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Related Experiment Video

Updated: Mar 8, 2026

Mass Cytometry Analysis of Systemic and Local Immune Responses in Hepatocellular Carcinoma
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A transcriptome profile in hepatocellular carcinomas based on integrated analysis of microarray studies.

Feifei Wang1, Ruliang Wang1, Qiuwen Li1

  • 1Department of Oncology, The First Affiliated Hospital of PLA General Hospital, Fucheng Road 51, Beijing, 100048, China.

Diagnostic Pathology
|January 15, 2017
PubMed
Summary

Developing new biomarkers for hepatocellular carcinoma (HCC) is crucial due to poor survival rates. This study identified potential diagnostic and prognostic biomarkers, including ASPM, CCT3, and NEK2, through integrated gene expression analysis.

Keywords:
Differentially expressed geneExpression profileHepatocellular cancerIntegrated analysisReal time polymerase chain reactionTCGA validation

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Area of Science:

  • Oncology
  • Bioinformatics
  • Genomics

Background:

  • Hepatocellular carcinoma (HCC) has a poor 5-year survival rate (50-70%) despite new treatments.
  • Lack of early diagnostic biomarkers contributes to late detection and poor outcomes.
  • Urgent need for novel biomarkers for early HCC diagnosis to reduce mortality.

Purpose of the Study:

  • To identify novel biomarkers for early diagnosis of hepatocellular carcinoma (HCC).
  • To analyze gene expression data comprehensively for HCC.
  • To explore potential therapeutic targets for HCC.

Main Methods:

  • Integrated analysis of seven HCC gene expression datasets using bioinformatics.
  • Validation of findings using real-time polymerase chain reaction (RT-PCR).
  • Confirmation of results with The Cancer Genome Atlas (TCGA) database.

Main Results:

  • Identified 1167 differentially expressed genes (DEGs) in HCC.
  • DEGs are primarily involved in cell cycle, oocyte meiosis, and maturation.
  • ASPM, CCT3, and NEK2 showed significant association with overall survival in HCC patients (TCGA data).

Conclusions:

  • Integrated analysis effectively reduces microarray heterogeneity for accurate HCC transcriptome profiling.
  • Identified potential biomarkers (ASPM, CCT3, NEK2) for HCC diagnosis and prognosis.
  • These biomarkers may serve as potential therapeutic targets for HCC.