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Related Experiment Video

Updated: Oct 14, 2025

Characterizing Mutational Load and Clonal Composition of Human Blood

Characterizing Mutational Load and Clonal Composition of Human Blood

Published on: July 11, 2019

Clone decomposition based on mutation signatures provides novel insights into mutational processes.

Taro Matsutani¹, Michiaki Hamada¹

¹Graduate School of Advanced Science and Engineering, Waseda University, 55N-06-10, 3-4-1, Okubo Shinjuku-ku, Tokyo 169-8555, Japan.

NAR Genomics and Bioinformatics

|November 4, 2021

Summary

We introduce SigTracer, a new Bayesian method to analyze intra-tumor heterogeneity and cancer genome evolution. SigTracer improves clone decomposition and provides insights into mutation signatures and their origins.

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Last Updated: Oct 14, 2025

Characterizing Mutational Load and Clonal Composition of Human Blood

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Published on: July 11, 2019

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

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Published on: February 3, 2023

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

Area of Science:

Genomics
Bioinformatics
Cancer Research

Background:

Intra-tumor heterogeneity, where mutation profiles vary within a tumor, is prevalent in cancers.
Understanding this heterogeneity is crucial for clinical applications.
Existing methods for predicting heterogeneity, like CloneSig, have limitations in clone number selection and modeling.

Purpose of the Study:

To develop a novel method, SigTracer, for analyzing intra-tumor heterogeneity.
To address limitations in existing clone decomposition and modeling techniques.
To provide more accurate insights into mutational processes and signature origins.

Main Methods:

SigTracer employs a hierarchical Bayesian approach.
It simultaneously models variant allele frequency and mutation signatures.
The method is validated against artificial cancer genome data.

Main Results:

SigTracer demonstrates more accurate clone decompositions compared to existing methods.
Application to blood cancer whole-genome sequences revealed insights into mutation signatures.
Specifically, it confirmed SBS9 signature enrichment in immunoglobulin regions for chronic lymphocytic leukemia and identified its role in mutating cell-cell adhesion regions.

Conclusions:

SigTracer offers a robust approach to analyzing intra-tumor heterogeneity.
The method enhances our understanding of mutation signature origins and their impact on cancer genomes.
Accurate mutation assignment by SigTracer can reveal novel biological insights into mutational processes.