Exome sequencing-based copy-number variation and loss of heterozygosity detection: ExomeCNV

Whole-exome sequencing of muscle-invasive bladder cancer identifies recurrent copy number variation in IPO11 and prognostic significance of importin-11 overexpression on poor survival

Non-muscle-invasive bladder cancer (NMIBC) often has a worse prognosis following its progression to muscle-invasive bladder cancer (MIBC), despite radical cystectomy with pelvic lymph node dissection combined with chemotherapy. Therefore, the discovery of novel biomarkers for predicting the progression of this disease and of therapeutic targets for preventing it is crucial. We performed whole-exome sequencing to analyze superficial tumor tissues (T_sup) and basal tumor tissues (T_bas) from 3 MIBC patients and identified previously unreported copy number variations in IPO11 that warrants further investigation as a molecular target. In addition, we identified a significant association between the absolute copy number and mRNA expression of IPO11 and found that high importin-11 expression was correlated with poor 3-year overall survival (OS), cancer-specific survival (CSS) and cancer-free survival (CFS) compared with low expression in the BCa patients. Importin-11 overexpression was also an independent risk factor for CSS and CFS in the BCa patients. Our study has revealed that IPO11 copy number amplification contributes to its overexpression and that these changes are unfavorable prognostic factors in NMIBC. Thus, IPO11 copy number amplification and importin-11 overexpression are promising biomarkers for predicting the progression and poor prognosis of patients with NMIBC.

Genetic heterogeneity in primary and relapsed mantle cell lymphomas: Impact of recurrent CARD11 mutations

The genetic mechanisms underlying disease progression, relapse and therapy resistance in mantle cell lymphoma (MCL) remain largely unknown. Whole-exome sequencing was performed in 27 MCL samples from 13 patients, representing the largest analyzed series of consecutive biopsies obtained at diagnosis and/or relapse for this type of lymphoma. Eighteen genes were found to be recurrently mutated in these samples, including known (ATM, MEF2B and MLL2) and novel mutation targets (S1PR1 and CARD11). CARD11, a scaffold protein required for B-cell receptor (BCR)-induced NF-κB activation, was subsequently screened in an additional 173 MCL samples and mutations were observed in 5.5% of cases. Based on in vitro cell line-based experiments, overexpression of CARD11 mutants were demonstrated to confer resistance to the BCR-inhibitor ibrutinib and NF-κB-inhibitor lenalidomide. Genetic alterations acquired in the relapse samples were found to be largely non-recurrent, in line with the branched evolutionary pattern of clonal evolution observed in most cases. In summary, this study highlights the genetic heterogeneity in MCL, in particular at relapse, and provides for the first time genetic evidence of BCR/NF-κB activation in a subset of MCL.

Whole-exome sequencing of oral mucosal melanoma reveals mutational profile and therapeutic targets

Oral mucosal melanoma (OMM) is a rare and aggressive subtype of melanoma with little known about its pathogenesis or carcinogenesis. We therefore performed whole-exome sequencing (WES) on 19 matched OMM tumor/normal pairs in order to gain insight into potential genetic drivers of tumor formation. For the first time, we describe the comprehensive mutational profile of OMM. Our data suggest that the genetic background of OMM differs from those of other melanoma subtypes. We identified recurrent mutations involving KIT, POLE, PTPRD, PTCHD2, and DMXL2. Notably, copy number analysis revealed recurrently amplified regions of 12q14 (57.9%, containing CDK4) and 5p15 (47.4%, containing TERT). CNV analysis in a separate cohort of 15 samples validated the frequent CNV in CDK4 and TERT. We also observed that the melanocyte development and pigmentation signaling pathway is frequently altered in OMM. Furthermore, our data suggest several altered genes that may be amenable for targeted therapy. We identified one patient with metastatic OMM in our cohort who was identified to harbor a targetable KIT mutation using our WES results. This patient was able to achieve complete remission following implementation of KIT-targeted therapy. These findings provide further insight into the genetic underpinnings of OMM development and suggest that patients with OMM may benefit from WES analysis to identify potential targetable genetic mutations. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Improving molecular diagnosis of Chinese patients with Charcot-Marie-Tooth by targeted next-generation sequencing and functional analysis

Charcot-Marie-Tooth (CMT) disease is the most common hereditary peripheral neuropathy. More than 50 causative genes have been identified. The lack of genotype-phenotype correlations in many CMT patients make it difficult to decide which genes are affected. Recently, targeted next-generation sequencing (NGS) has been introduced as an alternative approach for diagnosis of genetic disorders. Here, we applied targeted NGS in combination with PMP22 duplication/deletion analysis to screen causative genes in 22 Chinese CMT families. The novel variants detected by targeted NGS were then further studied in cultured cells. Of the 22 unrelated patients, 8 had PMP22 duplication. The targeted NGS revealed 10 possible pathogenic variants in 11 patients, including 7 previously reported variants and 3 novel heterozygous variants (GJB1: p.Y157H; MFN2: p.G127S; YARS: p.V293M). Further classification of the novel variants according to American College of Medical Genetics and Genomics (ACMG) standards and guidelines and functional analysis in cultured cells indicated that p.Y157H in GJB1 was pathogenic, p.G127S in MFN2 was likely pathogenic, while p.V293M in YARS was likely benign. Our results suggest the potential for targeted NGS to make a more rapid and precise diagnosis in CMT patients. Moreover, the functional analysis is required when the novel variants are indistinct.

Dynamic epigenetic changes to VHL occur with sunitinib in metastatic clear cell renal cancer

Background

Genetic intratumoral heterogeneity (ITH) hinders biomarker development in metastatic clear cell renal cancer (mccRCC). Epigenetic relative to genetic ITH or the presence of consistent epigenetic changes following targeted therapy in mccRCC have not been evaluated. The aim of this study was to determine methylome/genetic ITH and to evaluate specific epigenetic and genetic changes associated with sunitinib therapy.

Patients and methods

Multi-region DNA sampling performed on sequential frozen pairs of primary tumor tissue from 14 metastatic ccRCC patients, in the Upfront Sunitinib (SU011248) Therapy Followed by Surgery in Patients with Metastatic Renal Cancer: a Pilot Phase II Study (SuMR; ClinicalTrials.gov identifier: NCT01024205), at presentation (biopsy) and after 3-cycles of 50mg sunitinib (nephrectomy). Untreated biopsy and nephrectomy samples before and after renal artery ligation were controls. Ion Proton sequencing of 48 key ccRCC genes, and MethylCap-seq DNA methylation analysis was performed, data was analysed using the statistical computing environment R.

Results

Unsupervised hierarchical clustering revealed complete methylome clustering of biopsy and three nephrectomy samples for each patient (14/14 patients). For mutational status, untreated biopsy and all treated nephrectomy samples clustered together in 8/13 (61.5%) patients. The only methylation target significantly altered following sunitinib therapy was VHL promoter region 7896829 which was hypermethylated with treatment (FDR=0.077, P<0.001) and consistent for all patients (pre-treatment 50% patients had VHL mutations, 14% patients VHL hypermethylation). Renal artery ligation did not affect this result. No significant differences in driver or private mutation count was found with sunitinib treatment.

Conclusions

Demonstration of relative methylome homogeneity and consistent VHL hypermethylation, after sunitinib, may overcome the hurdle of ITH present at other molecular levels for biomarker research.

