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Erschienen in: Breast Cancer Research 1/2016

Open Access 01.12.2016 | Research article

Insulin-like growth factor 1 receptor expression and IGF1R 3129G > T polymorphism are associated with response to neoadjuvant chemotherapy in breast cancer patients: results from the NEOZOTAC trial (BOOG 2010-01)

verfasst von: Stefanie de Groot, Ayoub Charehbili, Hanneke W. M. van Laarhoven, Antien L. Mooyaart, N. Geeske Dekker-Ensink, Saskia van de Ven, Laura G. M. Janssen, Jesse J. Swen, Vincent T. H. B. M. Smit, Joan B. Heijns, Lonneke W. Kessels, Tahar van der Straaten, Stefan Böhringer, Hans Gelderblom, Jacobus J. M. van der Hoeven, Henk-Jan Guchelaar, Hanno Pijl, Judith R. Kroep, on behalf of the Dutch Breast Cancer Research Group

Erschienen in: Breast Cancer Research | Ausgabe 1/2016

Abstract

Background

The insulin-like growth factor 1 (IGF-1) pathway is involved in cell growth and proliferation and is associated with tumorigenesis and therapy resistance. This study aims to elucidate whether variation in the IGF-1 pathway is predictive for pathologic response in early HER2 negative breast cancer (BC) patients, taking part in the phase III NEOZOTAC trial, randomizing between 6 cycles of neoadjuvant TAC chemotherapy with or without zoledronic acid.

Methods

Formalin-fixed paraffin-embedded tissue samples of pre-chemotherapy biopsies and operation specimens were collected for analysis of IGF-1 receptor (IGF-1R) expression (n = 216) and for analysis of 8 candidate single nucleotide polymorphisms (SNPs) in genes of the IGF-1 pathway (n = 184) using OpenArray® RealTime PCR. Associations with patient and tumor characteristics and chemotherapy response according to Miller and Payne pathologic response were performed using chi-square and regression analysis.

Results

During chemotherapy, a significant number of tumors (47.2 %) showed a decrease in IGF-1R expression, while in a small number of tumors an upregulation was seen (15.1 %). IGF-1R expression before treatment was not associated with pathological response, however, absence of IGF-1R expression after treatment was associated with a better response in multivariate analysis (P = 0.006) and patients with a decrease in expression during treatment showed a better response to chemotherapy as well (P = 0.020). Moreover, the variant T allele of 3129G > T in IGF1R (rs2016347) was associated with a better pathological response in multivariate analysis (P = 0.032).

Conclusions

Absent or diminished expression of IGF-1R after neoadjuvant chemotherapy was associated with a better pathological response. Additionally, we found a SNP (rs2016347) in IGF1R as a potential predictive marker for chemotherapy efficacy in BC patients treated with TAC.

Trial registration

ClinicalTrials.gov NCT01099436. Registered April 6, 2010.
Hinweise

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

Conception and design: SdG, AC, HWMvL, SvdV, LGMJ, HG, H-JG, HP, and JRK. Study coordination: AC, SvdV, JRK, and Dutch breast cancer group. Development of experiments: SdG, AC, HWMvL, ALM, NGD-E, LGMJ, TvdS, HP, and JRK. Acquisition of data: SdG, AC, HWMvL, ALM, NGD-E, LGMJ, VTHBMS, JBH, LWK, TvdS, and JRK. Analysis and interpretation of data: SdG, AC, ALM, LGMJ, JJS, TvdS, SB, JJMvH, H-JG, HP, and JRK. Study supervision: HG, JJMvdH, HP, and JRK. Writing of the manuscript: SdG, NGD-E, SB, HP, and JRK. All authors critically revised and approved the final manuscript and agree to be accountable for all aspects of the work.
Abkürzungen
AUC
Area under the curve
BC
Breast cancer
BSA
Bovine serum albumin
CART
Classification and regression tree
CI
Confidence interval
CTCAE
Common Terminology Criteria for Adverse Events
ER
Estrogen receptor
FFPE
Formalin-fixed paraffin-embedded
HR
Hormone receptor
IGF
Insulin-like growth factor
IGF-1R
Insulin-like growth factor 1 receptor
IGF-BP
Insulin-like growth factor binding protein
IHC
Immunohistochemistry
MAF
Minor allele frequency
MP
Miller and Payne
OR
Odds ratio
PBS
Phosphate-buffered saline
pCR
Pathological complete response
PR
Progesterone receptor
SNP
Single nucleotide polymorphism
TAC
Docetaxel, doxorubicin, and cyclophosphamide

Background

Insulin-like growth factor (IGF)-1 and other members of the IGF-1 pathway have been associated with development, progression, and metastasis of several cancers [1, 2]. Additionally, epidemiologic studies have shown a relation between high circulating IGF-1 levels, breast density [3], and risk of breast cancer (BC) [4]. Increased IGF-1 levels are associated with an elevated BC mortality [5] and with inherent resistance to anti-tumor treatments in preclinical models [69]. Furthermore, the IGF-1 receptor (IGF-1R), a transmembrane tyrosine kinase, is frequently upregulated in BC [10, 11]. The biological activity of IGF-1 and IGF-2 depends on binding with the insulin-like growth factor binding proteins (IGF-BPs), mainly IGF-BP3 [12, 13]. Both IGFs bind the IGF-1R and activate the Ras/mitogen-activated protein kinase (MAPK) and phosphatidylinositol-3-kinase (PI3K)/AKT pathways, through which cell proliferation is stimulated and apoptosis is inhibited, respectively [14, 15]. Additionally, the IGF-1R and the estrogen receptor (ER) have been shown to work synergistically, whereby activated ER binds to the promoter regions of IGF1R to promote transcription and IGF-1 is able to activate unliganded ER [16, 17].
Previous research has shown that low IGF-1R expression in the tumor is predictive for pathological complete response (pCR) in ER-positive tumors [10] and that upregulation of IGF-1R during chemotherapy predicts a poor outcome in a relative small, heterogeneous group of BC patients [18]. Moreover, genes encoding members of the IGF-1 pathway are known to harbor several single nucleotide polymorphisms (SNPs) that influence the activity of the pathway. SNPs associated with IGF-1 and IGF-BP3 plasma levels and breast density are described [19, 20] as well as SNPs associated with therapy resistance and outcome [21, 22].
Neoadjuvant chemotherapy has been demonstrated to be equivalent to adjuvant chemotherapy for BC survival. This treatment has the advantage of more frequent breast-conserving therapy [23] and offers the opportunity for translational research of molecular predictors of tumor response. Additionally, the Miller and Payne (MP) histological grading system can be used to assess response to neoadjuvant chemotherapy because it is associated with patients’ disease-free and overall survival [24, 25]. This study evaluates the expression of the IGF-1R of the tumor before and after neoadjuvant chemotherapy and whether it predicts pathological response according to MP classification after neoadjuvant chemotherapy in human epidermal growth factor receptor 2 (HER2)-negative early BC patients treated in the NEOZOTAC trial [26]. Moreover, we aim to identify SNPs, which have been described to influence the activity of the IGF-1 pathway, to predict chemotherapy efficacy in this cohort. In addition, these SNPs are tested for association with the occurrence of side effects.

