Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2019 Jun 1.
Published in final edited form as: Pharmacogenet Genomics. 2018 Jun;28(6):147–152. doi: 10.1097/FPC.0000000000000337

Germline genome-wide association studies in women receiving neoadjuvant chemotherapy with or without bevacizumab

James N Ingle 1,*, Krishna R Kalari 2,*, D Lawrence Wickerham 3,4, Gunter von Minckwitz 5, Peter A Fasching 6, Yoichi Furukawa 7, Taisei Mushiroda 7, Matthew P Goetz 1, Poulami Barman 2, Erin E Carlson 2, Priya Rastogi 4,8, Joseph P Costantino 4,9, Junmei Cairns 10, Soonmyung Paik 4,11, Harry D Bear 4,12, Michiaki Kubo 7, Liewei Wang 10, Norman Wolmark 4,13, Richard M Weinshilboum 10
PMCID: PMC5965682  NIHMSID: NIHMS964008  PMID: 29768301

Abstract

Neoadjuvant chemotherapy (NAC) for breast cancer is widely employed and we performed genome-wide association studies (GWAS) to determine if germline genetic variability was associated with benefit in terms of pathological complete response (pCR), disease-free survival (DFS), and overall survival (OS) in patients entered on the NSABP B-40 NAC trial where patients were randomized to receive, or not, bevacizumab in addition to chemotherapy. Patient DNA samples were genotyped with the Illumina OmniExpress BeadChip. Replication was attempted with genotyping data from 1398 HER2-negative patients entered on the GeparQuinto NAC study in which patients were also randomized to receive, or not, bevacizumab in addition to chemotherapy. 920 women from B-40 were analyzed and 237 patients achieved a pCR. GWAS with three phenotypes (pCR, DFS, OS) revealed no SNPs that were genome-wide significant (i.e., p≤5E-08) signals; p-values for top SNPs were 2.04E-07, 5.61E-08, and 5.63E-08, respectively, and these SNPs were not significant in the GeparQuinto data. An ad hoc GWAS was performed in the patients randomized to bevacizumab (457 patients with 128 pCR) that showed signals on chromosome 6, located within a gene, CDKAL1, that approached, but did not reach, genome-wide significance (top SNP rs7453577, p=2.97E-07). However, this finding was significant when tested in the GeparQuinto dataset (p=0.04). In conclusion, we identified no SNPs significantly associated with NAC. The observation, in a hypothesis-generating GWAS, of a SNP in CDKAL1 associated with pCR in the bevacizumab arm of both B-40 and GeparQuinto requires further validation and study.

Keywords: neoadjuvant chemotherapy, bevacizumab, breast cancer, pharmacogenomics

Introduction

There is increasing use of neoadjuvant chemotherapy (NAC) in the management of early-stage breast cancer(1). Based on the importance of angiogenesis in breast cancer progression(2) and promising results from early studies of bevacizumab, a monoclonal antibody that blocks angiogenesis by inhibiting vascular endothelial growth factor A (VEGF-A), in metastatic breast cancer(3), multiple clinical trials in the neoadjuvant setting were conducted. Four of these trials have reported results, including NSBAP B-40(4, 5), GeparQuinto(6, 7), CALGB 40603(8), and the ARTemis trial(9).

Achievement of a pathological complete response (pCR), with complete eradication of invasive breast cancer in the breast and nodes, has been associated with improved survival with the greatest prognostic value in aggressive tumor subtypes(10). We hypothesized that there are genes related to the achievement of a pCR in women treated with NAC with or without bevacizumab, and that we would be able to identify germ-line genetic variation measured as single nucleotide polymorphisms (SNPs) associated with pCR with a genome-wide association study (GWAS) utilizing B-40(4) and attempting replication with HER2-negative patients entered on GeparQuinto(6).

Methods

Source of Patients

All patients with HER2-negative early breast cancer entered on NSABP B-40 (schema: Supplementary Figure 1) with a blood sample for DNA extraction and consent for genetic testing were eligible following Mayo IRB review.

Definition of Phenotype

The pCR definition was the complete eradication of all invasive breast cancer in both the breast and regional nodes.

