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. 2020 Nov 5;107(5):837-848.
doi: 10.1016/j.ajhg.2020.09.001. Epub 2020 Oct 5.

Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk

Iris Kramer  1 , Maartje J Hooning  2 , Nasim Mavaddat  3 , Michael Hauptmann  4 , Renske Keeman  1 , Ewout W Steyerberg  5 , Daniele Giardiello  6 , Antonis C Antoniou  3 , Paul D P Pharoah  7 , Sander Canisius  8 , Zumuruda Abu-Ful  9 , Irene L Andrulis  10 , Hoda Anton-Culver  11 , Kristan J Aronson  12 , Annelie Augustinsson  13 , Heiko Becher  14 , Matthias W Beckmann  15 , Sabine Behrens  16 , Javier Benitez  17 , Marina Bermisheva  18 , Natalia V Bogdanova  19 , Stig E Bojesen  20 , Manjeet K Bolla  3 , Bernardo Bonanni  21 , Hiltrud Brauch  22 , Michael Bremer  23 , Sara Y Brucker  24 , Barbara Burwinkel  25 , Jose E Castelao  26 , Tsun L Chan  27 , Jenny Chang-Claude  28 , Stephen J Chanock  29 , Georgia Chenevix-Trench  30 , Ji-Yeob Choi  31 , Christine L Clarke  32 ; NBCS Collaborators  33 ; J Margriet Collée  34 , Fergus J Couch  35 , Angela Cox  36 , Simon S Cross  37 , Kamila Czene  38 , Mary B Daly  39 , Peter Devilee  40 , Thilo Dörk  41 , Isabel Dos-Santos-Silva  42 , Alison M Dunning  43 , Miriam Dwek  44 , Diana M Eccles  45 , D Gareth Evans  46 , Peter A Fasching  47 , Henrik Flyger  48 , Manuela Gago-Dominguez  49 , Montserrat García-Closas  29 , José A García-Sáenz  50 , Graham G Giles  51 , David E Goldgar  52 , Anna González-Neira  53 , Christopher A Haiman  54 , Niclas Håkansson  55 , Ute Hamann  56 , Mikael Hartman  57 , Bernadette A M Heemskerk-Gerritsen  2 , Antoinette Hollestelle  2 , John L Hopper  58 , Ming-Feng Hou  59 , Anthony Howell  60 ; ABCTB Investigators  61 ; kConFab Investigators  62 ; Hidemi Ito  63 , Milena Jakimovska  64 , Anna Jakubowska  65 , Wolfgang Janni  66 , Esther M John  67 , Audrey Jung  16 , Daehee Kang  68 , C Marleen Kets  69 , Elza Khusnutdinova  70 , Yon-Dschun Ko  71 , Vessela N Kristensen  72 , Allison W Kurian  73 , Ava Kwong  74 , Diether Lambrechts  75 , Loic Le Marchand  76 , Jingmei Li  77 , Annika Lindblom  78 , Jan Lubiński  79 , Arto Mannermaa  80 , Mehdi Manoochehri  56 , Sara Margolin  81 , Keitaro Matsuo  63 , Dimitrios Mavroudis  82 , Alfons Meindl  83 , Roger L Milne  51 , Anna Marie Mulligan  84 , Taru A Muranen  85 , Susan L Neuhausen  86 , Heli Nevanlinna  85 , William G Newman  46 , Andrew F Olshan  87 , Janet E Olson  88 , Håkan Olsson  13 , Tjoung-Won Park-Simon  41 , Julian Peto  42 , Christos Petridis  89 , Dijana Plaseska-Karanfilska  64 , Nadege Presneau  44 , Katri Pylkäs  90 , Paolo Radice  91 , Gad Rennert  9 , Atocha Romero  92 , Rebecca Roylance  93 , Emmanouil Saloustros  94 , Elinor J Sawyer  95 , Rita K Schmutzler  96 , Lukas Schwentner  66 , Christopher Scott  88 , Mee-Hoong See  97 , Mitul Shah  43 , Chen-Yang Shen  98 , Xiao-Ou Shu  99 , Sabine Siesling  100 , Susan Slager  88 , Christof Sohn  101 , Melissa C Southey  102 , John J Spinelli  103 , Jennifer Stone  104 , William J Tapper  45 , Maria Tengström  105 , Soo Hwang Teo  106 , Mary Beth Terry  107 , Rob A E M Tollenaar  108 , Ian Tomlinson  109 , Melissa A Troester  87 , Celine M Vachon  110 , Chantal van Ongeval  111 , Elke M van Veen  46 , Robert Winqvist  90 , Alicja Wolk  112 , Wei Zheng  99 , Argyrios Ziogas  11 , Douglas F Easton  7 , Per Hall  113 , Marjanka K Schmidt  114
Collaborators, Affiliations

Breast Cancer Polygenic Risk Score and Contralateral Breast Cancer Risk

Iris Kramer et al. Am J Hum Genet. .

