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<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">OR</journal-id>
<journal-title-group>
<journal-title>Oncology Reports</journal-title></journal-title-group>
<issn pub-type="ppub">1021-335X</issn>
<issn pub-type="epub">1791-2431</issn>
<publisher>
<publisher-name>D.A. Spandidos</publisher-name></publisher></journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3892/or.2013.2540</article-id>
<article-id pub-id-type="publisher-id">or-30-03-1119</article-id>
<article-categories>
<subj-group>
<subject>Articles</subject></subj-group></article-categories>
<title-group>
<article-title>Glutathione and glutathione peroxidase expression in breast cancer: An immunohistochemical and molecular study</article-title></title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>JARDIM</surname><given-names>BRUNA VICTORASSO</given-names></name><xref rid="af1-or-30-03-1119" ref-type="aff">1</xref><xref rid="af2-or-30-03-1119" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author">
<name><surname>MOSCHETTA</surname><given-names>MARINA GOBBE</given-names></name><xref rid="af2-or-30-03-1119" ref-type="aff">2</xref><xref rid="af3-or-30-03-1119" ref-type="aff">3</xref></contrib>
<contrib contrib-type="author">
<name><surname>LEONEL</surname><given-names>CAMILA</given-names></name><xref rid="af1-or-30-03-1119" ref-type="aff">1</xref><xref rid="af2-or-30-03-1119" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author">
<name><surname>GELALETI</surname><given-names>GABRIELA BOTTARO</given-names></name><xref rid="af1-or-30-03-1119" ref-type="aff">1</xref><xref rid="af2-or-30-03-1119" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author">
<name><surname>REGIANI</surname><given-names>VITOR RAFAEL</given-names></name><xref rid="af2-or-30-03-1119" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author">
<name><surname>FERREIRA</surname><given-names>L&#x000CD;VIA CARVALHO</given-names></name><xref rid="af1-or-30-03-1119" ref-type="aff">1</xref><xref rid="af2-or-30-03-1119" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author">
<name><surname>LOPES</surname><given-names>JULIANA RAMOS</given-names></name><xref rid="af1-or-30-03-1119" ref-type="aff">1</xref><xref rid="af2-or-30-03-1119" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author">
<name><surname>DE CAMPOS ZUCCARI</surname><given-names>DEBORA AP. PIRES</given-names></name><xref rid="af2-or-30-03-1119" ref-type="aff">2</xref><xref rid="af3-or-30-03-1119" ref-type="aff">3</xref><xref ref-type="corresp" rid="c1-or-30-03-1119"/></contrib></contrib-group>
<aff id="af1-or-30-03-1119">
<label>1</label>Department of Biology, Sao Paulo State University - UNESP/IBILCE, 15090-000 S&#x000E3;o Jos&#x000E9; do Rio Preto, SP, Brazil</aff>
<aff id="af2-or-30-03-1119">
<label>2</label>Department of Molecular Biology, Laboratory of Molecular Research in Cancer (LIMC), Faculty of Medicine of Sao Jose do Rio Preto (FAMERP), 15090-000 S&#x000E3;o Jos&#x000E9; do Rio Preto, SP, Brazil</aff>
<aff id="af3-or-30-03-1119">
<label>3</label>Department of Molecular Biology, Faculty of Medicine of Sao Jose do Rio Preto (FAMERP), 15090-000 S&#x000E3;o Jos&#x000E9; do Rio Preto, SP, Brazil</aff>
<author-notes>
<corresp id="c1-or-30-03-1119">Correspondence to: Dr Debora Ap. Pires de Campos Zuccari, Laboratory of Molecular Research in Cancer (LIMC), Department of Molecular Biology, Faculty of Medicine of Sao Jose do Rio Preto (FAMERP), Brigadeiro Faria Lima 5416, 15090-000 S&#x000E3;o Jos&#x000E9; do Rio Preto, SP, Brazil, E-mail: <email>debora.zuccari@famerp.br</email></corresp></author-notes>
<pub-date pub-type="ppub">
<month>9</month>
<year>2013</year></pub-date>
<pub-date pub-type="epub">
<day>13</day>
<month>06</month>
<year>2013</year></pub-date>
<volume>30</volume>
<issue>3</issue>
<fpage>1119</fpage>
<lpage>1128</lpage>
<history>
<date date-type="received">
<day>20</day>
<month>02</month>
<year>2013</year></date>
<date date-type="accepted">
<day>18</day>
<month>04</month>
<year>2013</year></date></history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2013, Spandidos Publications</copyright-statement>
<copyright-year>2013</copyright-year>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/3.0">
<license-p>This is an open-access article licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. The article may be redistributed, reproduced, and reused for non-commercial purposes, provided the original source is properly cited.</license-p></license></permissions>
<abstract>
