Multi-omics analysis identifies SNP-associated immune-related signatures by integrating Mendelian randomization and machine learning in hepatocellular carcinoma
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View abstract on PubMed
Summary
This summary is machine-generated.This study developed a novel riskScore model to predict outcomes for hepatocellular carcinoma (HCC) patients. The model integrates genetic and immune data, improving patient stratification and guiding chemotherapy decisions for better HCC treatment.
Area Of Science
- Oncology
- Genomics
- Immunology
Background
- Hepatocellular carcinoma (HCC) presents a significant global health challenge with high mortality and limited treatment options.
- Accurate patient stratification and personalized therapies are crucial due to HCC's complex molecular and immune characteristics.
Purpose Of The Study
- To identify key genes influencing HCC prognosis and develop a robust prognostic model.
- To integrate genetic, clinical, and immune data for improved patient stratification and treatment prediction in HCC.
Main Methods
- Utilized large-scale gene expression data (TCGA, GSE54236) and eQTL GWAS data.
- Applied Mendelian randomization, survival analysis, and 101 machine learning algorithms to build a prognostic model.
- Validated the riskScore model using survival analysis, drug sensitivity prediction, and in vitro assays.
Main Results
- Identified 27 candidate genes, with 16 classified as high-risk, and developed a riskScore model with excellent prognostic performance (C-index > 0.7).
- High-risk patients showed poorer prognosis, increased immune cell infiltration (T cells, neutrophils), and greater sensitivity to specific chemotherapies (5-Fluorouracil, Paclitaxel).
- TP53 and MUC16 mutations were frequent in high-risk groups; SLC16A3 and STRBP genes promoted HCC cell proliferation and invasion.
Conclusions
- The developed riskScore model effectively stratifies HCC patients based on integrated genetic and immune factors.
- This model shows potential for clinical application in patient stratification and optimizing chemotherapy strategies for hepatocellular carcinoma.
- Key genes like SLC16A3 and STRBP play a significant role in HCC progression, offering potential therapeutic targets.
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