Detection of CNVs in NGS Data Using VS-CNV

Copy number variations have been linked to numerous genetic diseases including cancer, Parkinson's disease, pancreatitis, and lupus. While current best practices for CNV detection often require using microarrays for detecting large CNVs or multiplex ligation-dependent probe amplification (MLPA) for gene-sized CNVs, new methods have been developed with the goal of replacing both of these specialized assays with bioinformatic analysis applied to next-generation sequencing (NGS) data. Because NGS is already used by clinical labs to detect small coding variants, this approach reduces associated costs, resources, and analysis time. This chapter provides an overview of the various approaches to CNV detection via NGS data, and examines VS-CNV, a commercial tool developed by Golden Helix, which provides robust CNV calling capabilities for both gene panel and exome data.

aCNViewer: Comprehensive genome-wide visualization of absolute copy number and copy neutral variations

Motivation

Copy number variations (CNV) include net gains or losses of part or whole chromosomal regions. They differ from copy neutral loss of heterozygosity (cn-LOH) events which do not induce any net change in the copy number and are often associated with uniparental disomy. These phenomena have long been reported to be associated with diseases and particularly in cancer. Losses/gains of genomic regions are often correlated with lower/higher gene expression. On the other hand, loss of heterozygosity (LOH) and cn-LOH are common events in cancer and may be associated with the loss of a functional tumor suppressor gene. Therefore, identifying recurrent CNV and cn-LOH events can be important as they may highlight common biological components and give insights into the development or mechanisms of a disease. However, no currently available tools allow a comprehensive whole-genome visualization of recurrent CNVs and cn-LOH in groups of samples providing absolute quantification of the aberrations leading to the loss of potentially important information.

Results

To overcome these limitations, we developed aCNViewer (Absolute CNV Viewer), a visualization tool for absolute CNVs and cn-LOH across a group of samples. aCNViewer proposes three graphical representations: dendrograms, bi-dimensional heatmaps showing chromosomal regions sharing similar abnormality patterns, and quantitative stacked histograms facilitating the identification of recurrent absolute CNVs and cn-LOH. We illustrated aCNViewer using publically available hepatocellular carcinomas (HCCs) Affymetrix SNP Array data (Fig 1A). Regions 1q and 8q present a similar percentage of total gains but significantly different copy number gain categories (p-value of 0.0103 with a Fisher exact test), validated by another cohort of HCCs (p-value of 5.6e-7) (Fig 2B).

Availability and implementation

aCNViewer is implemented in python and R and is available with a GNU GPLv3 license on GitHub https://github.com/FJD-CEPH/aCNViewer and Docker https://hub.docker.com/r/fjdceph/acnviewer/.

Contact

aCNViewer@cephb.fr

Genomic landscape of ovarian clear cell carcinoma via whole exome sequencing

OBJECTIVE

To analyze whole exome sequencing (WES) data on ovarian clear cell carcinoma (OCCC) in Korean patients via the technique of next generation sequencing (NGS). Genomic profiles were compared between endometriosis-associated OCCC (EMS-OCCC) and Non-EMS-OCCC.

METHODS

We used serum samples and cancer tissues, stored at the Seoul National University Hospital Human Biobank, that were initially collected from women diagnosed with OCCC between 2012 and 2016. In total, 15 patients were enrolled: 5 with pathologically confirmed EMS-OCCC and 10 with Non-EMS-OCCC. We performed NGS WES on 15 fresh frozen OCCC tissues and matched serum samples, enabling comprehensive genomic characterization of OCCC.

RESULTS

OCCC was characterized by complex genomic alterations, with a median of 178 exonic mutations (range, 111-25,798) and a median of 343 somatic copy number variations (range, 43-1,820) per tumor sample. In all, 54 somatic mutations were discovered across 14 genes, including PIK3CA (40%), ARID1A (40%), and KRAS (20%) in the 15 Korean OCCCs. Copy number gains in NTRK1 (33%), MYC (40%), and GNAS (47%) and copy number losses in TET2 (73%), TSC1 (67%), BRCA2 (60%), and SMAD4 (47%) were frequent. The significantly altered pathways were associated with proliferation and survival (including the PI3K/AKT, TP53, and ERBB2 pathways) in 87% of OCCCs and with chromatin remodeling in 47% of OCCCs. No significant differences in frequencies of genetic alterations were detected between EMS-OCCC and Non-EMS-OCCC groups.

CONCLUSION

We successfully characterized the genomic landscape of 15 Korean patients with OCCC. We identified potential therapeutic targets for the treatment of this malignancy.

Detection of genome-wide copy number variants in myeloid malignancies using next-generation sequencing

AIMS

Genetic abnormalities, including copy number variants (CNV), copy number neutral loss of heterozygosity (CN-LOH) and gene mutations, underlie the pathogenesis of myeloid malignancies and serve as important diagnostic, prognostic and/or therapeutic markers. Currently, multiple testing strategies are required for comprehensive genetic testing in myeloid malignancies. The aim of this proof-of-principle study was to investigate the feasibility of combining detection of genome-wide large CNVs, CN-LOH and targeted gene mutations into a single assay using next-generation sequencing (NGS).

METHODS

For genome-wide CNV detection, we designed a single nucleotide polymorphism (SNP) sequencing backbone with 22 762 SNP regions evenly distributed across the entire genome. For targeted mutation detection, 62 frequently mutated genes in myeloid malignancies were targeted. We combined this SNP sequencing backbone with a targeted mutation panel, and sequenced 9 healthy individuals and 16 patients with myeloid malignancies using NGS.

RESULTS

We detected 52 somatic CNVs, 11 instances of CN-LOH and 39 oncogenic mutations in the 16 patients with myeloid malignancies, and none in the 9 healthy individuals. All CNVs and CN-LOH were confirmed by SNP microarray analysis.

CONCLUSIONS

We describe a genome-wide SNP sequencing backbone which allows for sensitive detection of genome-wide CNVs and CN-LOH using NGS. This proof-of-principle study has demonstrated that this strategy can provide more comprehensive genetic profiling for patients with myeloid malignancies using a single assay.

Spontaneous development of Epstein-Barr Virus associated human lymphomas in a prostate cancer xenograft program

Prostate cancer research is hampered by the lack of in vivo preclinical models that accurately reflect patient tumour biology and the clinical heterogeneity of human prostate cancer. To overcome these limitations we propagated and characterised a new collection of patient-derived prostate cancer xenografts. Tumour fragments from 147 unsupervised, surgical prostate samples were implanted subcutaneously into immunodeficient Rag2^-/-γC^-/- mice within 24 hours of surgery. Histologic and molecular characterisation of xenografts was compared with patient characteristics, including androgen-deprivation therapy, and exome sequencing. Xenografts were established from 47 of 147 (32%) implanted primary prostate cancers. Only 14% passaged successfully resulting in 20 stable lines; derived from 20 independent patient samples. Surprisingly, only three of the 20 lines (15%) were confirmed as prostate cancer; one line comprised of mouse stroma, and 16 were verified as human donor-derived lymphoid neoplasms. PCR for Epstein-Barr Virus (EBV) nuclear antigen, together with exome sequencing revealed that the lymphomas were exclusively EBV-associated. Genomic analysis determined that 14 of the 16 EBV⁺ lines had unique monoclonal or oligoclonal immunoglobulin heavy chain gene rearrangements, confirming their B-cell origin. We conclude that the generation of xenografts from tumour fragments can commonly result in B-cell lymphoma from patients carrying latent EBV. We recommend routine screening, of primary outgrowths, for latent EBV to avoid this phenomenon.

