Biology subjects

Alexandrov, L. B.

Publications and source records attributed to Alexandrov, L. B..

35 records · Page 2Linked to original sources

bioRxiv2023

Visualizing and exploring patterns of large mutational events with SigProfilerMatrixGenerator

BackgroundAll cancers harbor somatic mutations in their genomes. In principle, mutations affecting between one and fifty base pairs are generally classified as small mutational events. Conversely, large mutational events affect more than fifty base pairs, and, in most cases, they encompass copy-number and structural variants affecting many thousands of base pairs. Prior studies have demonstrated that examining patterns of somatic mutations can be leveraged to provide both biological and clinical insights, thus, resulting in an extensive repertoire of tools for evaluating small mutational events. Recently, classification schemas for examining large-scale mutational events have emerged and shown their utility across the spectrum of human cancers. However, there has been no standard bioinformatics tool that allows visualizing and exploring these large-scale mutational events ResultsHere, we present a new version of SigProfilerMatrixGenerator that now delivers integrated capabilities for examining large mutational events. The tool provides support for examining copy-number variants and structural variants under two previously developed classification schemas and it supports data from numerous algorithms and data modalities. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment. ConclusionsThe new version of SigProfilerMatrixGenerator provides the first standardized bioinformatics tool for optimized exploration and visualization of two previously developed classification schemas for copy number and structural variants. The tool is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/.

bioinformatics↗

bioRxiv2022

Mitotic tethering enables en masse inheritance of a shattered micronuclear chromosome

Chromothripsis, the shattering and imperfect reassembly of one (or a few) chromosome(s)1, is an ubiquitous2 mutational process generating localized complex chromosomal rearrangements that drive genome evolution in cancer. Chromothripsis can be initiated by missegregation errors in mitosis3,4 or DNA metabolism5-7 that lead to entrapment of chromosomes within micronuclei and their subsequent fragmentation in the next interphase or upon mitotic entry6,8-10. Here, we use inducible degrons to demonstrate that chromothriptically produced pieces of a micronucleated chromosome are tethered together in mitosis by a protein complex consisting of Mediator of DNA damage checkpoint 1 (MDC1), DNA Topoisomerase II Binding Protein 1 (TOPBP1), and Cellular Inhibitor of PP2A (CIP2A), thereby enabling en masse segregation to the same daughter cell. Such tethering is shown to be crucial for the viability of cells undergoing chromosome missegregation and shattering after transient inactivation of the spindle assembly checkpoint. Pan-cancer analysis of transcriptome and whole-genome sequencing data revealed that chromothriptic genome rearrangements were accompanied by elevated expression of MDC1, TOPBP1, and CIP2A. Thus, chromatin-bound tethers maintain proximity of fragments of a shattered chromosome enabling their re-encapsulation into, and religation within, a daughter cell nucleus to form heritable, chromothriptically rearranged chromosomes found in the majority of human cancers.

cancer biology↗

bioRxiv2022

Extrachromosomal DNA in the cancerous transformation of Barrett's esophagus

BACKGROUNDOncogenes are commonly amplified on extrachromosomal DNA (ecDNA) contributing to poor outcomes for patients. Currently, the chronology of ecDNA development is not known. We studied the origination and evolution of ecDNA in patients with Barretts esophagus (BE) who progressed to esophageal adenocarcinoma (EAC). METHODSWe analyzed whole-genome sequencing (WGS) data from a BE surveillance cohort and EAC patients at Cambridge University UK (n=206 patients). We also analyzed WGS data from biopsies taken at two time points from multiple sites in the esophagus from 80 patients enrolled in a case-control study at the Fred Hutchinson Cancer Center (FHCC) - 40 BE patients who progressed to EAC and 40 who did not. RESULTSecDNA was detected in 24% and 43% of BE patients with BE-associated early and late-stage EAC, respectively, in the Cambridge cross-sectional cohort. ecDNA was found in 33% of all FHCC BE patients who developed cancer, either prior to, or at EAC diagnosis. ecDNA was strongly associated with patients who developed cancer, in contrast with FHCC BE patients who did not progress (odds ratio, 18.8, CI - 2.3-152, p=3.3x10-4). ecDNAs were enriched for oncogenes and immunomodulatory genes and could be detected early in the transition from high-grade dysplasia to cancer and increased in copy number and complexity over time. CONCLUSIONSecDNAs can develop before a diagnosis of cancer in BE patients and are strongly selected for during the evolution to EAC. ecDNAs promote diverse oncogene and immunomodulatory gene amplification during EAC development and progression.

