European Journal of Cancer (2014) xxx, xxx– xxx
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Significant survival impact of MACC1 polymorphisms in HER2 positive breast cancer patients Axel Muendlein a,c, Michael Hubalek e, Simone Geller-Rhomberg a,c, Klaus Gasser a,b,c, Thomas Winder a,b,c, Heinz Drexel a,b,c, Thomas Decker d, Elisabeth Mueller-Holzner e, Martina Chamson e, Christian Marth e, Alois H. Lang a,b,⇑ a
Vorarlberg Institute for Vascular Investigation and Treatment, 6800 Feldkirch, Austria Department of Medicine and Cardiology, Academic Teaching Hospital Feldkirch, 6800 Feldkirch, Austria c Private University of the Principality of Liechtenstein, 9495 Triesen, Liechtenstein d Studienzentrum Onkologie Ravensburg, 88212 Ravensburg, Germany e Department of Obstetrics and Gynecology, Innsbruck Medical University, 6020 Innsbruck, Austria b
Received 8 January 2014; received in revised form 10 April 2014; accepted 9 May 2014
KEYWORDS Breast neoplasms Survival MACC1 Polymorphism Single nucleotide
Abstract Background: Deregulation of hepatocyte growth factor (HGF)/mesenchymalepithelial transition factor (MET) signalling has been associated with poor clinical outcome in breast cancer and other cancers. The recently discovered metastasis-associated in colon cancer-1 (MACC1) gene is a key regulator of the HGF/MET pathway. Potential links between genetic variants of the MACC1 gene and survival in breast cancer patients are unknown. In the present study, we therefore aimed to investigate the influence of MACC1 polymorphisms on event-free and overall survival in patients with human epidermal growth factor 2 (HER2)-positive breast cancer. Methods: The present study included 164 consecutive white patients with HER2-positive breast cancer. Three MACC1 polymorphisms, rs1990172, rs975263 and rs3735615, already associated with cancer prognosis or with potential functional effects, were genotyped by the 50 nuclease assay. Results: Multivariate Cox regression analysis adjusted for age and tumour stage showed increased risk for progression or death for carriers of the rare allele (G-allele) of single nucleotide polymorphism (SNP) rs1990172 (hazard ratios (HR) = 2.26; p = 0.004 and HR = 3.13; p = 0.001 for event-free survival and overall survival, respectively). In addition, we were able to demonstrate an adverse effect on cancer prognosis for carriers of the rare allele (T-allele) of SNP rs975263 (HR = 2.17; p = 0.007 and HR = 2.80; p = 0.003 for event-free survival and
⇑ Corresponding author at: Department of Medicine and Cardiology, Academic Teaching Hospital Feldkirch, 6807 Feldkirch, Austria. Tel.: +43 5572 3032301; fax: +43 5572 3037511. E-mail address: [email protected] (A.H. Lang).
http://dx.doi.org/10.1016/j.ejca.2014.05.007 0959-8049/Ó 2014 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Muendlein A. et al., Significant survival impact of MACC1 polymorphisms in HER2 positive breast cancer patients, Eur J Cancer (2014), http://dx.doi.org/10.1016/j.ejca.2014.05.007
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overall survival, respectively). The rare allele (C-allele) of SNP rs3735615 showed a significant protective impact on event-free survival as well as overall survival (HR = 0.25; p = 0.001, and HR = 0.16; p = 0.001, respectively). Conclusions: This study provides first evidence that MACC1 polymorphisms are associated with clinical outcome for HER2-positive breast cancer patients. Further studies are warranted to validate these findings. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Metastatic dissemination of primary tumours is the leading cause of cancer-associated deaths. Although local invasion and the formation of metastases are clinically the most relevant of all the processes involved in carcinogenesis, they are the least well understood at the molecular level [1]. The hepatocyte growth factor (HGF)/mesenchymal-epithelial transition factor (cMET) signalling complex is known to activate a number of signalling pathways that contribute to the invasion and metastasis of a primary tumour [2,3]. cMET is a tyrosine kinase receptor and HGF is the only known ligand so far. HGF binding to cMET leads to formation of phosphorylated cMET, which activates downstream effectors such as phosphatidylinositol 3-kinase (PI3K/ AKT), mitogen-activated protein kinase (ERK/MAPK) and signal transducer and activator of transcription (STATs) pathways [4–6]. Through these cellular signalling pathways HGF/cMET interaction plays a key role in cellular proliferation, survival, migration and invasion [7–9]. Dysregulation of cMET is strongly associated with tumour progression and adverse survival outcomes in breast cancer [10,11] and other cancers such as colon cancer, non-small-cell lung cancer, ovarian cancer, and gastric cancer [12–15]. Interestingly, a recent study by Minuti et al. [16] provides evidence for a critical role of HGF/MET signalling pathway for sensitivity to anti-human epidermal growth factor 2 (HER2) agents. High gene copy numbers of cMET and HGF correlate with an increased risk of trastuzumab-based therapy failure in HER2-positive metastatic breast cancer patients. The recently identified metastasis-associated in colon cancer-1 (MACC1) gene acts as a key regulator of cMET expression [17,18] entering the HGF/cMET signalling complex upstream of cMET. MACC1 was first identified by Stein et al. [17] to be overexpressed in primary and metastatic tumour specimens of colon cancer as compared to normal colon mucosa and was associated with colon cancer metastasis and reduced metastasis-free survival. Subsequent studies have shown that overexpression of MACC1 correlates positively with poor clinical outcome in patients with gastric cancer [19,20], lung adenocarcinoma [21], hepatocellular carcinoma [22] and breast cancer [23].
Single nucleotide polymorphisms (SNPs) may contribute to altered MACC1 expression or function and consequently may influence the prognosis of cancer. Recently, our group reported a significant association of the MACC1 tagging SNP rs1990172 with reduced overall survival in colorectal cancer patients [24]. The variant is in linkage disequilibrium with a non-synonymous SNP, rs975263 (Leu515Ser), which may exert a causal effect on MACC1 protein function or structure. Notably, both SNPs have been associated with a poor prognosis of hepatocellular carcinoma patients [25]. Another missense genetic variant, rs3735615 (Arg804Thr), lies in an evolutionary conserved region and might have therefore a decisive role on the effectiveness of MACC1 [26]. In the present study, we aimed to investigate the influence of the MACC1 polymorphisms rs1990172, rs975263 and rs3735615 on event-free and overall survival in patients with HER2-positive breast cancer. 2. Methods 2.1. Patients Formalin-fixed paraffin embedded (FFPE) tissue samples of 164 consecutive white patients with HER2positive breast cancer treated between 2000 and 2010 at the Department of Gynecology and Obstetrics, Medical University of Innsbruck, Austria, were available for the present study. HER2-positivity was diagnosed in cases with an immunohistochemistical score of 3+. In cases scored with 2+ positivity, fluorescence in situ hybridisation (FISH) or silver in situ hybridisation (SISH) analysis has been performed to demonstrate overexpression of the HER-2 gene. Tumours were classified according to the guidelines of the American Joint Committee on Cancer (AJCC) staging system [27]. Event-free survival was calculated as the time from cancer diagnosis to either relapse or death from any cause or the last follow up, at which point data were collected. Overall survival was measured from time from cancer diagnosis until final follow-up or death from any cause. The ethics committee of Innsbruck Medical University approved the present study and written informed consent was obtained from all patients in accordance with the Declaration of Helsinki.
