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Integrative profiling of liver cancer reveals lysine metabolic reprogramming and patient stratification with distinct immune microenvironment and therapeutic responses

GSE290298 Homo sapiens Expression profiling by high throughput sequencing 10 samples 2025/12/02 GPL24676
Summary
Liver cancer is a major global health challenge with high aggressiveness and recurrence rate. Metabolic reprogramming is one of the cancer hallmarks and allows tumor cells to adapt to drastic changes, supporting their rapid growth, survival, and proliferation under various conditions. Several amino acids have been found to undergo metabolic reprogramming in tumors and thus being potential anti-tumor targets. However, the characterization and implication of lysine metabolic reprogramming in tumors remains largely unexplored. Therefore, we carried out transcriptomics, proteomics, single-cell omics, immunohistochemistry, and multiplex immunofluorescence profiling on tumor and adjacent normal tissues obtained from 30 hepatocellular carcinoma patients to characterize the lysine metabolism in liver cancer and investigate its implications for tumor prognosis, immune microenvironment, and immunotherapy responses. Integrative analyses and quantitative evaluations revealed the reprogrammed lysine metabolism and inter-patient heterogeneity in liver cancer. The patients with lower lysine metabolism in tumors had worse prognoses and a predominance of immunosuppressive TIME, including increased infiltration of myeloid-derived suppressor cells, Tregs, TIM3+CD8+, and LAG3+CD8+T cells. These immunosuppressive cells contribute to immunotherapeutic resistance and promote tumor progression. Collectively, we highlighted the significance of lysine metabolism in shaping TIME and therapeutic responses of liver cancer, offering new insights into clinical molecular subtyping and potential therapeutic strategies.
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NCBI GEO page ↗ Paper (PMID 41107837) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
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