Methods

Study population

From July 2010 until April 2012, 250 women participated in the multicenter phase III NEOZOTAC trial, randomizing between TAC chemotherapy (75 mg/m2 docetaxel, 50 mg/m2 doxorubicin, and 500 mg/m2 cyclophosphamide) with or without zoledronic acid (4 mg within 24 hours after chemotherapy). Eligible patients had a histologically confirmed diagnosis of HER2-negative stage II or III BC. Other inclusion and exclusion criteria have been described elsewhere [26]. Tumor regression was scored according to the MP classification [24]. pCR was defined as the absence of residual invasive cancer within the breast and lymph nodes [24]. Side effects and hematological toxicity were graded according to the Common Terminology Criteria for Adverse Events version 4.0 (CTCAE v.4.0) [27]. All patients gave written informed consent. The study was conducted in accordance with the Declaration of Helsinki (2008) and approved by the Ethics Committee of the Leiden University Medical Center in agreement with the Dutch law for medical research involving humans.

Immunohistochemistry

Formalin-fixed paraffin-embedded (FFPE) tumor tissue samples of prechemotherapy biopsies and operation specimens were collected for analysis of IGF-1R expression using immunohistochemistry (IHC). From each FFPE tumor tissue sample, one section of 4 μm was cut and deparaffinized with xylene, rehydrated through graded alcohol, and rinsed in distilled water. After blocking of endogenous peroxidase activity with 0.3 % H2O2 for 20 minutes, heat-induced antigen retrieval was performed in the EnVision™ Flex Target Retrieval Solution in PT Link (Dako, Glostrup, Denmark) at low pH. After blocking with 5 % normal goat serum to reduce aspecific binding by the primary antibody, the sections were incubated overnight at room temperature in a humidified chamber with the IGF-1R antibody (IGF-1 receptor β, D4O6W, rabbit monoclonal; Cell Signaling Technology, Danvers, MA, USA) diluted in phosphate-buffered saline (PBS)/bovine serum albumin (BSA) 1 % at a dilution of 1:200. After the primary antibody incubation, the sections were washed with PBS and incubated with a secondary anti-rabbit antibody EnVision™ (Dako, Glostrup, Denmark) for 30 minutes and visualized using liquid DAB+ (Dako, Glostrup, Denmark). Eventually, sections were counterstained with Mayer’s hematoxylin, dehydrated, and subsequently permanently mounted with Pertex (Histolab, Gothenburg, Sweden). Breast and placenta sections that had previously been identified to express the IGF-1R were used as positive controls, and sections that underwent the IHC staining procedure without application of primary antibodies served as negative controls. Membranous IGF-1R expression was scored on a scale of 0–3+ (see Fig. 1). Samples were considered negative if 0 or 1+ was scored, and positive if 2+ and 3+ was given. The staining was scored by two independent researchers (SdG and ALM).

SNP selection

To select relevant SNPs in the IGF-1 pathway, a PubMed search with the keywords “IGF-1”, “IGF-2”, “IGF-BP3”, “IGF-1R”, “single nucleotide polymorphism”, “breast cancer”, and/or “clinical outcome” was conducted in July 2013. SNPs that were associated with IGF-1 or IGF-BP3 plasma levels, BC risk, or clinical outcome in cancer patients treated with chemotherapy, were selected. SNPs with a minor allele frequency (MAF) >0.01 in a Caucasian population according to the HapMap project database and with a potential functionality according to the literature review or using national institutes of health functionality database were selected [28]. To minimize the number of tested associations, tagging SNPs were selected for SNPs that were in linkage disequilibrium (r 2 > 0.7). The selected SNPs in the IGF1, IGF2, IGFBP3, and IGF1R genes are summarized in Table 1.
Table 1
Selected SNPs in IGF-1 pathway
RS number
Gene
Alleles (major > minor)
Position in gene and functionality
Clinical influence of polymorphism
rs10735380
IGF1
A > G
Transcription factor binding site, intronic
Variant G allele associated with increased serum IGF-1 level [20, 35, 41]
rs1520220
IGF1
C > G
Intronic
Variant G allele associated with increased serum IGF-1 level [35, 42] and BC risk [42].
rs6220
IGF1
A > G
3′-untranslated region, microRNA binding site
Variant G allele associated with increased serum IGF-1 level and increased BC risk [42]
rs2946834
IGF1
G > A
3′-untranslated region
Variant A allele associated with increased serum IGF-1 level [35, 42] and with worse outcome in BC [21]
rs2270628
IGFBP3
C > T
Downstream
Variant T allele associated with decreased serum IGF-BP3 level [20, 35, 36]
rs2854746
IGFBP3
G > C
Nonsynonymous in exon 1
Variant C allele associated with increased serum IGF-BP3 level [20, 35, 36, 43] and with better outcome in advanced gastric cancer treated with CT [44]
(Ala32Gly)
rs4320932
IGF2
T > C
Transcription factor binding site, intronic
Variant C allele associated with worse outcome in ovarian cancer and worse response to CT [45]
rs2016347
IGF1R
G > T
3′-untranslated region, microRNA binding site
Variant T allele associated with better outcome in ER+ BC [22]
SNPs selected on basis of literature research and the clinical influence. rs reference SNP number, BC breast cancer, CT chemotherapy, ER estrogen receptor, IGF insulin-like growth factor, IGFBP3 insulin-like growth factor binding protein 3, IGF1R insulin-like growth factor 1 receptor, SNP single nucleotide polymorphism

DNA isolation and preamplification

DNA was extracted from FFPE tissue samples. Preferentially, tissue from tumor-negative breast tissue and tumor-negative lymph nodes was used (N = 95); however, when this was unavailable or unclear from the pathology report tissue from tumor-containing blocks was used. Three sections of 4 μm were incubated overnight at 50 °C in 500 μl lysis buffer (NH4Cl 8.4 g/l, KHCO3 1.0 g/l, proteinase K 0.25 mg/ml). Next, 300 μl was taken to extract DNA using the Maxwell forensic DNA isolation kit (Promega, Leiden, the Netherlands) according to the manufacturer’s protocol. DNA isolated from FFPE tissue is cross-linked and fragmented into pieces with a length of a few hundred base pairs. To make DNA isolated from FFPE tissue more suitable for genotyping, preamplification was accomplished for enrichment of the target DNA [29]. The preamplification step consisted of a PCR reaction with eight diluted TaqMan assays (LifeTechnologies, Nieuwerkerk aan den IJssel, the Netherlands) and was performed using the following protocol; to 2.5 μl DNA, 1 μl of a dilution of eight TaqMan assays (pooled at a final concentration of 0.2×) and 3.5 μl HotStarTaq DNA polymerase was added and amplified on a conventional PCR machine. The following PCR conditions were used; 10 minutes at 95 °C followed by 18 cycles each consisting of 15 seconds at 95 °C and 4 minutes at 60 °C. The mixture was diluted 15 times and 2 μl was used for real-time PCR analysis. The selected SNPs were analyzed using TaqMan OpenArray® technology (Life Technologies); however, in case of low call rate, missing samples were reanalyzed separately using the Viia7 RealTime PCR system (Life Technologies).

