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Hepatocellular carcinoma (HCC) is a major cause of cancer-related death due to early metastasis or recurrence. Tumor angiogenesis plays an essential role in the tumorigenesis of HCC. Accumulated studies have validated the crucial role of lncRNAs in tumor angiogenesis. Here, we established an angiogenesis-related multi-lncRNAs risk model based on the machine learning for HCC prognosis prediction. Firstly, a total of 348 differential expression angiogenesis-related lncRNAs were identified by correlation analysis. Then, 20 of these lncRNAs were selected through univariate cox analysis and used for in-depth study of machine learning. After 1,000 random sampling cycles calculating by random forest algorithm, four lncRNAs were found to be highly associated with HCC prognosis, namely LUCAT1, AC010761.1, AC006504.7 and MIR210HG. Subsequently, the results from both the training and validation sets revealed that the four lncRNAs-based risk model was suitable for predicting HCC recurrence. Moreover, the infiltration of macrophages and CD8 T cells were shown to be closely associated with risk score and promotion of immune escape. The reliability of this model was validated by exploring the biological functions of lncRNA MIR210HG in HCC cells. The results showed that MIR210HG silence inhibited HCC growth and migration through upregulating PFKFB4 and SPAG4. Taken together, this angiogenesis-related risk model could serve as a reliable and promising tool to predict the prognosis of HCC.
Pubmed ID: 37550755 RIS Download
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Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.
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View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsA commercial antibody supplier which supplies primary and secondary antibodies, biochemicals, proteins, peptides, lysates, immunoassays and other kits.
View all literature mentionsA unified data repository of the National Cancer Institute (NCI)'s Genomic Data Commons (GDC) that enables data sharing across cancer genomic studies in support of precision medicine. The GDC supports several cancer genome programs at the NCI Center for Cancer Genomics (CCG), including The Cancer Genome Atlas (TCGA), Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and the Cancer Genome Characterization Initiative (CGCI). The GDC Data Portal provides a platform for efficiently querying and downloading high quality and complete data. The GDC also provides a GDC Data Transfer Tool and a GDC API for programmatic access.
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