Publications by authors named "Stefano Lise"

29 Publications

  • Page 1 of 1

The Immunogenic Potential of Recurrent Cancer Drug Resistance Mutations: An Study.

Front Immunol 2020 8;11:524968. Epub 2020 Oct 8.

Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.

Cancer somatic mutations have been identified as a source of antigens that can be targeted by cancer immunotherapy. In this work, expanding on previous studies, we analyze the HLA-presentation properties of mutations that are known to drive resistance to cancer targeted-therapies. We survey a large dataset of mutations that confer resistance to different drugs and occur in numerous genes and tumor types. We show that a significant number of them are predicted to be potentially immunogenic across a large proportion of the human population. Further, by analyzing a cohort of patients carrying a small subset of these resistance mutations, we provide evidence that what is observed in the general population may be indicative of the mutations' immunogenic potential in resistant patients. Two of the mutations in our dataset had previously been experimentally validated by others and it was confirmed that some of their associated neopeptides elicit T-cell responses . The identification of potent cancer-specific antigens can be instrumental for developing more effective immunotherapies. In this work, we propose a novel list of drug-resistance mutations, several of which are recurrent, that could be of particular interest in the context of off-the-shelf precision immunotherapies such as therapeutic cancer vaccines.
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http://dx.doi.org/10.3389/fimmu.2020.524968DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7578429PMC
October 2020

Clinical Reversion Analysis Identifies Hotspot Mutations and Predicted Neoantigens Associated with Therapy Resistance.

Cancer Discov 2020 Oct 22;10(10):1475-1488. Epub 2020 Jul 22.

The CRUK Gene Function Laboratory, The Institute of Cancer Research, London, United Kingdom.

Reversion mutations in or are associated with resistance to PARP inhibitors and platinum. To better understand the nature of these mutations, we collated, codified, and analyzed more than 300 reversions. This identified reversion "hotspots" and "deserts" in regions encoding the and terminus, respectively, of BRCA2, suggesting that pathogenic mutations in these regions may be at higher or lower risk of reversion. Missense and splice-site pathogenic mutations in also appeared less likely to revert than truncating mutations. Most reversions were <100 bp deletions. Although many deletions exhibited microhomology, this was not universal, suggesting that multiple DNA-repair processes cause reversion. Finally, we found that many reversions were predicted to encode immunogenic neopeptides, suggesting a route to the treatment of reverted disease. As well as providing a freely available database for the collation of future reversion cases, these observations have implications for how drug resistance might be managed in -mutant cancers. SIGNIFICANCE: Reversion mutations in genes are a major cause of clinical platinum and PARP inhibitor resistance. This analysis of all reported clinical reversions suggests that the position of mutations affects the risk of reversion. Many reversions are also predicted to encode tumor neoantigens, providing a potential route to targeting resistance..
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http://dx.doi.org/10.1158/2159-8290.CD-19-1485DOI Listing
October 2020

Genome-wide plasma DNA methylation features of metastatic prostate cancer.

J Clin Invest 2020 04;130(4):1991-2000

University College London Cancer Institute, London, United Kingdom.

Tumor DNA circulates in the plasma of cancer patients admixed with DNA from noncancerous cells. The genomic landscape of plasma DNA has been characterized in metastatic castration-resistant prostate cancer (mCRPC) but the plasma methylome has not been extensively explored. Here, we performed next-generation sequencing (NGS) on plasma DNA with and without bisulfite treatment from mCRPC patients receiving either abiraterone or enzalutamide in the pre- or post-chemotherapy setting. Principal component analysis on the mCRPC plasma methylome indicated that the main contributor to methylation variance (principal component one, or PC1) was strongly correlated with genomically determined tumor fraction (r = -0.96; P < 10-8) and characterized by hypermethylation of targets of the polycomb repressor complex 2 components. Further deconvolution of the PC1 top-correlated segments revealed that these segments are comprised of methylation patterns specific to either prostate cancer or prostate normal epithelium. To extract information specific to an individual's cancer, we then focused on an orthogonal methylation signature, which revealed enrichment for androgen receptor binding sequences and hypomethylation of these segments associated with AR copy number gain. Individuals harboring this methylation pattern had a more aggressive clinical course. Plasma methylome analysis can accurately quantitate tumor fraction and identify distinct biologically relevant mCRPC phenotypes.
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http://dx.doi.org/10.1172/JCI130887DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7108919PMC
April 2020

Author Correction: Extreme intratumour heterogeneity and driver evolution in mismatch repair deficient gastro-oesophageal cancer.

Nat Commun 2020 Jan 29;11(1):675. Epub 2020 Jan 29.

Translational Oncogenomics Laboratory, Centre for Evolution and Cancer, The Institute of Cancer Research, London, SW3 6JB, United Kingdom.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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http://dx.doi.org/10.1038/s41467-020-14602-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6989513PMC
January 2020

Extreme intratumour heterogeneity and driver evolution in mismatch repair deficient gastro-oesophageal cancer.

Nat Commun 2020 01 16;11(1):139. Epub 2020 Jan 16.

Translational Oncogenomics Laboratory, Centre for Evolution and Cancer, The Institute of Cancer Research, London, SW3 6JB, United Kingdom.

Mismatch repair deficient (dMMR) gastro-oesophageal adenocarcinomas (GOAs) show better outcomes than their MMR-proficient counterparts and high immunotherapy sensitivity. The hypermutator-phenotype of dMMR tumours theoretically enables high evolvability but their evolution has not been investigated. Here we apply multi-region exome sequencing (MSeq) to four treatment-naive dMMR GOAs. This reveals extreme intratumour heterogeneity (ITH), exceeding ITH in other cancer types >20-fold, but also long phylogenetic trunks which may explain the exquisite immunotherapy sensitivity of dMMR tumours. Subclonal driver mutations are common and parallel evolution occurs in RAS, PIK3CA, SWI/SNF-complex genes and in immune evasion regulators. MSeq data and evolution analysis of single region-data from 64 MSI GOAs show that chromosome 8 gains are early genetic events and that the hypermutator-phenotype remains active during progression. MSeq may be necessary for biomarker development in these heterogeneous cancers. Comparison with other MSeq-analysed tumour types reveals mutation rates and their timing to determine phylogenetic tree morphologies.
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http://dx.doi.org/10.1038/s41467-019-13915-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6965135PMC
January 2020

Modeling of Chemoresistant Neuroblastoma Provides New Insights into Chemorefractory Disease and Metastasis.

