Interaction effect of PTEN and CDKN1B chromosomal regions on prostate cancer linkage

Jianfeng Xu1, Carl D Langefeld, S Lilly Zheng

  • 1Center for Human Genomics, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA. jxu@wfubmc.edu

Human Genetics
|June 9, 2004
PubMed

Insights

Interactions between PTEN and CDKN1B genes significantly increase prostate cancer risk in hereditary cancer families. This study highlights the importance of analyzing gene interactions for complex disease susceptibility.

Area of Science:

  • Genetics
  • Oncology
  • Molecular Biology

Background:

  • PTEN (Phosphatase and tensin homolog) and CDKN1B (Cyclin-dependent kinase inhibitor 1B) are known tumor suppressors.
  • Mouse models indicate combined PTEN and CDKN1B action has stronger tumor suppressor function, with heterozygous knockouts leading to 100% prostate cancer penetrance.

Purpose of the Study:

  • To investigate if epistatic interactions between PTEN and CDKN1B contribute to increased prostate cancer risk in humans.
  • To analyze linkage and interaction effects in high-risk hereditary prostate cancer families.

Main Methods:

  • Epistatic PTEN and CDKN1B interaction analyses were performed in 188 high-risk hereditary prostate cancer families.
  • Nonparametric linkage (NPL) regression and ordered subset analysis (OSA) were employed to model allele sharing and interaction effects.
  • Fine-mapping markers in PTEN (10q23) and CDKN1B (12p13) regions were utilized.

Main Results:

  • Significant evidence of epistatic interaction between PTEN and CDKN1B was observed at chromosomal regions 10q23-24 and 12p11-13.
  • NPL regression analysis showed a P-value of 0.0002 for the interaction effect across all families.
  • OSA revealed significant LOD-delta scores (3.15 at 10q23-24 and 2.63 at 12p11-13) in specific family subsets.

Conclusions:

  • The findings support epistatic interactions between PTEN and CDKN1B in influencing prostate cancer risk.
  • Modeling epistatic effects in linkage analysis is a valuable approach for detecting susceptibility genes in complex diseases.

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