A novel approach for determining cancer genomic breakpoints in the presence of normal DNA

Mapping of deletion breakpoints at the CDKN2A locus in melanoma: detection of MTAP-ANRIL fusion transcripts

Genomic locus at chromosome 9p21 that contains the CDKN2A and CDKN2B tumor suppressor genes is inactivated through mutations, deletions and promoter methylation in multiple human cancers. Additionally, the locus encodes an anti-sense RNA (ANRIL). Both hemizygous and homozygous deletions at the locus targeting multiple genes are fairly common in different cancers. We in this study investigated breakpoints in five melanoma cell lines, derived from metastasized tumors, with previously identified homozygous deletions using array comparative genomic hybridization (aCGH). For breakpoint mapping, we used primer approximation multiplex PCR (PAMP) and inverse PCR techniques. Our results showed that three cell lines carried complex rearrangements. In two other cell lines, with focal deletions of 141 kb and 181 kb, we identified fusion gene products, involving MTAP and ANRIL. We also confirmed the complex rearrangements and focal deletions in DNA from tumor tissues corresponding to three cell lines. The rapid amplification of 3′cDNA ends (3′RACE) carried out on transcripts resulted in identification of three isoforms of MTAP-ANRIL fusion gene. Screening of cDNA from 64 melanoma cell lines resulted in detection of fusion transcripts in 13 (20%) cell lines that involved exons 4-7 of the MTAP and exon 2 or 5 of the ANRIL genes. We also detected fusion transcripts involving MTAP and ANRIL in two of the seven primary melanoma tumors with focal deletion at the locus. The results from the study, besides identifying complex rearrangements involving CDKN2A locus, show frequent occurrence of fusion transcripts involving MTAP and ANRIL genes.

Amplification and thrifty single-molecule sequencing of recurrent somatic structural variations

Deletion of tumor-suppressor genes as well as other genomic rearrangements pervade cancer genomes across numerous types of solid tumor and hematologic malignancies. However, even for a specific rearrangement, the breakpoints may vary between individuals, such as the recurrent CDKN2A deletion. Characterizing the exact breakpoints for structural variants (SVs) is useful for designating patient-specific tumor biomarkers. We propose AmBre (Amplification of Breakpoints), a method to target SV breakpoints occurring in samples composed of heterogeneous tumor and germline DNA. Additionally, AmBre validates SVs called by whole-exome/genome sequencing and hybridization arrays. AmBre involves a PCR-based approach to amplify the DNA segment containing an SV's breakpoint and then confirms breakpoints using sequencing by Pacific Biosciences RS. To amplify breakpoints with PCR, primers tiling specified target regions are carefully selected with a simulated annealing algorithm to minimize off-target amplification and maximize efficiency at capturing all possible breakpoints within the target regions. To confirm correct amplification and obtain breakpoints, PCR amplicons are combined without barcoding and simultaneously long-read sequenced using a single SMRT cell. Our algorithm efficiently separates reads based on breakpoints. Each read group supporting the same breakpoint corresponds with an amplicon and a consensus amplicon sequence is called. AmBre was used to discover CDKN2A deletion breakpoints in cancer cell lines: A549, CEM, Detroit562, MOLT4, MCF7, and T98G. Also, we successfully assayed RUNX1–RUNX1T1 reciprocal translocations by finding both breakpoints in the Kasumi-1 cell line. AmBre successfully targets SVs where DNA harboring the breakpoints are present in 1:1000 mixtures.

MCMC-ODPR: primer design optimization using Markov Chain Monte Carlo sampling

Background

Next generation sequencing technologies often require numerous primer designs that require good target coverage that can be financially costly. We aimed to develop a system that would implement primer reuse to design degenerate primers that could be designed around SNPs, thus find the fewest necessary primers and the lowest cost whilst maintaining an acceptable coverage and provide a cost effective solution. We have implemented Metropolis-Hastings Markov Chain Monte Carlo for optimizing primer reuse. We call it the Markov Chain Monte Carlo Optimized Degenerate Primer Reuse (MCMC-ODPR) algorithm.

