Daniel Vodák

Performance comparison of four exome capture systems for deep sequencing

BackgroundRecent developments in deep (next-generation) sequencing technologies are significantly impacting medical research. The global analysis of protein coding regions in genomes of interest by whole exome sequencing is a widely used application. Many technologies for exome capture are commercially available; here we compare the performance of four of them: NimbleGen’s SeqCap EZ v3.0, Agilent’s SureSelect v4.0, Illumina’s TruSeq Exome, and Illumina’s Nextera Exome, all applied to the same human tumor DNA sample.ResultsEach capture technology was evaluated for its coverage of different exome databases, target coverage efficiency, GC bias, sensitivity in single nucleotide variant detection, sensitivity in small indel detection, and technical reproducibility. In general, all technologies performed well; however, our data demonstrated small, but consistent differences between the four capture technologies. Illumina technologies cover more bases in coding and untranslated regions. Furthermore, whereas most of the technologies provide reduced coverage in regions with low or high GC content, the Nextera technology tends to bias towards target regions with high GC content.ConclusionsWe show key differences in performance between the four technologies. Our data should help researchers who are planning exome sequencing to select appropriate exome capture technology for their particular application.

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.

The androgen receptor controls expression of the cancer-associated sTn antigen and cell adhesion through induction of ST6GalNAc1 in prostate cancer

Patterns of glycosylation are important in cancer, but the molecular mechanisms that drive changes are often poorly understood. The androgen receptor drives prostate cancer (PCa) development and progression to lethal metastatic castration-resistant disease. Here we used RNA-Seq coupled with bioinformatic analyses of androgen-receptor (AR) binding sites and clinical PCa expression array data to identify ST6GalNAc1 as a direct and rapidly activated target gene of the AR in PCa cells. ST6GalNAc1 encodes a sialytransferase that catalyses formation of the cancer-associated sialyl-Tn antigen (sTn), which we find is also induced by androgen exposure. Androgens induce expression of a novel splice variant of the ST6GalNAc1 protein in PCa cells. This splice variant encodes a shorter protein isoform that is still fully functional as a sialyltransferase and able to induce expression of the sTn-antigen. Surprisingly, given its high expression in tumours, stable expression of ST6GalNAc1 in PCa cells reduced formation of stable tumours in mice, reduced cell adhesion and induced a switch towards a more mesenchymal-like cell phenotype in vitro. ST6GalNAc1 has a dynamic expression pattern in clinical datasets, being significantly up-regulated in primary prostate carcinoma but relatively down-regulated in established metastatic tissue. ST6GalNAc1 is frequently upregulated concurrently with another important glycosylation enzyme GCNT1 previously associated with prostate cancer progression and implicated in Sialyl Lewis X antigen synthesis. Together our data establishes an androgen-dependent mechanism for sTn antigen expression in PCa, and are consistent with a general role for the androgen receptor in driving important coordinate changes to the glycoproteome during PCa progression.

Unscrambling the genomic chaos of osteosarcoma reveals extensive transcript fusion, recurrent rearrangements and frequent novel TP53 aberrations

In contrast to many other sarcoma subtypes, the chaotic karyotypes of osteosarcoma have precluded the identification of pathognomonic translocations. We here report hundreds of genomic rearrangements in osteosarcoma cell lines, showing clear characteristics of microhomology-mediated break-induced replication (MMBIR) and end-joining repair (MMEJ) mechanisms. However, at RNA level, the majority of the fused transcripts did not correspond to genomic rearrangements, suggesting the involvement of trans-splicing, which was further supported by typical trans-splicing characteristics. By combining genomic and transcriptomic analysis, certain recurrent rearrangements were identified and further validated in patient biopsies, including a PMP22-ELOVL5 gene fusion, genomic structural variations affecting RB1, MTAP/CDKN2A and MDM2, and, most frequently, rearrangements involving TP53. Most cell lines (7/11) and a large fraction of tumor samples (10/25) showed TP53 rearrangements, in addition to somatic point mutations (6 patient samples, 1 cell line) and MDM2 amplifications (2 patient samples, 2 cell lines). The resulting inactivation of p53 was demonstrated by a deficiency of the radiation-induced DNA damage response. Thus, TP53 rearrangements are the major mechanism of p53 inactivation in osteosarcoma. Together with active MMBIR and MMEJ, this inactivation probably contributes to the exceptional chromosomal instability in these tumors. Although rampant rearrangements appear to be a phenotype of osteosarcomas, we demonstrate that among the huge number of probable passenger rearrangements, specific recurrent, possibly oncogenic, events are present. For the first time the genomic chaos of osteosarcoma is characterized so thoroughly and delivered new insights in mechanisms involved in osteosarcoma development and may contribute to new diagnostic and therapeutic strategies.

