scholarly journals Somatic Mutations Render Human Exome and Pathogen DNA more Similar

2018 ◽  
Author(s):  
Ehsan Ebrahimzadeh ◽  
Maggie Engler ◽  
David Tse ◽  
Razvan Cristescu ◽  
Aslan Tchamkerten

AbstractImmunotherapy has recently shown important clinical successes in a substantial number of oncology indications. Additionally, the tumor somatic mutation load has been shown to associate with response to these therapeutic agents, and specific mutational signatures are hypothesized to improve this association, including signatures related to pathogen insults. We sought to study in silico the validity of these observations and addressed three questions. First, we investigated whether somatic mutations typically involved in cancer may increase, in a statistically meaningful manner, the similarity between common pathogens and the human exome. Our study shows that specific common mutagenic processes like those resulting from exposure to ultraviolet light (in melanoma) or smoking (in lung cancer) induce, in the upper range of biologically plausible frequencies, peptides in the cancer exome that are statistically more similar to pathogen peptides than the normal exome. Second, we investigated whether this increased similarity is due to the specificities of the mutagenic process or uniformly random mutations at equal rate would trigger the same effect. For certain pathogens the increased similarity is more pronounced for specific mutagenic processes than for uniformly random mutations and for other pathogens the effects cannot be distinguished. Finally, we investigated whether specific mutational processes result in amino-acid changes with functional relevance that are more likely to be immunogenic. We showed that functional tolerance to mutagenic processes across species generally suggests more resilience to natural processes than to denovo mutagenesis. These results support the idea that recognition of pathogen sequences as well as differential functional tolerance to mutagenic processes may play an important role in the immune recognition process involved in tumor infiltration by lymphocytes.

2018 ◽  
Author(s):  
Omichessan Hanane ◽  
Severi Gianluca ◽  
Perduca Vittorio

AbstractMutational signatures refer to patterns in the occurrence of somatic mutations that reflect underlying mutational processes. To date, after the analysis of tens of thousands of genomes and exomes from about 40 different cancers types, 30 mutational signatures characterized by a unique probability profile across the 96 mutation types have been identified, validated and listed on the COSMIC (Catalogue of Somatic Mutations in Cancer) website. Simultaneously with this development, the last few years saw the publication of several concurrent methods (mathematical algorithms implemented in publicly available software packages) for either the quantification of the contribution of prespecified signatures (e.g. COSMIC signatures) in a given cancer genome or the identification of new signatures from a sample of cancer genomes. A review about existing computational tools has been recently published to guide researchers and practitioners in conducting their mutational signatures analysis, however, other tools have been introduced since its publication and, to date, there has not been a systematic evaluation and comparison of the performance of such tools. In order to fill this gap, we carry on an empirical evaluation study of all available packages to date, using both real and simulated data.


2017 ◽  
Author(s):  
Sandra Krüger ◽  
Rosario M Piro

The mutational processes responsible for the somatic mutations observed in tumor samples can significantly vary not only between tumor types but also among the individual cancers within a tumor class. Mutational processes can be represented by so called “mutational signatures” which reflect the occurrences of base changes within their sequence contexts (i.e., in dependence on their flanking bases). We present a user-friendly R package, called decompTumor2Sig, that can be used to evaluate the contribution of Shiraishi signatures to the somatic mutations found in an individual tumor.


2018 ◽  
Author(s):  
Ludmil B Alexandrov ◽  
Jaegil Kim ◽  
Nicholas J Haradhvala ◽  
Mi Ni Huang ◽  
Alvin WT Ng ◽  
...  

ABSTRACTSomatic mutations in cancer genomes are caused by multiple mutational processes each of which generates a characteristic mutational signature. Using 84,729,690 somatic mutations from 4,645 whole cancer genome and 19,184 exome sequences encompassing most cancer types we characterised 49 single base substitution, 11 doublet base substitution, four clustered base substitution, and 17 small insertion and deletion mutational signatures. The substantial dataset size compared to previous analyses enabled discovery of new signatures, separation of overlapping signatures and decomposition of signatures into components that may represent associated, but distinct, DNA damage, repair and/or replication mechanisms. Estimation of the contribution of each signature to the mutational catalogues of individual cancer genomes revealed associations with exogenous and endogenous exposures and defective DNA maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes contributing to the development of human cancer including a comprehensive reference set of mutational signatures in human cancer.


