Mutational signatures efficiently identify different mutational processes underlying cancers with similar somatic mutation spectra

2017 ◽  
Vol 806 ◽  
pp. 27-30 ◽  
Author(s):  
Nan Zhou ◽  
Yuan Yuan ◽  
Xin Long ◽  
Chuanfang Wu ◽  
Jinku Bao
Keyword(s):  
Somatic Mutation ◽  
Mutational Signatures ◽  
Mutation Spectra ◽  
Mutational Processes

scholarly journals Great ape mutation spectra vary across the phylogeny and the genome due to distinct mutational processes that evolve at different rates

2019 ◽  
Author(s):  
Michael E. Goldberg ◽  
Kelley Harris
Keyword(s):  
Replication Timing ◽  
Mutation Rates ◽  
Great Ape ◽  
Mutational Signatures ◽  
Clock Model ◽  
Cis Acting ◽  
Molecular Clock Model ◽  
Species Specific ◽  
Mutation Spectra ◽  
Mutational Processes

ABSTRACTRecent studies of hominoid variation have shown that mutation rates and spectra can evolve rapidly, contradicting the fixed molecular clock model. The relative mutation rates of three-base-pair motifs differ significantly among great ape species, suggesting the action of unknown modifiers of DNA replication fidelity. To illuminate the footprints of these hypothetical mutators, we measured mutation spectra of several functional compartments (such as late-replicating regions) that are likely targeted by localized mutational processes. Using genetic diversity from 88 great apes, we find that compartment-specific mutational signatures appear largely conserved between species. These signatures layer with species-specific signatures to create rich mutational portraits: for example, late-replicating regions in gorillas contain an identifiable mixture of a replication timing signature and a gorilla-specific signature. Our results suggest that cis-acting mutational modifiers are highly conserved between species and transacting modifiers are driving rapid mutation spectrum evolution.

scholarly journals Mutational signatures are jointly shaped by DNA damage and repair

2019 ◽  
Author(s):  
Nadezda V Volkova ◽  
Bettina Meier ◽  
Víctor González-Huici ◽  
Simone Bertolini ◽  
Santiago Gonzalez ◽  
...  
Keyword(s):  
Dna Damage ◽  
Dna Repair ◽  
Excision Repair ◽  
Dna Lesions ◽  
Single Nucleotide Variants ◽  
Mutational Signatures ◽  
Experimental Conditions ◽  
Repair Deficiency ◽  
Dna Repair Deficiency ◽  
Mutation Spectra

AbstractMutations arise when DNA lesions escape DNA repair. To delineate the contributions of DNA damage and DNA repair deficiency to mutagenesis we sequenced 2,717 genomes of wild-type and 53 DNA repair defective C. elegans strains propagated through several generations or exposed to 11 genotoxins at multiple doses. Combining genotoxin exposure and DNA repair deficiency alters mutation rates or leads to unexpected mutation spectra in nearly 40% of all experimental conditions involving 9/11 of genotoxins tested and 32/53 genotypes. For 8/11 genotoxins, signatures change in response to more than one DNA repair deficiency, indicating that multiple genes and pathways are involved in repairing DNA lesions induced by one genotoxin. For many genotoxins, the majority of observed single nucleotide variants results from error-prone translesion synthesis, rather than primary mutagenicity of altered nucleotides. Nucleotide excision repair mends the vast majority of genotoxic lesions, preventing up to 99% of mutations. Analogous mutagenic DNA damage-repair interactions can also be found in cancers, but, except for rare cases, effects are weak owing to the unknown histories of genotoxic exposures and DNA repair status. Overall, our data underscore that mutation spectra are joint products of DNA damage and DNA repair and imply that mutational signatures computationally derived from cancer genomes are more variable than currently anticipated.

scholarly journals Elevated somatic mutation burdens in normal human cells due to defective DNA polymerases

2020 ◽  
Author(s):  
Philip S. Robinson ◽  
Tim H.H. Coorens ◽  
Claire Palles ◽  
Emily Mitchell ◽  
Federico Abascal ◽  
...  
Keyword(s):  
Somatic Mutation ◽  
Normal Tissue ◽  
Familial Cancer ◽  
Dna Polymerases ◽  
Cell Types ◽  
Early Embryogenesis ◽  
High Fidelity ◽  
Mutational Signatures ◽  
Exonuclease Domain ◽  
Normal Human

