Identified GNGT1 and NMU as Combined Diagnosis Biomarker of Non-Small-Cell Lung Cancer Utilizing Bioinformatics and Logistic Regression

Abstract

Non-small-cell lung cancer (NSCLC) is one of the most devastating diseases worldwide. The study is aimed at identifying reliable prognostic biomarkers and to improve understanding of cancer initiation and progression mechanisms. RNA-Seq data were downloaded from The Cancer Genome Atlas (TCGA) database. Subsequently, comprehensive bioinformatics analysis incorporating gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and the protein-protein interaction (PPI) network was conducted to identify differentially expressed genes (DEGs) closely associated with NSCLC. Eight hub genes were screened out using Molecular Complex Detection (MCODE) and cytoHubba. The prognostic and diagnostic values of the hub genes were further confirmed by survival analysis and receiver operating characteristic (ROC) curve analysis. Hub genes were validated by other datasets, such as the Oncomine, Human Protein Atlas, and cBioPortal databases. Ultimately, logistic regression analysis was conducted to evaluate the diagnostic potential of the two identified biomarkers. Screening removed 1,411 DEGs, including 1,362 upregulated and 49 downregulated genes. Pathway enrichment analysis of the DEGs examined the Ras signaling pathway, alcoholism, and other factors. Ultimately, eight prioritized genes (GNGT1, GNG4, NMU, GCG, TAC1, GAST, GCGR1, and NPSR1) were identified as hub genes. High hub gene expression was significantly associated with worse overall survival in patients with NSCLC. The ROC curves showed that these hub genes had diagnostic value. The mRNA expressions of GNGT1 and NMU were low in the Oncomine database. Their protein expressions and genetic alterations were also revealed. Finally, logistic regression analysis indicated that combining the two biomarkers substantially improved the ability to discriminate NSCLC. GNGT1 and NMU identified in the current study may empower further discovery of the molecular mechanisms underlying NSCLC’s initiation and progression.

Identification of potential diagnostic and prognostic biomarkers for LUAD based on TCGA and GEO databases

“…Transducin, also known as GMPase, mediates the activation of a cyclic GTP-specific (guanosine monophosphate) phosphodiesterase by rhodopsin. Zhang et al [ 53 ] reported that the expression level of GNGT1 in NSCLC was overexpressed, and the high expression of GNGT1 was significantly associated with worse OS in patients with NSCLC. NPSR1 is a G-protein-coupled receptor that induces intracellular signaling upon stimulation by neuropeptide S (NPS) via mobilization of calcium, increased cyclic adenosine monophospate (cAMP) levels, and activation of the mitogen-activated protein kinase (MAPK) pathway [ 54 , 55 ].…”

“…NPSR1 is a G-protein-coupled receptor that induces intracellular signaling upon stimulation by neuropeptide S (NPS) via mobilization of calcium, increased cyclic adenosine monophospate (cAMP) levels, and activation of the mitogen-activated protein kinase (MAPK) pathway [ 54 , 55 ]. Zhang et al [ 53 ] found that the expression level of NPSR1 in NSCLC was overexpressed. In addition, a previous study suggested that NPSR1 is a marker widely expressed in neuroendocrine tumors (NET) with the exception of adrenal pheochromocytomas, the stimulation of NPSR1 with NPS results in activation of pathways that are relevant for cancer development [ 56 ].…”

“…Martinelli et al [ 75 ] found that high frequency of CALCA methylation was associated with non-seminomatous tumors and promoter methylation of CALCA predicts poor clinical outcome for testicular germ cell tumors patients. Zhang et al [ 53 ] found that the expression level of GNGT1 in NSCLC was high, and the high expression of GNGT1 was significantly associated with worse OS in patients with NSCLC.…”

A miR-212-3p/SLC6A1 Regulatory Sub-Network for the Prognosis of Hepatocellular Carcinoma

“…Nowadays, bioinformatics analysis has become increasingly important for exploring underlying mechanisms of various cancers. 39–42 This study has established a transgenic mouse model of liver cancer (Alb-Cre/Myc mice), and Myc is suggested to be a proverbial oncogenic factor in HCC, 43 providing a potential target for the prognosis and treatment of HCC dependent on Myc variants.…”

Sensitivity of Plasma Micrornas as a Probable Non-Small Cell Lung Cancer Biomarker and Its Significance

“…In contrast, the 5-year endurance percentage of stage I NSCLC positive individuals receiving successful treatment may be up to maximum of 83%. So, early detection of NSCLC can decrease death ratio [1][2][3] . Prompt recognition of NSCLC on X-ray and sputum cytology has less sensitivity.…”