MutationalPatterns: comprehensive genome-wide analysis of mutational processes

Blokzijl, Francis; Janssen, Roel; Boxtel, Ruben van; Cuppen, Edwin

doi:10.1101/071761

Cited by 132 publications

(166 citation statements)

References 42 publications

Supporting

Mentioning

163

Contrasting

Unclassified

Order By: Relevance

“…The catalogue of mutations from an individual cancer genome may have been generated by multiple mutational processes and thus incorporate multiple superimposed mutational signatures. Therefore, in order to systematically characterise the mutational processes contributing to cancer, mathematical methods have been developed that can be used to (i) decipher mutational signatures from a set of somatic mutational catalogues, (ii) estimate the numbers of mutations attributable to each signature in each sample, and (iii) annotate each mutation class in each tumour with the probability of arising from each signature [3][4][5][6][7][8][9][10][11][12][13][14][15] .…”

Section: Introductionmentioning

confidence: 99%

The Repertoire of Mutational Signatures in Human Cancer

Alexandrov¹,

Kim

Haradhvala

et al. 2018

Preprint

511

1,030

View full text Add to dashboard Cite

40 Somatic mutations in cancer genomes are caused by multiple mutational processes each of 41 which generates a characteristic mutational signature. Using 84,729,690 somatic mutations 42 from 4,645 whole cancer genome and 19,184 exome sequences encompassing most cancer 43 types we characterised 49 single base substitution, 11 doublet base substitution, four 44 clustered base substitution, and 17 small insertion and deletion mutational signatures. The 45 substantial dataset size compared to previous analyses enabled discovery of new signatures, 46 separation of overlapping signatures and decomposition of signatures into components that 47 may represent associated, but distinct, DNA damage, repair and/or replication mechanisms. 48 Estimation of the contribution of each signature to the mutational catalogues of individual 49 cancer genomes revealed associations with exogenous and endogenous exposures and 50 defective DNA maintenance processes. However, many signatures are of unknown cause. 51 This analysis provides a systematic perspective on the repertoire of mutational processes 52 contributing to the development of human cancer including a comprehensive reference set 53 of mutational signatures in human cancer. 54 55 56

show abstract

Section: Introductionmentioning

confidence: 99%

The Repertoire of Mutational Signatures in Human Cancer

Alexandrov¹,

Kim

Haradhvala

et al. 2018

Preprint

511

1,030

View full text Add to dashboard Cite

show abstract

“…As there is no para‐tumor tissue for this patient, we filtered SNPs using dbSNP141 27 and 1000 Genomes Project (v3) database 28 . We used MutationalPatterns 29 to decipher the mutational signature composition. For genes mutated in this prostate BCC sample, we checked their mutational frequencies in prostate cancer samples collected in cBioPortal 30 .…”

Section: Methodsmentioning

confidence: 99%

Mutational and transcriptomic landscapes of a rare human prostate basal cell carcinoma

Long

Jiang

et al. 2020

The Prostate

View full text Add to dashboard Cite

Background As a rare subtype of prostate carcinoma, basal cell carcinoma (BCC) has not been studied extensively and thus lacks systematic molecular characterization. Methods Here, we applied single‐cell genomic amplification and RNA‐Seq to a specimen of human prostate BCC (CK34βE12+/P63+/PAP−/PSA−). The mutational landscape was obtained via whole exome sequencing of the amplification mixture of 49 single cells, and the transcriptomes of 69 single cells were also obtained. Results The five putative driver genes mutated in BCC are CASC5, NUTM1, PTPRC, KMT2C, and TBX3, and the top three nucleotide substitutions are C>T, T>C, and C>A, similar to common prostate cancer. The distribution of the variant allele frequency values indicated that these single cells are from the same tumor clone. The 69 single cells were clustered into tumor, stromal, and immune cells based on their global transcriptomic profiles. The tumor cells specifically express basal cell markers like KRT5, KRT14, and KRT23 and epithelial markers EPCAM, CDH1, and CD24. The transcription factor covariance network analysis showed that the BCC tumor cells have distinct regulatory networks. By comparison with current prostate cancer datasets, we found that some of the bulk samples exhibit basal cell signatures. Interestingly, at single‐cell resolution the gene expression patterns of prostate BCC tumor cells show uniqueness compared with that of common prostate cancer‐derived circulating tumor cells. Conclusions This study, for the first time, discloses the comprehensive mutational and transcriptomic landscapes of prostate BCC, which lays a foundation for the understanding of its tumorigenesis mechanism and provides new insights into prostate cancers in general.

show abstract

“…A large set of mutational signatures is known from cancer studies 20 , some of which are well annotated with mutational influences. To fit the patterns of our DNMs to these signatures we used an algorithm similar to the one described in 28 : a non-negative least-squares algorithm finds the mixture of known signatures that describes best the observed pattern. In order to get an indication of the robustness of the fitted mixture of signatures, we resampled DNMs from the original set with replacement and repeated the fitting procedure.…”

Section: Methodsmentioning

confidence: 99%

Germlinede novomutation clusters arise during oocyte aging in genomic regions with increased double-strand break incidence

Goldmann

Seplyarskiy

Wong

et al. 2017

Preprint

View full text Add to dashboard Cite

Clustering of mutations has been found both in somatic mutations from cancer genomes and in germline de novo mutations (DNMs). We identified 1,755 clustered DNMs (cDNMs) within whole-genome sequencing data from 1,291 parent-offspring trios and investigated the underlying mutational mechanisms. We found that the number of clusters on the maternalallele was positively correlated with maternal age and that these consist of more individual mutations with larger intra-mutational distances compared to paternal clusters. More than 50% of maternal clusters were located on chromosomes 8, 9 and 16, in regions with an overall increased maternal mutation rate. Maternal clusters in these regions showed a distinct mutation signature characterized by C>G mutations. Finally, we found that maternal clusters associate with processes involving double-stranded-breaks (DSBs) such as meiotic gene conversions and de novo deletions events. These findings suggest accumulation of DSB-induced mutations throughout oocyte aging as an underlying mechanism leading to maternal mutation clusters.

show abstract

MutationalPatterns: comprehensive genome-wide analysis of mutational processes

Cited by 132 publications

References 42 publications

The Repertoire of Mutational Signatures in Human Cancer

The Repertoire of Mutational Signatures in Human Cancer

Mutational and transcriptomic landscapes of a rare human prostate basal cell carcinoma

Germlinede novomutation clusters arise during oocyte aging in genomic regions with increased double-strand break incidence

Contact Info

Product

Resources

About