deconstructSigs: delineating mutational processes in single tumors distinguishes DNA repair deficiencies and patterns of carcinoma evolution

By R. Rosenthal, Nicholas McGranahan, Javier Herrero, Barry S. Taylor, Charles Swanton. Genome Biology, 2016

1,016 citations recorded by the source corpus.

Analysis of somatic mutations provides insight into the mutational processes that have shaped the cancer genome, but such analysis currently requires large cohorts. We develop deconstructSigs, which allows the identification of mutational signatures within a single tumor sample. Application of deconstructSigs identifies samples with DNA repair deficiencies and reveals distinct and dynamic mutational processes molding the cancer genome in esophageal adenocarcinoma compared to squamous cell carcinomas. deconstructSigs confers the ability to define mutational processes driven by environmental exposures, DNA repair abnormalities, and mutagenic processes in individual tumors with implications for precision cancer medicine.

Subfields: Cancer Research, Molecular Biology, Pathology and Forensic Medicine

View Paper: https://www.semanticscholar.org/paper/93900e53dad2d380b7b7363b127b053bc319a260

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Citations in the corpus

Comprehensive Analysis of Hypermutation in Human Cancer (2017, neutral): “…GTTACGGCAGG-50 This Paper N/A Software and Algorithms R 3.3.3 The R Foundation https://www.r-project.org/ deconstructSigs Rosenthal et al., 2016 https://github.com/raerose01/deconstructSigs ggplot2 The R Foundation…”
Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab (2017, neutral): “8.0 Rosenthal et al., 2016; PMID: 26899170 https://www.rdocumentation.org/packages/ deconstructSigs/versions/1.8.0 DESeq2 v1.”
Genomic Hallmarks and Structural Variation in Metastatic Prostate Cancer. (2018, positive): “Evaluation of COSMIC mutation signatures was performed using the deconstructSigs package (Rosenthal et al., 2016), using the BSgenome.”
Allele-Specific HLA Loss and Immune Escape in Lung Cancer Evolution (2017, background): “To address whether a particular mutational process contributes to the subclonal mutational burden present in tumors with HLA LOH, we interrogated the mutational signatures present in each tumor (Alexandrov et al., 2013; Rosenthal et al., 2016).”
Pan-tumor genomic biomarkers for PD-1 checkpoint blockade–based immunotherapy (2018, neutral): “0) in R that selects the combination of knownmutational signatures that can account for the observedmutational profile in each sample (53).”
Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition (2021, positive): “DeconstructSigs (Rosenthal et al., 2016) was used to derive COSMIC mutational signatures (v2) (Alexandrov et al., 2015) for each tumor samples withR 50 somatic mutations (n = 872 patients).”
Clonal Heterogeneity and Tumor Evolution: Past, Present, and the Future. (2017, neutral): “squamous carcinoma and esophageal adenocarcinomas (de Bruin et al., 2014; McGranahan et al., 2015; Rosenthal et al., 2016).”
Maftools: efficient and comprehensive analysis of somatic variants in cancer (2018, methodology): “Several tools such as EmU and deconstructSigs offer statistical frameworks to identify de novo signatures and enrichment of known signatures (Fischer et al. 2013; Rosenthal et al. 2016).”
Immune Cell Abundance and T-cell Receptor Landscapes Suggest New Patient Stratification Strategies in Head and Neck Squamous Cell Carcinoma (2023, methodology): “Mutational signatures were inferred using deconstructSigs (22), based on the single base substitution (SBS) patterns reported in the COSMIC database (v3—”