Study Design

Anonymized samples were sent to Mayo Clinic for DNA extraction, were plated, and sent to the RIKEN Center for Integrative Medical Science for genotyping. The clinical and genotyping data were then analyzed at Mayo Clinic. The primary objective was to identify genetic variation measured as SNPs associated with pCR with a GWAS. Secondary objectives were to explore the association of SNPs with outcomes, i.e., disease-free survival (DFS) and overall survival (OS). An ad hoc exploratory GWAS was performed with the phenotype of pCR in patients randomized to bevacizumab.

Genotyping, quality control, and imputation

Genotyping was performed with the Illumina HumanOmniExpressExome BeadChips. Details regarding genotyping, quality control, and imputation are given the Supplementary Material.

The data from this GWAS have been deposited in the Data Base of Genotypes and Phenotypes (dbGaP). The dbGaP Study Accession Number is phs001365.v1.p1 and the URL is https://www.ncbi.nlm.nih.gov/projects/gapprev/gap/cgi-bin/preview1.cgi?GAP_phs_code=DlBPhGnsRxXYbJZW.

Statistical analysis

The primary analyses were based on logistic regression with SNP genotypes analyzed as log-additive effects on the chance of a pCR. The primary covariates that were adjusted for include treatment arm and any other clinical factors found to be associated with pCR (at p-value < 0.10). To control for potential population stratification, we used the program STRUCTURE and HapMap racial groups to determine additional covariates. We utilized EigenStrat to determine the eigen values for the SNP correlation matrix that statistically differed from zero(11, 12). To evaluate the association of SNPs with DFS and OS, we used the Cox proportional hazards model, including covariates to adjust for patient heterogeneity.

Replication

Replication of top SNPs from the four GWAS (pCR, DFS, OS, and pCR in bevacizumab patients) was attempted utilizing genotyping data from patients with HER2-negative early breast cancer entered on GeparQuinto (schema: Supplementary Figure 2, Supplementary Table). Details regarding genotyping, quality control, imputation, and sample cohorts for individual GWAS of GeparQuinto are given in the Supplementary Material.

Results

Patients studied

The participant flow diagram (Supplementary Figure 3) shows the B-40 patients included and excluded from the four GWAS with the phenotypes of 1) pCR, 2) DFS, 3) OS, and 4) pCR in bevacizumab-treated patients only. Supplementary Figure 4 shows the GeparQuinto patients included in the replication studies.

GWAS with phenotype of PCR

Table 1 shows the clinical summary of the 914 patients in the primary analysis. The analysis was adjusted for treatment (bevacizumab, no bevacizumab), race, completion of neoadjuvant chemotherapy, and tumor grade in addition to being stratified for categorical-age, ER/PR status, tumor size and nodal stage. The distribution of p-values is shown in the Manhattan plot (Figure 1A) and locus zoom (Supplementary Figure 5A) and revealed the top SNP (rs34843881, imputed) on chromosome 13 to have a p-value of 2.04E-07, which did not reach genome-wide statistical significance (Table 2). The Quantile-Quantile (QQ) plot for the conditional logistic regression results is shown in Supplementary Figure 6A. The top SNP was examined in GeparQuinto and showed p=0.73 (Table 2), indicating this was not an important signal.

Table 1.