<p>The use of prognostic markers for breast cancer allows therapeutic strategies to be defined more efficiently. The expression of glutathione (GSH) and glutathione peroxidase (GPX) in tumor cells has been evaluated as a predictor of prognosis and response to cytotoxic treatments. Its immunoexpression was assessed in 63 women diagnosed with invasive ductal carcinoma in a retrospective study. The results showed that high GSH expression was associated with tumors negative for the estrogen receptor (ER) (P&lt;0.05), and GPX expression was associated with tumors negative for the progesterone receptor (PR) and patient mortality. Focusing on the 37 patients who received adjuvant chemotherapy/radiotherapy (Group I), high expression of GPX was associated with a high rate of patient mortality (P&lt;0.05). The 19 patients who received only adjuvant chemotherapy (Group II) showed high expression of GSH in relation to metastasis (P&lt;0.05). In addition, high levels of GPX expression were significantly associated with a shorter overall survival (P&lt;0.05). To confirm this, the expression of precursor genes of GSH &#x0005B;glutamate cysteine ligase (GCLC) and glutathione synthetase (GSS)&#x0005D; and the GPX gene was analyzed using quantitative PCR in cultured neoplastic mammary cells treated with doxorubicin. Doxorubicin treatment was able to eliminate tumor cells without alterations in the gene expression of GSS, but led to underexpression of the GCLC and GPX genes. Our results suggest that high levels of GPX may be related to the development of resistance to chemotherapy in these tumors, response to treatment and the clinical course of the breast cancer patients.</p></abstract>
<kwd-group>
<kwd>glutathione</kwd>
<kwd>immunohistochemistry</kwd>
<kwd>real-time PCR</kwd>
<kwd>chemotherapy</kwd>
<kwd>prognosis</kwd></kwd-group></article-meta></front>
<body>
<sec sec-type="intro">
<title>Introduction</title>
<p>Breast cancer is the second most common type of cancer worldwide and the most common in women (<xref rid="b1-or-30-03-1119" ref-type="bibr">1</xref>,<xref rid="b2-or-30-03-1119" ref-type="bibr">2</xref>). In Brazil, it is estimated that 52,650 new cases of this tumor emerged in 2012 (<xref rid="b2-or-30-03-1119" ref-type="bibr">2</xref>), whereas in the USA and western Europe, the estimate is for 500,000 new cases/year (<xref rid="b3-or-30-03-1119" ref-type="bibr">3</xref>). Despite the high incidence, early diagnosis and introduction of more effective treatments make it possible to reduce mortality and improve the quality of life of patients with this disease (<xref rid="b4-or-30-03-1119" ref-type="bibr">4</xref>).</p>
<p>Every prognostic marker employed for determining global patient survival is capable of generating important information related to the clinical behavior of mammary gland tumors. However, in most cases, they neither predict disease progression nor the response to chemotherapy (<xref rid="b5-or-30-03-1119" ref-type="bibr">5</xref>,<xref rid="b6-or-30-03-1119" ref-type="bibr">6</xref>). According to vant&#x02019;t Veer <italic>et al</italic>(<xref rid="b5-or-30-03-1119" ref-type="bibr">5</xref>), women with breast cancer at the same disease stage can have completely different responses to the same treatment.</p>
<p>Systemic treatment of breast cancer includes the use of cytotoxic, hormonal and immunotherapeutic agents. In general, these treatments are active at the beginning of therapy in 90&#x00025; of primary breast cancers and 50&#x00025; of metastases; however, after a variable period, the disease tends to progress (<xref rid="b1-or-30-03-1119" ref-type="bibr">1</xref>,<xref rid="b7-or-30-03-1119" ref-type="bibr">7</xref>).</p>
<p>Better predictive and prognostics markers are needed in clinical practice (<xref rid="b8-or-30-03-1119" ref-type="bibr">8</xref>), since studies of clinical and molecular characteristics of tumors allow therapeutic strategies to be designed more efficiently and with less toxicity (<xref rid="b1-or-30-03-1119" ref-type="bibr">1</xref>,<xref rid="b4-or-30-03-1119" ref-type="bibr">4</xref>,<xref rid="b9-or-30-03-1119" ref-type="bibr">9</xref>). In this context, the expression of antioxidant proteins in tumor cells has been assessed as a predictive and prognosis factor of the response to cytotoxic treatments (<xref rid="b10-or-30-03-1119" ref-type="bibr">10</xref>&#x02013;<xref rid="b12-or-30-03-1119" ref-type="bibr">12</xref>).</p>
<p>Glutathione (GSH) is a tripeptide comprising of glycine, cysteine and glutamic acid residues (<xref rid="b13-or-30-03-1119" ref-type="bibr">13</xref>). Its synthesis requires the participation of two enzymes consecutively. First glutamate cysteine ligase enzyme (GCLC) conjugates glutamic acid and cysteine, producing &#x003B3;-glutamyl cysteine. This compound with its sulfhydryl group (SH) is responsible for the antioxidant activity of GSH. The second step is the binding of &#x003B3;-glutamyl cysteine to glycine catalyzed by glutathione synthetase (GSS), producing the tripeptide &#x003B3;-glutamyl cysteine glycine, known as GSH (<xref rid="b14-or-30-03-1119" ref-type="bibr">14</xref>,<xref rid="b15-or-30-03-1119" ref-type="bibr">15</xref>).</p>
