Citations 2
Breast Cancer Risk Factors and Survival by Tumor Subtype: Pooled Analyses from the Breast Cancer Association Consortium
Morra, Anna , Jung, Audrey , Behrens, Sabine , Keeman, Renske , Ahearn, Thomas U. , Arndt, Volker , Augustinsson, Annelie , Auvinen, Päivi , Becher, Heiko , Beckmann, Matthias W. , Bojesen, Stig E. , Bolla, Manjeet K. , Brenner, Hermann , Camp, Nicola J. , Campa, Daniele , Castelao, Jose E. , Choi, Ji‐Yeob , Cox, Angela , Easton, Douglas F. , Eccles, Diana M., Egan, Kathleen M. , Evans, D. Gareth , Fasching, Peter A. , Flyger, Henrik, Gago-Domínguez, Manuela , Gapstur, Susan M. , Gaudet, Mia M. , Grip, Mervi, Guénel, Pascal , Haiman, Christopher A. , Håkansson, Niclas , Hamann, Ute, Hartman, Mikael , Heyworth, Jane , Hoppe, Reiner , Hopper, John L. , Hunter, David J. , Jager, Agnes , Jakimovska, Milena , Janni, Wolfgang , Koutros, Stella , Kristensen, Vessela N. , Lambrechts, Diether , Li, Jingmei , Lindblom, Annika , Mannermaa, Arto , Manoochehri, Mehdi, Margolin, Sara , Mariapun, Shivaani, Mavroudis, Dimitrios, Muranen, Taru , Newman, William G. , Noh, Dong‐Young , Nordestgaard, Børge G. , Obi, Nadia , Olsson, Håkan , Park‐Simon, Tjoung‐Won , Petridis, Christos , Plaseska‐Karanfilska, Dijana , Rashid, Muhammad Usman , Rennert, Gad , Rennert, Gad , Rhenius, Valerie , Romero, Atocha , Saloustros, Emmanouil , Sawyer, Elinor J. , Schneeweiß, Andreas , Schwentner, Lukas , Shah, Mitul , Shen, Chen‐Yang , Tollenaar, Rob A.�E.�M. , Tomlinson, Ian , Torres, Diana , Vachon, Celine M. , Wang, Qin , Wang, Sophia , Williams, Justin A. , Winqvist, Robert , Wu, Anna H. , Yoo, Keun-Young, Yu, Jyh‐Cherng , Zheng, Wei , Yang, Xiaohong R. , Eliassen, A. Heather , García‐Closas, Montserrat , Teo, Soo‐Hwang , Chang‐Claude, Jenny , Eccles, Diana , Khaw, Kay‐Tee , Lambrechts, Diether , Arndt, Volker , Augustinsson, Annelie , Brenner, Hermann , Camp, Nicola J , Canzian, Federico , Cox, Angela , Dunning, Alison M , Evans, D Gareth , Fasching, Peter A , Gago-Dominguez, Manuela , García-Sáenz, José A , Gaudet, Mia M , Giles, Graham G , Guénel, Pascal , Hall, Per N , Hart, Steven N , Hartman, Mikael , Ito, Hidemi , Jager, Agnes , Jakubowska, Anna , Janni, Wolfgang , Kaaks, Rudolf , Kapoor, Pooja Middha , Koutros, Stella , Lambrechts, Diether , Li, Jingmei , Matsuo, Keitaro , Milne, Roger L , Muranen, Taru A , Newman, William G , Park-Simon, Tjoung-Won , Pharoah, Paul D P , Rennert, Gad , Rennert, Gad , Rhenius, Valerie , Romero, Atocha , Saloustros, Emmanouil , Schneeweiss, Andreas , Scott, Christopher , Southey, Melissa C , Stram, Daniel O. , Tamimi, Rulla M , Tomlinson, Ian , Torres, Diana , Vachon, Celine M. , Wolk, Alicja , Ziogas, Argyrios , Holmes, Michelle D , García-Closas, Montserrat , Teo, Soo H , Schmidt, Marjanka K , Chang-Claude, Jenny , Lambrechts, Diether , Behrens, Sabine , Eccles, Diana , Keeman, Renske , Zheng, Wei , Wang, Sophia S , Jung, Audrey Y , Becher, Heiko , Eliassen, A Heather , Håkansson, Niclas , Rashid, Muhammad U , Bojesen, Stig E , Lindblom, Annika , Plaseska-Karanfilska, Dijana , Sawyer, Elinor J , Anton‐Culver, Hoda , Freeman, Laura E. Beane , Blomqvist, Carl , Briceño, Ignacio , Brucker, Sara Yvonne , Canzian, Federico , Chanock, Stephen Jacob , Clarke, Christine L. , Couch, Fergus J. , Cross, Simon S. , Czene, Kamila , Dörk, Thilo , Dunning, Alison M. , Dwek, Miriam , García-Sáenz, José Á. , Giles, Graham G. , Han, Sileny , Hart, Steven N. , Ito, Hidemi , Jakubowska, Anna , Kaaks, Rudolf , Kang, Daehee , Middha, Pooja , Kitahara, Cari M. , Kraft, Peter , Lacey, James V. , Marchand, Loı̈c Le , Lubiński, Jan , Lush, Michael J. , Manoochehri, Mehdi, Matsuo, Keitaro , Milne, Roger L. , Olshan, Andrew F. , Pharoah, Paul D.P. , Presneau, Nadège , Scott, Christopher G. , Shu, Xiao‐Ou , Southey, Melissa C. , Tamimi, Rulla M. , Tapper, William , Troester, Melissa A. , Truong, Thérèse , Wolk, Alicja , Ziogas, Argyrios , Schmidt, Marjanka K.
