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Related Experiment Video

Updated: Mar 17, 2026

Mass Cytometry Analysis of Systemic and Local Immune Responses in Hepatocellular Carcinoma
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Systemic transcriptome analysis of hepatocellular carcinoma.

Cheng-Bo Yu1, Li-Yao Zhu2, Yu-Gang Wang3

  • 1State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, China.

Tumour Biology : the Journal of the International Society for Oncodevelopmental Biology and Medicine
|July 28, 2016
PubMed
Summary

This study systematically analyzed gene expression in hepatocellular carcinoma (HCC), classifying subtypes and identifying key genes. ZSCAN18 methylation may predict prognosis, while ABHD6 shows potential as an anti-cancer target.

Keywords:
ABHD6Hepatocellular carcinomaMolecular classificationTCGAZSCAN18

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Liver cancer, primarily hepatocellular carcinoma (HCC), is a major global health concern.
  • Understanding the molecular landscape of HCC is crucial for developing targeted therapies.

Purpose of the Study:

  • To systematically analyze gene expression characteristics and identify key genes involved in HCC.
  • To classify HCC into distinct molecular subtypes based on RNA sequencing data.
  • To investigate the roles of identified genes in HCC pathogenesis and their correlation with methylation and copy number variations.

Main Methods:

  • Systematic clustering of HCC samples using The Cancer Genome Atlas (TCGA) RNA-seq data.
  • Identification and analysis of characteristic genes across different molecular subtypes.
  • Integration of methylation and SNP 6.0 chip data for comprehensive analysis.
  • Functional annotation and pathway analysis of differentially expressed genes.

Main Results:

  • 3843 differential genes were identified in HCC.
  • 689 genes were enriched in 13 KEGG pathways.
  • Correlations between gene expression, methylation levels (27 positive, 924 negative), and copy number variations (43 positive) were established.
  • ZSCAN18 methylation and ABHD6 were highlighted as potential prognostic and therapeutic targets, respectively.

Conclusions:

  • Systematic gene expression profiling enables novel molecular subtyping of HCC.
  • Specific genes, such as ZSCAN18 and ABHD6, hold potential as prognostic markers and therapeutic targets for HCC.
  • This comprehensive analysis provides insights into the molecular heterogeneity and pathways driving HCC development.