Inmaculada De

Juan Ae

Eva Esteban

A E Sarai

Palanca Ae

Eva Barraga

Pascual Ae

Bolufer
email: bolufer_pas@gva.es

I De Juan

Á E Esteban

Á S Palanca

Á E Barraga

Á P Bolufer

High-resolution melting analysis for rapid screening of BRCA1 and BRCA2 Spanish mutations

Keywords: Hereditary breast and ovarian cancer, BRCA1, BRCA2, Screening, Mutations, High-resolution melting

The majority of BRCA1 and BRCA2 mutation detection procedures include screening methods, all of which are time-consuming. High-resolution melting (HRM) is a promising pre-screening method of gene scanning that combines simplicity and rapid identification of genetic variants. We evaluated HRM in the screening of BRCA1/2 Spanish mutations. We studied 40 BRCA1 and 47 BRCA2 DNA samples with different Spanish mutations. We included a group of 20 unknown DNAs from patients with sporadic breast cancer (BC). The assay was performed with the LightCycler Ò 480 Instrument (Roche). The HRM discriminates all the BRCA1/2 Spanish mutations studied from wild-type DNA. Besides, 54 out of 87 mutations were clearly differentiated from each other. In sporadic BC 11 polymorphisms and three unclassified variants were found in both genes. HRM is a valuable method for rapid screening of BRCA1/2 Spanish mutations and is capable of differentiating new genetic variants in PCR products.

Introduction

BRCA1 (OMIM#113705) [1] and BRCA2 (OMIM#600185) [2] are the two major genes responsible for hereditary breast (BC) and/or ovarian cancer (OC). In particular, BRCA1 accounts for 52% of hereditary breast cancer families, especially those with OC, and BRCA2 represents an additional 32%, including male BC [START_REF] Ford | Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families: the breast cancer linkage consortium[END_REF]. Females with BRCA1/2 deleterious mutations have a lifetime risk of 37-85% and 15-41% for BC and OC, respectively [START_REF] Ford | Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families: the breast cancer linkage consortium[END_REF][START_REF] Brose | Cancer risk estimates for BRCA1 mutation carriers identified in a risk evaluation program[END_REF].

In the Spanish population 51 different pathogenic mutations have been identified in BRCA1 and 50 in BRCA2 [START_REF] Bolufer | BRCA1 and BRCA2 mutations in patients with familial breast cancer[END_REF][START_REF] Dı ´ez | Analysis of BRCA1 and BRCA2 genes in spanish breast/ovarian cancer patients: a high proportion of mutations unique to spain and evidence of founder effects[END_REF][START_REF] Martı ´nez-Ferrandis | Mutational analysis of BRCA1 and BRCA2 in Mediterranean Spanish women with early-onset breast cancer: identification of three novel pathogenic mutations. human mutation; mutation in brief #659[END_REF][START_REF] Esteban | BRCA1 and BRCA2 mutations in families studied in the program of genetic counselling in cancer of the Valencian community (Spain)[END_REF].

In our laboratory, the BRCA1 and BRCA2 mutations were detected using the polymerase chain reaction (PCR) by amplifying the exons of both genes and the exon-intron boundaries, using the primer pairs and PCR conditions reported in the Breast Cancer Information Core (BIC) [START_REF]Breast Cancer Information Core[END_REF]. Mutational screening was carried out by the pre-screening of heteroduplex formed in the PCR products by conformation sensitive gel electrophoresis [START_REF] Ganguly | Conformation-sensitive gel electrophoresis for rapid detection of single-base differences in double-stranded PCR products and DNA fragments: evidence for solvent-induced bends in DNA heteroduplexes[END_REF]. However, this method requires post-PCR treatment prior to gel electrophoresis, being time-consuming and expensive.

High resolution melting (HRM) analysis is a new and attractive gene scan tool that quickly performs the PCR and identifies sequence alterations without requiring post-PCR treatment [START_REF] Montgomery | Simultaneous mutation scanningand genotyping by highresolution DNA melting analysis[END_REF][START_REF] Wittwer | High-resolution genotyping by amplicon melting analysis using LCGreen[END_REF]. Several HRM methods for mutation detection of human genetic diseases [START_REF] Kennerson | Mutation scanning the GJB1 gene with high-resolution melting analysis: implications for mutation scanning of genes for Charcot-Marie-Tooth disease[END_REF][START_REF] Laurie | Detection of factor VIII gene mutations by high-resolution melting analysis[END_REF][START_REF] Margraf | Mutation scanning of the RET protooncogene using high resolution melting analysis[END_REF][START_REF] Margraf | RET proto-oncogene genotyping using unlabeled probes, the masking technique, and amplicon high-resolution melting analysis[END_REF][START_REF] Willmore-Payne | Detection of c-kit exons 11-and 17-activating mutations in testicular seminomas by high-resolution melting amplicon analysis[END_REF] and polymorphisms [START_REF] Hill | Detection and identification of cytochrome P-450 2C9 alleles *1, *2, and *3 by high-resolution melting curve analysis of PCR amplicons[END_REF][START_REF] Liew | Genotyping of human platelet antigens 1 to 6 and 15 by highresolution amplicon melting and conventional hybridization probes[END_REF][START_REF] Reed | Sensitivity and specificity of singlenucleotide polymorphism scanning by high-resolution melting analysis[END_REF] have been further reported.

With regard to BRCA1 and BRCA2 mutations the only reports on HRM thus far were that of Dufrense et al [START_REF] Dufrense | BRCA1 and BRCA2 mutation screening using SmartCycler II high-resolution melt curve analysis[END_REF] and Takano et al [START_REF] Takano | Rapid detection of carriers with BRCA1 and BRCA2 mutations using high resolution melting analysis[END_REF] who proved the utility of HRM for the detection of the three common Ashkenazi founder mutations, 187_189delAG and 5382insC in BRCA1 and 6174delT in BRCA2. Therefore, there is a lack of information on the capability of HRM to detect a broad spectrum of BRCA1/2 mutations. This prompted us to investigate the usefulness of HRM for the screening of the BRCA1 and BRCA2 mutations reported hitherto in the Spanish population.

Material and methods

Patients and samples

We included 87 DNA samples containing most of the different mutations hitherto found in the Spanish population [START_REF] Bolufer | BRCA1 and BRCA2 mutations in patients with familial breast cancer[END_REF][START_REF] Dı ´ez | Analysis of BRCA1 and BRCA2 genes in spanish breast/ovarian cancer patients: a high proportion of mutations unique to spain and evidence of founder effects[END_REF][START_REF] Martı ´nez-Ferrandis | Mutational analysis of BRCA1 and BRCA2 in Mediterranean Spanish women with early-onset breast cancer: identification of three novel pathogenic mutations. human mutation; mutation in brief #659[END_REF][START_REF] Esteban | BRCA1 and BRCA2 mutations in families studied in the program of genetic counselling in cancer of the Valencian community (Spain)[END_REF], 40 out of 51 BRCA1 mutations (Table 1) and 47 out of 50 BRCA2 mutations (Table 2), some collected in our laboratory and others kindly provided by colleagues from laboratories involved in the study of BRCA1/2 mutations (see Acknowledgements). To validate the HRM method we included a reference group of 20 unknown DNAs obtained from sporadic BC patients. All these patients were informed of the study aim and written consent was given to the document elaborated by the Ethical Committee of the Hospital in accordance with the Helsinki Declaration (World Medical Association Declaration of Helsinki. Ethical Principles for Medical Research Involving Human Subjects 2004).

