Identification of somatically acquired rearrangements in cancer using genome-wide massively parallel paired-end sequencing

Genomic scars as biomarkers of homologous recombination deficiency and drug response in breast and ovarian cancers

Poly (ADP-ribose) polymerase (PARP) inhibitors and platinum-based chemotherapies have been found to be particularly effective in tumors that harbor deleterious germline or somatic mutations in the BRCA1 or BRCA2 genes, the products of which contribute to the conservative homologous recombination repair of DNA double-strand breaks. Nonetheless, several setbacks in clinical trial settings have highlighted some of the issues surrounding the investigation of PARP inhibitors, especially the identification of patients who stand to benefit from such drugs. One potential approach to finding this patient subpopulation is to examine the tumor DNA for evidence of a homologous recombination defect. However, although the genomes of many breast and ovarian cancers are replete with aberrations, the presence of numerous factors able to shape the genomic landscape means that only some of the observed DNA abnormalities are the outcome of a cancer cell’s inability to faithfully repair DNA double-strand breaks. Consequently, recently developed methods for comprehensively capturing the diverse ways in which homologous recombination deficiencies may arise beyond BRCA1/2 mutation have used DNA microarray and sequencing data to account for potentially confounding features in the genome. Scores capturing telomeric allelic imbalance, loss of heterozygosity (LOH) and large scale transition score, as well as the total number of coding mutations are measures that summarize the total burden of certain forms of genomic abnormality. By contrast, other studies have comprehensively catalogued different types of mutational pattern and their relative contributions to a given tumor sample. Although at least one study to explore the use of the LOH scar in a prospective clinical trial of a PARP inhibitor in ovarian cancer is under way, limitations that result in a relatively low positive predictive value for these biomarkers remain. Tumors whose genome has undergone one or more events that restore high-fidelity homologous recombination are likely to be misclassified as double-strand break repair-deficient and thereby sensitive to PARP inhibitors and DNA damaging chemotherapies as a result of prior repair deficiency and its genomic scarring. Therefore, we propose that integration of a genomic scar-based biomarker with a marker of resistance in a high genomic scarring burden context may improve the performance of any companion diagnostic for PARP inhibitors.

Targeting RPL39 and MLF2 reduces tumor initiation and metastasis in breast cancer by inhibiting nitric oxide synthase signaling

We previously described a gene signature for breast cancer stem cells (BCSCs) derived from patient biopsies. Selective shRNA knockdown identified ribosomal protein L39 (RPL39) and myeloid leukemia factor 2 (MLF2) as the top candidates that affect BCSC self-renewal. Knockdown of RPL39 and MLF2 by specific siRNA nanoparticles in patient-derived and human cancer xenografts reduced tumor volume and lung metastases with a concomitant decrease in BCSCs. RNA deep sequencing identified damaging mutations in both genes. These mutations were confirmed in patient lung metastases (n = 53) and were statistically associated with shorter median time to pulmonary metastasis. Both genes affect the nitric oxide synthase pathway and are altered by hypoxia. These findings support that extensive tumor heterogeneity exists within primary cancers; distinct subpopulations associated with stem-like properties have increased metastatic potential.

FIGG: simulating populations of whole genome sequences for heterogeneous data analyses

Background

High-throughput sequencing has become one of the primary tools for investigation of the molecular basis of disease. The increasing use of sequencing in investigations that aim to understand both individuals and populations is challenging our ability to develop analysis tools that scale with the data. This issue is of particular concern in studies that exhibit a wide degree of heterogeneity or deviation from the standard reference genome. The advent of population scale sequencing studies requires analysis tools that are developed and tested against matching quantities of heterogeneous data.

Results

We developed a large-scale whole genome simulation tool, FIGG, which generates large numbers of whole genomes with known sequence characteristics based on direct sampling of experimentally known or theorized variations. For normal variations we used publicly available data to determine the frequency of different mutation classes across the genome. FIGG then uses this information as a background to generate new sequences from a parent sequence with matching frequencies, but different actual mutations. The background can be normal variations, known disease variations, or a theoretical frequency distribution of variations.

Conclusion

In order to enable the creation of large numbers of genomes, FIGG generates simulated sequences from known genomic variation and iteratively mutates each genome separately. The result is multiple whole genome sequences with unique variations that can primarily be used to provide different reference genomes, model heterogeneous populations, and can offer a standard test environment for new analysis algorithms or bioinformatics tools.

Constitutional and somatic rearrangement of chromosome 21 in acute lymphoblastic leukaemia

Changes in gene dosage are a major driver of cancer, known to be caused by a finite, but increasingly well annotated, repertoire of mutational mechanisms. This can potentially generate correlated copy-number alterations across hundreds of linked genes, as exemplified by the 2% of childhood acute lymphoblastic leukaemia (ALL) with recurrent amplification of megabase regions of chromosome 21 (iAMP21). We used genomic, cytogenetic and transcriptional analysis, coupled with novel bioinformatic approaches, to reconstruct the evolution of iAMP21 ALL. Here we show that individuals born with the rare constitutional Robertsonian translocation between chromosomes 15 and 21, rob(15;21)(q10;q10)c, have approximately 2,700-fold increased risk of developing iAMP21 ALL compared to the general population. In such cases, amplification is initiated by a chromothripsis event involving both sister chromatids of the Robertsonian chromosome, a novel mechanism for cancer predisposition. In sporadic iAMP21, breakage-fusion-bridge cycles are typically the initiating event, often followed by chromothripsis. In both sporadic and rob(15;21)c-associated iAMP21, the final stages frequently involve duplications of the entire abnormal chromosome. The end-product is a derivative of chromosome 21 or the rob(15;21)c chromosome with gene dosage optimized for leukaemic potential, showing constrained copy-number levels over multiple linked genes. Thus, dicentric chromosomes may be an important precipitant of chromothripsis, as we show rob(15;21)c to be constitutionally dicentric and breakage-fusion-bridge cycles generate dicentric chromosomes somatically. Furthermore, our data illustrate that several cancer-specific mutational processes, applied sequentially, can coordinate to fashion copy-number profiles over large genomic scales, incrementally refining the fitness benefits of aggregated gene dosage changes.

Deconvolving tumor purity and ploidy by integrating copy number alterations and loss of heterozygosity

MOTIVATION

Next-generation sequencing (NGS) has revolutionized the study of cancer genomes. However, the reads obtained from NGS of tumor samples often consist of a mixture of normal and tumor cells, which themselves can be of multiple clonal types. A prominent problem in the analysis of cancer genome sequencing data is deconvolving the mixture to identify the reads associated with tumor cells or a particular subclone of tumor cells. Solving the problem is, however, challenging because of the so-called 'identifiability problem', where different combinations of tumor purity and ploidy often explain the sequencing data equally well.

RESULTS

We propose a new model to resolve the identifiability problem by integrating two types of sequencing information-somatic copy number alterations and loss of heterozygosity-within a unified probabilistic framework. We derive algorithms to solve our model, and implement them in a software package called PyLOH. We benchmark the performance of PyLOH using both simulated data and 12 breast cancer sequencing datasets and show that PyLOH outperforms existing methods in disambiguating the identifiability problem and estimating tumor purity.

AVAILABILITY AND IMPLEMENTATION

The PyLOH package is written in Python and is publicly available at https://github.com/uci-cbcl/PyLOH.

CONTACT

xhx@ics.uci.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Cross-species analysis of mouse and human cancer genomes

Fundamental advances in our understanding of the human cancer genome have been made over the last five years, driven largely by the development of next-generation sequencing (NGS) technologies. Here we will discuss the tools and technologies that have been used to profile human tumors, how they may be applied to the analysis of the mouse cancer genome, and the results thus far. In addition to mutations that disrupt cancer genes, NGS is also being applied to the analysis of the transcriptome of cancers, and, through the use of techniques such as ChIP-Seq, the protein-DNA landscape is also being revealed. Gaining a comprehensive picture of the mouse cancer genome, at the DNA level and through the analysis of the transcriptome and regulatory landscape, will allow us to "biofilter" for driver genes in more complex human cancers and represents a critical test to determine which mouse cancer models are faithful genetic surrogates of the human disease.

The bright side of transposons in crop evolution

The past decades have revealed an unexpected yet prominent role of so-called 'junk DNA' in the regulation of gene expression, thereby challenging our view of the mechanisms underlying phenotypic evolution. In particular, several mechanisms through which transposable elements (TEs) participate in functional genome diversity have been depicted, bringing to light the 'TEs bright side'. However, the relative contribution of those mechanisms and, more generally, the importance of TE-based polymorphisms on past and present phenotypic variation in crops species remain poorly understood. Here, we review current knowledge on both issues, and discuss how analyses of massively parallel sequencing data combined with statistical methodologies and functional validations will help unravelling the impact of TEs on crop evolution in a near future.

DB2: a probabilistic approach for accurate detection of tandem duplication breakpoints using paired-end reads

Background

With the advent of paired-end high throughput sequencing, it is now possible to identify various types of structural variation on a genome-wide scale. Although many methods have been proposed for structural variation detection, most do not provide precise boundaries for identified variants. In this paper, we propose a new method, Distribution Based detection of Duplication Boundaries (DB²), for accurate detection of tandem duplication breakpoints, an important class of structural variation, with high precision and recall.

Results

Our computational experiments on simulated data show that DB² outperforms state-of-the-art methods in terms of finding breakpoints of tandem duplications, with a higher positive predictive value (precision) in calling the duplications’ presence. In particular, DB²’s prediction of tandem duplications is correct 99% of the time even for very noisy data, while narrowing down the space of possible breakpoints within a margin of 15 to 20 bps on the average. Most of the existing methods provide boundaries in ranges that extend to hundreds of bases with lower precision values. Our method is also highly robust to varying properties of the sequencing library and to the sizes of the tandem duplications, as shown by its stable precision, recall and mean boundary mismatch performance. We demonstrate our method’s efficacy using both simulated paired-end reads, and those generated from a melanoma sample and two ovarian cancer samples. Newly discovered tandem duplications are validated using PCR and Sanger sequencing.

Conclusions

Our method, DB², uses discordantly aligned reads, taking into account the distribution of fragment length to predict tandem duplications along with their breakpoints on a donor genome. The proposed method fine tunes the breakpoint calls by applying a novel probabilistic framework that incorporates the empirical fragment length distribution to score each feasible breakpoint. DB² is implemented in Java programming language and is freely available at http://mendel.gene.cwru.edu/laframboiselab/software.php.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-175) contains supplementary material, which is available to authorized users.

Acetaldehyde and the genome: beyond nuclear DNA adducts and carcinogenesis

The designation of acetaldehyde associated with the consumption of alcoholic beverages as "carcinogenic to humans" (Group 1) by the International Agency for Research on Cancer (IARC) has brought renewed attention to the biological effects of acetaldehyde, as the primary oxidative metabolite of alcohol. Therefore, the overall focus of this review is on acetaldehyde and its direct and indirect effects on the nuclear and mitochondrial genome. We first consider different acetaldehyde-DNA adducts, including a critical assessment of the evidence supporting a role for acetaldehyde-DNA adducts in alcohol related carcinogenesis, and consideration of additional data needed to make a conclusion. We also review recent data on the role of the Fanconi anemia DNA repair pathway in protecting against acetaldehyde genotoxicity and carcinogenicity, as well as teratogenicity. We also review evidence from the older literature that acetaldehyde may impact the genome indirectly, via the formation of adducts with proteins that are themselves critically involved in the maintenance of genetic and epigenetic stability. Finally, we note the lack of information regarding acetaldehyde effects on the mitochondrial genome, which is notable since aldehyde dehydrogenase 2 (ALDH2), the primary acetaldehyde metabolic enzyme, is located in the mitochondrion, and roughly 30% of East Asian individuals are deficient in ALDH2 activity due to a genetic variant in the ALDH2 gene. In summary, a comprehensive understanding of all of the mechanisms by which acetaldehyde impacts the function of the genome has implications not only for alcohol and cancer, but types of alcohol related pathologies as well.

