hsa-miR-190b, hsa-miR-3170, hsa-miR-4762, hsa-miR-18a were identified and used to establish the prediction model. The target genes of the 4 miRNAs were involved in cancer signaling pathways as revealed by KEGG. Cox regression analysis showed that the prognostic model of miRNA was an independent influencing factor in Sarcoma patients (P<0.05). Survival analysis confirmed that the overall survival rate of sarcoma patients with low risk scores was significantly higher than those with high risk scores (P<0.01).
Conclusions: The miRNA prognosis model established in this study can be used to predict the prognosis of Sarcoma patients, and these 4 miRNAs may involve in cancer signaling pathways by regulating these target genes
Methods: In this study, miRNA expression data of sarcoma tissues samples were downloaded from The Cancer Genome Atlas (TCGA) database. The univariable cox regression and log likelihood were performed to screen the miRNAs related with prognosis. The Cox proportional hazard regression model was used to establish a multi-gene prognostic model based on the expression value of the miRNAs. The survival curve was created by the KM method. The interaction network and function annotation of the target genes were analyzed to investigate the mechanism of the key miRNAs.
Results: Hsa-miR-190b, hsa-miR-3170, hsa-miR-4762, hsa-miR-18a were identified and used to establish the prediction model. The target genes of the 4 miRNAs were involved in cancer signaling pathways as revealed by KEGG. Cox regression analysis showed that the prognostic model of miRNA was an independent influencing factor in Sarcoma patients (P<0.05). Survival analysis confirmed that the overall survival rate of sarcoma patients with low risk scores was significantly higher than those with high risk scores (P<0.01).
Conclusions: The miRNA prognosis model established in this study can be used to predict the prognosis of Sarcoma patients, and these 4 miRNAs may involve in cancer signaling pathways by regulating these target genes