WISExome: a within-sample comparison approach to detect copy number variations in whole exome sequencing data

In clinical genetics, detection of single nucleotide polymorphisms (SNVs) as well as copy number variations (CNVs) is essential for patient genotyping. Obtaining both CNV and SNV information from WES data would significantly simplify clinical workflow. Unfortunately, the sequence reads obtained with WES vary between samples, complicating accurate CNV detection with WES. To avoid being dependent on other samples, we developed a within-sample comparison approach (WISExome). For every (WES) target region on the genome, we identified a set of reference target regions elsewhere on the genome with similar read frequency behavior. For a new sample, aberrations are detected by comparing the read frequency of a target region with the distribution of read frequencies in the reference set. WISExome correctly identifies known pathogenic CNVs (range 4 Kb–5.2 Mb). Moreover, WISExome prioritizes pathogenic CNVs by sorting them on quality and annotations of overlapping genes in OMIM. When comparing WISExome to four existing CNV detection tools, we found that CoNIFER detects much fewer CNVs and XHMM breaks calls made by other tools into smaller calls (fragmentation). CODEX and CLAMMS seem to perform more similar to WISExome. CODEX finds all known pathogenic CNVs, but detects much more calls than all other methods. CLAMMS and WISExome agree the most. CLAMMS does, however, miss one of the known CNVs and shows slightly more fragmentation. Taken together, WISExome is a promising tool for genome diagnostics laboratories as the workflow can be solely based on WES data.

A method to reduce ancestry related germline false positives in tumor only somatic variant calling

BACKGROUND

Significant clinical and research applications are driving large scale adoption of individualized tumor sequencing in cancer in order to identify tumors-specific mutations. When a matched germline sample is available, somatic mutations may be identified using comparative callers. However, matched germline samples are frequently not available such as with archival tissues, which makes it difficult to distinguish somatic from germline variants. While population databases may be used to filter out known germline variants, recent studies have shown private germline variants result in an inflated false positive rate in unmatched tumor samples, and the number germline false positives in an individual may be related to ancestry.

METHODS

First, we examined the relationship between the germline false positives and ancestry. Then we developed and implemented a tumor only caller (LumosVar) that leverages differences in allelic frequency between somatic and germline variants in impure tumors. We used simulated data to systematically examine how copy number alterations, tumor purity, and sequencing depth should affect the sensitivity of our caller. Finally, we evaluated the caller on real data.

RESULTS

We find the germline false-positive rate is significantly higher for individuals of non-European Ancestry largely due to the limited diversity in public polymorphism databases and due to population-specific characteristics such as admixture or recent expansions. Our Bayesian tumor only caller (LumosVar) is able to greatly reduce false positives from private germline variants, and our sensitivity is similar to predictions based on simulated data.

CONCLUSIONS

Taken together, our results suggest that studies of individuals of non-European ancestry would most benefit from our approach. However, high sensitivity requires sufficiently impure tumors and adequate sequencing depth. Even in impure tumors, there are copy number alterations that result in germline and somatic variants having similar allele frequencies, limiting the sensitivity of the approach. We believe our approach could greatly improve the analysis of archival samples in a research setting where the normal is not available.

Anaconda: AN automated pipeline for somatic COpy Number variation Detection and Annotation from tumor exome sequencing data

Background

Copy number variations (CNVs) are the main genetic structural variations in cancer genome. Detecting CNVs in genetic exome region is efficient and cost-effective in identifying cancer associated genes. Many tools had been developed accordingly and yet these tools lack of reliability because of high false negative rate, which is intrinsically caused by genome exonic bias.

Results

To provide an alternative option, here, we report Anaconda, a comprehensive pipeline that allows flexible integration of multiple CNV-calling methods and systematic annotation of CNVs in analyzing WES data. Just by one command, Anaconda can generate CNV detection result by up to four CNV detecting tools. Associated with comprehensive annotation analysis of genes involved in shared CNV regions, Anaconda is able to deliver a more reliable and useful report in assistance with CNV-associate cancer researches.

Conclusion

Anaconda package and manual can be freely accessed at http://mcg.ustc.edu.cn/bsc/ANACONDA/.

Electronic supplementary material

The online version of this article (10.1186/s12859-017-1833-3) contains supplementary material, which is available to authorized users.

Genetic analysis of parathyroid and pancreatic tumors in a patient with multiple endocrine neoplasia type 1 using whole-exome sequencing

Background

Multiple endocrine neoplasia type 1 (MEN1) syndrome is an autosomal dominant hereditary disorder characterized by the presence of endocrine tumors affecting the parathyroid, pancreas, and pituitary. A heterozygous germline inactivating mutation in the MEN1 gene (first hit) may be followed by somatic loss of the remaining normal copy or somatic mutations in the MEN1 gene (second hit). Whole-exome sequencing has been successfully used to elucidate the mutations associated with the different types of tumors.

Case presentation

We performed whole-exome sequencing (WES) on three parathyroid tumors, one pancreatic insulinoma, and a blood sample taken from the same patient with MEN1 to study tumor heterogeneity in MEN1 originating from different tumors. We identified a novel frame-shift deletion (c.1382_1383delAG, p.E461GfsX69) in the MEN1 gene using WES, which was confirmed by Sanger sequencing. WES and the SNP array revealed somatic LOH on chromosome 11 in parathyroid tumors (left upper, left lower, and right upper parathyroid). However, we did not detect a somatic MEN1 gene mutation or LOH in the pancreatic insulinoma. WES revealed two somatic functional variants outside the MEN1 gene in the pancreatic insulinoma.

Conclusions

This study revealed heterogeneity among tumors in the same patient with MEN1, suggesting that different tumor-specific tumorigenic mechanisms may contribute to the pathogenesis of MEN1 tumors. The present study supports the clinical applicability of the WES strategy to research on multiple tumor samples and blood.

Electronic supplementary material

The online version of this article (10.1186/s12881-017-0465-9) contains supplementary material, which is available to authorized users.

Detection of structural mosaicism from targeted and whole-genome sequencing data

Structural mosaic abnormalities are large post-zygotic mutations present in a subset of cells and have been implicated in developmental disorders and cancer. Such mutations have been conventionally assessed in clinical diagnostics using cytogenetic or microarray testing. Modern disease studies rely heavily on exome sequencing, yet an adequate method for the detection of structural mosaicism using targeted sequencing data is lacking. Here, we present a method, called MrMosaic, to detect structural mosaic abnormalities using deviations in allele fraction and read coverage from next-generation sequencing data. Whole-exome sequencing (WES) and whole-genome sequencing (WGS) simulations were used to calculate detection performance across a range of mosaic event sizes, types, clonalities, and sequencing depths. The tool was applied to 4911 patients with undiagnosed developmental disorders, and 11 events among nine patients were detected. For eight of these 11 events, mosaicism was observed in saliva but not blood, suggesting that assaying blood alone would miss a large fraction, possibly >50%, of mosaic diagnostic chromosomal rearrangements.

A short review of variants calling for single-cell-sequencing data with applications

The field of single-cell sequencing is fleetly expanding, and many techniques have been developed in the past decade. With this technology, biologists can study not only the heterogeneity between two adjacent cells in the same tissue or organ, but also the evolutionary relationships and degenerative processes in a single cell. Calling variants is the main purpose in analyzing single cell sequencing (SCS) data. Currently, some popular methods used for bulk-cell-sequencing data analysis are tailored directly to be applied in dealing with SCS data. However, SCS requires an extra step of genome amplification to accumulate enough quantity for satisfying sequencing needs. The amplification yields large biases and thus raises challenge for using the bulk-cell-sequencing methods. In order to provide guidance for the development of specialized analyzed methods as well as using currently developed tools for SNS, this paper aims to bridge the gap. In this paper, we firstly introduced two popular genome amplification methods and compared their capabilities. Then we introduced a few popular models for calling single-nucleotide polymorphisms and copy-number variations. Finally, break-through applications of SNS were summarized to demonstrate its potential in researching cell evolution.