ABSTRACTMutation accumulation over time in normal somatic cells contributes to cancer development and is proposed as a cause of ageing. DNA polymerases Pol ε and Pol δ replicate DNA with high fidelity during normal cell divisions. However, in some cancers defective proofreading due to acquired mutations in the exonuclease domains of POLE or POLD1 causes markedly elevated somatic mutation burdens with distinctive mutational signatures. POLE and POLD1 exonuclease domain mutations also cause familial cancer predisposition when inherited through the germline. Here, we sequenced normal tissue DNA from individuals with germline POLE or POLD1 exonuclease domain mutations. Increased mutation burdens with characteristic mutational signatures were found to varying extents in all normal adult somatic cell types examined, during early embryogenesis and in sperm. Mutation burdens were further markedly elevated in neoplasms from these individuals. Thus human physiology is able to tolerate ubiquitously elevated mutation burdens. Indeed, with the exception of early onset cancer, individuals with germline POLE and POLD1 exonuclease domain mutations are not reported to show abnormal phenotypic features, including those of premature ageing. The results, therefore, do not support a simple model in which all features of ageing are attributable to widespread cell malfunction directly resulting from somatic mutation burdens accrued during life.

scholarly journals Mutational signatures associated with tobacco smoking in human cancer

2016 ◽  
Author(s):  
Ludmil B. Alexandrov ◽  
Young Seok Ju ◽  
Kerstin Haase ◽  
Peter Van Loo ◽  
Iñigo Martincorena ◽  
...  
Keyword(s):  
Tobacco Smoke ◽  
Tobacco Smoking ◽  
Human Cancer ◽  
Mutational Signatures ◽  
Cytidine Deaminases ◽  
Endogenous Clock ◽  
Cancer Types ◽  
Tobacco Carcinogens ◽  
Mutational Processes ◽  
Mutational Process

ABSTRACTTobacco smoking increases the risk of at least 15 classes of cancer. We analyzed somatic mutations and DNA methylation in 5,243 cancers of types for which tobacco smoking confers an elevated risk. Smoking is associated with increased mutation burdens of multiple distinct mutational signatures, which contribute to different extents in different cancers. One of these signatures, mainly found in cancers derived from tissues directly exposed to tobacco smoke, is attributable to misreplication of DNA damage caused by tobacco carcinogens. Others likely reflect indirect activation of DNA editing by APOBEC cytidine deaminases and of an endogenous clock-like mutational process. 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.ONE SENTENCE SUMMARYMultiple distinct mutational processes associate with tobacco smoking in cancer reflecting direct and indirect effects of tobacco smoke.

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

2020 ◽  
Author(s):  
Damian Wojtowicz ◽  
Jan Hoinka ◽  
Bayarbaatar Amgalan ◽  
Yoo-Ah Kim ◽  
Teresa M. Przytycka
Keyword(s):  
Dna Damage ◽  
Dna Repair ◽  
Mutational Signatures ◽  
Dna Damage And Repair ◽  
Therapeutic Implications ◽  
Mutational Landscape ◽  
Repair Processes ◽  
Cancer Genomes ◽  
Current Paradigm ◽  
Mutational Processes

AbstractMany mutagenic processes leave characteristic imprints on cancer genomes known as mutational signatures. These signatures have been of recent interest regarding their applicability in studying processes shaping the mutational landscape of cancer. In particular, pinpointing the presence of altered DNA repair pathways can have important therapeutic implications. However, mutational signatures of DNA repair deficiencies are often hard to infer. This challenge emerges as a result of deficient DNA repair processes acting by modifying the outcome of other mutagens. Thus, they exhibit non-additive effects that are not depicted by the current paradigm for modeling mutational processes as independent signatures. To close this gap, we present RepairSig, a method that accounts for interactions between DNA damage and repair and is able to uncover unbiased signatures of deficient DNA repair processes. In particular, RepairSig was able to replace three MMR deficiency signatures previously proposed to be active in breast cancer, with just one signature strikingly similar to the experimentally derived signature. As the first method to model interactions between mutagenic processes, RepairSig is an important step towards biologically more realistic modeling of mutational processes in cancer. The source code for RepairSig is publicly available at https://github.com/ncbi/RepairSig.