Statistical analysis

Possible associations between parameters were analyzed using Pearson’s chi-square test and logistic regression. Univariate and multivariate odds ratios (ORs), 95 % confidence intervals (CIs), and P values were derived from logistic regressions. IGF-1R expression and clinical variables, which have been reported to be associated with pCR, were tested in univariate analysis (e.g., hormone receptor (HR) status and clinical T status). The association between IGF-1R expression and MP classification were tested using a logistic ordinal regression where MP classification groups were treated as ordered. In multivariate analyses, parameters were adjusted for covariates with P <0.1. We also reanalyzed the latter model using linear regression to check for linearity of relationship between IGF-1R expression and MP classification.
Genotype distributions were tested for adherence to Hardy–Weinberg equilibrium and SNPs significant at the 0.05 level after Bonferroni correction were excluded from the analysis. Genotypes found to be (borderline) significant in the univariate logistic regression models were carried forward to the multivariate model, adjusting for covariates with P < 0.1. To correct for multiple testing, a global score test including all SNPs was performed [30]. The score test assumes that the regression coefficients of the SNPs are normally distributed and tests whether the variance of this distribution is bigger than zero. In that case at least one regression coefficient has to be unequal to zero. To investigate the individual, relative contribution of SNPs, a classification and regression tree (CART) was computed (Statistical Package for Social Sciences (SPSS): classify, tree; (IBM Corp., Armonk, NY, USA)). A receiver operating characteristic curve and the area under the curve (AUC) were computed for the predicted probabilities of the CART. The global P value was computed using the package globaltest in R version 3.1.3 (The R Foundation for Statistical Computing, Institute for Statistics and Mathematics, Vienna, Austria). All other analyses were computed using SPSS software™ 20.0 (IBM Corp.). A significance level of 0.05 was used for all tests.

Results

Patient characteristics

Patients of both study arms, chemotherapy with or without zoledronic acid, were included in this study, as no differences were found between both arms regarding pathological response [26]. FFPE tissue was available from 216 (86.4 %) of 250 patients. Clinical characteristics of the 216 patients are presented in Table 2, which are comparable with the characteristics of the entire cohort of the NEOZOTAC trial [26]. Almost 12 % of the patients had a pCR.
Table 2
Patient characteristics
 
Patients (N = 216) in NEOZOTAC
Median age, years (range)
 
49.5 (28–70)
Median BMI, kg/m2 (range)
 
26.2 (18.3–42.0)
Clinical T stage
cT1 or cT2
123 (56.9 %)
 
cT3 or cT4
93 (43.1 %)
Clinical N stage
cN0
101 (46.8 %)
 
cN+
115 (53.2 %)
Tumor type
Ductal
128 (59.3 %)
 
Lobular
38 (17.6 %)
 
Other
18 (8.4 %)
 
Unknown
32 (14.8 %)
HR status
ER+ and/or PR+
180 (83.3 %)
 
ER– and PR–
36 (16.7 %)
Allocated treatment
TAC
109 (50.5 %)
 
TAC + ZA
107 (49.5 %)
pCR breast and LN
Yes
25 (11.6 %)
 
No
184 (85.2 %)
 
Unknown
7 (3.2 %)
MP breast
1
33 (15.3 %)
 
2
56 (25.9 %)
 
3
41 (19.0 %)
 
4
42 (19.4 %)
 
5
35 (16.2 %)
 
Unknown
9 (4.2 %)
BMI body mass index, ER estrogen receptor, HR hormone receptor, LN lymph nodes, MP Miller and Payne, pCR pathologic complete response, PR progesterone receptor, TAC docetaxel, doxorubicin, and cyclophosphamide, ZA zoledronic acid

IGF-1R expression

FFPE breast tumor tissue from 216 patients was available for analyzing at least one condition (biopsy and/or operation specimen), while both samples were available for 106 cases. Data of available tissue are summarized in the consort diagram (Fig. 2). Representative tissue examples with different scoring values can be found in Fig. 1. High IGF-1R expression in the prechemotherapy biopsy was associated with ER expression (P = 0.001) and the progesterone receptor (PR) expression (P = 0.035). ER and/or PR-positive tumors showed positive IGF-1R on the membrane in 78.0 % of the cases, while triple-negative tumors showed positivity for IGF-1R in only 50.0 % of the cases.
During chemotherapy, a significant subset (47.2 %), of tumors showed a decrease in IGF-1R expression while in a small subset of tumors the IGF-1R was upregulated (15.1 %). IGF-1R expression before treatment was not associated with pathological response (Fig. 3). However, the absence of IGF-1R expression (45 %) after treatment in the postchemotherapy operation specimens was associated with a better pathological response comparing ordinal MP classification response in univariate analysis (OR 2.60, 95 % CI 1.31–5.18, P = 0.006) (Fig. 3). This result remained significant in multivariate analysis when adjusting for HR status and clinical N stage (OR 2.64, 95 % CI 1.32–5.31, P = 0.006). With linear regression P = 0.008, indicating that the relationship between MP classification and IGF-1R expression is almost linear. Additionally, patients with a decrease in expression during treatment showed a better response to chemotherapy as well (OR 2.64, 95 % CI 1.17–5.98, P = 0.020 in multivariate analysis). Treatment with zoledronic acid had no influence on the IGF-1R expression in the operation specimen after treatment (P = 0.620) nor on diminished IGF-1R expression during treatment (P = 0.830) (data not shown).

IGF-1R pathway SNPs

FFPE tissue samples from 184 (74 %) of 250 patients were available for analysis of IGF-1 pathway polymorphisms (preferentially tumor-negative tissue, see Methods). Data of available tissue are summarized in the consort diagram (Fig. 2). Of the eight genotyped SNPs, two significantly deviated from the Hardy–Weinberg equilibrium (rs2946834 and rs1520220). After correction for multiple testing, rs2946834 still significantly deviated from the Hardy–Weinberg equilibrium and was therefore excluded from the analysis. The genotype frequencies of rs1520220 did not differ from those observed in a publicly available database of European subjects (e.g., from the HapMap project) [28]. All eight SNPs had a call rate above 85 %, which is shown in Table 3. Clinical T stage, clinical N stage, and HR status were associated with pCR, wherefore was adjusted in multivariate analyses (Table 4). The variant T allele of 3129G > T in IGF1R (rs2016347) was associated with pCR in multivariate analysis (4.4 % for GG vs. 16.7 % GT/TT, P = 0.032) and the variant C allele of rs2854746 in IGFBP3 tended to be associated with pCR in multivariate analysis (7.3 % for GG vs. 18.1 % GC/CC, P = 0.058). The global P value used for multiple testing correction for all eight SNPs together was P = 0.0095 for the dominant model (global score test). The CART derived from these SNPs is shown in Fig. 4. The corresponding AUC was 0.613 (95 % CI 0.518–0.707, P = 0.040).
Table 3
Distribution of genotypes of the investigated SNPs
SNP
Allele
N = 184 (%)
HWE χ2
P value
Call rate (%)
rs10735380
AA
110 (54.3)
2.1
0.144
94
IGF1
AG
68 (37.0)
   
 
GG
5 (2.7)
   
 
NE
11 (6.0)
   
rs1520220
CC
115 (62.5)
4.4
0.040a
94
IGF1
CG
46 k
   
 
GG
11 (6.0)
   
 
NE
12 (6.5)
   
rs6220
AA
91 (49.5)
3.3
0.068
89
IGF1
AG
56 (30.4)
   
 
GG
17 (9.2)
   
 
NE
20 (10.9)
   
rs2946834b
GG
82 (44.6)
10.1
0.001a
88
IGF1
GA
53 (28.8)
   
 
AA
26 (14.1)
   
 
NE
23 (12.5)
   
rs2270628
CC
105 (57.1)
2.8
0.096
87
IGFBP3
CT
45 (24.5)
   
 
TT
10 (5.4)
   
 
NE
24 (13.0)
   
rs2854746
GG
59 (32.1)
1.9
0.170
90
IGFBP3
GC
72 (39.1)
   
 
CC
34 (18.5)
   
 
NE
19 (10.3)
   
rs4320932
TT
111 (60.3)
0.04
0.843
96
IGF2
TC
57 (31)
   
 
CC
8 (4.3)
   
