Background: Pancreatic cancer mutation signatures closely resemble breast cancer, suggesting that both cancers may have common predisposition mechanisms that may include commonly inherited SNPs.

Methods: We examined 23 genetic variants known to be associated with pancreatic cancer as breast cancer risk factors in the Root genome-wide association study (GWAS; 1,657 cases and 2,029 controls of African diaspora) and GAME-ON/DRIVE GWAS (16,003 cases and 41,335 controls of European ancestry).

Results: None of the pancreatic cancer susceptibility variants were individually associated with breast cancer risk after adjustment for multiple testing (at α = 0.002) in the two populations. In Root GWAS, a change by one SD in the polygenic risk score (PRS) was not significantly associated with breast cancer. In addition, we did not observe a trend in the relationship between PRS percentiles and breast cancer risk.

Conclusions: The association between reported pancreatic cancer genetic susceptibility variants and breast cancer development in women of African or European ancestry is likely weak, if it does exist.

Impact: Known GWAS-derived susceptibility variants of pancreatic cancer do not explain its shared genetic etiology with breast cancer. Cancer Epidemiol Biomarkers Prev; 27(1); 116–8. ©2017 AACR.

Patients with pancreatic cancer have been found to carry rare germline deleterious variants in breast cancer susceptibility genes, such as BRCA1, BRCA2, PALB2, and ATM (1–3). In addition, a number of common SNPs were identified to be associated with common diseases, including pancreatic and breast cancers, by hypothesis-free genome-wide association study (GWAS) approach. Couch and colleagues evaluated the SNPs associated with breast cancer risk for influence on pancreatic cancer risk and found the SNP rs1045485 retained significance after adjusting for multiple testing (4). Furthermore, an interesting phenomenon indicated in the Catalogue of Somatic Mutations in Cancer was that the 7 mutational signatures of pancreatic cancer were all shared by those of breast cancer (http://cancer.sanger.ac.uk/signatures/matrix.png). These lines of evidence suggest that breast cancer and pancreatic cancer might have common predisposition mechanisms.

To date, many of the common variants associated with the risk of pancreatic cancer have been identified by the GWAS approach, and more than 20 loci reached the standard GWAS significance threshold (5), but no study has explored the possible associations between these SNPs and breast cancer risk. Here, we examined whether GWAS-identified genetic susceptibility to pancreatic cancer is related to breast cancer risk using GWAS datasets from two breast cancer consortia: Root and GAME-ON/DRIVE.

The Root consortium contained 1,657 cases and 2,029 controls of African diaspora, in which genotyping was conducted using the Illumina HumanOmni2.5-8v1 array, and imputation was conducted with the 1000 Genomes Project Phase 1 as reference panel (6). The GAME-ON/DRIVE GWAS is a meta-analysis of 12 breast cancer GWAS, including 16,003 cases and 41,335 controls of European ancestry (http://gameon.dfci.harvard.edu). Both studies were conducted in accordance of U.S. common rule, have been approved by their institutional review board, and obtained informed written consent from all the participants (6).

A total of 23 known independent pancreatic cancer susceptibility loci (P < 5 × 10−8) were extracted from the NHGRI-EBI GWAS Catalog (https://www.ebi.ac.uk/gwas/, accessed on January 14, 2017). For Root GWAS, we used logistic regression with case status as the outcome and an additive model for genotype, adjusting for age (10-year groups), study site, and the first four eigenvectors from principal component analysis. For GAME-ON/DRIVE GWAS, fixed-effects meta-analysis was used and the SEs were adjusted by the inflation factors. We also constructed a polygenic risk score (PRS) based on risk allele frequencies across all loci and evaluated its relation to breast cancer risk in Root. The PRS was calculated as the log OR-weighted sum of risk allele counts, defined as |{\rm{PRS}} = \sum\nolimits_{i = 1}^{23} {{n_i} \times ln( {O{R_i}} )} $|⁠, where |{n_i}$| is the number of risk alleles carried by an individual at the ith SNP with |{n_i} = \{ {0,{\rm{\ }}1,{\rm{\ }}2} \},{\rm{\ }}$| and |O{R_i}$| is the per-allele OR associated with the ith SNP. Adjusted ORs and 95% confidence intervals (CI) were used to measure the association of breast cancer risk with genetic variants or PRS. Statistical significance was declared at the 0.0022 (0.05/23) level for each SNP.