Development of detection method for novel fusion gene using GeneChip exon array

Background

Fusion genes have been recognized to play key roles in oncogenesis. Though, many techniques have been developed for genome-wide analysis of fusion genes, a more efficient method is desired.

Results

We introduced a new method of detecting the novel fusion gene by using GeneChip Exon Array that enables exon expression analysis on a whole-genome scale and TAIL-PCR. To screen genes with abnormal exon expression profiles, we developed computational program, and confirmed that the program was able to search the fusion partner gene using Exon Array data of T-cell acute lymphocytic leukemia (T-ALL) cell lines. It was reported that the T-ALL cell lines, ALL-SIL, BE13 and LOUCY, harbored the fusion gene NUP214-ABL1, NUP214-ABL1 and SET-NUP214, respectively. The program extracted the candidate genes with abnormal exon expression profiles: 1 gene in ALL-SIL, 1 gene in BE13, and 2 genes in LOUCY. The known fusion partner gene NUP214 was included in the genes in ALL-SIL and LOUCY. Thus, we applied the proposed program to the detection of fusion partner genes in other tumors. To discover novel fusion genes, we examined 24 breast cancer cell lines and 20 pancreatic cancer cell lines by using the program. As a result, 20 and 23 candidate genes were obtained for the breast and pancreatic cancer cell lines respectively, and seven genes were selected as the final candidate gene based on information of the EST data base, comparison with normal cell samples and visual inspection of Exon expression profile. Finding of fusion partners for the final candidate genes was tried by TAIL-PCR, and three novel fusion genes were identified.

Conclusions

The usefulness of our detection method was confirmed. Using this method for more samples, it is thought that fusion genes can be identified.

PSCC: sensitive and reliable population-scale copy number variation detection method based on low coverage sequencing

Background

Copy number variations (CNVs) represent an important type of genetic variation that deeply impact phenotypic polymorphisms and human diseases. The advent of high-throughput sequencing technologies provides an opportunity to revolutionize the discovery of CNVs and to explore their relationship with diseases. However, most of the existing methods depend on sequencing depth and show instability with low sequence coverage. In this study, using low coverage whole-genome sequencing (LCS) we have developed an effective population-scale CNV calling (PSCC) method.

Methodology/Principal Findings

In our novel method, two-step correction was used to remove biases caused by local GC content and complex genomic characteristics. We chose a binary segmentation method to locate CNV segments and designed combined statistics tests to ensure the stable performance of the false positive control. The simulation data showed that our PSCC method could achieve 99.7%/100% and 98.6%/100% sensitivity and specificity for over 300 kb CNV calling in the condition of LCS (∼2×) and ultra LCS (∼0.2×), respectively. Finally, we applied this novel method to analyze 34 clinical samples with an average of 2× LCS. In the final results, all the 31 pathogenic CNVs identified by aCGH were successfully detected. In addition, the performance comparison revealed that our method had significant advantages over existing methods using ultra LCS.

Conclusions/Significance

Our study showed that PSCC can sensitively and reliably detect CNVs using low coverage or even ultra-low coverage data through population-scale sequencing.

Next generation sequencing and its application in deciphering head and neck cancer

Head and neck squamous cell carcinoma (HNSCC) are a group of heterogeneous tumours mainly attributable to tobacco use, alcohol consumption and infection with human papillomavirus. Based on the stage of cancer at the time of diagnosis, patients are managed by surgery, radiotherapy, chemotherapy or a combination of these. Early diagnosis usually improves patient prognosis. Since their first commercial application in 2005, next generation sequencing (NGS) platforms are rapidly changing the face of basic science laboratories; however prior to progressing to clinical applications, clinicians should carefully examine currently available data and guidelines for technical and ethical matters concerning NGS. In this review, we compare various commercially available NGS platforms, with special consideration given to their clinical application in the management of HNSCC.

Socrates: identification of genomic rearrangements in tumour genomes by re-aligning soft clipped reads

Motivation: Methods for detecting somatic genome rearrangements in tumours using next-generation sequencing are vital in cancer genomics. Available algorithms use one or more sources of evidence, such as read depth, paired-end reads or split reads to predict structural variants. However, the problem remains challenging due to the significant computational burden and high false-positive or false-negative rates.

Results: In this article, we present Socrates (SOft Clip re-alignment To idEntify Structural variants), a highly efficient and effective method for detecting genomic rearrangements in tumours that uses only split-read data. Socrates has single-nucleotide resolution, identifies micro-homologies and untemplated sequence at break points, has high sensitivity and high specificity and takes advantage of parallelism for efficient use of resources. We demonstrate using simulated and real data that Socrates performs well compared with a number of existing structural variant detection tools.

Availability and implementation: Socrates is released as open source and available from http://bioinf.wehi.edu.au/socrates.

Contact:papenfuss@wehi.edu.au

Supplementary information:Supplementary data are available at Bioinformatics online.

[Next-generation sequencing for lung cancer]

肺癌在生物学上具有侵袭性，并且是癌症相关死亡的主要原因。根据临床特征、预后、对治疗的反应和耐受性，每一例肺癌患者的进展均是独特的。传统上基于毛细管的单基因测序的第一代技术（如Sanger测序法）已被允许大量平行测序且成本更低、通量更高的下一代测序技术（next-generation sequencing, NGS）所替代。与传统方法相比，NGS技术取得显著进步。我们希望这些方法可全面地解释癌症全球图谱，并提供更多信息以满足个体化用药的需求。本综述包括对不同NGS技术的简要说明，NGS在肺癌研究进展中的应用和重要发现的总结，包括对已知靶基因（EGFR 、ALK 和KRAS ）的进一步探索、其它肺癌突变的鉴定和癌症基因组研究的全局协调。

Studying cancer genomics through next-generation DNA sequencing and bioinformatics

Cancer is a complex disease driven by multiple mutations acquired over the lifetime of the cancer cells. These alterations, termed somatic mutations to distinguish them from inherited germline mutations, can include single-nucleotide substitutions, insertions, deletions, copy number alterations, and structural rearrangements. A patient's cancer can contain a combination of these aberrations, and the ability to generate a comprehensive genetic profile should greatly improve patient diagnosis and treatment. Next-generation sequencing has become the tool of choice to uncover multiple cancer mutations from a single tumor source, and the falling costs of this rapid high-throughput technology are encouraging its transition from basic research into a clinical setting. However, the detection of mutations in sequencing data is still an evolving area and cancer genomic data requires some special considerations. This chapter discusses these aspects and gives an overview of current bioinformatics methods for the detection of somatic mutations in cancer sequencing data.

Multilayered molecular profiling supported the monoclonal origin of metastatic renal cell carcinoma

Primary renal cell carcinomas (pRCCs) have a high degree of intratumoral heterogeneity and are composed of multiple distinct subclones. However, it remains largely unknown that whether metastatic renal cell carcinomas (mRCCs) also have startling intratumoral heterogeneity or whether development of mRCCs is due to early dissemination or late diagnosis. To decipher the evolution of mRCC, we analyzed the multilayered molecular profiles of pRCC, local invasion of the vena cava (IVC), and distant metastasis to the brain (MB) from the same patient using whole-genome sequencing, whole-exome sequencing, DNA methylome profiling, and transcriptome sequencing. We found that mRCC had a lower degree of heterogeneity than pRCC and was likely to result from recent clonal expansion of a rare, advantageous subclone. Consequently, some key pathways that are targeted by clinically available drugs showed distinct expression patterns between pRCC and mRCC. From the genetic distances between different tumor subclones, we estimated that the progeny subclone giving rise to distant metastasis took over half a decade to acquire the full potential of metastasis since the birth of the subclone that evolved into IVC. Our evidence supported that mRCC was monoclonal and distant metastasis occurred late during renal cancer progression. Thus, there was a broad window for early detection of circulating tumor cells and future targeted treatments for patients with mRCCs should rely on the molecular profiles of metastases.

Identification of medium-sized genomic deletions with low coverage, mate-paired restricted tags

Background

Genomic deletions are known to be widespread in many species. Variant sequencing-based approaches for identifying deletions have been developed, but their powers to detect those deletions that affect medium-sized regions are limited when the sequencing coverage is low.

Results

We present a cost-effective method for identifying medium-sized deletions in genomic regions with low genomic coverage. Two mate-paired libraries were separately constructed from human cancerous tissue to generate paired short reads (ditags) from restriction fragments digested with a 4-base restriction enzyme. A total of 3 Gb of paired reads (1.0× genome size) was collected, and 175 deletions were inferred by identifying the ditags with disorder alignments to the reference genome sequence. Sanger sequencing results confirmed an overall detection accuracy of 95%. Good reproducibility was verified by the deletions that were detected by both libraries.

Conclusions

We provide an approach to accurately identify medium-sized deletions in large genomes with low sequence coverage. It can be applied in studies of comparative genomics and in the identification of germline and somatic variants.

Chromothripsis and beyond: rapid genome evolution from complex chromosomal rearrangements

Recent genome sequencing studies have identified several classes of complex genomic rearrangements that appear to be derived from a single catastrophic event. These discoveries identify ways that genomes can be altered in single large jumps rather than by many incremental steps. Here we compare and contrast these phenomena and examine the evidence that they arise "all at once." We consider the impact of massive chromosomal change for the development of diseases such as cancer and for evolution more generally. Finally, we summarize current models for underlying mechanisms and discuss strategies for testing these models.

Evolving techniques for gene fusion detection in soft tissue tumours

Chromosomal rearrangements resulting in the fusion of coding parts from two genes or in the exchange of regulatory sequences are present in approximately 20% of all human neoplasms. More than 1000 such gene fusions have now been described, with close to 100 of them in soft tissue tumours. Although little is still known about the functional outcome of many of these gene fusions, it is well established that most of them have a major impact on tumorigenesis. Furthermore, the strong association between type of gene fusion and morphological subtype makes them highly useful diagnostic markers. Until recently, the vast majority of gene fusions were identified through molecular cytogenetic characterization of rearrangements detected at chromosome banding analysis, followed by use of the reverse transcriptase-polymerase chain reaction (RT-PCR) and Sanger sequencing. With the advent of next-generation sequencing (NGS) technologies, notably of whole transcriptomes or all poly-A(+) mRNA molecules, the possibility of detecting new gene fusions has increased dramatically. Already, a large number of novel gene fusions have been identified through NGS approaches and it can be predicted that these technologies soon will become standard diagnostic clinical tools.

Characterization of GM events by insert knowledge adapted re-sequencing approaches

Detection methods and data from molecular characterization of genetically modified (GM) events are needed by stakeholders of public risk assessors and regulators. Generally, the molecular characteristics of GM events are incomprehensively revealed by current approaches and biased towards detecting transformation vector derived sequences. GM events are classified based on available knowledge of the sequences of vectors and inserts (insert knowledge). Herein we present three insert knowledge-adapted approaches for characterization GM events (TT51-1 and T1c-19 rice as examples) based on paired-end re-sequencing with the advantages of comprehensiveness, accuracy, and automation. The comprehensive molecular characteristics of two rice events were revealed with additional unintended insertions comparing with the results from PCR and Southern blotting. Comprehensive transgene characterization of TT51-1 and T1c-19 is shown to be independent of a priori knowledge of the insert and vector sequences employing the developed approaches. This provides an opportunity to identify and characterize also unknown GM events.

RNA-dependent genome processing during nuclear differentiation: the model systems of stichotrichous ciliates

We introduce ciliated protozoa, and more specifically the stichotrichous ciliates Oxytricha and Stylonychia, as biological model systems for the analysis of programmed DNA-reorganization processes during nuclear differentiation. These include DNA excision, DNA elimination, reordering of gene segments and specific gene amplification. We show that small nuclear RNAs specify DNA sequences to be excised or retained, but also discuss the need for a RNA template molecule derived from the parental nucleus for these processes. This RNA template guides reordering of gene segments to become functional genes and determines gene copy number in the differentiated nucleus. Since the template is derived from the parental macronucleus, gene reordering and DNA amplification are inherited in a non-Mendelian epigenetic manner.

Use of autocorrelation scanning in DNA copy number analysis

MOTIVATION

Data quality is a critical issue in the analyses of DNA copy number alterations obtained from microarrays. It is commonly assumed that copy number alteration data can be modeled as piecewise constant and the measurement errors of different probes are independent. However, these assumptions do not always hold in practice. In some published datasets, we find that measurement errors are highly correlated between probes that interrogate nearby genomic loci, and the piecewise-constant model does not fit the data well. The correlated errors cause problems in downstream analysis, leading to a large number of DNA segments falsely identified as having copy number gains and losses.

METHOD

We developed a simple tool, called autocorrelation scanning profile, to assess the dependence of measurement error between neighboring probes.

RESULTS

Autocorrelation scanning profile can be used to check data quality and refine the analysis of DNA copy number data, which we demonstrate in some typical datasets.

CONTACT

lzhangli@mdanderson.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Computational tools for copy number variation (CNV) detection using next-generation sequencing data: features and perspectives

Copy number variation (CNV) is a prevalent form of critical genetic variation that leads to an abnormal number of copies of large genomic regions in a cell. Microarray-based comparative genome hybridization (arrayCGH) or genotyping arrays have been standard technologies to detect large regions subject to copy number changes in genomes until most recently high-resolution sequence data can be analyzed by next-generation sequencing (NGS). During the last several years, NGS-based analysis has been widely applied to identify CNVs in both healthy and diseased individuals. Correspondingly, the strong demand for NGS-based CNV analyses has fuelled development of numerous computational methods and tools for CNV detection. In this article, we review the recent advances in computational methods pertaining to CNV detection using whole genome and whole exome sequencing data. Additionally, we discuss their strengths and weaknesses and suggest directions for future development.

Detection of chromosomal alterations in the circulation of cancer patients with whole-genome sequencing

Clinical management of cancer patients could be improved through the development of noninvasive approaches for the detection of incipient, residual, and recurrent tumors. We describe an approach to directly identify tumor-derived chromosomal alterations through analysis of circulating cell-free DNA from cancer patients. Whole-genome analyses of DNA from the plasma of 10 colorectal and breast cancer patients and 10 healthy individuals with massively parallel sequencing identified, in all patients, structural alterations that were not present in plasma DNA from healthy subjects. Detected alterations comprised chromosomal copy number changes and rearrangements, including amplification of cancer driver genes such as ERBB2 and CDK6. The level of circulating tumor DNA in the cancer patients ranged from 1.4 to 47.9%. The sensitivity and specificity of this approach are dependent on the amount of sequence data obtained and are derived from the fact that most cancers harbor multiple chromosomal alterations, each of which is unlikely to be present in normal cells. Given that chromosomal abnormalities are present in nearly all human cancers, this approach represents a useful method for the noninvasive detection of human tumors that is not dependent on the availability of tumor biopsies.

Next-generation sequencing for lung cancer

Lung cancer is biologically aggressive and is the leading cause of cancer-related deaths. The development of lung cancer is unique in each patient according to clinical characterizations, prognosis, response and tolerance to treatment. Traditional capillary-based single-gene sequencing by a first-generation technique (known as Sanger sequencing) has been replaced by next-generation sequencing (NGS) since it allows massive parallel sequencing with lower cost and higher throughput. The NGS approach has made remarkable advances compared with traditional methods. We expect these methodologies to comprehensively interpret the global landscape of cancer and provide more information to fulfill the needs of personalized medicine. This review covers a brief introduction and summary on various NGS technologies, applications and important findings by NGS in lung cancer advances, including further discoveries in previously known target genes (EGFR, ALK and KRAS), the identification of additional lung cancer mutations and the global coordination of cancer genome studies.

Chromosomal structural variations during progression of a prostate epithelial cell line to a malignant metastatic state inactivate the NF2, NIPSNAP1, UGT2B17, and LPIN2 genes

Prostate cancer is the second highest cause of male cancer deaths in the United States. A significant number of tumors advance to a highly invasive and metastatic stage, which is typically resistant to traditional cancer therapeutics. In order to identify chromosomal structural variants that may contribute to prostate cancer progression we sequenced the genomes of a HPV-18 immortalized nonmalignant human prostate epithelial cell line, RWPE1, and compared it to its malignant, metastatic derivative, WPE1-NB26. There were a total of 34 large (> 1 Mbp) and 38 small copy number variants (<100 kbp) in WPE1-NB26 that were not present in the precursor cell line. We also identified and validated 46 structural variants present in the two cell lines, of which 23 were unique to WPE1-NB26. Structural variants unique to the malignant cell line inactivated: (1) the neurofibromin2 (NF2) gene, a known tumor suppressor; (2) its neighboring gene NIPSNAP1, another putative tumor suppressor that inhibits TRPV6, an anti-apoptotic oncogene implicated in prostate cancer progression; (3) UGT2B17, a gene that inactivates dihydrotestosterone, a known activator of prostate cancer progression; and (4) LPIN2, a phosphatidic acid phosphatase and a co-factor of PGC1a that is important for lipid metabolism and for suppressing autoinflammation. Our results illustrate the value of comparing the genomes of defined related pairs of cell lines to discover chromosomal structural variants that may contribute to cancer progression.

Characterization at nucleotide resolution of the homogeneously staining region sites of insertion in two cancer cell lines

The mechanisms of formation of intrachromosomal amplifications in tumours are still poorly understood. By using quantitative polymerase chain reaction, DNA sequencing, chromosome walking, in situ hybridization on metaphase chromosomes and whole-genome analysis, we studied two cancer cell lines containing an MYC oncogene amplification with acquired copies ectopically inserted in rearranged chromosomes 17. These intrachromosomal amplifications result from the integration of extrachromosomal DNA molecules. Replication stress could explain the formation of the double-strand breaks involved in their insertion and in the rearrangements of the targeted chromosomes. The sequences of the junctions indicate that homologous recombination was not involved in their formation and support a non-homologous end-joining process. The replication stress-inducible common fragile sites present in the amplicons may have driven the intrachromosomal amplifications. Mechanisms associating break-fusion-bridge cycles and/or chromosome fragmentation may have led to the formation of the uncovered complex structures. To our knowledge, this is the first characterization of an intrachromosomal amplification site at nucleotide resolution.

Identification of cancer gene fusions based on advanced analysis of the human genome or transcriptome

Many gene fusions have been recognized as important diagnostic and/or prognostic markers in human malignancies. In recent years, novel gene fusions have been identified in cases without prior knowledge of the genetic background. Accompanied by a powerful computational data analysis method, new genome-wide screening approaches were used to detect cryptic genomic aberrations. This review focused on advanced genomewide screening approaches in fusion gene identification, such as microarray-based approaches, next-generation sequencing, and NanoString nCounter gene expression system. The fundamental rationale and strategy for fusion gene identification using each biotech platform are also discussed.

Next-generation sequencing of paired tyrosine kinase inhibitor-sensitive and -resistant EGFR mutant lung cancer cell lines identifies spectrum of DNA changes associated with drug resistance

Somatic mutations in kinase genes are associated with sensitivity of solid tumors to kinase inhibitors, but patients with metastatic cancer eventually develop disease progression. In EGFR mutant lung cancer, modeling of acquired resistance (AR) with drug-sensitive cell lines has identified clinically relevant EGFR tyrosine kinase inhibitor (TKI) resistance mechanisms such as the second-site mutation, EGFR T790M, amplification of the gene encoding an alternative kinase, MET, and epithelial-mesenchymal transition (EMT). The full spectrum of DNA changes associated with AR remains unknown. We used next-generation sequencing to characterize mutational changes associated with four populations of EGFR mutant drug-sensitive and five matched drug-resistant cell lines. Comparing resistant cells with parental counterparts, 18-91 coding SNVs/indels were predicted to be acquired and 1-27 were lost; few SNVs/indels were shared across resistant lines. Comparison of two related parental lines revealed no unique coding SNVs/indels, suggesting that changes in the resistant lines were due to drug selection. Surprisingly, we observed more CNV changes across all resistant lines, and the line with EMT displayed significantly higher levels of CNV changes than the other lines with AR. These results demonstrate a framework for studying the evolution of AR and provide the first genome-wide spectrum of mutations associated with the development of cellular drug resistance in an oncogene-addicted cancer. Collectively, the data suggest that CNV changes may play a larger role than previously appreciated in the acquisition of drug resistance and highlight that resistance may be heterogeneous in the context of different tumor cell backgrounds.

The Growing Importance of CNVs: New Insights for Detection and Clinical Interpretation

Differences between genomes can be due to single nucleotide variants, translocations, inversions, and copy number variants (CNVs, gain or loss of DNA). The latter can range from sub-microscopic events to complete chromosomal aneuploidies. Small CNVs are often benign but those larger than 500 kb are strongly associated with morbid consequences such as developmental disorders and cancer. Detecting CNVs within and between populations is essential to better understand the plasticity of our genome and to elucidate its possible contribution to disease. Hence there is a need for better-tailored and more robust tools for the detection and genome-wide analyses of CNVs. While a link between a given CNV and a disease may have often been established, the relative CNV contribution to disease progression and impact on drug response is not necessarily understood. In this review we discuss the progress, challenges, and limitations that occur at different stages of CNV analysis from the detection (using DNA microarrays and next-generation sequencing) and identification of recurrent CNVs to the association with phenotypes. We emphasize the importance of germline CNVs and propose strategies to aid clinicians to better interpret structural variations and assess their clinical implications.

Genome-wide identification of genes with amplification and/or fusion in small cell lung cancer

To obtain a landscape of gross genetic alterations in small cell lung cancer (SCLC), genome-wide copy number analysis and whole-transcriptome sequencing were performed in 58 and 42 SCLCs, respectively. Focal amplification of known oncogene loci, MYCL1 (1p34.2), MYCN (2p24.3), and MYC (8q24.21), was frequently and mutually exclusively detected. MYCL1 and MYC were co-amplified with other regions on either the same or the different chromosome in several cases. In addition, the 9p24.1 region was identified as being amplified in SCLCs without amplification of MYC family oncogenes. Notably, expression of the KIAA1432 gene in this region was significantly higher in KIAA1432 amplified cells than in non-amplified cells, and its mRNA expression showed strong correlations with the copy numbers. Thus, KIAA1432 is a novel gene activated by amplification in SCLCs. By whole-transcriptome sequencing, a total of 60 fusion transcripts, transcribed from 95 different genes, were identified as being expressed in SCLC cells. However, no in-frame fusion transcripts were recurrently detected in ≥2 SCLCs, and genes in the amplified regions, such as PVT1 neighboring MYC and RLF in MYCL1 amplicons, were recurrently fused with genes in the same amplicons or with those in different amplicons on either the same or different chromosome. Thus, it was indicated that amplification and fusion of several genes on chromosomes 1 and 8 occur simultaneously but not sequentially through chromothripsis in the development of SCLC, and amplification rather than fusion of genes plays an important role in its development.

Detection of E2A-PBX1 fusion transcripts in human non-small-cell lung cancer

Background

E2A-PBX1 fusion gene caused by t(1;19)(q23;p13), has been well characterized in acute lymphoid leukemia (ALL). There is no report on E2A-PBX1 fusion transcripts in non-small-cell lung cancer (NSCLC).

Methods

We used polymerase chain reaction (PCR) to detect E2A-PBX1 fusion transcripts in human NSCLC tissue specimens and cell lines. We analyzed correlation of E2A-PBX1 fusion transcripts with clinical outcomes in 76 patients with adenocarcinoma in situ (AIS) and other subgroups. We compared mutation status of k-ras, p53 and EGFR in 22 patients with E2A-PBX1 fusion transcripts.

