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Multicenter Study
. 2016 Dec 6;7(49):80140-80163.
doi: 10.18632/oncotarget.12818.

Association of Breast Cancer Risk With Genetic Variants Showing Differential Allelic Expression: Identification of a Novel Breast Cancer Susceptibility Locus at 4q21

Yosr Hamdi  1 Penny Soucy  1 Véronique Adoue  2   3   4 Kyriaki Michailidou  5   6 Sander Canisius  7 Audrey Lemaçon  8 Arnaud Droit  8 Irene L Andrulis  9   10 Hoda Anton-Culver  11 Volker Arndt  12 Caroline Baynes  13 Carl Blomqvist  14 Natalia V Bogdanova  15   16 Stig E Bojesen  17   18   19 Manjeet K Bolla  5 Bernardo Bonanni  20 Anne-Lise Borresen-Dale  21 Judith S Brand  22 Hiltrud Brauch  23   24   25 Hermann Brenner  12   25   26 Annegien Broeks  7 Barbara Burwinkel  27   28 Jenny Chang-Claude  29   30 NBCS CollaboratorsFergus J Couch  31 Angela Cox  32 Simon S Cross  33 Kamila Czene  22 Hatef Darabi  22 Joe Dennis  5 Peter Devilee  34   35 Thilo Dörk  16 Isabel Dos-Santos-Silva  36 Mikael Eriksson  22 Peter A Fasching  37   38 Jonine Figueroa  39   40 Henrik Flyger  41 Montserrat García-Closas  40 Graham G Giles  42   43 Mark S Goldberg  44   45 Anna González-Neira  46 Grethe Grenaker-Alnæs  21 Pascal Guénel  47 Lothar Haeberle  37 Christopher A Haiman  48 Ute Hamann  49 Emily Hallberg  50 Maartje J Hooning  51 John L Hopper  43 Anna Jakubowska  52 Michael Jones  53 Maria Kabisch  49 Vesa Kataja  54   55 Diether Lambrechts  56   57 Loic Le Marchand  58 Annika Lindblom  59 Jan Lubinski  52 Arto Mannermaa  54   60   61 Mel Maranian  13 Sara Margolin  62 Frederik Marme  27   63 Roger L Milne  42   43 Susan L Neuhausen  64 Heli Nevanlinna  65 Patrick Neven  66 Curtis Olswold  50 Julian Peto  36 Dijana Plaseska-Karanfilska  67 Katri Pylkäs  68   69 Paolo Radice  70 Anja Rudolph  29 Elinor J Sawyer  71 Marjanka K Schmidt  7 Xiao-Ou Shu  72 Melissa C Southey  73 Anthony Swerdlow  74 Rob A E M Tollenaar  75 Ian Tomlinson  76 Diana Torres  49   77 Thérèse Truong  47 Celine Vachon  50 Ans M W Van Den OuwelandQin Wang  5 Robert Winqvist  68   69 kConFab/AOCS InvestigatorsWei Zheng  72 Javier Benitez  46   78 Georgia Chenevix-Trench  79 Alison M Dunning  13 Paul D P Pharoah  5   13 Vessela Kristensen  21   80 Per Hall  22 Douglas F Easton  5   13 Tomi Pastinen  81   82 Silje Nord  21 Jacques Simard  1
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Free PMC article
Multicenter Study

Association of Breast Cancer Risk With Genetic Variants Showing Differential Allelic Expression: Identification of a Novel Breast Cancer Susceptibility Locus at 4q21

Yosr Hamdi et al. Oncotarget. .
Free PMC article

Abstract

There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance inexpression of these genes in breast carcinomas.

Keywords: association studies; breast cancer; cis-regulatory variants; differential allelic expression; genetic susceptibility.

Conflict of interest statement

CONFLICTS OF INTEREST

The authors declare they have no conflict of interest.

