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Author Correction: Landscape of somatic mutations in 560 breast cancer whole-genome sequences

February 2019
Nature 566(7742):1

DOI:10.1038/s41586-019-0883-2

Authors:

Serena Nik-Zainal

University of Cambridge

Johan Staaf

Lund University

Manasa Ramakrishna

University of Cambridge

Show all 88 authorsHide

In the Methods section of this Article, ‘greater than’ should have been ‘less than’ in the sentence ‘Putative regions of clustered rearrangements were identified as having an average inter-rearrangement distance that was at least 10 times greater than the whole-genome average for the individual sample. ’. The Article has not been corrected.

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CORRECTION

https://doi.org/10.1038/s41586-019-0883-2

Author Correction: Landscape of

somatic mutations in 560 breast

cancer whole-genome sequences

Serena Nik-Zainal, Helen Davies, Johan Staaf,

Manasa Ramakrishna, Dominik Glodzik, Xueqing Zou,

Inigo Martincorena, Ludmil B. Alexandrov, Sancha Martin,

David C. Wedge, Peter Van Loo, Young Seok Ju, Marcel Smid,

Arie B. Brinkman, Sandro Morganella, Miriam R. Aure,

Ole Christian Lingjærde, Anita Langerød, Markus Ringnér,

Sung-Min Ahn, Sandrine Boyault, Jane E. Brock,

Annegien Broeks, Adam Butler, Christine Desmedt,

Luc Dirix, Serge Dronov, Aquila Fatima, John A. Foekens,

Moritz Gerstung, Gerrit K. J. Hooijer, Se Jin Jang, David R.

Jones, Hyung-Yong Kim, Tari A. King, Savitri Krishnamurthy,

Hee Jin Lee, Jeong-Yeon Lee, Yilong Li, Stuart McLaren,

Andrew Menzies, Ville Mustonen, Sarah O’Meara, Iris

Pauporté, Xavier Pivot, Colin A. Purdie, Keiran Raine,

Kamna Ramakrishnan, F. Germán Rodríguez-González,

Gilles Romieu, Anieta M. Sieuwerts, Peter T. Simpson,

Rebecca Shepherd, Lucy Stebbings, Olafur A. Stefansson,

Jon Teague, Stefania Tommasi, Isabelle Treilleux,

Gert G. Van den Eynden, Peter Vermeulen, Anne Vincent-

Salomon, Lucy Yates, Carlos Caldas, Laura van’t Veer,

Andrew Tutt, Stian Knappskog, Benita Kiat Tee Tan, Jos Jonkers,

Åke Borg, Naoto T. Ueno, Christos Sotiriou, Alain Viari,

P. Andrew Futreal, Peter J. Campbell, Paul N. Span,

Steven Van Laere, Sunil R. Lakhani, Jorunn E. Eyfjord,

Alastair M. Thompson, Ewan Birney, Hendrik G. Stunnenberg,

Marc J. van de Vijver, John W. M. Martens, Anne-Lise

Børresen-Dale, Andrea L. Richardson, Gu Kong, Gilles Thomas

& Michael R. Stratton

Correction to: Nature https://doi.org/10.1038/nature17676,

published online 2 May 2016.

In the Methods section of this Article, ‘greater than’ should have been

‘less than’ in the sentence ‘Putative regions of clustered rearrangements

were identified as having an average inter-rearrangement distance that

was at least 10 times greater than the whole-genome average for the

individual sample. ’ . The original Article has not been corrected online.

CORRECTIONS & AMENDMENTS

7 FEBRUARY 2019 | VOL 566 | NATURE | E1

In BRCA1 and BRCA2 Breast Cancers, Chromosome Breaks Occur near Herpes Tumor Virus Sequences