genomics↗

bioRxiv2022

Topography of mutational signatures in human cancer

The somatic mutations found in a cancer genome are imprinted by different mutational processes. Each process exhibits a characteristic mutational signature, which can be affected by the genome architecture. However, the interplay between mutational signatures and topographical genomic features has not been extensively explored. Here, we integrate mutations from 5,120 whole-genome sequenced tumours from 40 cancer types with 516 topographical features from ENCODE to evaluate the effect of nucleosome occupancy, histone modifications, CTCF binding, replication timing, and transcription/replication strand asymmetries on the cancer-specific accumulation of mutations from distinct mutagenic processes. Most mutational signatures are affected by topographical features with signatures of related aetiologies being similarly affected. Certain signatures exhibit periodic behaviours or cancer-type specific enrichments/depletions near topographical features, revealing further information about the processes that imprinted them. Our findings, disseminated via COSMIC, provide a comprehensive online resource for exploring the interactions between mutational signatures and topographical features across human cancer. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=175 SRC="FIGDIR/small/493921v2_figu1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@abf065org.highwire.dtl.DTLVardef@33ad99org.highwire.dtl.DTLVardef@ca37b6org.highwire.dtl.DTLVardef@fa7c6_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIComprehensive topography analysis of mutational signatures encompassing 82,890,857 somatic mutations in 5,120 whole-genome sequenced tumours integrated with 516 tissue-matched topographical features from the ENCODE project. C_LIO_LIThe accumulation of somatic mutations from most mutational signatures is affected by nucleosome occupancy, histone modifications, CTCF binding sites, transcribed regions, or replication strand/timing. C_LIO_LIMutational signatures with related aetiologies are consistently characterized by similar genome topographies across tissue types. C_LIO_LITopography analysis allows both separating signatures from different aetiologies and understanding the genomic specificity of clustered somatic mutations. C_LIO_LIA comprehensive online resource, disseminate through the COSMIC signatures database, that allows researchers to explore the interactions between somatic mutational processes and genome architecture within and across cancer types. C_LI

cancer biology↗

bioRxiv2022

Examining clustered somatic mutations with SigProfilerClusters

SummaryClustered mutations are found in the human germline as well as in the genomes of cancer and normal somatic cells. Clustered events can be imprinted by a multitude of mutational processes, and they have been implicated in both cancer evolution and development disorders. Existing tools for identifying clustered mutations have been optimized for a particular subtype of clustered event and, in most cases, relied on a predefined inter-mutational distance (IMD) cutoff combined with a piecewise linear regression analysis. Here we present SigProfilerClusters, an automated tool for detecting all types of clustered mutations by calculating a sample-dependent IMD threshold using a simulated background model that takes into account extended sequence context, transcriptional strand asymmetries, and regional mutation densities. SigProfilerClusters disentangles all types of clustered events from non-clustered mutations and annotates each clustered event into an established subclass, including the widely used classes of doublet-base substitutions, multi-base substitutions, omikli, and kataegis. SigProfilerClusters outputs non-clustered mutations and clustered events using standard data formats as well as provides multiple visualizations for exploring the distributions and patterns of clustered mutations across the genome. AvailabilitySigProfilerClusters is freely available at https://github.com/AlexandrovLab/SigProfilerClusters with support across most operating systems and extensive documentation at https://osf.io/qpmzw/wiki/home/. Contactebergstr@eng.ucsd.edu or L2alexandrov@health.ucsd.edu

