Stephen J. Salipante

Exome sequencing identifies a spectrum of mutation frequencies in advanced and lethal prostate cancers

To catalog protein-altering mutations that may drive the development of prostate cancers and their progression to metastatic disease systematically, we performed whole-exome sequencing of 23 prostate cancers derived from 16 different lethal metastatic tumors and three high-grade primary carcinomas. All tumors were propagated in mice as xenografts, designated the LuCaP series, to model phenotypic variation, such as responses to cancer-directed therapeutics. Although corresponding normal tissue was not available for most tumors, we were able to take advantage of increasingly deep catalogs of human genetic variation to remove most germline variants. On average, each tumor genome contained ∼200 novel nonsynonymous variants, of which the vast majority was specific to individual carcinomas. A subset of genes was recurrently altered across tumors derived from different individuals, including TP53, DLK2, GPC6, and SDF4. Unexpectedly, three prostate cancer genomes exhibited substantially higher mutation frequencies, with 2,000–4,000 novel coding variants per exome. A comparison of castration-resistant and castration-sensitive pairs of tumor lines derived from the same prostate cancer highlights mutations in the Wnt pathway as potentially contributing to the development of castration resistance. Collectively, our results indicate that point mutations arising in coding regions of advanced prostate cancers are common but, with notable exceptions, very few genes are mutated in a substantial fraction of tumors. We also report a previously undescribed subtype of prostate cancers exhibiting “hypermutated” genomes, with potential implications for resistance to cancer therapeutics. Our results also suggest that increasingly deep catalogs of human germline variation may challenge the necessity of sequencing matched tumor-normal pairs.

Validation and implementation of targeted capture and sequencing for the detection of actionable mutation, copy number variation, and gene rearrangement in clinical cancer specimens

Recent years have seen development and implementation of anticancer therapies targeted to particular gene mutations, but methods to assay clinical cancer specimens in a comprehensive way for the critical mutations remain underdeveloped. We have developed UW-OncoPlex, a clinical molecular diagnostic assay to provide simultaneous deep-sequencing information, based on >500× average coverage, for all classes of mutations in 194 clinically relevant genes. To validate UW-OncoPlex, we tested 98 previously characterized clinical tumor specimens from 10 different cancer types, including 41 formalin-fixed paraffin-embedded tissue samples. Mixing studies indicated reliable mutation detection in samples with ≥ 10% tumor cells. In clinical samples with ≥ 10% tumor cells, UW-OncoPlex correctly identified 129 of 130 known mutations [sensitivity 99.2%, (95% CI, 95.8%-99.9%)], including single nucleotide variants, small insertions and deletions, internal tandem duplications, gene copy number gains and amplifications, gene copy losses, chromosomal gains and losses, and actionable genomic rearrangements, including ALK-EML4, ROS1, PML-RARA, and BCR-ABL. In the same samples, the assay also identified actionable point mutations in genes not previously analyzed and novel gene rearrangements of MLL and GRIK4 in melanoma, and of ASXL1, PIK3R1, and SGCZ in acute myeloid leukemia. To best guide existing and emerging treatment regimens and facilitate integration of genomic testing with patient care, we developed a framework for data analysis, decision support, and reporting clinically actionable results.

Single molecule molecular inversion probes for targeted, high-accuracy detection of low-frequency variation

The detection and quantification of genetic heterogeneity in populations of cells is fundamentally important to diverse fields, ranging from microbial evolution to human cancer genetics. However, despite the cost and throughput advances associated with massively parallel sequencing, it remains challenging to reliably detect mutations that are present at a low relative abundance in a given DNA sample. Here we describe smMIP, an assay that combines single molecule tagging with multiplex targeted capture to enable practical and highly sensitive detection of low-frequency or subclonal variation. To demonstrate the potential of the method, we simultaneously resequenced 33 clinically informative cancer genes in eight cell line and 45 clinical cancer samples. Single molecule tagging facilitated extremely accurate consensus calling, with an estimated per-base error rate of 8.4 × 10(-6) in cell lines and 2.6 × 10(-5) in clinical specimens. False-positive mutations in the single molecule consensus base-calls exhibited patterns predominantly consistent with DNA damage, including 8-oxo-guanine and spontaneous deamination of cytosine. Based on mixing experiments with cell line samples, sensitivity for mutations above 1% frequency was 83% with no false positives. At clinically informative sites, we identified seven low-frequency point mutations (0.2%-4.7%), including BRAF p.V600E (melanoma, 0.2% alternate allele frequency), KRAS p.G12V (lung, 0.6%), JAK2 p.V617F (melanoma, colon, two lung, 0.3%-1.4%), and NRAS p.Q61R (colon, 4.7%). We anticipate that smMIP will be broadly adoptable as a practical and effective method for accurately detecting low-frequency mutations in both research and clinical settings.