Preprint

Jul 2021

Bernard A Friedenson

Inherited mutations in BRCA1 and BRCA2 genes increase risks for breast, ovarian, and other cancers. Both genes encode proteins for accurately repairing chromosome breaks. If mutations inactivate this function, broken chromosomes may not be restored correctly, allowing breaks to persist or rearrange chromosomes. These abnormalities are potentially catastrophic events that can originate from viral infections. I used bioinformatic analyses of publicly available breast cancer patient data to show that the distribution of chromosome breaks in hereditary breast cancers differs markedly from sporadic breast cancers. Then I tested hereditary breast cancer sequence data around chromosome breaks for DNA similarity to all known viruses. Human DNA flanking breakpoints usually had decisive matches to Epstein-Barr virus (EBV / HHV4) tumor variants HKHD40 and HKNPC60. Many breakpoints were near EBV genome anchor sites, human EBV tumor-like sequences, EBV-associated epigenetic marks, and some fragile sites. On chromosomes 2 and 12, sequences near EBV genome anchor sites accounted for 90% and 88% of breakpoints (p<0.0001), respectively. On chromosome 4, 51/52 inter-chromosomal breakpoints were close to EBV-like sequences in 19 hereditary breast cancers. In contrast, 19 sporadic breast cancers only had 12 interchromosomal breakpoint regions on chromosome 4 near EBV-like sequences. On various other chromosomes, five EBV genome anchor sites were near hereditary breast cancer breakpoints at precisely defined, disparate gene or LINE locations. Independent evidence further implicating EBV in hereditary breast cancer breakpoints is that 25 breast cancer break positions are within 1.25% of breakpoints in model EBV cancers. In addition to BRCA1 or BRCA2 mutations, all the hereditary breast cancers had mutated genes essential for immune responses. This compromise facilitates reactivation of herpes viruses which produce nucleases capable of breaking chromosomes. EBV also causes other deleterious effects: anchored EBV episomes can interfere with normal replication and obstruct DNA break repairs; even very early infection causes massive transcription changes. The results, therefore, imply proactive treatment and prevention of herpes viral infections may prevent some chromosome breaks and benefit BRCA mutation carriers.

In BRCA1 and BRCA2 Breast Cancers, Chromosome Breaks Occur Near Herpes Tumor Virus Sequences

Preprint

May 2021

Bernard A Friedenson

Inherited mutations in BRCA1 and BRCA2 genes increase risks for breast, ovarian, and other cancers. Both genes encode proteins for accurately repairing chromosome breaks. If mutations inactivate this function, chromosome fragments may not be restored correctly. Resulting chromosome rearrangements can become critical breast cancer drivers. Because I had data from thousands of cancer structural alterations that matched viral infections, I wondered whether infections contribute to chromosome breaks and rearrangements in hereditary breast cancers. There are currently no interventions to prevent chromosome breaks because they are thought to be unavoidable. However, if chromosome breaks come from infections, they can be treated or prevented. I used bioinformatic analyses to test publicly available breast cancer sequence data around chromosome breaks for DNA similarity to all known viruses. Human DNA flanking breakpoints usually had the strongest matches to Epstein-Barr virus (EBV) tumor variants HKHD40 and HKNPC60. Many breakpoints were near sites that anchor EBV genomes, human EBV tumor-like sequences, EBV-associated epigenetic marks, and fragile sites. On chromosome 2, sequences near EBV genome anchor sites accounted for 90% of breakpoints (p<0.0001). On chromosome 4, 51/52 inter-chromosomal breakpoints were close to EBV-like sequences. Five EBV genome anchor sites were near breast cancer breakpoints at precisely defined, disparate gene or LINE locations. Breakpoint flanking regions resembled known EBV-cancers. Twenty-five breakpoints in breast cancers were within 1.25% of EBV cancer breakpoints. In addition to BRCA1 or BRCA2 mutations, all the breast cancers had mutated genes essential for immune responses. Because of this immune compromise, herpes viruses can activate and produce nucleases that break chromosomes. Alternatively, anchored viral episomes can obstruct break repairs, whatever the cause. The results, therefore, imply proactive treatment and prevention of herpes viral infections may prevent some chromosome breaks and benefit BRCA mutation carriers.