Primers

We designed the primer sets on the BRCA1 and BRCA2 DNA sequences (Gene Bank gi: 30039658 and gi: 37675288, respectively) where the Spanish mutations were located using Primer 3, v.0.4.0 software [START_REF] Rozen | Primer3 on the WWW for general users and for biologist programmers[END_REF]. The primer sets selected, 21 for BRCA1 and 25 for BRCA2 (Tables 1 and2), should fulfil the criteria of having an annealing temperature of 568 C and the PCR products should be shorter than 300 bp (median size 191 bp, range: 98-280). The primers synthesized were all of standard molecular biology quality (Tib Molbiol, Berlin, Germany).

High-resolution melting

PCR reactions were performed in triplicate in 10 ll final volume using LightCycler Ò 480 High Resolution Melting Master (Reference 04909631001, Roche Diagnostics) 9 1-contains Taq, nucleotides and the dye ResoLight-and 30 ng DNA. The primers and MgCl 2 were used at 0.2 lM and 2.5 mM, respectively, for all BRCA1 PCRs (Table 1). For BRCA2 PCRs we used three different primers and MgCl 2 concentrations (Table 2) . In each assay we included DNA with known BRCA1/2 Spanish mutations corresponding to the primer set, unknown DNA samples of patients with sporadic BC and wild-type control DNA.

The HRM assays were performed using the LightCycler Ò 480 Instrument (Reference Catalog # 04640268001, Roche Diagnostics; Roche Instrument Center AG, Forrenstrasse, CH-6343 Rotkreuz, Switzerlans) provided with the software LightCycler Ò 480 Gene Scanning Software Version 1.0 (Roche Instrument Center, Forrenstrasse, CH-6343 Rotkreuz, Switzerland).

The PCR program requires SYBR Green I filter (533 nm) and it consists of an initial denaturation-activation step at 95°C for 10 min, followed by a 45-cycle program (denaturation at 95°C for 10 s, annealing at 56°C for 13 s and elongation at 72°C for 14 s with reading of the fluorescence; acquisition mode: single). The melting program includes three steps: denaturalization at 958C for 1 min, renaturation at 40°C for 1 min and then melting, that consists of a continuous fluorescent reading from 60 to 908C at 25 acquisition per °C.

Gene scanning

The melting curve analysis performed by the Gene Scanning Software comprises three steps: normalization of melting curves, equalling to 100% the initial fluorescence and to 0% the fluorescence remnant after DNA dissociation, shifting of the temperature axis of the normalized melting curves to the point where the entire double-stranded DNA is completely denatured, and finally, the difference plot analyzes the differences in melting curve shape by subtracting the curves from wild-type and unknown DNA, therefore the difference plot helps clustering the samples into groups.

In order to evaluate the discriminating power of each mutation in relation to the wild-type control DNA, we established the resolution defined as the difference between the relative fluorescence signals between the maximum of the peaks of the mutation and the wild-type DNA in the difference plot. We, according to Laurie et al. [START_REF] Laurie | Detection of factor VIII gene mutations by high-resolution melting analysis[END_REF], considered that a mutation was clearly differentiated from wild-type DNA when the absolute value of resolution was greater than 5.

The PCR products were tested by agarose gel electrophoresis confirming the presence of a single PCR product with the expected size.

Sequencing

All the known mutations and genetic variants detected have been confirmed by sequencing the PCR products. The PCR products generated after HRM can be sequenced directly. This requires the removal the primer by purifying PCR products as follows: 8 ll of PCR product was incubated with 2.0 ll of ExoSap-IT (GE Healthcare) for 15 min at 37°C followed by 15 min at 80°C for enzyme inactivation. The sequence reaction was performed in 10 ll final volume using 5 ll of the purified PCR product, 3.2 pmol of one of PCR primers and 1 ll of ABI PRISM terminator cycle sequencing kit v1.1 (Applied Biosystems). The sequencing program is a 25-cycle PCR program (denaturation 96°C 10 s; annealing 50°C 5 s and elongation 60°C 4 min). The sequencing reaction products were purified by sodium ethanol-acetate precipitation. The sequence detection was performed in the ABI Prism 3130 Genetic Analyzer (Applied Biosystems, 850 Lincoln Centre Drive, Foster City, California 94404, USA).

Results

The PCR products showed a median melting temperature of 80.7°C (range: 72.3°C to 85.1°C). All PCR products obtained after HRM were electrophoresed in 2% agarose showing the presence of a unique product of the expected size. The shapes of difference plot curves of the triplicates of each DNA sample were very reproducible both in shape and peak height.

The HRM differentiated all the 40 BRCA1 mutations, including the most frequent Spanish mutations for this gene [START_REF] Dı ´ez | Analysis of BRCA1 and BRCA2 genes in spanish breast/ovarian cancer patients: a high proportion of mutations unique to spain and evidence of founder effects[END_REF][START_REF] Filippini | Multiplex SNaPshot for detection of BRCA1/2 common mutations in Spanish and Spanish related breast/ovarian cancer families[END_REF] from the wild-type control DNA on the basis of the shape of difference plot curves (Table 1, Fig. 1 and Supplementary Fig. 4). Thirty-four out of 40 mutations studied (85%) were clearly distinguishable from the wild-type control DNA (resolution [START_REF] Bolufer | BRCA1 and BRCA2 mutations in patients with familial breast cancer[END_REF]. The six remaining mutations: c.1791delA, c. In BRCA2, HRM also allows the differentiation of the 47 Spanish mutations, including the most frequent Spanish mutations [START_REF] Dı ´ez | Analysis of BRCA1 and BRCA2 genes in spanish breast/ovarian cancer patients: a high proportion of mutations unique to spain and evidence of founder effects[END_REF][START_REF] Filippini | Multiplex SNaPshot for detection of BRCA1/2 common mutations in Spanish and Spanish related breast/ovarian cancer families[END_REF] from the wild-type control DNA (Table 2, Fig. 3, Supplementary Fig. 5). Forty one of these (87%) were clearly distinguishable from the wild-type control DNA. However, four of these mutations, c.1538_1541del-AAGA and c.1676_1677delAGinsTTAC of exon 10, and c.8260_8261insGA and c.8267_8268delAC of exon18 (See Supplementary Fig. 5 PCR N8 5 and 21) could not be distinguished between them, due to its similarity in shape and peak height. Besides, 32 out of the 47 BRCA2 mutations studied could be clearly differentiated from each other.

In the study performed in BRCA2 in the 20 sporadic BC patients, we only found four polymorphisms, c.203G [ A of exon 2 in 11 patients, c.1342A [ C and c.1593A [ G of exon 10 in 8 and two patients, respectively, and c.9266C [ T of exo ´n 23 in one patient. We have, also detected two unclassified variants, the c.654-89T [ C of exon 5 and the c.2137 + 12delT in exon 10, in two patients, each one (Fig. 2c,d).

