Pathway-level mutation analysis in primary high-grade serous ovarian cancer and matched brain metastases.

Brain metastases (BMs) in ovarian cancer (OC) are a rare event. BMs occur most frequently in high-grade serous (HGS) OC. The molecular features of BMs in HGSOC are poorly understood. We performed a whole-exome sequencing analysis of ten matched pairs of formalin-fixed paraffin-embedded samples from primary HGSOC and corresponding BMs. Enrichment significance (p value; false discovery rate) was computed using the Reactome, the Kyoto Encyclopedia of Genes and Genomes pathway collections, and the Gene Ontology Biological Processes. Germline DNA damage repair variants were found in seven cases (70%) and involved the BRCA1, BRCA2, ATM, RAD50, ERCC4, RPA1, MLHI, and ATR genes. Somatic mutations of TP53 were found in nine cases (90%) and were the only stable mutations between the primary tumor and BMs. Disturbed pathways in BMs versus primary HGSOC constituted a complex network and included the cell cycle, the degradation of the extracellular matrix, cell junction organization, nucleotide metabolism, lipid metabolism, the immune system, G-protein-coupled receptors, intracellular vesicular transport, and reaction to chemical stimuli (Golgi vesicle transport and olfactory signaling). Pathway analysis approaches allow for a more intuitive interpretation of the data as compared to considering single-gene aberrations and provide an opportunity to identify clinically informative alterations in HGSOC BM.

Systematic Analysis of Genetic and Pathway Determinants of Eribulin Sensitivity across 100 Human Cancer Cell Lines from the Cancer Cell Line Encyclopedia (CCLE).

Eribulin, a natural product-based microtubule targeting agent with cytotoxic and noncytotoxic mechanisms, is FDA approved for certain patients with advanced breast cancer and liposarcoma. To investigate the feasibility of developing drug-specific predictive biomarkers, we quantified antiproliferative activities of eribulin versus paclitaxel and vinorelbine against 100 human cancer cell lines from the Cancer Cell Line Encyclopedia, and correlated results with publicly available databases to identify genes and pathways associated with eribulin response, either uniquely or shared with paclitaxel or vinorelbine. Mean expression ratios of 11,985 genes between the most and least sensitive cell line quartiles were sorted by p-values and drug overlaps, yielding 52, 29 and 80 genes uniquely associated with eribulin, paclitaxel and vinorelbine, respectively. Further restriction to minimum 2-fold ratios followed by reintroducing data from the middle two quartiles identified 9 and 13 drug-specific unique fingerprint genes for eribulin and vinorelbine, respectively; surprisingly, no gene met all criteria for paclitaxel. Interactome and Reactome pathway analyses showed that unique fingerprint genes of both drugs were primarily associated with cellular signaling, not microtubule-related pathways, although considerable differences existed in individual pathways identified. Finally, four-gene (C5ORF38, DAAM1, IRX2, CD70) and five-gene (EPHA2, NGEF, SEPTIN10, TRIP10, VSIG10) multivariate regression models for eribulin and vinorelbine showed high statistical correlation with drug-specific responses across the 100 cell lines and accurately calculated predicted mean IC50s for the most and least sensitive cell line quartiles as surrogates for responders and nonresponders, respectively. Collectively, these results provide a foundation for developing drug-specific predictive biomarkers for eribulin and vinorelbine.

Safety, Feasibility, and Merits of Longitudinal Molecular Testing of Multiple Metastatic Sites to Inform mTNBC Patient Treatment in the Intensive Trial of Omics in Cancer.

PURPOSE: Patients with metastatic triple-negative breast cancer (mTNBC) have poor outcomes. The Intensive Trial of Omics in Cancer (ITOMIC) sought to determine the feasibility and potential efficacy of informing treatment decisions through multiple biopsies of mTNBC deposits longitudinally over time, accompanied by analysis using a distributed network of experts. METHODS: Thirty-one subjects were enrolled and 432 postenrollment biopsies performed (clinical and study-directed) of which 332 were study-directed. Molecular profiling included whole-genome sequencing or whole-exome sequencing, cancer-associated gene panel sequencing, RNA-sequencing, and immunohistochemistry. To afford time for analysis, subjects were initially treated with cisplatin (19 subjects), or another treatment they had not received previously. The results were discussed at a multi-institutional ITOMIC Tumor Board, and a report transmitted to the subject's oncologist who arrived at the final treatment decision in conjunction with the subject. Assistance was provided to access treatments that were predicted to be effective. RESULTS: Multiple biopsies in single settings and over time were safe, and comprehensive analysis was feasible. Two subjects were found to have lung cancer, one had carcinoma of unknown primary site, tumor samples from three subjects were estrogen receptor-positive and from two others, human epidermal growth factor receptor 2-positive. Two subjects withdrew. Thirty-four of 112 recommended treatments were accessed using approved drugs, clinical trials, and single-patient investigational new drugs. After excluding the three subjects with nonbreast cancers and the two subjects who withdrew, 22 of 26 subjects (84.6%) received at least one ITOMIC Tumor Board-recommended treatment. CONCLUSION: Further exploration of this approach in patients with mTNBC is merited.

