Abstract
Colon adenocarcinoma is one of the tumors with the highest mortality rate, and tumorigenesis or development of colon adenocarcinoma is the major reason leading to patient death. However, the molecular mechanism and biomarker to predict tumor progression are currently unclear. With the goal of understanding the molecular mechanism and tumor progression, we utilized the TCGA database to identify differentially expressed genes. After identifying the differentially expressed genes among colon adenocarcinoma tissues with different expression levels of LGR4 and normal tissue, protein-protein interaction, gene ontology, pathway enrichment, gene set enrichment analysis, and immune cell infiltration analysis were conducted. Here, the top 10 hub genes, i.e., ALB, F2, APOA2, CYP1A1, SPRR2B, APOA1, APOB, CYP3A4, SST, and GCG, were identified, and relative correlation analysis was conducted. Kaplan-Meier analysis revealed that higher expression of LGR4 correlates with overall survival of colon adenocarcinoma patients, although expression levels of LGR4 in normal tissues are higher than in tumor tissues. Further functional analysis demonstrated that higher expression of LGR4 in colon adenocarcinoma may be linked to up-regulate metabolism-related pathways, for example, the cholesterol biosynthesis pathway. These results were confirmed by gene set enrichment analysis. Immune cell infiltration analysis clearly showed that the infiltration percentage of T cells was significantly higher than other immune cells, and TIMER analysis revealed a positive correlation between T-cell infiltration and LGR4 expression. Finally, COAD cancer cells, Caco-2, were employed to be incubated with squalene and 25-hydroxycholesterol-3-sulfate, and relative experimental results confirmed that the cholesterol biosynthesis pathway involved in modulating the proliferation of COAD tumorigenesis. Our investigation revealed that LGR4 can be an emerging diagnostic and prognostic biomarker for colon adenocarcinoma by affecting metabolism-related pathways.
Keywords:
LGR4; bioinformatics analysis; colon adenocarcinoma; tumorgenesis.