bioinformatics↗

bioRxiv2021

Comprehensive analysis of mutational signatures in pediatric cancers

Analysis of mutational signatures can reveal the underlying molecular mechanisms of the processes that have imprinted the somatic mutations found in a cancer genome. Here, we present a pan-cancer mutational signatures analysis of single base substitutions (SBS) and small insertion and deletions (ID) in pediatric cancers encompassing 537 whole genome sequenced tumors from 20 molecularly defined cancer subtypes. We identified only a small number of mutational signatures active in pediatric cancers when compared to the previously analyzed adult cancers. Further, we report a significant difference in the proportion of pediatric tumors which show homologous recombination repair defect signature SBS3 compared to prior analyses. Correlating genomic alterations with signature activities, we identified an association of TP53 mutation status with substitution signatures SBS2, SBS8, SBS13 and indel signatures ID2 and ID9, as well as chromothripsis associated with SBS8, SBS40 and ID9. This analysis provides a systematic overview of COSMIC v.3 SBS and ID mutational signatures active across pediatric cancers, which is highly relevant for understanding tumor biology as well as enabling future research in defining biomarkers of treatment response.

cancer biology↗

bioRxiv2021

Comprehensive analysis of clustered mutations in cancer reveals recurrent APOBEC3 mutagenesis of ecDNA

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.

cancer biology↗

bioRxiv2021

Signatures of copy number alterations in human cancer

The gains and losses of DNA that emerge as a consequence of mitotic errors and chromosomal instability are prevalent in cancer. These copy number alterations contribute to cancer initiaition, progression and therapeutic resistance. Here, we present a conceptual framework for examining the patterns of copy number alterations in human cancer using whole-genome sequencing, whole-exome sequencing, and SNP6 microarray data making it widely applicable to diverse datasets. Deploying this framework to 9,873 cancers representing 33 human cancer types from the TCGA project revealed a set of 19 copy number signatures that explain the copy number patterns of 93% of TCGA samples. 15 copy number signatures were attributed to biological processes of whole-genome doubling, aneuploidy, loss of heterozygosity, homologous recombination deficiency, and chromothripsis. The aetiology of four copy number signatures are unexplained and some cancer types have unique patterns of amplicon signatures associated with extrachromosomal DNA, disease-specific survival, and gains of proto-oncogenes such as MDM2. In contrast to base-scale mutational signatures, no copy number signature associated with known cancer risk factors. The results provide a foundation for exploring patterns of copy number changes in cancer genomes and synthesise the global landscape of copy number alterations in human cancer by revealing a diversity of mutational processes giving rise to copy number changes.

cancer biology↗

bioRxiv2021

Pre-mutagenic and mutagenic changes imprinted on the genomes of mammalian cells after irradiation with a nail polish dryer

Ultraviolet A light is commonly emitted by UV-nail polish dryers with recent reports suggesting that long-term use may increase the risk for developing skin cancer. However, no experimental evaluation has been conducted to reveal the effect of radiation emitted by UV-nail polish dryers on mammalian cells. Here, we show that irradiation by a UV-nail polish dryer causes high levels of reactive oxygen species, consistent with 8-oxo-7,8-dihydroguanine damage and mitochondrial dysfunction. Analysis of somatic mutations reveals a dose-dependent increase of C:G>A:T substitutions in irradiated samples with mutagenic patterns similar to mutational signatures attributed to reactive oxygen species. In summary, this study demonstrates that radiation emitted by UV-nail polish dryers can both damage DNA and permanently engrave mutations on the genomes of mammalian cells. These results have far-reaching implications in regard to public health and to preventing skin cancer due to consumer-based exposure to ultraviolet light from artificial sources.

cancer biology↗

bioRxiv2021

Somatic mutational profiles and germline polygenic risk scores in human cancer

The mutational profile of a cancer reflects the activity of the mutagenic processes which have been operative throughout the lineage of the cancer cell. These processes leave characteristic profiles of somatic mutations called mutational signatures. Mutational signatures, including single-based substitution (SBS) signatures, may reflect the effects of exogenous or endogenous exposures. Here, we used polygenic risk score (PRS) as proxies for exposures and examined the association between somatic mutational profiles and germline PRS in 12 cancer types from The Cancer Genome Atlas project. We found 17 statistically significant associations after Bonferroni correction (p < 3.15x10-5), including positive associations between germline inflammatory bowel disease PRS and number of somatic mutations of signature SBS1 in prostate cancer and APOBEC-related signatures in breast cancer. The age at menarche PRS was inversely associated with mutation counts of SBS1 in prostate cancer. Our analysis suggests that there are robust associations between tumor somatic mutational profiles and germline PRS. These may reflect mechanisms through hormone regulation and immunological responses that contribute to cancer etiology and drive cancer progression.