<p>Glutathione peroxidase (GPX) contains selenium at a catalytic site and uses GSH as an electron donor for the reduction of H<sub>2</sub>O<sub>2</sub> to H<sub>2</sub>O, converting itself to its oxidized form, glutathione disulfide (GSSG) (<xref rid="b16-or-30-03-1119" ref-type="bibr">16</xref>,<xref rid="b17-or-30-03-1119" ref-type="bibr">17</xref>). GSH is considered one of the most important agents of the antioxidant defense system of the cell. Because it is conjugated to GPX, GSH plays a role in the removal of xenobiotic and carcinogenic agents (<xref rid="b18-or-30-03-1119" ref-type="bibr">18</xref>).</p>
<p>High levels of GSH and/or GPX increase the antioxidant capacity, as observed in many tumor cells. Although the mechanism and the consequences of these changes are not well characterized (<xref rid="b17-or-30-03-1119" ref-type="bibr">17</xref>), recent research has demonstrated that an increase in antioxidants in neoplastic mammary tissue provides certain advantages to these cells when compared to healthy tissue. The presence of these enzymes in neoplastic cells may represent a low-grade response to treatments that cause oxidative damage, such as radiotherapy and various chemotherapeutics (<xref rid="b19-or-30-03-1119" ref-type="bibr">19</xref>,<xref rid="b20-or-30-03-1119" ref-type="bibr">20</xref>).</p>
<p>These previous findings show the importance of GSH and GPX expression in tumor cells, making them potential predictive and prognostic markers for breast cancer. Thus, the aim of this study was to determine the prognostic and predictive values of GSH and GPX expression and their relationship to several clinicopathological parameters, patient overall survival, and response to breast cancer treatment.</p></sec>
<sec sec-type="methods">
<title>Materials and methods</title>
<sec>
<title>Immunohistochemical study</title>
<sec>
<title>Sample characterization</title>
<p>In a retrospective study, tumor fragments were selected from 63 women aged 30 to 99 years (mean 58 years) attending the Obstetrics and Gynecology service, Hospital de Base, Faculty of Medicine of S&#x000E3;o Jos&#x000E9; do Rio Preto from 2000 to 2005. The clinicopathological parameters of the patients were obtained from the service medical records.</p>
<p>Patients with no other malignancy who were subjected to mastectomy/quandrantectomy but not to neoadjuvant chemotherapy/radiotherapy were included in the study. All the patients had been diagnosed with invasive ductal carcinoma. A panel of classic prognostic markers were evaluated: estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2/neu), p53 tumor-suppressor gene and the cell proliferation marker, Ki-67. Furthermore, the patients were divided in to 4 subgroups according to the immunohistochemistry of the following markers: luminal A (ER<sup>&#x0002B;</sup>PR<sup>&#x0002B;</sup>HER-2/neu<sup>&#x02212;</sup>), luminal B (ER<sup>&#x0002B;</sup>PR<sup>&#x0002B;</sup>HER-2/neu<sup>&#x0002B;</sup>), HER-2/neu<sup>&#x0002B;</sup>, and triple-negative (ER<sup>&#x02212;</sup>PR<sup>&#x02212;</sup>HER-2/neu<sup>&#x02212;</sup>).</p>
<p>The parameters for histopathological evaluation were those recommended by the International Union Against Cancer (UICC) TNM classification of 1989. Among the entire group, 37 patients (59&#x00025;) who had received the same treatment including surgery and adjuvant chemotherapy/radiotherapy &#x0005B;5-fluorouracil/epirubicin/cyclophosphamide (FEC)&#x0005D; were designated as group I; 19 patients (30&#x00025;) who had received only adjuvant chemotherapy were designated as group II and 7 patients (11&#x00025;) who had received no treatment after surgery were designated as group III. The patients underwent clinical evaluation every 3&#x02013;4 months. Local tumor recurrence and metastasis in such cases were carefully monitored, as well as the date and cause of death in order to record the survival time of each patient.</p>
<p>Patient follow-up ranged from 120 to 2,704 days, with a median of 1,473 days. For analysis of survival curves, the patients were divided into higher and lower enzyme expression groups using a cut-off value established by the receiver operating characteristic curve (ROC). Only patients who died of tumor disease were included in the final analysis. Patients with an incomplete follow-up were excluded. The study was approved by the Research Ethics Committee of the Faculty of Medicine of S&#x000E3;o Jos&#x000E9; do Rio Preto (protocol no. 25372009).</p></sec>
<sec>
<title>Immunohistochemical technique</title>
<p>For administration of the technique, blocks of paraffin-embedded tumor fragments were cut to provide 3-&#x003BC;m sections. The sections were prepared on silanized slides and subsequently deparaffinized, rehydrated through graded alcohol and incubated with 3&#x00025; hydrogen peroxidase for 30 min to block endogenous peroxidase activity. Antigen retrieval was carried out in a Pan Steam (ARNO, S&#x000E3;o Paulo, Brazil) at 95&#x000B0;C with buffer for 35 min for each specific antibody (<xref rid="tI-or-30-03-1119" ref-type="table">Table I</xref>). After cooling, the slides were covered with bovine serum albumin (BSA) solution for 30 min and incubated at 4&#x000B0;C overnight with the antibodies described in <xref rid="tI-or-30-03-1119" ref-type="table">Table I</xref>.</p>
