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Knockdown TNF family prognosis index crucial gene PDE4B promoted PANoptosis of ovarian carcinoma cell:Based in vitro and in vivo experiments

  • 0National Clinical Research Center for Laboratory Medicine, Department of Laboratory Medicine, The First Hospital of China Medical University, Units of Medical Laboratory , Chinese Academy of Medical Sciences, Shenyang, 110001, PR China.
Translational Oncology +

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April 17, 2025

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April 17, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study identifies 14 key genes for ovarian cancer prognosis using transcriptomic and single-cell data. These findings offer new insights for developing targeted ovarian cancer treatments.

Area Of Science

  • Oncology
  • Genomics
  • Bioinformatics

Background

  • Ovarian cancer has high incidence and mortality rates.
  • Understanding its molecular mechanisms is crucial for improving patient outcomes.

Purpose Of The Study

  • To elucidate the molecular mechanisms of ovarian cancer.
  • To identify key genes and pathways involved in ovarian cancer pathogenesis.
  • To develop a prognostic model for ovarian cancer.

Main Methods

  • Analysis of bulk transcriptomic and single-cell sequencing data.
  • Gene Set Variation Analysis (GSVA), Weighted Gene Co-expression Network Analysis (WGCNA), and Gene Ontology (GO) enrichment analysis.
  • Multivariable Cox regression and LASSO analyses for prognostic model construction.

Main Results

  • Identified crucial pathways in ovarian cancer pathogenesis.
  • Developed a 14-gene prognostic model (GFPT2, PDE4B, PODNL1, TGFBI, CSF1R, PTGIS, SFRP2, COL5A2, TRAC, SLAMF7, VCAN, GBP1P1, C2, TRBV28) with robust diagnostic and prognostic capabilities.
  • Explored gene expression patterns, immune cell infiltration, and drug sensitivity in single-cell data.

Conclusions

  • The 14-gene model provides a strong foundation for ovarian cancer prognosis.
  • The study offers novel insights for targeted treatment and drug development in ovarian cancer patients.

Keywords: