The role of tandem duplicator phenotype in tumour evolution in high-grade serous ovarian cancer

FANCD2 expression affects platinum response and further characteristics of high grade serous ovarian cancer in cells with different genetic backgrounds

High-grade serous ovarian cancer (HGSOC) is the most prevalent subtype of ovarian cancer and demonstrates 5-year survival of just 40%. One of the major causes of mortality is the development of tumour resistance to platinum-based chemotherapy, which can be modulated by dysregulation of DNA damage repair pathways. We therefore investigated the contribution of the DNA interstrand crosslink repair protein FANCD2 to chemosensitivity in HGSOC. Increased FANCD2 protein expression was observed in some cell line models of platinum resistant HGSOC compared with paired platinum sensitive models. Knockdown of FANCD2 in some cell lines, including the platinum resistant PEO4, led to increased carboplatin sensitivity. Investigation into mechanisms of FANCD2 regulation showed that increased FANCD2 expression in platinum resistant cells coincides with increased expression of mTOR. Treatment with mTOR inhibitors resulted in FANCD2 depletion, suggesting that mTOR can mediate platinum sensitivity via regulation of FANCD2. Tumours from a cohort of HGSOC patients showed varied nuclear and cytoplasmic FANCD2 expression, however this was not significantly associated with clinical characteristics. Knockout of FANCD2 was associated with increased cell migration, which may represent a non-canonical function of cytoplasmic FANCD2. We conclude that upregulation of FANCD2, possibly mediated by mTOR, is a potential mechanism of chemoresistance in HGSOC and modulation of FANCD2 expression can influence platinum sensitivity and other tumour cell characteristics.

A comparative analysis of 2D and 3D experimental data for the identification of the parameters of computational models

Computational models are becoming an increasingly valuable tool in biomedical research. Their accuracy and effectiveness, however, rely on the identification of suitable parameters and on appropriate validation of the in-silico framework. Both these steps are highly dependent on the experimental model used as a reference to acquire the data. Selecting the most appropriate experimental framework thus becomes key, together with the analysis of the effect of combining results from different experimental models, a common practice often necessary due to limited data availability. In this work, the same in-silico model of ovarian cancer cell growth and metastasis, was calibrated with datasets acquired from traditional 2D monolayers, 3D cell culture models or a combination of the two. The comparison between the parameters sets obtained in the different conditions, together with the corresponding simulated behaviours, is presented. It provides a framework for the study of the effect of the different experimental models on the development of computational systems. This work also provides a set of general guidelines for the comparative testing and selection of experimental models and protocols to be used for parameter optimization in computational models.

Olaparib-Resistant BRCA2MUT Ovarian Cancer Cells with Restored BRCA2 Abrogate Olaparib-Induced DNA Damage and G2/M Arrest Controlled by the ATR/CHK1 Pathway for Survival

The PARP inhibitor (PARPi) olaparib is currently the drug of choice for serous ovarian cancer (OC), especially in patients with homologous recombination (HR) repair deficiency associated with deleterious BRCA1/2 mutations. Unfortunately, OC patients who fail to respond to PARPi or relapse after treatment have limited therapeutic options. To elucidate olaparib resistance and enhance the efficacy of olaparib, intracellular factors exploited by OC cells to achieve decreased sensitivity to PARPi were examined. An olaparib-resistant OC cell line, PEO1-OR, was established from BRCA2MUT PEO1 cells. The anticancer activity and action of olaparib combined with inhibitors of the ATR/CHK1 pathway (ceralasertib as ATRi, MK-8776 as CHK1i) in olaparib-sensitive and -resistant OC cell lines were evaluated. Whole-exome sequencing revealed that PEO1-OR cells acquire resistance through subclonal enrichment of BRCA2 secondary mutations that restore functional full-length protein. Moreover, PEO1-OR cells upregulate HR repair-promoting factors (BRCA1, BRCA2, RAD51) and PARP1. Olaparib-inducible activation of the ATR/CHK1 pathway and G2/M arrest is abrogated in olaparib-resistant cells. Drug sensitivity assays revealed that PEO1-OR cells are less sensitive to ATRi and CHK1i agents. Combined treatment is less effective in olaparib-resistant cells considering inhibition of metabolic activity, colony formation, survival, accumulation of DNA double-strand breaks, and chromosomal aberrations. However, synergistic antitumor activity between compounds is achievable in PEO1-OR cells. Collectively, olaparib-resistant cells display co-existing HR repair-related mechanisms that confer resistance to olaparib, which may be effectively utilized to resensitize them to PARPi via combination therapy. Importantly, the addition of ATR/CHK1 pathway inhibitors to olaparib has the potential to overcome acquired resistance to PARPi.

Evolutionary perspectives, heterogeneity and ovarian cancer: a complicated tale from past to present

Ovarian cancer is composed of a complex system of cells best described by features such as clonal evolution, spatial and temporal genetic heterogeneity, and development of drug resistance, thus making it the most lethal gynecologic cancer. Seminal work on cancer as an evolutionary process has a long history; however, recent cost-effective large-scale molecular profiling has started to provide novel insights coupled with the development of mathematical algorithms. In the current review, we have systematically searched for articles that focused on the clonal evolution of ovarian cancer to offer the whole landscape of research that has been done and highlight future research avenues given its characteristic features and connections to evolutionary biology.

Homologous Recombination Deficiency in Pancreatic Cancer: A Systematic Review and Prevalence Meta-Analysis

PURPOSE

To analyze the prevalence of homologous recombination deficiency (HRD) in patients with pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

We conducted a systematic review and meta-analysis of the prevalence of HRD in PDAC from PubMed, Scopus, and Cochrane Library databases, and online cancer genomic data sets. The main outcome was pooled prevalence of somatic and germline mutations in the better characterized HRD genes (BRCA1, BRCA2, PALB2, ATM, ATR, CHEK2, RAD51, and the FANC genes). The secondary outcomes were prevalence of germline mutations overall, and in sporadic and familial cases; prevalence of germline BRCA1/2 mutations in Ashkenazi Jewish (AJ); and prevalence of HRD based on other definitions (ie, alterations in other genes, genomic scars, and mutational signatures). Random-effects modeling with the Freeman-Tukey transformation was used for the analyses. PROSPERO registration number: (CRD42020190813).

RESULTS

Sixty studies with 21,842 participants were included in the systematic review and 57 in the meta-analysis. Prevalence of germline and somatic mutations was BRCA1: 0.9%, BRCA2: 3.5%, PALB2: 0.2%, ATM: 2.2%, CHEK2: 0.3%, FANC: 0.5%, RAD51: 0.0%, and ATR: 0.1%. Prevalence of germline mutations was BRCA1: 0.9% (2.4% in AJ), BRCA2: 3.8% (8.2% in AJ), PALB2: 0.2%, ATM: 2%, CHEK2: 0.3%, and FANC: 0.4%. No significant differences between sporadic and familial cases were identified. HRD prevalence ranged between 14.5%-16.5% through targeted next-generation sequencing and 24%-44% through whole-genome or whole-exome sequencing allowing complementary genomic analysis, including genomic scars and other signatures (surrogate markers of HRD).

CONCLUSION

Surrogate readouts of HRD identify a greater proportion of patients with HRD than analyses limited to gene-level approaches. There is a clear need to harmonize HRD definitions and to validate the optimal biomarker for treatment selection. Universal HRD screening including integrated somatic and germline analysis should be offered to all patients with PDAC.

A survey of cancer genome signatures identifies genes connected to distinct chromosomal instability phenotypes

Certain breast and ovarian cancers are characterised by high levels of chromosomal instability. We established a suite of eleven SNP array-based signatures of various forms of chromosomal instability. To understand what biological mechanisms might underpin these signatures, we generated and assembled genetic-feature data including allele-specific expression, fusion genes, gene expression, methylation, somatic coding mutations and protein expression. For each signature, we extracted a compendium of significantly associated genetic features using machine learning. We established an association between subchromosomal allelic imbalance-based measures and DNA repair genes. Numerical chromosomal instability and chromothripsis were found to have distinct genetic associations but shared a relationship to mitotic processes, while whole-genome doubling was characterised by TP53 mutation, and high AURKA and GINS1 expression. Furthermore, we identified two genetically distinct forms of tandem duplicator phenotypes. These findings identify potentially novel genomic targets for validation and drug development for specific subsets of breast and ovarian cancer.

Copy number signature analysis tool and its application in prostate cancer reveals distinct mutational processes and clinical outcomes

Genome alteration signatures reflect recurring patterns caused by distinct endogenous or exogenous mutational events during the evolution of cancer. Signatures of single base substitution (SBS) have been extensively studied in different types of cancer. Copy number alterations are important drivers for the progression of multiple cancer. However, practical tools for studying the signatures of copy number alterations are still lacking. Here, a user-friendly open source bioinformatics tool "sigminer" has been constructed for copy number signature extraction, analysis and visualization. This tool has been applied in prostate cancer (PC), which is particularly driven by complex genome alterations. Five copy number signatures are identified from human PC genome with this tool. The underlying mutational processes for each copy number signature have been illustrated. Sample clustering based on copy number signature exposure reveals considerable heterogeneity of PC, and copy number signatures show improved PC clinical outcome association when compared with SBS signatures. This copy number signature analysis in PC provides distinct insight into the etiology of PC, and potential biomarkers for PC stratification and prognosis.

Targeting DNA Damage Response and Replication Stress in Pancreatic Cancer

BACKGROUND & AIMS

Continuing recalcitrance to therapy cements pancreatic cancer (PC) as the most lethal malignancy, which is set to become the second leading cause of cancer death in our society. The study aim was to investigate the association between DNA damage response (DDR), replication stress, and novel therapeutic response in PC to develop a biomarker-driven therapeutic strategy targeting DDR and replication stress in PC.

METHODS

We interrogated the transcriptome, genome, proteome, and functional characteristics of 61 novel PC patient-derived cell lines to define novel therapeutic strategies targeting DDR and replication stress. Validation was done in patient-derived xenografts and human PC organoids.

RESULTS

Patient-derived cell lines faithfully recapitulate the epithelial component of pancreatic tumors, including previously described molecular subtypes. Biomarkers of DDR deficiency, including a novel signature of homologous recombination deficiency, cosegregates with response to platinum (P < .001) and PARP inhibitor therapy (P < .001) in vitro and in vivo. We generated a novel signature of replication stress that predicts response to ATR (P < .018) and WEE1 inhibitor (P < .029) treatment in both cell lines and human PC organoids. Replication stress was enriched in the squamous subtype of PC (P < .001) but was not associated with DDR deficiency.

CONCLUSIONS

Replication stress and DDR deficiency are independent of each other, creating opportunities for therapy in DDR-proficient PC and after platinum therapy.

Algorithmic approaches to clonal reconstruction in heterogeneous cell populations

BACKGROUND

The reconstruction of clonal haplotypes and their evolutionary history in evolving populations is a common problem in both microbial evolutionary biology and cancer biology. The clonal theory of evolution provides a theoretical framework for modeling the evolution of clones.

RESULTS

In this paper, we review the theoretical framework and assumptions over which the clonal reconstruction problem is formulated. We formally define the problem and then discuss the complexity and solution space of the problem. Various methods have been proposed to find the phylogeny that best explains the observed data. We categorize these methods based on the type of input data that they use (space-resolved or time-resolved), and also based on their computational formulation as either combinatorial or probabilistic. It is crucial to understand the different types of input data because each provides essential but distinct information for drastically reducing the solution space of the clonal reconstruction problem. Complementary information provided by single cell sequencing or from whole genome sequencing of randomly isolated clones can also improve the accuracy of clonal reconstruction. We briefly review the existing algorithms and their relationships. Finally we summarize the tools that are developed for either directly solving the clonal reconstruction problem or a related computational problem.

CONCLUSIONS

In this review, we discuss the various formulations of the problem of inferring the clonal evolutionary history from allele frequeny data, review existing algorithms and catergorize them according to their problem formulation and solution approaches. We note that most of the available clonal inference algorithms were developed for elucidating tumor evolution whereas clonal reconstruction for unicellular genomes are less addressed. We conclude the review by discussing more open problems such as the lack of benchmark datasets and comparison of performance between available tools.

Hierarchical Clustering of DNA k-mer Counts in RNAseq Fastq Files Identifies Sample Heterogeneities

We apply hierarchical clustering (HC) of DNA k-mer counts on multiple Fastq files. The tree structures produced by HC may reflect experimental groups and thereby indicate experimental effects, but clustering of preparation groups indicates the presence of batch effects. Hence, HC of DNA k-mer counts may serve as a diagnostic device. In order to provide a simple applicable tool we implemented sequential analysis of Fastq reads with low memory usage in an R package (seqTools) available on Bioconductor. The approach is validated by analysis of Fastq file batches containing RNAseq data. Analysis of three Fastq batches downloaded from ArrayExpress indicated experimental effects. Analysis of RNAseq data from two cell types (dermal fibroblasts and Jurkat cells) sequenced in our facility indicate presence of batch effects. The observed batch effects were also present in reads mapped to the human genome and also in reads filtered for high quality (Phred > 30). We propose, that hierarchical clustering of DNA k-mer counts provides an unspecific diagnostic tool for RNAseq experiments. Further exploration is required once samples are identified as outliers in HC derived trees.

Copy number signatures and mutational processes in ovarian carcinoma

The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.

Copy number signatures and mutational processes in ovarian carcinoma

The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.

Copy number signatures and mutational processes in ovarian carcinoma

The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.

The Tandem Duplicator Phenotype Is a Prevalent Genome-Wide Cancer Configuration Driven by Distinct Gene Mutations

The tandem duplicator phenotype (TDP) is a genome-wide instability configuration primarily observed in breast, ovarian, and endometrial carcinomas. Here, we stratify TDP tumors by classifying their tandem duplications (TDs) into three span intervals, with modal values of 11 kb, 231 kb, and 1.7 Mb, respectively. TDPs with ∼11 kb TDs feature loss of TP53 and BRCA1. TDPs with ∼231 kb and ∼1.7 Mb TDs associate with CCNE1 pathway activation and CDK12 disruptions, respectively. We demonstrate that p53 and BRCA1 conjoint abrogation drives TDP induction by generating short-span TDP mammary tumors in genetically modified mice lacking them. Lastly, we show how TDs in TDP tumors disrupt heterogeneous combinations of tumor suppressors and chromatin topologically associating domains while duplicating oncogenes and super-enhancers.

Structural Alterations Driving Castration-Resistant Prostate Cancer Revealed by Linked-Read Genome Sequencing

Nearly all prostate cancer deaths are from metastatic castration-resistant prostate cancer (mCRPC), but there have been few whole-genome sequencing (WGS) studies of this disease state. We performed linked-read WGS on 23 mCRPC biopsy specimens and analyzed cell-free DNA sequencing data from 86 patients with mCRPC. In addition to frequent rearrangements affecting known prostate cancer genes, we observed complex rearrangements of the AR locus in most cases. Unexpectedly, these rearrangements include highly recurrent tandem duplications involving an upstream enhancer of AR in 70%-87% of cases compared with <2% of primary prostate cancers. A subset of cases displayed AR or MYC enhancer duplication in the context of a genome-wide tandem duplicator phenotype associated with CDK12 inactivation. Our findings highlight the complex genomic structure of mCRPC, nominate alterations that may inform prostate cancer treatment, and suggest that additional recurrent events in the non-coding mCRPC genome remain to be discovered.

Sorting cancer karyotypes using double-cut-and-joins, duplications and deletions

Motivation

Problems of genome rearrangement are central in both evolution and cancer research. Most genome rearrangement models assume that the genome contains a single copy of each gene and the only changes in the genome are structural, i.e., reordering of segments. In contrast, tumor genomes also undergo numerical changes such as deletions and duplications, and thus the number of copies of genes varies. Dealing with unequal gene content is a very challenging task, addressed by few algorithms to date. More realistic models are needed to help trace genome evolution during tumorigenesis.

Results

Here we present a model for the evolution of genomes with multiple gene copies using the operation types double-cut-and-joins, duplications and deletions. The events supported by the model are reversals, translocations, tandem duplications, segmental deletions, and chromosomal amplifications and deletions, covering most types of structural and numerical changes observed in tumor samples. Our goal is to find a series of operations of minimum length that transform one karyotype into the other. We show that the problem is NP-hard and give an integer linear programming formulation that solves the problem exactly under some mild assumptions. We test our method on simulated genomes and on ovarian cancer genomes. Our study advances the state of the art in two ways: It allows a broader set of operations than extant models, thus being more realistic, and it is the first study attempting to reconstruct the full sequence of structural and numerical events during cancer evolution.

Availability

Code and data are available in https://github.com/Shamir-Lab/Sorting-Cancer-Karyotypes.

Contact

ronzeira@post.tau.ac.il, rshamir@tau.ac.il.

Supplementary information

Supplementary data are available at Bioinformatics online.

Targeting DNA repair: the genome as a potential biomarker

Genomic instability and mutations are fundamental aspects of human malignancies, leading to progressive accumulation of the hallmarks of cancer. For some time, it has been clear that key mutations may be used as both prognostic and predictive biomarkers, the best-known examples being the presence of germline BRCA1 or BRCA2 mutations, which are not only associated with improved prognosis in ovarian cancer, but are also predictive of response to poly(ADP-ribose) polymerase (PARP) inhibitors. Although biomarkers as specific and powerful as these are rare in human malignancies, next-generation sequencing and improved bioinformatic analyses are revealing mutational signatures, i.e. broader patterns of alterations in the cancer genome that have the power to reveal information about underlying driver mutational processes. Thus, the cancer genome can act as a stratification factor in clinical trials and, ultimately, will be used to drive personalized treatment decisions. In this review, we use ovarian high-grade serous carcinoma (HGSC) as an example of a disease of extreme genomic complexity that is marked by widespread copy number alterations, but that lacks powerful driver oncogene mutations. Understanding of the genomics of HGSC has led to the routine introduction of germline and somatic BRCA1/2 testing, as well as testing of mutations in other homologous recombination genes, widening the range of patients who may benefit from PARP inhibitors. We will discuss how whole genome-wide analyses, including loss of heterozygosity quantification and whole genome sequencing, may extend this paradigm to allow all patients to benefit from effective targeted therapies. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Genomic signatures as predictive biomarkers of homologous recombination deficiency in ovarian cancer

DNA repair deficiency is a common hallmark of many cancers and is increasingly recognised as a target for cancer therapeutics. Selecting patients for these treatments requires a functional assessment of multiple redundant DNA repair pathways. With the advent of whole-genome sequencing of cancer genomes, it is increasingly recognised that multiple signatures of mutational and chromosomal alterations can be correlated with specific DNA repair defects. The clinical relevance of this approach is underlined by the use of poly-(ADP-ribose) polymerase inhibitors (PARPi) in homologous recombination (HR) deficient high-grade serous ovarian cancers. Beyond deleterious mutations in HR-related genes such as BRCA1/2, it is recognised that HR deficiency endows ovarian cancers with specific signatures of base substitutions and structural chromosomal variation. Multiple metrics quantifying loss-of-heterozygosity (LOH) events were proposed and implemented in trials with PARPi. However, it was shown that some of the HR-deficient cases, i.e. CDK12-mutated tumours, were not associated with high LOH-based scores, but with distinct patterns of genomic alterations such as tandem duplication. Therefore, more complex signatures of structural genomic variation were identified and quantified. Ultimately, optimal prediction models for treatments targeting DNA repair will need to integrate multiples of these genomic signatures and will also need to assess multiple resistance mechanisms such as genomic reversion events that partially or fully re-activate DNA repair.

Intratumoral heterogeneity and subclonal diversification of early breast cancer

Heterogeneity has long been recognized as a feature of some primary breast cancers manifesting as mixed histopathological subtypes or variable expression of the therapeutic targets ER, PgR and HER2. The recent emergence of next generation sequencing (NGS) technologies has revolutionized our understanding of the extent and nature of subclonal diversification. Careful examination of primary breast cancers often reveals multiple genomically distinct subclones that may contain driver alterations that follow spatial patterns of segregation. Subclonality is of clinical relevance as it forms the substrate of selection and can give rise to aggressive clinical features such as invasiveness, metastasis and treatment resistance. However, spatial and temporal intra-tumoral heterogeneity pose fundamental challenges to representative sampling and consequently the feasibility of a personalized medicine approach. Fundamental clinical and biological questions are starting to be addressed by applying NGS to the study of intra-tumoral heterogeneity and the insights that it provides should be used to better inform the prospective design of clinico-genomics trials.

An Organismal CNV Mutator Phenotype Restricted to Early Human Development

De novo copy number variants (dnCNVs) arising at multiple loci in a personal genome have usually been considered to reflect cancer somatic genomic instabilities. We describe a multiple dnCNV (MdnCNV) phenomenon in which individuals with genomic disorders carry five to ten constitutional dnCNVs. These CNVs originate from independent formation incidences, are predominantly tandem duplications or complex gains, exhibit breakpoint junction features reminiscent of replicative repair, and show increased de novo point mutations flanking the rearrangement junctions. The active CNV mutation shower appears to be restricted to a transient perizygotic period. We propose that a defect in the CNV formation process is responsible for the "CNV-mutator state," and this state is dampened after early embryogenesis. The constitutional MdnCNV phenomenon resembles chromosomal instability in various cancers. Investigations of this phenomenon may provide unique access to understanding genomic disorders, structural variant mutagenesis, human evolution, and cancer biology.

[On the possibility to determine genetic identity of the tissues with malignant tumours imbedded in paraffin blocks]

The results of analysis of the literature data were used to develop the forensic medical criteria for the assessment of the suitability of paraffin blocks containing the imbedded malignant tumours for the genetic identification of the tissues. The forensic medical criteria and the algorithm for the preliminary characteristic of the material of interest were proposed to avoid the potential errors. It is not recommended to use gastrointestinal carcinomas, breast tumours, and poorly differentiated ovarian tumours. Also unsuitable is the material formerly exposed to radio- and chemotherapeutic agents or paraffin blocks stored during more than 5-7 years. In the doubtful cases, immunohistochemical studies must be carried out to confirm microsatellite instability. Moreover, the tumour genotype and DNA composition from the patients' blood should be confirmed.

The tandem duplicator phenotype as a distinct genomic configuration in cancer

Next-generation sequencing studies have revealed genome-wide structural variation patterns in cancer, such as chromothripsis and chromoplexy, that do not engage a single discernable driver mutation, and whose clinical relevance is unclear. We devised a robust genomic metric able to identify cancers with a chromotype called tandem duplicator phenotype (TDP) characterized by frequent and distributed tandem duplications (TDs). Enriched only in triple-negative breast cancer (TNBC) and in ovarian, endometrial, and liver cancers, TDP tumors conjointly exhibit tumor protein p53 (TP53) mutations, disruption of breast cancer 1 (BRCA1), and increased expression of DNA replication genes pointing at rereplication in a defective checkpoint environment as a plausible causal mechanism. The resultant TDs in TDP augment global oncogene expression and disrupt tumor suppressor genes. Importantly, the TDP strongly correlates with cisplatin sensitivity in both TNBC cell lines and primary patient-derived xenografts. We conclude that the TDP is a common cancer chromotype that coordinately alters oncogene/tumor suppressor expression with potential as a marker for chemotherapeutic response.

Ovarian Cancers Harboring Inactivating Mutations in CDK12 Display a Distinct Genomic Instability Pattern Characterized by Large Tandem Duplications

CDK12 is a recurrently mutated gene in serous ovarian carcinoma, whose downregulation is associated with impaired expression of DNA damage repair genes and subsequent hypersensitivity to DNA-damaging agents and PARP1/2 inhibitors. In this study, we investigated the genomic landscape associated with CDK12 inactivation in patients with serous ovarian carcinoma. We show that CDK12 loss was consistently associated with a particular genomic instability pattern characterized by hundreds of tandem duplications of up to 10 megabases (Mb) in size. Tandem duplications were characterized by a bimodal (∼0.3 and ∼3 Mb) size distribution and overlapping microhomology at the breakpoints. This genomic instability, denoted as the CDK12 TD-plus phenotype, is remarkably distinct from other alteration patterns described in breast and ovarian cancers. The CDK12 TD-plus phenotype was associated with a greater than 10% gain in genomic content and occurred at a 3% to 4% rate in The Cancer Genome Atlas-derived and in-house cohorts of patients with serous ovarian carcinoma. Moreover, CDK12-inactivating mutations together with the TD-plus phenotype were also observed in prostate cancers. Our finding provides new insight toward deciphering the function of CDK12 in genome maintenance and oncogenesis. Cancer Res; 76(7); 1882-91. ©2016 AACR.

Deciphering the Code of the Cancer Genome: Mechanisms of Chromosome Rearrangement

Chromosome rearrangement plays a causal role in tumorigenesis by contributing to the inactivation of tumor suppressor genes, the dysregulated expression or amplification of oncogenes and the generation of novel gene fusions. Chromosome breaks are important intermediates in this process. How, when and where these breaks arise and the specific mechanisms engaged in their repair strongly influence the resulting patterns of chromosome rearrangement. Here, we review recent progress in understanding how certain distinctive features of the cancer genome, including clustered mutagenesis, tandem segmental duplications, complex breakpoints, chromothripsis, chromoplexy and chromoanasynthesis may arise.

Reduced accumulation of platinum drugs is not observed in drug-resistant ovarian cancer cell lines derived from cisplatin-treated patients

The resistance of ovarian cancer towards front-line chemotherapy, usually cisplatin or carboplatin in combination with paclitaxel or docetaxel, remains a major clinical challenge. Resistance to these agents has been largely studied using cell lines selected for resistance to agents in vitro. We examined a series of paired cell lines derived from patients with ovarian cancer prior to chemotherapy (PEO1, PEO4, PEO14 and PEA1), and following the acquisition of resistance to a platinum-based chemotherapy regimen (PEO6, PEO23 and PEA2, respectively). All resistant patient lines showed resistance to cisplatin (2-5-fold), but this did not correspond with lowered accumulation. No general cross-resistance was observed for oxaliplatin, paclitaxel or docetaxel, and paclitaxel accumulation was not affected. PEO1 cells carrying BRCA2 mutations were hypersensitive to the PARP inhibitors olaparib and velaparib, but all other cell lines expressing functional forms of BRCA2 were less sensitive. While reduced drug accumulation was not observed, we believe these pairs of lines are of use to researchers studying Pt drug resistance and experimental therapeutics against drug-resistant ovarian cancer.

Mobile element insertions are frequent in oesophageal adenocarcinomas and can mislead paired-end sequencing analysis

BACKGROUND

Mobile elements are active in the human genome, both in the germline and cancers, where they can mutate driver genes.

RESULTS

While analysing whole genome paired-end sequencing of oesophageal adenocarcinomas to find genomic rearrangements, we identified three ways in which new mobile element insertions appear in the data, resembling translocation or insertion junctions: inserts where unique sequence has been transduced by an L1 (Long interspersed element 1) mobile element; novel inserts that are confidently, but often incorrectly, mapped by alignment software to L1s or polyA tracts in the reference sequence; and a combination of these two ways, where different sequences within one insert are mapped to different loci. We identified nine unique sequences that were transduced by neighbouring L1s, both L1s in the reference genome and L1s not present in the reference. Many of the resulting inserts were small fragments that include little or no recognisable mobile element sequence. We found 6 loci in the reference genome to which sequence reads from inserts were frequently mapped, probably erroneously, by alignment software: these were either L1 sequence or particularly long polyA runs. Inserts identified from such apparent rearrangement junctions averaged 16 inserts/tumour, range 0-153 insertions in 43 tumours. However, many inserts would not be detected by mapping the sequences to the reference genome, because they do not include sufficient mappable sequence. To estimate total somatic inserts we searched for polyA sequences that were not present in the matched normal or other normals from the same tumour batch, and were not associated with known polymorphisms. Samples of these candidate inserts were verified by sequencing across them or manual inspection of surrounding reads: at least 85 % were somatic and resembled L1-mediated events, most including L1Hs sequence. Approximately 100 such inserts were detected per tumour on average (range zero to approximately 700).

CONCLUSIONS

Somatic mobile elements insertions are abundant in these tumours, with over 75 % of cases having a number of novel inserts detected. The inserts create a variety of problems for the interpretation of paired-end sequencing data.

Verifying the markers of ovarian cancer using RNA-seq data

Markers associated with diagnosis, presentation and potential therapeutic targets have received widespread attention in ovarian cancer research in the past few years. However, the majority of these markers have been investigated individually, and the changes in expression and the association between them are rarely documented. Next‑generation sequencing, also termed RNA-seq when the sequencing targets are cDNAs, can provide a whole blueprint of the transcriptome of a specific tissue. In the present study, RNA-seq data of human ovarian cancer samples were used to verify the expression of known markers and to identify the association between them. A total of 563 markers associated with ovarian cancer were retrieved from the database of the National Center of Biotechnology Information, and used as the target markers. The transcriptome of the ovarian tissue of four different tumors, containing tumor presentation and recurrence stages, were sequenced using the Illumina GAII platform. Approximately 85.97% markers were expressed of the total 563 markers, and the majority of them were involved in pathways associated with cancer, signaling and infection. In total, 85 markers were found to be aberrantly expressed in tumor cells from patients with ovarian cancer who had recurrences, including 33 upregulated markers at the recurrence stage. Therefore, they may have roles ovarian tumor due to their aberrant expression. Differentially expressed markers and the associations between them can be assessed by examining the RNA-seq data. These findings may provide novel information for further studies on ovarian cancer.

Next-generation sequencing of duplication CNVs reveals that most are tandem and some create fusion genes at breakpoints

Interpreting the genomic and phenotypic consequences of copy-number variation (CNV) is essential to understanding the etiology of genetic disorders. Whereas deletion CNVs lead obviously to haploinsufficiency, duplications might cause disease through triplosensitivity, gene disruption, or gene fusion at breakpoints. The mutational spectrum of duplications has been studied at certain loci, and in some cases these copy-number gains are complex chromosome rearrangements involving triplications and/or inversions. However, the organization of clinically relevant duplications throughout the genome has yet to be investigated on a large scale. Here we fine-mapped 184 germline duplications (14.7 kb-25.3 Mb; median 532 kb) ascertained from individuals referred for diagnostic cytogenetics testing. We performed next-generation sequencing (NGS) and whole-genome sequencing (WGS) to sequence 130 breakpoints from 112 subjects with 119 CNVs and found that most (83%) were tandem duplications in direct orientation. The remainder were triplications embedded within duplications (8.4%), adjacent duplications (4.2%), insertional translocations (2.5%), or other complex rearrangements (1.7%). Moreover, we predicted six in-frame fusion genes at sequenced duplication breakpoints; four gene fusions were formed by tandem duplications, one by two interconnected duplications, and one by duplication inserted at another locus. These unique fusion genes could be related to clinical phenotypes and warrant further study. Although most duplications are positioned head-to-tail adjacent to the original locus, those that are inverted, triplicated, or inserted can disrupt or fuse genes in a manner that might not be predicted by conventional copy-number assays. Therefore, interpreting the genetic consequences of duplication CNVs requires breakpoint-level analysis.

Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis

BACKGROUND

The major clinical challenge in the treatment of high-grade serous ovarian cancer (HGSOC) is the development of progressive resistance to platinum-based chemotherapy. The objective of this study was to determine whether intra-tumour genetic heterogeneity resulting from clonal evolution and the emergence of subclonal tumour populations in HGSOC was associated with the development of resistant disease.

METHODS AND FINDINGS

Evolutionary inference and phylogenetic quantification of heterogeneity was performed using the MEDICC algorithm on high-resolution whole genome copy number profiles and selected genome-wide sequencing of 135 spatially and temporally separated samples from 14 patients with HGSOC who received platinum-based chemotherapy. Samples were obtained from the clinical CTCR-OV03/04 studies, and patients were enrolled between 20 July 2007 and 22 October 2009. Median follow-up of the cohort was 31 mo (interquartile range 22-46 mo), censored after 26 October 2013. Outcome measures were overall survival (OS) and progression-free survival (PFS). There were marked differences in the degree of clonal expansion (CE) between patients (median 0.74, interquartile range 0.66-1.15), and dichotimization by median CE showed worse survival in CE-high cases (PFS 12.7 versus 10.1 mo, p = 0.009; OS 42.6 versus 23.5 mo, p = 0.003). Bootstrap analysis with resampling showed that the 95% confidence intervals for the hazard ratios for PFS and OS in the CE-high group were greater than 1.0. These data support a relationship between heterogeneity and survival but do not precisely determine its effect size. Relapsed tissue was available for two patients in the CE-high group, and phylogenetic analysis showed that the prevalent clonal population at clinical recurrence arose from early divergence events. A subclonal population marked by a NF1 deletion showed a progressive increase in tumour allele fraction during chemotherapy.

CONCLUSIONS

This study demonstrates that quantitative measures of intra-tumour heterogeneity may have predictive value for survival after chemotherapy treatment in HGSOC. Subclonal tumour populations are present in pre-treatment biopsies in HGSOC and can undergo expansion during chemotherapy, causing clinical relapse.