ColoSeq Provides Comprehensive Lynch and Polyposis Syndrome Mutational Analysis Using Massively Parallel Sequencing

Lynch syndrome (hereditary nonpolyposis colon cancer) and adenomatous polyposis syndromes frequently have overlapping clinical features. Current approaches for molecular genetic testing are often stepwise, taking a best-candidate gene approach with testing of additional genes if initial results are negative. We report a comprehensive assay called ColoSeq that detects all classes of mutations in Lynch and polyposis syndrome genes using targeted capture and massively parallel next-generation sequencing on the Illumina HiSeq2000 instrument. In blinded specimens and colon cancer cell lines with defined mutations, ColoSeq correctly identified 28/28 (100%) pathogenic mutations in MLH1, MSH2, MSH6, PMS2, EPCAM, APC, and MUTYH, including single nucleotide variants (SNVs), small insertions and deletions, and large copy number variants. There was 100% reproducibility of detection mutation between independent runs. The assay correctly identified 222 of 224 heterozygous SNVs (99.4%) in HapMap samples, demonstrating high sensitivity of calling all variants across each captured gene. Average coverage was greater than 320 reads per base pair when the maximum of 96 index samples with barcodes were pooled. In a specificity study of 19 control patients without cancer from different ethnic backgrounds, we did not find any pathogenic mutations but detected two variants of uncertain significance. ColoSeq offers a powerful, cost-effective means of genetic testing for Lynch and polyposis syndromes that eliminates the need for stepwise testing and multiple follow-up clinical visits.

Performance Comparison of Illumina and Ion Torrent Next-Generation Sequencing Platforms for 16S rRNA-Based Bacterial Community Profiling

ABSTRACT High-throughput sequencing of the taxonomically informative 16S rRNA gene provides a powerful approach for exploring microbial diversity. Here we compare the performances of two common “benchtop” sequencing platforms, Illumina MiSeq and Ion Torrent Personal Genome Machine (PGM), for bacterial community profiling by 16S rRNA (V1-V2) amplicon sequencing. We benchmarked performance by using a 20-organism mock bacterial community and a collection of primary human specimens. We observed comparatively higher error rates with the Ion Torrent platform and report a pattern of premature sequence truncation specific to semiconductor sequencing. Read truncation was dependent on both the directionality of sequencing and the target species, resulting in organism-specific biases in community profiles. We found that these sequencing artifacts could be minimized by using bidirectional amplicon sequencing and an optimized flow order on the Ion Torrent platform. Results of bacterial community profiling performed on the mock community and a collection of 18 human-derived microbiological specimens were generally in good agreement for both platforms; however, in some cases, results differed significantly. Disparities could be attributed to the failure to generate full-length reads for particular organisms on the Ion Torrent platform, organism-dependent differences in sequence error rates affecting classification of certain species, or some combination of these factors. This study demonstrates the potential for differential bias in bacterial community profiles resulting from the choice of sequencing platform alone.

Rapid 16S rRNA next-generation sequencing of polymicrobial clinical samples for diagnosis of complex bacterial infections.

Classifying individual bacterial species comprising complex, polymicrobial patient specimens remains a challenge for culture-based and molecular microbiology techniques in common clinical use. We therefore adapted practices from metagenomics research to rapidly catalog the bacterial composition of clinical specimens directly from patients, without need for prior culture. We have combined a semiconductor deep sequencing protocol that produces reads spanning 16S ribosomal RNA gene variable regions 1 and 2 (∼360 bp) with a de-noising pipeline that significantly improves the fraction of error-free sequences. The resulting sequences can be used to perform accurate genus- or species-level taxonomic assignment. We explore the microbial composition of challenging, heterogeneous clinical specimens by deep sequencing, culture-based strain typing, and Sanger sequencing of bulk PCR product. We report that deep sequencing can catalog bacterial species in mixed specimens from which usable data cannot be obtained by conventional clinical methods. Deep sequencing a collection of sputum samples from cystic fibrosis (CF) patients reveals well-described CF pathogens in specimens where they were not detected by standard clinical culture methods, especially for low-prevalence or fastidious bacteria. We also found that sputa submitted for CF diagnostic workup can be divided into a limited number of groups based on the phylogenetic composition of the airway microbiota, suggesting that metagenomic profiling may prove useful as a clinical diagnostic strategy in the future. The described method is sufficiently rapid (theoretically compatible with same-day turnaround times) and inexpensive for routine clinical use.