<p>Subsequently they were washed with phosphate-buffered saline (PBS) for 15 min and incubated with the Easy Path kit (Erviegas, S&#x000E3;o Paulo, Brazil), which consisted of the secondary antibody biotinylated anti-mouse, rabbit, and goat immunoglobulins for 1 h and the streptavidin-peroxidase complex for 30 min, followed by washing with PBS for 15 min. We applied 0.5&#x00025; 3,3&#x02032;-diaminobenzidine tetrahydrochloride (DAB; Signet Laboratories, Dedham, MA, USA) to the slides for 2&#x02013;5 min at 20&#x02013;22&#x000B0;C. The slides were counterstained with Harris&#x02019;s hematoxylin for 40 sec. Negative controls were obtained by omitting the primary antibody, and liver or prostate tissue served as an internal positive control in every assay.</p></sec>
<sec>
<title>Evaluation of immunohistochemical staining</title>
<p>To assess the immunoexpression of GSH and GPX, multiple fields were examined on each slide, particularly demarcated areas with distinct brown staining. The slides were photographed and the enzymes were quantified by AxioVision software and by observation through a &#x000D7;40 lens of a Zeiss Axioskop2 microscope.</p>
<p>For each sample, three regions of tumor tissue were selected and 20 spots of the tumor cells were marked within each region, thereby analyzing 60 different spots of every sample to average the relative intensity of immunoreactivity. The values were obtained as arbitrary units (au), and the mean optical density (MOD) indicated the specific staining intensity in the immunoreactive areas.</p>
<p>The staining of HER-2/neu was considered by counting the number of positively stained cells in the membrane and was expressed as a percentage of the total tumor cells. According to ASCO/CAP guidelines (<xref rid="b21-or-30-03-1119" ref-type="bibr">21</xref>) the following categories were defined: 0, no immunostaining; 1&#x0002B;, weak or incomplete staining of the membrane in any proportion of tumor cells; 2&#x0002B;, complete membrane staining or weak staining in 10&#x00025; of the tumor cells stained; 3&#x0002B;, uniform and intense staining of the membrane in more than 30&#x00025; of tumor cells. Tumors scored with 0 or 1&#x0002B; were considered negative and those with scores 2&#x0002B; or 3&#x0002B; were considered positive. Tumors were categorized into two groups in relation to cellular proliferation according to the staining of Ki-67 based on the count of the number of positively stained cells and expressed as a percentage of the total: 0 or 1, no cellular proliferation; 2 or 3, the presence of cellular proliferation. The same parameter was used in the classification of the ER, PR and p53 tumor-suppressor gene: 0 or 1, no staining; 2, 3 or 4, presence of staining.</p></sec>
<sec>
<title>Statistical analysis</title>
<p>The patients were separated into groups according to the clinicopathological variables. The averages of the densitometric analysis referring to the densitometry results and the quantification of the different breast tumor groups were compared by Student&#x02019;s t-test or ANOVA, followed by the Bonferroni test. The values are expressed as means &#x000B1; SEM.</p>
<p>The cut-off for the risk of death was determined by ROC. Survival curves were plotted by the Kaplan-Meier method, and the differences between the curves were evaluated by a log-rank test and hazard function. Multivariate logistic regression was performed to evaluate the factors that influenced death. For all tests, P&lt;0.05 was considered to indicate a statistically significant result. All analyses were performed using GraphPad Prism 4 and StatsDirect software.</p></sec></sec>
<sec>
<title>Molecular study</title>
<sec>
<title>Sample characterization</title>
<p>Twelve core biopsies or tumor fragments &gt;2 cm were collected by surgery from the breast cancer patients who were diagnosed with ductal carcinoma, who had not undergone chemotherapy and/or radiation therapy prior to the point of collection. The tumor fragments were washed in PBS containing 1&#x00025; penicillin/streptomycin, cut into microfragments with a scalpel and incubated at 37&#x000B0;C in 5&#x00025; CO<sub>2</sub> with RPMI-1640 supplemented with 20&#x00025; BSA, 1&#x00025; penicillin/streptomycin and 1&#x00025; L-glutamine. The cells were cultivated until they reached 80&#x00025; confluence and were subjected to immunocytochemistry using the primary antibodies anti-cytokeratin, anti-vimentin and anti-calponin to confirm epithelial origin.</p></sec>
<sec>
<title>Treatment of the cells in vitro</title>
<p>Cells were divided into two groups: control (no treatment), and cells treated with 0.2 mg routine chemotherapy (doxorubicin) for 24 h. At the end of the treatment, cell viability was verified by cell counting in a Neubauer chamber (LaborOptik, Bad Homburg, Hessen, Germany) with trypan blue dye (0.4&#x00025;).</p></sec>
<sec>
<title>Quantitative PCR</title>
