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Related Concept Videos

Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
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Related Experiment Video

Updated: May 13, 2025

Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
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A gene signature associated with cellular senescence serves as an important prognostic indicator in hepatocellular

Yongfeng Yan1, Kai Chen1, Qian Sun1

  • 1Department of Laboratory, Tianjin Beichen Hospital, Tianjin, China.

Translational Cancer Research
|April 14, 2025
PubMed
Summary

This study developed a prognostic model for hepatocellular carcinoma (HCC) using cellular senescence-related genes. This model may aid in predicting HCC patient outcomes and developing targeted therapies.

Keywords:
Hepatocellular carcinoma (HCC)biomarkerscellular senescencecellular senescence-related signature

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Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Hepatocellular carcinoma (HCC) is a lethal malignancy with challenging prognosis prediction.
  • Cellular senescence, a key hallmark of cancer, offers potential for developing prognostic gene signatures.
  • Investigating the role of cellular senescence is crucial for advancing HCC clinical decision-making.

Purpose of the Study:

  • To investigate the role of cellular senescence in hepatocellular carcinoma (HCC).
  • To establish a prognostic model for HCC based on cellular senescence-related gene expression.
  • To identify potential therapeutic targets for HCC.

Main Methods:

  • Utilized RNA sequencing data and clinical information from The Cancer Genome Atlas (TCGA) HCC database.
  • Stratified HCC patients into low- and high-risk groups based on senescence-related genes.
  • Developed a senescence score model and analyzed gene expression pathways (KEGG) and immune cell populations.

Main Results:

  • Identified significant correlations between HCC subtypes (C1) and clinical factors (age, sex, TNM stage, grade).
  • Upregulated genes in high-risk C1 HCC were linked to cell cycle, DNA replication, and senescence pathways.
  • Downregulated genes were associated with metabolic pathways, chemical carcinogenesis, and PPAR signaling; distinct immune cell profiles were observed between C1 and C2 HCC samples.
  • A prognostic gene model including VDAC2, CXCL8, MYBL2, RAD9A, LIN52, RHEB, GADD45G, E2F5, MAP2K2, CDC25A, PPP1CB, and HRAS was developed.

Conclusions:

  • Established a novel prognostic model for HCC utilizing cellular senescence-related gene expression.
  • The findings offer insights for developing innovative targeted therapies for HCC.
  • The study highlights the significance of cellular senescence in HCC progression and prognosis.