 
NE
8 (4.3)
   
rs2016347
GG
48 (26.1)
1.8
0.185
96
IGF1R
GT
96 (52.2)
   
 
TT
32 (17.4)
   
 
NE
8 (4.3)
   
aNot in HWE
bSNP excluded from analyses because the SNP is significantly deviated from HWE after Bonferroni correction
HWE Hardy–Weinberg equilibrium, IGF insulin-like growth factor, IGFBP3 insulin-like growth factor binding protein 3, IGF1R insulin-like growth factor-1 receptor, NE Not evaluable (despite attempt to genotype), SNP single nucleotide polymorphism
Table 4
Associations between tumor and patient characteristics, SNPs, and pCR in breast and lymph nodes
    
Univariate analysis
Multivariate analysis
Parameter
 
N
% pCR
OR
95 % CI
P value
OR
95 % CI
P value
Clinical T stage
cT1/cT2
106
17.9
1
Reference
 
1
Reference
 
 
cT3/T4
73
6.8
0.34
0.12–0.95
0.039
0.49
0.16–1.50
0.209
Clinical N stage
cN0
84
21.4
1
Reference
 
1
Reference
 
 
cN+
95
6.3
0.25
0.09–0.66
0.005
0.19
0.06–0.58
0.003
HR status
ER+ and/or PR+
151
8.6
1
Reference
 
1
Reference
 
 
Triple negative
28
39.3
6.87
2.66–17.7
0.00007
9.35
3.09–28.3
0.00008
Allocated treatment
TAC + ZA
87
14.9
1
Reference
0.559
   
TAC only
92
12.0
0.77
0.33–1.83
    
Age
   
0.96
0.89–1.09
0.186
   
BMI
   
0.97
0.88–1.08
0.581
   
rs10735380
AA
97
13.4
1
Reference
    
IGF1
AG
66
13.6
1.02
0.41–2.55
0.966
   
 
GG
5
20.0
1.61
0.17–15.6
0.679
   
rs1520220
CC
111
15.3
1
Reference
    
IGF1
CG
45
13.3
0.85
0.31–2.32
0.752
   
 
GG
11
0.0
   
rs6220
AA
88
11.4
1
Reference
    
IGF1
AG
56
16.1
1.49
0.57–3.94
0.418
   
 
GG
17
17.6
1.67
0.41–6.48
0.475
   
rs2270628
CC
101
11.9
1
Reference
    
IGFBP3
CT
45
17.8
1.60
0.61–4.24
0.342
   
 
TT
9
0.0
   
rs2854746
GG
55
7.3
1
Reference
 
1
Reference
 
IGFBP3
GC
72
16.7
2.55
0.78–8.40
0.124
3.06
0.82–11.4
0.097
 
CC
33
21.2
3.43
0.92–12.8
0.066
4.02
0.92–17.6
0.065
 
GG
55
7.3
1
Reference
 
1
Reference
 
 
GC/CC
105
18.1
2.82
0.91–8.74
0.073
3.35
0.96–11.7
0.058
rs4320932
TT
106
15.1
1
Reference
    
IGF2
TC
57
12.3
0.79
0.30–2.04
0.623
   
 
CC
8
12.5
0.80
0.09–6.98
0.843
   
rs2016347
GG
45
4.4
1
Reference
 
1
Reference
 
IGF1R
GT
94
17.0
4.41
0.97–20.1
0.055
5.58
1.08–28.7
0.040
 
TT
32
15.6
3.98
0.72–22.0
0.113
6.67
1.03–43.1
0.046
 
GG
45
4.4
1
Reference
 
1
Reference
 
 
GT/TT
126
16.7
4.30
1.00–19.1
0.056
5.82
1.17–29.1
0.032
BMI body mass index, CI confidence interval, ER estrogen receptor, HR hormone receptor, IGF insulin-like growth factor 1, IGFBP3 insulin-like growth factor binding protein 3, IGF1R insulin-like growth factor 1 receptor, OR odds ratio, pCR pathological complete response, PR progesterone receptor, SNP single nucleotide polymorphism, TAC docetaxel, doxorubicin, cyclophosphamide, ZA zoledronic acid
Moreover, the variant T allele of C > T in IGFBP3 (rs2270628) was associated with a higher occurrence of grade III/IV side effects in univariate analysis (OR 2.20, 95 % CI 1.04–4.67, P = 0.039) and multivariate analysis (18.1 % for CC vs. 32.7 % CT/TT, OR 2.30, 95 % CI 1.06–4.98, P = 0.034) (data not shown). The multivariate analysis was adjusted for body mass index, as it was significantly associated with grade III/IV side effects.

Genotype–phenotype associations

rs2016347 in IGF1R was not associated with IGF-1R expression before chemotherapy (78.3 % for GG vs. 65.9 % GT/TT, P = 0.115) or after chemotherapy (50.0 % for GG vs. 67.7 % GT/TT, P = 0.099).

Discussion

This translational study showed that IGF-1R expression changed in most of the tumors during treatment in stage II/III HER2-negative BC patients treated with neoadjuvant TAC chemotherapy and that absent or diminished expression after treatment was associated with a better pathological response according to MP classification. Additionally, we found that the variant T allele of 3129G > T in IGF1R (rs2016347) was significantly associated with a better pathological response according to MP classification after neoadjuvant chemotherapy.
Changes of IGF-1R expression of the tumor during chemotherapy have been described previously [18, 31]. Our study confirms these results in a larger and more homogeneous patient cohort. Moreover, in the current trial a greater part of the tumors showed a decline in IGF-1R expression (47.2 %) compared with the prior described 14.0 %. This might be explained by the difference in chemotherapy regimens used as well as the absence of HER2 expression in our cohort, as HER2-positive tumors show less IGF-1R expression [10, 11]. The decline of IGF-1R expression in the tumor during TAC treatment observed in our study might reflect chemotherapy efficacy, as patients with a decline in IGF-1R expression showed a significantly better pathological response than tumors with no change or an increase in expression. In keeping with this inference, downregulation of IGF-1R during chemotherapy treatment is associated with prolonged survival [18]. Bhargava et al. [10] showed that low IGF-1R expression before treatment was associated with a better response to neoadjuvant chemotherapy in ER-positive tumors, but not in triple-negative tumors. We could not reproduce this association, but this could be explained by the difference in cohort (e.g., differences in HER2 status and chemotherapy regimen).
In our exploratory analysis of IGF-1 pathway polymorphisms, the variant T allele of 3129G > T in IGF1R (rs2016347) was associated with a better pathological response according to MP classification after neoadjuvant chemotherapy. This is in accordance with studies that associated 3129G > T in IGF1R (rs2016347) with cancer prognosis and treatment outcome [22, 32, 33]. Winder et al. [22] found that the T allele was associated with a better overall survival in colorectal cancer patients treated with cetuximab [33] and a better overall survival in ER-positive BC patients treated with tamoxifen. rs2016347 is localized in the 3′-untranslated region of the IGF1R gene, functioning as a microRNA binding site [28]. Because microRNA binding sites are important for mRNA translation and degradation, the variant T allele of rs2016347 might disturb binding to this microRNA site [34]. Although the precise functional effect of IGF1R rs2016347 is unknown, it would be a plausible explanation that the T allele of rs2016347 may reduce IGF-1R expression. However, in our study rs2016347 in IGF1R was not associated with IGF-1R expression.
The variant T allele of C > T in IGFBP3 (rs2270628) was associated with the occurrence of grade III/IV side effects. Although the mechanism is unclear, several studies have shown that the variant T allele of rs2270628 is associated with decreased serum IGF-BP3 levels [35, 36]. IGF-1 activity depends on binding with IGF-BP3 [12, 13], so it may be that higher activity of IGF-1 due to lower levels of IGF-BP3 causes a higher incidence of toxicity of chemotherapy in our study [6].
Our study has some limitations. Using our approach, we could not investigate the best responders (MP5) after chemotherapy because inherently no tumor tissue was left to measure IGF-1R in the operation specimen. Moreover, the response of the lymph nodes is not evaluated in the MP grading system because it focuses only on the primary tumor. Although, the survival of patients with a partial response is affected by residual lymph node status [37]. Additionally, the number of evaluable triple-negative tumors was too small to evaluate for differences in response associated with IGF-1R between HR-positive tumors and triple-negative tumors. Our sample size for the explorative genotype–phenotype optional side study was small and this was probably the reason why we could not reproduce the associations between the serum IGF-1 and IGF-BP3 levels and SNPs. However, the results of our study provide further evidence for the importance of patient selection for (co)treatment with an IGF-1 inhibitor. Until now no convincing benefit of IGF-I pathway inhibitors was found in clinical studies in BC [3840]. These studies lacked patient selection based on IGF-1 pathway activity. It may be hypothesized that patients with a diminished IGF-1R after chemotherapy will not benefit from an IGF-1R inhibitor, while a patient with upregulated IGF-1R might benefit.