Please cite this article in press as: Muendlein A. et al., Significant survival impact of MACC1 polymorphisms in HER2 positive breast cancer patients, Eur J Cancer (2014), http://dx.doi.org/10.1016/j.ejca.2014.05.007
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2.2. Genotyping Genomic DNA was extracted from sections of archived formalin-fixed paraffin embedded tissue blocks using the QIAamp DNA FFPE Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Genotyping of MACC1 variants rs1990172, rs975263 and rs3735615 was carried out by the 50 nuclease assay using TaqManÒ MGB probes on a LightCyclerÒ 480 Real-Time PCR System (F. Hoffmann-La Roche Ltd, Basel, Switzerland). TaqManÒ MGB probes were provided together with corresponding PCR primers by the Assay-on-demande service (Applied Biosystems, Forster City, CA) for rs1990172 and rs3735615 (order numbers: C_2632417_10 and C_27489506_10, respectively) and by the Assay-by-designe service (Applied Biosystems) for rs975263 (catalogue number: 4332077). The 50 nuclease assay was performed in a 15 ll volume, comprising 10–30 ng genomic DNA, 1 TaqManÒ Genotyping PCR Master Mix (Applied Biosystems), and 1 primer/ probe mix under the following amplification conditions: 10 min at 95 °C and 45 cycles at 92 °C for 15 s and 60 °C for 1 min. Reference controls as well as nontemplate controls were included in each run. Genotypes were automatically determined by LightCyclerÒ software 1.5 followed by a visual control of accurate genotype classification.
2.3. Statistical analysis Differences in categorical study variables between genotypes were tested for statistical significance with the Chi-squared test. For continuous variables analysis of variance (ANOVA) was applied. Hazard ratios and 95% confidence intervals (CI) of the hazard ratios were derived from univariate and multivariate Cox proportional hazards models. Survival curves were generated using the Kaplan–Meier method and compared using the Log–Rank–Mantel–Cox-Test. Observed numbers of each genotype were compared with those expected to test whether the sample was in Hardy–Weinberg equilibrium using the Chi-Square test with one degree of freedom. To test for multiplicity Bonferroni correction was used. P-values 6 0.05 were considered as significant. Statistical analyses were performed with the software package SPSS 11.5 for Windows (SPSS, Inc., Chicago, IL, USA). Statistical power analysis was performed using the Power and Sample Size Program [28] under an additive model of inheritance. On the basis of minor allele frequencies of 40% on average of included SNPs given in the NCBI SNP database (http://www.ncbi.nlm.nih.gov/snp/) and assuming a median survival time of 4 years of controls (carriers of the common alleles) and a median follow up period of 4.2 years, power analysis indicated that 160 patients would be needed to
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demonstrate a hazard ratio of 0.60 or 1.85 for the respective rare alleles at an alpha fault of 0.01 with a power of 80%. 3. Results 3.1. Patient characteristics The patient characteristics at baseline are given in table 1. Over a median follow up period of 4.2 years, 25 events (relapse or death) and 16 deaths, respectively, were recorded. About a third of patients did not receive trastuzumab because at that time the agent was not approved in the adjuvant setting yet. As soon as the approval was given all subsequent patients were treated with trastuzumab. Among given patient characteristics, AJCC stage was significantly associated with event-free survival (p = 0.042). Age at cancer diagnosis and AJCC stage were significantly associated with overall survival (p = 0.027 and p = 0.002, respectively). Other given patient characteristics were not associated with eventfree or overall survival (all p-values > 0.05). 3.2. Results from genotyping Observed genotyping frequencies as well as results from Hardy–Weinberg disequilibrium analysis are presented in Supplementary Table S1. MACC1 SNP genotype frequencies did not deviate significantly from Hardy–Weinberg. Pairwise squared correlation coefficients were r2 = 0.749 between SNP rs1990172 and rs975263, r2 = 0.227 between SNP rs1990172 and rs3735615 and r2 = 0.191 between SNP rs3735615 and rs975263. 3.3. Association of MACC1 SNP genotypes with clinicopathological patient characteristics Association MACC1 polymorphisms with clinicopathological features are presented in Supplementary Tables S2(a–c). MACC1 variant rs1990172 was significantly associated with menopausal status (p = 0.041). All three SNPs were significantly associated with chemotherapy (p = 0.006, p = 0.008, and p = 0.026 for rs1990172, rs975263 and rs3735615, respectively). No other significant associations between determined MACC1 SNPs and other clinical or pathological characteristics could be observed (all p-values > 0.05). 3.4. Association of MACC1 SNPs with survival Kaplan–Meier curves for event-free survival and overall survival according to genotypes (homozygous common allele, heterozygous, homozygous rare allele) of included MACC1 SNPs are shown in Fig. 1. Genotypes compassing rare alleles of SNP rs1990172 (GC,
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Table 1 Patient characteristics. Characteristic Age (years) Menopausal status Lymph node involvement* AJCC stage*
Histological grade*
Hormone receptor status Radiotherapy* Chemotherapy Hormone therapy* Trastuzumab therapy*
n Mean (±SD) Median (range) Pre Post Negative Positive I II III IV G1 G2 G3 ER+ or PR+ ER and PR No Yes No Yes No Yes No Yes
%
58.5 (±14.2) 59.4 (31.9–90.7) 51 31.1 113 68.9 103 62.8 57 34.8 85 54.8 55 34.2 20 12.6 1 0.6 22 13.4 109 66.5 23 14.0 121 73.8 43 26.2 77 48.7 81 51.3 80 48.8 84 51.2 56 34.8 105 65.2 37 36.3 65 63.7
* Lymph node involvement, missing samples: n = 4; AJCC stage, missing samples: n = 3; grade score, missing samples: n = 10, radiotherapy, missing samples: n = 6; hormone therapy, missing samples: n = 3; trastuzumab therapy, missing samples: n = 62. Tumours were classified according to the guidelines of the American Joint Committee on Cancer (AJCC) staging system.
GG) and SNP rs975263 (CT, TT), respectively, showed a significant increased risk for progression or death. Otherwise, genotypes compassing rare alleles of SNP rs3735615 (CC, GC) showed a significant protective impact on event-free survival as well as overall survival. Univariate and multivariate Cox regression analysis, adjusting for tumour, node, metastasis (TNM) stage and age, were used to further investigate the impact of included MACC1 variants on event-free survival and overall survival using an additive, dominant and recessive model of inheritance, respectively. Results are presented in Table 2. After adjustment for multiple testing using Bonferroni correction and in univariate as well as multivariate Cox regression analysis, SNP rs1990172 remained significantly associated with eventfree survival and overall survival using an additive and a dominant model of inheritance; SNP rs975263 remained significantly associated with event-free survival and overall survival by an additive model of inheritance; SNP rs3735615 remained significantly associated with event-free survival using an additive and a dominant model of inheritance and with overall survival under a dominant model of inheritance, respectively. 3.5. Results from in silico analysis To estimate the pathogenicity of the two missense variants rs975263 (Ser515Leu) and rs3735615 (Arg804Thr) in silico bioinformatic tools ‘sorting intol-
Fig. 1. Kaplan–Meier curves of included SNPs are shown for (A) event-free survival and (B) overall survival. P-values were calculated by Log– rank tests.
