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Identification of hub genes associated with neutrophils infiltration in colorectal cancer.

ABSTRACT: Colorectal cancer (CRC) is the leading cause of cancer-related mortality in the world. Accumulating evidence indicate that tumour infiltrating immune cells participated in cancer progression. Among them, tumour infiltrating neutrophils (TINs) are reported to play crucial role in various cancers. In this study, we used CIBERSORTx, a digital cytometry tool to evaluate the neutrophils infiltration in CRC based on gene expression data of CRC tissues from GSE39582 data set and The Cancer Genome Atlas data set (TCGA-COAD and TCGA-READ). Weighted gene co-expression network analysis (WGCNA) was conducted in GSE39582 data set to identify hub genes associated with neutrophil infiltration. The association of hub gene and neutrophils was then validated in TCGA cohorts and an independent RJ cohort. Functional analysis was performed to investigate the molecular mechanisms of the interested hub gene. We found that neutrophil infiltration is elevated in CRC tissues, and it is related to a poorer prognosis. A total of 18 gene modules are identified by WGCNA in GSE39582 data set, among which lightcyan module is significantly correlated with neutrophils infiltration. Furthermore, Superoxide Dismutase 2 (SOD2) in lightcyan module was proved to correlated with neutrophils infiltration in various cancer types. In addition, SOD2 expression is highly associated with several chemokines, including CXCL8, a neutrophils-related attractant, and functional analysis revealed that SOD2 is involved in neutrophils recruitment biological process. These results indicate that an 'SOD2-CXCL8-neutrophil recruitment' axis plays a potential role in colorectal cancer progression.

SUBMITTER: Su H

PROVIDER: S-EPMC8034475 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:IntroductionProstate cancer (PCa) is one of the most common malignant tumors of the male urogenital system; however, the underlying mechanisms remain largely unclear. This study integrated two cohort profile datasets to elucidate the potential hub genes and mechanisms in PCa.Methods and resultsGene expression profiles GSE55945 and GSE6919 were filtered from the Gene Expression Omnibus (GEO) database to obtain 134 differentially expressed genes (DEGs) (14 upregulated and 120 downregulated) in PCa. Gene Ontology and pathway enrichment were performed using the Database for Annotation, Visualization, and Integrated Discovery, showing that these DEGs were mainly involved in biological functions such as cell adhesion, extracellular matrix, migration, focal adhesion, and vascular smooth muscle contraction. The STRING database and Cytoscape tools were used to analyze protein-protein interactions and identify 15 hub candidate genes. Violin plot, boxplot, and prognostic curve analyses were performed using Gene Expression Profiling Interactive Analysis, which identified seven hub genes, including upregulated expressed SPP1 and downregulated expressed MYLK, MYL9, MYH11, CALD1, ACTA2, and CNN1 in PCa compared with normal tissue. Correlation analysis was performed using the OmicStudio tools, which showed that these hub genes were moderately to strongly correlated with each other. Finally, quantitative reverse transcription PCR and western blotting were performed to validate the hub genes, showing that the abnormal expression of the seven hub genes in PCa was consistent with the analysis results of the GEO database.DiscussionTaken together, MYLK, MYL9, MYH11, CALD1, ACTA2, SPP1, and CNN1 are hub genes significantly associated with PCa occurrence. These genes are abnormally expressed, leading to the formation, proliferation, invasion, and migration of PCa cells and promoting tumor neovascularization. These genes may serve as potential biomarkers and therapeutic targets in patients with PCa.

Project description:AimsIn the cancer-related research field, there is currently a major need for a greater number of valuable biomarkers to predict the prognosis of hepatocellular carcinoma (HCC). In this study, we aimed to screen hub genes related to immune cell infiltration and explore their prognostic value for HCC.MethodsWe analyzed five datasets (GSE46408, GSE57957, GSE74656, GSE76427, and GSE87630) from the Gene Expression Omnibus database to screen the differentially expressed genes (DEGs). A protein-protein interaction network of the DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes; then, the hub genes were identified. Functional enrichment of the genes was performed on the Metascape website. Next, the expression of these hub genes was validated in several databases, including Oncomine, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), and Human Protein Atlas. We explored the correlations between the hub genes and infiltrated immune cells in the TIMER2.0 database. The survival curves were generated in GEPIA2, and the univariate and multivariate Cox regression analyses were performed using TIMER2.0.ResultsThe top ten hub genes [DNA topoisomerase II alpha (TOP2A), cyclin B2 (CCNB2), protein regulator of cytokinesis 1 (PRC1), Rac GTPase-activating protein 1 (RACGAP1), aurora kinase A (AURKA), cyclin-dependent kinase inhibitor 3 (CDKN3), nucleolar and spindle-associated protein 1 (NUSAP1), cell division cycle-associated 5 (CDCA5), abnormal spindle microtubule assembly (ASPM), and non-SMC condensin I complex subunit G (NCAPG)] were identified in subsequent analysis. These genes are most markedly enriched in cell division, suggesting their close association with tumorigenesis. Multi-database analyses validated that the hub genes were upregulated in HCC tissues. All hub genes positively correlated with several types of immune infiltration, including B cells, CD4+ T cells, macrophages, and dendritic cells. Furthermore, these hub genes served as independent prognostic factors, and the expression of these hub genes combing with the macrophage levels could help predict an unfavorable prognosis of HCC.ConclusionIn sum, these hub genes (TOP2A, CCNB2, PRC1, RACGAP1, AURKA, CDKN3, NUSAP1, CDCA5, ASPM, and NCAPG) may be pivotal markers for prognostic prediction as well as potentially work as targets for immune-based intervention strategies in HCC.

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Identification of hub genes associated with neutrophils infiltration in colorectal cancer.

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