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author:("henriot, Marc")
1.  Common Variation at 1q24.1 (ALDH9A1) Is a Potential Risk Factor for Renal Cancer 
PLoS ONE  2015;10(3):e0122589.
So far six susceptibility loci for renal cell carcinoma (RCC) have been discovered by genome-wide association studies (GWAS). To identify additional RCC common risk loci, we performed a meta-analysis of published GWAS (totalling 2,215 cases and 8,566 controls of Western-European background) with imputation using 1000 Genomes Project and UK10K Project data as reference panels and followed up the most significant association signals [22 single nucleotide polymorphisms (SNPs) and 3 indels in eight genomic regions] in 383 cases and 2,189 controls from The Cancer Genome Atlas (TCGA). A combined analysis identified a promising susceptibility locus mapping to 1q24.1 marked by the imputed SNP rs3845536 (Pcombined =2.30x10-8). Specifically, the signal maps to intron 4 of the ALDH9A1 gene (aldehyde dehydrogenase 9 family, member A1). We further evaluated this potential signal in 2,461 cases and 5,081 controls from the International Agency for Research on Cancer (IARC) GWAS of RCC cases and controls from multiple European regions. In contrast to earlier findings no association was shown in the IARC series (P=0.94; Pcombined =2.73x10-5). While variation at 1q24.1 represents a potential risk locus for RCC, future replication analyses are required to substantiate our observation.
doi:10.1371/journal.pone.0122589
PMCID: PMC4380462  PMID: 25826619
2.  Capture Hi-C identifies the chromatin interactome of colorectal cancer risk loci 
Nature Communications  2015;6:6178.
Multiple regulatory elements distant from their targets on the linear genome can influence the expression of a single gene through chromatin looping. Chromosome conformation capture implemented in Hi-C allows for genome-wide agnostic characterization of chromatin contacts. However, detection of functional enhancer–promoter interactions is precluded by its effective resolution that is determined by both restriction fragmentation and sensitivity of the experiment. Here we develop a capture Hi-C (cHi-C) approach to allow an agnostic characterization of these physical interactions on a genome-wide scale. Single-nucleotide polymorphisms associated with complex diseases often reside within regulatory elements and exert effects through long-range regulation of gene expression. Applying this cHi-C approach to 14 colorectal cancer risk loci allows us to identify key long-range chromatin interactions in cis and trans involving these loci.
Multiple regulatory elements distant from their targets on the linear genome can influence gene expression through chromatin looping. Here, the authors report an improved chromosome conformation capture approach that can be used to identify long-range chromatin interactions in cancer risk loci.
doi:10.1038/ncomms7178
PMCID: PMC4346635  PMID: 25695508
3.  Rare variants of large effect in BRCA2 and CHEK2 affect risk of lung cancer 
Wang, Yufei | McKay, James D. | Rafnar, Thorunn | Wang, Zhaoming | Timofeeva, Maria | Broderick, Peter | Zong, Xuchen | Laplana, Marina | Wei, Yongyue | Han, Younghun | Lloyd, Amy | Delahaye-Sourdeix, Manon | Chubb, Daniel | Gaborieau, Valerie | Wheeler, William | Chatterjee, Nilanjan | Thorleifsson, Gudmar | Sulem, Patrick | Liu, Geoffrey | Kaaks, Rudolf | Henrion, Marc | Kinnersley, Ben | Vallée, Maxime | LeCalvez-Kelm, Florence | Stevens, Victoria L. | Gapstur, Susan M. | Chen, Wei V. | Zaridze, David | Szeszenia-Dabrowska, Neonilia | Lissowska, Jolanta | Rudnai, Peter | Fabianova, Eleonora | Mates, Dana | Bencko, Vladimir | Foretova, Lenka | Janout, Vladimir | Krokan, Hans E. | Gabrielsen, Maiken Elvestad | Skorpen, Frank | Vatten, Lars | Njølstad, Inger | Chen, Chu | Goodman, Gary | Benhamou, Simone | Vooder, Tonu | Valk, Kristjan | Nelis, Mari | Metspalu, Andres | Lener, Marcin | Lubiński, Jan | Johansson, Mattias | Vineis, Paolo | Agudo, Antonio | Clavel-Chapelon, Francoise | Bueno-de-Mesquita, H.Bas | Trichopoulos, Dimitrios | Khaw, Kay-Tee | Johansson, Mikael | Weiderpass, Elisabete | Tjønneland, Anne | Riboli, Elio | Lathrop, Mark | Scelo, Ghislaine | Albanes, Demetrius | Caporaso, Neil E. | Ye, Yuanqing | Gu, Jian | Wu, Xifeng | Spitz, Margaret R. | Dienemann, Hendrik | Rosenberger, Albert | Su, Li | Matakidou, Athena | Eisen, Timothy | Stefansson, Kari | Risch, Angela | Chanock, Stephen J. | Christiani, David C. | Hung, Rayjean J. | Brennan, Paul | Landi, Maria Teresa | Houlston, Richard S. | Amos, Christopher I.
Nature genetics  2014;46(7):736-741.