Correction: Predicting Carriers of Ongoing Selective Sweeps without Knowledge of the Favored Allele.

[This corrects the article DOI: 10.1371/journal.pgen.1005527.].

Senp1 drives hypoxia-induced polycythemia via GATA1 and Bcl-xL in subjects with Monge's disease.

In this study, because excessive polycythemia is a predominant trait in some high-altitude dwellers (chronic mountain sickness [CMS] or Monge's disease) but not others living at the same altitude in the Andes, we took advantage of this human experiment of nature and used a combination of induced pluripotent stem cell technology, genomics, and molecular biology in this unique population to understand the molecular basis for hypoxia-induced excessive polycythemia. As compared with sea-level controls and non-CMS subjects who responded to hypoxia by increasing their RBCs modestly or not at all, respectively, CMS cells increased theirs remarkably (up to 60-fold). Although there was a switch from fetal to adult HgbA0 in all populations and a concomitant shift in oxygen binding, we found that CMS cells matured faster and had a higher efficiency and proliferative potential than non-CMS cells. We also established that SENP1 plays a critical role in the differential erythropoietic response of CMS and non-CMS subjects: we can convert the CMS phenotype into that of non-CMS and vice versa by altering SENP1 levels. We also demonstrated that GATA1 is an essential downstream target of SENP1 and that the differential expression and response of GATA1 and Bcl-xL are a key mechanism underlying CMS pathology.

A Distributed Network for Intensive Longitudinal Monitoring in Metastatic Triple-Negative Breast Cancer.

Accelerating cancer research is expected to require new types of clinical trials. This report describes the Intensive Trial of OMics in Cancer (ITOMIC) and a participant with triple-negative breast cancer metastatic to bone, who had markedly elevated circulating tumor cells (CTCs) that were monitored 48 times over 9 months. A total of 32 researchers from 14 institutions were engaged in the patient's evaluation; 20 researchers had no prior involvement in patient care and 18 were recruited specifically for this patient. Whole-exome sequencing of 3 bone marrow samples demonstrated a novel ROS1 variant that was estimated to be present in most or all tumor cells. After an initial response to cisplatin, a hypothesis of crizotinib sensitivity was disproven. Leukapheresis followed by partial CTC enrichment allowed for the development of a differential high-throughput drug screen and demonstrated sensitivity to investigational BH3-mimetic inhibitors of BCL-2 that could not be tested in the patient because requests to the pharmaceutical sponsors were denied. The number and size of CTC clusters correlated with clinical status and eventually death. Focusing the expertise of a distributed network of investigators on an intensively monitored patient with cancer can generate high-resolution views of the natural history of cancer and suggest new opportunities for therapy. Optimization requires access to investigational drugs.

Predicting Carriers of Ongoing Selective Sweeps without Knowledge of the Favored Allele.

Methods for detecting the genomic signatures of natural selection have been heavily studied, and they have been successful in identifying many selective sweeps. For most of these sweeps, the favored allele remains unknown, making it difficult to distinguish carriers of the sweep from non-carriers. In an ongoing selective sweep, carriers of the favored allele are likely to contain a future most recent common ancestor. Therefore, identifying them may prove useful in predicting the evolutionary trajectory--for example, in contexts involving drug-resistant pathogen strains or cancer subclones. The main contribution of this paper is the development and analysis of a new statistic, the Haplotype Allele Frequency (HAF) score. The HAF score, assigned to individual haplotypes in a sample, naturally captures many of the properties shared by haplotypes carrying a favored allele. We provide a theoretical framework for computing expected HAF scores under different evolutionary scenarios, and we validate the theoretical predictions with simulations. As an application of HAF score computations, we develop an algorithm (PreCIOSS: Predicting Carriers of Ongoing Selective Sweeps) to identify carriers of the favored allele in selective sweeps, and we demonstrate its power on simulations of both hard and soft sweeps, as well as on data from well-known sweeps in human populations.