NSABP B-40 Clinical Summary

No Bevacizumab (N=459) Bevacizumab (N=455) Total (N=914)
Age at Randomization
 Median 49.0 48.0 49.0
 Q1, Q3 41.0, 56.0 42.0, 56.0 41.0, 56.0
 Range (25.0–70.0) (24.0–71.0) (24.0–71.0)
pCR Breast and Nodes
 No 350 (76.3%) 328 (72.1%) 678 (74.2%)
 Yes 109 (23.7%) 127 (27.9%) 236 (25.8%)
Gemcitabine
 No 314 (68.4%) 305 (67.0%) 619 (67.7%)
 Yes 145 (31.6%) 150 (33.0%) 295 (32.3%)
Capecitabine
 No 303 (66.0%) 301 (66.2%) 604 (66.1%)
 Yes 156 (34.0%) 154 (33.8%) 310 (33.9%)
Bevacizumab
 No 459 (100.0%) 0 (0.0%) 459 (50.2%)
 Yes 0 (0.0%) 455 (100.0%) 455 (49.8%)
Clinical Tumor Status
 2–4cm 212 (46.2%) 202 (44.4%) 414 (45.3%)
 >4cm 247 (53.8%) 253 (55.6%) 500 (54.7%)
Clinical Nodal Status
 Negative 243 (52.9%) 251 (55.2%) 494 (54.0%)
 Positive 216 (47.1%) 204 (44.8%) 420 (46.0%)
Hormone Receptor Status
 Negative 197 (42.9%) 193 (42.4%) 390 (42.7%)
 Positive 262 (57.1%) 262 (57.6%) 524 (57.3%)
Estrogen Receptor/Progesterone Receptor
 Negative/Negative 197 (43.2%) 193 (42.4%) 390 (42.8%)
 Negative/Positive 8 (1.8%) 9 (2.0%) 17 (1.9%)
 Positive/Negative 40 (8.8%) 47 (10.3%) 87 (9.5%)
 Positive/Positive 211 (46.3%) 206 (45.3%) 417 (45.8%)
 Positive/unknown 3 (0.6%) 0 3 (0.3%)
Histologic Tumor Grade
 Well 33 (7.2%) 30 (6.6%) 63 (6.9%)
 Moderate 149 (32.5%) 160 (35.2%) 309 (33.8%)
 Poor 269 (58.6%) 261 (57.4%) 530 (58.0%)
 Unknown 8 (1.7%) 4 (0.9%) 12 (1.3%)
Breast
 Left 227 (49.5%) 226 (49.7%) 453 (49.6%)
 Right 232 (50.5%) 229 (50.3%) 461 (50.4%)
Completion of Neoadjuvant Treatment Protocol
 Yes 372 (81.0%) 353 (77.6%) 725 (79.3%)
 No 87 (19.0%) 102 (22.4%) 189 (20.7%)
structure_race
 AA 69 (15.0%) 51 (11.2%) 120 (13.1%)
 CA 352 (76.7%) 377 (82.9%) 729 (79.8%)
 HC 13 (2.8%) 4 (0.9%) 17 (1.9%)
 UN 25 (5.4%) 23 (5.1%) 48 (5.3%)

Figure 1.

Figure 1

Manhattan plots of p-values for conditional logistic regression analysis of the NSABP B-40 trial for A) pathologic complete response (pCR), B) disease-free survival, C) overall survival, and D) pCR in bevacizumab-treated patients only.

Table 2.

Top SNP from the GWAS for pCR, DFS, OS, and bevacizumab-treated patients with replication utilizing GeparQuinto

B40 GeparQuinto
rsID CHR POS CA MA N MAF OR lci uci pvalue N MAF OR lci uci Pvalue
pCR rs34843881 13 25971560 C T 914 0.096 2.899 1.940 4.331 2.04E−07 1398 0.095 0.937 0.650 1.352 0.73
DFS rs78269823 14 39264849 C T 890 0.067 0.197 0.093 0.416 5.61E−08 1398 0.117 0.952 0.688 1.316 0.76
OS rs56330643 14 100388910 A G 891 0.297 2.050 1.588 2.645 5.63E−08 1398 0.357 0.926 0.738 1.161 0.50
Bev, pCR rs7453577 6 20987675 G A 447 0.203 2.734 1.861 4.016 2.97E−07 733 0.209 1.498 1.029 2.182 0.04

rsID: reference sequence ID,

GWAS with phenotype of disease-free survival

The GWAS with the phenotype of DFS was performed with 890 patients since 24 of the 914 patients were removed due to missing outcome data and/or tumor grade. A DFS event occurred in 219 (24.6%) of the patients. Stepwise analysis showed clinical variables such as treatment, tumor grade, and completion of neoadjuvant chemotherapy were associated with DFS and these variables were controlled for in the analysis, in addition to race. The Manhattan plot (Figure 1B) and locus zoom (Supplementary Figure 5B) revealed the top SNP (rs78269823, imputed) on chromosome 14 to have a p-value of 5.61E-08, which approached but did not reach genome-wide significance. The QQ plot is shown in Supplementary Figure 6B. The top SNP was examined in GeparQuinto and showed p=0.76 (Table 2), indicating this was not an important signal.

GWAS with phenotype of overall survival

The GWAS with the phenotype of OS was performed with 891 patients of whom 144(16.1%) had died. The model was controlled by the same variables as for DFS. The Manhattan plot (Figure 1C) and locus zoom (Supplementary Figure 5C) revealed the top SNP (rs56330643, imputed) on chromosome 14 to have a p-value of 5.63E-08, which approached but did not reach genome-wide significance. The QQ-plot is shown in Supplementary Figure 6C). The top SNP was examined in GeparQuinto and showed p=0.50 (Table 2), indicating this was not an important signal.