We conducted imputation to the 1000 Genomes Project of four genome-wide association studies of lung cancer in populations of European ancestry (11,348 cases and 15,861 controls) and genotyped an additional 10,246 cases and 38,295 controls for follow-up. We identified large-effect genome-wide associations for squamous lung cancer with the rare variants of BRCA2-K3326X (rs11571833; odds ratio [OR]=2.47, P=4.74×10−20) and of CHEK2-I157T (rs17879961; OR=0.38 P=1.27×10−13). We also showed an association between common variation at 3q28 (TP63; rs13314271; OR=1.13, P=7.22×10−10) and lung adenocarcinoma previously only reported in Asians. These findings provide further evidence for inherited genetic susceptibility to lung cancer and its biological basis. Additionally, our analysis demonstrates that imputation can identify rare disease-causing variants having substantive effects on cancer risk from pre-existing GWAS data.
doi:10.1038/ng.3002
PMCID: PMC4074058  PMID: 24880342
4.  visPIG - A Web Tool for Producing Multi-Region, Multi-Track, Multi-Scale Plots of Genetic Data 
PLoS ONE  2014;9(9):e107497.
We present VISual Plotting Interface for Genetics (visPIG; http://vispig.icr.ac.uk), a web application to produce multi-track, multi-scale, multi-region plots of genetic data. visPIG has been designed to allow users not well versed with mathematical software packages and/or programming languages such as R [1], Matlab®, Python, etc., to integrate data from multiple sources for interpretation and to easily create publication-ready figures. While web tools such as the UCSC Genome Browser [2] or the WashU Epigenome Browser [3] allow custom data uploads, such tools are primarily designed for data exploration. This is also true for the desktop-run Integrative Genomics Viewer (IGV) [4],[5]. Other locally run data visualisation software such as Circos [6] require significant computer skills of the user. The visPIG web application is a menu-based interface that allows users to upload custom data tracks and set track-specific parameters. Figures can be downloaded as PDF or PNG files. For sensitive data, the underlying R [1] code can also be downloaded and run locally. visPIG is multi-track: it can display many different data types (e.g association, functional annotation, intensity, interaction, heat map data,…). It also allows annotation of genes and other custom features in the plotted region(s). Data tracks can be plotted individually or on a single figure. visPIG is multi-region: it supports plotting multiple regions, be they kilo- or megabases apart or even on different chromosomes. Finally, visPIG is multi-scale: a sub-region of particular interest can be 'zoomed' in. We describe the various features of visPIG and illustrate its utility with examples. visPIG is freely available through http://vispig.icr.ac.uk under a GNU General Public License (GPLv3).
doi:10.1371/journal.pone.0107497
PMCID: PMC4160258  PMID: 25208325
5.  Common variation at 2q22.3 (ZEB2) influences the risk of renal cancer 
Human Molecular Genetics  2012;22(4):825-831.
Genome-wide association studies (GWASs) of renal cell cancer (RCC) have identified four susceptibility loci thus far. To identify an additional RCC common susceptibility locus, we conducted a GWAS and performed a meta-analysis with published GWASs (totalling 2215 cases and 8566 controls of European background) and followed up the most significant association signals [nine single nucleotide polymorphisms (SNPs) in eight genomic regions] in 3739 cases and 8786 controls. A combined analysis identified a novel susceptibility locus mapping to 2q22.3 marked by rs12105918 (P = 1.80 × 10−8; odds ratio 1.29, 95% CI: 1.18–1.41). The signal localizes to intron 2 of the ZEB2 gene (zinc finger E box-binding homeobox 2). Our findings suggest that genetic variation in ZEB2 influences the risk of RCC. This finding provides further insights into the genetic and biological basis of inherited genetic susceptibility to RCC.
doi:10.1093/hmg/dds489
PMCID: PMC3554205  PMID: 23184150
6.  Inherited variation at chromosome 12p13.33 including RAD52 influences squamous cell lung carcinoma risk 
Cancer Discovery  2011;2(2):131-139.
While lung cancer is largely caused by tobacco smoking, inherited genetic factors play a role in its etiology. Genome-wide association studies (GWAS) in Europeans have robustly demonstrated only three polymorphic variations influencing lung cancer risk. Tumor heterogeneity may have hampered the detection of association signal when all lung cancer subtypes were analyzed together. In a GWAS of 5,355 European smoking lung cancer cases and 4,344 smoking controls, we conducted a pathway-based analysis in lung cancer histologic subtypes with 19,082 SNPs mapping to 917 genes in the HuGE-defined “inflammation” pathway. We identified a susceptibility locus for squamous cell lung carcinoma (SQ) at 12p13.33 (RAD52, rs6489769), and replicated the association in three independent samples totaling 3,359 SQ cases and 9,100 controls (odds ratio=1.20, Pcombined=2.3×10−8).
Significance
The combination of pathway-based approaches and information on disease specific subtypes can improve the identification of cancer susceptibility loci in heterogeneous diseases.
doi:10.1158/2159-8290.CD-11-0246
PMCID: PMC3354721  PMID: 22585858
Lung cancer; histology; squamous cell carcinoma; pathway analysis; RAD52

Results 1-6 (6)