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Serum biomarker profiles and response to neoadjuvant chemotherapy for locally advanced breast cancer

Serum biomarker profiles and response to neoadjuvant chemotherapy for locally advanced breast cancer Introduction Neoadjuvant chemotherapy has become the Results Biomarker levels were compared retrospectively with standard of care for the diverse population of women diagnosed clinical and pathologic treatment responses. Univariate analysis with locally advanced breast cancer. Serum biomarker levels are of the data identified several groups of biomarkers that differed increasingly being investigated for their ability to predict therapy significantly among treatment outcome groups early in the response and aid in the development of individualized treatment course of neoadjuvant chemotherapy. Multivariate statistical regimens. Multianalyte profiles may offer greater predictive analysis revealed multibiomarker panels that could differentiate power for neoadjuvant treatment response than the individual between treatment response groups with high sensitivity and biomarkers currently in use. specificity. Methods Serum samples were collected from 44 patients enrolled in a phase I–II, open-label study of liposomal Conclusion We demonstrate here that serum biomarker profiles doxorubicin and paclitaxel in combination with whole breast may offer predictive power concerning treatment response and hyperthermia for the neoadjuvant treatment of locally advanced outcome in the neoadjuvant setting. The continued development breast cancer (stage IIB or stage III). Samples were collected of these findings will be of considerable clinical utility in the prior to each of four rounds of treatment and prior to definitive design of treatment regimens for individual breast cancer surgery. Samples were assayed by Luminex assay for 55 serum patients. biomarkers, including cancer antigens, growth/angiogenic factors, apoptosis-related molecules, metastasis-related molecules, adhesion molecules, adipokines, cytokines, chemokines, hormones, and other proteins. Trial registration #NCT00346229. IIB disease [1]. The clinical definition of LABC continues to Introduction Locally advanced breast cancer (LABC) is a generalized diag- evolve and differ among physicians, and now includes nonmet- nosis that includes all stage III disease and a subset of stage astatic T3 or T4 tumors as well as N2/N3 disease involving cCR = clinical complete response; EGFR = epidermal growth factor receptor; IL = interleukin; LABC = locally advanced breast cancer; MIF = migra- tion inhibitory factor; MMP = matrix metalloproteinase; NAC = neoadjuvant chemotherapy; pCR = pathologic complete response; TNF = tumor necro- sis factor; tPAI-1 = tissue plasminogen activator inhibitor 1. Page 1 of 9 (page number not for citation purposes) Breast Cancer Research Vol 10 No 3 Nolen et al. limited metastasis [2], thus broadening the already diverse duct intreatment analyses of molecular markers that may pre- spectrum of LABC presentations. According to the American dict response to therapy. The emergence of new technologies College of Surgeons Data Base, approximately 6% of all US such as transcriptional and proteomic profiling has greatly breast cancer cases present as stage III [3]. This number has aided such investigations [18,19]. For instance, it has been declined dramatically over the past decade due to improved reported that mutations in p53 are associated with a lower screening and detection practices. The 5-year relative survival response rate following NAC [20,21], while coexpression of rate for stage III breast cancer is approximately 50%, com- HER-2/Neu and topoisomerse II is associated with greater pared with 87% for stage I. The median survival for women response rates [22]. Measurements of the traditional breast with stage III disease is 4.9 years [1]. cancer markers CA15-3 and HER-2/Neu, however, have dem- onstrated only limited predictive value in the NAC setting Neoadjuvant chemotherapy (NAC), the delivery of systemic [23,24]. chemotherapy prior to surgical resection, has emerged as the preferred initial component of therapy for patients diagnosed In the present study we examine a diverse panel of serum with LABC in an effort to enhance the prospect of breast-con- biomarkers in order to identify individual biomarkers and com- serving surgery and to render inoperable tumors resectable binations that may be useful in predicting treatment response [4,5]. NAC offers the theoretical advantages of early initiation early in the course of NAC for the treatment of LABC. of systemic therapy, delivery of drugs through intact vascula- ture, in vivo assessment of therapy response, and the oppor- Materials and methods Patients tunity to study the biological effects of chemotherapy [6]. Preoperative systemic chemotherapy may also eradicate dis- Serum samples were collected from patients enrolled in a tant micrometastases and thus improve the overall effective- phase I–II, open-label study of liposomal doxorubicin (Evacet; ness of treatment [7]. Several studies comparing NAC with Elan Corp., Stevenage, UK) and paclitaxel (Bristol Myers more traditional adjuvant chemotherapy have found similar sur- Squibb, Princeton, NJ, USA) in combination with whole breast vival rates between the two options [5,8,9], and the use of hyperthermia for the neoadjuvant treatment of LABC (stage IIB NAC is further supported by findings that delaying surgery for or stage III). This trial required informed consent and was con- the administration of chemotherapy does not adversely affect ducted under the approval of the Duke University Institutional treatment outcome when compared with adjuvant chemother- Review Board. Protocol-eligible patients were treated with the apy [10,11]. combination of Evacet, paclitaxel, and hyperthermia every 3 weeks. The hyperthermia procedure has been described pre- A pathologic complete response (pCR) following NAC implies viously [25]. the absence of residual invasive or in situ disease and corre- lates strongly with both prolonged disease-free survival and Following neoadjuvant therapy, patients received appropriate overall survival [12,13]. A recent review of several randomized surgical removal of their primary breast tumor as well as axillary clinical trials of NAC for operable breast cancer reported a lymph node dissection. Immediately after surgery, patients response rate of 49% to 94% with a pCR rate of 4% to 34% underwent radiation therapy followed by an additional eight [12]. In patients treated with NAC, 60% to 80% demonstrate cycles each of 21-day standard dose cyclophosphamide (600 2 2 2 some clinical response with 10% to 20% achieving a clinical mg/m ), methotrexate (40 mg/m ), 5-fluorouracil (600 mg/m ) complete response (cCR) [4]. Clinical response, however, and appropriate hormonal therapy. often does not correlate with pathologic response as a full one-third of patients achieving a cCR are found to have path- The clinical trial accrued a total of 47 patients. Three patients ologic evidence of residual disease [9,14]. Despite these diffi- were deemed nonevaluable because of failure to complete all culties in assessing response, patients demonstrating four cycles of the neoadjuvant portion