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Mutations01:39

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Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
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Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
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Spontaneous mutations arise infrequently during DNA replication due to errors in the process. A key factor behind these errors is tautomeric shifts in nitrogenous bases, where bases transition from keto to enol forms or amino to imino forms. This shift can alter base-pairing rules, leading to mutations. Additionally, reactive oxygen species (ROS) arising from aerobic metabolism can damage DNA, resulting in depurination (loss of a purine base) or depyrimidination (loss of a pyrimidine base).
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Related Experiment Video

Updated: Apr 25, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
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HapMuC: somatic mutation calling using heterozygous germ line variants near candidate mutations.

Naoto Usuyama1, Yuichi Shiraishi1, Yusuke Sato2

  • 1Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655 and Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.

Bioinformatics (Oxford, England)
|August 16, 2014
PubMed
Summary

HapMuC improves somatic mutation detection by using germ line variants for haplotype phasing. This novel Bayesian method enhances accuracy and outperforms existing callers in identifying low-allele-frequency mutations in cancer research.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Somatic mutation detection is crucial for cancer research.
  • Accurate identification of low-allele-frequency mutations in impure tumor samples remains challenging.
  • Existing methods do not leverage haplotype information for improved somatic mutation calling.

Purpose of the Study:

  • To develop a novel Bayesian hierarchical method (HapMuC) for somatic mutation detection.
  • To enhance the accuracy of somatic mutation calling by incorporating haplotype phasing information.
  • To improve the sensitivity and specificity of detecting low-allele-frequency somatic mutations.

Main Methods:

  • Developed HapMuC, a Bayesian hierarchical model incorporating heterozygous germ line variants.
  • Constructed generative mutation and error models.
  • Utilized variational Bayesian inference to infer haplotype frequencies and compute marginal likelihoods.
  • Derived a Bayes factor to evaluate the presence of somatic mutations.

Main Results:

  • HapMuC demonstrated superior specificity and sensitivity compared to existing methods.
  • Performance was validated using simulations, TCGA Mutation Calling Benchmark 4 datasets, and COLO-829 cell line data.
  • The method effectively leverages haplotype information to improve mutation detection power.

Conclusions:

  • HapMuC offers a significant advancement in somatic mutation calling by integrating haplotype information.
  • The method provides a more accurate and sensitive approach for identifying somatic point mutations in cancer genomics.
  • HapMuC is a valuable tool for cancer research, particularly for analyzing heterogeneous tumor samples.