Cancer Res 2019 10 12;79(20):5382-5393. Epub 2019 Aug 12.

Division of Clinical Studies, The Institute of Cancer Research, London, United Kingdom.

Neuroblastoma is a pediatric cancer that is frequently metastatic and resistant to conventional treatment. In part, a lack of natively metastatic, chemoresistant models has limited our insight into the development of aggressive disease. The Th- genetically engineered mouse model develops rapidly progressive chemosensitive neuroblastoma and lacks clinically relevant metastases. To study tumor progression in a context more reflective of clinical therapy, we delivered multicycle treatment with cyclophosphamide to Th- mice, individualizing therapy using MRI, to generate the Th- model. These mice developed chemoresistance and spontaneous bone marrow metastases. Tumors exhibited an altered immune microenvironment with increased stroma and tumor-associated fibroblasts. Analysis of copy number aberrations revealed genomic changes characteristic of human -amplified neuroblastoma, specifically copy number gains at mouse chromosome 11, syntenic with gains on human chromosome 17q. RNA sequencing revealed enriched expression of genes associated with 17q gain and upregulation of genes associated with high-risk neuroblastoma, such as the cell-cycle regulator cyclin B1-interacting protein 1 () and thymidine kinase (). The antiapoptotic, prometastatic JAK-STAT3 pathway was activated in chemoresistant tumors, and treatment with the JAK1/JAK2 inhibitor CYT387 reduced progression of chemoresistant tumors and increased survival. Our results highlight that under treatment conditions that mimic chemotherapy in human patients, Th- mice develop genomic, microenvironmental, and clinical features reminiscent of human chemorefractory disease. The Th- model therefore is a useful tool to dissect in detail mechanisms that drive metastasis and chemoresistance, and highlights dysregulation of signaling pathways such as JAK-STAT3 that could be targeted to improve treatment of aggressive disease. SIGNIFICANCE: An mouse model of high-risk treatment-resistant neuroblastoma exhibits changes in the tumor microenvironment, widespread metastases, and sensitivity to JAK1/2 inhibition.
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http://dx.doi.org/10.1158/0008-5472.CAN-18-2759DOI Listing
October 2019

Identification of single nucleotide variants using position-specific error estimation in deep sequencing data.

BMC Med Genomics 2019 08 2;12(1):115. Epub 2019 Aug 2.

Centre for Evolution and Cancer, The Institute of Cancer Research, London, UK.

Background: Targeted deep sequencing is a highly effective technology to identify known and novel single nucleotide variants (SNVs) with many applications in translational medicine, disease monitoring and cancer profiling. However, identification of SNVs using deep sequencing data is a challenging computational problem as different sequencing artifacts limit the analytical sensitivity of SNV detection, especially at low variant allele frequencies (VAFs).

Methods: To address the problem of relatively high noise levels in amplicon-based deep sequencing data (e.g. with the Ion AmpliSeq technology) in the context of SNV calling, we have developed a new bioinformatics tool called AmpliSolve. AmpliSolve uses a set of normal samples to model position-specific, strand-specific and nucleotide-specific background artifacts (noise), and deploys a Poisson model-based statistical framework for SNV detection.

Results: Our tests on both synthetic and real data indicate that AmpliSolve achieves a good trade-off between precision and sensitivity, even at VAF below 5% and as low as 1%. We further validate AmpliSolve by applying it to the detection of SNVs in 96 circulating tumor DNA samples at three clinically relevant genomic positions and compare the results to digital droplet PCR experiments.

Conclusions: AmpliSolve is a new tool for in-silico estimation of background noise and for detection of low frequency SNVs in targeted deep sequencing data. Although AmpliSolve has been specifically designed for and tested on amplicon-based libraries sequenced with the Ion Torrent platform it can, in principle, be applied to other sequencing platforms as well. AmpliSolve is freely available at https://github.com/dkleftogi/AmpliSolve .
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http://dx.doi.org/10.1186/s12920-019-0557-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6679440PMC
August 2019

Genomic and Transcriptomic Determinants of Therapy Resistance and Immune Landscape Evolution during Anti-EGFR Treatment in Colorectal Cancer.

Cancer Cell 2019 07;36(1):35-50.e9

Translational Oncogenomics Lab, The Institute of Cancer Research, 237 Fulham Road, London SW3 6JB, UK; GI Cancer Unit, The Royal Marsden Hospital, London SW3 6JJ, UK. Electronic address:

Despite biomarker stratification, the anti-EGFR antibody cetuximab is only effective against a subgroup of colorectal cancers (CRCs). This genomic and transcriptomic analysis of the cetuximab resistance landscape in 35 RAS wild-type CRCs identified associations of NF1 and non-canonical RAS/RAF aberrations with primary resistance and validated transcriptomic CRC subtypes as non-genetic predictors of benefit. Sixty-four percent of biopsies with acquired resistance harbored no genetic resistance drivers. Most of these had switched from a cetuximab-sensitive transcriptomic subtype at baseline to a fibroblast- and growth factor-rich subtype at progression. Fibroblast-supernatant conferred cetuximab resistance in vitro, confirming a major role for non-genetic resistance through stromal remodeling. Cetuximab treatment increased cytotoxic immune infiltrates and PD-L1 and LAG3 immune checkpoint expression, potentially providing opportunities to treat cetuximab-resistant CRCs with immunotherapy.
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http://dx.doi.org/10.1016/j.ccell.2019.05.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6617392PMC
July 2019

Mutations in MAST1 Cause Mega-Corpus-Callosum Syndrome with Cerebellar Hypoplasia and Cortical Malformations.

