Journal of Jilin University(Medicine Edition) ›› 2025, Vol. 51 ›› Issue (3): 703-715.doi: 10.13481/j.1671-587X.20250315

• Research in clinical medicine • Previous Articles    

Bioinformatics analysis on adjustment effect of colorectal liver metastases model in mice based on complement alternative pathway and its experimental verification

Changyu SHI1,Yong LI1,Jing DENG1,Chunmei PIAO2,Ming JIN1()   

  1. 1.Department of Biochemistry and Molecular Biology,School of Medical Sciences,Yanbian University,Yanji 133000,China
    2.Affiliated Beijing Anzhen Hospital,Capital Medical University,Beijing Institute of Heart Lung and Blood Vessel Diseases,Beijing 100029,China
  • Received:2024-05-09 Accepted:2024-08-06 Online:2025-05-28 Published:2025-07-18
  • Contact: Ming JIN E-mail:jinming@ybu.edu.cn

Abstract:

Objective To discuss the regulatory role of complement alternative pathway in mouse colorectal cancer (CRC) liver metastasis model based on bioinformatics methods, and to clarify its mechanism through experimental verification. Methods Using “CRC liver metastasis” as the keyword, the GSE81558 dataset was retrieved from Gene Expression Omnibus (GEO) database, including normal colon tissue samples, CRC tissue samples and CRC liver metastasis tissue samples. Bioinformatics methods were used to analyze and screen differentially expressed genes (DEGs). Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using R and Cytoscape software, and the results were visualized. Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was used to evaluate protein-protein interactions (PPIs) of DEGs and construct PPI network. Twelve C57BL/6 mice were injected with SL4 tumor cells into spleen, and the liver tissues were collected at 0, 7 and 14 d. Real-time fluorescence quantitative PCR (RT-qPCR) method was used to detect the expression levels of complement pathway-related genes in liver metastatic foci. The CRC liver metastasis mouse model was used to verify the complement signaling pathway. The mice were divided into control group, factor B knockout group (FB-/-) and C4 factor knockout group (C4-/-), and there were 6 mice in each group. The liver weights of the mice were measured; HE staining was used to detect the percentage of metastatic area in liver tissue in control group and FB-/- group; immunohistochemistry was used to detect macrophage infiltration in liver tissue in control group and FB-/- group, and the percentage of macrophage infiltration was calculated. Results The distances between normal colon tissue samples and CRC tissue samples, as well as between CRC tissue samples and CRC liver metastasis tissue samples were far, indicating significant differences between samples, allowing subsequent analysis of DEGs. A total of 1 908 DEGs were screened in the dataset comparing normal colon tissue samples and CRC tissue samples, including 771 up-regulated DEGs and 1 137 down-regulated DEGs. Twenty-three up-regulated DEGs and 100 down-regulated DEGs were identified in the dataset comparing CRC and CRC liver metastasis. The GO functional enrichment analysis results showed that compared with normal colon tissue samples, DEGs in CRC samples were mainly enriched in biological processes (BP) related to cell cycle and mitosis, including mitotic cell cycle process, cell division, response to hormone, mitotic nuclear division and response to lipid. Compared with CRC samples, the DEGs in CRC liver metastasis samples were mainly enriched in coagulation-related BP, including platelet degranulation, blood coagulation regulation, acute-phase response, hemostasis regulation and coagulation regulation. The KEGG pathway enrichment analysis results showed that compared with normal colon tissue samples, the DEGs in CRC tissue samples were mainly enriched in cell cycle and p53 signaling pathways. Compared with CRC tissue samples, the DEGs in CRC liver metastasis tissue samples were mainly enriched in complement, coagulation cascade and metabolism-related signaling pathways. The Hub genes identified in PPI network were related to blood proteins. The RT-qPCR results showed that compared with 0 d group, the mRNA expression level of complement related genes complement 1q (C1q) in liver metastatic foci tissue sampres in 7 d group was significantly decreased (P<0.05), the mRNA expression levels of complement 3 (C3), complement 5 (C5), FB, and factor D (FD) were significantly increased (P<0.05 or P<0.01), the mRNA expression levels of complement pathway-related genes C1q, complement 2 (C2), C3, complement fragment 3a receptor (C3aR), C5, complement fragment 5a receptor (C5aR), decay-accelerating factor (DAF), FB and FD in liver metastatic foci tissue sampres in 14 d group were significantly increased (P<0.05 or P<0.01). Compared with control group, the liver weight of the mice in FB-/- group was significantly decreased (P<0.01), while there was no significant difference was observed in C4-/- group (P>0.05). The HE staining results showed that compared with control group, the liver metastatic foci in FB-/- mice were significantly decreased, and the percentage of metastatic area was decreased (P<0.01). The immunohistochemistry results showed that compared with control group, the macrophage infiltration in liver metastatic foci of the mice in FB-/- group was reduced, and the percentage of macrophage infiltration was decreased (P<0.01). Conclusion Complement cascade is associated with CRC liver metastasis, and the alternative complement pathway regulates CRC liver metastasis, suggesting this pathway may serve as a potential therapeutic target for CRC liver metastasis.

Key words: Colorectal cancer, Liver metastasis, Gene Expression Omnibus database, Bioinformatics, Differentially expressed genes

CLC Number: 

  • R735.3