Abstract

Previous research has shown that polygenic risk scores (PRSs) can be used to stratify women according to their risk of developing primary invasive breast cancer. This study aimed to evaluate the association between a recently validated PRS of 313 germline variants (PRS313) and contralateral breast cancer (CBC) risk. We included 56,068 women of European ancestry diagnosed with first invasive breast cancer from 1990 onward with follow-up from the Breast Cancer Association Consortium. Metachronous CBC risk (N = 1,027) according to the distribution of PRS313 was quantified using Cox regression analyses. We assessed PRS313 interaction with age at first diagnosis, family history, morphology, ER status, PR status, and HER2 status, and (neo)adjuvant therapy. In studies of Asian women, with limited follow-up, CBC risk associated with PRS313 was assessed using logistic regression for 340 women with CBC compared with 12,133 women with unilateral breast cancer. Higher PRS313 was associated with increased CBC risk: hazard ratio per standard deviation (SD) = 1.25 (95%CI = 1.18-1.33) for Europeans, and an OR per SD = 1.15 (95%CI = 1.02-1.29) for Asians. The absolute lifetime risks of CBC, accounting for death as competing risk, were 12.4% for European women at the 10th percentile and 20.5% at the 90th percentile of PRS313. We found no evidence of confounding by or interaction with individual characteristics, characteristics of the primary tumor, or treatment. The C-index for the PRS313 alone was 0.563 (95%CI = 0.547-0.586). In conclusion, PRS313 is an independent factor associated with CBC risk and can be incorporated into CBC risk prediction models to help improve stratification and optimize surveillance and treatment strategies.

Keywords: contralateral breast cancer; epidemiology; genetic; polygenic risk score.

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Conflict of interest statement

M.W.B. conducts research funded by Amgen, Novartis, and Pfizer, outside the submitted work. P.A.F. conducts research funded by Amgen, Novartis, and Pfizer, outside the submitted work. He received honoraria from Roche, Novartis, and Pfizer. H.N. received honorarium from Astra Zeneca outside the submitted work.

Figures

Figure 1
Figure 1
Estimates for Contralateral Breast Cancer Risk by Percentile Categories of the 313-Variant PRS (PRS313) The figure shows the hazard ratios per SD and 95% confidence intervals for percentiles of the PRS313 relative to the middle quintile (underlying table can be found in Table S5). The solid line denotes the estimates for contralateral breast cancer risk with the PRS313 fitted as a continuous covariate. Coefficients to construct the PRS313 are shown in Table S3. The PRS313 was standardized by SD = 0.61, in line with Mavaddat et al. The analyses were performed with attained age as timescale. PRS, polygenic risk score; SD, standard deviation.
Figure 2
Figure 2
Predicted Contralateral Breast Cancer Risk by Percentile of the 313-Variant PRS (PRS313) with Death as Competing Risk Coefficients to construct the PRS313 are shown in Table S3. The PRS313 was standardized by SD = 0.61, in line with Mavaddat et al. The CBC incidences were calculated based on incidence data from the Netherlands Cancer Registry and relative risks estimated as described in the Material and Methods. PRS, polygenic risk score; CBC, contralateral breast cancer.
Figure 3
Figure 3
Distribution of the 313-Variant PRS (PRS313) in 62,830 Control Women without Any Diagnosis of Breast Cancer, 81,000 Women with Unilateral Breast Cancer, and 3,607 Women with Contralateral Breast Cancer Coefficients to construct the PRS313 are shown in Table S3. The PRS313 was standardized by SD = 0.61, in line with Mavaddat et al. PRS, polygenic risk score; BC, breast cancer; CBC, contralateral breast cancer; SD, standard deviation.
See this image and copyright information in PMC

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