A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer.

Authors:
Dr. Jonine Figueroa, PhD
Dr. Jonine Figueroa, PhD
Usher Institute of Population Health Sciences and Informatics
Chancellor's Fellow
Molecular epidemiology
Edinburgh, Scotland | United Kingdom
Lang Wu Wei Shi Jirong Long Xingyi Guo Kyriaki Michailidou Jonathan Beesley Manjeet K Bolla Xiao-Ou Shu Yingchang Lu Qiuyin Cai Fares Al-Ejeh Esdy Rozali Qin Wang Joe Dennis Bingshan Li Chenjie Zeng Helian Feng Alexander Gusev Richard T Barfield Irene L Andrulis Hoda Anton-Culver Volker Arndt Kristan J Aronson Paul L Auer Myrto Barrdahl Caroline Baynes Matthias W Beckmann Javier Benitez Marina Bermisheva Carl Blomqvist Natalia V Bogdanova Stig E Bojesen Hiltrud Brauch Hermann Brenner Louise Brinton Per Broberg Sara Y Brucker Barbara Burwinkel Trinidad Caldés Federico Canzian Brian D Carter J Esteban Castelao Jenny Chang-Claude Xiaoqing Chen Ting-Yuan David Cheng Hans Christiansen Christine L Clarke Margriet Collée Sten Cornelissen Fergus J Couch David Cox Angela Cox Simon S Cross Julie M Cunningham Kamila Czene Mary B Daly Peter Devilee Kimberly F Doheny Thilo Dörk Isabel Dos-Santos-Silva Martine Dumont Miriam Dwek Diana M Eccles Ursula Eilber A Heather Eliassen Christoph Engel Mikael Eriksson Laura Fachal Peter A Fasching Dieter Flesch-Janys Olivia Fletcher Henrik Flyger Lin Fritschi Marike Gabrielson Manuela Gago-Dominguez Susan M Gapstur Montserrat García-Closas Mia M Gaudet Maya Ghoussaini Graham G Giles Mark S Goldberg David E Goldgar Anna González-Neira Pascal Guénel Eric Hahnen Christopher A Haiman Niclas Håkansson Per Hall Emily Hallberg Ute Hamann Patricia Harrington Alexander Hein Belynda Hicks Peter Hillemanns Antoinette Hollestelle Robert N Hoover John L Hopper Guanmengqian Huang Keith Humphreys David J Hunter Anna Jakubowska Wolfgang Janni Esther M John Nichola Johnson Kristine Jones Michael E Jones Audrey Jung Rudolf Kaaks Michael J Kerin Elza Khusnutdinova Veli-Matti Kosma Vessela N Kristensen Diether Lambrechts Loic Le Marchand Jingmei Li Sara Lindström Jolanta Lissowska Wing-Yee Lo Sibylle Loibl Jan Lubinski Craig Luccarini Michael P Lux Robert J MacInnis Tom Maishman Ivana Maleva Kostovska Arto Mannermaa JoAnn E Manson Sara Margolin Dimitrios Mavroudis Hanne Meijers-Heijboer Alfons Meindl Usha Menon Jeffery Meyer Anna Marie Mulligan Susan L Neuhausen Heli Nevanlinna Patrick Neven Sune F Nielsen Børge G Nordestgaard Olufunmilayo I Olopade Janet E Olson Håkan Olsson Paolo Peterlongo Julian Peto Dijana Plaseska-Karanfilska Ross Prentice Nadege Presneau Katri Pylkäs Brigitte Rack Paolo Radice Nazneen Rahman Gad Rennert Hedy S Rennert Valerie Rhenius Atocha Romero Jane Romm Anja Rudolph Emmanouil Saloustros Dale P Sandler Elinor J Sawyer Marjanka K Schmidt Rita K Schmutzler Andreas Schneeweiss Rodney J Scott Christopher G Scott Sheila Seal Mitul Shah Martha J Shrubsole Ann Smeets Melissa C Southey John J Spinelli Jennifer Stone Harald Surowy Anthony J Swerdlow Rulla M Tamimi William Tapper Jack A Taylor Mary Beth Terry Daniel C Tessier Abigail Thomas Kathrin Thöne Rob A E M Tollenaar Diana Torres Thérèse Truong Michael Untch Celine Vachon David Van Den Berg Daniel Vincent Quinten Waisfisz Clarice R Weinberg Camilla Wendt Alice S Whittemore Hans Wildiers Walter C Willett Robert Winqvist Alicja Wolk Lucy Xia Xiaohong R Yang Argyrios Ziogas Elad Ziv Alison M Dunning Paul D P Pharoah Jacques Simard Roger L Milne Stacey L Edwards Peter Kraft Douglas F Easton Georgia Chenevix-Trench Wei Zheng

Nat Genet 2018 07 18;50(7):968-978. Epub 2018 Jun 18.

Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA.

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

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http://dx.doi.org/10.1038/s41588-018-0132-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314198PMC
July 2018
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1 Citation
29.352 Impact Factor

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