APOBEC3A is an oral cancer prognostic biomarker in Taiwanese carriers of an APOBEC deletion polymorphism

Oral squamous cell carcinoma is a prominent cancer worldwide, particularly in Taiwan. By integrating omics analyses in 50 matched samples, we uncover in Taiwanese patients a predominant mutation signature associated with cytidine deaminase APOBEC, which correlates with the upregulation of APOBEC3A expression in the APOBEC3 gene cluster at 22q13. APOBEC3A expression is significantly higher in tumors carrying APOBEC3B-deletion allele(s). High-level APOBEC3A expression is associated with better overall survival, especially among patients carrying APOBEC3B-deletion alleles, as examined in a second cohort (n = 188; p = 0.004). The frequency of APOBEC3B-deletion alleles is ~50% in 143 genotyped oral squamous cell carcinoma -Taiwan samples (27A3B^−/−:89A3B^+/−:27A3B^+/+), compared to the 5.8% found in 314 OSCC-TCGA samples. We thus report a frequent APOBEC mutational profile, which relates to a APOBEC3B-deletion germline polymorphism in Taiwanese oral squamous cell carcinoma that impacts expression of APOBEC3A, and is shown to be of clinical prognostic relevance. Our finding might be recapitulated by genomic studies in other cancer types.

Oral squamous cell carcinoma is a prevalent malignancy in Taiwan. Here, the authors show that OSCC in Taiwanese show a frequent deletion polymorphism in the cytidine deaminases gene cluster APOBEC3 resulting in increased expression of A3A, which is shown to be of clinical prognostic relevance.

ALPK3 gene mutation in a patient with congenital cardiomyopathy and dysmorphic features

Primary cardiomyopathy is one of the most common inherited cardiac diseases and harbors significant phenotypic and genetic heterogeneity. Because of this, genetic testing has become standard in treatment of this disease group. Indeed, in recent years, next-generation DNA sequencing has found broad applications in medicine, both as a routine diagnostic tool for genetic disorders and as a high-throughput discovery tool for identifying novel disease-causing genes. We describe a male infant with primary dilated cardiomyopathy who was diagnosed using intrauterine echocardiography and found to progress to hypertrophic cardiomyopathy after birth. This proband was born to a nonconsanguineous family with a past history of a male fetus that died because of cardiac abnormalities at 30 wk of gestation. Using whole-exome sequencing, a novel homozygous frameshift mutation (c.2018delC; p.Gln675SerfsX30) in ALPK3 was identified and confirmed with Sanger sequencing. Heterozygous family members were normal with echocardiographic examination. To date, only two studies have reported homozygous pathogenic variants of ALPK3, with a total of seven affected individuals with cardiomyopathy from four unrelated consanguineous families. We include a discussion of the patient's phenotypic features and a review of relevant literature findings.

Burden and Profile of Somatic Mutation in Duodenal Adenomas from Patients with Familial Adenomatous- and MUTYH-associated Polyposis

Purpose: Duodenal polyposis and cancer are important causes of morbidity and mortality in familial adenomatous polyposis (FAP) and MUTYH-associated polyposis (MAP). This study aimed to comprehensively characterize somatic genetic changes in FAP and MAP duodenal adenomas to better understand duodenal tumorigenesis in these disorders.Experimental Design: Sixty-nine adenomas were biopsied during endoscopy in 16 FAP and 10 MAP patients with duodenal polyposis. Ten FAP and 10 MAP adenomas and matched blood DNA samples were exome sequenced, 42 further adenomas underwent targeted sequencing, and 47 were studied by array comparative genomic hybridization. Findings in FAP and MAP duodenal adenomas were compared with each other and to the reported mutational landscape in FAP and MAP colorectal adenomas.Results: MAP duodenal adenomas had significantly more protein-changing somatic mutations (P = 0.018), truncating mutations (P = 0.006), and copy number variants (P = 0.005) than FAP duodenal adenomas, even though MAP patients had lower Spigelman stage duodenal polyposis. Fifteen genes were significantly recurrently mutated. Targeted sequencing of APC, KRAS, PTCHD2, and PLCL1 identified further mutations in each of these genes in additional duodenal adenomas. In contrast to MAP and FAP colorectal adenomas, neither exome nor targeted sequencing identified WTX mutations (P = 0.0017).Conclusions: The mutational landscapes in FAP and MAP duodenal adenomas overlapped with, but had significant differences to those reported in colorectal adenomas. The significantly higher burden of somatic mutations in MAP than FAP duodenal adenomas despite lower Spigelman stage disease could increase cancer risk in the context of apparently less severe benign disease. Clin Cancer Res; 23(21); 6721-32. ©2017 AACR.

Whole-genome sequencing revealed novel prognostic biomarkers and promising targets for therapy of ovarian clear cell carcinoma

Background:

Ovarian clear cell carcinoma (OCCC) is mostly resistant to standard chemotherapy that results in poor patient survival. To understand the genetic background of these tumours, we performed whole-genome sequencing of OCCC tumours.

Methods:

Tumour tissue samples and matched blood samples were obtained from 55 Japanese women diagnosed with OCCC. Whole-genome sequencing was performed using the Illumina HiSeq platform according to standard protocols.

Results:

Alterations to the switch/sucrose non-fermentable (SWI/SNF) subunit, the phosphatidylinositol-3-kinase (PI3K)/Akt signalling pathway, and the receptor tyrosine kinase (RTK)/Ras signalling pathway were found in 51%, 42%, and 29% of OCCC tumours, respectively. The 3-year overall survival (OS) rate for patients with an activated PI3K/Akt signalling pathway was significantly higher than that for those with inactive pathway (91 vs 40%, hazard ratio 0.24 (95% confidence interval (CI) 0.10–0.56), P=0.0010). Similarly, the OS was significantly higher in patients with the activated RTK/Ras signalling pathway than in those with the inactive pathway (91 vs 53%, hazard ratio 0.35 (95% CI 0.13–0.94), P=0.0373). Multivariable analysis revealed that activation of the PI3K/Akt and RTK/Ras signalling pathways was an independent prognostic factor for patients with OCCC.

Conclusions:

The PI3K/Akt and RTK/Ras signalling pathways may be potential prognostic biomarkers for OCCC patients. Furthermore, our whole-genome sequencing data highlight important pathways for molecular and biological characterisations and potential therapeutic targeting in OCCC.

ExCNVSS: A Noise-Robust Method for Copy Number Variation Detection in Whole Exome Sequencing Data

Copy number variations (CNVs) are structural variants associated with human diseases. Recent studies verified that disease-related genes are based on the extraction of rare de novo and transmitted CNVs from exome sequencing data. The need for more efficient and accurate methods has increased, which still remains a challenging problem due to coverage biases, as well as the sparse, small-sized, and noncontinuous nature of exome sequencing. In this study, we developed a new CNV detection method, ExCNVSS, based on read coverage depth evaluation and scale-space filtering to resolve these problems. We also developed the method ExCNVSS_noRatio, which is a version of ExCNVSS, for applying to cases with an input of test data only without the need to consider the availability of a matched control. To evaluate the performance of our method, we tested it with 11 different simulated data sets and 10 real HapMap samples' data. The results demonstrated that ExCNVSS outperformed three other state-of-the-art methods and that our method corrected for coverage biases and detected all-sized CNVs even without matched control data.