scholarly journals The mutational landscape of human somatic and germline cells

2020 ◽  
Author(s):  
Luiza Moore ◽  
Alex Cagan ◽  
Tim H.H. Coorens ◽  
Matthew D.C. Neville ◽  
Rashesh Sanghvi ◽  
...  
Keyword(s):  
Human Population ◽  
Cell Types ◽  
Mutational Signatures ◽  
Division Rate ◽  
Anatomical Structures ◽  
Mutational Landscape ◽  
Cell Division Rate ◽  
Normal Human ◽  
Multiple Samples ◽  
Mutational Processes

AbstractDuring the course of a lifetime normal human cells accumulate mutations. Here, using multiple samples from the same individuals we compared the mutational landscape in 29 anatomical structures from soma and the germline. Two ubiquitous mutational signatures, SBS1 and SBS5/40, accounted for the majority of acquired mutations in most cell types but their absolute and relative contributions varied substantially. SBS18, potentially reflecting oxidative damage, and several additional signatures attributed to exogenous and endogenous exposures contributed mutations to subsets of cell types. The mutation rate was lowest in spermatogonia, the stem cell from which sperm are generated and from which most genetic variation in the human population is thought to originate. This was due to low rates of ubiquitous mutation processes and may be partially attributable to a low cell division rate of basal spermatogonia. The results provide important insights into how mutational processes affect the soma and germline.

scholarly journals Mutational signature learning with supervised negative binomial non-negative matrix factorization

2020 ◽  
Vol 36 (Supplement_1) ◽  
pp. i154-i160 ◽  
Author(s):  
Xinrui Lyu ◽  
Jean Garret ◽  
Gunnar Rätsch ◽  
Kjong-Van Lehmann
Keyword(s):  
Matrix Factorization ◽  
Negative Binomial ◽  
Extraction Methods ◽  
Supplementary Information ◽  
Cancer Type ◽  
Mutational Signatures ◽  
Signature Extraction ◽  
Mutational Signature ◽  
Mutational Processes ◽  
Non Negative Matrix Factorization

Abstract Motivation Understanding the underlying mutational processes of cancer patients has been a long-standing goal in the community and promises to provide new insights that could improve cancer diagnoses and treatments. Mutational signatures are summaries of the mutational processes, and improving the derivation of mutational signatures can yield new discoveries previously obscured by technical and biological confounders. Results from existing mutational signature extraction methods depend on the size of available patient cohort and solely focus on the analysis of mutation count data without considering the exploitation of metadata. Results Here we present a supervised method that utilizes cancer type as metadata to extract more distinctive signatures. More specifically, we use a negative binomial non-negative matrix factorization and add a support vector machine loss. We show that mutational signatures extracted by our proposed method have a lower reconstruction error and are designed to be more predictive of cancer type than those generated by unsupervised methods. This design reduces the need for elaborate post-processing strategies in order to recover most of the known signatures unlike the existing unsupervised signature extraction methods. Signatures extracted by a supervised model used in conjunction with cancer-type labels are also more robust, especially when using small and potentially cancer-type limited patient cohorts. Finally, we adapted our model such that molecular features can be utilized to derive an according mutational signature. We used APOBEC expression and MUTYH mutation status to demonstrate the possibilities that arise from this ability. We conclude that our method, which exploits available metadata, improves the quality of mutational signatures as well as helps derive more interpretable representations. Availability and implementation https://github.com/ratschlab/SNBNMF-mutsig-public. Supplementary information Supplementary data are available at Bioinformatics online.

Identification, incidence and clinical outcomes of patients (pts) with hypermutated prostate cancer (PC).