Results

After repeating the program 1020 times to assess the variance, an average of 17.14% fewer primers were found to be necessary using MCMC-ODPR for an equivalent coverage without implementing primer reuse. The algorithm was able to reuse primers up to five times. We compared MCMC-ODPR with single sequence primer design programs Primer3 and Primer-BLAST and achieved a lower primer cost per amplicon base covered of 0.21 and 0.19 and 0.18 primer nucleotides on three separate gene sequences, respectively. With multiple sequences, MCMC-ODPR achieved a lower cost per base covered of 0.19 than programs BatchPrimer3 and PAMPS, which achieved 0.25 and 0.64 primer nucleotides, respectively.

Conclusions

MCMC-ODPR is a useful tool for designing primers at various melting temperatures at good target coverage. By combining degeneracy with optimal primer reuse the user may increase coverage of sequences amplified by the designed primers at significantly lower costs. Our analyses showed that overall MCMC-ODPR outperformed the other primer-design programs in our study in terms of cost per covered base.

John Cunningham virus T-antigen expression in anal carcinoma

BACKGROUND

Anal carcinoma is thought to be driven by human papillomavirus (HPV) infection through interrupting function of cell regulatory proteins such as p53 and pRb. John Cunningham virus (JCV) expresses a T-antigen that causes malignant transformation through development of aneuploidy and interaction with some of the same regulatory proteins as HPV. JCV T-antigen is present in brain, gastric, and colon malignancies, but has not been evaluated in anal cancers. The authors examined a cohort of anal cancers for JCV T-antigen and correlated this with clinicopathologic data.

METHODS

Archived anal carcinomas were analyzed for JCV T-antigen expression. DNA from tumor and normal tissue was sequenced for JCV with viral copies determined by quantitative polymerase chain reaction and Southern blotting. HPV and microsatellite instability (MSI) status was correlated with JCV T-antigen expression.

RESULTS

Of 21 cases of anal cancer (mean age 49 years, 38% female), 12 (57%) were in human immunodeficiency virus (HIV)-positive individuals. All 21 cancers expressed JCV T-antigen, including 9 HPV-negative specimens. More JCV copies were present in cancer versus surrounding normal tissue (mean 32.54 copies/μg DNA vs 2.98 copies/μg DNA, P = .0267). There was no correlation between disease stage and viral copies, nor between viral copies and HIV-positive or -negative status (28.7 vs 36.34 copies/μg DNA, respectively, P = .7804). In subset analysis, no association was found between JCV T-antigen expression and HPV or MSI status.

CONCLUSIONS

Anal carcinomas uniformly express JCV T-antigen and contain more viral copies compared with surrounding normal tissue. JCV and its T-antigen oncogenic protein, presumably through interruption of cell regulatory proteins, may play a role in anal cancer pathogenesis.

Detection of multiple human papillomavirus genotypes in anal carcinoma

Infection with human papillomavirus (HPV) is a major risk factor for development of anal squamous cell carcinoma. Despite over 100 genotypes of the virus, HPV 16 and 18 are considered pathogenic as they are seen in the majority of cervical and anal cancers. We have employed a custom microarray to examine DNA for several HPV genotypes. We aimed to determine the accuracy of our microarray in anal cancer DNA for HPV genotypes compared to the DNA sequencing gold standard.

METHODS

We utilized a sensitive microarray platform to classify 37 types of mucosal HPVs including 14 known high-risk and 23 low-risk types based on cervical cancer data. We utilized DNA from pathologically confirmed cases of anal squamous cell carcinoma. All samples underwent microarray HPV genotyping and PCR analysis.

RESULTS

HPV was detected in 18/20 (90%) anal cancers. HPV genotypes 16 and 18 were present in the majority of specimens, with HPV 16 being the most common. Eighty percent of anal cancers had at least two HPV types. Ten percent of cases (2/20) tested negative using our microarray; DNA sequencing confirmed the lack of presence of HPV DNA in these samples.

CONCLUSIONS

Microarray technology is an accurate way to screen for various genotypes of HPV in anal cancer, with 100% correlation with genomic DNA detection of HPV. The majority of anal cancers in our study associated with pathogenic HPV 16 and/or 18. Other HPV genotypes are present simultaneously with HPV 16 and 18, and might contribute to its pathogenesis.