<p>Total RNA was extracted from the cell culture with TRIzol (Invitrogen Life Technologies, S&#x000E3;o Paulo, Brazil) as recommended by the laboratory and the total RNA from each sample was reverse transcribed to complementary DNA (cDNA) using a High Capacity cDNA kit (Applied Biosystems, Foster City, CA, USA).</p>
<p>Quantitative real-time polymerase chain reactions were performed in triplicate using StepOnePlus&#x02122; System (Applied Biosystems). Briefly, the reactions were performed in a 20 &#x003BC;l volume with 10 &#x003BC;l of Power SYBR<sup>&#x000AE;</sup>-Green PCR Master Mix (Applied Biosystems), 250 nM of each primer, and 10 ng of cDNA. PCR conditions consisted of 50&#x000B0;C for 2 min, 95&#x000B0;C for 10 min, followed by 35 cycles of 95&#x000B0;C for 15 sec and 60&#x000B0;C for 1 min. Following PCR, dissociation curve analysis was performed to confirm the desired single gene product: one cycle of 95&#x000B0;C for 15 sec, 60&#x000B0;C for 1 min, and 95&#x000B0;C for 15 sec was carried out.</p>
<p>Each transcript level was normalized by division with the expression values of <italic>HPRT1</italic> used as an internal control. Gene expression stability was analyzed by geNorm software. The transcript level was calculated using the 2<sup>&#x02212;Ct</sup> method (<xref rid="b22-or-30-03-1119" ref-type="bibr">22</xref>). The Ct was the difference between the threshold cycles of the target and the internal control and Ct was the difference between the average Ct of the sample and the average Ct of the calibrator sample. The fold difference (relative abundance) was calculated using the 2<sup>&#x02212;&#x00394;&#x00394;CT</sup> formula and plotted as mean &#x000B1; SD of the triplicate reactions. At least 3-fold differences were considered significant.</p>
<p>A negative control was included in each reaction, and one sample was chosen for reaction calibration. Experiments were repeated when the coefficient of variation was higher than 5&#x00025;. After each reaction, the products were analyzed on 2&#x00025; agarose gel stained with ethidium bromide.</p>
<p>The gene was searched, selected in PubMed (<ext-link xlink:href="http://www.ncbi.nlm.nih.gov/entrez" ext-link-type="uri">http://www.ncbi.nlm.nih.gov/entrez</ext-link>), and synthesized from human messenger RNA already sequenced and confirmed. Its design was made using the program PRIMER 3 (<ext-link xlink:href="http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.Cgi" ext-link-type="uri">http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.Cgi</ext-link>). The <italic>HPRT1</italic> gene was used as an endogenous control. Primers used for amplification include: GSS foward, 5&#x02032;-TGCTAAAGCCCCAGAGAG AG-3&#x02032; and reverse, 5&#x02032;-AGCAGGCAATTCTCAAAAGG-3&#x02032;; GCLC foward, 5&#x02032;-GCACAACGTTCTCAAGTG-3&#x02032; and reverse, 5&#x02032;-TGGTTTGGGTTTGTCCTTTC-3&#x02032;; GPX foward, 5&#x02032;-ATGGCGCAATTGTCCAAG-3&#x02032; and reverse, 5&#x02032;-CTGGCC TCCCCTTACAGTG-3&#x02032;; HPRT1 foward, 5&#x02032;-TTATAGTCAAG GGCATATCC-3&#x02032; and reverse, 5&#x02032;-AGCTTGCTGGTGAAA AGGAC-3&#x02032;.</p>
<p>The genes were classified as underexpressed (samples with less than -1 log3 measurement) and overexpressed (samples with quantification greater than 1 log3).</p></sec></sec></sec>
<sec sec-type="results">
<title>Results</title>
<p>All tumors were histological grade II invasive ductal carcinoma, with a preponderance of tumors of clinical stage II (76.2&#x00025;), in agreement with the TNM (tumor, node and metastasis) classification.</p>
<sec>
<title>Immunohistochemical procedure</title>
<p>Immunostaining of GSH and GPX was evident in the cytoplasm and focally in the nuclei of the neoplastic cells, whereas the stroma showed no reactivity (<xref rid="f1-or-30-03-1119" ref-type="fig">Fig. 1</xref>).</p>
<p>Regarding the classical markers, GSH expression was correlated with tumor ER-positivity, and GPX correlated with tumor PR-negativity (P&#x0003D;0.03) (<xref rid="tII-or-30-03-1119" ref-type="table">Table II</xref>). Only 13 (20.6&#x00025;) of the patients had tumors with luminal expression A (ER<sup>&#x0002B;</sup>PR<sup>&#x0002B;</sup>HER-2/neu<sup>&#x02212;</sup>), whereas 22 (35&#x00025;) of the patients had tumors with luminal expression B (ER<sup>&#x0002B;</sup>PR<sup>&#x0002B;</sup>HER-2/neu<sup>&#x0002B;</sup>); 41 (65&#x00025;) patients were HER-2/neu<sup>&#x0002B;</sup> independently of the hormone receptors, and 9 (14.2&#x00025;) patients had a triple-negative (ER<sup>&#x02212;</sup> PR<sup>&#x02212;</sup>HER-2/neu<sup>&#x02212;</sup>) phenotype. Nevertheless, there was no correlation between GSH or GPX expression and the different clinical groups (P&gt;0.05).</p>