Discussion

Some of the major advantages of HRM are cost-effectiveness, simplicity, absence of post-PCR treatment, and, particularly, the swiftness to identify genetic variants or mutations. The HRM method set up here could differentiate all the 87 BRCA1 and BRCA2 Spanish mutations studied from wild-type DNA, 78 of them (% 90 %) with broad differences and the remaining nine with lower resolution. Besides, 54 mutations present in the same PCR Even though HRM is not specific for the mutations, if known mutations are included in the assay as positive control samples, the software is capable of identifying the samples with the same mutations on the basis of having similar difference plot shapes. With regard to this, we have verified that all the samples classed in the same group showed identical sequence (data not shown). However, in any case, the genetic variant could be easily identified by direct sequencing of the PCR product obtained after HRM. The method is particularly suitable for the detection of heterozygous mutations that form heteroduplexes such are the ones reported in BRCA1 and BRCA2 genes.

Filippi et al [START_REF] Filippini | Multiplex SNaPshot for detection of BRCA1/2 common mutations in Spanish and Spanish related breast/ovarian cancer families[END_REF] recently reported a method that detects 10 common Spanish mutations (5 in BRCA1 and 5 in BRCA2). The method is based on Multiplex SNaPshot and capillary electrophoresis. This technique has the advantage over HRM of being specific, however it is complex, requires post-PCR manipulations, it is time-consuming and it is more expensive than HRM. Furthermore, the method deals with a limited number of Spanish mutations, whereas the HRM here established covers nearly all Spanish mutations. Although we could not confirm in the group of sporadic BC the capability of HRM to detect Spanish mutations, this ability was assured by the inclusion of DNA control samples containing known Spanish mutations corresponding to the PCR product in each assay. Nevertheless, in this group we could confirm the capability of HRM to detect unsuspected genetic variants present in the PCR products that were subsequently confirmed by sequencing (Fig. 2). Regardless of all this, the ability of HRM to detect Spanish mutations in new samples should be confirmed in prospective studies carried out in large series of individuals with strong family histories of BC/OC. In summary we have set up a very fast, simple and nonexpensive HRM that with 46 independent PCR and in only 96 min identifies nearly all the BRCA1 and BRCA2 Spanish mutations hitherto known. Since the method is focused on the regions where the Spanish mutations occurs the lack of mutation in a DNA sample does not rule out the existence of mutations in other regions of the genes. Our results support that HRM is a very fast and reliable method adequate for the screening of the Spanish BRCA1 and BRCA2 mutations which could replace the currently methods applied in the screening of mutations.

Actually, we are applying this method in the family studies of carriers of Spanish mutations. In a near future,

9 n

 9 . = sample not available a Resolution = Difference between the relative signal difference at the peak maximum of each mutation and the peak maximum of wild-type DNA; L.B.M = Laboratory of Molecular Biology (Hospital La Fe, Valencia); I.B.G.M = Institute of Biology and Molecular Genetics (Valladolid); CIC = Cancer Research Centre (Salamanca) .a. = sample not available a Resolution = Difference between the relative signal difference at the peak maximum of each mutation and the peak maximum of wild-type DNA; L.B.M = Laboratory of Molecular Biology (Hospital La Fe, Valencia); I.B.G.M = Institute of Biology and Molecular Genetics (Valladolid); C.I.C. = Cancer Research Centre (Salamanca)

  Fig. 1 Difference plots of the most frequent BRCA1 Spanish mutations. Panel (a): Exon 2 Spanish mutations. Panel (b): Exon 5 Spanish mutations. Panel (c): Exon 8 Spanish mutations. Panel (d): Exon 18 Spanish mutations. For PCR conditions see Table 1

  c.3667 A [ G of exon 11 in 3, 10, 10 and 12 patients, respectively and c.4427T [ C (Fig.2a) of exon 13 in 10 patients and we also found the unclassified variant c.5371G [ A in exon 20 in one patient (Fig.2b).

Fig. 2

 2 Fig. 2 Sequence variants detected in BRCA1 (Panels a and b) and BRCA2 (Panels c and d) in sporadic BC. Panel (a): Exon 13 of BRCA1: c.4427T [ C polymorphism and c.4424delCT control mutation. Panel (b): Exon 20 of BRCA1: c.5371G [ A unclassified variant detected and c.5396 + 1G [ A control Spanish mutation. Panel (c):

Fig. 3

 3 Fig. 3 Difference plots of the most frequent BRCA2 Spanish mutations. Panel (a): Exon 11/PCR 9 Spanish mutations. Panel (b): Exon 11/PCR13 Spanish mutations. Panel (c): Exon 11/PCR18

Table 1

 1 High-resolution melting of BRCA1

		Difference plot	(resolution) a	7.31	14.91	17.73	8.43	15.00	9.00	24.37		14.20		7.96	71.30	51.92		22.00	16.45	3.02	-	3.81	6.81	15.81	4.00	-	3.78	5.47		25.00	-	22.43	30.00	19.00	36.00	-
		Primer(lM)/	MgCL 2 (mM)	0.2/2.5		0.2/2.5		0.2/2.5		0.2/2.5		0.2/2.5		0.2/2.5		0.2/2.5		0.2/2.5		0.2/2.5		0.2/2.5			0.2/2.5			0.2/2.5		0.2/2.5		0.2/2.5	0.2/2.5
		Amplicon	size (bp)	140		123		199		230		95		181		188		137		264		249			280			205		184		193	210
		Primers forward/reverse (5 0 ?3 0 )		GACGTTGTCATTAGTTCTTTGG/	GGTCAATTCTGTTCATTTGC	GCCTCATTTATTTTCTTTTTCTCC/	ATGGAGCCACATAACACATTCA	TTCATGGCTATTTGCCTTTTG/	GTGGTTGCTTCCAACCTAGC	GGTGTCAAGTTTCTCTTCAGG/	AATCCAGCAATTATTATTAAATA	AGCTGAGAGGCATCCAGAAA/	GCTGTAATGAGCTGGCATGA	ATAGGCGGACTCCCAGCAC/	TCACTTCTGGAAAACCACTCA	TCAAATGCCAAAGTAGCTGATG/	TTCCGATAGGTTTTCCCAAA	AGAGCGTCCCCTCACAAATA/	CCGTTTGGTTAGTTCCCTGA	GGAACTAACCAAACGGAGCA/	CGCATGAATATGCCTGGTAG	GAAAGCTGAACCTATAAGCAGCA/	GTTTCTGCTGTGCCTGACTG		TTTGTCAATCCTAGCCTTCCA/	GTCCCTTGGGGTTTTCAAAT		CCAGTCATTTGCTCCGTTTT/	CTGACCAACCACAGGAAAGC	TAGGGGTTTTGCAACCTGAG/	GAACAAACCTGAGATGCATGA	TGCATCTCAGGTTTGTTCTGA/	CCCTCTTCGGTAACCCTGA	CGTTGCTACCGAGTGTCTGT/	GAAAGGATCCTGGGTGTTTG
	Spanish mutations	PCR N8 References		1 Dı ´ez O et al. [6]	1 Dı ´ez O et al. [6]	2 Dı ´ez O et al. [6]	2 Dı ´ez O et al. [6]	3 D ı ´ez O et al. [6]	3 D ı ´ez O et al. [6]	4 Dı ´ez O et al. [6]		5 Dı ´ez O et al. [6]		6 Dı ´ez O et al. [6]	6 Dı ´ez O et al. [6]	7 D ı ´ez O et al. [6]		8 Bolufer et al. [5]	8 L.B.M. Valencia	9 C.I.C. Salamanca	n.a. C.I.C. Salamanca	10 Dı ´ez O et al. [6]	10 Esteban et al. [8]	10 Dı ´ez O et al. [6]	11 I.B.G.M. Valladolid	n.a. I.B.G.M. Valladolid	11 I.B.G. M. Valladolid	12 I.B.G.M. Valladolid		13 Esteban et al. [8]	n.a. Dı ´ez O et al. [6]	14 L.B.M. Valencia	15 Bolufer et al. [5]	15 Esteban et al. [8]	15 Dı ´ez O et al. [6]	n.a Dı ´ez O et al. [6]
		Mutations		c.187_188delAG	c.189_192dupTGTC	c.236_237delTG	c.243delA	c.330A [ G	c.331 + 1G [ A	c.589_590delCT		c.910_913delGTTC		c.1135_1136insA	c.1240_1242delCACinsT	c.1452G [ T		c.1623delTTAAA	c.1689delG	c.1791delA	c.1806C [ T	c.2031delG	c.2072del4	c.2080delA	c.2360deC	c.2411_2429dup19	c.2508_2509delGA	c.2802_2805del5		c.3450delCAAG	c.3600_3610del11	c.3700delC	c.3889_3890delAG	c.3904C [ A	c.3958delCTCAinsAGGC	c.4230_4231insATCT
		Exon		2	2	3	3	5	5	8		11		11	11	11		11	11	11	11	11	11	11	11	11	11	11		11	11	11	11	11	11	12