Integrated analysis of whole-genome paired-end and mate-pair sequencing data for identifying genomic structural variations in multiple myeloma

We present a pipeline to perform integrative analysis of mate-pair (MP) and paired-end (PE) genomic DNA sequencing data. Our pipeline detects structural variations (SVs) by taking aligned sequencing read pairs as input and classifying these reads into properly paired and discordantly paired categories based on their orientation and inferred insert sizes. Recurrent SV was identified from the discordant read pairs. Our pipeline takes into account genomic annotation and genome repetitive element information to increase detection specificity. Application of our pipeline to whole-genome MP and PE sequencing data from three multiple myeloma cell lines (KMS11, MM.1S, and RPMI8226) recovered known SVs, such as heterozygous TRAF3 deletion, as well as a novel experimentally validated SPI1 - ZNF287 inter-chromosomal rearrangement in the RPMI8226 cell line.

Systems consequences of amplicon formation in human breast cancer

Chromosomal structural variations play an important role in determining the transcriptional landscape of human breast cancers. To assess the nature of these structural variations, we analyzed eight breast tumor samples with a focus on regions of gene amplification using mate-pair sequencing of long-insert genomic DNA with matched transcriptome profiling. We found that tandem duplications appear to be early events in tumor evolution, especially in the genesis of amplicons. In a detailed reconstruction of events on chromosome 17, we found large unpaired inversions and deletions connect a tandemly duplicated ERBB2 with neighboring 17q21.3 amplicons while simultaneously deleting the intervening BRCA1 tumor suppressor locus. This series of events appeared to be unusually common when examined in larger genomic data sets of breast cancers albeit using approaches with lesser resolution. Using siRNAs in breast cancer cell lines, we showed that the 17q21.3 amplicon harbored a significant number of weak oncogenes that appeared consistently coamplified in primary tumors. Down-regulation of BRCA1 expression augmented the cell proliferation in ERBB2-transfected human normal mammary epithelial cells. Coamplification of other functionally tested oncogenic elements in other breast tumors examined, such as RIPK2 and MYC on chromosome 8, also parallel these findings. Our analyses suggest that structural variations efficiently orchestrate the gain and loss of cancer gene cassettes that engage many oncogenic pathways simultaneously and that such oncogenic cassettes are favored during the evolution of a cancer.

Heterogeneity in the inter-tumor transcriptome of high risk prostate cancer

BACKGROUND

Genomic analyses of hundreds of prostate tumors have defined a diverse landscape of mutations and genome rearrangements, but the transcriptomic effect of this complexity is less well understood, particularly at the individual tumor level. We selected a cohort of 25 high-risk prostate tumors, representing the lethal phenotype, and applied deep RNA-sequencing and matched whole genome sequencing, followed by detailed molecular characterization.

RESULTS

Ten tumors were exposed to neo-adjuvant hormone therapy and expressed marked evidence of therapy response in all except one extreme case, which demonstrated early resistance via apparent neuroendocrine transdifferentiation. We observe high inter-tumor heterogeneity, including unique sets of outlier transcripts in each tumor. Interestingly, outlier expression converged on druggable cellular pathways associated with cell cycle progression, translational control or immune regulation, suggesting distinct contemporary pathway affinity and a mechanism of tumor stratification. We characterize hundreds of novel fusion transcripts, including a high frequency of ETS fusions associated with complex genome rearrangements and the disruption of tumor suppressors. Remarkably, several tumors express unique but potentially-oncogenic non-ETS fusions, which may contribute to the phenotype of individual tumors, and have significance for disease progression. Finally, one ETS-negative tumor has a striking tandem duplication genotype which appears to be highly aggressive and present at low recurrence in ETS-negative prostate cancer, suggestive of a novel molecular subtype.

CONCLUSIONS

The multitude of rare genomic and transcriptomic events detected in a high-risk tumor cohort offer novel opportunities for personalized oncology and their convergence on key pathways and functions has broad implications for precision medicine.

Recurrent ESR1-CCDC170 rearrangements in an aggressive subset of oestrogen receptor-positive breast cancers

Characterizing the genetic alterations leading to the more aggressive forms of estrogen receptor positive (ER+) breast cancers are of critical significance in breast cancer management. Here we identify recurrent rearrangements between estrogen receptor gene ESR1 and its neighbor CCDC170, which are enriched in the more aggressive and endocrine-resistant luminal-B tumors, through large-scale analyses of breast cancer transcriptome and copy number alterations. Further screening of 200 ER+ breast cancers identifies eight ESR1-CCDC170 positive tumors. These fusions encode N-terminally truncated CCDC170 proteins (ΔCCDC170). When introduced into ER+ breast cancer cells, ΔCCDC170 leads to markedly increased cell motility and anchorage-independent growth, reduced endocrine sensitivity, and enhanced xenograft tumor formation. Mechanistic studies suggest that ΔCCDC170 engages Gab1 signalosome to potentiate growth factor signaling and enhance cell motility. Together, this study identifies neoplastic ESR1-CCDC170 fusions in a more aggressive subset of ER+ breast cancer, which suggests a new concept of ER pathobiology in breast cancer.

Mechanisms underlying mutational signatures in human cancers

The collective somatic mutations observed in a cancer are the outcome of multiple mutagenic processes that have been operative over the lifetime of a patient. Each process leaves a characteristic imprint--a mutational signature--on the cancer genome, which is defined by the type of DNA damage and DNA repair processes that result in base substitutions, insertions and deletions or structural variations. With the advent of whole-genome sequencing, researchers are identifying an increasing array of these signatures. Mutational signatures can be used as a physiological readout of the biological history of a cancer and also have potential use for discerning ongoing mutational processes from historical ones, thus possibly revealing new targets for anticancer therapies.

Phylogenetic quantification of intra-tumour heterogeneity

Intra-tumour genetic heterogeneity is the result of ongoing evolutionary change within each cancer. The expansion of genetically distinct sub-clonal populations may explain the emergence of drug resistance, and if so, would have prognostic and predictive utility. However, methods for objectively quantifying tumour heterogeneity have been missing and are particularly difficult to establish in cancers where predominant copy number variation prevents accurate phylogenetic reconstruction owing to horizontal dependencies caused by long and cascading genomic rearrangements. To address these challenges, we present MEDICC, a method for phylogenetic reconstruction and heterogeneity quantification based on a Minimum Event Distance for Intra-tumour Copy-number Comparisons. Using a transducer-based pairwise comparison function, we determine optimal phasing of major and minor alleles, as well as evolutionary distances between samples, and are able to reconstruct ancestral genomes. Rigorous simulations and an extensive clinical study show the power of our method, which outperforms state-of-the-art competitors in reconstruction accuracy, and additionally allows unbiased numerical quantification of tumour heterogeneity. Accurate quantification and evolutionary inference are essential to understand the functional consequences of tumour heterogeneity. The MEDICC algorithms are independent of the experimental techniques used and are applicable to both next-generation sequencing and array CGH data.