Conclusions

IGF-1R expression in the tumor changed during chemotherapy and absent or diminished expression of IGF-1R after treatment was associated with a better pathological response. rs2016347 in IGF1R was associated with pCR after TAC chemotherapy. These observations may help to predict the efficacy of TAC chemotherapy and to select patients who might benefit from (co)treatment with an IGF-1 pathway inhibitor.

Acknowledgments

The authors thank all of the participating centers and are greatly indebted to the patients for participating in this study. They thank the LUMC Datacenter, Department of Surgery, for trial coordination and data collection. This work was supported by grants from the Dutch Cancer Society (2010-4682), Amgen, Novartis, and Sanofi Aventis. The Dutch Breast Cancer Research Group (BOOG), Amsterdam, the Netherlands is sponsor of this study.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

Conception and design: SdG, AC, HWMvL, SvdV, LGMJ, HG, H-JG, HP, and JRK. Study coordination: AC, SvdV, JRK, and Dutch breast cancer group. Development of experiments: SdG, AC, HWMvL, ALM, NGD-E, LGMJ, TvdS, HP, and JRK. Acquisition of data: SdG, AC, HWMvL, ALM, NGD-E, LGMJ, VTHBMS, JBH, LWK, TvdS, and JRK. Analysis and interpretation of data: SdG, AC, ALM, LGMJ, JJS, TvdS, SB, JJMvH, H-JG, HP, and JRK. Study supervision: HG, JJMvdH, HP, and JRK. Writing of the manuscript: SdG, NGD-E, SB, HP, and JRK. All authors critically revised and approved the final manuscript and agree to be accountable for all aspects of the work.
Literatur
1.
Zurück zum Zitat Samani AA, Yakar S, LeRoith D, Brodt P. The role of the IGF system in cancer growth and metastasis: overview and recent insights. Endocr Rev. 2007;28:20–47.CrossRefPubMed Samani AA, Yakar S, LeRoith D, Brodt P. The role of the IGF system in cancer growth and metastasis: overview and recent insights. Endocr Rev. 2007;28:20–47.CrossRefPubMed
2.
Zurück zum Zitat Renehan AG, Zwahlen M, Minder C, O’dwyer ST, Shalet SM, Egger M. Insulin-like growth factor (IGF)-I, IGF binding protein-3, and cancer risk: systematic review and meta-regression analysis. Lancet. 2004;363:1346–53.CrossRefPubMed Renehan AG, Zwahlen M, Minder C, O’dwyer ST, Shalet SM, Egger M. Insulin-like growth factor (IGF)-I, IGF binding protein-3, and cancer risk: systematic review and meta-regression analysis. Lancet. 2004;363:1346–53.CrossRefPubMed
3.
Zurück zum Zitat Diorio C, Pollak M, Byrne C, Masse B, Hebert-Croteau N, Yaffe M, et al. Insulin-like growth factor-I, IGF-binding protein-3, and mammographic breast density. Cancer Epidemiol Biomarkers Prev. 2005;14:1065–73.CrossRefPubMed Diorio C, Pollak M, Byrne C, Masse B, Hebert-Croteau N, Yaffe M, et al. Insulin-like growth factor-I, IGF-binding protein-3, and mammographic breast density. Cancer Epidemiol Biomarkers Prev. 2005;14:1065–73.CrossRefPubMed
4.
Zurück zum Zitat Key TJ, Appleby PN, Reeves GK, Roddam AW. Insulin-like growth factor 1 (IGF1), IGF binding protein 3 (IGFBP3), and breast cancer risk: pooled individual data analysis of 17 prospective studies. Lancet Oncol. 2010;11:530–42.CrossRefPubMed Key TJ, Appleby PN, Reeves GK, Roddam AW. Insulin-like growth factor 1 (IGF1), IGF binding protein 3 (IGFBP3), and breast cancer risk: pooled individual data analysis of 17 prospective studies. Lancet Oncol. 2010;11:530–42.CrossRefPubMed
5.
Zurück zum Zitat Duggan C, Wang CY, Neuhouser ML, Xiao L, Smith AW, Reding KW, et al. Associations of insulin-like growth factor and insulin-like growth factor binding protein-3 with mortality in women with breast cancer. Int J Cancer. 2013;132:1191–200.CrossRefPubMed Duggan C, Wang CY, Neuhouser ML, Xiao L, Smith AW, Reding KW, et al. Associations of insulin-like growth factor and insulin-like growth factor binding protein-3 with mortality in women with breast cancer. Int J Cancer. 2013;132:1191–200.CrossRefPubMed
6.
Zurück zum Zitat Lee C, Safdie FM, Raffaghello L, Wei M, Madia F, Parrella E, et al. Reduced levels of IGF-I mediate differential protection of normal and cancer cells in response to fasting and improve chemotherapeutic index. Cancer Res. 2010;70:1564–72.CrossRefPubMedPubMedCentral Lee C, Safdie FM, Raffaghello L, Wei M, Madia F, Parrella E, et al. Reduced levels of IGF-I mediate differential protection of normal and cancer cells in response to fasting and improve chemotherapeutic index. Cancer Res. 2010;70:1564–72.CrossRefPubMedPubMedCentral
7.
Zurück zum Zitat Lin MZ, Marzec KA, Martin JL, Baxter RC. The role of insulin-like growth factor binding protein-3 in the breast cancer cell response to DNA-damaging agents. Oncogene 2012;33:88-96. Lin MZ, Marzec KA, Martin JL, Baxter RC. The role of insulin-like growth factor binding protein-3 in the breast cancer cell response to DNA-damaging agents. Oncogene 2012;33:88-96.
8.
Zurück zum Zitat Zhang Y, Moerkens M, Ramaiahgari S, de Bont H, Price L, Meerman J, et al. Elevated insulin-like growth factor 1 receptor signaling induces antiestrogen resistance through the MAPK/ERK and PI3K/Akt signaling routes. Breast Cancer Res. 2011;13:R52.CrossRefPubMedPubMedCentral Zhang Y, Moerkens M, Ramaiahgari S, de Bont H, Price L, Meerman J, et al. Elevated insulin-like growth factor 1 receptor signaling induces antiestrogen resistance through the MAPK/ERK and PI3K/Akt signaling routes. Breast Cancer Res. 2011;13:R52.CrossRefPubMedPubMedCentral
9.
Zurück zum Zitat Nahta R, Yuan LX, Zhang B, Kobayashi R, Esteva FJ. Insulin-like growth factor-I receptor/human epidermal growth factor receptor 2 heterodimerization contributes to trastuzumab resistance of breast cancer cells. Cancer Res. 2005;65:11118–28.CrossRefPubMed Nahta R, Yuan LX, Zhang B, Kobayashi R, Esteva FJ. Insulin-like growth factor-I receptor/human epidermal growth factor receptor 2 heterodimerization contributes to trastuzumab resistance of breast cancer cells. Cancer Res. 2005;65:11118–28.CrossRefPubMed