Breast Cancer Res Treat (2009) 115:405-414

Acknowledgements This work has been founded by the grants FIS PI060505 (Instituto de Salud Carlos III) and AP-042/07 (Consellerı ´a de Sanitat). We also express our gratitude to the ''Fundacio ´n para Investigacio ´n La Fe'' for having granted Inmaculada de Juan (Bch Sc and Specialist in Clinical Chemistry) in a research project on sporadic breast cancer, which made possible her participation in the present study. We should thank and name the colleagues who kindly provided DNA samples containing mutations, and those others that send us patient's samples for the present: Cristina Miner (Laboratorio de Gene ´tica del Ca ´ncer, Instituto de Biologı ´a y Gene ´tica Molecular, Valladolid), Orlan Diez (Servicio de Gene ´tica, Hospital de la Santa Creu i San Pau, Barcelona), Trinidad Calde ´s (Laboratorio de Biologı ´a Molecular, Hospital Clı ´nico San Carlos, Madrid), Rogelio Gonza ´lez (Centro de Investigacio ´n del Ca ´ncer, Salamanca), Javier Benı ´tez (Centro Nacional de Investigaciones Oncolo ´gicas, Madrid), Ana Vega (Unidad de Medicina Molecular, Fundacio ´n Pu ´blica Galega de Medicina Xeno ´mica-SERGAS, Hospital Clı ´nico Universitario de Santiago de Compostela, Santiago de Compostela), Ismael Aznar (Servicio de Cirugı ´a del Hospital La Fe), Carlos Va ´zquez (Servicio de Cirugı ´a del IVO), Isabel Chirivella (Unidad de Consejo Gene ´tico en Ca ´ncer Hospital Clı ´nico Universitario, Valencia), A ´ngel Segura (Unidad de Consejo Gene ´tico en Ca ´ncer Hospital Universitario La Fe, Valencia), Carmen Guille ´n (Unidad de Consejo Gene ´tico en Ca ´ncer Hospital General de Elche, Alicante), Eduardo Martı ´nez (Unidad de Consejo Gene ´tico en Ca ´ncer Consorcio Hospital Provincial, Castello ´n), Dolores Cuevas (Servicio de Protocolizacio ´n e Integracio ´n Asistencial, Direccio ´n General de Asistencia Sanitaria, Agencia Valenciana de Salud), Dolores Salas (Oficina del Plan de Ca ´ncer, Direccio ´n General de Salud Pu ´blica, Consellerı ´a de Sanitat de Comunidad Valenciana).


Shirley M Potter

Roisin M Dwyer
email: roisin.dwyer@nuigalway.ie

Catherine E Curran

Emer Hennessy

Kate A Harrington

Damian G Griffin

Michael J Kerin

A E Roisin

M Dwyer Ae

A E Emer

Hennessy Ae

Kate A Harrington Ae

A E Michael

J Kerin

Á R M Dwyer

Á E Hennessy

Á M J Kerin

Systemic chemokine levels in breast cancer patients and their relationship with circulating menstrual hormones

Keywords: Breast cancer, Menstrual hormones, Monocyte Chemotactic Protein-1 (MCP-1/CCL2), Prognosis, Stromal Cell-derived Factor 1-a

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Breast cancer development and progression is influenced by intrinsic properties of the tumour cells, as well as macro-environmental factors, with an intensive interplay existing between the tumour cells and signalling molecules such as chemokines [START_REF] Kerin | Host microenvironment in breast cancer development: inflammatory cells, cytokines and chemokines in breast cancer progression: reciprocal tumor-microenvironment interactions[END_REF]. Chemokines are chemotactic cytokines that act by altering the function of target cells in a paracrine, autocrine or endocrine manner. Chemokine gradients are central to the movement of cells in many normal and pathological processes by inducing cytoskeletal rearrangement, adhesion and directional migration. Chemokine receptor expression and activation on malignant cells have previously been shown to promote growth, survival and migration of cancer cells within and from the primary tumour site, and thereby contribute to locoregional and metastatic spread [START_REF] Balkwill | Cancer and the chemokine network[END_REF][START_REF] Kulbe | The chemokine network in cancer-much more than directing cell movement[END_REF]. Alterations in the systemic concentration of such chemokines may have potential for use as a marker of disease prognosis and monitoring, as in the case of other established tumour biomarkers, such as Prostate Specific Antigen or CA 15.3 [START_REF] Mcshane | REporting recommendations for tumor MARKer prognostic studies (REMARK)[END_REF][START_REF] Rao | Potential prognostic and therapeutic roles for cytokines in breast cancer[END_REF].