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Table 2 Association of rs1990172, rs975263 and rs3735615 with event-free survival and overall survival. SNP
rs1990172
Genetic model
Additive Dominant Recessive
rs975263
Additive Dominant Recessive
rs3735615
Additive Dominant Recessive
Adjustment model
Event-free survival HR
[95%CI]
Overall survival P-value*
P-value**
HR
[95%CI]
P-value*
P-value**
Model Model Model Model Model Model
1 2 1 2 1 2
2.35 2.26 3.93 4.19 2.78 2.26
1.37–4.04 1.30–3.91 1.54–10.02 1.61–10.93 1.03–7.52 0.76–6.76
0.002 0.004 0.004 0.003 0.044 0.144
0.012 0.024 0.024 0.018 0.264 0.864
2.85 3.13 5.54 9.35 3.63 3.63
1.46–5.58 1.62–6.05 1.56–19.74 2.38–36.76 1.11–11.49 1.11–11.89
0.002 0.001 0.008 0.001 0.029 0.033
0.012 0.006 0.048 0.006 0.174 0.198
Model Model Model Model Model Model
1 2 1 2 1 2
2.25 2.17 2.71 2.87 3.61 3.02
1.30–3.90 1.23–3.82 1.16–6.23 1.22–6.75 1.33–9.81 0.99–9.23
0.004 0.007 0.019 0.016 0.012 0.052
0.024 0.042 0.114 0.096 0.072 0.312
2.55 2.80 2.71 3.99 5.19 5.09
1.29–5.07 1.42–5.51 0.98–7.50 1.37–11.60 1.56–16.89 1.46–17.75
0.007 0.003 0.055 0.011 0.006 0.011
0.042 0.018 0.330 0.066 0.036 0.066
Model Model Model Model Model Model
1 2 1 2 1 2
0.30 0.25 0.24 0.19 0.22 0.18
0.14–0.64 0.12–0.55 0.10–0.56 0.08–0.46 0.03–1.60 0.03–1.37
0.002 0.001 0.001 >0.001 0.134 0.098
0.012 0.006 0.006 0.002 0.804 0.588
0.31 0.16 0.21 0.09 0.32 0.22
0.12–0.78 0.06–0.47 0.07–0.65 0.03–0.32 0.04–2.44 0.03–1.70
0.013 0.001 0.007 >0.001 0.272 0.147
0.078 0.006 0.042 0.001 1.000 0.882
Association of included MACC1 SNPs with event-free survival and overall survival are given for additive, dominant, and recessive genetic models of inheritance. Hazard ratios (HR) and 95% confidence intervals (95% CI) were obtained from univariate Cox regression analysis (model 1) and multivariate Cox regression analysis (model 2) adjusting for age at cancer diagnosis and TNM stage. * P-value, nominal. ** P-value, adjusted for multiplicity using Bonferroni correction.
erant from tolerant’ (SIFT; http://sift.jcvi.org) [29] and ‘polymorphism phenotyping v2’ (PolyPhen-2; http:// genetics.bwh.harvard.edu/pph2) [30] were used. SIFT predicts substitutions with scores less than 0.05 as deleterious and PolyPhen-2 scores are evaluated as 0.000 (most probably benign) to 0.999 (most probably damaging). SIFT and PolyPhen in silico analysis of rs975263 did not indicate a major impact of this variant on protein structure or function (SIFT-score = 0.035; PolyPhenscore = 0.014). Otherwise, MACC1 SNP rs3735615 was predicted to exert a probably damaging effect in both in silico bioinformatic tools (SIFT-score = 0.003; PolyPhen-score = 0.999). 4. Discussion This is the first study investigating the influence of MACC1 polymorphisms on clinical outcome of HER2 positive breast cancer patients until now. The most important finding is that several MACC1 polymorphisms demonstrate significant association with the prognosis of HER2-positive breast cancer patients. Our observation is well in line with previous findings by our group [24] demonstrating significant impact of MACC1 variant rs1990172 on overall survival in colorectal cancer. Variant rs1990172 is located within intron 2 of the MACC1 gene and does not affect any splice site of a coding exon [24]. Therefore, it remains unclear, if rs1990172 is the causative SNP responsible for the
observed effects. The non-synonymous variant rs975263 (Leu515Ser) is closely linked to rs1990172 and might exert causal effects on MACC1 protein function. However, in silico analysis did not suggest an adverse impact of this amino acid substitution on the structure or function of the MACC1 protein. Further, the observed correlation between rs975263 and breast cancer survival did not surpass the impact of rs1990172 on breast cancer survival, indicating that the significant association between rs975263 and breast cancer prognosis is due to its close linkage to rs1990172 and not vice versa. Additional studies, such as fine mapping studies and directed functional studies to determine the molecular consequences of this genetic variation are needed. Further, our study showed a protective effect of the missense genetic variant rs3735615 on breast cancer survival. The variant is located in an evolutionary conserved position and bioinformatic tools SIFT and PolyPhen both indicate a major damaging effect of rs3735615 on MACC1 protein structure or function. In vitro studies have shown that overexpression of MACC1 leads to upregulation of cMET mRNA expression [17,18]. High levels of cMET in breast carcinoma have been correlated with histological grade, high proliferative cell index, a greater incidence of metastases and shorter survival rates [10,11,31–33]. Consequently, low levels of cMET lead to more a favourable prognosis in breast cancer patients. A dysfunctional MACC1 protein may activate cMET transcription to a much lesser extent
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than a normal functional MACC1 protein. Therefore, it can be hypothesised that the observed protective effect of rs3735615 on breast cancer survival is due to a less functional MACC1 protein caused by the genetic variant, limiting cMET expression and as a consequence metastatic potential of cancer cells. Notably, altered expression of cMET is of particular importance in HER2 positive tumours as cMET and HER2 have been shown to synergize in promoting cellular invasion, suggesting that tumours that express both receptors may be more aggressive [34]. Furthermore, increased expression of other tyrosine kinases such as cMET in HER2 positive tumours may influence sensitivity to anti-HER2 agents. Indeed, it has been shown that sensitisation to trastuzumab is influenced by cMET activity in HER2 positive breast tumour cells [35]. Additionally, high gene copy numbers of cMET have been associated with an increased risk of trastuzumab-based therapy failure in HER2-positive metastatic breast cancer patients [16]. Consequently, the important role of HGF/cMET pathway activation in human cancer has affected drug development. Clinical studies of the therapeutic efficacy of biologic antagonists, low molecular weight synthetic compounds or small molecule inhibitors directed to target either ligand binding or receptor activation are ongoing and some are already in phase III trials [36,37]. It is a well known fact that the major determinant of responsiveness to targeted therapeutics is the presence of a constitutively hyperactive form of the druggable molecule, which usually occurs as a consequence of genetic abnormalities such as point mutations, gene amplification or chromosomal translocation [38]. In a similar way, aberrant gene expression of the target molecule due to disordered transcriptional activation may affect treatment response. Functional SNPs at the MACC1 locus associated with altered MACC1 activity or function may influence cMET transcription and, therefore, may act as easily detectable predictive markers in anti-HGF/MET treatment in the future. All three included MACC1 variants were significantly associated with chemotherapy. Chemotherapy correlates with tumour aggressiveness, indicated by increased tumour stage, positive lymph node involvement, negative hormone receptor status and pre-menopausal status, and is often not indicated in some cases of less aggressive tumours. Therefore, it could be speculated that MACC1 SNPs might be associated with tumour aggressiveness. However, none of included MACC1 SNPs were significantly associated with one of the individual factors indicating tumour aggressiveness mentioned above, beside menopausal status for rs1990172. Therefore, the observed significant association between MACC1 SNPs and chemotherapy remains to be specified.