of the trial. The clinical complete clinical or pathologic responses to NAC generally characteristics of the patient study group are presented in achieve improved outcomes to overall treatment [14,15]. Table 1. Accurate modalities for assessing chemotherapy response are Collection and storage of blood serum critical to the evaluation and expansion of the use of NAC for Serum samples were obtained prior to the start of neoadjuvant breast cancer. Conventional methods including clinical exami- therapy (pretreatment), prior to cycles 2, 3, and 4 of neoadju- nation, mammogram, and breast ultrasound are incorrect in vant therapy, and prior to definitive surgery. Blood was drawn identifying pCR patients in nearly one-half of all cases [2]. Sev- using standard phlebotomy procedures and was collected eral groups have reported promising results in their attempts without anticoagulant. Blood was allowed to coagulate for up to predict treatment response utilizing unconventional tech- to 2 hours at room temperature. Sera were separated by cen- niques such as diffuse optical spectroscopy and magnetic res- trifugation, immediately aliquoted, frozen, and stored at -80°C. onance imaging [16,17]. A growing number of investigators No more than two freeze–thaw cycles were allowed for any have begun to utilize the preoperative nature of NAC to con- sample. Page 2 of 9 (page number not for citation purposes) Available online http://breast-cancer-research.com/content/10/3/R45 Table 1 trations of analytes were quantitated from median fluores- cence intensities using standard curves generated by Bio-Rad Clinical characteristics of study patients five-parameter curve fitting) to the series of known concentra- tions for each analyte. Characteristic Number of patients Patients in study Statistical analysis Total enrolled 47 Clinical response The Mann–Whitney nonparametric t test was used to evaluate Total completing treatment 44 the significance of differences in serum biomarker levels Clinical stage pretreatment expressed as the median fluorescence intensity between treat- Stage IIB 15 ment response groups separated by treatment timepoints. The level of significance was taken as P < 0.05. For multivariate Stage IIIA 12 analysis of biomarker combinations, a CART classification tree Stage IIIB 16 [28-30] diagnostic model was created. The Statistical Analy- Clinical response sis System (SAS version 9: SAS Institute, Inc., Cary, NC, USA) was used to fit the logistic regressions using PROC Complete 12 LOGISTIC. The best subset for each size panel of analytes Partial 20 was identified through the brand and bound algorithm of Fur- Stable disease 12 nival and Wilson [31]. This algorithm maximizes the score function over all possible combinations of analytes for any Pathologic response given size panel. The Statistical Analysis System was also Complete 4 used to fit the logistic regressions and to identify the best sub- Partial 23 sets for each size panel of biomarkers. Panels were generated Stable disease 17 from size 1 to size 10. Sensitivities were estimated for specificities of 90%, 95%, and 98% by ranking the predicted fit for each control subject, Multiplexed bead-based immunoassay determining the cutoff points corresponding to these levels of The xMAP™ bead-based technology (Luminex Corp., Austin, specificity, and applying the cutoff points to the ranked predic- TX, USA) permits simultaneous analysis of numerous analytes tions for the alternative treatment response group. To minimize in a single sample. Fifty-five bead-based xMAP™ immu- overfitting bias, leave-one-out cross-validation was used. The noassays for a variety of serum biomarkers were utilized in the MATLAB routines treefit and treeval were used. For panel present study (Table 2). selection, markers were selected incrementally. Given an existing subset of the markers, each marker was considered a Assays for ErbB2, epidermal growth factor receptor (EGFR), potential addition to the panel. We began with no markers and CA 15-3, carcinoembryonic antigen, Cyfra 21-1, CA 19-9, CA added until little additional progress was made. 72-4, α-fetoprotein, mesothelin, insulin-like growth factor bind- ing protein 1, human kallikrein 10, and HE4 were developed in Pathologic response the UPCI Luminex Core Facility [26]. The inter-assay variability Within each timepoint of treatment, biomarker expression val- of each assay was 5% to 11%, and the intra-assay variability ues – expressed as the median fluorescence intensity – were was 2% to 9%. Assays for MMP-2 and MMP-3 were obtained adjusted by the following procedure. Quantile normalization from R&D Systems (Minneapolis, MN, USA), assays for MIP- was performed using the normalize BetweenArrays function 1β, eotaxin, IP-10, IL-2R, IL-1Rα, IL-6R, DR5, TNF-RI, and (limma package) in R [32], missing values were filled in using TNF-RII were obtained from Invitrogen (Camarillo, CA), and k-nearest neighbor imputation, and values were log-trans- the remaining assays were obtained from Millipore/Linco formed. Research (St Charles, MO, USA). Overall, eight different mul- tiplexed panels were used. Normalized values were filtered according to a univariate, two- sided t test. From this filtered set, values were progressively Multiplex analysis included and excluded from a stepwise regression model. The Assays were performed according to the manufacturers' pro- final logistic regression model was then subjected to leave- tocols. Luminex Core Facility assays were performed as one-out cross-validation to assess the predictive value. described previously [27]. Samples were analyzed using the Bio-Plex suspension array system (Bio-Rad Laboratories, Her- cules, CA, USA). Biomarker expression levels were expressed as median fluorescent intensities generated by analyzing 50 to 100 microbeads for each analyte in each sample. The concen- Page 3 of 9 (page number not for citation purposes) Breast Cancer Research Vol 10 No 3 Nolen et al. Table 2 Complete list of biomarkers tested Biomarker category Individual biomarkers Cancer antigens/oncogenes α-Fetoprotein, CA 125, CA 19-9, CA 15-3, CA 72-4, carcinoembryonic antigen Cytokines/chemokines/receptors Eotaxin, fractalkine, granulocyte–macrophage colony-stimulating factor, IFNγ, IL-10, IL-12p70, IL-13, IL-1β, IL- 1Rα, IL-2, IL-2R, IL-4, IL-5, IL-6, IL-6R, IL-7, IL-8, IP-10, migration inhibitory factor, MIP-1β, soluble CD40L, TNFα, TNF-R1, TNF-R2 Growth/angiogenic factors Epidermal growth factor receptor, ErbB2, insulin-like growth factor binding protein 1, transforming growth factor alpha Proteases Kallikrein 10, MMP-2, MMP-3, MMP-9 Hormones Adrenocorticotropic hormone, follicle-stimulating hormone, growth hormone, luteinizing hormone, prolactin, thyroid-stimulating hormone Adipokines Adiponectin Apoptosis-related molecules Cyfra 21-1, DR5, soluble Fas, soluble Fas ligand Metastasis-related molecules Myeloperoxidase, tissue plasminogen activator inhibitor 1 Adhesion molecules Soluble intracellular adhesion molecule 1, soluble vascular cell adhesion molecule 1 Other proteins HE4, mesothelin while levels of tissue plasminogen activator inhibitor 1 (tPAI-1) Results Multiplex analysis of serum levels of various biomarkers were significantly lower in the same group (P < 0.05, Figure in LABC patients receiving