A practical guide for mutational signature analysis in hematological malignancies
Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data.
- 5 samples
- DAC: EGAC00001000000
- Technology: HiSeq X Ten
- PUB DUO:0000019 (version: 2021-02-23)publication requiredThis data use modifier indicates that requestor agrees to make results of studies using the data available to the larger scientific community.
- US DUO:0000026 (version: 2021-02-23)user specific restrictionThis data use modifier indicates that use is limited to use by approved users.
- IS DUO:0000028 (version: 2021-02-23)institution specific restrictionThis data use modifier indicates that use is limited to use within an approved institution.
- GRU DUO:0000042 (version: 2021-02-23)general research useThis data use permission indicates that use is allowed for general research use for any research purpose.
Wellcome Trust Sanger Institute Cancer Genome Group Data Sharing Policy
Studies are experimental investigations of a particular phenomenon, e.g., case-control studies on a particular trait or cancer research projects reporting matching cancer normal genomes from patients.
| Study ID | Study Title | Study Type |
|---|---|---|
| EGAS00001002274 | Cancer Genomics |
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