It should be noted, that a recent study by Schmid et al. [39] did not observe a significant association between several SNPs located in the coding region of the MACC1 gene and including variant rs3735615 (but not rs975263 and rs1990172) and survival in 154 patients with colorectal cancer. Differences between the two cohorts not only in tumour type, but also in the clinicopathological features including gender, age at diagnosis or tumour stages of included patients may have contributed to discordant results. Further, cohorts of breast cancer patients as well as cohorts of colorectal cancer patients are both of moderate sample size. Therefore, studies with larger sample sizes are needed to further clarify the association of the genetic diversity of the MACC1 locus on the clinical outcome of cancer patients. There are potential limitations of our study, which should be considered. As mentioned above, sample size of included study population is moderate. However, our study appears adequately powered to demonstrate observed hazard ratios of included SNPs. Further, it should be stressed that associations between included MACC1 polymorphisms and patients’ survival are all of high statistical significance and remained significant after correction for multiple testing. Clearly, replication of our observations in large independent studies is necessary to validate the prognostic relevance of MACC1 polymorphisms to the clinical outcome of breast or other types of cancer. The present study included only patients with HER2 positive breast cancer. Of note, breast cancer is a heterogeneous disease that is classified into several classes, traditionally based on status of oestrogen receptor, progesterone receptor, and HER2 or on gene expression profiles. These subtypes have different epidemiological risk factors, different natural histories, and different responses to systemic and local therapies [40]. Therefore, in breast cancer research it is important to consider the various distinct subtypes in order to properly assess the impact of predictive or prognostic biomarkers on clinical outcome. Concordantly, the present study focuses on cases within one subclass of breast cancer, that is, HER2 positive breast cancer. Further, due the recently described close association between increased HGF/ cMET signalling and resistance to anti-HER2 agents [16,35], HER2 positive breast cancer patients represent a group of special interest to investigate the impact of members of the HGF/MET signalling pathway, such as MACC1, on breast cancer prognosis. In summary, our study provides first evidence that MACC1 variants rs1990172, rs975263 and rs3735615 are associated with event-free as well as overall survival in HER2-positive breast cancer patients. Our observations are consistent with a previous study, noting that MACC1 variant rs1990172 significantly correlates with survival in colorectal cancer patients. The observed
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protective effect of rs3735615 on cancer prognosis is supported by data from in silico analysis attesting a damaging effect of the variant allele on protein function. Further studies are warranted to validate our findings. Funding The present study was part financed by the European Union’s European Regional Development Fund through the INTERREG IV Programme ‘AlpenrheinBodensee-Hochrhein’; Project Number: 179. Conflict of interest statement None declared. Acknowledgements We are grateful to Mr. John Christensen (Dornbirn, Austria) for proofreading our manuscript. The present study was part financed by the European Union’s European Regional Development Fund through the INTERREG IV program ‘Alpenrhein-BodenseeHochrhein’; Project Number: 179. The sponsors had no involvements in the study design, in the collection, analysis and interpretation of data or the writing of the manuscript or in the decision to submit the manuscript for publication. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/ 10.1016/j.ejca.2014.05.007. References [1] Christofori G. New signals from the invasive front. Nature 2006;441:444–50. [2] Birchmeier C, Birchmeier W, Gherardi E, Vande Woude GF. Met, metastasis, motility and more. Nat Rev Mol Cell Biol 2003;4:915–25. [3] Boccaccio C, Comoglio PM. Invasive growth: a MET-driven genetic programme for cancer and stem cells. Nat Rev Cancer 2006;6:637–45. [4] Xiao GH, Jeffers M, Bellacosa A, Mitsuuchi Y, Vande Woude GF, Testa JR. Anti-apoptotic signaling by hepatocyte growth factor/Met via the phosphatidylinositol 3-kinase/Akt and mitogen-activated protein kinase pathways. Proc Natl Acad Sci U S A 2001;98:247–52. [5] Ponzetto C, Bardelli A, Zhen Z, et al. A multifunctional docking site mediates signaling and transformation by the hepatocyte growth factor/scatter factor receptor family. Cell 1994;77:261–71. [6] Seiden-Long IM, Brown KR, Shih W, et al. Transcriptional targets of hepatocyte growth factor signaling and Ki-ras oncogene activation in colorectal cancer. Oncogene 2006;25:91–102. [7] Brinkmann V, Foroutan H, Sachs M, Weidner KM, Birchmeier W. Hepatocyte growth factor/scatter factor induces a variety of tissue-specific morphogenic programs in epithelial cells. J Cell Biol 1995;131:1573–86.
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[8] Silvagno F, Follenzi A, Arese M, et al. In vivo activation of met tyrosine kinase by heterodimeric hepatocyte growth factor molecule promotes angiogenesis. Arterioscler Thromb Vasc Biol 1995;15:1857–65. [9] Stoker M, Gherardi E, Perryman M, Gray J. Scatter factor is a fibroblast-derived modulator of epithelial cell mobility. Nature 1987;327:239–42. [10] Raghav KP, Wang W, Liu S, et al. CMET and phospho-cMET protein levels in breast cancers and survival outcomes. Clin Cancer Res 2012;18:2269–77. [11] Beviglia L, Matsumoto K, Lin CS, Ziober BL, Kramer RH. Expression of the c-Met/HGF receptor in human breast carcinoma: correlation with tumor progression. Int J Cancer 1997;74:301–9. [12] Agarwal S, Zerillo C, Kolmakova J, et al. Association of constitutively activated hepatocyte growth factor receptor (Met) with resistance to a dual EGFR/Her2 inhibitor in non-small-cell lung cancer cells. Br J Cancer 2009;100:941–9. [13] Sawada K, Radjabi AR, Shinomiya N, et al. C-Met overexpression is a prognostic factor in ovarian cancer and an effective target for inhibition of peritoneal dissemination and invasion. Cancer Res 2007;67:1670–9. [14] Taniguchi K, Yonemura Y, Nojima N, et al. The relation between the growth patterns of gastric carcinoma and the expression of hepatocyte growth factor receptor (c-met), autocrine motility factor receptor, and urokinase-type plasminogen activator receptor. Cancer 1998;82:2112–22. [15] Kammula US, Kuntz EJ, Francone TD, et al. Molecular coexpression of the c-Met oncogene and hepatocyte growth factor in primary colon cancer predicts tumor stage and clinical outcome. Cancer Lett 2007;248:219–28. [16] Minuti G, Cappuzzo F, Duchnowska R, et al. Increased MET and HGF gene copy numbers are associated with trastuzumab failure in HER2-positive metastatic breast cancer. Br J Cancer 2012;107:793–9. [17] Stein U, Walther W, Arlt F, et al. MACC1, a newly identified key regulator of HGF-MET signaling, predicts colon cancer metastasis. Nat Med 2009;15:59–67. [18] Stein U, Smith J, Walther W, Arlt F. MACC1 controls Met: what a difference an Sp1 site makes. Cell Cycle 2009;8:2467–9. [19] Shirahata A, Sakata M, Kitamura Y, et al. MACC 1 as a marker for peritoneal-disseminated gastric carcinoma. Anticancer Res 2010;30:3441–4. [20] Wang L, Wu Y, Lin L, et al. Metastasis-associated in colon cancer-1 upregulation predicts a poor prognosis of gastric cancer, and promotes tumor cell proliferation and invasion. Int J Cancer 2013;133:1419–30. [21] Shimokawa H, Uramoto H, Onitsuka T, et al. Overexpression of MACC1 mRNA in lung adenocarcinoma is associated with postoperative recurrence. J Thorac Cardiovasc Surg 2011;141:895–8. [22] Yang YP, Qu JH, Chang XJ, et al. High intratumoral metastasisassociated in colon cancer-1 expression predicts poor outcomes of cryoablation therapy for advanced hepatocellular carcinoma. J Transl Med 2013;11:41. [23] Huang Y, Zhang H, Cai J, et al. Overexpression of MACC1 and its significance in human breast cancer progression. Cell Biosci 2013;3:16. [24] Lang AH, Geller-Rhomberg S, Winder T, et al. A common variant of the MACC1 gene is significantly associated with overall survival in colorectal cancer patients. BMC Cancer 2012;12:20. [25] Zheng Z, Gao S, Yang Z, et al. Single nucleotide polymorphisms in the metastasis-associated in colon cancer-1 gene predict the recurrence of hepatocellular carcinoma after transplantation. Int J Med Sci 2014;11:142–50. [26] Stein U, Dahlmann M, Walther W. MACC1 – more than metastasis? Facts and predictions about a novel gene. J Mol Med 2010;88:11–8.