neoadjuvant chemotherapy 1a). Higher levels of IL-6 and IL-8 were also observed in Of the 44 evaluable patients enrolled in the clinical trial, 12 patients achieving a cCR, although this observation was not demonstrated a cCR, 20 demonstrated a clinical partial statistically significant (P < 0.07, Figure 1). response, and 12 had no response. Of the same group, four patients demonstrated a pCR, 23 demonstrated a pathologic A CART classification tree analysis of serum biomarker levels partial response, and 17 had no response. One patient out of from these patients identified a three-biomarker panel consist- the total 44 did not have blood drawn prior to the second cycle ing of α-fetoprotein, soluble vascular cell adhesion molecule 1, of NAC and was excluded from the analysis for that timepoint. and MMP-9 that could distinguish between the response groups with 83% sensitivity and 91% specificity (Table 3). A bead-based 55-biomarker panel was utilized to screen the Interestingly, when the 11 patients achieving a cCR were com- sera from patients. The biomarkers included cancer antigens, bined with 19 patients achieving a clinical partial response and growth/angiogenic factors, apoptosis-related molecules, were compared with the nonresponders, tPAI-1 alone could metastasis-related molecules, adhesion molecules, adipok- distinguish responders from nonresponders with 75% sensi- ines, cytokines, chemokines, hormones, proteases, and other tivity and 77% specificity (Table 3 and Figure 1d). Serum lev- proteins (Table 2). Biomarker levels were compared at each els of tPAI-1 were significantly lower in responders (cCR and treatment timepoint between complete responders, partial clinical partial response) compared with nonresponders (P < responders, and nonresponders within each response classi- 0.007, Figure 1b). fication (clinical or pathologic). Analysis of serum biomarker levels according to clinical Combinations of biomarkers were evaluated by multivariate response prior to the second cycle of neoadjuvant analysis for the ability to predict a particular response. Our chemotherapy analysis was limited to serum samples collected prior to the For this analysis, 11 patients achieving a cCR were compared initiation of NAC and prior to the second cycle of therapy. We with 11 patients demonstrated no response. Serum levels of did not identify any significant correlations between biomarker IL-8 were significantly higher and those of insulin-like growth levels and pathologic response at the pretreatment timepoint. factor binding protein 1 were significantly lower in patients achieving a cCR (P < 0.05, Figure 1c). CART classification Analysis of pretreatment serum biomarker levels tree analysis of serum biomarker levels from these patients according to clinical response identified a three-biomarker panel consisting of MMP-3, For this analysis, 11 patients achieving a cCR were compared luteinizing hormone, and thyroid stimulating hormone that with 12 patients demonstrating no response. Serum levels of could distinguish between clinical response groups with 82% MMP-9 were significantly higher in patients achieving a cCR sensitivity and 73% specificity (Table 3). Page 4 of 9 (page number not for citation purposes) Available online http://breast-cancer-research.com/content/10/3/R45 Figure 1 Se Seru rum bioma m biomar rke ker an r analysis alysis of n of ne eoadj oadjuvan uvant t c ch hem emoth othe erapy rapy for loca for locally lly adva advanc nced brea ed breast ca st canc ncer a er ac cc cordin ording g to to clinica clinicall re response sponse. (a) Pretreatment serum levels of IL-6, IL-8, MMP-9, and tissue plasminogen activator inhibitor 1 (tPAI-1) were compared between 11 patients achieving a clinical complete response (cCR) and 12 patients demonstrating no response (NR) to neoadjuvant chemotherapy (NAC). (b) Pretreatment serum levels of tPAI-1 were compared between 30 patients achieving a cCR or clinical partial response (cPR) and 12 patients demonstrating NR to NAC. (c) Serum levels of insulin-like growth factor binding protein 1 (IGFBP-1) and IL-8 measured prior to the second round of NAC were compared between 11 patients achieving a cCR and 11 patients demonstrating NR to NAC. (d) Cumulative receiver operating characteristics for responders versus nonresponders based on pretreatment serum levels of tPAI-1. Statistical significance: *P < 0.05; **P < 0.01. Analysis of serum biomarker levels according to responders from nonresponders with 85% sensitivity and pathologic response prior to the second cycle of 69% specificity (Table 3 and Figure 2b). neoadjuvant chemotherapy For this analysis, 27 patients achieving a pCR or pathologic Discussion partial response were compared with 16 patients demonstrat- The heterogeneity displayed by patients diagnosed with ing no response. Serum levels of EGFR, soluble Fas ligand, LABC runs counter to the rationale for generalized treatment migration inhibitory factor (MIF), and MMP-2 were significantly regimens. A wide array of treatment options exist for the treat- higher in responders compared with non-responders (P < ment of breast cancer – including adjuvant and NAC, hormone 0.05, Figure 2a). therapy, radiotherapy, and surgery – and the vast majority of these options have been well researched. The ability to dynam- A logistic regression analysis of the serum biomarker levels in ically tailor the components of a particular treatment regimen these patients identified a five-biomarker panel consisting of on a patient by patient basis would be invaluable. Such an ErbB2, EGFR, MIF, MMP-2, and CD40L that could distinguish accomplishment will require the identification and develop- Table 3 Predictive power of multimarker panels Panel Timepoint Response type Sensitivity (%) Specificity (%) α-Fetoprotein, soluble vascular cell adhesion Pretreatment Clinical complete response versus no 83 91 molecule 1, MMP-9 response Tissue plasminogen activator inhibitor 1 Pretreatment Clinical complete response/clinical partial 75 77 response versus no response MMP-3, luteinizing hormone, thyroid-stimulating Pre-cycle 2 Clinical complete response versus no 82 73 hormone response ErbB2, epidermal growth factor receptor, Pre-cycle 2 Pathologic complete response/pathologic 85 69 migration inhibitory factor, MMP-2, CD40 ligand partial response versus no response Page 5 of 9 (page number not for citation purposes) Breast Cancer Research Vol 10 No 3 Nolen et al. Figure 2 Ser Seru um bi m biom omarke arker an r anal alys ysis of is of n ne eo oa ad dju juva vant nt c ch he emoth mother erapy for apy for loca locally a lly ad dva vance nced brea d breast c st ca ance ncer ac r according to pa cording to patho thollogic ogic re respo spon nse. se (a) Serum levels of epidermal growth factor receptor (EGFR), soluble Fas ligand (sFasL), migration inhibitory factor (MIF), and MMP-2 measured prior to the second round of neoadjuvant chemotherapy (NAC) in 27 patients achieving a pathologic complete response (pCR) or partial pathologic response (pPR) and 16 patients demonstrating no response (NR) to NAC. (b) Cumulative receiver operating characteristics for patients achieving a pCR or pPR versus nonresponders to NAC based on serum levels of ErbB2, EGFR, MIF, MMP-2, and CD40 measured prior to the second