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Updated: Feb 25, 2026

Comparative Lesions Analysis Through a Targeted Sequencing Approach
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Published on: November 5, 2019

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Variation in organ-specific PIK3CA and KRAS mutant levels in normal human tissues correlates with mutation prevalence

Barbara L Parsons1, Karen L McKim1, Meagan B Myers1

  • 1Division of Genetic and Molecular Toxicology, U.S. Food and Drug Administration, National Center for Toxicological Research, Jefferson, Arkansas.

Environmental and Molecular Mutagenesis
|July 30, 2017
PubMed

Insights

Interindividual variability in normal tissue mutations correlates with cancer prevalence, suggesting a metric for early carcinogenesis and potential prophylactic therapies. This study quantifies hotspot cancer driver mutations (CDMs) in various tissues.

Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Large-scale sequencing reveals cancer mutation complexity.
  • Allele-specific competitive blocker PCR (ACB-PCR) quantifies hotspot cancer driver mutations (CDMs).
  • Understanding CDMs in normal and cancerous tissues is crucial for cancer research.

Purpose of the Study:

  • To quantify PIK3CA and KRAS mutant fractions (MFs) in various normal and cancerous tissues.
  • To investigate the relationship between MF variability in normal tissues and cancer mutation frequencies.
  • To explore the implications for identifying early carcinogenesis drivers and developing prophylactic therapies.

Main Methods:

  • Utilized allele-specific competitive blocker PCR (ACB-PCR) for sensitive quantification of mutant fractions.
  • Measured PIK3CA H1047R, PIK3CA E545K, KRAS G12D, and KRAS G12V MFs in normal colonic mucosa, lung, breast, thyroid, colonic adenomas, adenocarcinomas, lung adenocarcinomas, and mammary ductal carcinomas.
  • Integrated new data with existing ACB-PCR data for comprehensive analysis.

Main Results:

  • Reported MF measurements for key PIK3CA and KRAS mutations across multiple tissue types.
  • Revealed a correlation between interindividual variability of mutations in normal tissues and their detection frequency in corresponding carcinomas (COSMIC database).
  • Demonstrated that normal tissue mutation variability may serve as a metric for identifying early carcinogenesis drivers.

Conclusions:

  • Interindividual variability in normal tissue mutations can predict mutations critical for tissue-specific carcinogenesis.
  • Personalized cancer therapeutics targeting oncogenic products may be repurposed for cancer risk reduction.
  • This approach offers novel insights into early cancer development and prevention strategies.
Keywords:
biomarkercancer susceptibilityclonal selectionpersonalized medicinetumor heterogeneity

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