ArticleScientific reports2025
Machine learning developed LKB1-AMPK signaling related signature for prognosis and drug sensitivity in hepatocellular carcinoma.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- LKB1 dictates sensitivity to immunotherapy through Skp2-mediated ubiquitination of immune checkpoint proteins in HCC with python analysis.Iranian journal of basic medical sciences · 2026Article
- Computer-Aided Drug Design Across Breast Cancer Subtypes: Methods, Applications and Translational Outlook.International journal of molecular sciences · 2025Review
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3 authors.
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Abstract
Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide, posing a significant threat to the life and health of people globally. LKB1-AMPK signaling pathway plays a significant role in the regulation of cellular metabolism, proliferation and survival in cancer. To construct a LKB1-AMPK signaling-related gene signature (LRS), an ensemble of ten machine learning algorithms was applied across four datasets. Several indicators were employed to assess the effectiveness of LRS in forecasting immunological responses. Additionally, in vitro studies were conducted to investigate the biological roles of LKB1 in HCC. The optimal LRS developed using the Lasso algorithm served as a significant risk factor for HCC patients. HCC patients with a high LRS score exhibited poorer prognoses, with 1-, 3-, and 5-year ROC AUC values of 0.863, 0.826, and 0.831, respectively. Conversely, a low LRS score was associated with higher levels of CD8
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