Neuron 2018 12 15;100(6):1354-1368.e5. Epub 2018 Nov 15.

Research Institute of Molecular Pathology, Campus Vienna Biocenter 1, Vienna Biocenter (VBC), Vienna 1030, Austria. Electronic address:

Corpus callosum malformations are associated with a broad range of neurodevelopmental diseases. We report that de novo mutations in MAST1 cause mega-corpus-callosum syndrome with cerebellar hypoplasia and cortical malformations (MCC-CH-CM) in the absence of megalencephaly. We show that MAST1 is a microtubule-associated protein that is predominantly expressed in post-mitotic neurons and is present in both dendritic and axonal compartments. We further show that Mast1 null animals are phenotypically normal, whereas the deletion of a single amino acid (L278del) recapitulates the distinct neurological phenotype observed in patients. In animals harboring Mast1 microdeletions, we find that the PI3K/AKT3/mTOR pathway is unperturbed, whereas Mast2 and Mast3 levels are diminished, indicative of a dominant-negative mode of action. Finally, we report that de novo MAST1 substitutions are present in patients with autism and microcephaly, raising the prospect that mutations in this gene give rise to a spectrum of neurodevelopmental diseases.
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http://dx.doi.org/10.1016/j.neuron.2018.10.044DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6436622PMC
December 2018

Microenvironmental niche divergence shapes BRCA1-dysregulated ovarian cancer morphological plasticity.

Nat Commun 2018 09 25;9(1):3917. Epub 2018 Sep 25.

Centre for Evolution and Cancer, The Institute of Cancer Research, London, SM2 5NG, UK.

How tumor microenvironmental forces shape plasticity of cancer cell morphology is poorly understood. Here, we conduct automated histology image and spatial statistical analyses in 514 high grade serous ovarian samples to define cancer morphological diversification within the spatial context of the microenvironment. Tumor spatial zones, where cancer cell nuclei diversify in shape, are mapped in each tumor. Integration of this spatially explicit analysis with omics and clinical data reveals a relationship between morphological diversification and the dysregulation of DNA repair, loss of nuclear integrity, and increased disease mortality. Within the Immunoreactive subtype, spatial analysis further reveals significantly lower lymphocytic infiltration within diversified zones compared with other tumor zones, suggesting that even immune-hot tumors contain cells capable of immune escape. Our findings support a model whereby a subpopulation of morphologically plastic cancer cells with dysregulated DNA repair promotes ovarian cancer progression through positive selection by immune evasion.
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http://dx.doi.org/10.1038/s41467-018-06130-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156340PMC
September 2018

Ultra-Sensitive Mutation Detection and Genome-Wide DNA Copy Number Reconstruction by Error-Corrected Circulating Tumor DNA Sequencing.

Clin Chem 2018 11 27;64(11):1626-1635. Epub 2018 Aug 27.

Centre for Evolution and Cancer, Division of Molecular Pathology, The Institute of Cancer Research, London, UK;

Background: Circulating free DNA sequencing (cfDNA-Seq) can portray cancer genome landscapes, but highly sensitive and specific technologies are necessary to accurately detect mutations with often low variant frequencies.

Methods: We developed a customizable hybrid-capture cfDNA-Seq technology using off-the-shelf molecular barcodes and a novel duplex DNA molecule identification tool for enhanced error correction.

Results: Modeling based on cfDNA yields from 58 patients showed that this technology, requiring 25 ng of cfDNA, could be applied to >95% of patients with metastatic colorectal cancer (mCRC). cfDNA-Seq of a 32-gene, 163.3-kbp target region detected 100% of single-nucleotide variants, with 0.15% variant frequency in spike-in experiments. Molecular barcode error correction reduced false-positive mutation calls by 97.5%. In 28 consecutively analyzed patients with mCRC, 80 out of 91 mutations previously detected by tumor tissue sequencing were called in the cfDNA. Call rates were similar for point mutations and indels. cfDNA-Seq identified typical mCRC driver mutations in patients in whom biopsy sequencing had failed or did not include key mCRC driver genes. Mutations only called in cfDNA but undetectable in matched biopsies included a subclonal resistance driver mutation to anti-EGFR antibodies in , parallel evolution of multiple mutations in 2 cases, and mutations originating from clonal hematopoiesis. Furthermore, cfDNA-Seq off-target read analysis allowed simultaneous genome-wide copy number profile reconstruction in 20 of 28 cases. Copy number profiles were validated by low-coverage whole-genome sequencing.

Conclusions: This error-corrected, ultradeep cfDNA-Seq technology with a customizable target region and publicly available bioinformatics tools enables broad insights into cancer genomes and evolution.

Clinicaltrialsgov Identifier: NCT02112357.
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http://dx.doi.org/10.1373/clinchem.2018.289629DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6214522PMC
November 2018

A Novel Strategy Combining Array-CGH, Whole-exome Sequencing and In Utero Electroporation in Rodents to Identify Causative Genes for Brain Malformations.

J Vis Exp 2017 12 1(130). Epub 2017 Dec 1.

INSERM INMED; Aix-Marseille University;

Birth defects that involve the cerebral cortex - also known as malformations of cortical development (MCD) - are important causes of intellectual disability and account for 20-40% of drug-resistant epilepsy in childhood. High-resolution brain imaging has facilitated in vivo identification of a large group of MCD phenotypes. Despite the advances in brain imaging, genomic analysis and generation of animal models, a straightforward workflow to systematically prioritize candidate genes and to test functional effects of putative mutations is missing. To overcome this problem, an experimental strategy enabling the identification of novel causative genes for MCD was developed and validated. This strategy is based on identifying candidate genomic regions or genes via array-CGH or whole-exome sequencing and characterizing the effects of their inactivation or of overexpression of specific mutations in developing rodent brains via in utero electroporation. This approach led to the identification of the C6orf70 gene, encoding for a putative vesicular protein, to the pathogenesis of periventricular nodular heterotopia, a MCD caused by defective neuronal migration.
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http://dx.doi.org/10.3791/53570DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5755514PMC
December 2017

Making the most of RNA-seq: Pre-processing sequencing data with Opossum for reliable SNP variant detection.