cycle of NAC. Statistical sig- nificance: *P < 0.05. ment of improved prognostic factors on which to base thera- IL-8 have been associated with poor prognosis in women with peutic decisions, since currently used measurements of breast cancer [37,38]. These cytokines have also been impli- clinical and radiological response lack the necessary preci- cated in the blood-borne response to paclitaxel treatment [39]. sion. In the present article we demonstrate the predictive value The prognostic value of MMP-9 serum levels is currently of serum biomarkers for the response to NAC for LABC. The unclear [33], but several studies have examined extensively diverse nature of the biomarker relationships identified in the the role of matrix metalloproteinases in breast cancer [40,41]. study underscores the diversity of the disease characteristics present in the patient population. Our results also demonstrate a correlation between lower pre- treatment serum levels of tPAI-1 and improved clinical Previous studies have examined the value of biomarkers such response. In fact, tPAI-1 levels alone were able to discriminate as carcinoembryonic antigen, CA 15-3, MMP-2, MMP-9, tis- responders from nonresponders with 75% sensitivity and sue polypeptide antigen (TPA), tissue polypeptide-specific 77% specificity prior to the start of NAC. tPAI-1 is a major antigen (TPS), EGFR, and HER-2/neu in predicting response physiological inhibitor of tissue-type plasminogen activators to NAC for breast cancer [33-36]. The results of these inves- and has been implicated in tumor growth, invasion, and angio- tigations have been mixed. To our knowledge, the panel of genesis. The function of tPAI-1 as a regulator of plasminogen serum biomarkers examined in the present study is the largest activation places it in a position to modulate degradation of the and most diverse to date and the majority of the relationships extracellular matrix and antiangiogenic effects mediated by we identify have not been described previously. plasmin and angiostatin, respectively. Several groups have illustrated experimentally the role of tPAI-1 in tumor progres- Our results indicate that elevated serum levels of IL-6, IL-8, sion and its negative prognostic value in breast cancer [42- and MMP-9 prior to the initiation of treatment correlate with 44]. improved clinical response. The observed increases in IL-6 and IL-8 serum levels of 2.74 and 3.13 pg/ml, respectively In sera collected after patients had received the initial cycle of (Figure 1a), were not significant in our study given the limited chemotherapy we observed that increased levels of IL-4, IL-8, 23-patient enrollment. Utilizing these data, we predict that an and adrenocorticotropic hormone and decreased levels of enrollment of 59 patients would be sufficient to confer signifi- insulin-like growth factor binding protein 1 all correlated with cance (P < 0.05) upon these observations with a power of 0.9. improved clinical response at differing levels of significance. Increased serum levels of the inflammatory cytokines IL-6 and The increase in levels of inflammatory cytokines following Page 6 of 9 (page number not for citation purposes) Available online http://breast-cancer-research.com/content/10/3/R45 chemotherapy is in line with clinical expectations and is evi- this will increase immensely. Continuing efforts in line with dence that the therapeutic agents are active in the patient's those presented here should bring us closer to providing system. The roles of the insulin-like growth factor system and effective and efficient individualized treatment to women diag- hormones in the response to chemotherapy have not been sig- nosed with this challenging disease. nificantly evaluated; however, both groups have known roles in the development of breast cancer [45,46]. Competing interests The authors declare that they have no competing interests. With regards to pathologic response, we observed a correla- tion between increased levels of soluble Fas ligand, MMP-2, Authors' contributions MIF, and EGFR and improved response. A proapoptotic BMN participated in the Luminex assays, oversaw the data response following chemotherapy, as evidenced by increased analysis, and drafted the manuscript. JRM and KB conceived soluble Fas ligand in the sera, is to be expected. Our observa- the study and coordination the transfer of patient samples. ST, tion of increased levels of MMP-2 in the sera of responders AR, TML, and YW carried out the statistical analysis. AEL con- supports the notion of matrix metalloproteinase involvement in ceived the study, participated in the study design, and helped breast cancer. The precise role of macrophage MIF in breast to draft the manuscript. cancer development and treatment response remains unknown, but MIF has been implicated in tumor cell survival Acknowledgements The present work was supported by the DAMD17-03-1-0696 DOD pathways [47]. The value of EGFR serum and tissue levels in Award, the 'Avon–NCI Progress for Patients' Award, and the predicting response to chemotherapy has been examined pre- BCTR0600911 Susan G Komen Foundation Award (AEL). The authors viously with inconclusive results [43,48]. Increased expression would like to acknowledge Adele Marrangoni, Lyudmila Velikokhatnaya, of EGFR has been demonstrated elsewhere to suggest a poor Matt Winans, and Denise Prosser for their extensive technical support prognosis in breast cancer [49]. relating to the Luminex analysis. It is noteworthy to mention that our present analysis did not References identify any significant relationships between CA 15-3 or 1. Singletary SE, Allred C, Ashley P, Bassett LW, Berry D, Bland KI, Borgen PI, Clark GM, Edge SB, Hayes DF, Hughes LL, Hutter RV, HER2/Neu and response to NAC. This observation adds to Morrow M, Page DL, Recht A, Theriault RL, Thor A, Weaver DL, several sparse and conflicting reports in the literature Wieand HS, Greene FL: Staging system for breast cancer: revi- [23,50,51]. It would appear from this uncertainty that, sions for the 6th edition of the AJCC Cancer Staging Manual. Surg Clin N Am 2003, 83:803-819. although these particular biomarkers have shown the most 2. 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Gianni L, Zambetti M, Clark K, Baker J, Cronin M, Wu J, Mariani G, Rocz Akad Med Bialymst 2003, 48:82-84. Rodriguez J, Carcangiu M, Watson D, Valagussa P, Rouzier R, 39. Pusztai L, Mendoza TR, Reuben JM, Martinez MM, Willey JS, Lara Symmans WF, Ross JS, Hortobagyi GN, Pusztai L, Shak S: Gene J, Syed A, Fritsche HA, Bruera E, Booser D, Valero V, Arun B, Ibra- expression profiles in paraffin-embedded core biopsy tissue him N, Rivera E, Royce M, Cleeland CS, Hortobagyi GN: Changes predict response to chemotherapy in women with locally in plasma levels of inflammatory cytokines in response to advanced breast cancer. J Clin Oncol 2005, 23:7265-7277. paclitaxel chemotherapy. Cytokine 2004, 25:94-102. 20. Anelli A, Brentani RR, Gadelha AP, Amorim De Albuquerque A, 40. 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Serum biomarker profiles and response to neoadjuvant chemotherapy for locally advanced breast cancer

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Springer Journals
Copyright
Copyright © 2008 by Nolen et al.; licensee BioMed Central Ltd.