Cancer Epidemiology, Biomarkers & Prevention | January 26, 2021 | Volume: 30 | Issue: 4 | Pages: 623-642
Abstract Background: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype. Methods: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer–specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype. Results: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (Padj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5–25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06–1.34)]; current versus never smoking [1.37 (1.27–1.47)], high versus low physical activity [0.43 (0.21–0.86)], age ≥30 years versus <20 years at first pregnancy [0.79 (0.72–0.86)]; >0–<5 years versus ≥10 years since last full-term birth [1.31 (1.11–1.55)]; ever versus never use of oral contraceptives [0.91 (0.87–0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen–progestin therapy [0.61 (0.54–0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02–1.21) for current versus never smoking. Conclusions: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype. Impact: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.
Exploratory Genome-Wide Interaction Analysis of Nonsteroidal Anti-inflammatory Drugs and Predicted Gene Expression on Colorectal Cancer Risk
Petersen, Paneen S., Schmit, Stephanie L. , Drew, David A. , Berndt, Sonja I. , Brenner, Hermann , Casey, Graham , Chang‐Claude, Jenny , Gallinger, Steven , Gruber, Stephen B. , Haile, Robert W. , Harrison, Tabitha A. , Hoffmeister, Michael , Jacobs, Eric J. , Joshi, Amit D. , Li, Li , Lindor, Noralane M. , Martín, Vicente , Maclnnis, Robert J., Moreno, Vı́ctor , Nan, Hongmei , Rennert, Gad , Slattery, Martha L. , Thibodeau, S. N., Weinstein, Stephanie J. , Woods, Michael O. , Peters, Ulrike , Brenner, Hermann , Rennert, Gad , Drew, David A , Brenner, Hermann , Gruber, Stephen B , Haile, Robert W , Harrison, Tabitha A , Hoffmeister, Michael , Martín, Vicente , Milne, Roger L , Maclnnis, Robert , Moreno, Victor , Potter, John D , Rennert, Gad , Slattery, Martha L , Thibodeau, Steve N, Weinstein, Stephanie J , Rennert, Gad , Brenner, Hermann , Nan, Hongmei , Wang, Xiaoliang , Su, Yu-Ru , Bien, Stephanie A. , Albanes, Demetrius , Campbell, Peter T. , Jenkins, Mark A. , Lin, Yi , Marchand, Loı̈c Le , Milne, Roger L. , Newcomb, Polly A. , Potter, John D. , Chan, Andrew T. , White, Emily , Hsu, Li
Cancer Epidemiology, Biomarkers & Prevention | July 10, 2020 | Volume: 29 | Issue: 9 | Pages: 1800-1808
Abstract Background: Regular use of nonsteroidal anti-inflammatory drugs (NSAID) is associated with lower risk of colorectal cancer. Genome-wide interaction analysis on single variants (G × E) has identified several SNPs that may interact with NSAIDs to confer colorectal cancer risk, but variations in gene expression levels may also modify the effect of NSAID use. Therefore, we tested interactions between NSAID use and predicted gene expression levels in relation to colorectal cancer risk. Methods: Genetically predicted gene expressions were tested for interaction with NSAID use on colorectal cancer risk among 19,258 colorectal cancer cases and 18,597 controls from 21 observational studies. A Mixed Score Test for Interactions (MiSTi) approach was used to jointly assess G × E effects which are modeled via fixed interaction effects of the weighted burden within each gene set (burden) and residual G × E effects (variance). A false discovery rate (FDR) at 0.2 was applied to correct for multiple testing. Results: Among the 4,840 genes tested, genetically predicted expression levels of four genes modified the effect of any NSAID use on colorectal cancer risk, including DPP10 (PG×E = 1.96 × 10−4), KRT16 (PG×E = 2.3 × 10−4), CD14 (PG×E = 9.38 × 10−4), and CYP27A1 (PG×E = 1.44 × 10−3). There was a significant interaction between expression level of RP11-89N17 and regular use of aspirin only on colorectal cancer risk (PG×E = 3.23 × 10−5). No interactions were observed between predicted gene expression and nonaspirin NSAID use at FDR < 0.2. Conclusions: By incorporating functional information, we discovered several novel genes that interacted with NSAID use. Impact: These findings provide preliminary support that could help understand the chemopreventive mechanisms of NSAIDs on colorectal cancer.