Publications by authors named "Simon Tavaré"

136 Publications

CamGFR v2: A New Model for Estimating the Glomerular Filtration Rate from Standardized or Non-standardized Creatinine in Patients with Cancer.

Clin Cancer Res 2021 Mar 10;27(5):1381-1390. Epub 2020 Dec 10.

Cold Spring Harbor Laboratory, Cold Spring Harbor, New York.

Purpose: Management of patients with cancer, specifically carboplatin dosing, requires accurate knowledge of glomerular filtration rate (GFR). Direct measurement of GFR is resource limited. Available models for estimated GFR (eGFR) are optimized for patients without cancer and either isotope dilution mass spectrometry (IDMS)- or non-IDMS-standardized creatinine measurements. We present an eGFR model for patients with cancer compatible with both creatinine measurement methods.

Experimental Design: GFR measurements, biometrics, and IDMS- or non-IDMS-standardized creatinine values were collected for adult patients from three cancer centers. Using statistical modeling, an IDMS and non-IDMS creatinine-compatible eGFR model (CamGFR v2) was developed. Its performance was compared with that of the existing models Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), Modification of Diet in Renal Disease (MDRD), Full Age Spectrum (FAS), Lund-Malmö revised, and CamGFR v1, using statistics for bias, precision, accuracy, and clinical robustness.

Results: A total of 3,083 IDMS- and 4,612 non-IDMS-standardized creatinine measurements were obtained from 7,240 patients. IDMS-standardized creatinine values were lower than non-IDMS-standardized values in within-center comparisons (13.8% lower in Cambridge; < 0.0001 and 19.3% lower in Manchester; < 0.0001), and more consistent between centers. CamGFR v2 was the most accurate [root-mean-squared error for IDMS, 14.97 mL/minute (95% confidence interval, 13.84-16.13) and non-IDMS, 15.74 mL/minute (14.86-16.63)], most clinically robust [proportion with >20% error of calculated carboplatin dose for IDMS, 0.12 (0.09-0.14) and non-IDMS, 0.17 (0.15-0.2)], and least biased [median residual for IDMS, 0.73 mL/minute (-0.68 to 2.2) and non-IDMS, -0.43 mL/minute (-1.48 to 0.91)] eGFR model, particularly when eGFR was larger than 60 ml/minute.

Conclusions: CamGFR v2 can utilize IDMS- and non-IDMS-standardized creatinine measurements and outperforms previous models. CamGFR v2 should be examined prospectively as a practice-changing standard of care for eGFR-based carboplatin dosing.
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http://dx.doi.org/10.1158/1078-0432.CCR-20-3201DOI Listing
March 2021

The mutREAD method detects mutational signatures from low quantities of cancer DNA.

Nat Commun 2020 06 23;11(1):3166. Epub 2020 Jun 23.

Medical Research Council Cancer Unit, Hutchison/Medical Research Council Research Centre, University of Cambridge, Cambridge, UK.

Mutational processes acting on cancer genomes can be traced by investigating mutational signatures. Because high sequencing costs limit current studies to small numbers of good-quality samples, we propose a robust, cost- and time-effective method, called mutREAD, to detect mutational signatures from small quantities of DNA, including degraded samples. We show that mutREAD recapitulates mutational signatures identified by whole genome sequencing, and will ultimately allow the study of mutational signatures in larger cohorts and, by compatibility with formalin-fixed paraffin-embedded samples, in clinical settings.
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http://dx.doi.org/10.1038/s41467-020-16974-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7311535PMC
June 2020

Identification of Subtypes of Barrett's Esophagus and Esophageal Adenocarcinoma Based on DNA Methylation Profiles and Integration of Transcriptome and Genome Data.

Gastroenterology 2020 05 4;158(6):1682-1697.e1. Epub 2020 Feb 4.

MRC Cancer Unit, Hutchison/MRC Research Centre, University of Cambridge, Cambridge, United Kingdom. Electronic address:

Background & Aims: Esophageal adenocarcinomas (EACs) are heterogeneous and often preceded by Barrett's esophagus (BE). Many genomic changes have been associated with development of BE and EAC, but little is known about epigenetic alterations. We performed epigenetic analyses of BE and EAC tissues and combined these data with transcriptome and genomic data to identify mechanisms that control gene expression and genome integrity.

Methods: In a retrospective cohort study, we collected tissue samples and clinical data from 150 BE and 285 EAC cases from the Oesophageal Cancer Classification and Molecular Stratification consortium in the United Kingdom. We analyzed methylation profiles of all BE and EAC tissues and assigned them to subgroups using non-negative matrix factorization with k-means clustering. Data from whole-genome sequencing and transcriptome studies were then incorporated; we performed integrative methylation and RNA-sequencing analyses to identify genes that were suppressed with increased methylation in promoter regions. Levels of different immune cell types were computed using single-sample gene set enrichment methods. We derived 8 organoids from 8 EAC tissues and tested their sensitivity to different drugs.