Wellcome Open Res 2017 Jan 17;2. Epub 2017 Jan 17.

Centre for Evolution and Cancer, The Institute of Cancer Research, Sutton, UK.

Identifying variants from RNA-seq (transcriptome sequencing) data is a cost-effective and versatile alternative to whole-genome sequencing. However, current variant callers do not generally behave well with RNA-seq data due to reads encompassing intronic regions. We have developed a software programme called Opossum to address this problem. Opossum pre-processes RNA-seq reads prior to variant calling, and although it has been designed to work specifically with Platypus, it can be used equally well with other variant callers such as GATK HaplotypeCaller. In this work, we show that using Opossum in conjunction with either Platypus or GATK HaplotypeCaller maintains precision and improves the sensitivity for SNP detection compared to the GATK Best Practices pipeline. In addition, using it in combination with Platypus offers a substantial reduction in run times compared to the GATK pipeline so it is ideal when there are only limited time or computational resources available.
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http://dx.doi.org/10.12688/wellcomeopenres.10501.2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322827PMC
January 2017

Combination of Whole Genome Sequencing, Linkage, and Functional Studies Implicates a Missense Mutation in Titin as a Cause of Autosomal Dominant Cardiomyopathy With Features of Left Ventricular Noncompaction.

Circ Cardiovasc Genet 2016 Oct 13;9(5):426-435. Epub 2016 Sep 13.

Background: High throughput next-generation sequencing techniques have made whole genome sequencing accessible in clinical practice; however, the abundance of variation in the human genomes makes the identification of a disease-causing mutation on a background of benign rare variants challenging.

Methods And Results: Here we combine whole genome sequencing with linkage analysis in a 3-generation family affected by cardiomyopathy with features of autosomal dominant left ventricular noncompaction cardiomyopathy. A missense mutation in the giant protein titin is the only plausible disease-causing variant that segregates with disease among the 7 surviving affected individuals, with interrogation of the entire genome excluding other potential causes. This A178D missense mutation, affecting a conserved residue in the second immunoglobulin-like domain of titin, was introduced in a bacterially expressed recombinant protein fragment and biophysically characterized in comparison to its wild-type counterpart. Multiple experiments, including size exclusion chromatography, small-angle x ray scattering, and circular dichroism spectroscopy suggest partial unfolding and domain destabilization in the presence of the mutation. Moreover, binding experiments in mammalian cells show that the mutation markedly impairs binding to the titin ligand telethonin.

Conclusions: Here we present genetic and functional evidence implicating the novel A178D missense mutation in titin as the cause of a highly penetrant familial cardiomyopathy with features of left ventricular noncompaction. This expands the spectrum of titin's roles in cardiomyopathies. It furthermore highlights that rare titin missense variants, currently often ignored or left uninterpreted, should be considered to be relevant for cardiomyopathies and can be identified by the approach presented here.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5068189PMC
http://dx.doi.org/10.1161/CIRCGENETICS.116.001431DOI Listing
October 2016

Autosomal dominant osteopetrosis associated with renal tubular acidosis is due to a CLCN7 mutation.

Am J Med Genet A 2016 11 19;170(11):2988-2992. Epub 2016 Aug 19.

Academic Endocrine Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Oxford, United Kingdom.

The aim of this study was to identify the causative mutation in a family with an unusual presentation of autosomal dominant osteopetrosis (OPT), proximal renal tubular acidosis (RTA), renal stones, epilepsy, and blindness, a combination of features not previously reported. We undertook exome sequencing of one affected and one unaffected family member, followed by targeted analysis of known candidate genes to identify the causative mutation. This identified a missense mutation (c.643G>A; p.Gly215Arg) in the gene encoding the chloride/proton antiporter 7 (gene CLCN7, protein CLC-7), which was confirmed by amplification refractory mutation system (ARMS)-PCR, and to be present in the three available patients. CLC-7 mutations are known to cause autosomal dominant OPT type 2, also called Albers-Schonberg disease, which is characterized by osteosclerosis, predominantly of the spine, pelvis and skull base, resulting in bone fragility and fractures. Albers-Schonberg disease is not reported to be associated with RTA, but autosomal recessive OPT type 3 (OPTB3) with RTA is associated with carbonic anhydrase type 2 (CA2) mutations. No mutations were detected in CA2 or any other genes known to cause proximal RTA. Neither CLCN7 nor CA2 mutations have previously been reported to be associated with renal stones or epilepsy. Thus, we identified a CLCN7 mutation in a family with autosomal dominant osteopetrosis, RTA, renal stones, epilepsy, and blindness. © 2016 Wiley Periodicals, Inc.
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http://dx.doi.org/10.1002/ajmg.a.37755DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5132132PMC
November 2016

Premalignant SOX2 overexpression in the fallopian tubes of ovarian cancer patients: Discovery and validation studies.

EBioMedicine 2016 Aug 2;10:137-49. Epub 2016 Jul 2.