<p>Immunohistochemical expression of GSH and GPX was assessed in relation to the clinical course of the patients, taking into account local recurrence, metastasis and/or rate of mortality (<xref rid="tII-or-30-03-1119" ref-type="table">Table II</xref>). High expression of GPX was significantly correlated with a high rate of patient mortality (P&#x0003D;0.03) (<xref rid="tIII-or-30-03-1119" ref-type="table">Table III</xref>). Group I showed higher GPX expression in patients that succumbed to disease (P&#x0003D;0.02) and Group II showed higher GSH expression in patients with metastasis (P&#x0003D;0.03) (<xref rid="tIII-or-30-03-1119" ref-type="table">Table III</xref>).</p>
<p>ROC was calculated to explore the performance, and the threshold values for GSH and GPX expression were used to predict the risk of mortality in breast cancer patients. The ROC graph indicated calculations for sensitivity/specificity of the patients. Thus, the best cut-off value for GSH to discriminate high risk of death in all patients was MOD &#x0003D; 170 au (sensitivity &#x0003D; 30&#x00025; and specificity &#x0003D; 88&#x00025;). For GPX the best cut-off in the total population was: MOD &#x0003D; 200 au (sensitivity &#x0003D; 60&#x00025; and specificity &#x0003D; 67&#x00025;).</p>
<p>Multivariate logistic regression showed that clinical stages III or IV and metastasis were associated with an increased risk of mortality in the breast cancer patients (P&lt;0.05) (<xref rid="tIV-or-30-03-1119" ref-type="table">Table IV</xref>). In addition, in patients &gt;50 years of age, high levels of cell proliferation (Ki-67 positivity), local recurrence and higher GPX expression showed a significant trend towards an increased risk of mortality (P&#x0003D;0.05&#x02013;0.06) (<xref rid="tIV-or-30-03-1119" ref-type="table">Table IV</xref>).</p>
<p>Patient follow-up ranged from 144 days (0.4 years) to 2,704 days (7.4 years) with a median of 1,542 days (4.2 years). For analysis of the survival curves, the patients were divided into higher and lower enzyme expression groups using a cut-off value established from the ROC curve. There was no correlation between GSH expression and overall survival in groups I, II and III (P&gt;0.05). High GPX expression was correlated with a lower overall survival rate in the entire group (P&#x0003D;0.03) (<xref rid="f2-or-30-03-1119" ref-type="fig">Fig. 2</xref>).</p></sec>
<sec>
<title>Quantitative PCR</title>
<p>Samples collected for the <italic>in vitro</italic> study were from patients diagnosed with invasive ductal carcinoma; 3 patients with histological grade I (25&#x00025;), 6 with grade II (50&#x00025;) and 3 with grade III (25&#x00025;). Only one patient had local recurrence and 1 patient died of metastasis. Following cell culture, the epithelial origin was confirmed by immunocytochemistry, and GCLC, GSS and GPX gene expression was evaluated after treatment with doxorubicin.</p>
<p>The GCLC gene, responsible for the first step in the synthesis of GSH, was underexpressed in 7 (58.3&#x00025;) of the culture samples following treatment with chemotherapy. This gene was overexpressed in one (8.3&#x00025;) of the samples, and 4 (33.3&#x00025;) samples failed to reach the minimum level of expression in the log3 range required to be considered indistinguishable from the controls (<xref rid="f3-or-30-03-1119" ref-type="fig">Fig. 3</xref>). Only in 1 (8.3&#x00025;) culture sample treated with chemotherapy was the GSS gene overexpressed. Eleven (91.6&#x00025;) samples fail to reach the minimum level of expression in the log3 range required to be considered indistinguishable from the controls (<xref rid="f4-or-30-03-1119" ref-type="fig">Fig. 4</xref>).</p>
<p>The GPX gene was underexpressed in 6 (50&#x00025;) of the culture samples treated with chemotherapy. Only one (8.3&#x00025;) sample showed overexpression and 5 (41.6&#x00025;) samples showed no significant difference in expression compared to the control cells (<xref rid="f5-or-30-03-1119" ref-type="fig">Fig. 5</xref>).</p></sec></sec>
<sec sec-type="discussion">
<title>Discussion</title>
<p>Studies concerning the association between immunohistochemical expression of GSH, as well as GPX, the clinicopathological parameters of breast cancer patients are sparse. The majority of previous studies have used biochemical methods to quantify the activity of these proteins, comparing patients with breast cancer and healthy control patients (<xref rid="b19-or-30-03-1119" ref-type="bibr">19</xref>,<xref rid="b20-or-30-03-1119" ref-type="bibr">20</xref>,<xref rid="b23-or-30-03-1119" ref-type="bibr">23</xref>,<xref rid="b24-or-30-03-1119" ref-type="bibr">24</xref>).</p>
<p>In this study, tumors considered ER-positive presented higher expression of the GSH protein when compared to those that were ER-negative. In addition, PR-negative tumors presented higher expression of GPX compared to those that were PR-positive. According to Fernandes <italic>et al</italic>(<xref rid="b25-or-30-03-1119" ref-type="bibr">25</xref>), individual analyses of the hormonal receptors are not conclusive. With the combined evaluation of hormonal receptors and the HER-2/neu protein, mammary carcinomas can be grouped into 4 main subtypes that provide important information related to the degree of malignancy and therapeutic response to certain drugs (<xref rid="b25-or-30-03-1119" ref-type="bibr">25</xref>,<xref rid="b26-or-30-03-1119" ref-type="bibr">26</xref>). Triple-negative carcinomas are considered more aggressive than the luminal A or B subtypes, or even those overexpressing HER-2/neu. There was no statistical correlation between GSH and GPX expression and these carcinoma subtypes.</p>