Endothelin receptor B, a candidate gene from human studies at high altitude, improves cardiac tolerance to hypoxia in genetically engineered heterozygote mice.

To better understand human adaptation to stress, and in particular to hypoxia, we took advantage of one of nature's experiments at high altitude (HA) and studied Ethiopians, a population that is well-adapted to HA hypoxic stress. Using whole-genome sequencing, we discovered that EDNRB (Endothelin receptor type B) is a candidate gene involved in HA adaptation. To test whether EDNRB plays a critical role in hypoxia tolerance and adaptation, we generated EdnrB knockout mice and found that when EdnrB (-/+) heterozygote mice are treated with lower levels of oxygen (O2), they tolerate various levels of hypoxia (even extreme hypoxia, e.g., 5% O2) very well. For example, they maintain ejection fraction, cardiac contractility, and cardiac output in severe hypoxia. Furthermore, O2 delivery to vital organs was significantly higher and blood lactate was lower in EdnrB (-/+) compared with wild type in hypoxia. Tissue hypoxia in brain, heart, and kidney was lower in EdnrB (-/+) mice as well. These data demonstrate that a lower level of EDNRB significantly improves cardiac performance and tissue perfusion under various levels of hypoxia. Transcriptomic profiling of left ventricles revealed three specific genes [natriuretic peptide type A (Nppa), sarcolipin (Sln), and myosin light polypeptide 4 (Myl4)] that were oppositely expressed (q < 0.05) between EdnrB (-/+) and wild type. Functions related to these gene networks were consistent with a better cardiac contractility and performance. We conclude that EDNRB plays a key role in hypoxia tolerance and that a lower level of EDNRB contributes, at least in part, to HA adaptation in humans.

Misassembly detection using paired-end sequence reads and optical mapping data.

MOTIVATION: A crucial problem in genome assembly is the discovery and correction of misassembly errors in draft genomes. We develop a method called misSEQuel that enhances the quality of draft genomes by identifying misassembly errors and their breakpoints using paired-end sequence reads and optical mapping data. Our method also fulfills the critical need for open source computational methods for analyzing optical mapping data. We apply our method to various assemblies of the loblolly pine, Francisella tularensis, rice and budgerigar genomes. We generated and used stimulated optical mapping data for loblolly pine and F.tularensis and used real optical mapping data for rice and budgerigar. RESULTS: Our results demonstrate that we detect more than 54% of extensively misassembled contigs and more than 60% of locally misassembled contigs in assemblies of F.tularensis and between 31% and 100% of extensively misassembled contigs and between 57% and 73% of locally misassembled contigs in assemblies of loblolly pine. Using the real optical mapping data, we correctly identified 75% of extensively misassembled contigs and 100% of locally misassembled contigs in rice, and 77% of extensively misassembled contigs and 80% of locally misassembled contigs in budgerigar. AVAILABILITY AND IMPLEMENTATION: misSEQuel can be used as a post-processing step in combination with any genome assembler and is freely available at http://www.cs.colostate.edu/seq/.

The genetic basis of chronic mountain sickness.

Chronic mountain sickness (CMS) is a disease that affects many high-altitude dwellers, particularly in the Andean Mountains in South America. The hallmark symptom of CMS is polycythemia, which causes increased risk of pulmonary hypertension and stroke (among other symptoms). A prevailing hypothesis in high-altitude medicine is that CMS results from a population-specific "maladaptation" to the hypoxic conditions at high altitude. In contrast, the prevalence of CMS is very low in other high-altitude populations (e.g., Tibetans and Ethiopians), which are seemingly well adapted to hypoxia. In recent years, concurrent with the advent of genomic technologies, several studies have investigated the genetic basis of adaptation to altitude. These studies have identified several candidate genes that may underlie the adaptation, or maladaptation. Interestingly, some of these genes are targeted by known drugs, raising the possibility of new treatments for CMS and other ischemic diseases. We review recent discoveries, alongside the methodologies used to obtain them, and outline some of the challenges remaining in the field.

Whole genome sequencing of Ethiopian highlanders reveals conserved hypoxia tolerance genes.

