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TP53 mutations, expression and interaction networks in human cancers.

Xiaosheng Wang1, Qingrong Sun2

  • 1Department of Basic Medicine, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211198, China.

Oncotarget
|November 24, 2016
PubMed
Summary
This summary is machine-generated.

TP53 mutations are common in many cancers and linked to poor outcomes. This study analyzes TP53 networks and identifies potential therapeutic targets for TP53-mutated cancers.

Keywords:
TP53 expressionTP53 interaction networksTP53 mutationshuman cancerssynthetic lethality

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Area of Science:

  • Oncology
  • Genomics
  • Molecular Biology

Background:

  • TP53 mutations are frequent in human cancers.
  • Understanding TP53's role in oncogenesis and its interaction networks is crucial.
  • A systematic analysis across diverse cancer types is needed.

Purpose of the Study:

  • To systematically analyze TP53 mutations, gene expression, clinical outcomes, and interaction networks in 33 cancer types.
  • To identify genes regulated by p53 and those correlated with TP53 expression.
  • To discover synthetic lethal partners of TP53 for targeted therapy development.

Main Methods:

  • Utilized The Cancer Genome Atlas (TCGA) data for comprehensive analysis.
  • Examined TP53 mutation status, gene expression, and clinical data across 33 cancer types.
  • Performed survival analyses and leveraged the Cancer Cell Line Project for validation.

Main Results:

  • TP53 is the most frequently mutated gene in several cancers, often an early event.
  • Identified genes repressed by p53 and genes with expression correlating to TP53 levels.
  • TP53-truncating mutations typically decrease TP53 expression; non-truncating mutations can increase it.
  • TP53 mutations and elevated TP53 expression correlate with worse patient prognoses.
  • Identified and validated candidate synthetic lethal genes for TP53.

Conclusions:

  • TP53 mutations significantly impact cancer development and patient outcomes.
  • p53 interaction networks offer insights into cancer biology.
  • Candidate synthetic lethal genes represent promising therapeutic targets for TP53-mutated cancers.
  • This research supports the development of personalized therapies.