genomics↗

bioRxiv2020

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

Mutational signature analysis is commonly performed in genomic studies surveying cancer and normal somatic tissues. Here we present SigProfilerExtractor, an automated tool for accurate de novo extraction of mutational signatures for all types of somatic mutations. Benchmarking with a total of 34 distinct scenarios encompassing 2,500 simulated signatures operative in more than 60,000 unique synthetic genomes and 20,000 synthetic exomes demonstrates that SigProfilerExtractor outperforms thirteen other tools across all datasets with and without noise. For genome simulations with 5% noise, reflecting high-quality genomic datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true positive signatures while yielding more than 5-fold less false positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome sequenced and 19,184 whole-exome sequenced cancers reveals four previously missed mutational signatures. Two of the signatures are confirmed in independent cohorts with one of these signatures associating with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting mutational signatures, and several novel mutational signatures including a signature putatively attributed to direct tobacco smoking mutagenesis in bladder cancer and in normal bladder epithelium.

bioinformatics↗

bioRxiv2020

Generating realistic null hypothesis of cancer mutational landscapes using SigProfilerSimulator

Performing a statistical test requires a null hypothesis. In cancer genomics, a key challenge is the fast generation of accurate somatic mutational landscapes that can be used as a realistic null hypothesis for making biological discoveries. Here we present SigProfilerSimulator, a powerful tool that is capable of simulating the mutational landscapes of thousands of cancer genomes at different resolutions within seconds. Applying SigProfilerSimulator to 2,144 whole-genome sequenced cancers reveals: (i) that most doublet base substitutions are not due to two adjacent single base substitutions but likely occur as single genomic events; (ii) that an extended sequencing context of +/-2bp is required to more completely capture the patterns of substitution mutational signatures in human cancer; (iii) information on false-positive discovery rate of commonly used bioinformatics tools for detecting driver genes. SigProfilerSimulators breadth of features allows one to construct a tailored null hypothesis and use it for evaluating the accuracy of other bioinformatics tools or for downstream statistical analysis for biological discoveries.

genomics↗

bioRxiv2019

Novel syngeneic animal model of tobacco-associated oral cancer reveals the activity of in situ anti-CTLA-4

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. Tobacco use is the main risk factor for HNSCC, and tobacco-associated HNSCCs have poor prognosis and response to available treatments. Recently approved anti-PD-1 immune checkpoint inhibitors showed limited activity ([≤]20%) in HNSCC, highlighting the need to identify new therapeutic options. For this, mouse models that accurately reflect the complexity of the HNSCC mutational landscape and tumor immune environment are urgently needed. Here, we report the first mouse HNSCC model system that recapitulates the human tobacco-related HNSCC mutanome, in which tumors grow when implanted in the tongue of immunocompetent mice. These HNSCC lesions have similar immune infiltration and response rates to anti-PD-1 ([≤]20%) immunotherapy as human HNSCCs. Remarkably, we found that >70% of HNSCC lesions respond to intratumoral anti-CTLA-4. This syngeneic HNSCC mouse model provides a platform for the development of novel immunotherapeutic options for HNSCC.

cancer biology↗

bioRxiv2019

SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns of small mutational events

BackgroundCancer genomes are peppered with somatic mutations imprinted by different mutational processes. The mutational pattern of a cancer genome can be used to identify and understand the etiology of the underlying mutational processes. A plethora of prior research has focused on examining mutational signatures and mutational patterns from single base substitutions and their immediate sequencing context. We recently demonstrated that further classification of small mutational events (including substitutions, insertions, deletions, and doublet substitutions) can be used to provide a deeper understanding of the mutational processes that have molded a cancer genome. However, there has been no standard tool that allows fast, accurate, and comprehensive classification for all types of small mutational events\n\nResultsHere, we present SigProfilerMatrixGenerator, a computational tool designed for optimized exploration and visualization of mutational patterns for all types of small mutational events. SigProfilerMatrixGenerator is written in Python with an R wrapper package provided for users that prefer working in an R environment. SigProfilerMatrixGenerator produces fourteen distinct matrices by considering transcriptional strand bias of individual events and by incorporating distinct classifications for single base substitutions, doublet base substitutions, and small insertions and deletions. While the tool provides a comprehensive classification of mutations, SigProfilerMatrixGenerator is also faster and more memory efficient than existing tools that generate only a single matrix.\n\nConclusionsSigProfilerMatrixGenerator provides a standardized method for classifying small mutational events that is both efficient and scalable to large datasets. In addition to extending the classification of single base substitutions, the tool is the first to provide support for classifying doublet base substitutions and small insertions and deletions. SigProfilerMatrixGenerator is freely available at https://github.com/AlexandrovLab/SigProfilerMatrixGenerator with an extensive documentation at https://osf.io/s93d5/wiki/home/.

