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Cancers Originate from Somatic Mutations in a Single Cell02:21

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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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Related Experiment Video

Updated: Mar 22, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
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A somatic reference standard for cancer genome sequencing.

David W Craig1, Sara Nasser1, Richard Corbett2

  • 1Translational Genomics Research Institute, Phoenix, Arizona, USA.

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|April 21, 2016
PubMed
Summary

This study introduces a new reference standard for cancer somatic variant detection using whole genome sequencing. This standard enables accurate calibration of next-generation sequencing analysis tools across different institutions.

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Area of Science:

  • Genomics
  • Cancer Research
  • Bioinformatics

Background:

  • Next-generation sequencing (NGS) enables large-scale identification of somatic alterations in cancer.
  • Calibration of NGS somatic analysis tools is limited by the absence of reliable tumor/normal reference standards.

Purpose of the Study:

  • To establish a reference standard for evaluating and calibrating next-generation sequencing somatic variant detection pipelines.
  • To provide a benchmark for quantitative comparison of somatic mutation analysis across institutions.

Main Methods:

  • Paired, PCR-free whole genome sequencing of a matched metastatic melanoma cell line (COLO829) and normal sample.
  • Sequencing performed across three independent institutions with separate library preparations, sequencing runs, and analyses.
  • Data combined with previously generated data for comparison with earlier NGS technology.

Main Results:

  • High-coverage sequencing (mean 99X for tumor, 103X for normal) generated a comprehensive dataset.
  • Identification of consensus variants including hallmark mutations (e.g., BRAF V600E, PTEN deletion, TERT promoter substitution).
  • Characterization of common events: >35,000 point mutations, 446 small insertions/deletions, and >6,000 genes affected by copy number changes.

Conclusions:

  • The generated reference dataset serves as an initial standard for the scientific community.
  • Enables quantitative evaluation and improvement of somatic mutation detection pipelines.
  • Facilitates cross-institutional validation and standardization of cancer genomic analyses.