Large inverted duplications in the human genome form via a fold-back mechanism

Inverted duplications are a common type of copy number variation (CNV) in germline and somatic genomes. Large duplications that include many genes can lead to both neurodevelopmental phenotypes in children and gene amplifications in tumors. There are several models for inverted duplication formation, most of which include a dicentric chromosome intermediate followed by breakage-fusion-bridge (BFB) cycles, but the mechanisms that give rise to the inverted dicentric chromosome in most inverted duplications remain unknown. Here we have combined high-resolution array CGH, custom sequence capture, next-generation sequencing, and long-range PCR to analyze the breakpoints of 50 nonrecurrent inverted duplications in patients with intellectual disability, autism, and congenital anomalies. For half of the rearrangements in our study, we sequenced at least one breakpoint junction. Sequence analysis of breakpoint junctions reveals a normal-copy disomic spacer between inverted and non-inverted copies of the duplication. Further, short inverted sequences are present at the boundary of the disomic spacer and the inverted duplication. These data support a mechanism of inverted duplication formation whereby a chromosome with a double-strand break intrastrand pairs with itself to form a “fold-back” intermediate that, after DNA replication, produces a dicentric inverted chromosome with a disomic spacer corresponding to the site of the fold-back loop. This process can lead to inverted duplications adjacent to terminal deletions, inverted duplications juxtaposed to translocations, and inverted duplication ring chromosomes.

Chromosomes with large inverted duplications and terminal deletions cause neurodevelopmental disorders in children. These chromosome rearrangements typically involve hundreds of genes, leading to significant changes in gene dosage. Though inverted duplications adjacent to terminal deletions are a relatively common type of chromosomal imbalance, the DNA repair mechanism responsible for their formation is not known. In this study, we analyze the genomic organization of the largest collection of human inverted duplications. We find a common inverted duplication structure, consistent with a model that requires DNA to fold back and form a dicentric chromosome intermediate. These data provide insight into the formation of nonrecurrent inverted duplications in the human genome.

The causes and consequences of genetic heterogeneity in cancer evolution

Recent studies have revealed extensive genetic diversity both between and within tumours. This heterogeneity affects key cancer pathways, driving phenotypic variation, and poses a significant challenge to personalized cancer medicine. A major cause of genetic heterogeneity in cancer is genomic instability. This instability leads to an increased mutation rate and can shape the evolution of the cancer genome through a plethora of mechanisms. By understanding these mechanisms we can gain insight into the common pathways of tumour evolution that could support the development of future therapeutic strategies.

Ovarian cancer evolution through stochastic genome alterations: defining the genomic role in ovarian cancer

Ovarian cancer is the fifth leading cause of death among women worldwide. Characterized by complex etiology and multi-level heterogeneity, its origins are not well understood. Intense research efforts over the last decade have furthered our knowledge by identifying multiple risk factors that are associated with the disease. However, it is still unclear how genetic heterogeneity contributes to tumor formation, and more specifically, how genome-level heterogeneity acts as the key driving force of cancer evolution. Most current genomic approaches are based on 'average molecular profiling.' While effective for data generation, they often fail to effectively address the issue of high level heterogeneity because they mask variation that exists in a cell population. In this synthesis, we hypothesize that genome-mediated cancer evolution can effectively explain diverse factors that contribute to ovarian cancer. In particular, the key contribution of genome replacement can be observed during major transitions of ovarian cancer evolution including cellular immortalization, transformation, and malignancy. First, we briefly review major updates in the literature, and illustrate how current gene-mediated research will offer limited insight into cellular heterogeneity and ovarian cancer evolution. We next explain a holistic framework for genome-based ovarian cancer evolution and apply it to understand the genomic dynamics of a syngeneic ovarian cancer mouse model. Finally, we employ single cell assays to further test our hypothesis, discuss some predictions, and report some recent findings.

Cross-species array comparative genomic hybridization identifies novel oncogenic events in zebrafish and human embryonal rhabdomyosarcoma

Human cancer genomes are highly complex, making it challenging to identify specific drivers of cancer growth, progression, and tumor maintenance. To bypass this obstacle, we have applied array comparative genomic hybridization (array CGH) to zebrafish embryonal rhabdomyosaroma (ERMS) and utilized cross-species comparison to rapidly identify genomic copy number aberrations and novel candidate oncogenes in human disease. Zebrafish ERMS contain small, focal regions of low-copy amplification. These same regions were commonly amplified in human disease. For example, 16 of 19 chromosomal gains identified in zebrafish ERMS also exhibited focal, low-copy gains in human disease. Genes found in amplified genomic regions were assessed for functional roles in promoting continued tumor growth in human and zebrafish ERMS – identifying critical genes associated with tumor maintenance. Knockdown studies identified important roles for Cyclin D2 (CCND2), Homeobox Protein C6 (HOXC6) and PlexinA1 (PLXNA1) in human ERMS cell proliferation. PLXNA1 knockdown also enhanced differentiation, reduced migration, and altered anchorage-independent growth. By contrast, chemical inhibition of vascular endothelial growth factor (VEGF) signaling reduced angiogenesis and tumor size in ERMS-bearing zebrafish. Importantly, VEGFA expression correlated with poor clinical outcome in patients with ERMS, implicating inhibitors of the VEGF pathway as a promising therapy for improving patient survival. Our results demonstrate the utility of array CGH and cross-species comparisons to identify candidate oncogenes essential for the pathogenesis of human cancer.

Cancer is a complex genetic disease that is often associated with regional gains and losses of genomic DNA segments. These changes result in aberrant gene expression and drive continued tumor growth. Because amplified and deleted DNA segments tend to span large regions of chromosomes, it has been challenging to identify the genes that are required for continued tumor growth and progression. Array comparative genomic hybridization (array CGH) is an effective technology in identifying abnormal copy number variations in cancer genomes. In this study, array CGH was used in a zebrafish model of embryonal rhabdomyosarcoma - a pediatric muscle tumor. Our work shows that the zebrafish cancer genome contains a small number of recurrent DNA copy number changes, which are also commonly amplified in the human disease. Moreover, these chromosomal regions are small, facilitating rapid identification of candidate oncogenes. A subset of genes identified in zebrafish array CGH was prioritized for functional characterization in human ERMS, identifying evolutionarily conserved pathways that regulate proliferation, migration, differentiation, and neovascularization. Our results demonstrate the broad utility of cross-species array CGH comparisons of human and zebrafish cancer and provide a much needed discovery platform for identifying critical cancer-causing genes in a wide range of malignancies.