10.
Zurück zum Zitat Bhargava R, Beriwal S, McManus K, Dabbs DJ. Insulin-like growth factor receptor-1 (IGF-1R) expression in normal breast, proliferative breast lesions, and breast carcinoma. Appl Immunohistochem Mol Morphol. 2011;19:218–25.PubMed Bhargava R, Beriwal S, McManus K, Dabbs DJ. Insulin-like growth factor receptor-1 (IGF-1R) expression in normal breast, proliferative breast lesions, and breast carcinoma. Appl Immunohistochem Mol Morphol. 2011;19:218–25.PubMed
11.
Zurück zum Zitat Yerushalmi R, Gelmon KA, Leung S, Gao D, Cheang M, Pollak M, et al. Insulin-like growth factor receptor (IGF-1R) in breast cancer subtypes. Breast Cancer Res Treat. 2012;132:131–42.CrossRefPubMed Yerushalmi R, Gelmon KA, Leung S, Gao D, Cheang M, Pollak M, et al. Insulin-like growth factor receptor (IGF-1R) in breast cancer subtypes. Breast Cancer Res Treat. 2012;132:131–42.CrossRefPubMed
12.
Zurück zum Zitat Jones JI, Clemmons DR. Insulin-like growth factors and their binding proteins: biological actions. Endocr Rev. 1995;16:3–34.PubMed Jones JI, Clemmons DR. Insulin-like growth factors and their binding proteins: biological actions. Endocr Rev. 1995;16:3–34.PubMed
13.
Zurück zum Zitat Stewart CE, Rotwein P. Growth, differentiation, and survival: multiple physiological functions for insulin-like growth factors. Physiol Rev. 1996;76:1005–26.PubMed Stewart CE, Rotwein P. Growth, differentiation, and survival: multiple physiological functions for insulin-like growth factors. Physiol Rev. 1996;76:1005–26.PubMed
14.
Zurück zum Zitat Zhang X, Lin M, van Golen KL, Yoshioka K, Itoh K, Yee D. Multiple signaling pathways are activated during insulin-like growth factor-I (IGF-I) stimulated breast cancer cell migration. Breast Cancer Res Treat. 2005;93:159–68.CrossRefPubMed Zhang X, Lin M, van Golen KL, Yoshioka K, Itoh K, Yee D. Multiple signaling pathways are activated during insulin-like growth factor-I (IGF-I) stimulated breast cancer cell migration. Breast Cancer Res Treat. 2005;93:159–68.CrossRefPubMed
15.
Zurück zum Zitat Zhu C, Qi X, Chen Y, Sun B, Dai Y, Gu Y. PI3K/Akt and MAPK/ERK1/2 signaling pathways are involved in IGF-1-induced VEGF-C upregulation in breast cancer. J Cancer Res Clin Oncol. 2011;137:1587–94.CrossRefPubMed Zhu C, Qi X, Chen Y, Sun B, Dai Y, Gu Y. PI3K/Akt and MAPK/ERK1/2 signaling pathways are involved in IGF-1-induced VEGF-C upregulation in breast cancer. J Cancer Res Clin Oncol. 2011;137:1587–94.CrossRefPubMed
16.
Zurück zum Zitat Hamelers IH, Steenbergh PH. Interactions between estrogen and insulin-like growth factor signaling pathways in human breast tumor cells. Endocr Relat Cancer. 2003;10:331–45.CrossRefPubMed Hamelers IH, Steenbergh PH. Interactions between estrogen and insulin-like growth factor signaling pathways in human breast tumor cells. Endocr Relat Cancer. 2003;10:331–45.CrossRefPubMed
17.
Zurück zum Zitat Maor S, Mayer D, Yarden RI, Lee AV, Sarfstein R, Werner H, et al. Estrogen receptor regulates insulin-like growth factor-I receptor gene expression in breast tumor cells: involvement of transcription factor Sp1. J Endocrinol. 2006;191:605–12.CrossRefPubMed Maor S, Mayer D, Yarden RI, Lee AV, Sarfstein R, Werner H, et al. Estrogen receptor regulates insulin-like growth factor-I receptor gene expression in breast tumor cells: involvement of transcription factor Sp1. J Endocrinol. 2006;191:605–12.CrossRefPubMed
18.
Zurück zum Zitat Heskamp S, Boerman OC, Molkenboer-Kuenen JD, Wauters CA, Strobbe LJ, Mandigers CM, et al. Upregulation of IGF-1R expression during neoadjuvant therapy predicts poor outcome in breast cancer patients. PLoS One. 2015;10:e0117745.CrossRefPubMedPubMedCentral Heskamp S, Boerman OC, Molkenboer-Kuenen JD, Wauters CA, Strobbe LJ, Mandigers CM, et al. Upregulation of IGF-1R expression during neoadjuvant therapy predicts poor outcome in breast cancer patients. PLoS One. 2015;10:e0117745.CrossRefPubMedPubMedCentral
19.
Zurück zum Zitat Diorio C, Brisson J, Berube S, Pollak M. Genetic polymorphisms involved in insulin-like growth factor (IGF) pathway in relation to mammographic breast density and IGF levels. Cancer Epidemiol Biomarkers Prev. 2008;17:880–8.CrossRefPubMed Diorio C, Brisson J, Berube S, Pollak M. Genetic polymorphisms involved in insulin-like growth factor (IGF) pathway in relation to mammographic breast density and IGF levels. Cancer Epidemiol Biomarkers Prev. 2008;17:880–8.CrossRefPubMed
20.
Zurück zum Zitat Gu F, Schumacher FR, Canzian F, Allen NE, Albanes D, Berg CD, et al. Eighteen insulin-like growth factor pathway genes, circulating levels of IGF-I and its binding protein, and risk of prostate and breast cancer. Cancer Epidemiol Biomarkers Prev. 2010;19:2877–87.CrossRefPubMedPubMedCentral Gu F, Schumacher FR, Canzian F, Allen NE, Albanes D, Berg CD, et al. Eighteen insulin-like growth factor pathway genes, circulating levels of IGF-I and its binding protein, and risk of prostate and breast cancer. Cancer Epidemiol Biomarkers Prev. 2010;19:2877–87.CrossRefPubMedPubMedCentral
21.
Zurück zum Zitat Muendlein A, Lang AH, Geller-Rhomberg S, Winder T, Gasser K, Drexel H, et al. Association of a common genetic variant of the IGF-1 gene with event-free survival in patients with HER2-positive breast cancer. J Cancer Res Clin Oncol. 2013;139:491–8.CrossRefPubMed Muendlein A, Lang AH, Geller-Rhomberg S, Winder T, Gasser K, Drexel H, et al. Association of a common genetic variant of the IGF-1 gene with event-free survival in patients with HER2-positive breast cancer. J Cancer Res Clin Oncol. 2013;139:491–8.CrossRefPubMed
22.
Zurück zum Zitat Winder T, Giamas G, Wilson PM, Zhang W, Yang D, Bohanes P, et al. Insulin-like growth factor receptor polymorphism defines clinical outcome in estrogen receptor-positive breast cancer patients treated with tamoxifen. Pharmacogenomics J. 2014;14:28–34.CrossRefPubMed Winder T, Giamas G, Wilson PM, Zhang W, Yang D, Bohanes P, et al. Insulin-like growth factor receptor polymorphism defines clinical outcome in estrogen receptor-positive breast cancer patients treated with tamoxifen. Pharmacogenomics J. 2014;14:28–34.CrossRefPubMed