<p>The immunohistochemical expression of GSH and GPX was also related to the clinical progression of the breast cancer patients. Patients that received only adjuvant chemotherapy (Group II) and had metastases showed higher GSH expression. Ballatorri <italic>et al</italic>(<xref rid="b17-or-30-03-1119" ref-type="bibr">17</xref>) demonstrated that a high level of GSH increased the antioxidant capacity of neoplastic cells, making them more resistant to chemotherapy. Based on this, high expression of GSH can be characterized as an indicator of low response to chemotherapy in those analyzed patients in this study, and may have contributed to the development of metastasis.</p>
<p>High expression of GPX was associated with a high rate of mortality, upon univaried and multivariate analyses. In addition, patients with lower GPX expression had a lower overall survival time. The association between high GPX expression and mortality remained significant when evaluated only in the patients restricted to the group of 37 women treated with adjuvant chemotherapy and radiotherapy (Group I). The correlations found in this study may be explained on the basis of enzymatic reactions catalyzed by GPX. Some chemotherapeutic and radiotherapeutic protocols potentially increase the already existent oxidative stress in neoplastic processes, causing damage to DNA and cell death (<xref rid="b27-or-30-03-1119" ref-type="bibr">27</xref>). High levels of GPX are known to correlate with cellular responses to oxidative stress. In this way, cytotoxic treatments can reduce intracellular GPX concentrations, based on the high concentration of GSSG in the environment, or, on the other hand, cytotoxic treatments can induce GPX expression as a cellular response to a high concentration of H<sub>2</sub>O<sub>2</sub>(<xref rid="b17-or-30-03-1119" ref-type="bibr">17</xref>,<xref rid="b20-or-30-03-1119" ref-type="bibr">20</xref>,<xref rid="b28-or-30-03-1119" ref-type="bibr">28</xref>,<xref rid="b29-or-30-03-1119" ref-type="bibr">29</xref>). A high level of GPX helps prevent oxidative damage that would otherwise lead to tumor cell death due to the applied treatments (<xref rid="b18-or-30-03-1119" ref-type="bibr">18</xref>,<xref rid="b19-or-30-03-1119" ref-type="bibr">19</xref>).</p>
<p><italic>In vitro</italic> studies corroborate the participation of GSH and GPX in cellular resistance to treatments. In this study, there was no significant expression of GSS after treatment with doxorubicin, whereas the GCLC and GPX genes were underexpressed in 58.8 and 50&#x00025; of the samples, respectively.</p>
<p>Many studies have demonstrated that alterations in expression of genes responsible for the synthesis of GSH or GPX usually occur after <italic>in vitro</italic> treatment with doxorubicin or similar drugs. It is suggested that a large production of reactive oxygen species (ROS) following treatment with doxorubicin is responsible for the cytotoxicity noted in neoplastic cells, and as a consequence, these cells overexpress genes responsible for the synthesis of antioxidants, such as GSH and GPX, making them more resistant to oxidative damages (<xref rid="b30-or-30-03-1119" ref-type="bibr">30</xref>). Ozkan and Fiskin (<xref rid="b31-or-30-03-1119" ref-type="bibr">31</xref>) found that the application of epirubicin (analogous to the structure of doxorubicin) in mammary neoplastic cells reduced GSH and GPX activity within 24 h of <italic>in vitro</italic> exposure. More unlikely, a study by Ilvsova <italic>et al</italic>(<xref rid="b32-or-30-03-1119" ref-type="bibr">32</xref>) showed that the total GSH concentration in the blood of breast cancer patients increased significantly 24 h after doxorubicin administration.</p>
<p>Han <italic>et al</italic>(<xref rid="b33-or-30-03-1119" ref-type="bibr">33</xref>), using the MCF-7 breast cancer cell line, found a high sensitivity to doxorubicin when the levels of GSH decreased. Vibet <italic>et al</italic>(<xref rid="b34-or-30-03-1119" ref-type="bibr">34</xref>) using docosahexaenoic acid, known to increase the oxidative mechanism of chemotherapeutics in mammary neoplastic cells when combined with doxorubicin, showed that a high concentration of ROS, due to this treatment, inhibited GPX activity. The same finding was noted in animal models of breast cancer. In this way, Sun <italic>et al</italic>(<xref rid="b35-or-30-03-1119" ref-type="bibr">35</xref>) observed that high H<sub>2</sub>O<sub>2</sub> concentrations increased the sensivity of tumor cells <italic>in vitro</italic> and <italic>in vivo</italic> not only to doxorubicin, but to ionizing radiation. In contrast, Di <italic>et al</italic>(<xref rid="b36-or-30-03-1119" ref-type="bibr">36</xref>) demonstrated that GSH overexpression did not prevent apoptosis in tumor cells after treatment with doxorubicin, suggesting that the cytotoxicity of this drug is not directly correlated with ROS production.</p>