Results

We detected E2A-PBX1 transcripts in 23 of 184 (12.5%) NSCLC tissue specimens and 3 of 13 (23.1%) NSCLC cell lines. Presence of E2A-PBX1 fusion transcripts correlated with smoking status in female patients (P = 0.048), AIS histology (P = 0.006) and tumor size (P = 0.026). The overall survival was associated with gender among AIS patients (P = 0.0378) and AIS patients without E2A-PBX1 fusion transcripts (P = 0.0345), but not among AIS patients with E2A-PBX1 fusion transcripts (P = 0.6401). The overall survival was also associated with status of E2A-PBX1 fusion transcripts among AIS stage IA patients (P = 0.0363) and AIS stage IA female patients (P = 0.0174). In addition, among the 22 patients with E2A-PBX1 fusion transcripts, 12 (54.5%) patients including all four non-smokers, showed no common mutations in k-ras, p53 and EGFR.

Conclusions

E2A-PBX1 fusion gene caused by t(1;19)(q23;p13) may be a common genetic change in AIS and a survival determinant for female AIS patients at early stage.

Future of Clinical Genomics in Pediatric Oncology

The somatic genomic alterations in pediatric cancers to some extent overlap with those seen in adult cancers, but the exact distribution throughout the genome and the types and frequency of alterations differ. The ultimate goal of genomic research in children, as with adults, is translation to the clinic to achieve more accurate diagnosis, more precise risk stratification, and more effective, less toxic therapy. The genomic features of pediatric malignancies and pediatric-specific issues in clinical investigation may make translating genomic discoveries to the clinic more difficult. However, through large-scale molecular profiling of pediatric tumors, continued coordinated efforts to evaluate novel therapies in the pediatric population, thoughtful phase II and III trial design, and continued drug development, genomically based therapies will become more common in the pediatric oncology clinic in the future.

CNV-TV: a robust method to discover copy number variation from short sequencing reads

Background

Copy number variation (CNV) is an important structural variation (SV) in human genome. Various studies have shown that CNVs are associated with complex diseases. Traditional CNV detection methods such as fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (aCGH) suffer from low resolution. The next generation sequencing (NGS) technique promises a higher resolution detection of CNVs and several methods were recently proposed for realizing such a promise. However, the performances of these methods are not robust under some conditions, e.g., some of them may fail to detect CNVs of short sizes. There has been a strong demand for reliable detection of CNVs from high resolution NGS data.

Results

A novel and robust method to detect CNV from short sequencing reads is proposed in this study. The detection of CNV is modeled as a change-point detection from the read depth (RD) signal derived from the NGS, which is fitted with a total variation (TV) penalized least squares model. The performance (e.g., sensitivity and specificity) of the proposed approach are evaluated by comparison with several recently published methods on both simulated and real data from the 1000 Genomes Project.

Conclusion

The experimental results showed that both the true positive rate and false positive rate of the proposed detection method do not change significantly for CNVs with different copy numbers and lengthes, when compared with several existing methods. Therefore, our proposed approach results in a more reliable detection of CNVs than the existing methods.

Criteria for inference of chromothripsis in cancer genomes

Chromothripsis scars the genome when localized chromosome shattering and repair occurs in a one-off catastrophe. Outcomes of this process are detectable as massive DNA rearrangements affecting one or a few chromosomes. Although recent findings suggest a crucial role of chromothripsis in cancer development, the reproducible inference of this process remains challenging, requiring that cataclysmic one-off rearrangements be distinguished from localized lesions that occur progressively. We describe conceptual criteria for the inference of chromothripsis, based on ruling out the alternative hypothesis that stepwise rearrangements occurred. Robust means of inference may facilitate in-depth studies on the impact of, and the mechanisms underlying, chromothripsis.

Breakpoint analysis of transcriptional and genomic profiles uncovers novel gene fusions spanning multiple human cancer types

Gene fusions, like BCR/ABL1 in chronic myelogenous leukemia, have long been recognized in hematologic and mesenchymal malignancies. The recent finding of gene fusions in prostate and lung cancers has motivated the search for pathogenic gene fusions in other malignancies. Here, we developed a “breakpoint analysis” pipeline to discover candidate gene fusions by tell-tale transcript level or genomic DNA copy number transitions occurring within genes. Mining data from 974 diverse cancer samples, we identified 198 candidate fusions involving annotated cancer genes. From these, we validated and further characterized novel gene fusions involving ROS1 tyrosine kinase in angiosarcoma (CEP85L/ROS1), SLC1A2 glutamate transporter in colon cancer (APIP/SLC1A2), RAF1 kinase in pancreatic cancer (ATG7/RAF1) and anaplastic astrocytoma (BCL6/RAF1), EWSR1 in melanoma (EWSR1/CREM), CDK6 kinase in T-cell acute lymphoblastic leukemia (FAM133B/CDK6), and CLTC in breast cancer (CLTC/VMP1). Notably, while these fusions involved known cancer genes, all occurred with novel fusion partners and in previously unreported cancer types. Moreover, several constituted druggable targets (including kinases), with therapeutic implications for their respective malignancies. Lastly, breakpoint analysis identified new cell line models for known rearrangements, including EGFRvIII and FIP1L1/PDGFRA. Taken together, we provide a robust approach for gene fusion discovery, and our results highlight a more widespread role of fusion genes in cancer pathogenesis.

Gene fusions represent an important class of cancer genes, created by rearrangements of the genome that bring together two different genes. Because they are unique to cancer cells, gene fusions are ideal diagnostic markers and therapeutic targets. While gene fusions were once thought restricted mainly to blood cancers, recent discoveries suggest they are more widespread. Here, we have developed an approach for mining DNA microarray data to detect the tell-tale signatures of gene fusions, as “breakpoints” occurring within the encoding DNA or expressed transcripts. We apply this approach to a large collection of nearly 1,000 human cancer specimens. From this analysis, we discover and verify twelve new gene fusions occurring in diverse cancer types. We verify that some of these rearrangements recur in other samples of the same cancer type (supporting a causal role) and that the cancers show dependency on the fusion for cancer cell growth. Notably, some of these fusions (e.g. CEP85L/ROS1 in angiosarcoma) represent the first for that cancer type and thus provide important new biological insight. Some are also good drug targets (including rearrangements of ROS1, RAF1, and CDK6 kinases), with clear implications for therapy.