Subject
Biomedicine; Cancer Research; Oncology; Surgical Oncology
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1465-542X
DOI
10.1186/bcr2096
pmid
18474099
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Abstract

Introduction Neoadjuvant chemotherapy has become the Results Biomarker levels were compared retrospectively with standard of care for the diverse population of women diagnosed clinical and pathologic treatment responses. Univariate analysis with locally advanced breast cancer. Serum biomarker levels are of the data identified several groups of biomarkers that differed increasingly being investigated for their ability to predict therapy significantly among treatment outcome groups early in the response and aid in the development of individualized treatment course of neoadjuvant chemotherapy. Multivariate statistical regimens. Multianalyte profiles may offer greater predictive analysis revealed multibiomarker panels that could differentiate power for neoadjuvant treatment response than the individual between treatment response groups with high sensitivity and biomarkers currently in use. specificity. Methods Serum samples were collected from 44 patients enrolled in a phase I–II, open-label study of liposomal Conclusion We demonstrate here that serum biomarker profiles doxorubicin and paclitaxel in combination with whole breast may offer predictive power concerning treatment response and hyperthermia for the neoadjuvant treatment of locally advanced outcome in the neoadjuvant setting. The continued development breast cancer (stage IIB or stage III). Samples were collected of these findings will be of considerable clinical utility in the prior to each of four rounds of treatment and prior to definitive design of treatment regimens for individual breast cancer surgery. Samples were assayed by Luminex assay for 55 serum patients. biomarkers, including cancer antigens, growth/angiogenic factors, apoptosis-related molecules, metastasis-related molecules, adhesion molecules, adipokines, cytokines, chemokines, hormones, and other proteins. Trial registration #NCT00346229. IIB disease [1]. The clinical definition of LABC continues to Introduction Locally advanced breast cancer (LABC) is a generalized diag- evolve and differ among physicians, and now includes nonmet- nosis that includes all stage III disease and a subset of stage astatic T3 or T4 tumors as well as N2/N3 disease involving cCR = clinical complete response; EGFR = epidermal growth factor receptor; IL = interleukin; LABC = locally advanced breast cancer; MIF = migra- tion inhibitory factor; MMP = matrix metalloproteinase; NAC = neoadjuvant chemotherapy; pCR = pathologic complete response; TNF = tumor necro- sis factor; tPAI-1 = tissue plasminogen activator inhibitor 1. Page 1 of 9 (page number not for citation purposes) Breast Cancer Research Vol 10 No 3 Nolen et al. limited metastasis [2], thus broadening the already diverse duct intreatment analyses of molecular markers that may pre- spectrum of LABC presentations. According to the American dict response to therapy. The emergence of new technologies College of Surgeons Data Base, approximately 6% of all US such as transcriptional and proteomic profiling has greatly breast cancer cases present as stage III [3]. This number has aided such investigations [18,19]. For instance, it has been declined dramatically over the past decade due to improved reported that mutations in p53 are associated with a lower screening and detection practices. The 5-year relative survival response rate following NAC [20,21], while coexpression of rate for stage III breast cancer is approximately 50%, com- HER-2/Neu and topoisomerse II is associated with greater pared with 87% for stage I. The median survival for women response rates [22]. Measurements of the traditional breast with stage III disease is 4.9 years [1]. cancer markers CA15-3 and HER-2/Neu, however, have dem- onstrated only limited predictive value in the NAC setting Neoadjuvant chemotherapy (NAC), the delivery of systemic [23,24]. chemotherapy prior to surgical resection, has emerged as the preferred initial component of therapy for patients diagnosed In the present study we examine a diverse panel of serum with LABC in an effort to enhance the prospect of breast-con- biomarkers in order to identify individual biomarkers and com- serving surgery and to render inoperable tumors resectable binations that may be useful in predicting treatment response [4,5]. NAC offers the theoretical advantages of early initiation early in the course of NAC for the treatment of LABC. of systemic therapy, delivery of drugs through intact vascula- ture, in vivo assessment of therapy response, and the oppor- Materials and methods Patients tunity to study the biological effects of chemotherapy [6]. Preoperative systemic chemotherapy may also eradicate dis- Serum samples were collected from patients enrolled in a tant micrometastases and thus improve the overall effective- phase I–II, open-label study of liposomal doxorubicin (Evacet; ness of treatment [7]. Several studies comparing NAC with Elan Corp., Stevenage, UK) and paclitaxel (Bristol Myers more traditional adjuvant chemotherapy have found similar sur- Squibb, Princeton, NJ, USA) in combination with whole breast vival rates between the two options [5,8,9], and the use of hyperthermia for the neoadjuvant treatment of LABC (stage IIB NAC is further supported by findings that delaying surgery for or stage III). This trial required informed consent and was con- the administration of chemotherapy does not adversely affect ducted under the approval of the Duke University Institutional treatment outcome when compared with adjuvant chemother- Review Board. Protocol-eligible patients were treated with the apy [10,11]. combination of Evacet, paclitaxel, and hyperthermia every 3 weeks. The hyperthermia procedure has been described pre- A pathologic complete response (pCR) following NAC implies viously [25]. the absence of residual invasive or in situ disease and corre- lates strongly with both prolonged disease-free survival and Following neoadjuvant therapy, patients received appropriate overall survival [12,13]. A recent review of several randomized surgical removal of their primary breast tumor as well as axillary clinical trials of NAC for operable breast cancer reported a lymph node dissection. Immediately after surgery, patients response rate of 49% to 94% with a pCR rate of 4% to 34% underwent radiation therapy followed by an additional eight [12]. In patients treated with NAC, 60% to 80% demonstrate cycles each of 21-day standard dose cyclophosphamide (600 2 2 2 some clinical response with 10% to 20% achieving a clinical mg/m ), methotrexate (40 mg/m ), 5-fluorouracil (600 mg/m ) complete response (cCR) [4]. Clinical response, however, and appropriate hormonal therapy. often does not correlate with pathologic response as a full one-third of patients achieving a cCR are found to have path- The clinical trial accrued a total of 47 patients. Three patients ologic evidence of residual disease [9,14]. Despite these diffi- were deemed nonevaluable because of failure to complete all culties in assessing response, patients demonstrating four cycles of the neoadjuvant portion of the trial. The clinical complete clinical or pathologic responses to NAC generally characteristics of the patient study group are presented in achieve improved outcomes to overall treatment [14,15]. Table 1. Accurate modalities for assessing chemotherapy response are Collection and storage of blood serum critical to the evaluation and expansion of the use of NAC for Serum samples were obtained prior to the start of neoadjuvant breast cancer. Conventional methods including clinical exami- therapy (pretreatment), prior to cycles 2, 3, and 4 of neoadju- nation, mammogram, and breast ultrasound are incorrect in vant therapy, and prior to definitive surgery. Blood was drawn identifying pCR patients in nearly one-half of all cases [2]. Sev- using standard phlebotomy procedures and was collected eral groups have reported promising results in their attempts without anticoagulant. Blood was allowed to coagulate for up to predict treatment response utilizing unconventional tech- to 2 hours at room temperature. Sera were separated by cen- niques such as diffuse optical spectroscopy and magnetic res- trifugation, immediately aliquoted, frozen, and stored at -80°C. onance imaging [16,17]. A growing number of investigators No more than two freeze–thaw cycles were allowed for any have begun to utilize the preoperative nature of NAC to con- sample. Page 2 of 9 (page number not for citation purposes) Available online http://breast-cancer-research.com/content/10/3/R45 Table 1 trations of analytes were quantitated from median fluores- cence intensities using standard curves generated by Bio-Rad Clinical characteristics of study patients five-parameter curve fitting) to the series of known concentra- tions for each analyte. Characteristic Number of patients Patients in study Statistical analysis Total enrolled 47 Clinical response The Mann–Whitney nonparametric t test was used to evaluate Total completing treatment 44 the significance of differences in serum biomarker levels Clinical stage pretreatment expressed as the median fluorescence intensity between treat- Stage IIB 15 ment response groups separated by treatment timepoints. The level of significance was taken as P < 0.05. For multivariate Stage IIIA 12 analysis of biomarker combinations, a CART classification tree Stage IIIB 16 [28-30] diagnostic model was created. The Statistical Analy- Clinical response sis System (SAS version 9: SAS Institute, Inc., Cary, NC, USA) was used to fit the logistic regressions using PROC Complete 12 LOGISTIC. The best subset for each size panel of analytes Partial 20 was identified through the brand and bound algorithm of Fur- Stable disease 12 nival and Wilson [31]. This algorithm maximizes the score function over all possible combinations of analytes for any Pathologic response given size panel. The Statistical Analysis System was also Complete 4 used to fit the logistic regressions and to identify the best sub- Partial 23 sets for each size panel of biomarkers. Panels were generated Stable disease 17 from size 1 to size 10. Sensitivities were estimated for specificities of 90%, 95%, and 98% by ranking the predicted fit for each control subject, Multiplexed bead-based immunoassay determining the cutoff points corresponding to these levels of The xMAP™ bead-based technology (Luminex Corp., Austin, specificity, and applying the cutoff points to the ranked predic- TX, USA) permits simultaneous analysis of numerous analytes tions for the alternative treatment response group. To minimize in a single sample. Fifty-five bead-based xMAP™ immu- overfitting bias, leave-one-out cross-validation was used. The noassays for a variety of serum biomarkers were utilized in the MATLAB routines treefit and treeval were used. For panel present study (Table 2). selection, markers were selected incrementally. Given an existing subset of the markers, each marker was considered a Assays for ErbB2, epidermal growth factor receptor (EGFR), potential addition to the panel. We began with no markers and CA 15-3, carcinoembryonic antigen, Cyfra 21-1, CA 19-9, CA added until little additional progress was made. 72-4, α-fetoprotein, mesothelin, insulin-like growth factor bind- ing protein 1, human kallikrein 10, and HE4 were developed in Pathologic response the UPCI Luminex Core Facility [26]. The inter-assay variability Within each timepoint of treatment, biomarker expression val- of each assay was 5% to 11%, and the intra-assay variability ues – expressed as the median fluorescence intensity – were was 2% to 9%. Assays for MMP-2 and MMP-3 were obtained adjusted by the following procedure. Quantile normalization from R&D Systems (Minneapolis, MN, USA), assays for MIP- was performed using the normalize BetweenArrays function 1β, eotaxin, IP-10, IL-2R, IL-1Rα, IL-6R, DR5, TNF-RI, and (limma package) in R [32], missing values were filled in using TNF-RII were obtained from Invitrogen (Camarillo, CA), and k-nearest neighbor imputation, and values were log-trans- the remaining assays were obtained from Millipore/Linco formed. Research (St Charles, MO, USA). Overall, eight different mul- tiplexed panels were used. Normalized values were filtered according to a univariate, two- sided t test. From this filtered set, values were progressively Multiplex analysis included and excluded from a stepwise regression model. The Assays were performed according to the manufacturers' pro- final logistic regression model was then subjected to leave- tocols. Luminex Core Facility assays were performed as one-out cross-validation to assess the predictive value. described previously [27]. Samples were analyzed using the Bio-Plex suspension array system (Bio-Rad Laboratories, Her- cules, CA, USA). Biomarker expression levels were expressed as median fluorescent intensities generated by analyzing 50 to 100 microbeads for each analyte in each sample. The concen- Page 3 of 9 (page number not for citation purposes) Breast Cancer Research Vol 10 No 3 Nolen et al. Table 2 Complete list of biomarkers tested Biomarker category Individual biomarkers Cancer antigens/oncogenes α-Fetoprotein, CA 125, CA 19-9, CA 15-3, CA 72-4, carcinoembryonic antigen Cytokines/chemokines/receptors Eotaxin, fractalkine, granulocyte–macrophage colony-stimulating factor, IFNγ, IL-10, IL-12p70, IL-13, IL-1β, IL- 