Glucocorticoid receptor and Klf4 co-regulate anti-inflammatory genes in keratinocytes

The glucocorticoid (GC) receptor (GR) and Kruppel-like factor Klf4 are transcription factors that play major roles in skin homeostasis. However, whether these transcription factors cooperate in binding genomic regulatory regions in epidermal keratinocytes was not known. Here, we show that in dexamethasone-treated keratinocytes GR and Klf4 are recruited to genomic regions containing adjacent GR and KLF binding motifs to control transcription of the anti-inflammatory genes Tsc22d3 and Zfp36. GR- and Klf4 loss of function experiments showed total GR but partial Klf4 requirement for full gene induction in response to dexamethasone. In wild type keratinocytes induced to differentiate, GR and Klf4 protein expression increased concomitant with Tsc22d3 and Zfp36 up-regulation. In contrast, GR-deficient cells failed to differentiate or fully induce Klf4, Tsc22d3 and Zfp36 correlating with increased expression of the epithelium-specific Trp63, a known transcriptional repressor of Klf4. The identified transcriptional cooperation between GR and Klf4 may determine cell-type specific regulation and have implications for developing therapies for skin diseases.

BRAF V600E mutation in early-stage multiple myeloma: good response to broad acting drugs and no relation to prognosis.

In this study, we analyzed the prevalence and clone size of BRAF V600E mutation in 209 patients with multiple myeloma and related the results to clinical phenotype, response and survival. Biopsies were screened for BRAF V600E by allele-specific real-time PCR (AS-PCR). Positive results were confirmed by immunohistochemistry, Sanger sequencing and, in three patients from whom we had stored purified myeloma cells, whole-exome sequencing. Eleven patients (5.3%) were BRAF V600E mutation positive by AS-PCR and at least one other method. The fraction of mutated cells varied from 4 to 100%. BRAF V600E-positive patients had no characteristic clinical phenotype except for significantly higher levels of serum creatinine (125 versus 86 μmol/l) Seven of eleven patients responded with at least very good partial response to alkylators, immunomodulatory agents or proteasome inhibitors. Progression-free and overall survival were similar in patients with and without the mutation. By this integrated approach, we found that patients with BRAF V600E mutation responded very well to broad acting drugs and there was no relation to prognosis in early-stage myeloma. In particular, a large mutated cell fraction did not correlate with aggressive disease.

Glycosylation is an Androgen-Regulated Process Essential for Prostate Cancer Cell Viability

Steroid androgen hormones play a key role in the progression and treatment of prostate cancer, with androgen deprivation therapy being the first-line treatment used to control cancer growth. Here we apply a novel search strategy to identify androgen-regulated cellular pathways that may be clinically important in prostate cancer. Using RNASeq data, we searched for genes that showed reciprocal changes in expression in response to acute androgen stimulation in culture, and androgen deprivation in patients with prostate cancer. Amongst 700 genes displaying reciprocal expression patterns we observed a significant enrichment in the cellular process glycosylation. Of 31 reciprocally-regulated glycosylation enzymes, a set of 8 (GALNT7, ST6GalNAc1, GCNT1, UAP1, PGM3, CSGALNACT1, ST6GAL1 and EDEM3) were significantly up-regulated in clinical prostate carcinoma. Androgen exposure stimulated synthesis of glycan structures downstream of this core set of regulated enzymes including sialyl-Tn (sTn), sialyl LewisX (SLeX), O-GlcNAc and chondroitin sulphate, suggesting androgen regulation of the core set of enzymes controls key steps in glycan synthesis. Expression of each of these enzymes also contributed to prostate cancer cell viability. This study identifies glycosylation as a global target for androgen control, and suggests loss of specific glycosylation enzymes might contribute to tumour regression following androgen depletion therapy.

TP53 Mutation Spectrum in Smokers and Never Smoking Lung Cancer Patients.