Author(s):  
Sandra Krüger ◽  
Rosario M Piro

The mutational processes responsible for the somatic mutations observed in tumor samples can significantly vary not only between tumor types but also among the individual cancers within a tumor class. Mutational processes can be represented by so called “mutational signatures” which reflect the occurrences of base changes within their sequence contexts (i.e., in dependence on their flanking bases). We present a user-friendly R package, called decompTumor2Sig, that can be used to evaluate the contribution of Shiraishi signatures to the somatic mutations found in an individual tumor.


Science ◽  
2021 ◽  
pp. eaba7408
Author(s):  
Vladimir B. Seplyarskiy ◽  
Ruslan A. Soldatov ◽  
Evan Koch ◽  
Ryan J. McGinty ◽  
Jakob M. Goldmann ◽  
...  

Biological mechanisms underlying human germline mutations remain largely unknown. We statistically decompose variation in the rate and spectra of mutations along the genome using volume-regularized nonnegative matrix factorization. The analysis of a sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. We provide a biological interpretation for seven of these processes. We associate one process with bulky DNA lesions that resolve asymmetrically with respect to transcription and replication. Two processes track direction of replication fork and replication timing, respectively. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions and a mutagenic effect of LINE repeats. We localize a mutagenic process specific to oocytes from population sequencing data. This process appears transcriptionally asymmetric.


2018 ◽  
Author(s):  
Henry Lee-Six ◽  
Peter Ellis ◽  
Robert J. Osborne ◽  
Mathijs A. Sanders ◽  
Luiza Moore ◽  
...  

AbstractThe colorectal adenoma-carcinoma sequence has provided a paradigmatic framework for understanding the successive somatic genetic changes and consequent clonal expansions leading to cancer. As for most cancer types, however, understanding of the earliest phases of colorectal neoplastic change, which may occur in morphologically normal tissue, is comparatively limited because of the difficulty of detecting somatic mutations in normal cells. Each colorectal crypt is a small clone of cells derived from a single recently-existing stem cell. Here, we whole genome sequenced hundreds of normal crypts from 42 individuals. Signatures of multiple mutational processes were revealed, some ubiquitous and continuous, others only found in some individuals, in some crypts or during some phases of the cell lineage from zygote to adult cell. Likely driver mutations were present in ∼1% of normal colorectal crypts in middle-aged individuals, indicating that adenomas and carcinomas are rare outcomes of a pervasive process of neoplastic change across morphologically normal colorectal epithelium.


2017 ◽  
Author(s):  
Xiaoqing Huang ◽  
Damian Wojtowicz ◽  
Teresa M. Przytycka

AbstractCancers 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. Decomposition of cancer’s mutation catalog into mutations consistent with such signatures can provide valuable information about cancer etiology. However, the results from different decomposition methods are not always consistent. Hence, one needs to not only be able to decompose a patient’s mutational profile into signatures but also to establish the accuracy of such decomposition. We proposed two complementary ways of measuring confidence and stability of decomposition results and applied them to analyze mutational signatures in breast cancer genomes. We identified very stable and highly unstable signatures, as well as signatures that have been missed altogether. We also provided additional support for the novel signatures. Our results emphasize the importance of assessing the confidence and stability of inferred signature contributions. All tools developed in this paper have been implemented in an R package, called SignatureEstimation, which is available from https://www.ncbi.nlm.nih.gov/CBBresearch/Przytycka/index.cgi#signatureestimation.


2016 ◽  
Author(s):  
Ludmil B. Alexandrov ◽  
Young Seok Ju ◽  
Kerstin Haase ◽  
Peter Van Loo ◽  
Iñigo Martincorena ◽  
...  

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.


2020 ◽  
Author(s):  
Damian Wojtowicz ◽  
Jan Hoinka ◽  
Bayarbaatar Amgalan ◽  
Yoo-Ah Kim ◽  
Teresa M. Przytycka

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.


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