Two chemokines which have recently been highlighted as having roles in breast cancer are Stromal Cell Derived Factor-1a (SDF-1a) and Monocyte Chemotactic Protein-1 (MCP-1) [START_REF] Muller | Involvement of chemokine receptors in breast cancer metastasis[END_REF][START_REF] Kang | A multigenic program mediating breast cancer metastasis to bone[END_REF][START_REF] Saji | Significant correlation of monocyte chemoattractant protein-1 expression with neovascularization and progression of breast carcinoma[END_REF]. Interaction of SDF-1a with its main receptor, CXCR4, has a pivotal role to play in increased survival of cancer cells within the tumour, establishment of a tumour promoting chemokine network, as well as the directed migration of cancer cells to sites of metastasis [START_REF] Muller | Involvement of chemokine receptors in breast cancer metastasis[END_REF]. Normal breast tissues express very low levels of CXCR4, whereas breast neoplasms overexpress the receptor, with the highest expression reported in the most invasive tumour types [START_REF] Muller | Involvement of chemokine receptors in breast cancer metastasis[END_REF][START_REF] Kang | A multigenic program mediating breast cancer metastasis to bone[END_REF]9]. Although CXCR4 was previously believed to be the sole receptor for SDF-1a, more recently CXCR7 (RDC1, CCX-CKR2) has also been shown to be a target for this chemokine [START_REF] Burns | A novel chemokine receptor for SDF-1 and I-TAC involved in cell survival, cell adhesion, and tumor development[END_REF][START_REF] Balabanian | The chemokine SDF-1/CXCL12 binds to and signals through the orphan receptor RDC1 in T lymphocytes[END_REF]. CXCR7 promotes cell survival, growth, and adhesion in vitro and in vivo and has been shown to be expressed in several tumour cell lines, including the breast tumour lines MCF-7 and MDA-MB-435 [START_REF] Burns | A novel chemokine receptor for SDF-1 and I-TAC involved in cell survival, cell adhesion, and tumor development[END_REF]. Within the primary tumour, local production of SDF-1a promotes the growth of breast cancer cells, as well as the initial stages of angiogenesis [START_REF] Orimo | Stromal fibroblasts present in invasive human breast carcinomas promote tumor growth and angiogenesis through elevated SDF-1/CXCL12 secretion[END_REF]. Additionally, sites to which breast cancer cells preferentially metastasise, such as bone, liver, brain and lung, produce abundant amounts of SDF-1a [START_REF] Muller | Involvement of chemokine receptors in breast cancer metastasis[END_REF]. Previous reports have focused on SDF-1a and CXCR4 expression in breast cancer tissues primarily using immunohistochemistry and PCR based techniques [START_REF] Muller | Involvement of chemokine receptors in breast cancer metastasis[END_REF]. Li et al. [9] demonstrated by immunohistochemistry and RQ-PCR that HER2-neu upregulates the expression of CXCR4, which is required for HER2-neu enhanced invasion, migration, adhesion and metastasis to the lung and also that CXCR4 expression is correlated with overall patient survival in breast cancer, which has important clinical implications. Signalling through CXCR4 may contribute to critical pathways that determine the survival, invasion, or growth of disseminated HER2-neu-expressing breast cancer cells. HER2-neu could enhance the expression of CXCR4, which was required for metastatic colonization by HER2-neu expressing cells [9,[START_REF] Cabioglu | CXCL-12/stromal cellderived factor-1alpha transactivates HER2-neu in breast cancer cells by a novel pathway involving Src kinase activation[END_REF].

In a recent multi-center study by Hassan et al. [START_REF] Hassan | Plasma stromal cell-derived factor-1: host derived marker predictive of distant metastasis in breast cancer[END_REF], low plasma SDF-1a was found to be predictive of distant metastasis and an independent prognostic marker in breast cancer patients. This led to the hypothesis that elevated circulating SDF-1a levels in breast cancer patients may act to retain tumour cells in the circulation and prevent them from homing to their metastatic sites, with lower levels promoting establishment of metastases [START_REF] Hassan | Plasma stromal cell-derived factor-1: host derived marker predictive of distant metastasis in breast cancer[END_REF], thereby highlighting SDF-1a as a potential prognostic marker in breast cancer.

Monocyte Chemotactic Protein-1 is a 76-amino acid protein and is well established as a chemotactic factor regulating the recruitment of monocytes/macrophages and other cells to sites of inflammation. MCP-1 is not only secreted by many activated inflammatory or immune cells, but also by a variety of human and murine tumour cells [START_REF] Bhowmick | TGF-beta signaling in fibroblasts modulates the oncogenic potential of adjacent epithelia[END_REF]. Recent research has implicated MCP-1 as an active participant in the tumour microenvironment, influencing factors such as tumour-associated macrophages, growth, angiogenesis and metastasis [START_REF] Saji | Significant correlation of monocyte chemoattractant protein-1 expression with neovascularization and progression of breast carcinoma[END_REF][START_REF] Salcedo | Human endothelial cells express CCR2 and respond to MCP-1: direct role of MCP-1 in angiogenesis and tumor progression[END_REF][START_REF] Neumark | Progression of mouse mammary tumors: MCP-1-TNFalpha cross-regulatory pathway and clonal expression of promalignancy and antimalignancy factors[END_REF]. We have previously reported a trend toward higher levels of circulating MCP-1 in breast cancer patients compared to age-matched controls [START_REF] Dwyer | Monocyte chemotactic protein-1 secreted by primary breast tumors stimulates migration of mesenchymal stem cells[END_REF], with no significant correlation to commonly used prognostic indicators identified. A consensus has yet to be reached as to whether circulating MCP-1 is a positive or negative prognostic indicator in breast cancer patients [START_REF] Dehqanzada | Correlations between serum monocyte chemotactic protein-1 levels, clinical prognostic factors, and HER-2/neu vaccine-related immunity in breast cancer patients[END_REF][START_REF] Lebrecht | Monocyte chemoattractant protein-1 serum levels in patients with breast cancer[END_REF].

Circulating chemokines can potentially be regulated by endogenous hormones. The relationship between SDF-1a and circulating menstrual hormones has never previously been investigated, although it is known to be hormonally regulated at a cellular level and to mediate the proliferative action of Oestrogen [START_REF] Hall | Stromal cell-derived factor 1, a novel target of estrogen receptor action, mediates the mitogenic effects of estradiol in ovarian and breast cancer cells[END_REF]. Given that SDF-1a is one of the key factors implicated in the local micrometastatic milieu, alterations in the circulating levels of such a potent chemokine in a particular phase of the menstrual cycle may suggest a decreased potential for micrometastasis establishment in that phase. The question of hormonal regulation of systemic MCP-1 has previously been raised, but not fully elucidated [START_REF] Jilma-Stohlawetz | Fy phenotype and gender determine plasma levels of monocyte chemotactic protein[END_REF]. This laboratory previously reported [START_REF] Dwyer | Monocyte chemotactic protein-1 secreted by primary breast tumors stimulates migration of mesenchymal stem cells[END_REF] higher levels of MCP-1 in postmenopausal versus premenopausal breast cancer patients, suggesting underlying hormonal control of this chemokine. Premenopausal levels of both chemokines may correlate with phase of menstrual cycle and thereby influence timing of surgical intervention, as has been previously reported with other cytokines, such as Vascular Endothelial Growth Factor (VEGF) [START_REF] Heer | Vascular endothelial growth factor in premenopausal women-indicator of the best time for breast cancer surgery?[END_REF]. Both SDF-1a and MCP-1 have been implicated in the progression of breast cancer, having potential roles in angiogenesis and initiation of metastasis. The factors controlling these potent chemokines undoubtedly warrant further investigation.

The aim of this study was to investigate whether circulating SDF-1a levels are altered in breast cancer patients compared to age-matched healthy controls. A potential relationship between SDF-1a, MCP-1 and circulating menstrual hormones was also investigated.