Results: BE and EAC samples shared genome-wide methylation features, compared with normal tissues (esophageal, gastric, and duodenum; controls) from the same patients and grouped into 4 subtypes. Subtype 1 was characterized by DNA hypermethylation with a high mutation burden and multiple mutations in genes in cell cycle and receptor tyrosine signaling pathways. Subtype 2 was characterized by a gene expression pattern associated with metabolic processes (ATP synthesis and fatty acid oxidation) and lack methylation at specific binding sites for transcription factors; 83% of samples of this subtype were BE and 17% were EAC. The third subtype did not have changes in methylation pattern, compared with control tissue, but had a gene expression pattern that indicated immune cell infiltration; this tumor type was associated with the shortest time of patient survival. The fourth subtype was characterized by DNA hypomethylation associated with structure rearrangements, copy number alterations, with preferential amplification of CCNE1 (cells with this gene amplification have been reported to be sensitive to CDK2 inhibitors). Organoids with reduced levels of MGMT and CHFR expression were sensitive to temozolomide and taxane drugs.

Conclusions: In a comprehensive integrated analysis of methylation, transcriptome, and genome profiles of more than 400 BE and EAC tissues, along with clinical data, we identified 4 subtypes that were associated with patient outcomes and potential responses to therapy.
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http://dx.doi.org/10.1053/j.gastro.2020.01.044DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305027PMC
May 2020

Multicenter Validation of the CamGFR Model for Estimated Glomerular Filtration Rate.

JNCI Cancer Spectr 2019 Dec 19;3(4):pkz068. Epub 2019 Sep 19.

See the Notes section for the full list of authors' affiliations.

Important oncological management decisions rely on kidney function assessed by serum creatinine-based estimated glomerular filtration rate (eGFR). However, no large-scale multicenter comparisons of methods to determine eGFR in patients with cancer are available. To compare the performance of formulas for eGFR based on routine clinical parameters and serum creatinine not calibrated with isotope dilution mass spectrometry, we studied 3620 patients with cancer and 166 without cancer who had their glomerular filtration rate (GFR) measured with an exogenous nuclear tracer at one of seven clinical centers. The mean measured GFR was 86 mL/min. Accuracy of all models was center dependent, reflecting intercenter variability of isotope dilution mass spectrometry-creatinine measurements. CamGFR was the most accurate model for eGFR (root-mean-squared error 17.3 mL/min) followed by the Chronic Kidney Disease Epidemiology Collaboration model (root-mean-squared error 18.2 mL/min).
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http://dx.doi.org/10.1093/jncics/pkz068DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6846361PMC
December 2019

Loss of the interleukin-6 receptor causes immunodeficiency, atopy, and abnormal inflammatory responses.

J Exp Med 2019 09 24;216(9):1986-1998. Epub 2019 Jun 24.

Department of Laboratory Medicine, Clinical Center, National Institutes of Health, Bethesda, MD.

IL-6 excess is central to the pathogenesis of multiple inflammatory conditions and is targeted in clinical practice by immunotherapy that blocks the IL-6 receptor encoded by We describe two patients with homozygous mutations in who presented with recurrent infections, abnormal acute-phase responses, elevated IgE, eczema, and eosinophilia. This study identifies a novel primary immunodeficiency, clarifying the contribution of IL-6 to the phenotype of patients with mutations in , and genes encoding different components of the IL-6 signaling pathway, and alerts us to the potential toxicity of drugs targeting the IL-6R.
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http://dx.doi.org/10.1084/jem.20190344DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6719421PMC
September 2019

The landscape of selection in 551 esophageal adenocarcinomas defines genomic biomarkers for the clinic.

Nat Genet 2019 03 4;51(3):506-516. Epub 2019 Feb 4.

MRC cancer unit, Hutchison/MRC research Centre, University of Cambridge, Cambridge, UK.

Esophageal adenocarcinoma (EAC) is a poor-prognosis cancer type with rapidly rising incidence. Understanding of the genetic events driving EAC development is limited, and there are few molecular biomarkers for prognostication or therapeutics. Using a cohort of 551 genomically characterized EACs with matched RNA sequencing data, we discovered 77 EAC driver genes and 21 noncoding driver elements. We identified a mean of 4.4 driver events per tumor, which were derived more commonly from mutations than copy number alterations, and compared the prevelence of these mutations to the exome-wide mutational excess calculated using non-synonymous to synonymous mutation ratios (dN/dS). We observed mutual exclusivity or co-occurrence of events within and between several dysregulated EAC pathways, a result suggestive of strong functional relationships. Indicators of poor prognosis (SMAD4 and GATA4) were verified in independent cohorts with significant predictive value. Over 50% of EACs contained sensitizing events for CDK4 and CDK6 inhibitors, which were highly correlated with clinically relevant sensitivity in a panel of EAC cell lines and organoids.
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http://dx.doi.org/10.1038/s41588-018-0331-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6420087PMC
March 2019

Introduction to the Paul Joyce special issue.

Theor Popul Biol 2018 07;122:1-2

Department of Statistical Science, University of Idaho, 875 Perimeter Drive, MS 1104 Moscow, ID 83844, United States.

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http://dx.doi.org/10.1016/j.tpb.2018.07.001DOI Listing
July 2018

Fixation and Spread of Somatic Mutations in Adult Human Colonic Epithelium.

Cell Stem Cell 2018 Jun 17;22(6):909-918.e8. Epub 2018 May 17.

