AUTHOR=Zhang Xixia , Li Xiao , Wang Caixia , Wang Shuang , Zhuang Yuan , Liu Bing , Lian Xin TITLE=Identification of markers for predicting prognosis and endocrine metabolism in nasopharyngeal carcinoma by miRNA–mRNA network mining and machine learning JOURNAL=Frontiers in Endocrinology VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1174911 DOI=10.3389/fendo.2023.1174911 ISSN=1664-2392 ABSTRACT=Background

Nasopharyngeal cancer (NPC) has a high incidence in Southern China and Asia, and its survival is extremely poor in advanced patients. MiRNAs play critical roles in regulating gene expression and serve as therapeutic targets in cancer. This study sought to disclose key miRNAs and target genes responsible for NPC prognosis and endocrine metabolism.

Materials and methods

Three datasets (GSE32960, GSE70970, and GSE102349) of NPC samples came from Gene Expression Omnibus (GEO). Limma and WGCNA were applied to identify key prognostic miRNAs. There were 12 types of miRNA tools implemented to study potential target genes (mRNAs) of miRNAs. Univariate Cox regression and stepAIC were introduced to construct risk models. Pearson analysis was conducted to analyze the correlation between endocrine metabolism and RiskScore. Single-sample gene set enrichment analysis (ssGSEA), MCP-counter, and ESTIMATE were performed for immune analysis. The response to immunotherapy was predicted by TIDE and SubMap analyses.

Results

Two key miRNAs (miR-142-3p and miR-93) were closely involved in NPC prognosis. The expression of the two miRNAs was dysregulated in NPC cell lines. A total of 125 potential target genes of the key miRNAs were screened, and they were enriched in autophagy and mitophagy pathways. Five target genes (E2F1, KCNJ8, SUCO, HECTD1, and KIF23) were identified to construct a prognostic model, which was used to divide patients into high group and low group. RiskScore was negatively correlated with most endocrine-related genes and pathways. The low-risk group manifested higher immune infiltration, anticancer response, more activated immune-related pathways, and higher response to immunotherapy than the high-risk group.

Conclusions

This study revealed two key miRNAs that were highly contributable to NPC prognosis. We delineated the specific links between key miRNAs and prognostic mRNAs with miRNA–mRNA networks. The effectiveness of the five-gene model in predicting NPC prognosis as well as endocrine metabolism provided a guidance for personalized immunotherapy in NPC patients.