Accurate and sensitive mutational signature analysis with MuSiCal

Area of Science:

• Genomics
• Computational Biology
• Cancer Research

Background:

• Mutational signature analysis is a computational method to interpret somatic mutations.
• It aids understanding of cancer development and informs treatment but faces methodological challenges.
• These challenges hinder broader clinical applications of mutational signatures.

Purpose of the Study:

• To present the Mutational Signature Calculator (MuSiCal), an analytical framework designed to address key challenges in mutational signature analysis.
• To improve the discovery and assignment of mutational signatures in cancer genomes.
• To provide an updated catalog of mutational signatures and identify novel ones.

Main Methods:

• Development of a rigorous analytical framework with novel algorithms for signature discovery and assignment.
• Simulation studies to compare MuSiCal's performance against state-of-the-art algorithms.
• Reanalysis of over 2,700 cancer genomes using the MuSiCal framework.

Main Results:

• MuSiCal demonstrated superior performance in both signature discovery and assignment compared to existing algorithms in simulation studies.
• Reanalysis of cancer genomes yielded an improved catalog of signatures and their assignments.
• Nine novel indel signatures were discovered, and ambiguities in 'flat' signatures were resolved.

Conclusions:

• MuSiCal offers a robust solution to major problems in the standard mutational signature analysis workflow.
• The improved catalog and discovered signatures advance our understanding of cancer etiology.
• MuSiCal is expected to contribute to establishing best practices for mutational signature analysis in clinical settings.