Optimizing PCR assays for DNA-based cancer diagnostics

Somatically acquired DNA rearrangements are characteristic of many cancers. The use of these mutations as diagnostic markers is challenging, because tumor cells are frequently admixed with normal cells, particularly in early stage tumor samples, and thus the samples contain a high background of normal DNA. Detection is further confounded by the fact that the rearrangement boundaries are not conserved across individuals, and might vary over hundreds of kilobases. Here, we present an algorithm for designing polymerase chain reaction (PCR) primers and oligonucleotide probes to assay for these variant rearrangements. Specifically, the primers and probes tile the entire genomic region surrounding a rearrangement, so as to amplify the mutant DNA over a wide range of possible breakpoints and robustly assay for the amplified signal on an array. Our solution involves the design of a complex combinatorial optimization problem, and also includes a novel alternating multiplexing strategy that makes efficient detection possible. Simulations show that we can achieve near-optimal detection in many different cases, even when the regions are highly non-symmetric. Additionally, we prove that the suggested multiplexing strategy is optimal in breakpoint detection. We applied our technique to create a custom design to assay for genomic lesions in several cancer cell-lines associated with a disruption in the CDKN2A locus. The CDKN2A deletion has highly variable boundaries across many cancers. We successfully detect the breakpoint in all cell-lines, even when the region has undergone multiple rearrangements. These results point to the development of a successful protocol for early diagnosis and monitoring of cancer. For online Supplementary Material, see www.liebertonline.com.

A sequence-level map of chromosomal breakpoints in the MCF-7 breast cancer cell line yields insights into the evolution of a cancer genome

By applying a method that combines end-sequence profiling and massively parallel sequencing, we obtained a sequence-level map of chromosomal aberrations in the genome of the MCF-7 breast cancer cell line. A total of 157 distinct somatic breakpoints of two distinct types, dispersed and clustered, were identified. A total of 89 breakpoints are evenly dispersed across the genome. A majority of dispersed breakpoints are in regions of low copy repeats (LCRs), indicating a possible role for LCRs in chromosome breakage. The remaining 68 breakpoints form four distinct clusters of closely spaced breakpoints that coincide with the four highly amplified regions in MCF-7 detected by array CGH located in the 1p13.1-p21.1, 3p14.1-p14.2, 17q22-q24.3, and 20q12-q13.33 chromosomal cytobands. The clustered breakpoints are not significantly associated with LCRs. Sequences flanking most (95%) breakpoint junctions are consistent with double-stranded DNA break repair by nonhomologous end-joining or template switching. A total of 79 known or predicted genes are involved in rearrangement events, including 10 fusions of coding exons from different genes and 77 other rearrangements. Four fusions result in novel expressed chimeric mRNA transcripts. One of the four expressed fusion products (RAD51C-ATXN7) and one gene truncation (BRIP1 or BACH1) involve genes coding for members of protein complexes responsible for homology-driven repair of double-stranded DNA breaks. Another one of the four expressed fusion products (ARFGEF2-SULF2) involves SULF2, a regulator of cell growth and angiogenesis. We show that knock-down of SULF2 in cell lines causes tumorigenic phenotypes, including increased proliferation, enhanced survival, and increased anchorage-independent growth.

A sensitive array-based assay for identifying multiple TMPRSS2:ERG fusion gene variants

Studies of gene fusions in solid tumors are not as extensive as in hematological malignancies due to several technical and analytical problems associated with tumor heterogeneity. Nevertheless, there is a growing interest in the role of fusion genes in common epithelial tumors after the discovery of recurrent TMPRSS2:ETS fusions in prostate cancer. Among all of the reported fusion partners in the ETS gene family, TMPRSS2:ERG is the most prevalent one. Here, we present a simple and sensitive microarray-based assay that is able to simultaneously determine multiple fusion variants with a single RT-PCR in impure RNA specimens. The assay detected TMPRSS2:ERG fusion transcripts with a detection sensitivity of <10 cells in the presence of more than 3000 times excess normal RNA, and in primary prostate tumors having no >1% of cancer cells. The ability to detect multiple transcript variants in a single assay is critically dependent on both the primer and probe designs. The assay should facilitate clinical and basic studies for fusion gene screening in clinical specimens, as it can be readily adapted to include multiple gene loci.