bioinformatics↗

bioRxiv2018

Genomic evidence supports a clonal diaspora model for metastases of esophageal adenocarcinoma

Continual evolution of cancer makes it challenging to predict clinical outcomes. Highly varied and unpredictable patient outcomes in esophageal adenocarcinoma (EAC) prompted us to question the pattern and timing of metastatic spread. Whole genome sequencing and phylogenetic analysis of 396 samples across 18 EAC cases demonstrated a stellate pattern on the phylogenetic trees in 90% cases. The age-dependent trinucleotide signature, which can serve as a molecular clock, was absent or reduced in the stellate branches beyond the trunk in most cases (p<0.0001). Clustering of lymph nodes and distant metastases (n=250) demonstrated samples sharing a common clonal origin were widely dispersed anatomically. Metastatic subclones at autopsy were present in tissue and blood samples from earlier time-points. We infer that metastasis occurs rapidly across multiple sites, constituting a model of metastatic spread we term clonal diaspora. This has implications for understanding metastatic progression, clinical staging and patient management.

genomics↗

bioRxiv2018

Partially methylated domains are hypervariable in breast cancer and fuel widespread CpG island hypermethylation

Global loss of DNA methylation and CpG island (CGI) hypermethylation are regarded as key epigenomic aberrations in cancer. Global loss manifests itself in partially methylated domains (PMDs) which can extend up to megabases. However, the distribution of PMDs within and between tumor types, and their effects on key functional genomic elements including CGIs are poorly defined. Using whole genome bisulfite sequencing (WGBS) of breast cancers, we comprehensively show that loss of methylation in PMDs occurs in a large fraction of the genome and represents the prime source of variation in DNA methylation. PMDs are hypervariable in methylation level, size and distribution, and display elevated mutation rates. They impose intermediate DNA methylation levels incognizant of functional genomic elements including CGIs, underpinning a CGI methylator phenotype (CIMP). However, significant repression effects on cancer-genes are negligible as tumor suppressor genes are generally excluded from PMDs. The genomic distribution of PMDs reports tissue-of-origin of different cancers and may represent tissue-specific silent regions of the genome, which tolerate instability at the epigenetic, transcriptomic and genetic level.

cancer biology↗

bioRxiv2017

Germline determinants of the somatic mutation landscape in 2,642 cancer genomes

Cancers develop through somatic mutagenesis, however germline genetic variation can markedly contribute to tumorigenesis via diverse mechanisms. We discovered and phased 88 million germline single nucleotide variants, short insertions/deletions, and large structural variants in whole genomes from 2,642 cancer patients, and employed this genomic resource to study genetic determinants of somatic mutagenesis across 39 cancer types. Our analyses implicate damaging germline variants in a variety of cancer predisposition and DNA damage response genes with specific somatic mutation patterns. Mutations in the MBD4 DNA glycosylase gene showed association with elevated C>T mutagenesis at CpG dinucleotides, a ubiquitous mutational process acting across tissues. Analysis of somatic structural variation exposed complex rearrangement patterns, involving cycles of templated insertions and tandem duplications, in BRCA1-deficient tumours. Genome-wide association analysis implicated common genetic variation at the APOBEC3 gene cluster with reduced basal levels of somatic mutagenesis attributable to APOBEC cytidine deaminases across cancer types. We further inferred over a hundred polymorphic L1/LINE elements with somatic retrotransposition activity in cancer. Our study highlights the major impact of rare and common germline variants on mutational landscapes in cancer.

genomics↗