Pan-Cancer analysis shows that ACO2 is a potential prognostic and immunotherapeutic biomarker for multiple cancer types including hepatocellular carcinoma.

Background: Recent evidence increasingly suggests key roles for the tricarboxylic acid cycle and fatty acid metabolism in tumor progression and metastasis. Aconitase 2 (ACO2) is a component of the tricarboxylic acid cycle and represents a key cellular metabolic hub that promotes Methods: Through the comprehensive use of datasets from The Cancer Genome Atlas, Genotype-Tissue Expression Project, cBioPortal, Human Protein Atlas, UALCAN, Gene Expression Profiling Interactive Analysis, DNA Methylation Interactive Visualization Database, and TIMER2, we adopted bioinformatics methods to uncover the potential carcinogenic roles of ACO2, including by analysing ACO2 expression and correlations between prognosis, genetic mutations, immune cell infiltration, DNA methylation, tumor mutational burden, and microsatellite instability in different tumors. Additionally, the expression level and tumor-promoting effect of ACO2 were verified in hepatocellular carcinoma (HCC) cells. To explore the underlying mechanisms of ACO2 in human cancer, ACO2-related gene enrichment analysis and lipid metabolomics were performed using LM3 cells with or without ACO2 knockdown. Results: The results indicated that ACO2 was highly expressed in most cancers, showing early diagnostic value in six tumor types, and was positively or negatively associated with prognosis in different tumors. Moreover, ACO2 expression was associated with immune cell infiltration, such as CD8+ T cells and tumor-associated neutrophils, in some cancers. For most cancer types, there was a significant association between immune checkpoint-associated genes and ACO2 expression. Compared with normal hepatocytes, ACO2 was upregulated in HCC cells, which promoted their proliferation and migration. Furthermore, to explore the underlying molecular mechanism, we performed KEGG pathway enrichment analysis of ACO2-associated genes and lipidomics using LM3 cells with or without ACO2 knockdown, which screened 19 significantly altered metabolites, including 17 with reduced levels and 2 with increased levels. Conclusion: Through pan-cancer analysis, we discovered for the first time and verified that ACO2 could be a useful diagnostic biomarker for cancer detection. Additionally, ACO2 could be used as an auxiliary prognostic marker or as a marker for immunotherapy in some tumor types.