We report that levels of SDF-1a were significantly elevated in breast cancer patients compared to age matched controls, and exhibited a significant positive correlation with two well established indicators of prognosis, tumour grade and epithelial subtype. Examination of systemic levels of SDF-1a and MCP-1 throughout the menstrual cycle revealed that, while serum MCP-1 levels did not differ significantly across the menstrual cycle, plasma SDF-1a levels were significantly lower in the mid-luteal phase and showed a significant correlation with circulating Oestradiol.

Materials and methods

Study cohort

Following ethical committee approval and written informed consent, preoperative blood samples were collected prospectively from 114 consecutive breast cancer patients (36 pre-menopausal, 78 post-menopausal) and 85 age-matched controls (34 pre-menopausal, and 51 post-menopausal) (Table 1). All patients had histologically confirmed breast cancer and patients with benign disease or distal metastatic disease were excluded. Forty six patients had axillary node positive disease at the time of recruitment. One patient in the breast cancer cohort had received neo-adjuvant chemotherapy. Ten premenopausal patients were taking the Oral Contraceptive Pill and five postmenopausal patients were on Hormone Replacement Therapy at the time of recruitment. Post-menopausal status was defined as amenorrhea for more than 12 months. Control samples were collected from healthy women attending an outpatient facility, with no current or previous malignancy or inflammatory condition.

To study the relationship between SDF-1a, MCP-1 and menstrual hormones, plasma and serum samples were taken from 36 premenopausal healthy females, on a weekly basis for four consecutive weeks, i.e. 144 samples in total. Measurement of SDF-1a, MCP-1, FSH, LH, Oestradiol and Progesterone were performed on each individual sample as described below. Demographic data such as age, date of last menstrual period and current medications was also collected from this group.

Blood collection

Whole blood was collected in a Vacuette EDTA K3E blood bottle (Grenier Bio-one) for plasma (SDF-1a detection) and Vacutainer Serum Separator Tubes II (Becton Dickinson) for serum (MCP-1 detection). Upon receipt, samples for serum collection were allowed to clot for 30 min and then all samples were centrifuged at 2,000 rpm @ 4°C for 10 min in a Sorvall RT6000D centrifuge. Plasma/serum was removed, aliquoted and stored at -20°C until required.

Chemokine detection

Levels of SDF-1a and MCP-1 in patient plasma and serum samples were measured using QuantikineÒ Enzyme Linked Immunosorbent Assay (ELISA) kits (R & D Systems) according to the manufacturer's protocol. Briefly, this involves use of microplates that have been pre-coated with an antibody specific for the target chemokine. Samples or standards are applied to the wells for a fixed period of time, aspirated, and the wells washed repeatedly. A secondary target-specific conjugate is then added for a fixed time period, followed by substrate solution and a ''stop'' solution. The optical density of each well is then read on a microplate reader at 450 nm wavelength, and the chemokine concentration in each sample determined using the standard curve. This permitted direct quantification of the levels of SDF-1a and MCP-1. All samples were analysed in duplicate.

Analysis of menstrual status

Serum Luteinising Hormone (LH), Follicular Stimulating Hormone (FSH), Oestradiol and Progesterone were measured by direct chemiluminescence, using Siemens ADVIAÒ Centaur TM Immunoassay System. LH peak was taken to denote mid-cycle, while the mid-luteal phase was marked by a peak in systemic Progesterone. Other phases of the cycle were extrapolated from these two time points.

Culture of primary stromal cells

Following ethical committee approval and written informed consent, fresh specimens of human breast cancer

Analysis of SDF-1a/CXCL12 gene expression

Total RNA was isolated from primary breast cancer stromal cells (n = 16), and normal stromal cells (n = 4) using the RNeasyÒ Mini Kit (QIAGEN Ltd.) according to manufacturer's instructions, and included an on-column DNase treatment step. RNA concentration and integrity were determined using the NanoDropÒ ND-1000 Spectrophotometer (NanoDrop Technologies Inc, Wilmington, DE, USA), and 2100 BioAnalyser (Agilent Technologies, Waldbronn, Germany), respectively. First strand cDNA was generated from 1 lg of total RNA by reverse transcription using SuperScript III reverse transcriptase enzyme (Invitrogen, Carlsbad, CA, USA). cDNA samples were amplified and analysed by real-time quantitative PCR (RQ-PCR) using the ABI Prism 7000 (Applied Biosystems, Warrington, UK). TaqmanÒ Universal Master Mix was used as well as TaqmanÒ Gene Expression Assays (Applied Biosystems) designed for the target gene (SDF-1a/CXCL12), and endogenous RNA reference genes Hypoxanthine Guanine Phosphoribosyltransferase-1 (HPRT1) and Glucoronidase beta (GUSB). The comparative CT method for relative quantification was used, allowing determination of the quantity of SDF-1a/CXCL12 in stromal cells normalised to HPRT1 and GUSB, and levels in tumours cells expressed relative to normal stromal cells. Results were expressed in a linear form using the formula 2 -DDCT .

Statistical analysis

Data are presented as Mean ± SEM. Data were analysed using the software package SPSS 14.0 for Windows. Results with a P \ 0.05 were considered statistically significant. All tests were two-tailed. Levene's test confirmed equal variance of observations in each group and permitted parametric data to be compared using a student's unpaired t-test. Normality was confirmed using the Kolmogorov-Smirnov test. Linear regression analysis was preformed to investigate the relationship between plasma SDF-1a levels and commonly used clinical prognostic indicators. Pearson correlation and multiple regression analysis were used to identify any relationship between systemic chemokine levels, menstrual hormones and phase of menstrual cycle.

Results

Systemic SDF-1a levels SDF-1a levels were measured in plasma samples harvested from 114 breast cancer patients (preoperative) (Table 1), and 85 age-matched controls (34 premenopausal, 51 postmenopausal). Plasma SDF-1a was significantly higher in the breast cancer cohort (2448 ± 49 pg/ml) than in healthy controls (2141 ± 58 pg/ml, P \ 0.00005) (Fig. 1a). When divided on the basis of menopausal status, within the breast cancer group, postmenopausal patients had significantly higher SDF-1a than premenopausal patients, and this difference was not reflected in the control cohort (P \ 0.05, Fig. 1a). There was no significant difference in grade or size of tumours between pre-and post-menopausal groups. Only one patient had received neoadjuvant chemotherapy prior to recruitment (SDF-1a 2213.9 pg/ml). Ten premenopausal patients were taking the Oral Contraceptive Pill (Mean SDF-1a 2450.11 pg/ml), and five postmenopausal patients were on Hormonal Replacement Therapy (Mean SDF-1a 2485.12 pg/ml).