Exploratory GWAS in patients who received bevacizumab

The GWAS with the phenotype of pCR was performed with 447 patients who had received bevacizumab of whom 147 (32.8%) had achieved a pCR. The model was controlled for the stratification variables noted above, race, and tumor grade. The Manhattan plot (Figure 1D) and locus zoom (Supplementary Figure 5D) revealed the top SNP, (rs7453577, imputed) to have a p-value of 2.97E-07. The QQ plot is shown in Supplementary Figure 6D. The top SNP was examined in GeparQuinto and showed p=0.04 (Table 2), which achieved statistical significance.

Given the findings from GeparQuinto, we examined this area more closely. In the B-40 GWAS, there were a total of 17 SNPs in addition to the top SNP in a gene, CDKAL1 (CDK5 Regulatory Subunit Associated Protein 1 Like 1), with p-values ranging from 3.11E-07 to 8.63E-07. Included in these SNPs was a single genotyped SNP, rs1004172, with p=3.73E-07. The MAFs of these SNPs were 0.19–0.22.

Discussion

The primary objective of this study was to identify any association between germ-line genetic variation and pCR in women receiving NAC in B-40. The top SNP (rs34843881) did not achieve genome-wide significance (p=2.04 E-07). When this SNP was examined in GeparQuinto database there was no evidence of any association (p=0.73).

Secondary objectives were to identify any association between germ-line genetic variation and the outcomes of DFS and OS in women receiving NAC. The top SNPs from B-40 almost reached genome-wide significance, p-value accepted to be 5E-08, i.e., 5.61E-08 and 5.63E-08, respectively. However, when examined in GeparQuinto, the p-values were not replicated, being p=0.76 and p=0.50, respectively.

Because those studies reported a significantly higher pCR rate in the patients randomized to bevacizumab, we performed an exploratory GWAS only in the patients who received bevacizumab. The top SNP (rs7453577) had a p-value of 2.97E-07 in B40 and when examined in GeparQuinto was significant (p=0.04). Given that this was an ad hoc analysis, it must be considered hypothesis generating. The top SNP was located in CDKAL1, which encodes a protein that is a member of the methylthiotransferase family. The function of this gene is not known, but prior GWAS have linked SNPs in an intron of CDKAL1 with susceptibility to type II diabetes(13).

Ideally, a replication study should be identical to a discovery study. Whereas B-40 and GeparQuinto have substantial similarities, they also have differences. The anthracycline utilized was different being doxorubicin in B-40 and epirubicin in GeparQuinto. The sequencing of the anthracycline and taxane was opposite and the duration of bevacizumab therapy was different in the two studies. Patients were taken off study if a response was not seen after the 4 cycles of the anthracycline plus cyclophosphamide in the GeparQuinto study. Also, in B-40, bevacizumab had a significantly higher pCR rate in ER-positive patients whereas in GeparQuinto the bevacizumab had a significantly higher pCR rate in ER-negative patients. These differences demonstrate that in pharmacogenomics, the identification of an ideal replication study can be difficult.

Conclusions

We performed GWAS in a major NAC study and did not find a significant association between germ-line genetic variation and pCR, DFS, or OS. The observation of a SNP in CDKAL1 associated with pCR in the bevacizumab arm of both B40 and GeparQuinto requires further validation and study.

Supplementary Material

Supplementary Figure 1
Supplementary Figure 2
Supplementary Figure 3
Supplementary Figure 4
Supplementary Figure 5
Supplementary Figure 6
Supplementary Material

Acknowledgments

Financial support: These studies were supported in part by NIH grants U19 GM61388 (The Pharmacogenomics Research Network), P50CA116201 (Mayo Clinic Breast Cancer Specialized Program of Research Excellence), U24CA114732, and the RIKEN Center for Integrative Medical Science and the Biobank Japan Project funded by the Ministry of Education, Culture, Sports, Science and Technology, Japan. The B-40 clinical trial was supported by National Cancer Institute, Department of Health and Human Services, Public Health Service Grants: U10CA108068, U10CA180822, UG1CA189867, and U24CA1966067 (NRG Oncology); NCI-44066-26 (AR); Genentech, Inc., a full member of the Roche Group of companies; Roche Laboratories Inc.; and Lilly Research Laboratories, a division of Eli Lilly & Company.