For women of African ancestry, rs31490-G was a risk allele in both pancreatic and breast cancers, whereas the risk allele rs401681-T in pancreatic cancer became a protective allele in breast cancer (Table 1). Similarly, for women of European ancestry, rs11655237-T and rs2736098-C were found to be risk alleles in both pancreatic and breast cancers, but two pancreatic cancer risk alleles rs505922-C and rs687289-A turned to be protective for breast cancer (Table 1). The aforementioned SNPs were nominal significantly association with breast cancer risk; however, none of them remained significant after the adjustment for multiple testing.

Table 1.

Association of pancreatic cancer susceptibility variants with risk of breast cancer

Pancreatic cancerRootGAME-ON/DRIVE
SNPReference/effect alleleOR (95% CI)TypeaOR (95% CI)POR (95% CI)P
rs10919791 G/A 1.27 (1.18–1.33) Genotyped 1.01 (0.86–1.18) 0.940 1.02 (0.97–1.06) 0.465 
rs11655237 C/T 1.26 (1.19–1.34) 0.96 0.97 (0.87–1.09) 0.643 1.09 (1.02–1.16) 0.007b 
rs12413624 A/T 1.23 (1.16–1.31) 0.99 0.99 (0.85–1.15) 0.902 1.03 (1.00–1.08) 0.051 
rs1486134 T/G 1.14 (1.09–1.19) Genotyped 1.02 (0.90–1.16) 0.719 0.99 (0.95–1.03) 0.538 
rs1547374 G/A 1.27 (1.19–1.35) Genotyped 1.01 (0.92–1.11) 0.833 1.01 (0.97–1.04) 0.767 
rs16986825 C/T 1.18 (1.12–1.25) Genotyped 0.98 (0.76–1.26) 0.848 1.00 (0.96–1.05) 0.997 
rs17688601 A/C 1.14 (1.09–1.19) Genotyped 0.93 (0.74–1.15) 0.479 1.01 (0.97–1.05) 0.512 
rs2736098 T/C 1.25 (1.18–1.32) 0.95 1.09 (0.92–1.28) 0.330 1.05 (1.01–1.11) 0.022b 
rs31490 A/G 1.20 (1.14–1.27) Genotyped 1.12 (1.02–1.23) 0.020b 0.99 (0.95–1.02) 0.491 
rs372883 C/T 1.27 (1.19–1.33) Genotyped 1.00 (0.91–1.10) 0.988 1.00 (0.96–1.03) 0.899 
rs3790844 A/G 1.30 (1.19–1.41) Genotyped 1.03 (0.89–1.20) 0.703 1.01 (0.97–1.05) 0.675 
rs401681 C/T 1.20 (1.13–1.28) 1.00 0.89 (0.81–0.98) 0.018b 1.01 (0.98–1.05) 0.416 
rs505922 T/C 1.27 (1.19–1.35) 1.00 1.04 (0.94–1.14) 0.458 0.96 (0.93–1.00) 0.032b 
rs5768709 A/G 1.25 (1.17–1.34) 0.98 0.98 (0.89–1.09) 0.738 0.99 (0.95–1.03) 0.624 
rs687289 G/A 1.27 (1.20–1.35) Genotyped 1.06 (0.96–1.16) 0.264 0.96 (0.93–0.99) 0.021b 
rs6971499 C/T 1.27 (1.19–1.35) Genotyped 0.99 (0.87–1.14) 0.927 1.02 (0.96–1.08) 0.537 
rs7190458 G/A 1.46 (1.30–1.65) 0.91 0.93 (0.83–1.04) 0.179 1.05 (0.97–1.15) 0.225 
rs9543325 T/C 1.24 (1.16–1.32) Genotyped 1.05 (0.89–1.25) 0.529 0.99 (0.96–1.03) 0.684 
rs9554197 C/T 1.14 (1.10–1.19) Genotyped 1.03 (0.91–1.17) 0.606 1.00 (0.97–1.03) 0.986 