Detection Copy Number Variants from NGS with Sparse and Smooth Constraints

It is known that copy number variations (CNVs) are associated with complex diseases and particular tumor types, thus reliable identification of CNVs is of great potential value. Recent advances in next generation sequencing (NGS) data analysis have helped manifest the richness of CNV information. However, the performances of these methods are not consistent. Reliably finding CNVs in NGS data in an efficient way remains a challenging topic, worthy of further investigation. Accordingly, we tackle the problem by formulating CNVs identification into a quadratic optimization problem involving two constraints. By imposing the constraints of sparsity and smoothness, the reconstructed read depth signal from NGS is anticipated to fit the CNVs patterns more accurately. An efficient numerical solution tailored from alternating direction minimization (ADM) framework is elaborated. We demonstrate the advantages of the proposed method, namely ADM-CNV, by comparing it with six popular CNV detection methods using synthetic, simulated, and empirical sequencing data. It is shown that the proposed approach can successfully reconstruct CNV patterns from raw data, and achieve superior or comparable performance in detection of the CNVs compared to the existing counterparts.

Whole exome sequencing of an asbestos-induced wild-type murine model of malignant mesothelioma

BACKGROUND

Malignant mesothelioma (MM) is an aggressive cancer of the pleural and peritoneal cavities caused by exposure to asbestos. Asbestos-induced mesotheliomas in wild-type mice have been used extensively as a preclinical model because they are phenotypically identical to their human counterpart. However, it is not known if the genetic lesions in these mice tumours are similar to in the human disease, a prerequisite for any new preclinical studies that target genetic abnormalities.

METHODS

We performed whole exome sequencing of fifteen asbestos-induced murine MM tumour cell lines from BALB/c, CBA and C57BL/6 mouse strains and compared the somatic mutations and copy number variations with those recurrently reported in human MM. We then catalogued and characterised the mutational landscape of the wild-type murine MM tumours. Quantitative RT-PCR was used to interrogate the expression of key MM genes of interest in the mRNA.

RESULTS

Consistent with human MM tumours, we identified homozygous loss of the tumour suppressor Cdkn2a in 14/15 tumours. One tumour retained the first exon of both of the p16INK4a and p19ARF isoforms though this tumour also contained genetic amplification of Myc resulting in increased expression of the c-Myc proto-oncogene in the mRNA. There were no chromosomal losses in either the Bap1 or Nf2 regions. One tumour harbored homozygous loss of Trp53 in the DNA. Mutation rates were similar in tumours generated in the CBA and C57BL/6 strains when compared to human MM. Interestingly, all BALB/c tumour lines displayed high mutational loads, consistent with the known mutator phenotype of the host strain. The Wnt, MAPK and Jak-STAT signaling pathways were found to be the most commonly affected biological pathways. Mutations and copy number deletions also occurred in the Hedgehog and Hippo pathways.

CONCLUSIONS

These data suggest that in the wild-type murine model asbestos causes mesotheliomas in a similar way to in human MM. This further supports the notion that the murine model of MM represents a genuine homologue of the human disease, something uncommon in cancer, and is thus a valuable tool to provide insight into MM tumour development and to aide the search for novel therapeutic strategies.

An evaluation of copy number variation detection tools for cancer using whole exome sequencing data

BACKGROUND

Recently copy number variation (CNV) has gained considerable interest as a type of genomic/genetic variation that plays an important role in disease susceptibility. Advances in sequencing technology have created an opportunity for detecting CNVs more accurately. Recently whole exome sequencing (WES) has become primary strategy for sequencing patient samples and study their genomics aberrations. However, compared to whole genome sequencing, WES introduces more biases and noise that make CNV detection very challenging. Additionally, tumors' complexity makes the detection of cancer specific CNVs even more difficult. Although many CNV detection tools have been developed since introducing NGS data, there are few tools for somatic CNV detection for WES data in cancer.

RESULTS

In this study, we evaluated the performance of the most recent and commonly used CNV detection tools for WES data in cancer to address their limitations and provide guidelines for developing new ones. We focused on the tools that have been designed or have the ability to detect cancer somatic aberrations. We compared the performance of the tools in terms of sensitivity and false discovery rate (FDR) using real data and simulated data. Comparative analysis of the results of the tools showed that there is a low consensus among the tools in calling CNVs. Using real data, tools show moderate sensitivity (~50% - ~80%), fair specificity (~70% - ~94%) and poor FDRs (~27% - ~60%). Also, using simulated data we observed that increasing the coverage more than 10× in exonic regions does not improve the detection power of the tools significantly.

CONCLUSIONS

The limited performance of the current CNV detection tools for WES data in cancer indicates the need for developing more efficient and precise CNV detection methods. Due to the complexity of tumors and high level of noise and biases in WES data, employing advanced novel segmentation, normalization and de-noising techniques that are designed specifically for cancer data is necessary. Also, CNV detection development suffers from the lack of a gold standard for performance evaluation. Finally, developing tools with user-friendly user interfaces and visualization features can enhance CNV studies for a broader range of users.

SynthEx: a synthetic-normal-based DNA sequencing tool for copy number alteration detection and tumor heterogeneity profiling

Changes in the quantity of genetic material, known as somatic copy number alterations (CNAs), can drive tumorigenesis. Many methods exist for assessing CNAs using microarrays, but considerable technical issues limit current CNA calling based upon DNA sequencing. We present SynthEx, a novel tool for detecting CNAs from whole exome and genome sequencing. SynthEx utilizes a “synthetic-normal” strategy to overcome technical and financial issues. In terms of accuracy and precision, SynthEx is highly comparable to array-based methods and outperforms sequencing-based CNA detection tools. SynthEx robustly identifies CNAs using sequencing data without the additional costs associated with matched normal specimens.

Integrated genomic analyses of de novo pathways underlying atypical meningiomas

Meningiomas are mostly benign brain tumours, with a potential for becoming atypical or malignant. On the basis of comprehensive genomic, transcriptomic and epigenomic analyses, we compared benign meningiomas to atypical ones. Here, we show that the majority of primary (de novo) atypical meningiomas display loss of NF2, which co-occurs either with genomic instability or recurrent SMARCB1 mutations. These tumours harbour increased H3K27me3 signal and a hypermethylated phenotype, mainly occupying the polycomb repressive complex 2 (PRC2) binding sites in human embryonic stem cells, thereby phenocopying a more primitive cellular state. Consistent with this observation, atypical meningiomas exhibit upregulation of EZH2, the catalytic subunit of the PRC2 complex, as well as the E2F2 and FOXM1 transcriptional networks. Importantly, these primary atypical meningiomas do not harbour TERT promoter mutations, which have been reported in atypical tumours that progressed from benign ones. Our results establish the genomic landscape of primary atypical meningiomas and potential therapeutic targets.

Meningiomas are mostly benign brain tumours with the potential for becoming atypical or malignant. Here, the authors show that primary atypical meningiomas are epigenetically and genetically distinct from benign and progressed tumours, highlighting possible therapeutic targets such as PRC2.

Longitudinal analysis of treatment-induced genomic alterations in gliomas

Background

Glioblastoma multiforme (GBM) constitutes nearly half of all malignant brain tumors and has a median survival of 15 months. The standard treatment for these lesions includes maximal resection, radiotherapy, and chemotherapy; however, individual tumors display immense variability in their response to these approaches. Genomic techniques such as whole-exome sequencing (WES) provide an opportunity to understand the molecular basis of this variability.

Methods

Here, we report WES-guided treatment of a patient with a primary GBM and two subsequent recurrences, demonstrating the dynamic nature of treatment-induced molecular changes and their implications for clinical decision-making. We also analyze the Yale-Glioma cohort, composed of 110 whole exome- or whole genome-sequenced tumor-normal pairs, to assess the frequency of genomic events found in the presented case.