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[27] Edge SB, Byrd DR, Compton CC. AJCC Cancer Staging Manual. ed 7. Chicago, IL: Springer; 2009. [28] Dupont WD, Plummer Jr WD. Power and sample size calculations. A review and computer program. Control Clin Trials 1990;11:116–28. [29] Kumar P, Henikoff S, Ng PC. Predicting the effects of coding nonsynonymous variants on protein function using the SIFT algorithm. Nat Protoc 2009;4:1073–81. [30] Adzhubei IA, Schmidt S, Peshkin L, et al. A method and server for predicting damaging missense mutations. Nat Methods 2010;7:248–9. [31] Edakuni G, Sasatomi E, Satoh T, Tokunaga O, Miyazaki K. Expression of the hepatocyte growth factor/c-Met pathway is increased at the cancer front in breast carcinoma. Pathol Int 2001;51:172–8. [32] Garcia S, Dales JP, Charafe-Jauffret E, et al. Overexpression of cMet and of the transducers PI3K, FAK and JAK in breast carcinomas correlates with shorter survival and neoangiogenesis. Int J Oncol 2007;31:49–58. [33] Garcia S, Dales JP, Charafe-Jauffret E, et al. Poor prognosis in breast carcinomas correlates with increased expression of targetable CD146 and c-Met and with proteomic basal-like phenotype. Hum Pathol 2007;38:830–41.
[34] Khoury H, Naujokas MA, Zuo D, et al. HGF converts ErbB2/ Neu epithelial morphogenesis to cell invasion. Mol Biol Cell 2005;16:550–61. [35] Shattuck DL, Miller JK, Carraway 3rd KL, Sweeney C. Met receptor contributes to trastuzumab resistance of Her2-overexpressing breast cancer cells. Cancer Res. 2008;68:1471–7. [36] Blumenschein Jr GR, Mills GB, Gonzalez-Angulo AM. Targeting the hepatocyte growth factor-cMET axis in cancer therapy. J Clin Oncol 2012;30:3287–96. [37] Cecchi F, Rabe DC, Bottaro DP. Targeting the HGF/Met signalling pathway in cancer. Eur J Cancer 2010;46:1260–70. [38] Galimi F, Torti D, Sassi F, et al. Genetic and expression analysis of MET, MACC1 and HGF in metastatic colorectal cancer: Response to Met inhibition in patient xenografts and pathological correlations. Clin Cancer Res 2011;17:3146–56. [39] Schmid F, Burock S, Klockmeier K, Schlag PM, Stein U. SNPs in the coding region of the metastasis-inducing gene MACC1 and clinical outcome in colorectal cancer. Mol Cancer 2012;11:49. [40] Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thurlimann B, Senn HJ. Strategies for subtypes – dealing with the diversity of breast cancer: highlights of the St. Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011. Ann Oncol 2011;22:1736–47.
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Significant survival impact of MACC1 polymorphisms in HER2 positive breast cancer patients Axel Muendlein a,c, Michael Hubalek e, Simone Geller-Rhomberg a,c, Klaus Gasser a,b,c, Thomas Winder a,b,c, Heinz Drexel a,b,c, Thomas Decker d, Elisabeth Mueller-Holzner e, Martina Chamson e, Christian Marth e, Alois H. Lang a,b,⇑ a
Vorarlberg Institute for Vascular Investigation and Treatment, 6800 Feldkirch, Austria Department of Medicine and Cardiology, Academic Teaching Hospital Feldkirch, 6800 Feldkirch, Austria c Private University of the Principality of Liechtenstein, 9495 Triesen, Liechtenstein d Studienzentrum Onkologie Ravensburg, 88212 Ravensburg, Germany e Department of Obstetrics and Gynecology, Innsbruck Medical University, 6020 Innsbruck, Austria b
Received 8 January 2014; received in revised form 10 April 2014; accepted 9 May 2014
KEYWORDS Breast neoplasms Survival MACC1 Polymorphism Single nucleotide
Abstract Background: Deregulation of hepatocyte growth factor (HGF)/mesenchymalepithelial transition factor (MET) signalling has been associated with poor clinical outcome in breast cancer and other cancers. The recently discovered metastasis-associated in colon cancer-1 (MACC1) gene is a key regulator of the HGF/MET pathway. Potential links between genetic variants of the MACC1 gene and survival in breast cancer patients are unknown. In the present study, we therefore aimed to investigate the influence of MACC1 polymorphisms on event-free and overall survival in patients with human epidermal growth factor 2 (HER2)-positive breast cancer. Methods: The present study included 164 consecutive white patients with HER2-positive breast cancer. Three MACC1 polymorphisms, rs1990172, rs975263 and rs3735615, already associated with cancer prognosis or with potential functional effects, were genotyped by the 50 nuclease assay. Results: Multivariate Cox regression analysis adjusted for age and tumour stage showed increased risk for progression or death for carriers of the rare allele (G-allele) of single nucleotide polymorphism (SNP) rs1990172 (hazard ratios (HR) = 2.26; p = 0.004 and HR = 3.13; p = 0.001 for event-free survival and overall survival, respectively). In addition, we were able to demonstrate an adverse effect on cancer prognosis for carriers of the rare allele (T-allele) of SNP rs975263 (HR = 2.17; p = 0.007 and HR = 2.80; p = 0.003 for event-free survival and
⇑ Corresponding author at: Department of Medicine and Cardiology, Academic Teaching Hospital Feldkirch, 6807 Feldkirch, Austria. Tel.: +43 5572 3032301; fax: +43 5572 3037511. E-mail address: [email protected] (A.H. Lang).
http://dx.doi.org/10.1016/j.ejca.2014.05.007 0959-8049/Ó 2014 Elsevier Ltd. All rights reserved.