rs9573163 C/G 1.26 (1.18–1.34) 0.99 0.90 (0.79–1.04) 0.157 1.01 (0.97–1.04) 0.741 
rs9581943 G/A 1.15 (1.10–1.20) Genotyped 1.03 (0.87–1.22) 0.705 — — 
rs962856 T/C 1.12 (1.08–1.17) Genotyped 1.09 (0.97–1.22) 0.164 1.00 (0.97–1.04) 0.954 
rs9854771 A/G 1.12 (1.08–1.18) Genotyped 1.06 (0.95–1.18) 0.276 0.97 (0.93–1.01) 0.107 
Pancreatic cancerRootGAME-ON/DRIVE
SNPReference/effect alleleOR (95% CI)TypeaOR (95% CI)POR (95% CI)P
rs10919791 G/A 1.27 (1.18–1.33) Genotyped 1.01 (0.86–1.18) 0.940 1.02 (0.97–1.06) 0.465 
rs11655237 C/T 1.26 (1.19–1.34) 0.96 0.97 (0.87–1.09) 0.643 1.09 (1.02–1.16) 0.007b 
rs12413624 A/T 1.23 (1.16–1.31) 0.99 0.99 (0.85–1.15) 0.902 1.03 (1.00–1.08) 0.051 
rs1486134 T/G 1.14 (1.09–1.19) Genotyped 1.02 (0.90–1.16) 0.719 0.99 (0.95–1.03) 0.538 
rs1547374 G/A 1.27 (1.19–1.35) Genotyped 1.01 (0.92–1.11) 0.833 1.01 (0.97–1.04) 0.767 
rs16986825 C/T 1.18 (1.12–1.25) Genotyped 0.98 (0.76–1.26) 0.848 1.00 (0.96–1.05) 0.997 
rs17688601 A/C 1.14 (1.09–1.19) Genotyped 0.93 (0.74–1.15) 0.479 1.01 (0.97–1.05) 0.512 
rs2736098 T/C 1.25 (1.18–1.32) 0.95 1.09 (0.92–1.28) 0.330 1.05 (1.01–1.11) 0.022b 
rs31490 A/G 1.20 (1.14–1.27) Genotyped 1.12 (1.02–1.23) 0.020b 0.99 (0.95–1.02) 0.491 
rs372883 C/T 1.27 (1.19–1.33) Genotyped 1.00 (0.91–1.10) 0.988 1.00 (0.96–1.03) 0.899 
rs3790844 A/G 1.30 (1.19–1.41) Genotyped 1.03 (0.89–1.20) 0.703 1.01 (0.97–1.05) 0.675 
rs401681 C/T 1.20 (1.13–1.28) 1.00 0.89 (0.81–0.98) 0.018b 1.01 (0.98–1.05) 0.416 
rs505922 T/C 1.27 (1.19–1.35) 1.00 1.04 (0.94–1.14) 0.458 0.96 (0.93–1.00) 0.032b 
rs5768709 A/G 1.25 (1.17–1.34) 0.98 0.98 (0.89–1.09) 0.738 0.99 (0.95–1.03) 0.624 
rs687289 G/A 1.27 (1.20–1.35) Genotyped 1.06 (0.96–1.16) 0.264 0.96 (0.93–0.99) 0.021b 
rs6971499 C/T 1.27 (1.19–1.35) Genotyped 0.99 (0.87–1.14) 0.927 1.02 (0.96–1.08) 0.537 
rs7190458 G/A 1.46 (1.30–1.65) 0.91 0.93 (0.83–1.04) 0.179 1.05 (0.97–1.15) 0.225 
rs9543325 T/C 1.24 (1.16–1.32) Genotyped 1.05 (0.89–1.25) 0.529 0.99 (0.96–1.03) 0.684 
rs9554197 C/T 1.14 (1.10–1.19) Genotyped 1.03 (0.91–1.17) 0.606 1.00 (0.97–1.03) 0.986 
rs9573163 C/G 1.26 (1.18–1.34) 0.99 0.90 (0.79–1.04) 0.157 1.01 (0.97–1.04) 0.741 
rs9581943 G/A 1.15 (1.10–1.20) Genotyped 1.03 (0.87–1.22) 0.705 — — 
rs962856 T/C 1.12 (1.08–1.17) Genotyped 1.09 (0.97–1.22) 0.164 1.00 (0.97–1.04) 0.954 
rs9854771 A/G 1.12 (1.08–1.18) Genotyped 1.06 (0.95–1.18) 0.276 0.97 (0.93–1.01) 0.107 

aNumbers indicate the imputation scores.

bThe P values are significant at nominal level (<0.05), but turn out to be nonsignificant after multiple correction.