Classification and characterization of microsatellite instability across 18 cancer types

Microsatellite instability (MSI), the spontaneous loss or gain of nucleotides from repetitive DNA tracts, is a diagnostic phenotype for gastrointestinal, endometrial, and colorectal tumors, yet the landscape of instability events across a wider variety of cancer types remains poorly understood. To explore MSI across malignancies, we examined 5,930 cancer exomes from 18 cancer types at more than 200,000 microsatellite loci and constructed a genomic classifier for MSI. We identified MSI-positive tumors in 14 of the 18 cancer types. We also identified loci that were more likely to be unstable in particular cancer types, resulting in specific instability signatures that involved cancer-associated genes, suggesting that instability patterns reflect selective pressures and can potentially identify novel cancer drivers. We also observed a correlation between survival outcomes and the overall burden of unstable microsatellites, suggesting that MSI may be a continuous, rather than discrete, phenotype that is informative across cancer types. These analyses offer insight into conserved and cancer-specific properties of MSI and reveal opportunities for improved methods of clinical MSI diagnosis and cancer gene discovery.

Application of Whole-Genome Sequencing for Bacterial Strain Typing in Molecular Epidemiology

ABSTRACT Nosocomial infections pose a significant threat to patient health; however, the gold standard laboratory method for determining bacterial relatedness (pulsed-field gel electrophoresis [PFGE]) remains essentially unchanged 20 years after its introduction. Here, we explored bacterial whole-genome sequencing (WGS) as an alternative approach for molecular strain typing. We compared WGS to PFGE for investigating presumptive outbreaks involving three important pathogens: vancomycin-resistant Enterococcus faecium (n = 19), methicillin-resistant Staphylococcus aureus (n = 17), and Acinetobacter baumannii (n = 15). WGS was highly reproducible (average ≤ 0.39 differences between technical replicates), which enabled a functional, quantitative definition for determining clonality. Strain relatedness data determined by PFGE and WGS roughly correlated, but the resolution of WGS was superior (P = 5.6 × 10−8 to 0.016). Several discordant results were noted between the methods. A total of 28.9% of isolates which were indistinguishable by PFGE were nonclonal by WGS. For A. baumannii, a species known to undergo rapid horizontal gene transfer, 16.2% of isolate pairs considered nonidentical by PFGE were clonal by WGS. Sequencing whole bacterial genomes with single-nucleotide resolution demonstrates that PFGE is prone to false-positive and false-negative results and suggests the need for a new gold standard approach for molecular epidemiological strain typing.

Microsatellite Instability Detection by Next Generation Sequencing

BACKGROUND Microsatellite instability (MSI) is a useful phenotype in cancer diagnosis and prognosis. Nevertheless, methods to detect MSI status from next generation DNA sequencing (NGS) data are underdeveloped. METHODS We developed an approach to detect the MSI phenotype using NGS (mSINGS). The method was used to evaluate mononucleotide microsatellite loci that were incidentally sequenced after targeted gene enrichment and could be applied to gene or exome capture panels designed for other purposes. For each microsatellite locus, the number of differently sized repeats in experimental samples were quantified and compared to a population of normal controls. Loci were considered unstable if the experimental number of repeats was statistically greater than in the control population. MSI status was determined by the fraction of unstable microsatellite loci. RESULTS We examined data from 324 samples generated using targeted gene capture assays of 3 different sizes, ranging from a 0.85-Mb to a 44-Mb exome design and incorporating from 15 to 2957 microsatellite markers. When we compared mSING results to MSI-PCR as a gold standard for 108 cases, we found the approach to be both diagnostically sensitive (range of 96.4% to 100% across 3 panels) and specific (range of 97.2% to 100%) for determining MSI status. The fraction of unstable microsatellite markers calculated from sequencing data correlated with the number of unstable loci detected by conventional MSI-PCR testing. CONCLUSIONS NGS data can enable highly accurate detection of MSI, even from limited capture designs. This novel approach offers several advantages over existing PCR-based methods.

Complex MSH2 and MSH6 mutations in hypermutated microsatellite unstable advanced prostate cancer

A hypermutated subtype of advanced prostate cancer was recently described, but prevalence and mechanisms have not been well-characterized. Here we find that 12% (7 of 60) of advanced prostate cancers are hypermutated, and that all hypermutated cancers have mismatch repair gene mutations and microsatellite instability (MSI). Mutations are frequently complex MSH2 or MSH6 structural rearrangements rather than MLH1 epigenetic silencing. Our findings identify parallels and differences in the mechanisms of hypermutation in prostate cancer compared with other MSI-associated cancers.