1Rα, IL-2, IL-2R, IL-4, IL-5, IL-6, IL-6R, IL-7, IL-8, IP-10, migration inhibitory factor, MIP-1β, soluble CD40L, TNFα, TNF-R1, TNF-R2 Growth/angiogenic factors Epidermal growth factor receptor, ErbB2, insulin-like growth factor binding protein 1, transforming growth factor alpha Proteases Kallikrein 10, MMP-2, MMP-3, MMP-9 Hormones Adrenocorticotropic hormone, follicle-stimulating hormone, growth hormone, luteinizing hormone, prolactin, thyroid-stimulating hormone Adipokines Adiponectin Apoptosis-related molecules Cyfra 21-1, DR5, soluble Fas, soluble Fas ligand Metastasis-related molecules Myeloperoxidase, tissue plasminogen activator inhibitor 1 Adhesion molecules Soluble intracellular adhesion molecule 1, soluble vascular cell adhesion molecule 1 Other proteins HE4, mesothelin while levels of tissue plasminogen activator inhibitor 1 (tPAI-1) Results Multiplex analysis of serum levels of various biomarkers were significantly lower in the same group (P < 0.05, Figure in LABC patients receiving neoadjuvant chemotherapy 1a). Higher levels of IL-6 and IL-8 were also observed in Of the 44 evaluable patients enrolled in the clinical trial, 12 patients achieving a cCR, although this observation was not demonstrated a cCR, 20 demonstrated a clinical partial statistically significant (P < 0.07, Figure 1). response, and 12 had no response. Of the same group, four patients demonstrated a pCR, 23 demonstrated a pathologic A CART classification tree analysis of serum biomarker levels partial response, and 17 had no response. One patient out of from these patients identified a three-biomarker panel consist- the total 44 did not have blood drawn prior to the second cycle ing of α-fetoprotein, soluble vascular cell adhesion molecule 1, of NAC and was excluded from the analysis for that timepoint. and MMP-9 that could distinguish between the response groups with 83% sensitivity and 91% specificity (Table 3). A bead-based 55-biomarker panel was utilized to screen the Interestingly, when the 11 patients achieving a cCR were com- sera from patients. The biomarkers included cancer antigens, bined with 19 patients achieving a clinical partial response and growth/angiogenic factors, apoptosis-related molecules, were compared with the nonresponders, tPAI-1 alone could metastasis-related molecules, adhesion molecules, adipok- distinguish responders from nonresponders with 75% sensi- ines, cytokines, chemokines, hormones, proteases, and other tivity and 77% specificity (Table 3 and Figure 1d). Serum lev- proteins (Table 2). Biomarker levels were compared at each els of tPAI-1 were significantly lower in responders (cCR and treatment timepoint between complete responders, partial clinical partial response) compared with nonresponders (P < responders, and nonresponders within each response classi- 0.007, Figure 1b). fication (clinical or pathologic). Analysis of serum biomarker levels according to clinical Combinations of biomarkers were evaluated by multivariate response prior to the second cycle of neoadjuvant analysis for the ability to predict a particular response. Our chemotherapy analysis was limited to serum samples collected prior to the For this analysis, 11 patients achieving a cCR were compared initiation of NAC and prior to the second cycle of therapy. We with 11 patients demonstrated no response. Serum levels of did not identify any significant correlations between biomarker IL-8 were significantly higher and those of insulin-like growth levels and pathologic response at the pretreatment timepoint. factor binding protein 1 were significantly lower in patients achieving a cCR (P < 0.05, Figure 1c). CART classification Analysis of pretreatment serum biomarker levels tree analysis of serum biomarker levels from these patients according to clinical response identified a three-biomarker panel consisting of MMP-3, For this analysis, 11 patients achieving a cCR were compared luteinizing hormone, and thyroid stimulating hormone that with 12 patients demonstrating no response. Serum levels of could distinguish between clinical response groups with 82% MMP-9 were significantly higher in patients achieving a cCR sensitivity and 73% specificity (Table 3). Page 4 of 9 (page number not for citation purposes) Available online http://breast-cancer-research.com/content/10/3/R45 Figure 1 Se Seru rum bioma m biomar rke ker an r analysis alysis of n of ne eoadj oadjuvan uvant t c ch hem emoth othe erapy rapy for loca for locally lly adva advanc nced brea ed breast ca st canc ncer a er ac cc cordin ording g to to clinica clinicall re response sponse. (a) Pretreatment serum levels of IL-6, IL-8, MMP-9, and tissue plasminogen activator inhibitor 1 (tPAI-1) were compared between 11 patients achieving a clinical complete response (cCR) and 12 patients demonstrating no response (NR) to neoadjuvant chemotherapy (NAC). (b) Pretreatment serum levels of tPAI-1 were compared between 30 patients achieving a cCR or clinical partial response (cPR) and 12 patients demonstrating NR to NAC. (c) Serum levels of insulin-like growth factor binding protein 1 (IGFBP-1) and IL-8 measured prior to the second round of NAC were compared between 11 patients achieving a cCR and 11 patients demonstrating NR to NAC. (d) Cumulative receiver operating characteristics for responders versus nonresponders based on pretreatment serum levels of tPAI-1. Statistical significance: *P < 0.05; **P < 0.01. Analysis of serum biomarker levels according to responders from nonresponders with 85% sensitivity and pathologic response prior to the second cycle of 69% specificity (Table 3 and Figure 2b). neoadjuvant chemotherapy For this analysis, 27 patients achieving a pCR or pathologic Discussion partial response were compared with 16 patients demonstrat- The heterogeneity displayed by patients diagnosed with ing no response. Serum levels of EGFR, soluble Fas ligand, LABC runs counter to the rationale for generalized treatment migration inhibitory factor (MIF), and MMP-2 were significantly regimens. A wide array of treatment options exist for the treat- higher in responders compared with non-responders (P < ment of breast cancer – including adjuvant and NAC, hormone 0.05, Figure 2a). therapy, radiotherapy, and surgery – and the vast majority of these options have been well researched. The ability to dynam- A logistic regression analysis of the serum biomarker levels in ically tailor the components of a particular treatment regimen these patients identified a five-biomarker panel consisting of on a patient by patient basis would be invaluable. Such an ErbB2, EGFR, MIF, MMP-2, and CD40L that could distinguish accomplishment will require the identification and develop- Table 3 Predictive power of multimarker panels Panel Timepoint Response type Sensitivity (%) Specificity (%) α-Fetoprotein, soluble vascular