Results

Our longitudinal analysis revealed how the genomic profile evolved under the pressure of therapy. Specifically targeted approaches eradicated treatment-sensitive clones while enriching for resistant ones, generated due to chromothripsis, which we show to be a frequent event in GBMs based on our extended analysis of 110 gliomas in the Yale-Glioma cohort. Despite chromothripsis and the later acquired mismatch-repair deficiency, genomics-guided personalized treatment extended survival to over 5 years. Interestingly, the case displayed a favorable response to immune checkpoint inhibition after acquiring mismatch repair deficiency.

Conclusions

Our study demonstrates the importance of longitudinal genomic profiling to adjust to the dynamic nature of treatment-induced molecular changes to improve the outcomes of precision therapies.

Electronic supplementary material

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Genomic and transcriptomic analysis of imatinib resistance in gastrointestinal stromal tumors

Gastrointestinal stromal tumors represent the most common mesenchymal tumor of the digestive tract, driven by gain‐of‐function mutations in KIT. Despite its proven benefits, half of the patients treated with imatinib show disease progression within 2 years due to secondary resistance mutations in KIT. It remains unclear how the genomic and transcriptomic features change during the acquisition of imatinib resistance. Here, we performed exome sequencing and microarray transcription analysis for four imatinib‐resistant cell lines and one cell line briefly exposed to imatinib. We also performed exome sequencing of clinical tumor samples. The cell line briefly exposed to imatinib exhibited few single‐nucleotide variants and copy‐number alterations, but showed marked upregulation of genes related to detoxification and downregulation of genes involved in cell cycle progression. Meanwhile, resistant cell lines harbored numerous genomic changes: amplified genes related to detoxification and deleted genes with cyclin‐dependent kinase activity. Some variants in the resistant samples were traced back to the drug‐sensitive samples, indicating the presence of ancestral subpopulations. The subpopulations carried variants associated with cell death. Pre‐existing cancer cells with genetic alterations promoting apoptosis resistance may serve as a basis whereby cancer cells with critical mutations, such as secondary KIT mutations, can establish full imatinib resistance. © 2017 The Authors Genes, Chromosomes and Cancer Published by Wiley Periodicals, Inc.

PureCN: copy number calling and SNV classification using targeted short read sequencing

Background

Matched sequencing of both tumor and normal tissue is routinely used to classify variants of uncertain significance (VUS) into somatic vs. germline. However, assays used in molecular diagnostics focus on known somatic alterations in cancer genes and often only sequence tumors. Therefore, an algorithm that reliably classifies variants would be helpful for retrospective exploratory analyses. Contamination of tumor samples with normal cells results in differences in expected allelic fractions of germline and somatic variants, which can be exploited to accurately infer genotypes after adjusting for local copy number. However, existing algorithms for determining tumor purity, ploidy and copy number are not designed for unmatched short read sequencing data.

Results

We describe a methodology and corresponding open source software for estimating tumor purity, copy number, loss of heterozygosity (LOH), and contamination, and for classification of single nucleotide variants (SNVs) by somatic status and clonality. This R package, PureCN, is optimized for targeted short read sequencing data, integrates well with standard somatic variant detection pipelines, and has support for matched and unmatched tumor samples. Accuracy is demonstrated on simulated data and on real whole exome sequencing data.

Conclusions

Our algorithm provides accurate estimates of tumor purity and ploidy, even if matched normal samples are not available. This in turn allows accurate classification of SNVs. The software is provided as open source (Artistic License 2.0) R/Bioconductor package PureCN (http://bioconductor.org/packages/PureCN/).

Electronic supplementary material

The online version of this article (doi:10.1186/s13029-016-0060-z) contains supplementary material, which is available to authorized users.

A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data

Whole Exome Sequencing (WES) is the application of the next-generation technology to determine the variations in the exome and is becoming a standard approach in studying genetic variants in diseases. Understanding the exomes of individuals at single base resolution allows the identification of actionable mutations for disease treatment and management. WES technologies have shifted the bottleneck in experimental data production to computationally intensive informatics-based data analysis. Novel computational tools and methods have been developed to analyze and interpret WES data. Here, we review some of the current tools that are being used to analyze WES data. These tools range from the alignment of raw sequencing reads all the way to linking variants to actionable therapeutics. Strengths and weaknesses of each tool are discussed for the purpose of helping researchers make more informative decisions on selecting the best tools to analyze their WES data.

Exome copy number variation detection: Use of a pool of unrelated healthy tissue as reference sample

An increasing number of bioinformatic tools designed to detect CNVs (copy number variants) in tumor samples based on paired exome data where a matched healthy tissue constitutes the reference have been published in the recent years. The idea of using a pool of unrelated healthy DNA as reference has previously been formulated but not thoroughly validated. As of today, the gold standard for CNV calling is still aCGH but there is an increasing interest in detecting CNVs by exome sequencing. We propose to design a metric allowing the comparison of two CNV profiles, independently of the technique used and assessed the validity of using a pool of unrelated healthy DNA instead of a matched healthy tissue as reference in exome-based CNV detection. We compared the CNV profiles obtained with three different approaches (aCGH, exome sequencing with a matched healthy tissue as reference, exome sequencing with a pool of eight unrelated healthy tissue as reference) on three multiple myeloma samples. We show that the usual analyses performed to compare CNV profiles (deletion/amplification ratios and CNV size distribution) lack in precision when confronted with low LRR values, as they only consider the binary status of each CNV. We show that the metric-based distance constitutes a more accurate comparison of two CNV profiles. Based on these analyses, we conclude that a reliable picture of CNV alterations in multiple myeloma samples can be obtained from whole-exome sequencing in the absence of a matched healthy sample.

Genetic evolution of nevus of Ota reveals clonal heterogeneity acquiring BAP1 and TP53 mutations

Melanoma presents molecular alterations based on its anatomical location and exposure to environmental factors. Due to its intrinsic genetic heterogeneity, a simple snapshot of a tumor's genetic alterations does not reflect the tumor clonal complexity or specific gene-gene cooperation. Here, we studied the genetic alterations and clonal evolution of a unique patient with a Nevus of Ota that developed into a recurring uveal-like dermal melanoma. The Nevus of Ota and ulterior lesions contained GNAQ mutations were c-KIT positive, and tumors showed an increased RAS pathway activity during progression. Whole-exome sequencing of these lesions revealed the acquisition of BAP1 and TP53 mutations during tumor evolution, thereby unmasking clonal heterogeneity and allowing the identification of cooperating genes within the same tumor. Our results highlight the importance of studying tumor genetic evolution to identify cooperating mechanisms and delineate effective therapies.

A statistical approach to detection of copy number variations in PCR-enriched targeted sequencing data

BACKGROUND

Multiplex polymerase chain reaction (PCR) is a common enrichment technique for targeted massive parallel sequencing (MPS) protocols. MPS is widely used in biomedical research and clinical diagnostics as the fast and accurate tool for the detection of short genetic variations. However, identification of larger variations such as structure variants and copy number variations (CNV) is still being a challenge for targeted MPS. Some approaches and tools for structural variants detection were proposed, but they have limitations and often require datasets of certain type, size and expected number of amplicons affected by CNVs. In the paper, we describe novel algorithm for high-resolution germinal CNV detection in the PCR-enriched targeted sequencing data and present accompanying tool.

RESULTS

We have developed a machine learning algorithm for the detection of large duplications and deletions in the targeted sequencing data generated with PCR-based enrichment step. We have performed verification studies and established the algorithm's sensitivity and specificity. We have compared developed tool with other available methods applicable for the described data and revealed its higher performance.

CONCLUSION

We showed that our method has high specificity and sensitivity for high-resolution copy number detection in targeted sequencing data using large cohort of samples.