In BRCA1 and BRCA2 breast cancers, chromosome breaks occur near herpes tumor virus sequences

Preprint

Full-text available

Apr 2021

Bernard A Friedenson

Inherited mutations in BRCA1 and BRCA2 genes increase risks for breast, ovarian, and other cancers. Both genes encode proteins for accurately repairing chromosome breaks. If mutations inactivate this function, broken chromosome fragments get lost or reattach indiscriminately. These mistakes are characteristic of hereditary breast cancer. We tested the hypothesis that mistakes in reattaching broken chromosomes preferentially occur near viral sequences on human chromosomes. We tested millions of DNA bases around breast cancer breakpoints for similarities to all known viral DNA. DNA around breakpoints often closely matched the Epstein-Barr virus (EBV) tumor variants HKHD40 and HKNPC60. Almost all breakpoints were near EBV anchor sites, EBV tumor variant homologies, and EBV-associated regulatory marks. On chromosome 2, EBV binding sites accounted for 90% of breakpoints (p<0.0001). On chromosome 4, 51/52 inter-chromosomal breakpoints were close to EBV variant sequences. Five viral anchor sites at critical genes were near breast cancer breakpoints. Twenty-five breast cancer breakpoints were within 1.25% of breakpoints in model EBV cancers. EBV-like sequence patterns around breast cancer breakpoints resemble gene fusion breakpoints in model EBV cancers. All BRCA1 and BRCA2 breast cancers had mutated genes essential for immune responses. Because of this immune compromise, herpes viruses can attach and produce nucleases that break chromosomes. Alternatively, anchored viruses can retard break repairs, whatever the causes. The results imply proactive treatment and prevention of herpes viral infections may benefit BRCA mutation carriers.

Influence network model uncovers relations between biological processes and mutational signatures

Article

Full-text available

Mar 2023

Background There has been a growing appreciation recently that mutagenic processes can be studied through the lenses of mutational signatures, which represent characteristic mutation patterns attributed to individual mutagens. However, the causal links between mutagens and observed mutation patterns as well as other types of interactions between mutagenic processes and molecular pathways are not fully understood, limiting the utility of mutational signatures. Methods To gain insights into these relationships, we developed a network-based method, named GeneSigNet that constructs an influence network among genes and mutational signatures. The approach leverages sparse partial correlation among other statistical techniques to uncover dominant influence relations between the activities of network nodes. Results Applying GeneSigNet to cancer data sets, we uncovered important relations between mutational signatures and several cellular processes that can shed light on cancer-related processes. Our results are consistent with previous findings, such as the impact of homologous recombination deficiency on clustered APOBEC mutations in breast cancer. The network identified by GeneSigNet also suggest an interaction between APOBEC hypermutation and activation of regulatory T Cells (Tregs), as well as a relation between APOBEC mutations and changes in DNA conformation. GeneSigNet also exposed a possible link between the SBS8 signature of unknown etiology and the Nucleotide Excision Repair (NER) pathway. Conclusions GeneSigNet provides a new and powerful method to reveal the relation between mutational signatures and gene expression. The GeneSigNet method was implemented in python, and installable package, source codes and the data sets used for and generated during this study are available at the Github site https://github.com/ncbi/GeneSigNet.

Examining clustered somatic mutations with SigProfilerClusters

Article

Full-text available

May 2022
BIOINFORMATICS

Motivation: Clustered 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. Results: 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. Availability: SigProfilerClusters is supported across most operating systems and made freely available at https://github.com/AlexandrovLab/SigProfilerClusters with an extensive documentation located at https://osf.io/qpmzw/wiki/home/. Supplementary information: Supplementary data are available at Bioinformatics online.

Pan-Cancer Analysis of PARP1 Alterations as Biomarkers in the Prediction of Immunotherapeutic Effects and the Association of Its Expression Levels and Immunotherapy Signatures