BACKGROUND: Although it has long been proposed that genetic factors contribute to adaptation to high altitude, such factors remain largely unverified. Recent advances in high-throughput sequencing have made it feasible to analyze genome-wide patterns of genetic variation in human populations. Since traditionally such studies surveyed only a small fraction of the genome, interpretation of the results was limited. RESULTS: We report here the results of the first whole genome resequencing-based analysis identifying genes that likely modulate high altitude adaptation in native Ethiopians residing at 3,500 m above sea level on Bale Plateau or Chennek field in Ethiopia. Using cross-population tests of selection, we identify regions with a significant loss of diversity, indicative of a selective sweep. We focus on a 208 kbp gene-rich region on chromosome 19, which is significant in both of the Ethiopian subpopulations sampled. This region contains eight protein-coding genes and spans 135 SNPs. To elucidate its potential role in hypoxia tolerance, we experimentally tested whether individual genes from the region affect hypoxia tolerance in Drosophila. Three genes significantly impact survival rates in low oxygen: cic, an ortholog of human CIC, Hsl, an ortholog of human LIPE, and Paf-AHα, an ortholog of human PAFAH1B3. CONCLUSIONS: Our study reveals evolutionarily conserved genes that modulate hypoxia tolerance. In addition, we show that many of our results would likely be unattainable using data from exome sequencing or microarray studies. This highlights the importance of whole genome sequencing for investigating adaptation by natural selection.

Whole-genome sequencing uncovers the genetic basis of chronic mountain sickness in Andean highlanders.

The hypoxic conditions at high altitudes present a challenge for survival, causing pressure for adaptation. Interestingly, many high-altitude denizens (particularly in the Andes) are maladapted, with a condition known as chronic mountain sickness (CMS) or Monge disease. To decode the genetic basis of this disease, we sequenced and compared the whole genomes of 20 Andean subjects (10 with CMS and 10 without). We discovered 11 regions genome-wide with significant differences in haplotype frequencies consistent with selective sweeps. In these regions, two genes (an erythropoiesis regulator, SENP1, and an oncogene, ANP32D) had a higher transcriptional response to hypoxia in individuals with CMS relative to those without. We further found that downregulating the orthologs of these genes in flies dramatically enhanced survival rates under hypoxia, demonstrating that suppression of SENP1 and ANP32D plays an essential role in hypoxia tolerance. Our study provides an unbiased framework to identify and validate the genetic basis of adaptation to high altitudes and identifies potentially targetable mechanisms for CMS treatment.

Learning natural selection from the site frequency spectrum.

Genetic adaptation to external stimuli occurs through the combined action of mutation and selection. A central problem in genetics is to identify loci responsive to specific selective constraints. Many tests have been proposed to identify the genomic signatures of natural selection by quantifying the skew in the site frequency spectrum (SFS) under selection relative to neutrality. We build upon recent work that connects many of these tests under a common framework, by describing how selective sweeps affect the scaled SFS. We show that the specific skew depends on many attributes of the sweep, including the selection coefficient and the time under selection. Using supervised learning on extensive simulated data, we characterize the features of the scaled SFS that best separate different types of selective sweeps from neutrality. We develop a test, SFselect, that consistently outperforms many existing tests over a wide range of selective sweeps. We apply SFselect to polymorphism data from a laboratory evolution experiment of Drosophila melanogaster adapted to hypoxia and identify loci that strengthen the role of the Notch pathway in hypoxia tolerance, but were missed by previous approaches. We further apply our test to human data and identify regions that are in agreement with earlier studies, as well as many novel regions.

SEQuel: improving the accuracy of genome assemblies.

MOTIVATION: Assemblies of next-generation sequencing (NGS) data, although accurate, still contain a substantial number of errors that need to be corrected after the assembly process. We develop SEQuel, a tool that corrects errors (i.e. insertions, deletions and substitution errors) in the assembled contigs. Fundamental to the algorithm behind SEQuel is the positional de Bruijn graph, a graph structure that models k-mers within reads while incorporating the approximate positions of reads into the model. RESULTS: SEQuel reduced the number of small insertions and deletions in the assemblies of standard multi-cell Escherichia coli data by almost half, and corrected between 30% and 94% of the substitution errors. Further, we show SEQuel is imperative to improving single-cell assembly, which is inherently more challenging due to higher error rates and non-uniform coverage; over half of the small indels, and substitution errors in the single-cell assemblies were corrected. We apply SEQuel to the recently assembled Deltaproteobacterium SAR324 genome, which is the first bacterial genome with a comprehensive single-cell genome assembly, and make over 800 changes (insertions, deletions and substitutions) to refine this assembly. AVAILABILITY: SEQuel can be used as a post-processing step in combination with any NGS assembler and is freely available at http://bix.ucsd.edu/SEQuel/.