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overall survival, respectively). The rare allele (C-allele) of SNP rs3735615 showed a significant protective impact on event-free survival as well as overall survival (HR = 0.25; p = 0.001, and HR = 0.16; p = 0.001, respectively). Conclusions: This study provides first evidence that MACC1 polymorphisms are associated with clinical outcome for HER2-positive breast cancer patients. Further studies are warranted to validate these findings. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Metastatic dissemination of primary tumours is the leading cause of cancer-associated deaths. Although local invasion and the formation of metastases are clinically the most relevant of all the processes involved in carcinogenesis, they are the least well understood at the molecular level [1]. The hepatocyte growth factor (HGF)/mesenchymal-epithelial transition factor (cMET) signalling complex is known to activate a number of signalling pathways that contribute to the invasion and metastasis of a primary tumour [2,3]. cMET is a tyrosine kinase receptor and HGF is the only known ligand so far. HGF binding to cMET leads to formation of phosphorylated cMET, which activates downstream effectors such as phosphatidylinositol 3-kinase (PI3K/ AKT), mitogen-activated protein kinase (ERK/MAPK) and signal transducer and activator of transcription (STATs) pathways [4–6]. Through these cellular signalling pathways HGF/cMET interaction plays a key role in cellular proliferation, survival, migration and invasion [7–9]. Dysregulation of cMET is strongly associated with tumour progression and adverse survival outcomes in breast cancer [10,11] and other cancers such as colon cancer, non-small-cell lung cancer, ovarian cancer, and gastric cancer [12–15]. Interestingly, a recent study by Minuti et al. [16] provides evidence for a critical role of HGF/MET signalling pathway for sensitivity to anti-human epidermal growth factor 2 (HER2) agents. High gene copy numbers of cMET and HGF correlate with an increased risk of trastuzumab-based therapy failure in HER2-positive metastatic breast cancer patients. The recently identified metastasis-associated in colon cancer-1 (MACC1) gene acts as a key regulator of cMET expression [17,18] entering the HGF/cMET signalling complex upstream of cMET. MACC1 was first identified by Stein et al. [17] to be overexpressed in primary and metastatic tumour specimens of colon cancer as compared to normal colon mucosa and was associated with colon cancer metastasis and reduced metastasis-free survival. Subsequent studies have shown that overexpression of MACC1 correlates positively with poor clinical outcome in patients with gastric cancer [19,20], lung adenocarcinoma [21], hepatocellular carcinoma [22] and breast cancer [23].
Single nucleotide polymorphisms (SNPs) may contribute to altered MACC1 expression or function and consequently may influence the prognosis of cancer. Recently, our group reported a significant association of the MACC1 tagging SNP rs1990172 with reduced overall survival in colorectal cancer patients [24]. The variant is in linkage disequilibrium with a non-synonymous SNP, rs975263 (Leu515Ser), which may exert a causal effect on MACC1 protein function or structure. Notably, both SNPs have been associated with a poor prognosis of hepatocellular carcinoma patients [25]. Another missense genetic variant, rs3735615 (Arg804Thr), lies in an evolutionary conserved region and might have therefore a decisive role on the effectiveness of MACC1 [26]. In the present study, we aimed to investigate the influence of the MACC1 polymorphisms rs1990172, rs975263 and rs3735615 on event-free and overall survival in patients with HER2-positive breast cancer. 2. Methods 2.1. Patients Formalin-fixed paraffin embedded (FFPE) tissue samples of 164 consecutive white patients with HER2positive breast cancer treated between 2000 and 2010 at the Department of Gynecology and Obstetrics, Medical University of Innsbruck, Austria, were available for the present study. HER2-positivity was diagnosed in cases with an immunohistochemistical score of 3+. In cases scored with 2+ positivity, fluorescence in situ hybridisation (FISH) or silver in situ hybridisation (SISH) analysis has been performed to demonstrate overexpression of the HER-2 gene. Tumours were classified according to the guidelines of the American Joint Committee on Cancer (AJCC) staging system [27]. Event-free survival was calculated as the time from cancer diagnosis to either relapse or death from any cause or the last follow up, at which point data were collected. Overall survival was measured from time from cancer diagnosis until final follow-up or death from any cause. The ethics committee of Innsbruck Medical University approved the present study and written informed consent was obtained from all patients in accordance with the Declaration of Helsinki.
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2.2. Genotyping Genomic DNA was extracted from sections of archived formalin-fixed paraffin embedded tissue blocks using the QIAamp DNA FFPE Tissue Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Genotyping of MACC1 variants rs1990172, rs975263 and rs3735615 was carried out by the 50 nuclease assay using TaqManÒ MGB probes on a LightCyclerÒ 480 Real-Time PCR System (F. Hoffmann-La Roche Ltd, Basel, Switzerland). TaqManÒ MGB probes were provided together with corresponding PCR primers by the Assay-on-demande service (Applied Biosystems, Forster City, CA) for rs1990172 and rs3735615 (order numbers: C_2632417_10 and C_27489506_10, respectively) and by the Assay-by-designe service (Applied Biosystems) for rs975263 (catalogue number: 4332077). The 50 nuclease assay was performed in a 15 ll volume, comprising 10–30 ng genomic DNA, 1 TaqManÒ Genotyping PCR Master Mix (Applied Biosystems), and 1 primer/ probe mix under the following amplification conditions: 10 min at 95 °C and 45 cycles at 92 °C for 15 s and 60 °C for 1 min. Reference controls as well as nontemplate controls were included in each run. Genotypes were automatically determined by LightCyclerÒ software 1.5 followed by a visual control of accurate genotype classification.
2.3. Statistical analysis Differences in categorical study variables between genotypes were tested for statistical significance with the Chi-squared test. For continuous variables analysis of variance (ANOVA) was applied. Hazard ratios and 95% confidence intervals (CI) of the hazard ratios were derived from univariate and multivariate Cox proportional hazards models. Survival curves were generated using the Kaplan–Meier method and compared using the Log–Rank–Mantel–Cox-Test. Observed numbers of each genotype were compared with those expected to test whether the sample was in Hardy–Weinberg equilibrium using the Chi-Square test with one degree of freedom. To test for multiplicity Bonferroni correction was used. P-values 6 0.05 were considered as significant. Statistical analyses were performed with the software package SPSS 11.5 for Windows (SPSS, Inc., Chicago, IL, USA). Statistical power analysis was performed using the Power and Sample Size Program [28] under an additive model of inheritance. On the basis of minor allele frequencies of 40% on average of included SNPs given in the NCBI SNP database (http://www.ncbi.nlm.nih.gov/snp/) and assuming a median survival time of 4 years of controls (carriers of the common alleles) and a median follow up period of 4.2 years, power analysis indicated that 160 patients would be needed to
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demonstrate a hazard ratio of 0.60 or 1.85 for the respective rare alleles at an alpha fault of 0.01 with a power of 80%. 3. Results 3.1. Patient characteristics The patient characteristics at baseline are given in table 1. Over a median follow up period of 4.2 years, 25 events (relapse or death) and 16 deaths, respectively, were recorded. About a third of patients did not receive trastuzumab because at that time the agent was not approved in the adjuvant setting yet. As soon as the approval was given all subsequent patients were treated with trastuzumab. Among given patient characteristics, AJCC stage was significantly associated with event-free survival (p = 0.042). Age at cancer diagnosis and AJCC stage were significantly associated with overall survival (p = 0.027 and p = 0.002, respectively). Other given patient characteristics were not associated with eventfree or overall survival (all p-values > 0.05). 3.2. Results from genotyping Observed genotyping frequencies as well as results from Hardy–Weinberg disequilibrium analysis are presented in Supplementary Table S1. MACC1 SNP genotype frequencies did not deviate significantly from Hardy–Weinberg. Pairwise squared correlation coefficients were r2 = 0.749 between SNP rs1990172 and rs975263, r2 = 0.227 between SNP rs1990172 and rs3735615 and r2 = 0.191 between SNP rs3735615 and rs975263. 3.3. Association of MACC1 SNP genotypes with clinicopathological patient characteristics Association MACC1 polymorphisms with clinicopathological features are presented in Supplementary Tables S2(a–c). MACC1 variant rs1990172 was significantly associated with menopausal status (p = 0.041). All three SNPs were significantly associated with chemotherapy (p = 0.006, p = 0.008, and p = 0.026 for rs1990172, rs975263 and rs3735615, respectively). No other significant associations between determined MACC1 SNPs and other clinical or pathological characteristics could be observed (all p-values > 0.05). 3.4. Association of MACC1 SNPs with survival Kaplan–Meier curves for event-free survival and overall survival according to genotypes (homozygous common allele, heterozygous, homozygous rare allele) of included MACC1 SNPs are shown in Fig. 1. Genotypes compassing rare alleles of SNP rs1990172 (GC,
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Table 1 Patient characteristics. Characteristic Age (years) Menopausal status Lymph node involvement* AJCC stage*
Histological grade*
Hormone receptor status Radiotherapy* Chemotherapy Hormone therapy* Trastuzumab therapy*
n Mean (±SD) Median (range) Pre Post Negative Positive I II III IV G1 G2 G3 ER+ or PR+ ER and PR No Yes No Yes No Yes No Yes
%
58.5 (±14.2) 59.4 (31.9–90.7) 51 31.1 113 68.9 103 62.8 57 34.8 85 54.8 55 34.2 20 12.6 1 0.6 22 13.4 109 66.5 23 14.0 121 73.8 43 26.2 77 48.7 81 51.3 80 48.8 84 51.2 56 34.8 105 65.2 37 36.3 65 63.7
* Lymph node involvement, missing samples: n = 4; AJCC stage, missing samples: n = 3; grade score, missing samples: n = 10, radiotherapy, missing samples: n = 6; hormone therapy, missing samples: n = 3; trastuzumab therapy, missing samples: n = 62. Tumours were classified according to the guidelines of the American Joint Committee on Cancer (AJCC) staging system.