Clinical correlations

The histological tumour profile of patients included in this study reflected that of a typical breast cancer cohort (Table 1), with the majority of ductal histology. Analysis of clinical data revealed a significant relationship between the prognostic indicator tumor grade and plasma SDF-1a levels (Pearson correlation coefficient = 0.194, P \ 0.05) (Fig. 1b), with higher plasma SDF-1a levels associated with tumours of higher grade. Tumours were also classified according to epithelial subtype. As expected, the majority of tumours were Luminal A (Table 1). Increasing plasma SDF-1a levels were found to have a significant relationship with the subtypes associated with poorer prognosis, i.e. Basal and Her2 (Pearson correlation coefficient = 0.260, P \ 0.05) (Fig. 1c). A potential relationship between SDF-1a and available Nottingham Prognostic Index (NPI) scores was also investigated and a non-significant positive correlation was found (Pearson correlation coefficient = 0.146, P = 0.227, results not shown).

Hormonal control of chemokines

The mean age of the premenopausal control cohort was 25 years (Median = 23 years). All cycles were found to be ovulatory, that is, each showed an LH surge followed by an appropriate mid-luteal peak of Progesterone. Nine patients were taking an oral contraceptive pill at the time of the study and this had no significant impact on circulating SDF-1a or MCP-1 levels. Plasma SDF-1a was significantly lower in the mid-luteal phase of the menstrual cycle (2157 ± 60 pg/ml, P \ 0.05) than other time points, late luteal/early follicular (2387 ± 69 pg/ml), midfollicular (2267 ± 65 pg/ml), and mid-cycle (2349 ± 71 pg/ml) (Fig. 2a). SDF-1a displayed a significant correlation with Oestradiol (r = 0.213, P \ 0.005) throughout the cycle (Fig. 2b), with SDF-1a at it's lowest when Oestradiol was at its highest. MCP-1 levels did not differ significantly across the menstrual cycle and did not show any significant correlation to menstrual hormones (Fig. 2c).

Analysis of SDF-1a/CXCL12 gene expression

Following separation into individual stromal cell populations, total RNA was extracted and the SDF-1a/CXCL12 expression level was quantified in tumour stromal cells (n = 16, labelled A-P) compared to normal stromal cells (n = 4) harvested at reduction mammaplasty (Fig. 3). Results are expressed as Relative Quantity (Log 10 ) with the levels of expression in each sample corrected to the level of endogenous control (GUS & HPRT), and expressed relative to that detected in normal stromal cells, represented by the baseline of the graph. Although variable, there was an overall trend towards increased SDF-1a gene expression in tumour compared to normal stromal cells.

Discussion

Prognostic markers are markers that have been found to have a robust association with some clinical outcome, such Plasma SDF-1a was significantly higher in breast cancer patients (2448 ± 49 pg/ml) than in healthy controls (2141 ± 58 pg/ml, P \ 0.00005). Within the breast cancer cohort, SDF-1a levels were significantly higher in postmenopausal (PostMen, n = 78) compared to pre-menopausal patients (PreMen, n = 36) (P \ 0.05) which was not reflected in the control group. (b, c) Analysis of patient clinical data. A significant positive correlation was found between the prognostic indicator tumor grade (ranked I-III) and plasma SDF-1a levels (P \ 0.05) (b). Tumours were also classified according to epithelial subtype, and increasing SDF-1a was found to correlate with subtypes associated with poorer prognosis (P \ 0.05) (c) as overall survival or recurrence-free survival [START_REF] Mcshane | REporting recommendations for tumor MARKer prognostic studies (REMARK)[END_REF]. It remains crucially important to define more sensitive and specific indicators of prognosis that reflect the complicated and heterogeneous nature of breast cancer, and could identify patients at greatest risk of disease progression. Lymph node status, tumour size and grade, epithelial subtype and lymphovascular invasion are among the prognostic indicators currently employed to predict an individual's risk of progression [START_REF] Van't Veer | Gene expression profiling predicts clinical outcome of breast cancer[END_REF].

The data presented here reveals that breast cancer patients have a significantly higher level of plasma SDF-1a than healthy age-matched controls. Studies have shown that CXCR4 is present on platelets, and so to measure circulating levels of free SDF-1a, platelet free plasma was used [START_REF] Wang | The alpha-chemokine receptor CXCR4 is expressed on the megakaryocytic lineage from progenitor to platelets and modulates migration and adhesion[END_REF]. Plasma SDF-1a levels in our control group (2141 ± 58 pg/ ml) were similar to those previously reported in healthy subjects (2192 ± 76.4 pg/ml) [START_REF] Zannettino | Elevated serum levels of stromal-derived factor-1alpha are associated with increased osteoclast activity and osteolytic bone disease in multiple myeloma patients[END_REF]. Circulating levels of SDF-1a have recently been reported in patients with multiple myeloma [START_REF] Martin | Tumor angiogenesis is associated with plasma levels of stromal-derived factor-1alpha in patients with multiple myeloma[END_REF] and colorectal cancer [START_REF] Dimberg | Polymorphism and circulating levels of the chemokine CXCL12 in colorectal cancer patients[END_REF]. In multiple myeloma patients, levels of SDF-1a were found to positively correlate with the degree of bone marrow angiogenesis, while in colorectal cancer, low circulating levels correlated with higher tumour grade and CXCR4 expression [START_REF] Martin | Tumor angiogenesis is associated with plasma levels of stromal-derived factor-1alpha in patients with multiple myeloma[END_REF][START_REF] Dimberg | Polymorphism and circulating levels of the chemokine CXCL12 in colorectal cancer patients[END_REF]. In an extensive study Hassan et al [START_REF] Hassan | Plasma stromal cell-derived factor-1: host derived marker predictive of distant metastasis in breast cancer[END_REF] recently reported low plasma SDF-1a as a predictive marker of distant breast cancer metastasis and poorer survival, which contrasts with the results presented here. Although the cohort studied here is smaller, there were also significant differences in study design. Their patient cohort was divided based on plasma SDF-1a into ''Lo'' (\2295 pg/ml), ''Mid'' (2296-2557 pg/ ml) and ''Hi'' ([2557 pg/ml) with the relative risk of dying from breast cancer 5.17-fold higher in the ''Lo'' versus ''High'' group. The values found in the ''Lo'' group are similar to those found in normal healthy controls reported in our study and by others [START_REF] Zannettino | Elevated serum levels of stromal-derived factor-1alpha are associated with increased osteoclast activity and osteolytic bone disease in multiple myeloma patients[END_REF], and also this ''Lo'' group was not compared to a healthy age-matched control group. Low plasma SDF-1a was also associated with younger age at time of surgery, however menstrual or menopausal status was not specified. The increased levels detected in breast cancer patients versus age-matched controls in the current study had a significant predictive relationship to tumour grade (I-III), an indicator of the degree of tumour cell differentiation and a well established predictor of prognosis.

Breast cancer epithelial subtypes identified by gene microarray studies capture the heterogeneity of breast cancer and have a statistically robust relationship with disease-free and overall survival [START_REF] Van't Veer | Gene expression profiling predicts clinical outcome of breast cancer[END_REF]. Plasma SDF-1a levels also had a significant association with epithelial subtype, with higher SDF-1a levels seen in those classically associated with poorer prognosis, such as basal subtype. The relationship reported here between plasma SDF-1a and these subtypes further highlights the potential significance of this chemokine in disease progression. It is noteworthy that plasma levels also displayed a relationship with Nottingham Prognostic Index (NPI) values, which takes into account tumour size, grade and lymph node status [START_REF] Galea | The Nottingham Prognostic Index in primary breast cancer[END_REF], however this relationship did not achieve statistical significance (P = 0.227). The elevated pre-operative levels in breast cancer patients highlights the potential for SDF-1a as a novel diagnostic or prognostic biomarker for this disease. Further research is required to determine whether any relationship exists between SDF-1a and end-points such as disease free survival and overall survival.