cell adhesion Pretreatment Clinical complete response versus no 83 91 molecule 1, MMP-9 response Tissue plasminogen activator inhibitor 1 Pretreatment Clinical complete response/clinical partial 75 77 response versus no response MMP-3, luteinizing hormone, thyroid-stimulating Pre-cycle 2 Clinical complete response versus no 82 73 hormone response ErbB2, epidermal growth factor receptor, Pre-cycle 2 Pathologic complete response/pathologic 85 69 migration inhibitory factor, MMP-2, CD40 ligand partial response versus no response Page 5 of 9 (page number not for citation purposes) Breast Cancer Research Vol 10 No 3 Nolen et al. Figure 2 Ser Seru um bi m biom omarke arker an r anal alys ysis of is of n ne eo oa ad dju juva vant nt c ch he emoth mother erapy for apy for loca locally a lly ad dva vance nced brea d breast c st ca ance ncer ac r according to pa cording to patho thollogic ogic re respo spon nse. se (a) Serum levels of epidermal growth factor receptor (EGFR), soluble Fas ligand (sFasL), migration inhibitory factor (MIF), and MMP-2 measured prior to the second round of neoadjuvant chemotherapy (NAC) in 27 patients achieving a pathologic complete response (pCR) or partial pathologic response (pPR) and 16 patients demonstrating no response (NR) to NAC. (b) Cumulative receiver operating characteristics for patients achieving a pCR or pPR versus nonresponders to NAC based on serum levels of ErbB2, EGFR, MIF, MMP-2, and CD40 measured prior to the second cycle of NAC. Statistical sig- nificance: *P < 0.05. ment of improved prognostic factors on which to base thera- IL-8 have been associated with poor prognosis in women with peutic decisions, since currently used measurements of breast cancer [37,38]. These cytokines have also been impli- clinical and radiological response lack the necessary preci- cated in the blood-borne response to paclitaxel treatment [39]. sion. In the present article we demonstrate the predictive value The prognostic value of MMP-9 serum levels is currently of serum biomarkers for the response to NAC for LABC. The unclear [33], but several studies have examined extensively diverse nature of the biomarker relationships identified in the the role of matrix metalloproteinases in breast cancer [40,41]. study underscores the diversity of the disease characteristics present in the patient population. Our results also demonstrate a correlation between lower pre- treatment serum levels of tPAI-1 and improved clinical Previous studies have examined the value of biomarkers such response. In fact, tPAI-1 levels alone were able to discriminate as carcinoembryonic antigen, CA 15-3, MMP-2, MMP-9, tis- responders from nonresponders with 75% sensitivity and sue polypeptide antigen (TPA), tissue polypeptide-specific 77% specificity prior to the start of NAC. tPAI-1 is a major antigen (TPS), EGFR, and HER-2/neu in predicting response physiological inhibitor of tissue-type plasminogen activators to NAC for breast cancer [33-36]. The results of these inves- and has been implicated in tumor growth, invasion, and angio- tigations have been mixed. To our knowledge, the panel of genesis. The function of tPAI-1 as a regulator of plasminogen serum biomarkers examined in the present study is the largest activation places it in a position to modulate degradation of the and most diverse to date and the majority of the relationships extracellular matrix and antiangiogenic effects mediated by we identify have not been described previously. plasmin and angiostatin, respectively. Several groups have illustrated experimentally the role of tPAI-1 in tumor progres- Our results indicate that elevated serum levels of IL-6, IL-8, sion and its negative prognostic value in breast cancer [42- and MMP-9 prior to the initiation of treatment correlate with 44]. improved clinical response. The observed increases in IL-6 and IL-8 serum levels of 2.74 and 3.13 pg/ml, respectively In sera collected after patients had received the initial cycle of (Figure 1a), were not significant in our study given the limited chemotherapy we observed that increased levels of IL-4, IL-8, 23-patient enrollment. Utilizing these data, we predict that an and adrenocorticotropic hormone and decreased levels of enrollment of 59 patients would be sufficient to confer signifi- insulin-like growth factor binding protein 1 all correlated with cance (P < 0.05) upon these observations with a power of 0.9. improved clinical response at differing levels of significance. Increased serum levels of the inflammatory cytokines IL-6 and The increase in levels of inflammatory cytokines following Page 6 of 9 (page number not for citation purposes) Available online http://breast-cancer-research.com/content/10/3/R45 chemotherapy is in line with clinical expectations and is evi- this will increase immensely. Continuing efforts in line with dence that the therapeutic agents are active in the patient's those presented here should bring us closer to providing system. The roles of the insulin-like growth factor system and effective and efficient individualized treatment to women diag- hormones in the response to chemotherapy have not been sig- nosed with this challenging disease. nificantly evaluated; however, both groups have known roles in the development of breast cancer [45,46]. Competing interests The authors declare that they have no competing interests. With regards to pathologic response, we observed a correla- tion between increased levels of soluble Fas ligand, MMP-2, Authors' contributions MIF, and EGFR and improved response. A proapoptotic BMN participated in the Luminex assays, oversaw the data response following chemotherapy, as evidenced by increased analysis, and drafted the manuscript. JRM and KB conceived soluble Fas ligand in the sera, is to be expected. Our observa- the study and coordination the transfer of patient samples. ST, tion of increased levels of MMP-2 in the sera of responders AR, TML, and YW carried out the statistical analysis. AEL con- supports the notion of matrix metalloproteinase involvement in ceived the study, participated in the study design, and helped breast cancer. The precise role of macrophage MIF in breast to draft the manuscript. cancer development and treatment response remains unknown, but MIF has been implicated in tumor cell survival Acknowledgements The present work was supported by the DAMD17-03-1-0696 DOD pathways [47]. The value of EGFR serum and tissue levels in Award, the 'Avon–NCI Progress for Patients' Award, and the predicting response to chemotherapy has been examined pre- BCTR0600911 Susan G Komen Foundation Award (AEL). The authors viously with inconclusive results [43,48]. 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Published: May 12, 2008

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