A novel TP53-KPNA3 translocation defines a de novo treatment-resistant clone in osteosarcoma

Osteosarcoma is the most common primary bone cancer. It can be cured by aggressive surgery and chemotherapy, but outcomes for metastatic or chemoresistant disease remain dismal. Cancer sequencing studies have shown that the p53 pathway is dysregulated in nearly every case, often by translocation; however, no studies of osteosarcoma evolution or intratumor heterogeneity have been done to date. We studied a patient with chemoresistant, metastatic disease over the course of 3 years. We performed exome sequencing on germline DNA and DNA collected from tumor at three separate time points. We compared variant calls and variant allele frequencies between different samples. We identified subclonal mutations in several different genes in the primary tumor sample and found that one particular subclone dominated subsequent tumor samples at relapse. This clone was marked by a novel TP53-KPNA3 translocation and loss of the opposite-strand wild-type TP53 allele. Future research must focus on the functional significance of such clones and strategies to eliminate them.

Certified DNA Reference Materials to Compare HER2 Gene Amplification Measurements Using Next-Generation Sequencing Methods

The National Institute of Standards and Technology (NIST) Standard Reference Materials 2373 is a set of genomic DNA samples prepared from five breast cancer cell lines with certified values for the ratio of the HER2 gene copy number to the copy numbers of reference genes determined by real-time quantitative PCR and digital PCR. Targeted-amplicon, whole-exome, and whole-genome sequencing measurements were used with the reference material to compare the performance of both the laboratory steps and the bioinformatic approaches of the different methods using a range of amplification ratios. Although good reproducibility was observed in each next-generation sequencing method, slightly different HER2 copy numbers associated with platform-specific biases were obtained. This study clearly demonstrates the value of Standard Reference Materials 2373 as reference material and as a calibrator for evaluating assay performance as well as for increasing confidence in reporting HER2 amplification for clinical applications.

Implementation of next-generation sequencing for molecular diagnosis of hereditary breast and ovarian cancer highlights its genetic heterogeneity

Molecular diagnosis of hereditary breast and ovarian cancer (HBOC) by standard methodologies has been limited to the BRCA1 and BRCA2 genes. With the recent development of new sequencing methodologies, the speed and efficiency of DNA testing have dramatically improved. The aim of this work was to validate the use of next-generation sequencing (NGS) for the detection of BRCA1/BRCA2 point mutations in a diagnostic setting and to study the role of other genes associated with HBOC in Portuguese families. A cohort of 94 high-risk families was included in the study, and they were initially screened for the two common founder mutations with variant-specific methods. Fourteen index patients were shown to carry the Portuguese founder mutation BRCA2 c.156_157insAlu, and the remaining 80 were analyzed in parallel by Sanger sequencing for the BRCA1/BRCA2 genes and by NGS for a panel of 17 genes that have been described as involved in predisposition to breast and/or ovarian cancer. A total of 506 variants in the BRCA1/BRCA2 genes were detected by both methodologies, with a 100 % concordance between them. This strategy allowed the detection of a total of 39 deleterious mutations in the 94 index patients, namely 10 in BRCA1 (25.6 %), 21 in BRCA2 (53.8 %), four in PALB2 (10.3 %), two in ATM (5.1 %), one in CHEK2 (2.6 %), and one in TP53 (2.6 %), with 20.5 % of the deleterious mutations being found in genes other than BRCA1/BRCA2. These results demonstrate the efficiency of NGS for the detection of BRCA1/BRCA2 point mutations and highlight the genetic heterogeneity of HBOC.

Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas

RNA polymerase II mediates the transcription of all protein-coding genes in eukaryotic cells, a process that is fundamental to life. Genomic mutations altering this enzyme have not previously been linked to any pathology in humans, which is a testament to its indispensable role in cell biology. On the basis of a combination of next-generation genomic analyses of 775 meningiomas, we report that recurrent somatic p.Gln403Lys or p.Leu438_His439del mutations in POLR2A, which encodes the catalytic subunit of RNA polymerase II (ref. 1), hijack this essential enzyme and drive neoplasia. POLR2A mutant tumors show dysregulation of key meningeal identity genes, including WNT6 and ZIC1/ZIC4. In addition to mutations in POLR2A, NF2, SMARCB1, TRAF7, KLF4, AKT1, PIK3CA, and SMO, we also report somatic mutations in AKT3, PIK3R1, PRKAR1A, and SUFU in meningiomas. Our results identify a role for essential transcriptional machinery in driving tumorigenesis and define mutually exclusive meningioma subgroups with distinct clinical and pathological features.

CloneCNA: detecting subclonal somatic copy number alterations in heterogeneous tumor samples from whole-exome sequencing data

Background

Copy number alteration is a main genetic structural variation that plays an important role in tumor initialization and progression. Accurate detection of copy number alterations is necessary for discovering cancer-causing genes. Whole-exome sequencing has become a widely used technology in the last decade for detecting various types of genomic aberrations in cancer genomes. However, there are several major issues encountered in these detection problems, including normal cell contamination, tumor aneuploidy, and intra-tumor heterogeneity. Especially, deciphering the intra-tumor heterogeneity is imperative for identifying clonal and subclonal copy number alterations.

Results

We introduce CloneCNA, a novel bioinformatics tool for efficiently addressing these issues and automatically detecting clonal and subclonal somatic copy number alterations from heterogeneous tumor samples. CloneCNA fully explores the log ratio of read counts between paired tumor-normal samples and tumor B allele frequency of germline heterozygous SNP positions, further employs efficient statistical models to quantitatively represent copy number status of tumor sample containing multiple clones. We examine CloneCNA on simulated heterogeneous and real tumor samples, and the results demonstrate that CloneCNA has higher power to detect copy number alterations than existing methods.

Conclusions

CloneCNA, a novel algorithm is developed to efficiently and accurately identify somatic copy number alterations from heterogeneous tumor samples. We demonstrate the statistical framework of CloneCNA represents a remarkable advance for tumor whole-exome sequencing data. We expect that CloneCNA will promote cancer-focused studies for investigating the role of clonal evolution and elucidating critical events benefiting tumor tumourigenesis and progression.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1174-7) contains supplementary material, which is available to authorized users.

Germ line mutations in shelterin complex genes are associated with familial chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) can be familial; however, thus far no rare germ line disruptive alleles for CLL have been identified. We performed whole-exome sequencing of 66 CLL families, identifying 4 families where loss-of-function mutations in protection of telomeres 1 (POT1) co-segregated with CLL. The p.Tyr36Cys mutation is predicted to disrupt the interaction between POT1 and the telomeric overhang. The c.1164-1G>A splice-site, p.Gln358SerfsTer13 frameshift, and p.Gln376Arg missense mutations are likely to impact the interaction between POT1 and adrenocortical dysplasia homolog (ACD), which is a part of the telomere-capping shelterin complex. We also identified mutations in ACD (c.752-2A>C) and another shelterin component, telomeric repeat binding factor 2, interacting protein (p.Ala104Pro and p.Arg133Gln), in 3 CLL families. In a complementary analysis of 1083 cases and 5854 controls, the POT1 p.Gln376Arg variant, which has a global minor allele frequency of 0.0005, conferred a 3.61-fold increased risk of CLL (P = .009). This study further highlights telomere dysregulation as a key process in CLL development.