Footnotes

Conflict of interest: none declared

References

  • 1.Coates AS, Winer EP, Goldhirsch A, Gelber RD, Gnant M, Piccart-Gebhart M, et al. Tailoring therapies-improving the management of early breast cancer: St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2015. Ann Oncol. 2015;26:1533–46. doi: 10.1093/annonc/mdv221. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Weidner N, Semple JP, Welch WR, Folkman J. Tumor angiogenesis and metastasis--correlation in invasive breast carcinoma. N Engl J Med. 1991;324:1–8. doi: 10.1056/NEJM199101033240101. [DOI] [PubMed] [Google Scholar]
  • 3.Miller K, Wang M, Gralow J, Dickler M, Cobleigh M, Perez EA, et al. Paclitaxel plus bevacizumab versus paclitaxel alone for metastatic breast cancer. N Engl J Med. 2007;357:2666–76. doi: 10.1056/NEJMoa072113. [DOI] [PubMed] [Google Scholar]
  • 4.Bear HD, Tang G, Rastogi P, Geyer CE, Jr, Robidoux A, Atkins JN, et al. Bevacizumab added to neoadjuvant chemotherapy for breast cancer. N Engl J Med. 2012;366:310–20. doi: 10.1056/NEJMoa1111097. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Bear HD, Tang G, Rastogi P, Geyer CE, Jr, Liu Q, Robidoux A, et al. Neoadjuvant plus adjuvant bevacizumab in early breast cancer (NSABP B-40 [NRG Oncology]): secondary outcomes of a phase 3, randomised controlled trial. Lancet Oncol. 2015;16:1037–48. doi: 10.1016/S1470-2045(15)00041-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.von Minckwitz G, Eidtmann H, Rezai M, Fasching PA, Tesch H, Eggemann H, et al. Neoadjuvant chemotherapy and bevacizumab for HER2-negative breast cancer. N Engl J Med. 2012;366:299–309. doi: 10.1056/NEJMoa1111065. [DOI] [PubMed] [Google Scholar]
  • 7.von Minckwitz G, Loibl S, Untch M, Eidtmann H, Rezai M, Fasching PA, et al. Survival after neoadjuvant chemotherapy with or without bevacizumab or everolimus for HER2-negative primary breast cancer (GBG 44-GeparQuinto)dagger. Annals of oncology : official journal of the European Society for Medical Oncology. 2014;25:2363–72. doi: 10.1093/annonc/mdu455. [DOI] [PubMed] [Google Scholar]
  • 8.Sikov WM, Berry DA, Perou CM, Singh B, Cirrincione CT, Tolaney SM, et al. Impact of the addition of carboplatin and/or bevacizumab to neoadjuvant once-per-week paclitaxel followed by dose-dense doxorubicin and cyclophosphamide on pathologic complete response rates in stage II to III triple-negative breast cancer: CALGB 40603 (Alliance) J Clin Oncol. 2015;33:13–21. doi: 10.1200/JCO.2014.57.0572. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Earl HM, Hiller L, Dunn JA, Blenkinsop C, Grybowicz L, Vallier AL, et al. Efficacy of neoadjuvant bevacizumab added to docetaxel followed by fluorouracil, epirubicin, and cyclophosphamide, for women with HER2-negative early breast cancer (ARTemis): an open-label, randomised, phase 3 trial. Lancet Oncol. 2015;16:656–66. doi: 10.1016/S1470-2045(15)70137-3. [DOI] [PubMed] [Google Scholar]
  • 10.Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet. 2014;384:164–72. doi: 10.1016/S0140-6736(13)62422-8. [DOI] [PubMed] [Google Scholar]
  • 11.Patterson N, Price AL, Reich D. Population structure and eigenanalysis. PLoS Genet. 2006;2:e190. doi: 10.1371/journal.pgen.0020190. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–9. doi: 10.1038/ng1847. [DOI] [PubMed] [Google Scholar]
  • 13.Palmer CJ, Bruckner RJ, Paulo JA, Kazak L, Long JZ, Mina AI, et al. Cdkal1, a type 2 diabetes susceptibility gene, regulates mitochondrial function in adipose tissue. Mol Metab. 2017;6:1212–25. doi: 10.1016/j.molmet.2017.07.013. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Figure 1
Supplementary Figure 2
Supplementary Figure 3
Supplementary Figure 4
Supplementary Figure 5
Supplementary Figure 6
Supplementary Material

RESOURCES