Cancer Research-UK Cambridge Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. Electronic address:

We investigated the means and timing by which mutations become fixed in the human colonic epithelium by visualizing somatic clones and mathematical inference. Fixation requires two sequential steps. First, one of approximately seven active stem cells residing within each colonic crypt has to be mutated. Second, the mutated stem cell has to replace neighbors to populate the entire crypt in a process that takes several years. Subsequent clonal expansion due to crypt fission is infrequent for neutral mutations (around 0.7% of all crypts undergo fission in a single year). Pro-oncogenic mutations subvert both stem cell replacement to accelerate fixation and clonal expansion by crypt fission to achieve high mutant allele frequencies with age. The benchmarking of these behaviors allows the advantage associated with different gene-specific mutations to be compared irrespective of the cellular mechanisms by which they are conferred.
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http://dx.doi.org/10.1016/j.stem.2018.04.020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5989058PMC
June 2018

Ancestral inference from haplotypes and mutations.

Theor Popul Biol 2018 07 25;122:12-21. Epub 2018 Apr 25.

DAMTP, University of Cambridge, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA, UK.

We consider inference about the history of a sample of DNA sequences, conditional upon the haplotype counts and the number of segregating sites observed at the present time. After deriving some theoretical results in the coalescent setting, we implement rejection sampling and importance sampling schemes to perform the inference. The importance sampling scheme addresses an extension of the Ewens Sampling Formula for a configuration of haplotypes and the number of segregating sites in the sample. The implementations include both constant and variable population size models. The methods are illustrated by two human Y chromosome datasets.
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http://dx.doi.org/10.1016/j.tpb.2018.04.006DOI Listing
July 2018

Sequencing of prostate cancers identifies new cancer genes, routes of progression and drug targets.

Nat Genet 2018 05 16;50(5):682-692. Epub 2018 Apr 16.

The Institute of Cancer Research, London, UK.

Prostate cancer represents a substantial clinical challenge because it is difficult to predict outcome and advanced disease is often fatal. We sequenced the whole genomes of 112 primary and metastatic prostate cancer samples. From joint analysis of these cancers with those from previous studies (930 cancers in total), we found evidence for 22 previously unidentified putative driver genes harboring coding mutations, as well as evidence for NEAT1 and FOXA1 acting as drivers through noncoding mutations. Through the temporal dissection of aberrations, we identified driver mutations specifically associated with steps in the progression of prostate cancer, establishing, for example, loss of CHD1 and BRCA2 as early events in cancer development of ETS fusion-negative cancers. Computational chemogenomic (canSAR) analysis of prostate cancer mutations identified 11 targets of approved drugs, 7 targets of investigational drugs, and 62 targets of compounds that may be active and should be considered candidates for future clinical trials.
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http://dx.doi.org/10.1038/s41588-018-0086-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372064PMC
May 2018

Division-independent differentiation mandates proliferative competition among stem cells.

Proc Natl Acad Sci U S A 2018 04 19;115(14):E3182-E3191. Epub 2018 Mar 19.

Department of Biological Sciences, Columbia University, New York, NY 10027;

Cancer-initiating gatekeeper mutations that arise in stem cells would be especially potent if they stabilize and expand an affected stem cell lineage. It is therefore important to understand how different stem cell organization strategies promote or prevent variant stem cell amplification in response to different types of mutation, including those that activate proliferation. Stem cell numbers can be maintained constant while producing differentiated products through individually asymmetrical division outcomes or by population asymmetry strategies in which individual stem cell lineages necessarily compete for niche space. We considered alternative mechanisms underlying population asymmetry and used quantitative modeling to predict starkly different consequences of altering proliferation rate: A variant, faster proliferating mutant stem cell should compete better only when stem cell division and differentiation are independent processes. For most types of stem cells, it has not been possible to ascertain experimentally whether division and differentiation are coupled. However, follicle stem cells (FSCs) provided a favorable system with which to investigate population asymmetry mechanisms and also for measuring the impact of altered proliferation on competition. We found from detailed cell lineage studies that division and differentiation of an individual FSC are not coupled. We also found that FSC representation, reflecting maintenance and amplification, was highly responsive to genetic changes that altered only the rate of FSC proliferation. The FSC paradigm therefore provides definitive experimental evidence for the general principle that relative proliferation rate will always be a major determinant of competition among stem cells specifically when stem cell division and differentiation are independent.
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http://dx.doi.org/10.1073/pnas.1718646115DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5889645PMC
April 2018

Simulating the component counts of combinatorial structures.

Theor Popul Biol 2018 07 9;122:5-11. Epub 2018 Feb 9.

DAMTP, University of Cambridge, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA, UK. Electronic address:

This article describes and compares methods for simulating the component counts of random logarithmic combinatorial structures such as permutations and mappings. We exploit the Feller coupling for simulating permutations to provide a very fast method for simulating logarithmic assemblies more generally. For logarithmic multisets and selections, this approach is replaced by an acceptance/rejection method based on a particular conditioning relationship that represents the distribution of the combinatorial structure as that of independent random variables conditioned on a weighted sum. We show how to improve its acceptance rate. We illustrate the method by estimating the probability that a random mapping has no repeated component sizes, and establish the asymptotic distribution of the difference between the number of components and the number of distinct component sizes for a very general class of logarithmic structures.
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http://dx.doi.org/10.1016/j.tpb.2018.02.002DOI Listing
July 2018

Synthetic lethality between androgen receptor signalling and the PARP pathway in prostate cancer.

Nat Commun 2017 08 29;8(1):374. Epub 2017 Aug 29.

Science for Life Laboratory, Division of Translational Medicine and Chemical Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, S-171 21, Stockholm, Sweden.