Article

Full-text available

Aug 2021

Background Poly (ADP-ribose) polymerases-1 (PARP1) alterations are associated with PARP1 inhibitor resistance, regulating the function of Treg cells and PDL1 expression in tumor cells, and high PARP1 expression is significantly associated with aggressive behavior and chemotherapeutic resistance in several tumors. However, a comprehensive analysis of the predictive values of PARP1 alteration for immune checkpoint inhibitor (ICI) effectiveness in tumors remains unclear, and the associations between its expression and immunotherapy signatures also needs to be explored further. Methods We performed some analyses with the cBioPortal online database ( https://www.cbioportal.org ), TIMER2.0 (Tumor Immune Estimation Resource 2.0, http://timer.comp-genomics.org/ ) and TCGA database ( https://xenabrowser.net or https://portal.gdc.cancer.gov/ ). Survival analysis was conducted using Kaplan–Meier method, and the associations between PARP1 transcription levels and immune checkpoint gene expression, the number of neoantigens, tumor mutation burden (TMB) levels, and microsatellite instability (MSI) event are analyzed by spearman correlation analysis and visualization of those mentioned above is performed using R, version 3.6.3 ( http://www.r-project.org/ ). Results We found that PARP1 was altered in 1338 (2.9%) out of 45604 patients with diverse tumors, which was associated with markedly higher TMB levels in a variety of tumors (P < 0.01). Impressively, patients with PARP1 alterations in advanced tumors showed better overall survival (OS) in the ICI-treated cohort (P = 0.016). PARP1 altered group was substantially correlated with higher immune infiltrates across most tumors, including CD8+ T cells in colorectal adenocarcinoma (P = 0.0061), endometrial carcinoma (P = 0.0033), stomach cancer (P = 0.033), and cervical cancer (P = 0.026), respectively. The PARP1 altered group showed high expression in transcription (P < 0.001), and higher expression of LAG3, PDCD1, CTLA-4, and TIGIT (P < 0.05). Higher PARP1 expression was present in 27 tumor compared the corresponding normal tissues using the GTEx and TCGA databases and it had a worse OS in several tumors (P < 0.05). Further, high PARP1 expression was significantly associated with six immune cells (B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and dendritic cells) in most tumors, including colon adenocarcinoma (COAD), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), and liver hepatocellular carcinoma (LIHC) (P < 0.05). In particular, CD8+T cell infiltration, was also positively correlated with high PARP1 expression in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), kidney renal papillary cell carcinoma (KIRP), brain lower grade glioma (LGG), LIHC, pancreatic adenocarcinoma (PAAD), pheochromocytoma and paraganglioma (PCPG), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), testicular germ cell tumors (TGCT), thymoma (THYM), uterine corpus endometrial carcinoma (UCEC), uveal melanoma (UVM) (P < 0.05, no data shown), and PARP1 expression was significantly positively correlated with the transcription levels of some of the 47 immune checkpoint genes, such as CD274, CTLA4, and PDCD1 in several tumors, including PAAD, LIHC, KIRC, HNSC, and BLCA (P < 0.05). A significant positive association between PARP1 expression and the number of immune neoantigen was found within COAD, KIRC, lung adenocarcinoma (LUAD), PAAD and THYM (P < 0.05), and there were also significantly positive correlations between PARP1 expression and TMB in many tumors like adrenocortical carcinoma (ACC), COAD, kidney chromophobe (KICH), LGG, LUAD, READ, skin cutaneous melanoma (SKCM) and stomach adenocarcinoma (STAD) (P < 0.05). In addition, high PARP1 expression was positively associated with microsatellite instability event in COAD, KIRP, BRCA, glioblastoma multiforme (GBM), lung squamous cell carcinoma (LUSC), LGG, READ, UCEC, SKCM and LUAD (P < 0.05). Conclusions Our results highlight the significance of PARP1 alterations as pan-cancer predictive biomarkers for ICI treatment, and its expression levels seem to be correlated with the status of immunotherapy-associated signatures, thus may be a promising biomarker for predicting ICI response in several tumors.

Multi-Omics Mining of lncRNAs with Biological and Clinical Relevance in Cancer

Article

Full-text available

Nov 2023
INT J MOL SCI

In this review, we provide a general overview of the current panorama of mining strategies for multi-omics data to investigate lncRNAs with an actual or potential role as biological markers in cancer. Several multi-omics studies focusing on lncRNAs have been performed in the past with varying scopes. Nevertheless, many questions remain regarding the pragmatic application of different molecular technologies and bioinformatics algorithms for mining multi-omics data. Here, we attempt to address some of the less discussed aspects of the practical applications using different study designs for incorporating bioinformatics and statistical analyses of multi-omics data. Finally, we discuss the potential improvements and new paradigms aimed at unraveling the role and utility of lncRNAs in cancer and their potential use as molecular markers for cancer diagnosis and outcome prediction.