Ovarian Cancer Cell Laboratory, Weatherall Institute of Molecular Medicine, University of Oxford, Headington, Oxford OX3 9DS, UK; Nuffield Department of Obstetrics and Gynaecology, University of Oxford, Women's Centre, John Radcliffe Hospital, Oxford OX3 9DU, UK. Electronic address:

Current screening methods for ovarian cancer can only detect advanced disease. Earlier detection has proved difficult because the molecular precursors involved in the natural history of the disease are unknown. To identify early driver mutations in ovarian cancer cells, we used dense whole genome sequencing of micrometastases and microscopic residual disease collected at three time points over three years from a single patient during treatment for high-grade serous ovarian cancer (HGSOC). The functional and clinical significance of the identified mutations was examined using a combination of population-based whole genome sequencing, targeted deep sequencing, multi-center analysis of protein expression, loss of function experiments in an in-vivo reporter assay and mammalian models, and gain of function experiments in primary cultured fallopian tube epithelial (FTE) cells. We identified frequent mutations involving a 40kb distal repressor region for the key stem cell differentiation gene SOX2. In the apparently normal FTE, the region was also mutated. This was associated with a profound increase in SOX2 expression (p<2(-16)), which was not found in patients without cancer (n=108). Importantly, we show that SOX2 overexpression in FTE is nearly ubiquitous in patients with HGSOCs (n=100), and common in BRCA1-BRCA2 mutation carriers (n=71) who underwent prophylactic salpingo-oophorectomy. We propose that the finding of SOX2 overexpression in FTE could be exploited to develop biomarkers for detecting disease at a premalignant stage, which would reduce mortality from this devastating disease.
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http://dx.doi.org/10.1016/j.ebiom.2016.06.048DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5006641PMC
August 2016

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders.

Authors:
Jenny C Taylor Hilary C Martin Stefano Lise John Broxholme Jean-Baptiste Cazier Andy Rimmer Alexander Kanapin Gerton Lunter Simon Fiddy Chris Allan A Radu Aricescu Moustafa Attar Christian Babbs Jennifer Becq David Beeson Celeste Bento Patricia Bignell Edward Blair Veronica J Buckle Katherine Bull Ondrej Cais Holger Cario Helen Chapel Richard R Copley Richard Cornall Jude Craft Karin Dahan Emma E Davenport Calliope Dendrou Olivier Devuyst Aimée L Fenwick Jonathan Flint Lars Fugger Rodney D Gilbert Anne Goriely Angie Green Ingo H Greger Russell Grocock Anja V Gruszczyk Robert Hastings Edouard Hatton Doug Higgs Adrian Hill Chris Holmes Malcolm Howard Linda Hughes Peter Humburg David Johnson Fredrik Karpe Zoya Kingsbury Usha Kini Julian C Knight Jonathan Krohn Sarah Lamble Craig Langman Lorne Lonie Joshua Luck Davis McCarthy Simon J McGowan Mary Frances McMullin Kerry A Miller Lisa Murray Andrea H Németh M Andrew Nesbit David Nutt Elizabeth Ormondroyd Annette Bang Oturai Alistair Pagnamenta Smita Y Patel Melanie Percy Nayia Petousi Paolo Piazza Sian E Piret Guadalupe Polanco-Echeverry Niko Popitsch Fiona Powrie Chris Pugh Lynn Quek Peter A Robbins Kathryn Robson Alexandra Russo Natasha Sahgal Pauline A van Schouwenburg Anna Schuh Earl Silverman Alison Simmons Per Soelberg Sørensen Elizabeth Sweeney John Taylor Rajesh V Thakker Ian Tomlinson Amy Trebes Stephen Rf Twigg Holm H Uhlig Paresh Vyas Tim Vyse Steven A Wall Hugh Watkins Michael P Whyte Lorna Witty Ben Wright Chris Yau David Buck Sean Humphray Peter J Ratcliffe John I Bell Andrew Om Wilkie David Bentley Peter Donnelly Gilean McVean

Nat Genet 2015 Jul 18;47(7):717-726. Epub 2015 May 18.

Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.
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http://dx.doi.org/10.1038/ng.3304DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4601524PMC
July 2015

Periventricular heterotopia in 6q terminal deletion syndrome: role of the C6orf70 gene.

Brain 2013 Nov 20;136(Pt 11):3378-94. Epub 2013 Sep 20.

1 Paediatric Neurology and Neurogenetics Unit and Laboratories, A. Meyer Children's Hospital - Department of Neuroscience, Pharmacology and Child Health, University of Florence, 50139, Florence, Italy.

Periventricular nodular heterotopia is caused by defective neuronal migration that results in heterotopic neuronal nodules lining the lateral ventricles. Mutations in filamin A (FLNA) or ADP-ribosylation factor guanine nucleotide-exchange factor 2 (ARFGEF2) cause periventricular nodular heterotopia, but most patients with this malformation do not have a known aetiology. Using comparative genomic hybridization, we identified 12 patients with developmental brain abnormalities, variably combining periventricular nodular heterotopia, corpus callosum dysgenesis, colpocephaly, cerebellar hypoplasia and polymicrogyria, harbouring a common 1.2 Mb minimal critical deletion in 6q27. These anatomic features were mainly associated with epilepsy, ataxia and cognitive impairment. Using whole exome sequencing in 14 patients with isolated periventricular nodular heterotopia but no copy number variants, we identified one patient with periventricular nodular heterotopia, developmental delay and epilepsy and a de novo missense mutation in the chromosome 6 open reading frame 70 (C6orf70) gene, mapping in the minimal critical deleted region. Using immunohistochemistry and western blots, we demonstrated that in human cell lines, C6orf70 shows primarily a cytoplasmic vesicular puncta-like distribution and that the mutation affects its stability and subcellular distribution. We also performed in utero silencing of C6orf70 and of Phf10 and Dll1, the two additional genes mapping in the 6q27 minimal critical deleted region that are expressed in human and rodent brain. Silencing of C6orf70 in the developing rat neocortex produced periventricular nodular heterotopia that was rescued by concomitant expression of wild-type human C6orf70 protein. Silencing of the contiguous Phf10 or Dll1 genes only produced slightly delayed migration but not periventricular nodular heterotopia. The complex brain phenotype observed in the 6q terminal deletion syndrome likely results from the combined haploinsufficiency of contiguous genes mapping to a small 1.2 Mb region. Our data suggest that, of the genes within this minimal critical region, C6orf70 plays a major role in the control of neuronal migration and its haploinsufficiency or mutation causes periventricular nodular heterotopia.
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http://dx.doi.org/10.1093/brain/awt249DOI Listing
November 2013

Next generation sequencing for molecular diagnosis of neurological disorders using ataxias as a model.