Emerging data demonstrate homologous recombination (HR) defects in castration-resistant prostate cancers, rendering these tumours sensitive to PARP inhibition. Here we demonstrate a direct requirement for the androgen receptor (AR) to maintain HR gene expression and HR activity in prostate cancer. We show that PARP-mediated repair pathways are upregulated in prostate cancer following androgen-deprivation therapy (ADT). Furthermore, upregulation of PARP activity is essential for the survival of prostate cancer cells and we demonstrate a synthetic lethality between ADT and PARP inhibition in vivo. Our data suggest that ADT can functionally impair HR prior to the development of castration resistance and that, this potentially could be exploited therapeutically using PARP inhibitors in combination with androgen-deprivation therapy upfront in advanced or high-risk prostate cancer.Tumours with homologous recombination (HR) defects become sensitive to PARPi. Here, the authors show that androgen receptor (AR) regulates HR and AR inhibition activates the PARP pathway in vivo, thus inhibition of both AR and PARP is required for effective treatment of high risk prostate cancer.
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http://dx.doi.org/10.1038/s41467-017-00393-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5575038PMC
August 2017

New Model for Estimating Glomerular Filtration Rate in Patients With Cancer.

J Clin Oncol 2017 Aug 7;35(24):2798-2805. Epub 2017 Jul 7.

Tobias Janowitz, Edward H. Williams, Stephen J. Sammut, Andy G. Lynch, Duncan I. Jodrell, Simon Tavaré, and Helena Earl, Cancer Research UK Cambridge Institute, Tobias Janowitz, Peter B. Thomas, and Duncan I. Jodrell, University of Cambridge, Addenbrooke's Hospital, Cambridge; Andrea Marshall, University of Warwick, Coventry; Nicola Ainsworth, Queen Elizabeth Hospital, King's Lynn; Scott Shepherd, Royal Marsden Hospital, London; Jeff White, NHS Greater Glasgow and Clyde; and Patrick B. Mark, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom.

Purpose The glomerular filtration rate (GFR) is essential for carboplatin chemotherapy dosing; however, the best method to estimate GFR in patients with cancer is unknown. We identify the most accurate and least biased method. Methods We obtained data on age, sex, height, weight, serum creatinine concentrations, and results for GFR from chromium-51 (Cr) EDTA excretion measurements (Cr-EDTA GFR) from white patients ≥ 18 years of age with histologically confirmed cancer diagnoses at the Cambridge University Hospital NHS Trust, United Kingdom. We developed a new multivariable linear model for GFR using statistical regression analysis. Cr-EDTA GFR was compared with the estimated GFR (eGFR) from seven published models and our new model, using the statistics root-mean-squared-error (RMSE) and median residual and on an internal and external validation data set. We performed a comparison of carboplatin dosing accuracy on the basis of an absolute percentage error > 20%. Results Between August 2006 and January 2013, data from 2,471 patients were obtained. The new model improved the eGFR accuracy (RMSE, 15.00 mL/min; 95% CI, 14.12 to 16.00 mL/min) compared with all published models. Body surface area (BSA)-adjusted chronic kidney disease epidemiology (CKD-EPI) was the most accurate published model for eGFR (RMSE, 16.30 mL/min; 95% CI, 15.34 to 17.38 mL/min) for the internal validation set. Importantly, the new model reduced the fraction of patients with a carboplatin dose absolute percentage error > 20% to 14.17% in contrast to 18.62% for the BSA-adjusted CKD-EPI and 25.51% for the Cockcroft-Gault formula. The results were externally validated. Conclusion In a large data set from patients with cancer, BSA-adjusted CKD-EPI is the most accurate published model to predict GFR. The new model improves this estimation and may present a new standard of care.
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http://dx.doi.org/10.1200/JCO.2017.72.7578DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5562175PMC
August 2017

A comparative analysis of whole genome sequencing of esophageal adenocarcinoma pre- and post-chemotherapy.

Genome Res 2017 06 2;27(6):902-912. Epub 2017 May 2.

Medical Research Council Cancer Unit, Hutchison/Medical Research Council Research Centre, University of Cambridge, Cambridge CB2 0XZ, United Kingdom.

The scientific community has avoided using tissue samples from patients that have been exposed to systemic chemotherapy to infer the genomic landscape of a given cancer. Esophageal adenocarcinoma is a heterogeneous, chemoresistant tumor for which the availability and size of pretreatment endoscopic samples are limiting. This study compares whole-genome sequencing data obtained from chemo-naive and chemo-treated samples. The quality of whole-genomic sequencing data is comparable across all samples regardless of chemotherapy status. Inclusion of samples collected post-chemotherapy increased the proportion of late-stage tumors. When comparing matched pre- and post-chemotherapy samples from 10 cases, the mutational signatures, copy number, and SNV mutational profiles reflect the expected heterogeneity in this disease. Analysis of SNVs in relation to allele-specific copy-number changes pinpoints the common ancestor to a point prior to chemotherapy. For cases in which pre- and post-chemotherapy samples do show substantial differences, the timing of the divergence is near-synchronous with endoreduplication. Comparison across a large prospective cohort (62 treatment-naive, 58 chemotherapy-treated samples) reveals no significant differences in the overall mutation rate, mutation signatures, specific recurrent point mutations, or copy-number events in respect to chemotherapy status. In conclusion, whole-genome sequencing of samples obtained following neoadjuvant chemotherapy is representative of the genomic landscape of esophageal adenocarcinoma. Excluding these samples reduces the material available for cataloging and introduces a bias toward the earlier stages of cancer.
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http://dx.doi.org/10.1101/gr.214296.116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5453324PMC
June 2017

Mutational signatures in esophageal adenocarcinoma define etiologically distinct subgroups with therapeutic relevance.