23.
Zurück zum Zitat Mauri D, Pavlidis N, Ioannidis JP. Neoadjuvant versus adjuvant systemic treatment in breast cancer: a meta-analysis. J Natl Cancer Inst. 2005;97:188–94.CrossRefPubMed Mauri D, Pavlidis N, Ioannidis JP. Neoadjuvant versus adjuvant systemic treatment in breast cancer: a meta-analysis. J Natl Cancer Inst. 2005;97:188–94.CrossRefPubMed
24.
Zurück zum Zitat Ogston KN, Miller ID, Payne S, Hutcheon AW, Sarkar TK, Smith I, et al. A new histological grading system to assess response of breast cancers to primary chemotherapy: prognostic significance and survival. Breast. 2003;12:320–7.CrossRefPubMed Ogston KN, Miller ID, Payne S, Hutcheon AW, Sarkar TK, Smith I, et al. A new histological grading system to assess response of breast cancers to primary chemotherapy: prognostic significance and survival. Breast. 2003;12:320–7.CrossRefPubMed
25.
Zurück zum Zitat Romero A, Garcia-Saenz JA, Fuentes-Ferrer M, Lopez Garcia-Asenjo JA, Furio V, Roman JM, et al. Correlation between response to neoadjuvant chemotherapy and survival in locally advanced breast cancer patients. Ann Oncol. 2013;24:655–61.CrossRefPubMed Romero A, Garcia-Saenz JA, Fuentes-Ferrer M, Lopez Garcia-Asenjo JA, Furio V, Roman JM, et al. Correlation between response to neoadjuvant chemotherapy and survival in locally advanced breast cancer patients. Ann Oncol. 2013;24:655–61.CrossRefPubMed
26.
Zurück zum Zitat Charehbili A, van de Ven S, Smit VT, Meershoek-Klein KE, Hamdy NA, Putter H, et al. Addition of zoledronic acid to neoadjuvant chemotherapy does not enhance tumor response in patients with HER2-negative stage II/III breast cancer: the NEOZOTAC trial (BOOG 2010-01). Ann Oncol. 2014;25:998–1004.CrossRefPubMed Charehbili A, van de Ven S, Smit VT, Meershoek-Klein KE, Hamdy NA, Putter H, et al. Addition of zoledronic acid to neoadjuvant chemotherapy does not enhance tumor response in patients with HER2-negative stage II/III breast cancer: the NEOZOTAC trial (BOOG 2010-01). Ann Oncol. 2014;25:998–1004.CrossRefPubMed
29.
Zurück zum Zitat Baak-Pablo R, Dezentje V, Guchelaar HJ, Van der Straaten T. Genotyping of DNA samples isolated from formalin-fixed paraffin-embedded tissues using preamplification. J Mol Diagn. 2010;12:746–9.CrossRefPubMedPubMedCentral Baak-Pablo R, Dezentje V, Guchelaar HJ, Van der Straaten T. Genotyping of DNA samples isolated from formalin-fixed paraffin-embedded tissues using preamplification. J Mol Diagn. 2010;12:746–9.CrossRefPubMedPubMedCentral
30.
Zurück zum Zitat Goeman JJ, van de Geer SA, de Kort F, van Houwelingen HC. A global test for groups of genes: testingassociation with a clinical outcome. Bioinformatics. 2004;20:93-9. Goeman JJ, van de Geer SA, de Kort F, van Houwelingen HC. A global test for groups of genes: testingassociation with a clinical outcome. Bioinformatics. 2004;20:93-9.
31.
Zurück zum Zitat Collecchi P, Giannessi PG, Baldini E, Naccarato AG, Passoni A, Bevilacqua G, et al. Effects of primary chemotherapy on biological parameters of locally advanced breast cancer. Ann N Y Acad Sci. 1996;784:419–26.CrossRefPubMed Collecchi P, Giannessi PG, Baldini E, Naccarato AG, Passoni A, Bevilacqua G, et al. Effects of primary chemotherapy on biological parameters of locally advanced breast cancer. Ann N Y Acad Sci. 1996;784:419–26.CrossRefPubMed
32.
Zurück zum Zitat Chang CF, Pao JB, Yu CC, Huang CY, Huang SP, Yang YP, et al. Common variants in IGF1 pathway genes and clinical outcomes after radical prostatectomy. Ann Surg Oncol. 2013;20:2446–52.CrossRefPubMed Chang CF, Pao JB, Yu CC, Huang CY, Huang SP, Yang YP, et al. Common variants in IGF1 pathway genes and clinical outcomes after radical prostatectomy. Ann Surg Oncol. 2013;20:2446–52.CrossRefPubMed
33.
Zurück zum Zitat Winder T, Zhang W, Yang D, Ning Y, Bohanes P, Gerger A, et al. Germline polymorphisms in genes involved in the IGF1 pathway predict efficacy of cetuximab in wild-type KRAS mCRC patients. Clin Cancer Res. 2010;16:5591–602.CrossRefPubMedPubMedCentral Winder T, Zhang W, Yang D, Ning Y, Bohanes P, Gerger A, et al. Germline polymorphisms in genes involved in the IGF1 pathway predict efficacy of cetuximab in wild-type KRAS mCRC patients. Clin Cancer Res. 2010;16:5591–602.CrossRefPubMedPubMedCentral
34.
Zurück zum Zitat Leung AK, Sharp PA. Function and localization of microRNAs in mammalian cells. Cold Spring Harb Symp Quant Biol. 2006;71:29–38.CrossRefPubMed Leung AK, Sharp PA. Function and localization of microRNAs in mammalian cells. Cold Spring Harb Symp Quant Biol. 2006;71:29–38.CrossRefPubMed
35.
Zurück zum Zitat Patel AV, Cheng I, Canzian F, Le ML, Thun MJ, Berg CD, et al. IGF-1, IGFBP-1, and IGFBP-3 polymorphisms predict circulating IGF levels but not breast cancer risk: findings from the Breast and Prostate Cancer Cohort Consortium (BPC3). PLoS One. 2008;3:e2578.CrossRefPubMedPubMedCentral Patel AV, Cheng I, Canzian F, Le ML, Thun MJ, Berg CD, et al. IGF-1, IGFBP-1, and IGFBP-3 polymorphisms predict circulating IGF levels but not breast cancer risk: findings from the Breast and Prostate Cancer Cohort Consortium (BPC3). PLoS One. 2008;3:e2578.CrossRefPubMedPubMedCentral
36.
Zurück zum Zitat D’Aloisio AA, Schroeder JC, North KE, Poole C, West SL, Travlos GS, et al. IGF-I and IGFBP-3 polymorphisms in relation to circulating levels among African American and Caucasian women. Cancer Epidemiol Biomarkers Prev. 2009;18:954–66.CrossRefPubMedPubMedCentral D’Aloisio AA, Schroeder JC, North KE, Poole C, West SL, Travlos GS, et al. IGF-I and IGFBP-3 polymorphisms in relation to circulating levels among African American and Caucasian women. Cancer Epidemiol Biomarkers Prev. 2009;18:954–66.CrossRefPubMedPubMedCentral
