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MutationAssessor in cBioPortal.

Yang Su1, Xiang Li2, Boris Reva3

  • 1Department of Systems Biology, Harvard Medical School, Boston, MA, USA.

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|August 20, 2025
PubMed
Summary
This summary is machine-generated.

MutationAssessor (MA) version 4 refines functional impact scoring for cancer mutations. It enhances analysis of protein conservation and variant pathogenicity, aiding cancer genomics research.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Somatic and germline mutations in cancer require functional impact assessment.
  • MutationAssessor (MA) provides an evolution-based functional impact score (FIS) for mutations.
  • FIS scores leverage conservation patterns in protein families and subfamilies.

Purpose of the Study:

  • To introduce version 4 (r4) of MutationAssessor with significant improvements.
  • To refine the analysis of protein conservation patterns and sequence alignments.
  • To validate predicted functional impacts against curated variant databases and germline frequencies.

Main Methods:

  • Refined combinatorial entropy analysis of conservation patterns.
  • Recalculated full-length protein multiple sequence alignments using extensive sequence data.
  • Comparison of predicted functional impact with ClinVar classifications.
  • Analysis of variant frequency in germline genome sequences.
  • Exploration of switch-of-function mutational effects.

Main Results:

  • Enhanced accuracy in predicting the functional impact of cancer mutations.
  • Validation of FIS scores against known pathogenic and benign variants.
  • Observed inverse correlation between high functional impact and germline variant frequency.
  • Availability of functional impact data for ~4 million somatic mutations in cBioPortal.

Conclusions:

  • MutationAssessor r4 offers a robust tool for evaluating the functional consequences of cancer mutations.
  • The updated FIS provides valuable insights into mutation pathogenicity and evolutionary conservation.
  • The integration of MA data into cBioPortal facilitates cancer genomics research and clinical interpretation.