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 5072-5072
Author(s):  
Simon Yuen Fai Fu ◽  
Elie Ritch ◽  
Cameron Herberts ◽  
Steven Yip ◽  
Daniel Khalaf ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Median Time ◽  
Somatic Mutation ◽  
Clinical Data ◽  
Castration Resistant Prostate Cancer ◽  
Control Cohort ◽  
Mutational Signatures ◽  
Whole Exome ◽  
Mutation Burden ◽  
Homozygous Deletions

5072 Background: A small proportion of metastatic PC exhibit outlier somatic mutation (mut) rates exceeding the average of 4.4 mut/Mb. The incidence, clinical course and treatment response of pts with hypermutation (HM) is poorly characterised. Methods: We performed targeted sequencing from a panel of PC genes using plasma cell-free DNA samples collected from metastatic castration-resistant prostate cancer (mCRPC) pts and calculated somatic mutation burden. HM samples were additionally subjected to whole exome sequencing to determine trinucleotide mutational signatures and microsatellite instability (MSI). Clinical data was retrospectively collected and compared to a control cohort of 199 mCRPC pts. Results: 671 samples from 434 pts had ctDNA > 2% and were evaluable. 32 samples from 24 pts had > 11 mut/Mb and fell above the 95th percentile for mutation burden with a median mutation burden of 34 mut/Mb. 11 pts had deleterious mutations or homozygous deletions in mismatch repair (MMR) genes and 4 further pts had evidence of MMR deficiency (MMRd) from mutational signatures and MSI status. The remaining 9 pts had either BRCA2 mutations (n = 4), Kataegis (localized hypermutation, n = 3), or undefined causes for HM (n = 2). The incidence of MMRd was 3.5% (15/434), and germline MMRd was 0.2% (1/434). For MMRd pts with available clinical data (10/15) at diagnosis, the median age was 73.6 y, 70% had Gleason score ≥8, and 50% presented with M1 disease. Comparing the MMRd with the control cohort, median time from ADT to CRPC was 9.1 m (95% CI 6.9–11.4) vs. 18.2 m (95% CI 15.1–21.3), p = 0.001; median time from CRPC to death was 13.1 m (95% CI 0.3–25.9) vs. 40.1 m (95% CI 32.4–47.8), p < 0.001. Conclusions: HM and MMRd can be identified using liquid biopsy and could help to select pts for immunotherapy.

Mutational signatures and heterogeneous host response revealed via large-scale characterization of SARS-CoV-2 genomic diversity

2020 ◽  
Author(s):  
Alex Graudenzi ◽  
Davide Maspero ◽  
Fabrizio Angaroni ◽  
Rocco Piazza ◽  
Daniele Ramazzotti
Keyword(s):  
Large Scale ◽  
Purifying Selection ◽  
Genomic Diversity ◽  
Nucleotide Substitutions ◽  
Mutational Signatures ◽  
Mutational Hotspots ◽  
Scale Characterization ◽  
Definition Of ◽  
Mutational Processes

AbstractTo dissect the mechanisms underlying the inflation of variants in the SARS-CoV-2 genome, we present one of the largest up-to-date analyses of intra-host genomic diversity, which reveals that most samples present heterogeneous genomic architectures, due to the interplay between host-related mutational processes and transmission dynamics.The deconvolution of the set of intra-host minor variants unveils the existence of non overlapping mutational signatures related to specific nucleotide substitutions, which prove that distinct hosts respond differently to SARS-CoV-2 infections, and which are likely ruled by APOBEC, Reactive Oxygen Species (ROS) and ADAR.Thanks to a corrected-for-signatures dN/dS analysis we demonstrate that the mutational processes underlying such signatures are affected by purifying selection, with important exceptions. In fact, several mutations linked to low-rate mutational processes appear to transit to clonality in the population, eventually leading to the definition of new clonal genotypes and to a statistically significant increase of overall genomic diversity.Importantly, the analysis of the phylogenetic model shows the presence of multiple homoplasies, due to mutational hotspots, phantom mutations or positive selection, and supports the hypothesis of transmission of minor variants during infections. Overall, the results of this study pave the way for the integrated characterization of intra-host genomic diversity and clinical outcome of SARS-CoV-2 hosts.

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