Gene fusions by chromothripsis of chromosome 5q in the VCaP prostate cancer cell line

The VCaP cell line is widely used in prostate cancer research as it is a unique model to study castrate resistant disease expressing high levels of the wild type androgen receptor and the TMPRSS2-ERG fusion transcript. Using next generation sequencing, we assembled the structural variations in VCaP genomic DNA and observed a massive number of genomic rearrangements along the q arm of chromosome 5, characteristic of chromothripsis. Chromothripsis is a recently recognized phenomenon characterized by extensive chromosomal shattering in a single catastrophic event, mainly detected in cancer cells. Various structural events identified on chromosome 5q of VCaP resulted in gene fusions. Out of the 18 gene fusion candidates tested, 15 were confirmed on genomic level. In our set of gene fusions, only rarely we observe microhomology flanking the breakpoints. On RNA level, only five transcripts were detected and NDUFAF2-MAST4 was the only resulting in an in-frame fusion transcript. Our data indicate that although a marker of genomic instability, chromothripsis might lead to only a limited number of functionally relevant fusion genes.

Existing and emerging technologies for tumor genomic profiling

Ongoing global genome characterization efforts are revolutionizing our knowledge of cancer genomics and tumor biology. In parallel, information gleaned from these studies on driver cancer gene alterations--mutations, copy number alterations, translocations, and/or chromosomal rearrangements--an be leveraged, in principle, to develop a cohesive framework for individualized cancer treatment. These possibilities have been enabled, to a large degree, by revolutionary advances in genomic technologies that facilitate systematic profiling for hallmark cancer genetic alterations at increasingly fine resolutions. Ongoing innovations in existing genomics technologies, as well as the many emerging technologies, will likely continue to advance translational cancer genomics and precision cancer medicine.

Massively parallel sequencing reveals the complex structure of an irradiated human chromosome on a mouse background in the Tc1 model of Down syndrome

Down syndrome (DS) is caused by trisomy of chromosome 21 (Hsa21) and presents a complex phenotype that arises from abnormal dosage of genes on this chromosome. However, the individual dosage-sensitive genes underlying each phenotype remain largely unknown. To help dissect genotype – phenotype correlations in this complex syndrome, the first fully transchromosomic mouse model, the Tc1 mouse, which carries a copy of human chromosome 21 was produced in 2005. The Tc1 strain is trisomic for the majority of genes that cause phenotypes associated with DS, and this freely available mouse strain has become used widely to study DS, the effects of gene dosage abnormalities, and the effect on the basic biology of cells when a mouse carries a freely segregating human chromosome. Tc1 mice were created by a process that included irradiation microcell-mediated chromosome transfer of Hsa21 into recipient mouse embryonic stem cells. Here, the combination of next generation sequencing, array-CGH and fluorescence in situ hybridization technologies has enabled us to identify unsuspected rearrangements of Hsa21 in this mouse model; revealing one deletion, six duplications and more than 25 de novo structural rearrangements. Our study is not only essential for informing functional studies of the Tc1 mouse but also (1) presents for the first time a detailed sequence analysis of the effects of gamma radiation on an entire human chromosome, which gives some mechanistic insight into the effects of radiation damage on DNA, and (2) overcomes specific technical difficulties of assaying a human chromosome on a mouse background where highly conserved sequences may confound the analysis. Sequence data generated in this study is deposited in the ENA database, Study Accession number: ERP000439.

Increased CNV-region deletions in mild cognitive impairment (MCI) and Alzheimer's disease (AD) subjects in the ADNI sample

We investigated the genome-wide distribution of CNVs in the Alzheimer's disease (AD) Neuroimaging Initiative (ADNI) sample (146 with AD, 313 with Mild Cognitive Impairment (MCI), and 181 controls). Comparison of single CNVs between cases (MCI and AD) and controls shows overrepresentation of large heterozygous deletions in cases (p-value<0.0001). The analysis of CNV-Regions identifies 44 copy number variable loci of heterozygous deletions, with more CNV-Regions among affected than controls (p=0.005). Seven of the 44 CNV-Regions are nominally significant for association with cognitive impairment. We validated and confirmed our main findings with genome re-sequencing of selected patients and controls. The functional pathway analysis of the genes putatively affected by deletions of CNV-Regions reveals enrichment of genes implicated in axonal guidance, cell-cell adhesion, neuronal morphogenesis and differentiation. Our findings support the role of CNVs in AD, and suggest an association between large deletions and the development of cognitive impairment.

Nonreciprocal chromosomal translocations in renal cancer involve multiple DSBs and NHEJ associated with breakpoint inversion but not necessarily with transcription

Chromosomal translocations and other abnormalities are central to the initiation of cancer in all cell types. Understanding the mechanism is therefore important to evaluate the evolution of cancer from the cancer initiating events to overt disease. Recent work has concentrated on model systems to develop an understanding of the molecular mechanisms of translocations but naturally occurring events are more ideal case studies since biological selection is absent from model systems. In solid tumours, nonreciprocal translocations are most commonly found, and accordingly we have investigated the recurrent nonreciprocal t(3;5) chromosomal translocations in renal carcinoma to better understand the mechanism of these naturally occurring translocations in cancer. Unexpectedly, the junctions of these translocations can be associated with site-specific, intrachromosomal inversion involving at least two double strand breaks (DSB) in cis and rejoining by nonhomologous end joining or micro-homology end joining. However, these translocations are not necessarily associated with transcribed regions questioning accessibility per se in controlling these events. In addition, intrachromosomal deletions also occur. We conclude these naturally occurring, nonreciprocal t(3;5) chromosomal translocations occur after complex and multiple unresolved intrachromosomal DSBs leading to aberrant joining with concurrent interstitial inversion and that clonal selection of cells is the critical element in cancer development emerging from a plethora of DSBs that may not always be pathogenic.

Prevalence and clinical significance of the MYD88 (L265P) somatic mutation in Waldenström’s macroglobulinemia and related lymphoid neoplasms

Using a sensitive method, the MYD88 (L265P) mutation is detectable in all patients with Waldenström’s macroglobulinemia, therefore representing a hallmark of the disease. MYD88 (L265P) is also found in a substantial proportion of patients with IgM-MGUS.