Figures

Figure 1
Figure 1. Regional plots of breast cancer risk association at 4q21
Regional plot of association result, recombination hotspots and LD for the 4q21: 84,132,874-84,631,193 loci. The index SNP rs11099601 is plotted as a blue triangle. Directly genotyped SNPs are represented as triangles and imputed SNPs (r2 > 0.3, MAF > 0.02) are represented as circles. The LD (r2) for the index SNP with each SNP was computed based on European ancestry subjects included in the 1000 Genome Mar 2012 EUR. Pairwise r2 values are plotted using a red scale, where white and red signify r2 = 0 and 1, respectively. P-values were from the single-marker analysis based on logistic regression models after adjusted for age, study sites and the first six principal components plus one additional principal component for the LMBC in analyses of data from European descendants. SNPs are plotted according to their chromosomal position: physical locations are based on GRCh37/hg19. Gene annotation was based on the NCBI RefSeq genes from the UCSC Genome Browser.
Figure 2
Figure 2. Functional annotation of the 4q21 locus
A. Functional annotations using data from the ENCODE and NIH Roadmap Epigenomics projects. From top to bottom, epigenetic signals evaluated included DNase clusters in MCF7 and HMEC cells, chromatin state segmentation by Hidden Markov Model (ChromHMM) in HMEC, breast myoepithelial cells (BMC) and Variant human mammary epithelial cells (vHMEC), where red represents an active promoter region, orange a strong enhancer and yellow a poised enhancer respectively (the detailed color scheme of chromatin states is described in the UCSC browser), histone modifications in MCF7, HMEC and BMC cell lines; and overlap between candidate variants and Max binding site in MCF7 cells. All tracks were generated by the UCSC genome browser (hg 19). B. Long-range chromatin interactions. From top to bottom, ChIA-Pet interactions for PolII and CTCF in MCF7 cells and Hi-C interactions in HMEC cells. The ChIA-PET raw data available on GEO under the following accession (GSE63525.K56, GSE33664, GSE39495) were processed with the GenomicRanges package. C. Maps of mammary cell super-enhancer locations as defined in Hnisz et al. are shown in HMEC cells. Predicted enhancer-promoter determined interactions in MCF7 and HMEC cells, as defined by the integrated method for predicting enhancer targets (IM-PET) are shown. D. RNA-Seq data from MCF7 and HMEC cell lines. The value of the RNA-Seq analysis corresponds to the mean RPM value for FAM175A, MRPS18C, HELQ, AGPAT9, HSPE and COQ2 from four HMEC and 19 MCF7 datasets, respectively. The annotation was obtained through the Bioconductor annotation package TxDb.Hsapiens.UCSC.hg19.knownGene. The tracks have been generated using ggplot2 and ggbio library in R.
Figure 3
Figure 3. Boxplots representing differential expression of HELQ (A), MRPS18C (B), FAM175A (C) and HPSE (D) in breast tissues
Differential expression between normal breast and tumor tissue was determined by a Kruskal-Wallis rank sum test using TCGA breast cancer RNAseq data from primary tumor, metastasis and adjacent normal. Horizontal bars indicate mean expression levels.
Figure 4
Figure 4. Boxplots representing expression levels of HELQ (A), MRPS18C (B), FAM175A (C) and HPSE (D) in the 5 molecular subtypes (PAM50 classifier) of breast primary tumors
Differential expression between normal breast and tumor tissue was determined by a Kruskal-Wallis rank sum test. Analysis was performed using TCGA breast cancer RNAseq data from five molecular subtypes of breast primary tumors: Luminal A (LumA), Luminal B (LumB), Human epidermal growth factor receptor 2-enriched (Her2), Basal-like (Basal) and Normal-like (Normal). Horizontal bars indicate mean expression levels.
Figure 5
Figure 5. Manhattan plots of association for the eQTL results at the 4q21 locus in normal breast and breast cancer tissue
Y-axis shows -log10(P-value) while x-axis shows physical position. Circles of various shades of blue represent breast cancer risk associations for all breast cancer tumors, ER+ and ER- tumors. Other colored circles represent eQTL results in the following datasets: normal breast (NB93, NB116) in various shades of green, breast carcinomas in pink (BC241) and red (BC765). Risk association results as well as eQTL results are for both imputed and genotyped SNPs for all datasets.
Figure 6
Figure 6. Boxplots representing the most significant eQTL results for variant rs11099601 in normal breast tissue and breast tumor datasets
Box plots represent the expression levels of the indicated transcripts with respect to the rs11099601 genotypes. Expression levels are shown for A. HELQ in breast carcinoma BC241 dataset, B. HELQ in breast carcinoma BC765 dataset normalized per isoform, C. HELQ in normal breast NB93 dataset normalized by gene isoform, D. MRPS18C in breast carcinoma BC765 dataset, E. MRPS18C in breast carcinoma BC765 dataset normalized per isoform, F. FAM175A in breast carcinoma BC765 dataset and G. HSPE in normal breast NB116 dataset. Horizontal bars indicate mean expression level per genotype. r2 values indicate the percentage of variance in respective gene expression levels explained by rs11099601.

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