Dataset Information

A Five-MicroRNA Signature Predicts the Prognosis in Nasopharyngeal Carcinoma.

ABSTRACT:

Background

There is no effective prognostic signature that could predict the prognosis of nasopharyngeal carcinoma (NPC).

Methods

We constructed a prognostic signature based on five microRNAs using random forest and Least Absolute Shrinkage And Selection Operator (LASSO) algorithm on the GSE32960 cohort (N = 213). We verified its prognostic value using three independent external validation cohorts (GSE36682, N = 62; GSE70970, N = 246; and TCGA-HNSC, N = 523). Through principal component analysis, receiver operating characteristic curve analysis, and C-index calculation, we confirmed the predictive accuracy of this prognostic signature.

Results

We calculated the risk score based on the LASSO algorithm and divided the patients into high- and low-risk groups according to the calculated optimal cutoff value. The patients in the high-risk group tended to have a worse prognosis outcome and chemotherapy response. The time-dependent receiver operating characteristic curve showed that the 1-year overall survival rate of the five-microRNA signature had an area under the curve of more than 0.83. A functional annotation analysis of the five-microRNA signature showed that the patients in the high-risk group were usually accompanied by activation of DNA repair and MYC-target pathways, while the patients in the low-risk group had higher immune-related pathway signals.

Conclusions

We constructed a five-microRNA prognostic signature, which could accurately predict the prognosis of nasopharyngeal carcinoma, and constructed a nomogram that could conveniently predict the overall survival of patients.

SUBMITTER: Wu S

PROVIDER: S-EPMC8459682 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

A Five-MicroRNA Signature Predicts the Prognosis in Nasopharyngeal Carcinoma.

Wu Shixiong S Zhang Cen C Xie Jing J Li Shuang S Huang Shuo S

Frontiers in oncology 20210909

<h4>Background</h4>There is no effective prognostic signature that could predict the prognosis of nasopharyngeal carcinoma (NPC).<h4>Methods</h4>We constructed a prognostic signature based on five microRNAs using random forest and Least Absolute Shrinkage And Selection Operator (LASSO) algorithm on the GSE32960 cohort (<i>N</i> = 213). We verified its prognostic value using three independent external validation cohorts (GSE36682, <i>N</i> = 62; GSE70970, <i>N</i> = 246; and TCGA-HNSC, <i>N</i> = ...[more]

PMID: 34568051

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Project description:The aim of the present study was to identify microRNAs (miRNAs) that predict the prognosis of patients with nasopharyngeal carcinoma by integrated bioinformatics analysis. First, the original microarray dataset GSE32960, including 312 nasopharyngeal carcinomas and 18 normal samples, was downloaded from the Gene Expression Omnibus database. In addition, 46 differentially expressed miRNAs (DEMs) were screened. Then, four miRNAs, including hsa‑miR‑142‑3p, hsa‑miR‑150, hsa‑miR‑29b, and hsa‑miR‑29c, were obtained as prognostic markers by combining univariate Cox regression analysis with weighted gene coexpression network analysis (WGCNA). Subsequently, the risk score of 312 NPC patients from the signature of miRNAs was calculated, and patients were divided into high‑risk or low‑risk groups. Notably, compared with patients with low‑risk scores, high‑risk groups had shorter disease‑free survival (DFS), overall survival (OS), and distant metastasis‑free survival (DMFS). Receiver operating characteristic curve (ROC) analysis indicated that the risk score was a very effective prognostic factor. Moreover, the Search Tool for the Database for Annotation, Visualization, and Integrated Discovery (DAVID), Cytoscape, starBase, and Retrieval of Interacting Genes database (STRING) were used to establish the miRNA‑mRNA correlation network and the protein‑protein interaction (PPI) network. In addition, the shared genes superimposing 888 protein‑coding genes targeted by four hub miRNAs and 1,601 upregulated differentially expressed mRNAs accounted for 127 and were used for subsequent gene functional enrichment analysis. In particular, biological pathway analysis indicated that these genes mainly participate in some vital pathways related to cancer pathogenesis, such as the focal adhesion, PI3K/Akt, p53, and mTOR signalling pathways. In summary, the identification of NPC patients with a four‑miRNA signature may increase the prognostic value and provide reference information for precision medicine.

Project description:AimsEpidermal growth factor receptor (EGFR) belongs to the receptor tyrosine kinases family and overexpression of EGFR has been linked to poor prognosis and cancer progression. Somatostatin receptor 2 (SSTR2) is a G-protein-coupled receptor (GPCR) with diverse biological functions in humans, and it is upregulated through the NF-KB signalling pathway in nasopharyngeal carcinomas (NPC). However, no studies have examined the EGFR and SSTR2 in NPC. This study aimed to investigate whether SSTR2 is associated with EGFR and clinicopathological features in NPC.MethodsBioinformatics analysis was performed to assess the correlation between EGFR and SSTR2 based on the GEO database. The expression of SSTR2 and EGFR was evaluated by immunohistochemistry (IHC) in 491 cases of NPC and 50 cases of non-cancerous nasopharyngeal epithelium.ResultsThe bioinformatics analysis and IHC showed a positive correlation between SSTR2 and EGFR in NPC. High expression of SSTR2 and EGFR was significantly increased in NPC patients compared with non-cancerous nasopharyngeal epithelium. High expression of SSTR2 and/or EGFR was associated with a worse outcome and a higher risk of progression. The study found that patients receiving chemoradiotherapy (CR) with high expression of SSTR2, high expression of EGFR, and high coexpression of SSTR2 and EGFR had a poorer prognosis in both progression-free survival (PFS) and overall survival (OS). Interestingly, NPC patients with high expression of SSTR2, high expression of EGFR, high coexpression of EGFR and SSTR2, and EGFR/SSTR2 anyone high expression had a better prognosis with CR combined with targeted therapy. Cox multivariate analysis identified SSTR2 and EGFR as independent poor predictors of PFS.ConclusionOur study is the first to shed light on the intricate relationship between SSTR2 and EGFR in NPC and provides new insights into the potential benefits of EGFR targeted therapy for patients with high SSTR2 expression. Additionally, SSTR2 has potential as a new biomarker for poor prognosis in NPC patients.

Dataset Information

A Five-MicroRNA Signature Predicts the Prognosis in Nasopharyngeal Carcinoma.

Background

Methods

Results

Conclusions

Publications

A Five-MicroRNA Signature Predicts the Prognosis in Nasopharyngeal Carcinoma.

Similar Datasets

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