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Cancers Originate from Somatic Mutations in a Single Cell

Cancers Originate from Somatic Mutations in a Single Cell

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...

Mutations

Mutations

Mutations

Mutations

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.
Chromosomal Alterations Are Large-Scale Mutations
While point mutations are changes in a single nucleotide in...

Somatic to iPS Cell Reprogramming

Somatic to iPS Cell Reprogramming

Reprogramming alters the gene expression in somatic cells, transforming them into induced pluripotent stem (iPS) cells over several generations. Scientists can reprogram cells by introducing genes for four transcription factors—Oct4, Sox2, Klf4, and c-Myc (OSKM) by viral or non-viral methods. These factors are also known as Yamanaka factors after Shinya Yamanaka, who first generated iPS cells using mouse skin cells. Yamanaka was awarded the Nobel Prize in Physiology or Medicine in 2012...

Viral Mutations

Viral Mutations

A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...

Mutation, Gene Flow, and Genetic Drift

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).

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Related Experiment Video

Updated: Feb 11, 2026

Author Spotlight: Advancing the Detection of Low-Frequency Mutations in Cancer Tissues

Author Spotlight: Advancing the Detection of Low-Frequency Mutations in Cancer Tissues

Published on: August 23, 2024

Detecting Somatic Mutations in Normal Cells.

Yanmei Dou¹, Heather D Gold², Lovelace J Luquette²

¹Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Equal contributions.

Trends in Genetics : TIG

|May 8, 2018

Summary

This summary is machine-generated.

Detecting somatic mutations in non-tumor cells using high-throughput sequencing offers insights into normal cell processes and age-related diseases. This analysis aids in understanding mutational impacts beyond cancer.

Keywords:

cell lineage linked reads mosaicism phasing single-nucleotide variants

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Wild-type Blocking PCR Combined with Direct Sequencing as a Highly Sensitive Method for Detection of Low-Frequency Somatic Mutations

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Quantification of Colonic Stem Cell Mutations

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Last Updated: Feb 11, 2026

Author Spotlight: Advancing the Detection of Low-Frequency Mutations in Cancer Tissues

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Published on: August 23, 2024

Wild-type Blocking PCR Combined with Direct Sequencing as a Highly Sensitive Method for Detection of Low-Frequency Somatic Mutations

Wild-type Blocking PCR Combined with Direct Sequencing as a Highly Sensitive Method for Detection of Low-Frequency Somatic Mutations

Published on: March 29, 2017

Quantification of Colonic Stem Cell Mutations

Quantification of Colonic Stem Cell Mutations

Published on: September 25, 2015

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Somatic mutations are well-studied in cancer.
High-throughput sequencing now enables somatic mutation detection in non-tumor cells.
Understanding these mutations is key to normal cell biology and disease.

Purpose of the Study:

To describe methods for characterizing somatic mutations in normal and non-tumor disease tissues.
To discuss experimental designs and common pitfalls in somatic mutation detection.
To highlight recent advancements like phasing and linked-read technology.

Main Methods:

Utilizing high-throughput sequencing data.
Applying bioinformatic analysis pipelines.
Exploring experimental designs for somatic mutation characterization.

Main Results:

Somatic mutation analysis provides insights into mutational processes in normal cells.
This analysis aids in exploring developmental cell lineages.
Potential associations with age-related diseases can be examined.

Conclusions:

Bioinformatic analysis of genome sequencing data is crucial for characterizing somatic mutations.
These mutations have significant impacts on non-cancer tissues.
Further research will illuminate the role of somatic mutations in health and disease.