Pan-cancer Analysis Reveals SRC May Link Lipid Metabolism and Macrophages

Zhongyuan Chen; Yaqian Xiao; Pinhong Yang; Ruisong Wang

doi:10.30498/ijb.2023.335402.3325

Pan-cancer Analysis Reveals SRC May Link Lipid Metabolism and Macrophages

Iran J Biotechnol. 2023 Apr 1;21(2):e3325. doi: 10.30498/ijb.2023.335402.3325. eCollection 2023 Apr.

Authors

Zhongyuan Chen^{1

2}, Yaqian Xiao³, Pinhong Yang^{1

2}, Ruisong Wang^{1

2}

Affiliations

¹ College of Life and Environmental Sciences, Hunan University of Arts and Science, Changde, Hunan, China.
² Changde Research Centre for Artificial Intelligence and Biomedicine, Changde, Hunan, China.
³ Furong College, Hunan 3Furong College, Hunan University of Arts and Science, Changde, Hunan, China.

Abstract

Background: SRC is a member of the membrane-associated non-receptor protein tyrosine kinase superfamily. It has been reported to mediate inflammation and cancer. However, the exact molecular mechanism involved is still not clear.

Objectives: The current study was designed to explore the prognostic landscape of SRC and further investigate the relationship between SRC and immune infiltration in pan-cancer.

Materials and methods: Kaplan-Meier Plotter was used to detect the prognostic value of SRC in pan-cancer. Then using TIMER2.0 and CIBERSORT, the relationship between SRC and immune infiltration in pan-cancer was evaluated. Furthermore, the LinkedOmics database was used to screen SRC co-expressed genes, followed by functional enrichment of SRC co-expressed genes by Metascape online tool. STRING database and Cytoscape software were applied to construct and visualise the protein-protein interaction network of SRC co-expressed genes. MCODE plug-in was used to screen hub modules in the PPI network. The SRC co-expressed genes in hub modules were extracted, and the correlation analysis between interested SRC co-expressed genes and immune infiltration was conducted via TIMER2.0 and CIBERSORT.

Results: Our study demonstrated that SRC expression was significantly associated with overall survival and relapse-free survival in multiple cancer types. In addition, SRC expression was significantly correlated with the immune infiltration of B cells, dendritic cells, CD4⁺ T cells, macrophages, and neutrophils in pan-cancer. The expression of SRC had shown to have close correlations with M1 macrophage polarisation in LIHC, TGCT, THCA, and THYM. Moreover, the genes that co-expressed with SRC in LIHC, TGCT, THCA, and THYM were mainly enriched in lipid metabolism. Besides, correlation analysis showed that SRC co-expressed genes associated with lipid metabolism were also significantly correlated with the infiltration and polarisation of macrophages.

Conclusion: These results indicate that SRC can serve as a prognostic biomarker in pan-cancer and is related to macrophages infiltration and interacts with genes involved in lipid metabolism.

Keywords: Immune cell infiltration; Lipid metabolism; Macrophages; Pan-cancer; SRC.