Background: TP53 mutations are among the most common mutations found in lung cancers, identified as an independent prognostic factor in many types of cancers. The purpose of this study was to investigate the frequency and prognostic impact of TP53 mutations in never-smokers and in different histological subtypes of lung cancer. Methods: We analyzed tumor tissue from 394 non-small cell carcinomas including adenocarcinomas (n = 229), squamous cell carcinomas (n = 112), large cell carcinomas (n = 30), and others (n = 23) for mutations in TP53 by the use of Sanger sequencing (n = 394) and next generation sequencing (n = 100). Results: TP53 mutations were identified in 47.2% of the samples, with the highest frequency (65%) of mutations among squamous cell carcinomas. Among never-smokers, 36% carried a TP53 mutation, identified as a significant independent negative prognostic factor in this subgroup. For large cell carcinomas, a significantly prolonged progression free survival was found for those carrying a TP53 mutation. In addition, the frequency of frameshift mutations was doubled in squamous cell carcinomas (20.3%) compared to adenocarcinomas (9.1%). Conclusion: TP53 mutation patterns differ between the histological subgroups of lung cancers, and are also influenced by smoking history. This indicates that the histological subtypes in lung cancer are genetically different, and that smoking-induced TP53 mutations may have a different biological impact than TP53 mutations occurring in never-smokers.

GSuite HyperBrowser: Integrative analysis of dataset collections across the genome and epigenome

Abstract Background: Recent large-scale undertakings such as ENCODE and Roadmap Epigenomics have generated experimental data mapped to the human reference genome (as genomic tracks) representing a variety of functional elements across a large number of cell types. Despite the high potential value of these publicly available data for a broad variety of investigations, little attention has been given to the analytical methodology necessary for their widespread utilisation. Findings: We here present a first principled treatment of the analysis of collections of genomic tracks. We have developed novel computational and statistical methodology to permit comparative and confirmatory analyses across multiple and disparate data sources. We delineate a set of generic questions that are useful across a broad range of investigations and discuss the implications of choosing different statistical measures and null models. Examples include contrasting analyses across different tissues or diseases. The methodology has been implemented in a comprehensive open-source software system, the GSuite HyperBrowser. To make the functionality accessible to biologists, and to facilitate reproducible analysis, we have also developed a web-based interface providing an expertly guided and customizable way of utilizing the methodology. With this system, many novel biological questions can flexibly be posed and rapidly answered. Conclusions: Through a combination of streamlined data acquisition, interoperable representation of dataset collections, and customizable statistical analysis with guided setup and interpretation, the GSuite HyperBrowser represents a first comprehensive solution for integrative analysis of track collections across the genome and epigenome. The software is available at: https://hyperbrowser.uio.no.

A Comprehensive Assessment of Somatic Mutation Calling in Cancer Genomes

The emergence of next generation DNA sequencing technology is enabling high-resolution cancer genome analysis. Large-scale projects like the International Cancer Genome Consortium (ICGC) are systematically scanning cancer genomes to identify recurrent somatic mutations. Second generation DNA sequencing, however, is still an evolving technology and procedures, both experimental and analytical, are constantly changing. Thus the research community is still defining a set of best practices for cancer genome data analysis, with no single protocol emerging to fulfil this role. Here we describe an extensive benchmark exercise to identify and resolve issues of somatic mutation calling. Whole genome sequence datasets comprising tumor-normal pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, were shared within the ICGC and submissions of somatic mutation calls were compared to verified mutations and to each other. Varying strategies to call mutations, incomplete awareness of sources of artefacts, and even lack of agreement on what constitutes an artefact or real mutation manifested in widely varying mutation call rates and somewhat low concordance among submissions. We conclude that somatic mutation calling remains an unsolved problem. However, we have identified many issues that are easy to remedy that are presented here. Our study highlights critical issues that need to be addressed before this valuable technology can be routinely used to inform clinical decision-making. Abbreviations and Definitions SSM Somatic Single-base Mutations or Simple Somatic Mutations, refers to a somatic single base change SIM Somatic Insertion/deletion Mutation CNV Copy Number Variant SV Structural Variant SNP Single Nucleotide Polymorphisms, refers to a single base variable position in the germline with a frequency of > 1% in the general population CLL Chronic Lymphocytic Leukaemia MB Medulloblastoma ICGC International Cancer Genome Consortium BM Benchmark aligner = mapper, these terms are used interchangeably