GG) and SNP rs975263 (CT, TT), respectively, showed a significant increased risk for progression or death. Otherwise, genotypes compassing rare alleles of SNP rs3735615 (CC, GC) showed a significant protective impact on event-free survival as well as overall survival. Univariate and multivariate Cox regression analysis, adjusting for tumour, node, metastasis (TNM) stage and age, were used to further investigate the impact of included MACC1 variants on event-free survival and overall survival using an additive, dominant and recessive model of inheritance, respectively. Results are presented in Table 2. After adjustment for multiple testing using Bonferroni correction and in univariate as well as multivariate Cox regression analysis, SNP rs1990172 remained significantly associated with eventfree survival and overall survival using an additive and a dominant model of inheritance; SNP rs975263 remained significantly associated with event-free survival and overall survival by an additive model of inheritance; SNP rs3735615 remained significantly associated with event-free survival using an additive and a dominant model of inheritance and with overall survival under a dominant model of inheritance, respectively. 3.5. Results from in silico analysis To estimate the pathogenicity of the two missense variants rs975263 (Ser515Leu) and rs3735615 (Arg804Thr) in silico bioinformatic tools ‘sorting intol-
Fig. 1. Kaplan–Meier curves of included SNPs are shown for (A) event-free survival and (B) overall survival. P-values were calculated by Log– rank tests.
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Table 2 Association of rs1990172, rs975263 and rs3735615 with event-free survival and overall survival. SNP
rs1990172
Genetic model
Additive Dominant Recessive
rs975263
Additive Dominant Recessive
rs3735615
Additive Dominant Recessive
Adjustment model
Event-free survival HR
[95%CI]
Overall survival P-value*
P-value**
HR
[95%CI]
P-value*
P-value**
Model Model Model Model Model Model
1 2 1 2 1 2
2.35 2.26 3.93 4.19 2.78 2.26
1.37–4.04 1.30–3.91 1.54–10.02 1.61–10.93 1.03–7.52 0.76–6.76
0.002 0.004 0.004 0.003 0.044 0.144
0.012 0.024 0.024 0.018 0.264 0.864
2.85 3.13 5.54 9.35 3.63 3.63
1.46–5.58 1.62–6.05 1.56–19.74 2.38–36.76 1.11–11.49 1.11–11.89
0.002 0.001 0.008 0.001 0.029 0.033
0.012 0.006 0.048 0.006 0.174 0.198
Model Model Model Model Model Model
1 2 1 2 1 2
2.25 2.17 2.71 2.87 3.61 3.02
1.30–3.90 1.23–3.82 1.16–6.23 1.22–6.75 1.33–9.81 0.99–9.23
0.004 0.007 0.019 0.016 0.012 0.052
0.024 0.042 0.114 0.096 0.072 0.312
2.55 2.80 2.71 3.99 5.19 5.09
1.29–5.07 1.42–5.51 0.98–7.50 1.37–11.60 1.56–16.89 1.46–17.75
0.007 0.003 0.055 0.011 0.006 0.011
0.042 0.018 0.330 0.066 0.036 0.066
Model Model Model Model Model Model
1 2 1 2 1 2
0.30 0.25 0.24 0.19 0.22 0.18
0.14–0.64 0.12–0.55 0.10–0.56 0.08–0.46 0.03–1.60 0.03–1.37
0.002 0.001 0.001 >0.001 0.134 0.098
0.012 0.006 0.006 0.002 0.804 0.588
0.31 0.16 0.21 0.09 0.32 0.22
0.12–0.78 0.06–0.47 0.07–0.65 0.03–0.32 0.04–2.44 0.03–1.70
0.013 0.001 0.007 >0.001 0.272 0.147
0.078 0.006 0.042 0.001 1.000 0.882
Association of included MACC1 SNPs with event-free survival and overall survival are given for additive, dominant, and recessive genetic models of inheritance. Hazard ratios (HR) and 95% confidence intervals (95% CI) were obtained from univariate Cox regression analysis (model 1) and multivariate Cox regression analysis (model 2) adjusting for age at cancer diagnosis and TNM stage. * P-value, nominal. ** P-value, adjusted for multiplicity using Bonferroni correction.