Nat Genet 2016 10 5;48(10):1131-41. Epub 2016 Sep 5.

Medical Research Council Cancer Unit, Hutchison/Medical Research Council Research Centre, University of Cambridge, Cambridge, UK.

Esophageal adenocarcinoma (EAC) has a poor outcome, and targeted therapy trials have thus far been disappointing owing to a lack of robust stratification methods. Whole-genome sequencing (WGS) analysis of 129 cases demonstrated that this is a heterogeneous cancer dominated by copy number alterations with frequent large-scale rearrangements. Co-amplification of receptor tyrosine kinases (RTKs) and/or downstream mitogenic activation is almost ubiquitous; thus tailored combination RTK inhibitor (RTKi) therapy might be required, as we demonstrate in vitro. However, mutational signatures showed three distinct molecular subtypes with potential therapeutic relevance, which we verified in an independent cohort (n = 87): (i) enrichment for BRCA signature with prevalent defects in the homologous recombination pathway; (ii) dominant T>G mutational pattern associated with a high mutational load and neoantigen burden; and (iii) C>A/T mutational pattern with evidence of an aging imprint. These subtypes could be ascertained using a clinically applicable sequencing strategy (low coverage) as a basis for therapy selection.
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http://dx.doi.org/10.1038/ng.3659DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5957269PMC
October 2016

HDTD: analyzing multi-tissue gene expression data.

Bioinformatics 2016 07 7;32(14):2193-5. Epub 2016 Jun 7.

CRUK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.

Motivation: By collecting multiple samples per subject, researchers can characterize intra-subject variation using physiologically relevant measurements such as gene expression profiling. This can yield important insights into fundamental biological questions ranging from cell type identity to tumour development. For each subject, the data measurements can be written as a matrix with the different subsamples (e.g. multiple tissues) indexing the columns and the genes indexing the rows. In this context, neither the genes nor the tissues are expected to be independent and straightforward application of traditional statistical methods that ignore this two-way dependence might lead to erroneous conclusions. Herein, we present a suite of tools embedded within the R/Bioconductor package HDTD for robustly estimating and performing hypothesis tests about the mean relationship and the covariance structure within the rows and columns. We illustrate the utility of HDTD by applying it to analyze data generated by the Genotype-Tissue Expression consortium.

Availability And Implementation: The R package HDTD is part of Bioconductor. The source code and a comprehensive user's guide are available at http://bioconductor.org/packages/release/bioc/html/HDTD.html

Contact: : A.Touloumis@brighton.ac.uk

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btw224DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937203PMC
July 2016

Choline Kinase Alpha as an Androgen Receptor Chaperone and Prostate Cancer Therapeutic Target.

J Natl Cancer Inst 2016 May 11;108(5). Epub 2015 Dec 11.

Affiliations of authors:Cancer Research UK Cambridge Institute, University of Cambridge , Cambridge, UK (MA, CEM, NP, HIZ, AQ, AB, SM, BM, CE, SL, SW, VRZ, GS, RR, HM, AGL, CD, CT, AL, RS, JY, RS, JSC, JRG, ST, DEN); School of Medical Sciences, University of Aberdeen , Aberdeen, UK (FO, IJM); Department of Pathology, Addenbrooke's Hospital , Cambridge, UK (AYW, NS); Institute of Human Genetics, Jena University Hospital , Jena , Germany (ME, KL, WH, AB); Dame Roma Mitchell Cancer Research Laboratories, School of Medicine, Faculty of Health Sciences, University of Adelaide , Australia (LAS, WDT); Freemasons Foundation Centre for Men's Health, School of Medicine, Faculty of Health Sciences, University of Adelaide , Australia (LAS, WDT); Diatherix , Huntsville, AL (EG); Masonic Cancer Center, University of Minnesota , Minneapolis, MN (SMD); The Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia , Vancouver BC , Canada (PSR); Centre for Molecular Medicine Norway, Nordic EMBL Partnership, University of Oslo and Oslo University Hospital , Oslo , Norway (IGM); Department of Cancer Prevention, Institute of Cancer Research and Department of Urology, Oslo University Hospital , Oslo , Norway (IGM); Prostate Cancer UK/Movember Centre of Excellence, Queens University , Belfast , UK (IGM); Department of Oncology, Addenbrooke's Hospital , Cambridge, UK (MA, DEN).

Background: The androgen receptor (AR) is a major drug target in prostate cancer (PCa). We profiled the AR-regulated kinome to identify clinically relevant and druggable effectors of AR signaling.

Methods: Using genome-wide approaches, we interrogated all AR regulated kinases. Among these, choline kinase alpha (CHKA) expression was evaluated in benign (n = 195), prostatic intraepithelial neoplasia (PIN) (n = 153) and prostate cancer (PCa) lesions (n = 359). We interrogated how CHKA regulates AR signaling using biochemical assays and investigated androgen regulation of CHKA expression in men with PCa, both untreated (n = 20) and treated with an androgen biosynthesis inhibitor degarelix (n = 27). We studied the effect of CHKA inhibition on the PCa transcriptome using RNA sequencing and tested the effect of CHKA inhibition on cell growth, clonogenic survival and invasion. Tumor xenografts (n = 6 per group) were generated in mice using genetically engineered prostate cancer cells with inducible CHKA knockdown. Data were analyzed with χ(2) tests, Cox regression analysis, and Kaplan-Meier methods. All statistical tests were two-sided.