Enhanced copy number variants detection from whole-exome sequencing data using EXCAVATOR2

Copy Number Variants (CNVs) are structural rearrangements contributing to phenotypic variation that have been proved to be associated with many disease states. Over the last years, the identification of CNVs from whole-exome sequencing (WES) data has become a common practice for research and clinical purpose and, consequently, the demand for more and more efficient and accurate methods has increased. In this paper, we demonstrate that more than 30% of WES data map outside the targeted regions and that these reads, usually discarded, can be exploited to enhance the identification of CNVs from WES experiments. Here, we present EXCAVATOR2, the first read count based tool that exploits all the reads produced by WES experiments to detect CNVs with a genome-wide resolution. To evaluate the performance of our novel tool we use it for analysing two WES data sets, a population data set sequenced by the 1000 Genomes Project and a tumor data set made of bladder cancer samples. The results obtained from these analyses demonstrate that EXCAVATOR2 outperforms other four state-of-the-art methods and that our combined approach enlarge the spectrum of detectable CNVs from WES data with an unprecedented resolution. EXCAVATOR2 is freely available at http://sourceforge.net/projects/excavator2tool/.

Assessing the reproducibility of exome copy number variations predictions

Background

Reproducibility is receiving increased attention across many domains of science and genomics is no exception. Efforts to identify copy number variations (CNVs) from exome sequence (ES) data have been increasing. Many algorithms have been published to discover CNVs from exomes and a major challenge is the reproducibility in other datasets. Here we test exome CNV calling reproducibility under three conditions: data generated by different sequencing centers; varying sample sizes; and varying capture methodology.

Methods

Four CNV tools were tested: eXome Hidden Markov Model (XHMM), Copy Number Inference From Exome Reads (CoNIFER), EXCAVATOR, and Copy Number Analysis for Targeted Resequencing (CONTRA). To examine the reproducibility, we ran the callers on four datasets, varying sample sizes of N = 10, 30, 75, 100, 300, and data with different capture methodology. We examined the false negative (FN) calls and false positive (FP) calls for potential limitations of the CNV callers. The positive predictive value (PPV) was measured by checking the CNV call concordance against single nucleotide polymorphism array.

Results

Using independently generated datasets, we examined the PPV for each dataset and observed wide range of PPVs. The PPV values were highly data dependent (p <0.001). For the sample sizes and capture method analyses, we tested the callers in triplicates. Both analyses resulted in wide ranges of PPVs, even for the same test. Interestingly, negative correlations between the PPV and the sample sizes were observed for CoNIFER (ρ = –0.80). Further examination of FN calls showed that 44 % of these were missed by all callers and were attributed to the CNV size (46 % spanned ≤3 exons). Overlap of the FP calls showed that FPs were unique to each caller, indicative of algorithm dependency.

Conclusions

Our results demonstrate that further improvements in CNV callers are necessary to improve reproducibility and to include wider spectrum of CNVs (including the small CNVs). These CNV callers should be evaluated on multiple independent, heterogeneously generated datasets of varying size to increase robustness and utility. These approaches to the evaluation of exome CNV are essential to support wide utility and applicability of CNV discovery in exome studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0336-6) contains supplementary material, which is available to authorized users.

The stepwise evolution of the exome during acquisition of docetaxel resistance in breast cancer cells

BACKGROUND

Resistance to taxane-based therapy in breast cancer patients is a major clinical problem that may be addressed through insight of the genomic alterations leading to taxane resistance in breast cancer cells. In the current study we used whole exome sequencing to discover somatic genomic alterations, evolving across evolutionary stages during the acquisition of docetaxel resistance in breast cancer cell lines.

RESULTS

Two human breast cancer in vitro models (MCF-7 and MDA-MB-231) of the step-wise acquisition of docetaxel resistance were developed by exposing cells to 18 gradually increasing concentrations of docetaxel. Whole exome sequencing performed at five successive stages during this process was used to identify single point mutational events, insertions/deletions and copy number alterations associated with the acquisition of docetaxel resistance. Acquired coding variation undergoing positive selection and harboring characteristics likely to be functional were further prioritized using network-based approaches. A number of genomic changes were found to be undergoing evolutionary selection, some of which were likely to be functional. Of the five stages of progression toward resistance, most resistance relevant genomic variation appeared to arise midway towards fully resistant cells corresponding to passage 31 (5 nM docetaxel) for MDA-MB-231 and passage 16 (1.2 nM docetaxel) for MCF-7, and where the cells also exhibited a period of reduced growth rate or arrest, respectively. MCF-7 cell acquired several copy number gains on chromosome 7, including ABC transporter genes, including ABCB1 and ABCB4, as well as DMTF1, CLDN12, CROT, and SRI. For MDA-MB-231 numerous copy number losses on chromosome X involving more than 30 genes was observed. Of these genes, CASK, POLA1, PRDX4, MED14 and PIGA were highly prioritized by the applied network-based gene ranking approach. At higher docetaxel concentration MCF-7 subclones exhibited a copy number loss in E2F4, and the gene encoding this important transcription factor was down-regulated in MCF-7 resistant cells.

CONCLUSIONS

Our study of the evolution of acquired docetaxel resistance identified several genomic changes that might explain development of docetaxel resistance. Interestingly, the most relevant resistance-associated changes appeared to originate midway through the evolution towards fully resistant cell lines. Our data suggest that no single genomic event sufficiently predicts resistance to docetaxel, but require genomic alterations affecting multiple pathways that in concert establish the final resistance stage.

FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing

Allele-specific copy number analysis (ASCN) from next generation sequencing (NGS) data can greatly extend the utility of NGS beyond the identification of mutations to precisely annotate the genome for the detection of homozygous/heterozygous deletions, copy-neutral loss-of-heterozygosity (LOH), allele-specific gains/amplifications. In addition, as targeted gene panels are increasingly used in clinical sequencing studies for the detection of ‘actionable’ mutations and copy number alterations to guide treatment decisions, accurate, tumor purity-, ploidy- and clonal heterogeneity-adjusted integer copy number calls are greatly needed to more reliably interpret NGS-based cancer gene copy number data in the context of clinical sequencing. We developed FACETS, an ASCN tool and open-source software with a broad application to whole genome, whole-exome, as well as targeted panel sequencing platforms. It is a fully integrated stand-alone pipeline that includes sequencing BAM file post-processing, joint segmentation of total- and allele-specific read counts, and integer copy number calls corrected for tumor purity, ploidy and clonal heterogeneity, with comprehensive output and integrated visualization. We demonstrate the application of FACETS using The Cancer Genome Atlas (TCGA) whole-exome sequencing of lung adenocarcinoma samples. We also demonstrate its application to a clinical sequencing platform based on a targeted gene panel.

Somatic copy number alterations detected by ultra-deep targeted sequencing predict prognosis in oral cavity squamous cell carcinoma

Background

Ultra-deep targeted sequencing (UDT-Seq) has advanced our knowledge on the incidence and functional significance of somatic mutations. However, the utility of UDT-Seq in detecting copy number alterations (CNAs) remains unclear. With the goal of improving molecular prognostication and identifying new therapeutic targets, we designed this study to assess whether UDT-Seq may be useful for detecting CNA in oral cavity squamous cell carcinoma (OSCC).

Methods

We sequenced a panel of clinically actionable cancer mutations in 310 formalin-fixed paraffin-embedded OSCC specimens. A linear model was developed to overcome uneven coverage across target regions and multiple samples. The 5-year rates of secondary primary tumors, local recurrence, neck recurrence, distant metastases, and survival served as the outcome measures. We confirmed the prognostic significance of the CNA signatures in an independent sample of 105 primary OSCC specimens.

Results

The CNA burden across 10 targeted genes was found to predict prognosis in two independent cohorts. FGFR1 and PIK3CAamplifications were associated with prognosis independent of clinical risk factors. Genes exhibiting CNA were clustered in the proteoglycan metabolism, the FOXO signaling, and the PI3K-AKT signaling pathways, for which targeted drugs are already available or currently under development.

Conclusions

UDT-Seq is clinically useful to identify CNA, which significantly improve the prognostic information provided by traditional clinicopathological risk factors in OSCC patients.