New insights and clinical advancements in cellular oncology

The first joint meeting of the International Society for Cellular Oncology (ISCO) and the European Workshop on Cytogenetics and Molecular Genetics of Solid Tumors (EWCMST), organized by Bauke Ylstra, Juan Cigudosa and Nick Gilbert, was held from 4 to 8 March, 2012 in Palma de Mallorca, Spain. This meeting provided a novel and unique opportunity to jointly present the latest updates on the genetics of cancer and its implications for diagnosis, prognosis and therapy, now and in the future. Various aspects were highlighted, including the identification of effective therapeutic targets, the role of cellular senescence in tumor development and therapy, chromosome translocations in leukemias and solid tumors, mechanisms underlying fragile sites and chromosome instability, tumor-associated ‘omics’ landscapes, genetic and epidemiologic risk factors, the role of tissue and cancer stem cells, angiogenesis and the tumor micro-environment, and the epigenetics of cancer. In this report, new insights and clinical advancements related to these various topics are provided, based on information presented at the meeting.

A mechanism of gene amplification driven by small DNA fragments

DNA amplification is a molecular process that increases the copy number of a chromosomal tract and often causes elevated expression of the amplified gene(s). Although gene amplification is frequently observed in cancer and other degenerative disorders, the molecular mechanisms involved in the process of DNA copy number increase remain largely unknown. We hypothesized that small DNA fragments could be the trigger of DNA amplification events. Following our findings that small fragments of DNA in the form of DNA oligonucleotides can be highly recombinogenic, we have developed a system in the yeast Saccharomyces cerevisiae to capture events of chromosomal DNA amplification initiated by small DNA fragments. Here we demonstrate that small DNAs can amplify a chromosomal region, generating either tandem duplications or acentric extrachromosomal DNA circles. Small fragment-driven DNA amplification (SFDA) occurs with a frequency that increases with the length of homology between the small DNAs and the target chromosomal regions. SFDA events are triggered even by small single-stranded molecules with as little as 20-nt homology with the genomic target. A double-strand break (DSB) external to the chromosomal amplicon region stimulates the amplification event up to a factor of 20 and favors formation of extrachromosomal circles. SFDA is dependent on Rad52 and Rad59, partially dependent on Rad1, Rad10, and Pol32, and independent of Rad51, suggesting a single-strand annealing mechanism. Our results reveal a novel molecular model for gene amplification, in which small DNA fragments drive DNA amplification and define the boundaries of the amplicon region. As DNA fragments are frequently found both inside cells and in the extracellular environment, such as the serum of patients with cancer or other degenerative disorders, we propose that SFDA may be a common mechanism for DNA amplification in cancer cells, as well as a more general cause of DNA copy number variation in nature.

Evolution of the cancer genome

The advent of massively parallel sequencing technologies has allowed the characterization of cancer genomes at an unprecedented resolution. Investigation of the mutational landscape of tumours is providing new insights into cancer genome evolution, laying bare the interplay of somatic mutation, adaptation of clones to their environment and natural selection. These studies have demonstrated the extent of the heterogeneity of cancer genomes, have allowed inferences to be made about the forces that act on nascent cancer clones as they evolve and have shown insight into the mutational processes that generate genetic variation. Here we review our emerging understanding of the dynamic evolution of the cancer genome and of the implications for basic cancer biology and the development of antitumour therapy.

Structural mutations in cancer: mechanistic and functional insights

Next-generation sequencing (NGS) has enabled the comprehensive and precise identification of many somatic structural mutations in cancer. Analyses integrating point mutation information with data on rearrangements and copy number variation have revealed a higher-order organization of the seemingly random genetic events that lead to cancer. These meta-analyses provide a more refined view of the mutational mechanisms, genomic evolution, and combinations of mutations that contribute to tumorigenesis. Structural mutations, or genome-scale rearrangements of segments of DNA, may play a hitherto unappreciated role in cancer through their ability to move blocks of adjacent genes simultaneously, leading to concurrent oncogenic events. Moreover, whole-genome sequencing (WGS) data from tumors have revealed global rearrangements, such as those seen in the tandem duplicator phenotype and in chromothripsis, suggesting that massive rearrangements are a specific cancer phenotype. Taken together, the emerging data suggest that the chromosome structure itself functions as a systems oncogenic organizer.

Tandem duplication of chromosomal segments is common in ovarian and breast cancer genomes

The application of paired-end next generation sequencing approaches has made it possible to systematically characterize rearrangements of the cancer genome to base-pair level. Utilizing this approach, we report the first detailed analysis of ovarian cancer rearrangements, comparing high-grade serous and clear cell cancers, and these histotypes with other solid cancers. Somatic rearrangements were systematically characterized in eight high-grade serous and five clear cell ovarian cancer genomes and we report here the identification of > 600 somatic rearrangements. Recurrent rearrangements of the transcriptional regulator gene, TSHZ3, were found in three of eight serous cases. Comparison to breast, pancreatic and prostate cancer genomes revealed that a subset of ovarian cancers share a marked tandem duplication phenotype with triple-negative breast cancers. The tandem duplication phenotype was not linked to BRCA1/2 mutation, suggesting that other common mechanisms or carcinogenic exposures are operative. High-grade serous cancers arising in women with germline BRCA1 or BRCA2 mutation showed a high frequency of small chromosomal deletions. These findings indicate that BRCA1/2 germline mutation may contribute to widespread structural change and that other undefined mechanism(s), which are potentially shared with triple-negative breast cancer, promote tandem chromosomal duplications that sculpt the ovarian cancer genome.

Reconstructing cancer genomes from paired-end sequencing data

Background

A cancer genome is derived from the germline genome through a series of somatic mutations. Somatic structural variants - including duplications, deletions, inversions, translocations, and other rearrangements - result in a cancer genome that is a scrambling of intervals, or "blocks" of the germline genome sequence. We present an efficient algorithm for reconstructing the block organization of a cancer genome from paired-end DNA sequencing data.

Results

By aligning paired reads from a cancer genome - and a matched germline genome, if available - to the human reference genome, we derive: (i) a partition of the reference genome into intervals; (ii) adjacencies between these intervals in the cancer genome; (iii) an estimated copy number for each interval. We formulate the Copy Number and Adjacency Genome Reconstruction Problem of determining the cancer genome as a sequence of the derived intervals that is consistent with the measured adjacencies and copy numbers. We design an efficient algorithm, called Paired-end Reconstruction of Genome Organization (PREGO), to solve this problem by reducing it to an optimization problem on an interval-adjacency graph constructed from the data. The solution to the optimization problem results in an Eulerian graph, containing an alternating Eulerian tour that corresponds to a cancer genome that is consistent with the sequencing data. We apply our algorithm to five ovarian cancer genomes that were sequenced as part of The Cancer Genome Atlas. We identify numerous rearrangements, or structural variants, in these genomes, analyze reciprocal vs. non-reciprocal rearrangements, and identify rearrangements consistent with known mechanisms of duplication such as tandem duplications and breakage/fusion/bridge (B/F/B) cycles.

Conclusions

We demonstrate that PREGO efficiently identifies complex and biologically relevant rearrangements in cancer genome sequencing data. An implementation of the PREGO algorithm is available at http://compbio.cs.brown.edu/software/.