Results: CHKA expression was shown to be androgen regulated in cell lines, xenografts, and human tissue (log fold change from 6.75 to 6.59, P = .002) and was positively associated with tumor stage. CHKA binds directly to the ligand-binding domain (LBD) of AR, enhancing its stability. As such, CHKA is the first kinase identified as an AR chaperone. Inhibition of CHKA repressed the AR transcriptional program including pathways enriched for regulation of protein folding, decreased AR protein levels, and inhibited the growth of PCa cell lines, human PCa explants, and tumor xenografts.

Conclusions: CHKA can act as an AR chaperone, providing, to our knowledge, the first evidence for kinases as molecular chaperones, making CHKA both a marker of tumor progression and a potential therapeutic target for PCa.
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http://dx.doi.org/10.1093/jnci/djv371DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4849803PMC
May 2016

Metabolomic changes during cellular transformation monitored by metabolite-metabolite correlation analysis and correlated with gene expression.

Metabolomics 2015;11(6):1848-1863. Epub 2015 Aug 11.

Li Ka Shing Centre, Cancer Research UK Cambridge Institute, University of Cambridge, Robinson Way, Cambridge, CB2 0RE UK.

To investigate metabolic changes during cellular transformation, we used a H NMR based metabolite-metabolite correlation analysis (MMCA) method, which permits analysis of homeostatic mechanisms in cells at the steady state, in an inducible cell transformation model. Transcriptomic data were used to further explain the results. Transformed cells showed many more metabolite-metabolite correlations than control cells. Some had intuitively plausible explanations: a shift from glycolysis to amino acid oxidation after transformation was accompanied by a strongly positive correlation between glucose and glutamine and a strongly negative one between lactate and glutamate; there were also many correlations between the branched chain amino acids and the aromatic amino acids. Others remain puzzling: after transformation strong positive correlations developed between choline and a group of five amino acids, whereas the same amino acids showed correlations with phosphocholine, a membrane phospholipid precursor. MMCA in conjunction with transcriptome analysis has opened a new window into the metabolome.
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http://dx.doi.org/10.1007/s11306-015-0838-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4605990PMC
August 2015

Mobile element insertions are frequent in oesophageal adenocarcinomas and can mislead paired-end sequencing analysis.

BMC Genomics 2015 Jul 10;16:473. Epub 2015 Jul 10.

Department of Pathology, University of Cambridge, Hutchison-MRC Research Centre, Cambridge, UK.

Background: Mobile elements are active in the human genome, both in the germline and cancers, where they can mutate driver genes.

Results: While analysing whole genome paired-end sequencing of oesophageal adenocarcinomas to find genomic rearrangements, we identified three ways in which new mobile element insertions appear in the data, resembling translocation or insertion junctions: inserts where unique sequence has been transduced by an L1 (Long interspersed element 1) mobile element; novel inserts that are confidently, but often incorrectly, mapped by alignment software to L1s or polyA tracts in the reference sequence; and a combination of these two ways, where different sequences within one insert are mapped to different loci. We identified nine unique sequences that were transduced by neighbouring L1s, both L1s in the reference genome and L1s not present in the reference. Many of the resulting inserts were small fragments that include little or no recognisable mobile element sequence. We found 6 loci in the reference genome to which sequence reads from inserts were frequently mapped, probably erroneously, by alignment software: these were either L1 sequence or particularly long polyA runs. Inserts identified from such apparent rearrangement junctions averaged 16 inserts/tumour, range 0-153 insertions in 43 tumours. However, many inserts would not be detected by mapping the sequences to the reference genome, because they do not include sufficient mappable sequence. To estimate total somatic inserts we searched for polyA sequences that were not present in the matched normal or other normals from the same tumour batch, and were not associated with known polymorphisms. Samples of these candidate inserts were verified by sequencing across them or manual inspection of surrounding reads: at least 85 % were somatic and resembled L1-mediated events, most including L1Hs sequence. Approximately 100 such inserts were detected per tumour on average (range zero to approximately 700).

Conclusions: Somatic mobile elements insertions are abundant in these tumours, with over 75 % of cases having a number of novel inserts detected. The inserts create a variety of problems for the interpretation of paired-end sequencing data.
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http://dx.doi.org/10.1186/s12864-015-1685-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4498532PMC
July 2015

Phenotype specific analyses reveal distinct regulatory mechanism for chronically activated p53.

PLoS Genet 2015 Mar 19;11(3):e1005053. Epub 2015 Mar 19.

Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, United Kingdom.