Brain 2013 Oct 11;136(Pt 10):3106-18. Epub 2013 Sep 11.

1 Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK.

Many neurological conditions are caused by immensely heterogeneous gene mutations. The diagnostic process is often long and complex with most patients undergoing multiple invasive and costly investigations without ever reaching a conclusive molecular diagnosis. The advent of massively parallel, next-generation sequencing promises to revolutionize genetic testing and shorten the 'diagnostic odyssey' for many of these patients. We performed a pilot study using heterogeneous ataxias as a model neurogenetic disorder to assess the introduction of next-generation sequencing into clinical practice. We captured 58 known human ataxia genes followed by Illumina Next-Generation Sequencing in 50 highly heterogeneous patients with ataxia who had been extensively investigated and were refractory to diagnosis. All cases had been tested for spinocerebellar ataxia 1-3, 6, 7 and Friedrich's ataxia and had multiple other biochemical, genetic and invasive tests. In those cases where we identified the genetic mutation, we determined the time to diagnosis. Pathogenicity was assessed using a bioinformatics pipeline and novel variants were validated using functional experiments. The overall detection rate in our heterogeneous cohort was 18% and varied from 8.3% in those with an adult onset progressive disorder to 40% in those with a childhood or adolescent onset progressive disorder. The highest detection rate was in those with an adolescent onset and a family history (75%). The majority of cases with detectable mutations had a childhood onset but most are now adults, reflecting the long delay in diagnosis. The delays were primarily related to lack of easily available clinical testing, but other factors included the presence of atypical phenotypes and the use of indirect testing. In the cases where we made an eventual diagnosis, the delay was 3-35 years (mean 18.1 years). Alignment and coverage metrics indicated that the capture and sequencing was highly efficient and the consumable cost was ∼£400 (€460 or US$620). Our pathogenicity interpretation pathway predicted 13 different mutations in eight different genes: PRKCG, TTBK2, SETX, SPTBN2, SACS, MRE11, KCNC3 and DARS2 of which nine were novel including one causing a newly described recessive ataxia syndrome. Genetic testing using targeted capture followed by next-generation sequencing was efficient, cost-effective, and enabled a molecular diagnosis in many refractory cases. A specific challenge of next-generation sequencing data is pathogenicity interpretation, but functional analysis confirmed the pathogenicity of novel variants showing that the pipeline was robust. Our results have broad implications for clinical neurology practice and the approach to diagnostic testing.
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http://dx.doi.org/10.1093/brain/awt236DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3784284PMC
October 2013

Recessive mutations in SPTBN2 implicate β-III spectrin in both cognitive and motor development.

PLoS Genet 2012 6;8(12):e1003074. Epub 2012 Dec 6.

Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.

β-III spectrin is present in the brain and is known to be important in the function of the cerebellum. Heterozygous mutations in SPTBN2, the gene encoding β-III spectrin, cause Spinocerebellar Ataxia Type 5 (SCA5), an adult-onset, slowly progressive, autosomal-dominant pure cerebellar ataxia. SCA5 is sometimes known as "Lincoln ataxia," because the largest known family is descended from relatives of the United States President Abraham Lincoln. Using targeted capture and next-generation sequencing, we identified a homozygous stop codon in SPTBN2 in a consanguineous family in which childhood developmental ataxia co-segregates with cognitive impairment. The cognitive impairment could result from mutations in a second gene, but further analysis using whole-genome sequencing combined with SNP array analysis did not reveal any evidence of other mutations. We also examined a mouse knockout of β-III spectrin in which ataxia and progressive degeneration of cerebellar Purkinje cells has been previously reported and found morphological abnormalities in neurons from prefrontal cortex and deficits in object recognition tasks, consistent with the human cognitive phenotype. These data provide the first evidence that β-III spectrin plays an important role in cortical brain development and cognition, in addition to its function in the cerebellum; and we conclude that cognitive impairment is an integral part of this novel recessive ataxic syndrome, Spectrin-associated Autosomal Recessive Cerebellar Ataxia type 1 (SPARCA1). In addition, the identification of SPARCA1 and normal heterozygous carriers of the stop codon in SPTBN2 provides insights into the mechanism of molecular dominance in SCA5 and demonstrates that the cell-specific repertoire of spectrin subunits underlies a novel group of disorders, the neuronal spectrinopathies, which includes SCA5, SPARCA1, and a form of West syndrome.
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http://dx.doi.org/10.1371/journal.pgen.1003074DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3516553PMC
May 2013

Next-generation sequencing (NGS) as a diagnostic tool for retinal degeneration reveals a much higher detection rate in early-onset disease.

Eur J Hum Genet 2013 Mar 12;21(3):274-80. Epub 2012 Sep 12.

Oxford Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.

Inherited retinal degeneration (IRD) is a common cause of visual impairment (prevalence ∼1/3500). There is considerable phenotype and genotype heterogeneity, making a specific diagnosis very difficult without molecular testing. We investigated targeted capture combined with next-generation sequencing using Nimblegen 12plex arrays and the Roche 454 sequencing platform to explore its potential for clinical diagnostics in two common types of IRD, retinitis pigmentosa and cone-rod dystrophy. 50 patients (36 unknowns and 14 positive controls) were screened, and pathogenic mutations were identified in 25% of patients in the unknown, with 53% in the early-onset cases. All patients with new mutations detected had an age of onset <21 years and 44% had a family history. Thirty-one percent of mutations detected were novel. A de novo mutation in rhodopsin was identified in one early-onset case without a family history. Bioinformatic pipelines were developed to identify likely pathogenic mutations and stringent criteria were used for assignment of pathogenicity. Analysis of sequencing metrics revealed significant variability in capture efficiency and depth of coverage. We conclude that targeted capture and next-generation sequencing are likely to be very useful in a diagnostic setting, but patients with earlier onset of disease are more likely to benefit from using this strategy. The mutation-detection rate suggests that many patients are likely to have mutations in novel genes.
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http://dx.doi.org/10.1038/ejhg.2012.172DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3573204PMC
March 2013

Next-generation sequencing in health-care delivery: lessons from the functional analysis of rhodopsin.

