Detecting presence of mutational signatures in cancer with confidence

  title={Detecting presence of mutational signatures in cancer with confidence},
  author={Xiaoqing Huang and Damian W{\'o}jtowicz and Teresa M. Przytycka},
Cancers arise as the result of somatically acquired changes in the DNA of cancer cells. However, in addition to the mutations that confer a growth advantage, cancer genomes accumulate a large number of somatic mutations resulting from normal DNA damage and repair processes as well as mutations triggered by carcinogenic exposures or cancer related aberrations of DNA mainte-nance machinery. These mutagenic processes often produce characteristic mutational patterns called mutational signatures… 


A new descriptor of mutational signatures, DNA Repair FootPrint (RePrint), is introduced, and it is shown that it can capture common properties of deficiencies in repair mechanisms contributing to diverse signatures.

Computational tools to detect signatures of mutational processes in DNA from tumours: A review and empirical comparison of performance

An empirical study shows that the identification of signatures is more difficult for cancers characterized by multiple signatures each having a small contribution and suggests that detection methods based on probabilistic models, especially EMu and bayesNMF, have in general better performance than NMF-based methods.

Characteristics of mutational signatures of unknown etiology

Abstract Although not all somatic mutations are cancer drivers, their mutational signatures, i.e. the patterns of genomic alterations at a genome-wide scale, provide insights into past exposure to

A phylogenetic approach to study the evolution of somatic mutational processes in cancer

It is shown that the inference of branch-specific mutational signatures can be improved through a joint analysis of the collections of mutations mapped on proximal branches of the cancer cell phylogeny, which reduces the false-positive discovery rate of branches-specific signatures and can sometimes detect faint signatures.

Network-based approaches elucidate differences within APOBEC and clock-like signatures in breast cancer

This work investigated, for the first time, a network-level association of mutational signatures and dysregulated pathways and provides novel insights into mutagenic processes that the cancer genomes might have undergone and important clues for developing personalized drug therapies.

Computational tools to detect signatures of mutational processes in DNA from tumours: a review and empirical comparison of performance

An empirical evaluation study of all available packages to date for mutational signatures analysis, using both real and simulated data is carried on.

RepairSig: Deconvolution of DNA damage and repair contributions to the mutational landscape of cancer

RepairSig, a method that accounts for interactions between DNA damage and repair and is able to uncover unbiased signatures of deficient DNA repair processes, is presented, an important step towards biologically more realistic modeling of mutational processes in cancer.

Analysis of mutational signatures with yet another package for signature analysis

YAPSA allows to determine 95% confidence intervals for signature exposures, to perform constrained stratified signature analyses to obtain enrichment and depletion patterns of the identified signatures and, when applied to whole exome sequencing data, to correct for the triplet content of individual target capture kits.

Portrait of a cancer: mutational signature analyses for cancer diagnostics

The status of mutational signature analysis in cancer genomes is described and the opportunities and relevance, as well as future challenges, for further implementation of Mutational signatures in clinical tumor diagnostics and therapy guidance are discussed.

SigsPack, a package for cancer mutational signatures

SigsPack is presented, a Bioconductor package to estimate a sample’s exposure to mutational processes described by a set of mutational signatures, and provides functions to estimate stability of these exposures, using bootstrapping.



Signatures of mutational processes in human cancer

It is shown that hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types, and this results reveal the diversity of mutational processes underlying the development of cancer.

Mechanisms underlying mutational signatures in human cancers

Mutational signatures can be used as a physiological readout of the biological history of a cancer and also have potential use for discerning ongoing mutational processes from historical ones, thus possibly revealing new targets for anticancer therapies.

The topography of mutational processes in breast cancer genomes

Using somatic mutation catalogues from 560 breast cancer whole-genome sequences, it is shown that each of 12 base substitution, 2 insertion/deletion (indel) and 6 rearrangement mutational signatures present in breast tissue, exhibit distinct relationships with genomic features relating to transcription, DNA replication and chromatin organization.

Exploring background mutational processes to decipher cancer genetic heterogeneity

Abstract Much remains unknown about the progression and heterogeneity of mutational processes in different cancers and their diagnostic and clinical potential. A growing body of evidence supports

Mutational signatures: the patterns of somatic mutations hidden in cancer genomes

Landscape of somatic mutations in 560 breast cancer whole genome sequences

This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operative, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

Mutational signatures associated with tobacco smoking in human cancer

The results are consistent with the proposition that smoking increases cancer risk by increasing the somatic mutation load, although direct evidence for this mechanism is lacking in some smoking-related cancer types.