Evaluation of paired-end sequencing strategies for detection of genome rearrangements in cancer

Paired-end sequencing is emerging as a key technique for assessing genome rearrangements and structural variation on a genome-wide scale. This technique is particularly useful for detecting copy-neutral rearrangements, such as inversions and translocations, which are common in cancer and can produce novel fusion genes. We address the question of how much sequencing is required to detect rearrangement breakpoints and to localize them precisely using both theoretical models and simulation. We derive a formula for the probability that a fusion gene exists in a cancer genome given a collection of paired-end sequences from this genome. We use this formula to compute fusion gene probabilities in several breast cancer samples, and we find that we are able to accurately predict fusion genes in these samples with a relatively small number of fragments of large size. We further demonstrate how the ability to detect fusion genes depends on the distribution of gene lengths, and we evaluate how different parameters of a sequencing strategy impact breakpoint detection, breakpoint localization, and fusion gene detection, even in the presence of errors that suggest false rearrangements. These results will be useful in calibrating future cancer sequencing efforts, particularly large-scale studies of many cancer genomes that are enabled by next-generation sequencing technologies.

Cancer is driven by genomic mutations that can range from single nucleotide changes to chromosomal aberrations that rearrange large pieces of DNA. Often, these chromosomal aberrations disrupt a gene sequence, and even fuse the sequences of two genes, producing a “fusion gene.” Fusion genes have been identified as key participants in the development of several types of cancer. Using genome-sequencing technology it is now possible to identify chromosomal aberrations genome-wide and at high resolution. In this paper, we address the question of how much sequencing is required to detect a chromosomal aberration and to determine the location of the aberration precisely enough to identify if a fusion gene is created by this aberration. We derive a mathematical formula that accurately predicts a number of fusion genes in a breast cancer sequencing study. We also demonstrate how the ability to detect chromosomal aberrations and fusion genes depends on both the size of the fusion gene and the parameters of the genome sequencing strategy that is used. These results will be useful in calibrating future cancer sequencing efforts, especially those using next-generation sequencing technologies.

Methods for routine diagnosis of genomic rearrangements: multiplex PCR-based methods and future perspectives

Germline and somatic genomic rearrangement play a relevant role in the pathogenesis of genetic disorders, and their identification is a fundamental task in molecular diagnosis. However, screening for structural genomic abnormalities is often not included in routine mutational analyses and consequently the proportion of rearrangements playing a pathogenic role in several genetic disorders is likely to be underestimated. A wide range of molecular techniques for the detection of large genomic rearrangements has been developed: some methods have the power to screen the whole genome, others are designed to analyze one or few loci that are known to be involved in a specific disease; some may detect balanced rearrangements, while others only unbalanced rearrangements; some are suitable for detection of germline abnormalities, yet others also detect somatic abnormalities. This review provides a brief summary of principles, applications and limitations of the methods available for the screening of genomic rearrangements, focusing on multiplex PCR-based protocols that are currently employed in routine detection of extended germline genomic deletions or duplications. Future developments based on microarray platforms and high-throughput sequencing are also discussed.

Optimization of primer design for the detection of variable genomic lesions in cancer

Primer approximation multiplex PCR (PAMP) is a new experimental protocol for efficiently assaying structural variation in genomes. PAMP is particularly suited to cancer genomes where the precise breakpoints of alterations such as deletions or translocations vary between patients. The design of PCR primer sets for PAMP is challenging because a large number of primer pairs are required to detect alterations in the hundreds of kilobases range that can occur in cancer. These sets of primers must achieve high coverage of the region of interest, while avoiding primer dimers and satisfying the physico-chemical constraints of good PCR primers. We describe a natural formulation of these constraints as a combinatorial optimization problem. We show that the PAMP primer design problem is NP-hard, and design algorithms based on simulated annealing and integer programming, that provide good solutions to this problem in practice. The algorithms are applied to a test region around the known CDKN2A deletion, which show excellent results even in a 1:49 mixture of mutated:wild-type cells. We use these test results to help set design parameters for larger problems. We can achieve near-optimal designs for regions close to 1 Mb.