Potential effective diagnostic biomarker in patients with primary and metastatic small intestinal neuroendocrine tumors.

Small intestinal neuroendocrine tumors (SI-NETs) are the most common malignant tumors of the small intestine, with many patients presenting with metastases and their incidence increasing. We aimed to find effective diagnostic biomarkers for patients with primary and metastatic SI-NETs that could be applied for clinical diagnosis. We downloaded GSE65286 (training set) and GSE98894 (test set) from the GEO database and performed differential gene expression analysis to obtain differentially expressed genes (DEGs) and differentially expressed long non-coding RNAs (DElncRNAs). The functions and pathways involved in these genes were further explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. In addition, a global regulatory network involving dysregulated genes in SI-NETs was constructed based on RNAInter and TRRUST v2 databases, and the diagnostic power of hub genes was identified by receiver operating characteristic curve (ROC). A total of 2,969 DEGs and DElncRNAs were obtained in the training set. Enrichment analysis revealed that biological processes (BPs) and KEGG pathways were mainly associated with cancer. Based on gene set enrichment analysis (GSEA), we obtained five BPs (cytokinesis, iron ion homeostasis, mucopolysaccharide metabolic process, platelet degranulation and triglyceride metabolic process) and one KEGG pathway (ppar signaling pathway). In addition, the core set of dysregulated genes obtained included MYL9, ITGV8, FGF2, FZD7, and FLNC. The hub genes were upregulated in patients with primary SI-NETs compared to patients with metastatic SI-NETs, which is consistent with the training set. Significantly, the results of ROC analysis showed that the diagnostic power of the hub genes was strong in both the training and test sets. In summary, we constructed a global regulatory network in SI-NETs. In addition, we obtained the hub genes including MYL9, ITGV8, FGF2, FZD7, and FLNC, which may be useful for the diagnosis of patients with primary and metastatic SI-NETs.