37.
Zurück zum Zitat Zhang GC, Zhang YF, Xu FP, Qian XK, Guo ZB, Ren CY, et al. Axillary lymph node status, adjusted for pathologic complete response in breast and axilla after neoadjuvant chemotherapy, predicts differential disease-free survival in breast cancer. Curr Oncol. 2013;20:e180–92.CrossRefPubMedPubMedCentral Zhang GC, Zhang YF, Xu FP, Qian XK, Guo ZB, Ren CY, et al. Axillary lymph node status, adjusted for pathologic complete response in breast and axilla after neoadjuvant chemotherapy, predicts differential disease-free survival in breast cancer. Curr Oncol. 2013;20:e180–92.CrossRefPubMedPubMedCentral
38.
Zurück zum Zitat Ma CX, Suman VJ, Goetz M, Haluska P, Moynihan T, Nanda R, et al. A phase I trial of the IGF-1R antibody cixutumumab in combination with temsirolimus in patients with metastatic breast cancer. Breast Cancer Res Treat. 2013;139:145–53.CrossRefPubMedPubMedCentral Ma CX, Suman VJ, Goetz M, Haluska P, Moynihan T, Nanda R, et al. A phase I trial of the IGF-1R antibody cixutumumab in combination with temsirolimus in patients with metastatic breast cancer. Breast Cancer Res Treat. 2013;139:145–53.CrossRefPubMedPubMedCentral
39.
Zurück zum Zitat Murakami H, Doi T, Yamamoto N, Watanabe J, Boku N, Fuse N, et al. Phase 1 study of ganitumab (AMG 479), a fully human monoclonal antibody against the insulin-like growth factor receptor type I (IGF1R), in Japanese patients with advanced solid tumors. Cancer Chemother Pharmacol. 2012;70:407–14.CrossRefPubMedPubMedCentral Murakami H, Doi T, Yamamoto N, Watanabe J, Boku N, Fuse N, et al. Phase 1 study of ganitumab (AMG 479), a fully human monoclonal antibody against the insulin-like growth factor receptor type I (IGF1R), in Japanese patients with advanced solid tumors. Cancer Chemother Pharmacol. 2012;70:407–14.CrossRefPubMedPubMedCentral
40.
Zurück zum Zitat Robertson JF, Ferrero JM, Bourgeois H, Kennecke H, de Boer RH, Jacot W, et al. Ganitumab with either exemestane or fulvestrant for postmenopausal women with advanced, hormone-receptor-positive breast cancer: a randomised, controlled, double-blind, phase 2 trial. Lancet Oncol. 2013;14:228–35.CrossRefPubMed Robertson JF, Ferrero JM, Bourgeois H, Kennecke H, de Boer RH, Jacot W, et al. Ganitumab with either exemestane or fulvestrant for postmenopausal women with advanced, hormone-receptor-positive breast cancer: a randomised, controlled, double-blind, phase 2 trial. Lancet Oncol. 2013;14:228–35.CrossRefPubMed
41.
Zurück zum Zitat Verheus M, McKay JD, Kaaks R, Canzian F, Biessy C, Johansson M, et al. Common genetic variation in the IGF-1 gene, serum IGF-I levels and breast density. Breast Cancer Res Treat. 2008;112:109–22.CrossRefPubMed Verheus M, McKay JD, Kaaks R, Canzian F, Biessy C, Johansson M, et al. Common genetic variation in the IGF-1 gene, serum IGF-I levels and breast density. Breast Cancer Res Treat. 2008;112:109–22.CrossRefPubMed
42.
Zurück zum Zitat Al-Zahrani A, Sandhu MS, Luben RN, Thompson D, Baynes C, Pooley KA, et al. IGF1 and IGFBP3 tagging polymorphisms are associated with circulating levels of IGF1, IGFBP3 and risk of breast cancer. Hum Mol Genet. 2006;15:1–10.CrossRefPubMed Al-Zahrani A, Sandhu MS, Luben RN, Thompson D, Baynes C, Pooley KA, et al. IGF1 and IGFBP3 tagging polymorphisms are associated with circulating levels of IGF1, IGFBP3 and risk of breast cancer. Hum Mol Genet. 2006;15:1–10.CrossRefPubMed
43.
Zurück zum Zitat Cheng I, DeLellis HK, Haiman CA, Kolonel LN, Henderson BE, Freedman ML, et al. Genetic determinants of circulating insulin-like growth factor (IGF)-I, IGF binding protein (BP)-1, and IGFBP-3 levels in a multiethnic population. J Clin Endocrinol Metab. 2007;92:3660–6.CrossRefPubMed Cheng I, DeLellis HK, Haiman CA, Kolonel LN, Henderson BE, Freedman ML, et al. Genetic determinants of circulating insulin-like growth factor (IGF)-I, IGF binding protein (BP)-1, and IGFBP-3 levels in a multiethnic population. J Clin Endocrinol Metab. 2007;92:3660–6.CrossRefPubMed
44.
Zurück zum Zitat Graziano F, Ruzzo A, Canestrari E, Catalano V, Santini D, Galluccio N, et al. Host genetic variants in the IGF binding protein-3 impact on survival of patients with advanced gastric cancer treated with palliative chemotherapy. Pharmacogenomics. 2010;11:1247–56.CrossRefPubMed Graziano F, Ruzzo A, Canestrari E, Catalano V, Santini D, Galluccio N, et al. Host genetic variants in the IGF binding protein-3 impact on survival of patients with advanced gastric cancer treated with palliative chemotherapy. Pharmacogenomics. 2010;11:1247–56.CrossRefPubMed
45.
Zurück zum Zitat Lu L, Risch E, Deng Q, Biglia N, Picardo E, Katsaros D, et al. An insulin-like growth factor-II intronic variant affects local DNA conformation and ovarian cancer survival. Carcinogenesis. 2013;34:2024–30.CrossRefPubMed Lu L, Risch E, Deng Q, Biglia N, Picardo E, Katsaros D, et al. An insulin-like growth factor-II intronic variant affects local DNA conformation and ovarian cancer survival. Carcinogenesis. 2013;34:2024–30.CrossRefPubMed
Metadaten
Titel
Insulin-like growth factor 1 receptor expression and IGF1R 3129G > T polymorphism are associated with response to neoadjuvant chemotherapy in breast cancer patients: results from the NEOZOTAC trial (BOOG 2010-01)
verfasst von
Stefanie de Groot
Ayoub Charehbili
Hanneke W. M. van Laarhoven
Antien L. Mooyaart
N. Geeske Dekker-Ensink
Saskia van de Ven
Laura G. M. Janssen
Jesse J. Swen
Vincent T. H. B. M. Smit
Joan B. Heijns
Lonneke W. Kessels
Tahar van der Straaten
Stefan Böhringer
Hans Gelderblom
Jacobus J. M. van der Hoeven
Henk-Jan Guchelaar
Hanno Pijl
Judith R. Kroep
on behalf of the Dutch Breast Cancer Research Group
Publikationsdatum
01.12.2016
Verlag
BioMed Central
Erschienen in
Breast Cancer Research / Ausgabe 1/2016
Elektronische ISSN: 1465-542X
DOI
https://doi.org/10.1186/s13058-015-0663-3

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