The downstream functions of the DNA binding tumor suppressor p53 vary depending on the cellular context, and persistent p53 activation has recently been implicated in tumor suppression and senescence. However, genome-wide information about p53-target gene regulation has been derived mostly from acute genotoxic conditions. Using ChIP-seq and expression data, we have found distinct p53 binding profiles between acutely activated (through DNA damage) and chronically activated (in senescent or pro-apoptotic conditions) p53. Compared to the classical 'acute' p53 binding profile, 'chronic' p53 peaks were closely associated with CpG-islands. Furthermore, the chronic CpG-island binding of p53 conferred distinct expression patterns between senescent and pro-apoptotic conditions. Using the p53 targets seen in the chronic conditions together with external high-throughput datasets, we have built p53 networks that revealed extensive self-regulatory 'p53 hubs' where p53 and many p53 targets can physically interact with each other. Integrating these results with public clinical datasets identified the cancer-associated lipogenic enzyme, SCD, which we found to be directly repressed by p53 through the CpG-island promoter, providing a mechanistic link between p53 and the 'lipogenic phenotype', a hallmark of cancer. Our data reveal distinct phenotype associations of chronic p53 targets that underlie specific gene regulatory mechanisms.
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http://dx.doi.org/10.1371/journal.pgen.1005053DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4366240PMC
March 2015

multiSNV: a probabilistic approach for improving detection of somatic point mutations from multiple related tumour samples.

Nucleic Acids Res 2015 May 26;43(9):e61. Epub 2015 Feb 26.

Cancer Research UK Cambridge Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK

Somatic variant analysis of a tumour sample and its matched normal has been widely used in cancer research to distinguish germline polymorphisms from somatic mutations. However, due to the extensive intratumour heterogeneity of cancer, sequencing data from a single tumour sample may greatly underestimate the overall mutational landscape. In recent studies, multiple spatially or temporally separated tumour samples from the same patient were sequenced to identify the regional distribution of somatic mutations and study intratumour heterogeneity. There are a number of tools to perform somatic variant calling from matched tumour-normal next-generation sequencing (NGS) data; however none of these allow joint analysis of multiple same-patient samples. We discuss the benefits and challenges of multisample somatic variant calling and present multiSNV, a software package for calling single nucleotide variants (SNVs) using NGS data from multiple same-patient samples. Instead of performing multiple pairwise analyses of a single tumour sample and a matched normal, multiSNV jointly considers all available samples under a Bayesian framework to increase sensitivity of calling shared SNVs. By leveraging information from all available samples, multiSNV is able to detect rare mutations with variant allele frequencies down to 3% from whole-exome sequencing experiments.
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http://dx.doi.org/10.1093/nar/gkv135DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4482059PMC
May 2015

Genetic mapping of natural variation in schooling tendency in the threespine stickleback.

G3 (Bethesda) 2015 Feb 25;5(5):761-9. Epub 2015 Feb 25.

Divisions of Basic Sciences and Human Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109

Although there is a heritable basis for many animal behaviors, the genetic architecture of behavioral variation in natural populations remains mostly unknown, particularly in vertebrates. We sought to identify the genetic basis for social affiliation in two populations of threespine sticklebacks (Gasterosteus aculeatus) that differ in their propensity to school. Marine sticklebacks from Japan school strongly whereas benthic sticklebacks from a lake in Canada are more solitary. Here, we expanded on our previous efforts to identify quantitative trait loci (QTL) for differences in schooling tendency. We tested fish multiple times in two assays that test different aspects of schooling tendency: 1) the model school assay, which presents fish with a school of eight model sticklebacks; and 2) the choice assay, in which fish are given a choice between the model school and a stationary artificial plant. We found low-to-moderate levels of repeatability, ranging from 0.1 to 0.5, in schooling phenotypes. To identify the genomic regions that contribute to differences in schooling tendency, we used QTL mapping in two types of crosses: benthic × marine backcrosses and an F2 intercross. We found two QTL for time spent with the school in the model school assay, and one QTL for number of approaches to the school in the choice assay. These QTL were on three different linkage groups, not previously linked to behavioral differences in sticklebacks. Our results highlight the importance of using multiple crosses and robust behavioral assays to uncover the genetic basis of behavioral variation in natural populations.
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http://dx.doi.org/10.1534/g3.114.016519DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4426364PMC
February 2015

Testing the mean matrix in high-dimensional transposable data.

Biometrics 2015 Mar 23;71(1):157-166. Epub 2015 Jan 23.

EMBL-European Bioinformatics Institute, Hinxton CB10 1SD, U.K.

The structural information in high-dimensional transposable data allows us to write the data recorded for each subject in a matrix such that both the rows and the columns correspond to variables of interest. One important problem is to test the null hypothesis that the mean matrix has a particular structure without ignoring the dependence structure among and/or between the row and column variables. To address this, we develop a generic and computationally inexpensive nonparametric testing procedure to assess the hypothesis that, in each predefined subset of columns (rows), the column (row) mean vector remains constant. In simulation studies, the proposed testing procedure seems to have good performance and, unlike simple practical approaches, it preserves the nominal size and remains powerful even if the row and/or column variables are not independent. Finally, we illustrate the use of the proposed methodology via two empirical examples from gene expression microarrays.
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http://dx.doi.org/10.1111/biom.12257DOI Listing
March 2015

Epigenetic profile of human adventitial progenitor cells correlates with therapeutic outcomes in a mouse model of limb ischemia.

Arterioscler Thromb Vasc Biol 2015 Mar 8;35(3):675-88. Epub 2015 Jan 8.

From the Bristol Heart Institute, School of Clinical Sciences, University of Bristol, Bristol, UK (M.G., S.C.S., H.L.S., F.R., J.R., E.A., R.K., G.M., A.O., C.R., C.E., G.A., P.M.); The Institute of Cancer Research, Evolutionary Genomics and Modelling Team, Centre for Evolution and Cancer, Sutton, UK (I.S., A.S.); Imperial College, London, UK (P.C., C.E., G.A.); MultiMedica Research Institute, Milan, Italy (G.S.); Cancer Research UK Cambridge Institute, Cambridge, UK (A.T., S.T.); Centro Cardiologico Monzino, Milan, Italy (F.P., M.P.); and Austrian Institute of Technology, Vienna, Austria (M.H., V.K.).

