Recurrent somatic mutations in regulatory regions of human cancer genomes

Clustered somatic mutations are common in cancer genomes with prior analyses revealing several types of clustered single-base substitutions, including doublet- and multi-base substitutions, diffuse hypermutation termed omikli, and longer strand-coordinated events termed kataegis. Here, we provide a comprehensive characterization of clustered substitutions and clustered small insertions and deletions (indels) across 2,583 whole-genome sequenced cancers from 30 cancer types. While only 3.7% of substitutions and 0.9% of indels were found to be clustered, they contributed 8.4% and 6.9% of substitution and indel drivers, respectively. Multiple distinct mutational processes gave rise to clustered indels including signatures enriched in tobacco smokers and homologous-recombination deficient cancers. Doublet-base substitutions were caused by at least 12 mutational processes, while the majority of multi-base substitutions were generated by either tobacco smoking or exposure to ultraviolet light. Omikli events, previously attributed to the activity of APOBEC3 deaminases, accounted for a large proportion of clustered substitutions. However, only 16.2% of omikli matched APOBEC3 patterns with experimental validation confirming additional mutational processes giving rise to omikli. Kataegis was generated by multiple mutational processes with 76.1% of all kataegic events exhibiting AID/APOBEC3-associated mutational patterns. Co-occurrence of APOBEC3 kataegis and extrachromosomal-DNA (ecDNA) was observed in 31% of samples with ecDNA. Multiple distinct APOBEC3 kataegic events were observed on most mutated ecDNA. ecDNA containing known cancer genes exhibited both positive selection and kataegic hypermutation. Our results reveal the diversity of clustered mutational processes in human cancer and the role of APOBEC3 in recurrently mutating and fueling the evolution of ecDNA.

Download Full-text

Somatic mutations in human cancer—moving towards large scale resequencing of whole cancer genomes

New Biotechnology ◽

10.1016/j.nbt.2010.01.294 ◽

2010 ◽

Vol 27 ◽

pp. S4

Author(s):

A. Futreal

Keyword(s):

Large Scale ◽

Somatic Mutations ◽

Human Cancer ◽

Cancer Genomes

Download Full-text

The Repertoire of Mutational Signatures in Human Cancer

10.1101/322859 ◽

2018 ◽

Cited By ~ 74

Author(s):

Ludmil B Alexandrov ◽

Jaegil Kim ◽

Nicholas J Haradhvala ◽

Mi Ni Huang ◽

Alvin WT Ng ◽

...

Keyword(s):

Somatic Mutations ◽

Human Cancer ◽

Base Substitution ◽

Mutational Signatures ◽

Insertion And Deletion ◽

Damage Repair ◽

Cancer Genomes ◽

Dataset Size ◽

Dna Maintenance ◽

Mutational Processes

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.

Download Full-text

Faculty Opinions recommendation of Patterns of somatic mutation in human cancer genomes.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1068835.524914 ◽

2007 ◽

Author(s):

Anthony Means

Keyword(s):

Somatic Mutation ◽

Human Cancer ◽

Cancer Genomes

Download Full-text

Faculty Opinions recommendation of Patterns of somatic mutation in human cancer genomes.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1068835.521773 ◽

2007 ◽

Author(s):

Channing Der

Keyword(s):

Somatic Mutation ◽

Human Cancer ◽

Cancer Genomes

Download Full-text

Detection and benchmarking of somatic mutations in cancer genomes using RNA-seq data

10.1101/249219 ◽

2018 ◽

Cited By ~ 1

Author(s):

Alexandre Coudray ◽

Anna M. Battenhouse ◽

Philipp Bucher ◽

Vishwanath R. Iyer

Keyword(s):

Exome Sequencing ◽

Somatic Mutations ◽

Low Cost ◽

Systematic Evaluation ◽

Rna Seq ◽

Whole Exome ◽

Cancer Genomes ◽

Additional Support ◽

Coding Variants ◽

Measure Gene Expression

ABSTRACTTo detect functional somatic mutations in tumor samples, whole-exome sequencing (WES) is often used for its reliability and relative low cost. RNA-seq, while generally used to measure gene expression, can potentially also be used for identification of somatic mutations. However there has been little systematic evaluation of the utility of RNA-seq for identifying somatic mutations. Here, we develop and evaluate a pipeline for processing RNA-seq data from glioblastoma multiforme (GBM) tumors in order to identify somatic mutations. The pipeline entails the use of the STAR aligner 2-pass procedure jointly with MuTect2 from GATK to detect somatic variants. Variants identified from RNA-seq data were evaluated by comparison against the COSMIC and dbSNP databases, and also compared to somatic variants identified by exome sequencing. We also estimated the putative functional impact of coding variants in the most frequently mutated genes in GBM. Interestingly, variants identified by RNA-seq alone showed better representation of GBM-related mutations cataloged by COSMIC. RNA-seq-only data substantially outperformed the ability of WES to reveal potentially new somatic mutations in known GBM-related pathways, and allowed us to build a high-quality set of somatic mutations common to exome and RNA-seq calls. Using RNA-seq data in parallel with WES data to detect somatic mutations in cancer genomes can thus broaden the scope of discoveries and lend additional support to somatic variants identified by exome sequencing alone.

Download Full-text