Genet Med 2012 Nov 12;14(11):891-9. Epub 2012 Jul 12.

Nuffield Department of Clinical Neuroscience, Nuffield Laboratory of Ophthalmology, John Radcliffe Hospital, University of Oxford, UK.

Purpose: The interpretation of genetic information has always been challenging, but next-generation sequencing produces data on such a vast scale that many more variants of uncertain pathogenicity will be found. We exemplify this issue with reference to human rhodopsin, in which pathogenic mutations can lead to autosomal dominant retinitis pigmentosa.

Methods: Rhodopsin variants, with unknown pathogenicity, were found in patients by next-generation and Sanger sequencing and a multidisciplinary approach was used to determine their functional significance.

Results: Four variants in rhodopsin were identified: F45L, P53R, R69H, and M39R, with the latter two substitutions being novel. We investigated the cellular transport and photopigment function of all four human substitutions and found that the F45L and R69H variants behave like wild-type and are highly unlikely to be pathogenic. By contrast, P53R (a de novo change) and M39R were retained in the endoplasmic reticulum with significantly reduced functionality and are clearly pathogenic.

Conclusion: Potential pathogenicity of variants requires careful assessment using clinical, genetic, and functional data. We suggest that a multidisciplinary pathway of assessment, using several functional assays, will be required if next-generation sequencing is to be used effectively, reliably, and safely in the clinical environment.
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http://dx.doi.org/10.1038/gim.2012.73DOI Listing
November 2012

PepSite: prediction of peptide-binding sites from protein surfaces.

Nucleic Acids Res 2012 Jul 16;40(Web Server issue):W423-7. Epub 2012 May 16.

CellNetworks, University of Heidelberg, 69120 Heidelberg, Germany.

Complex biological functions emerge through intricate protein-protein interaction networks. An important class of protein-protein interaction corresponds to peptide-mediated interactions, in which a short peptide stretch from one partner interacts with a large protein surface from the other partner. Protein-peptide interactions are typically of low affinity and involved in regulatory mechanisms, dynamically reshaping protein interaction networks. Due to the relatively small interaction surface, modulation of protein-peptide interactions is feasible and highly attractive for therapeutic purposes. Unfortunately, the number of available 3D structures of protein-peptide interfaces is very limited. For typical cases where a protein-peptide structure of interest is not available, the PepSite web server can be used to predict peptide-binding spots from protein surfaces alone. The PepSite method relies on preferred peptide-binding environments calculated from a set of known protein-peptide 3D structures, combined with distance constraints derived from known peptides. We present an updated version of the web server that is orders of magnitude faster than the original implementation, returning results in seconds instead of minutes or hours. The PepSite web server is available at http://pepsite2.russelllab.org.
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http://dx.doi.org/10.1093/nar/gks398DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394340PMC
July 2012

Exome sequencing can detect pathogenic mosaic mutations present at low allele frequencies.

J Hum Genet 2012 Jan 1;57(1):70-2. Epub 2011 Dec 1.

NIHR Biomedical Research Centre, Wellcome Trust Centre for Human Genetics, Oxford, UK.

The development of next generation sequencing (NGS) has radically transformed the scientific landscape, making it possible to sequence the exome of any given individual in a cost-effective way. The power of this approach has been demonstrated by a number of groups who have identified pathogenic mutations in small pedigrees that have been resistant to traditional genetic mapping. Recently it has become clear that exome sequencing has great potential with respect to sporadic disease and the identification of de novo mutations. This is highlighted by studies reporting whole-exome sequencing of patient-parental trios affected by learning disability, autism and schizophrenia. It is widely anticipated that the introduction of this technique into a clinical setting will revolutionise genetic diagnosis. However, the sensitivity of NGS exome sequencing is currently unclear. Here, we describe the exome sequencing of DNA samples from a patient with double cortex syndrome and her parents, resulting in the detection of a mosaic splicing mutation in LIS1. This variant was found at an allele frequency of just 18%, demonstrating that NGS methods have the capacity to identify pathogenic mosaic mutations present at a low level.
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http://dx.doi.org/10.1038/jhg.2011.128DOI Listing
January 2012

Predictions of hot spot residues at protein-protein interfaces using support vector machines.

PLoS One 2011 Feb 28;6(2):e16774. Epub 2011 Feb 28.

Department of Computer Science, University College London, London, United Kingdom.

Protein-protein interactions are critically dependent on just a few 'hot spot' residues at the interface. Hot spots make a dominant contribution to the free energy of binding and they can disrupt the interaction if mutated to alanine. Here, we present HSPred, a support vector machine(SVM)-based method to predict hot spot residues, given the structure of a complex. HSPred represents an improvement over a previously described approach (Lise et al, BMC Bioinformatics 2009, 10:365). It achieves higher accuracy by treating separately predictions involving either an arginine or a glutamic acid residue. These are the amino acid types on which the original model did not perform well. We have therefore developed two additional SVM classifiers, specifically optimised for these cases. HSPred reaches an overall precision and recall respectively of 61% and 69%, which roughly corresponds to a 10% improvement. An implementation of the described method is available as a web server at http://bioinf.cs.ucl.ac.uk/hspred. It is free to non-commercial users.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0016774PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3046169PMC
February 2011

Prediction of hot spot residues at protein-protein interfaces by combining machine learning and energy-based methods.

