Multi omics analysis reveals senescence associated genes in metabolic dysfunction associated steatohepatitis related liver cancer and their functional validation

Background: Metabolic Dysfunction Associated Steatohepatitis Related Liver Cancer (MRLC) is a senescence associated disease. The role of Senescence Associated Genes (SAGs) in MRLC still needs further exploration.

Methods: The Global Burden of Disease Database was used to analyze the main age groups of MRLC incidence in the population. Mendelian randomization was used to analyze the causal relationship between senescence and MRLC. Differential expression genes, Weighted Gene Co-Expression Network analysis, multi machine learning methods, and Shapley Additive ExPlanations were used to screen core SAGs. CIBERSORT was used to perform immune infiltration analysis. Single-cell RNA Sequencing and scTenifoldKnk were used to visualization the cellular distribution of core SAGs and gene knockout in MRLC. Drug sensitively prediction and molecular docking were used to screen potential drugs targeting core SAGs for the treatment of MRLC. C57BL/6 mice was used to establish MRLC model for experiments.

Results: The disease burden of MRLC was mainly concentrated in the elderly population worldwide. SOD2, ALDH2, MME and IGFBP1 which were belonged to SAGs were differential expressed in MRLC compared to paracancerous, and function enrichment analysis suggested that these four SAGs may play important role in promoting proliferation and metastasis of MRLC through reprogramming metabolic and reshaping the immune microenvironment. EPZ5676 had excellent affinity with all four genes.

Conclusion: We highlight the role of SAGs in MRLC. SOD2, ALDH2, MME and IGFBP1 were potential biomarkers and therapeutic targets. EPZ5676 was a potential drug for treating MRLC by targeting these four genes.