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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...

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).

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...

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...

Random Error

Random Error

Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...

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Using X-ray Crystallography, Biophysics, and Functional Assays to Determine the Mechanisms Governing T-cell Receptor Recognition of Cancer Antigens

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GenBlosum: On Determining Whether Cancer Mutations Are Functional or Random.

Alejandro Leyva¹, Muhammad Khalid Khan Niazi²

¹Department of Biomedical Engineering, The Ohio State University, 2255 Kenny Rd., Colombus, OH 43210, USA.

|January 28, 2026

Summary

This summary is machine-generated.

This study introduces codon-aware neutral modeling to differentiate cancer-driving mutations from random genetic changes. The new method helps interpret genetic variants of unknown significance by analyzing evolutionary patterns in TP53 and PIK3CA mutations.

Keywords:

BLOSUM Monte Carlo simulation PIK3CA TP53 cancer genomics codon-aware model neutral evolution somatic mutation

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A Method for Screening and Validation of Resistant Mutations Against Kinase Inhibitors

A Method for Screening and Validation of Resistant Mutations Against Kinase Inhibitors

Published on: December 7, 2014

Area of Science:

Genomics
Cancer Biology
Evolutionary Genetics

Background:

Genetic mutations are central to cancer development.
Current methods for analyzing mutations, like WXS sequencing and BLOSUM scoring, do not fully account for base pair changes or contextualize mutations within neutral evolutionary processes.
Interpreting variants of unknown significance in clinical settings is challenging due to the difficulty in distinguishing oncogenic selection from random mutational degradation.

Purpose of the Study:

To develop and validate a novel model that integrates evolutionary conservation with base pair change probabilities.
To assess the deviation of observed mutations from codon-aware neutral expectations.
To improve the interpretation of genetic variants in cancer by distinguishing between selection and stochastic processes.

Main Methods:

Analysis of mutation sequences from the TCGA BRCA cohort, focusing on TP53 and PIK3CA genes.
Development of a model combining BLOSUM scoring with statistical modeling of base pair changes.
Comparison of observed mutational distributions against a neutral model to determine statistical significance using chi-square testing.

Main Results:

TP53 mutations in the TCGA BRCA cohort showed significantly more radical evolutionary changes than predicted by the codon-aware neutral model.
PIK3CA mutations exhibited significantly more conservative evolutionary patterns compared to neutral expectations.
These opposing patterns align with the distinct roles of TP53 (tumor suppressor) and PIK3CA (oncogene) in cancer, reflecting selection pressures.

Conclusions:

Codon-aware neutral modeling offers a statistical framework to identify mutations diverging from stochastic expectations.
This approach can assist in interpreting variants of unknown significance by contextualizing mutational severity.
The model provides insights into tumor evolution and may aid in prognostic assessment without requiring pre-established gene-level neutrality assumptions.