Objective: We investigated the association between the functional, epigenetic, and expressional profile of human adventitial progenitor cells (APCs) and therapeutic activity in a model of limb ischemia.

Approach And Results: Antigenic and functional features were analyzed throughout passaging in 15 saphenous vein (SV)-derived APC lines, of which 10 from SV leftovers of coronary artery bypass graft surgery and 5 from varicose SV removal. Moreover, 5 SV-APC lines were transplanted (8×10(5) cells, IM) in mice with limb ischemia. Blood flow and capillary and arteriole density were correlated with functional characteristics and DNA methylation/expressional markers of transplanted cells. We report successful expansion of tested lines, which reached the therapeutic target of 30 to 50 million cells in ≈10 weeks. Typical antigenic profile, viability, and migratory and proangiogenic activities were conserved through passaging, with low levels of replicative senescence. In vivo, SV-APC transplantation improved blood flow recovery and revascularization of ischemic limbs. Whole genome screening showed an association between DNA methylation at the promoter or gene body level and microvascular density and to a lesser extent with blood flow recovery. Expressional studies highlighted the implication of an angiogenic network centered on the vascular endothelial growth factor receptor as a predictor of microvascular outcomes. FLT-1 gene silencing in SV-APCs remarkably reduced their ability to form tubes in vitro and support tube formation by human umbilical vein endothelial cells, thus confirming the importance of this signaling in SV-APC angiogenic function.

Conclusions: DNA methylation landscape illustrates different therapeutic activities of human APCs. Epigenetic screening may help identify determinants of therapeutic vasculogenesis in ischemic disease.
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http://dx.doi.org/10.1161/ATVBAHA.114.304989DOI Listing
March 2015

HES5 silencing is an early and recurrent change in prostate tumourigenesis.

Endocr Relat Cancer 2015 Apr 5;22(2):131-44. Epub 2015 Jan 5.

Cancer Research UK Cambridge InstituteUniversity of Cambridge, Cambridge, CB2 0RE, UKDivision of Genetics and EpidemiologyThe Institute of Cancer Research, Sutton, UKDepartment of Biological Sciences and School of MedicineUniversity of East Anglia, Norwich, UKRoyal Marsden NHS Foundation TrustLondon and Sutton, UKDepartments of PathologyUrologySurgical OncologyAddenbrooke's Hospital, Hills Road, Cambridge, UK

Prostate cancer is the most common cancer in men, resulting in over 10 000 deaths/year in the UK. Sequencing and copy number analysis of primary tumours has revealed heterogeneity within tumours and an absence of recurrent founder mutations, consistent with non-genetic disease initiating events. Using methylation profiling in a series of multi-focal prostate tumours, we identify promoter methylation of the transcription factor HES5 as an early event in prostate tumourigenesis. We confirm that this epigenetic alteration occurs in 86-97% of cases in two independent prostate cancer cohorts (n=49 and n=39 tumour-normal pairs). Treatment of prostate cancer cells with the demethylating agent 5-aza-2'-deoxycytidine increased HES5 expression and downregulated its transcriptional target HES6, consistent with functional silencing of the HES5 gene in prostate cancer. Finally, we identify and test a transcriptional module involving the AR, ERG, HES1 and HES6 and propose a model for the impact of HES5 silencing on tumourigenesis as a starting point for future functional studies.
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http://dx.doi.org/10.1530/ERC-14-0454DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4335379PMC
April 2015

Quantifying the impact of inter-site heterogeneity on the distribution of ChIP-seq data.

Front Genet 2014 14;5:399. Epub 2014 Nov 14.

Cancer Research UK Cambridge Institute, University of Cambridge Cambridge, UK.

Chromatin Immunoprecipitation followed by sequencing (ChIP-seq) is a valuable tool for epigenetic studies. Analysis of the data arising from ChIP-seq experiments often requires implicit or explicit statistical modeling of the read counts. The simple Poisson model is attractive, but does not provide a good fit to observed ChIP-seq data. Researchers therefore often either extend to a more general model (e.g., the Negative Binomial), and/or exclude regions of the genome that do not conform to the model. Since many modeling strategies employed for ChIP-seq data reduce to fitting a mixture of Poisson distributions, we explore the problem of inferring the optimal mixing distribution. We apply the Constrained Newton Method (CNM), which suggests the Negative Binomial - Negative Binomial (NB-NB) mixture model as a candidate for modeling ChIP-seq data. We illustrate fitting the NB-NB model with an accelerated EM algorithm on four data sets from three species. Zero-inflated models have been suggested as an approach to improve model fit for ChIP-seq data. We show that the NB-NB mixture model requires no zero-inflation and suggest that in some cases the need for zero inflation is driven by the model's inability to cope with both artifactual large read counts and the frequently observed very low read counts. We see that the CNM-based approach is a useful diagnostic for the assessment of model fit and inference in ChIP-seq data and beyond. Use of the suggested NB-NB mixture model will be of value not only when calling peaks or otherwise modeling ChIP-seq data, but also when simulating data or constructing blacklists de novo.
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http://dx.doi.org/10.3389/fgene.2014.00399DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4231950PMC
December 2014