For Root GWAS, one SD change [0.571] in the PRS was not significantly associated with breast cancer. The ORs for developing breast cancer by percentiles of the PRS, relative to women in the middle quintile, showed no linear trend (Table 2). The discriminative accuracy of the pancreatic cancer PRS, as measured by the C-statistic, was 0.508 (95% CI, 0.489–0.526) for breast cancer.

Table 2.

Performance of PRS based on pancreatic cancer susceptibility variants in the GWAS of breast cancer in the African diaspora

Percentile of PRSCases (n = 1,657)Controls (n = 2,029)ORa (95% CI)
<5 165 204 0.99 (0.76–1.27) 
5–10 168 200 1.02 (0.79–1.32) 
10–20 155 214 0.85 (0.66–1.10) 
20–40 158 211 0.88 (0.68–1.13) 
40–60 336 400 1.00 (ref) 
60–80 171 199 1.00 (0.78–1.29) 
80–90 166 201 0.98 (0.76–1.27) 
90–95 173 197 1.01 (0.78–1.30) 
>95 165 203 0.97 (0.75–1.25) 
Continuous (per SD = 0.571) — — 1.01 (0.95–1.08) 
Percentile of PRSCases (n = 1,657)Controls (n = 2,029)ORa (95% CI)
<5 165 204 0.99 (0.76–1.27) 
5–10 168 200 1.02 (0.79–1.32) 
10–20 155 214 0.85 (0.66–1.10) 
20–40 158 211 0.88 (0.68–1.13) 
40–60 336 400 1.00 (ref) 
60–80 171 199 1.00 (0.78–1.29) 
80–90 166 201 0.98 (0.76–1.27) 
90–95 173 197 1.01 (0.78–1.30) 
>95 165 203 0.97 (0.75–1.25) 
Continuous (per SD = 0.571) — — 1.01 (0.95–1.08) 

aORs are for different percentiles of the polygenic PRS relative to the middle quintile (40%–60%) and were adjusted for age, study site, and the first four eigenvectors from principal components analysis.

We found that known GWAS risk variants for pancreatic cancer do not have a significant association with breast cancer risk among women of African or European ancestry. It is also worth noting that the direction in the associations for half of the nominal significant SNPs was not consistent with those observed in the pancreatic cancer studies that identified these SNPs as risk factors (Table 1). Our result is consistent with a recently published study using cancer-specific GWAS summary statistics data based on subjects of European ancestry, which did not find significant genetic correlations between pancreatic and breast cancer (genetic correlation coefficient = 0.17, P = 0.37; ref. 7). In conclusion, the association between known GWAS-identified pancreatic cancer susceptibility variants and breast cancer risk is likely weak in women of African or European ancestry, if it does exist.

No potential conflicts of interest were disclosed.

Conception and design: S. Wang, Y. Zheng

Development of methodology: S. Wang

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): Y. Zheng, T.O. Ogundiran, O. Ojengbede, W. Zheng, K.L. Nathanson, B. Nemesure, S. Ambs, D. Huo

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): S. Wang, Y. Zheng, D. Huo

Writing, review, and/or revision of the manuscript: S. Wang, Y. Zheng, T.O. Ogundiran, O. Ojengbede, W. Zheng, K.L. Nathanson, B. Nemesure, S. Ambs, O.I. Olopade, D. Huo

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): O. Ojengbede

Study supervision: O. Ojengbede, O.I. Olopade, D. Huo

O.I. Olopade received the following grants: NCI CA089085, CA142996, and CA161032; Susan G. Komen for the Cure SAC110026; American Cancer Society CRP-10-119-01-CCE; Ralph and Marion Falk Medical Research Trust; Breast Cancer Research Foundation; and Avon Foundation. D. Huo received American Cancer Society MRSG-13-063-01-TBG, Breast Cancer Research Foundation, and NCI CA161032. S. Ambs received NCI intramural grant ZIA BC 010887.

The authors thank all the women who participated in this research.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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