Vaccinia virus infection suppresses the cell microRNA machinery.

MicroRNAs are key players in the regulation of gene expression by posttranscriptional suppression. They are involved in physiological processes, and thus their deregulation may contribute to the development of diseases and progression of cancer. Virus-encoded microRNAs and microRNAs of host origin play an important role in controlling the virus life cycle and immunity. The aim of this study was to determine the effect of vaccinia virus (VACV) infection on the expression of host-encoded microRNAs. A marked general suppression of most microRNAs in the infected cells was observed within 24 hours after VACV infection of a number of cell types. We demonstrate that this suppression was associated with abrogation of expression of the Dicer1 enzyme, which is a key enzyme in the generation of microRNAs.

Novel insight into the non-coding repertoire through deep sequencing analysis.

Non-coding RNAs (ncRNA) account for a large portion of the transcribed genomic output. This diverse family of untranslated RNA molecules play a crucial role in cellular function. The use of 'deep sequencing' technology (also known as 'next generation sequencing') to infer transcript expression levels in general, and ncRNA specifically, is becoming increasingly common in molecular and clinical laboratories. We developed a software termed 'RandA' (which stands for ncRNA Read-and-Analyze) that performs comprehensive ncRNA profiling and differential expression analysis on deep sequencing generated data through a graphical user interface running on a local personal computer. Using RandA, we reveal the complexity of the ncRNA repertoire in a given cell population. We further demonstrate the relevance of such an extensive ncRNA analysis by elucidating a multitude of characterizing features in pathogen infected mammalian cells. RandA is available for download at http://ibis.tau.ac.il/RandA.

miRNAkey: a software for microRNA deep sequencing analysis.

MOTIVATION: MicroRNAs (miRNAs) are short abundant non-coding RNAs critical for many cellular processes. Deep sequencing (next-generation sequencing) technologies are being readily used to receive a more accurate depiction of miRNA expression profiles in living cells. This type of analysis is a key step towards improving our understanding of the complexity and mode of miRNA regulation. RESULTS: miRNAkey is a software package designed to be used as a base-station for the analysis of miRNA deep sequencing data. The package implements common steps taken in the analysis of such data, as well as adds unique features, such as data statistics and multiple read determination, generating a novel platform for the analysis of miRNA expression. A user-friendly graphical interface is applied to determine the analysis steps. The tabular and graphical output contains general and detailed reports on the sequence reads and provides an accurate picture of the differentially expressed miRNAs in paired samples. AVAILABILITY AND IMPLEMENTATION: See http://ibis.tau.ac.il/miRNAkey CONTACT: nshomron@post.tau.ac.il SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DNA Sudoku--harnessing high-throughput sequencing for multiplexed specimen analysis.

Next-generation sequencers have sufficient power to analyze simultaneously DNAs from many different specimens, a practice known as multiplexing. Such schemes rely on the ability to associate each sequence read with the specimen from which it was derived. The current practice of appending molecular barcodes prior to pooling is practical for parallel analysis of up to many dozen samples. Here, we report a strategy that permits simultaneous analysis of tens of thousands of specimens. Our approach relies on the use of combinatorial pooling strategies in which pools rather than individual specimens are assigned barcodes. Thus, the identity of each specimen is encoded within the pooling pattern rather than by its association with a particular sequence tag. Decoding the pattern allows the sequence of an original specimen to be inferred with high confidence. We verified the ability of our encoding and decoding strategies to accurately report the sequence of individual samples within a large number of mixed specimens in two ways. First, we simulated data both from a clone library and from a human population in which a sequence variant associated with cystic fibrosis was present. Second, we actually pooled, sequenced, and decoded identities within two sets of 40,000 bacterial clones comprising approximately 20,000 different artificial microRNAs targeting Arabidopsis or human genes. We achieved greater than 97% accuracy in these trials. The strategies reported here can be applied to a wide variety of biological problems, including the determination of genotypic variation within large populations of individuals.