erant from tolerant’ (SIFT; http://sift.jcvi.org) [29] and ‘polymorphism phenotyping v2’ (PolyPhen-2; http:// genetics.bwh.harvard.edu/pph2) [30] were used. SIFT predicts substitutions with scores less than 0.05 as deleterious and PolyPhen-2 scores are evaluated as 0.000 (most probably benign) to 0.999 (most probably damaging). SIFT and PolyPhen in silico analysis of rs975263 did not indicate a major impact of this variant on protein structure or function (SIFT-score = 0.035; PolyPhenscore = 0.014). Otherwise, MACC1 SNP rs3735615 was predicted to exert a probably damaging effect in both in silico bioinformatic tools (SIFT-score = 0.003; PolyPhen-score = 0.999). 4. Discussion This is the first study investigating the influence of MACC1 polymorphisms on clinical outcome of HER2 positive breast cancer patients until now. The most important finding is that several MACC1 polymorphisms demonstrate significant association with the prognosis of HER2-positive breast cancer patients. Our observation is well in line with previous findings by our group [24] demonstrating significant impact of MACC1 variant rs1990172 on overall survival in colorectal cancer. Variant rs1990172 is located within intron 2 of the MACC1 gene and does not affect any splice site of a coding exon [24]. Therefore, it remains unclear, if rs1990172 is the causative SNP responsible for the
observed effects. The non-synonymous variant rs975263 (Leu515Ser) is closely linked to rs1990172 and might exert causal effects on MACC1 protein function. However, in silico analysis did not suggest an adverse impact of this amino acid substitution on the structure or function of the MACC1 protein. Further, the observed correlation between rs975263 and breast cancer survival did not surpass the impact of rs1990172 on breast cancer survival, indicating that the significant association between rs975263 and breast cancer prognosis is due to its close linkage to rs1990172 and not vice versa. Additional studies, such as fine mapping studies and directed functional studies to determine the molecular consequences of this genetic variation are needed. Further, our study showed a protective effect of the missense genetic variant rs3735615 on breast cancer survival. The variant is located in an evolutionary conserved position and bioinformatic tools SIFT and PolyPhen both indicate a major damaging effect of rs3735615 on MACC1 protein structure or function. In vitro studies have shown that overexpression of MACC1 leads to upregulation of cMET mRNA expression [17,18]. High levels of cMET in breast carcinoma have been correlated with histological grade, high proliferative cell index, a greater incidence of metastases and shorter survival rates [10,11,31–33]. Consequently, low levels of cMET lead to more a favourable prognosis in breast cancer patients. A dysfunctional MACC1 protein may activate cMET transcription to a much lesser extent
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than a normal functional MACC1 protein. Therefore, it can be hypothesised that the observed protective effect of rs3735615 on breast cancer survival is due to a less functional MACC1 protein caused by the genetic variant, limiting cMET expression and as a consequence metastatic potential of cancer cells. Notably, altered expression of cMET is of particular importance in HER2 positive tumours as cMET and HER2 have been shown to synergize in promoting cellular invasion, suggesting that tumours that express both receptors may be more aggressive [34]. Furthermore, increased expression of other tyrosine kinases such as cMET in HER2 positive tumours may influence sensitivity to anti-HER2 agents. Indeed, it has been shown that sensitisation to trastuzumab is influenced by cMET activity in HER2 positive breast tumour cells [35]. Additionally, high gene copy numbers of cMET have been associated with an increased risk of trastuzumab-based therapy failure in HER2-positive metastatic breast cancer patients [16]. Consequently, the important role of HGF/cMET pathway activation in human cancer has affected drug development. Clinical studies of the therapeutic efficacy of biologic antagonists, low molecular weight synthetic compounds or small molecule inhibitors directed to target either ligand binding or receptor activation are ongoing and some are already in phase III trials [36,37]. It is a well known fact that the major determinant of responsiveness to targeted therapeutics is the presence of a constitutively hyperactive form of the druggable molecule, which usually occurs as a consequence of genetic abnormalities such as point mutations, gene amplification or chromosomal translocation [38]. In a similar way, aberrant gene expression of the target molecule due to disordered transcriptional activation may affect treatment response. Functional SNPs at the MACC1 locus associated with altered MACC1 activity or function may influence cMET transcription and, therefore, may act as easily detectable predictive markers in anti-HGF/MET treatment in the future. All three included MACC1 variants were significantly associated with chemotherapy. Chemotherapy correlates with tumour aggressiveness, indicated by increased tumour stage, positive lymph node involvement, negative hormone receptor status and pre-menopausal status, and is often not indicated in some cases of less aggressive tumours. Therefore, it could be speculated that MACC1 SNPs might be associated with tumour aggressiveness. However, none of included MACC1 SNPs were significantly associated with one of the individual factors indicating tumour aggressiveness mentioned above, beside menopausal status for rs1990172. Therefore, the observed significant association between MACC1 SNPs and chemotherapy remains to be specified.
It should be noted, that a recent study by Schmid et al. [39] did not observe a significant association between several SNPs located in the coding region of the MACC1 gene and including variant rs3735615 (but not rs975263 and rs1990172) and survival in 154 patients with colorectal cancer. Differences between the two cohorts not only in tumour type, but also in the clinicopathological features including gender, age at diagnosis or tumour stages of included patients may have contributed to discordant results. Further, cohorts of breast cancer patients as well as cohorts of colorectal cancer patients are both of moderate sample size. Therefore, studies with larger sample sizes are needed to further clarify the association of the genetic diversity of the MACC1 locus on the clinical outcome of cancer patients. There are potential limitations of our study, which should be considered. As mentioned above, sample size of included study population is moderate. However, our study appears adequately powered to demonstrate observed hazard ratios of included SNPs. Further, it should be stressed that associations between included MACC1 polymorphisms and patients’ survival are all of high statistical significance and remained significant after correction for multiple testing. Clearly, replication of our observations in large independent studies is necessary to validate the prognostic relevance of MACC1 polymorphisms to the clinical outcome of breast or other types of cancer. The present study included only patients with HER2 positive breast cancer. Of note, breast cancer is a heterogeneous disease that is classified into several classes, traditionally based on status of oestrogen receptor, progesterone receptor, and HER2 or on gene expression profiles. These subtypes have different epidemiological risk factors, different natural histories, and different responses to systemic and local therapies [40]. Therefore, in breast cancer research it is important to consider the various distinct subtypes in order to properly assess the impact of predictive or prognostic biomarkers on clinical outcome. Concordantly, the present study focuses on cases within one subclass of breast cancer, that is, HER2 positive breast cancer. Further, due the recently described close association between increased HGF/ cMET signalling and resistance to anti-HER2 agents [16,35], HER2 positive breast cancer patients represent a group of special interest to investigate the impact of members of the HGF/MET signalling pathway, such as MACC1, on breast cancer prognosis. In summary, our study provides first evidence that MACC1 variants rs1990172, rs975263 and rs3735615 are associated with event-free as well as overall survival in HER2-positive breast cancer patients. Our observations are consistent with a previous study, noting that MACC1 variant rs1990172 significantly correlates with survival in colorectal cancer patients. The observed
Please cite this article in press as: Muendlein A. et al., Significant survival impact of MACC1 polymorphisms in HER2 positive breast cancer patients, Eur J Cancer (2014), http://dx.doi.org/10.1016/j.ejca.2014.05.007
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protective effect of rs3735615 on cancer prognosis is supported by data from in silico analysis attesting a damaging effect of the variant allele on protein function. Further studies are warranted to validate our findings. Funding The present study was part financed by the European Union’s European Regional Development Fund through the INTERREG IV Programme ‘AlpenrheinBodensee-Hochrhein’; Project Number: 179. Conflict of interest statement None declared. Acknowledgements We are grateful to Mr. John Christensen (Dornbirn, Austria) for proofreading our manuscript. The present study was part financed by the European Union’s European Regional Development Fund through the INTERREG IV program ‘Alpenrhein-BodenseeHochrhein’; Project Number: 179. The sponsors had no involvements in the study design, in the collection, analysis and interpretation of data or the writing of the manuscript or in the decision to submit the manuscript for publication. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/ 10.1016/j.ejca.2014.05.007. References [1] Christofori G. New signals from the invasive front. Nature 2006;441:444–50. [2] Birchmeier C, Birchmeier W, Gherardi E, Vande Woude GF. Met, metastasis, motility and more. Nat Rev Mol Cell Biol 2003;4:915–25. [3] Boccaccio C, Comoglio PM. Invasive growth: a MET-driven genetic programme for cancer and stem cells. Nat Rev Cancer 2006;6:637–45. [4] Xiao GH, Jeffers M, Bellacosa A, Mitsuuchi Y, Vande Woude GF, Testa JR. Anti-apoptotic signaling by hepatocyte growth factor/Met via the phosphatidylinositol 3-kinase/Akt and mitogen-activated protein kinase pathways. Proc Natl Acad Sci U S A 2001;98:247–52. [5] Ponzetto C, Bardelli A, Zhen Z, et al. A multifunctional docking site mediates signaling and transformation by the hepatocyte growth factor/scatter factor receptor family. Cell 1994;77:261–71. [6] Seiden-Long IM, Brown KR, Shih W, et al. Transcriptional targets of hepatocyte growth factor signaling and Ki-ras oncogene activation in colorectal cancer. Oncogene 2006;25:91–102. [7] Brinkmann V, Foroutan H, Sachs M, Weidner KM, Birchmeier W. Hepatocyte growth factor/scatter factor induces a variety of tissue-specific morphogenic programs in epithelial cells. J Cell Biol 1995;131:1573–86.
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