BMC Bioinformatics 2009 Oct 30;10:365. Epub 2009 Oct 30.

Department of Computer Science, University College London, UK.

Background: Alanine scanning mutagenesis is a powerful experimental methodology for investigating the structural and energetic characteristics of protein complexes. Individual amino-acids are systematically mutated to alanine and changes in free energy of binding (DeltaDeltaG) measured. Several experiments have shown that protein-protein interactions are critically dependent on just a few residues ("hot spots") at the interface. Hot spots make a dominant contribution to the free energy of binding and if mutated they can disrupt the interaction. As mutagenesis studies require significant experimental efforts, there is a need for accurate and reliable computational methods. Such methods would also add to our understanding of the determinants of affinity and specificity in protein-protein recognition.

Results: We present a novel computational strategy to identify hot spot residues, given the structure of a complex. We consider the basic energetic terms that contribute to hot spot interactions, i.e. van der Waals potentials, solvation energy, hydrogen bonds and Coulomb electrostatics. We treat them as input features and use machine learning algorithms such as Support Vector Machines and Gaussian Processes to optimally combine and integrate them, based on a set of training examples of alanine mutations. We show that our approach is effective in predicting hot spots and it compares favourably to other available methods. In particular we find the best performances using Transductive Support Vector Machines, a semi-supervised learning scheme. When hot spots are defined as those residues for which DeltaDeltaG >or= 2 kcal/mol, our method achieves a precision and a recall respectively of 56% and 65%.

Conclusion: We have developed an hybrid scheme in which energy terms are used as input features of machine learning models. This strategy combines the strengths of machine learning and energy-based methods. Although so far these two types of approaches have mainly been applied separately to biomolecular problems, the results of our investigation indicate that there are substantial benefits to be gained by their integration.
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http://dx.doi.org/10.1186/1471-2105-10-365DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2777894PMC
October 2009

Docking protein domains in contact space.

BMC Bioinformatics 2006 Jun 21;7:310. Epub 2006 Jun 21.

Department of Biochemistry and Molecular Biology, University College London, UK.

Background: Many biological processes involve the physical interaction between protein domains. Understanding these functional associations requires knowledge of the molecular structure. Experimental investigations though present considerable difficulties and there is therefore a need for accurate and reliable computational methods. In this paper we present a novel method that seeks to dock protein domains using a contact map representation. Rather than providing a full three dimensional model of the complex, the method predicts contacting residues across the interface. We use a scoring function that combines structural, physicochemical and evolutionary information, where each potential residue contact is assigned a value according to the scoring function and the hypothesis is that the real configuration of contacts is the one that maximizes the score. The search is performed with a simulated annealing algorithm directly in contact space.

Results: We have tested the method on interacting domain pairs that are part of the same protein (intra-molecular domains). We show that it correctly predicts some contacts and that predicted residues tend to be significantly closer to each other than other pairs of residues in the same domains. Moreover we find that predicted contacts can often discriminate the best model (or the native structure, if present) among a set of optimal solutions generated by a standard docking procedure.

Conclusion: Contact docking appears feasible and able to complement other computational methods for the prediction of protein-protein interactions. With respect to more standard docking algorithms it might be more suitable to handle protein conformational changes and to predict complexes starting from protein models.
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http://dx.doi.org/10.1186/1471-2105-7-310DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1559650PMC
June 2006

The CATH Domain Structure Database and related resources Gene3D and DHS provide comprehensive domain family information for genome analysis.

Nucleic Acids Res 2005 Jan;33(Database issue):D247-51

Biochemistry and Molecular Biology Department, University College London, University of London, Gower Street, London WC1E 6BT, UK.

The CATH database of protein domain structures (http://www.biochem.ucl.ac.uk/bsm/cath/) currently contains 43,229 domains classified into 1467 superfamilies and 5107 sequence families. Each structural family is expanded with sequence relatives from GenBank and completed genomes, using a variety of efficient sequence search protocols and reliable thresholds. This extended CATH protein family database contains 616,470 domain sequences classified into 23,876 sequence families. This results in the significant expansion of the CATH HMM model library to include models built from the CATH sequence relatives, giving a 10% increase in coverage for detecting remote homologues. An improved Dictionary of Homologous superfamilies (DHS) (http://www.biochem.ucl.ac.uk/bsm/dhs/) containing specific sequence, structural and functional information for each superfamily in CATH considerably assists manual validation of homologues. Information on sequence relatives in CATH superfamilies, GenBank and completed genomes is presented in the CATH associated DHS and Gene3D resources. Domain partnership information can be obtained from Gene3D (http://www.biochem.ucl.ac.uk/bsm/cath/Gene3D/). A new CATH server has been implemented (http://www.biochem.ucl.ac.uk/cgi-bin/cath/CathServer.pl) providing automatic classification of newly determined sequences and structures using a suite of rapid sequence and structure comparison methods. The statistical significance of matches is assessed and links are provided to the putative superfamily or fold group to which the query sequence or structure is assigned.
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http://dx.doi.org/10.1093/nar/gki024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC539978PMC
January 2005

Nonconservative earthquake model of self-organized criticality on a random graph.

Phys Rev Lett 2002 Jun 16;88(22):228301. Epub 2002 May 16.

Department of Mathematics, Huxley Building, Imperial College of Science, Technology, and Medicine, London SW7 2BZ, United Kingdom.

We numerically investigate the Olami-Feder-Christensen model on a quenched random graph. Contrary to the case of annealed random neighbors, we find that the quenched model exhibits self-organized criticality deep within the nonconservative regime. The probability distribution for avalanche size obeys finite size scaling, with universal critical exponents. In addition, a power law relation between the size and the duration of an avalanche exists. We propose that this may represent the correct mean-field limit of the model rather than the annealed random neighbor version.
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http://dx.doi.org/10.1103/PhysRevLett.88.228301DOI Listing
June 2002