It is well established that SDF-1a is secreted by many different cell types, so undoubtedly there are other systemic factors at play in this group, such as the already firmly established constitutive expression of SDF-1a at the primary sites of breast cancer metastasis including bone, liver, brain and lung tissues [START_REF] Muller | Involvement of chemokine receptors in breast cancer metastasis[END_REF]. In agreement with previous reports [START_REF] Orimo | Stromal fibroblasts present in invasive human breast carcinomas promote tumor growth and angiogenesis through elevated SDF-1/CXCL12 secretion[END_REF][START_REF] Allinen | Molecular characterization of the tumor microenvironment in breast cancer[END_REF], in the current study we detected increased levels of SDF-1a gene expression in stromal cells derived from primary breast tumours, relative to the levels detected in normal breast tissue harvested at reduction mammaplasty. Hassan et al. [START_REF] Hassan | Plasma stromal cell-derived factor-1: host derived marker predictive of distant metastasis in breast cancer[END_REF] found no significant difference in SDF-1a levels before and after tumour resection in a cohort of 22 patients. Further research is required to determine the true contribution of tumour-derived SDF-1a to systemic levels of the chemokine.

Postmenopausal patients had significantly higher plasma SDF-1a than pre-menopausal breast cancer patients, a difference that was not seen in the corresponding control groups. SDF-1a has been shown to be an Oestrogen receptor-regulated gene and mediator of the mitogenic effects of Oestradiol in ovarian and breast cancer cell lines [START_REF] Hall | Stromal cell-derived factor 1, a novel target of estrogen receptor action, mediates the mitogenic effects of estradiol in ovarian and breast cancer cells[END_REF]. The relationship between systemic SDF-1a and circulating hormones has never previously been investigated. In this study, based on 36 healthy premenopausal subjects and 144 samples in total, a cyclical variation in circulating SDF-1a in relation to the phases of the menstrual cycle was demonstrated, suggesting a potential relationship between this chemokine and menstrual hormones, while no such relationship was observed with MCP-1. The level of SDF-1a was lowest at mid-luteal phase while Oestradiol levels were highest. The elevated systemic levels in postmenopausal compared to premenopausal breast cancer patients may be explained by a deregulation of Oestrogen control in this group, potentially mediated by Oestrogen receptor coactivators/corepressors whose expression is altered in breast cancer [START_REF] Kishimoto | The p160 family coactivators regulate breast cancer cell proliferation and invasion through autocrine/paracrine activity of SDF-1alpha/ CXCL12[END_REF]. The importance of this novel finding is increased in the light of a study by Holdaway et al. [START_REF] Holdaway | Characteristics of the menstrual cycle at the time of surgery for breast cancer[END_REF] which has shown that the hormone profile of the menstrual cycle is maintained in patients with breast cancer. Thus it is reasonable to extrapolate these findings in normal premenopausal women to those with breast cancer.

The controversy of timing of surgical intervention in premenopausal breast cancer patients was initiated by Hrushesky et al. [START_REF] Hrushesky | Menstrual influence on surgical cure of breast cancer[END_REF] and has since been supported by 4 major studies, all favouring the second half of the menstrual cycle as optimal for surgery [START_REF] Badwe | Timing of surgery during menstrual cycle and survival of premenopausal women with operable breast cancer[END_REF][START_REF] Veronesi | Effect of menstrual phase on surgical treatment of breast cancer[END_REF][START_REF] Mohr | Serum progesterone and prognosis in operable breast cancer[END_REF][START_REF] Senie | Timing of breast cancer excision during the menstrual cycle influences duration of disease-free survival[END_REF]. Our findings indicate that Oestradiol may cause down-regulation of SDF-1a in this phase. Given that SDF-1a is one of the key factors implicated in the local micrometastatic milieu, alterations in the circulating levels of such a potent chemokine in a particular phase of the menstrual cycle may suggest a decreased potential for micrometastasis establishment in that phase.

A previous study investigated MCP-1 levels through the menstrual cycle in a small group (n = 18, one sample per subject) of healthy premenopausal subjects who were not on oral contraceptives and found a significant decrease in MCP-1 levels from the follicular to the luteal phase of the cycle [START_REF] Jilma-Stohlawetz | Fy phenotype and gender determine plasma levels of monocyte chemotactic protein[END_REF]. Clearly the number of women in each phase of the cycle was small. In the current study, over the 144 samples taken, there was no correlation found between circulating MCP-1 and menstrual hormones, with no cyclical variation observed. This suggests differing control mechanisms operating between these two important chemokines.

The results presented here showing elevated SDF-1a in breast cancer patients, and it's association with commonly used prognostic indicators, highlights the potential importance of this chemokine in disease progression. Further study of SDF-1a and its receptors, both systemically and within the tumour microenvironment, may ultimately support prediction of metastatic potential, monitor response to treatment, or advance therapeutic options for this disease. Increased elucidation of the intrinsic factors that regulate this potent chemokine may have implications in terms of timing surgical intervention in premenopausal breast cancer patients and lead to increased understanding of the biology of chemokine regulation.

Fig. 1

 1 Fig.1(a) Graph showing plasma SDF-1a levels in 114 breast cancer patients (BrCa) (preoperative) and 85 age-matched controls (Cntrl). Plasma SDF-1a was significantly higher in breast cancer patients (2448 ± 49 pg/ml) than in healthy controls (2141 ± 58 pg/ml, P \ 0.00005). Within the breast cancer cohort, SDF-1a levels were significantly higher in postmenopausal (PostMen, n = 78) compared to pre-menopausal patients (PreMen, n = 36) (P \ 0.05) which was

Fig. 2 Fig. 3

 23 Fig. 2 Relationship between chemokines and circulating menstrual hormones. (a) Variation of systemic SDF-1a across phases of menstrual cycle. The levels of SDF-1a were significantly lower in the mid-luteal phase (P \ 0.05). (b) Correlation of systemic SDF-1a and Oestradiol across the menstrual cycle. SDF-1a was found to have

Table 1

 1 Breast cancer patient details

		Breast cancer patients
	Number of subjects
	Premenopausal	36
	Postmenopausal	78
	Mean age (years)
	Premenopausal	42
	Postmenopausal	58
	Histology
	Ductal	81
	Lobular	16
	Other	14
	Unknown	3
	Epithelial subtype
	Luminal A	73
	Luminal B	10
	Her2	4
	Basal	6
	Unknown	21
	Grade
	I	1 3
	II	54
	III	39
	Unknown	8

Breast Cancer Res Treat (2009) 115:279-287

Acknowledgements The National Breast Cancer Research Institute (NBCRI) provided the main source of funding for this work. RM Dwyer is also supported by a Health Research Board of Ireland Postdoctoral Fellowship. We are grateful to Dr. John Newell for advice relating to statistical analysis.