Targeting the replication stress response through synthetic lethal strategies in cancer medicine

Article

Jun 2021

The replication stress response (RSR) involves a downstream kinase cascade comprising ataxia telangiectasia-mutated (ATM), ATM and rad3-related (ATR), checkpoint kinases 1 and 2 (CHK1/2), and WEE1-like protein kinase (WEE1), which cooperate to arrest the cell cycle, protect stalled forks, and allow time for replication fork repair. In the presence of elevated replicative stress, cancers are increasingly dependent on RSR to maintain genomic integrity. An increasing number of drug candidates targeting key RSR nodes, as monotherapy through synthetic lethality, or through rational combinations with immune checkpoint inhibitors and targeted therapies, are demonstrating promising efficacy in early phase trials. RSR targeting is also showing potential in reversing PARP inhibitor resistance, an important area of unmet clinical need. In this review, we introduce the concept of targeting the RSR, detail the current landscape of monotherapy and combination strategies, and discuss emerging therapeutic approaches, such as targeting Polθ.

Clonal fitness inferred from time-series modelling of single-cell cancer genomes

Article

Full-text available

Jul 2021
NATURE

Progress in defining genomic fitness landscapes in cancer, especially those defined by copy number alterations (CNAs), has been impeded by lack of time-series single-cell sampling of polyclonal populations and temporal statistical models1–7. Here we generated 42,000 genomes from multi-year time-series single-cell whole-genome sequencing of breast epithelium and primary triple-negative breast cancer (TNBC) patient-derived xenografts (PDXs), revealing the nature of CNA-defined clonal fitness dynamics induced by TP53 mutation and cisplatin chemotherapy. Using a new Wright–Fisher population genetics model8,9 to infer clonal fitness, we found that TP53 mutation alters the fitness landscape, reproducibly distributing fitness over a larger number of clones associated with distinct CNAs. Furthermore, in TNBC PDX models with mutated TP53, inferred fitness coefficients from CNA-based genotypes accurately forecast experimentally enforced clonal competition dynamics. Drug treatment in three long-term serially passaged TNBC PDXs resulted in cisplatin-resistant clones emerging from low-fitness phylogenetic lineages in the untreated setting. Conversely, high-fitness clones from treatment-naive controls were eradicated, signalling an inversion of the fitness landscape. Finally, upon release of drug, selection pressure dynamics were reversed, indicating a fitness cost of treatment resistance. Together, our findings define clonal fitness linked to both CNA and therapeutic resistance in polyclonal tumours. Whole-genome sequencing of human cancer cells in patient-derived mouse xenograft models indicates a key role for TP53 in determining the fitness landscape of polyclonal cancer cell populations.

Chromothripsis drives the evolution of gene amplification in cancer

Article

Full-text available

Mar 2021
NATURE

Focal chromosomal amplification contributes to the initiation of cancer by mediating overexpression of oncogenes1–3, and to the development of cancer therapy resistance by increasing the expression of genes whose action diminishes the efficacy of anti-cancer drugs. Here we used whole-genome sequencing of clonal cell isolates that developed chemotherapeutic resistance to show that chromothripsis is a major driver of circular extrachromosomal DNA (ecDNA) amplification (also known as double minutes) through mechanisms that depend on poly(ADP-ribose) polymerases (PARP) and the catalytic subunit of DNA-dependent protein kinase (DNA-PKcs). Longitudinal analyses revealed that a further increase in drug tolerance is achieved by structural evolution of ecDNAs through additional rounds of chromothripsis. In situ Hi-C sequencing showed that ecDNAs preferentially tether near chromosome ends, where they re-integrate when DNA damage is present. Intrachromosomal amplifications that formed initially under low-level drug selection underwent continuing breakage–fusion–bridge cycles, generating amplicons more than 100 megabases in length that became trapped within interphase bridges and then shattered, thereby producing micronuclei whose encapsulated ecDNAs are substrates for chromothripsis. We identified similar genome rearrangement profiles linked to localized gene amplification in human cancers with acquired drug resistance or oncogene amplifications. We propose that chromothripsis is a primary mechanism that accelerates genomic DNA rearrangement and amplification into ecDNA and enables rapid acquisition of tolerance to altered growth conditions.

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