<p>In conclusion, GPX was highly expressed in breast cancer cells of patients with a worse clinical outcome and reduced overall survival who underwent chemotherapy and radiotherapy. Thus, it is suggested that GPX has an important role in the progression of this disease, especially as a possible prognostic marker for these patients. In addition, there was a relationship between application of the chemotherapeutic drug doxorubicin and reduced expression of the GPX gene, making it a candidate marker for predicting therapeutic responses in breast cancer cases, yet this needs to be confirmed in larger studies.</p></sec></body>
<back>
<ack>
<title>Acknowledgements</title>
<p>The authors thank the Capes/Coordena&#x000E7;&#x000E3;o de Aperfei&#x000E7;oamento de Pessoal de N&#x000ED;vel Superior and FAPESP/Funda&#x000E7;&#x000E3;o de Amparo &#x000E0; Pesquisa do Estado de S&#x000E3;o Paulo for their financial support. We are also grateful to Dr Dalisio de Santi Neto, Pathologist of the Department of Pathology and Forensic Medicine - FAMERP for the collaboration in this study.</p></ack>
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<floats-group>
<fig id="f1-or-30-03-1119" position="float">
<label>Figure 1</label>
<caption>
<p>Images of immunohistochemical staining for GSH and GPX (original magnification &#x000D7;400). (A) Immunostaining for GSH in breast cancer. Immunostaining was evident in the cytoplasm (arrow) and nucleus (arrowhead) of neoplastic cells. (B) Immunostaining for GSH in normal breast tissue of patients, with weak immunoreactivity in the cytoplasm of cells. (C) Immunostaining for GPX in breast cancer. Immunostaining was evident in the cytoplasm (arrow) and was focally present in the nucleus (arrowhead) of neoplastic cells. (D) Immunostaining for GPX in normal breast tissue, with weak immunoreactivity in the cytoplasm of cells.</p></caption>
<graphic xlink:href="OR-30-03-1119-g00.gif"/></fig>
<fig id="f2-or-30-03-1119" position="float">
<label>Figure 2</label>
<caption>
<p>Overall survival of the patients with high (dotted line) and low (continuous line) GPX expression. (Cut-off selected was MOD &#x0003D; 200 au; P&#x0003D;0.03; OR, 2.63; 95&#x00025; CI, 1.05&#x02013;7.01). OR, odds ratio; CI, confidence interval.</p></caption>
<graphic xlink:href="OR-30-03-1119-g01.gif"/></fig>
<fig id="f3-or-30-03-1119" position="float">
<label>Figure 3</label>
<caption>
<p>Quantitative gene expression of GCLC in the breast cancer cells. Quantitative gene expression in cells exposed to doxorubicin in relation to the pool of unexposed cells (control). Value of gene expression in log3.</p></caption>
<graphic xlink:href="OR-30-03-1119-g02.gif"/></fig>
<fig id="f4-or-30-03-1119" position="float">
<label>Figure 4</label>
<caption>
<p>Quantitative gene expression of GSS in the breast cancer cells. Quantitative gene expression in cells exposed to doxorubicin in relation to the pool of unexposed cells (control). Value of gene expression in log3.</p></caption>
<graphic xlink:href="OR-30-03-1119-g03.gif"/></fig>
<fig id="f5-or-30-03-1119" position="float">
<label>Figure 5</label>
<caption>
<p>Quantitative gene expression of GPX in the breast cancer cells. Quantitative gene expression in cells exposed to doxorubicin in relation to the pool of unexposed cells (control). Value of gene expression in log3.</p></caption>
<graphic xlink:href="OR-30-03-1119-g04.gif"/></fig>
<table-wrap id="tI-or-30-03-1119" position="float">
<label>Table I</label>
<caption>
<p>Specifications and manufacturers of the antibodies used for the study.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom">Antibody</th>
<th align="center" valign="bottom">Clonality</th>
<th align="center" valign="bottom">Dilution</th>
<th align="center" valign="bottom">Buffer</th>
<th align="center" valign="bottom">Company</th></tr></thead>
<tbody>
<tr>
<td align="left" valign="top">Primary antibody anti-ER</td>
<td align="left" valign="top">Monoclonal</td>
<td align="left" valign="top">1:100</td>
<td align="left" valign="top">Tris EDTA pH 9.0</td>
<td align="left" valign="top">Dako</td></tr>
<tr>
<td align="left" valign="top">Primary antibody anti-PR</td>
<td align="left" valign="top">Monoclonal</td>
<td align="left" valign="top">1:100</td>
<td align="left" valign="top">Tris EDTA pH 9.0</td>
<td align="left" valign="top">Biocare Medical</td></tr>
<tr>
<td align="left" valign="top">Primary antibody anti-HER-2/neu</td>
<td align="left" valign="top">Polyclonal</td>
<td align="left" valign="top">1:200</td>
<td align="left" valign="top">Tris EDTA pH 9.0</td>
<td align="left" valign="top">Dako</td></tr>
<tr>
<td align="left" valign="top">Primary antibody anti-p53</td>
<td align="left" valign="top">Monoclonal</td>
<td align="left" valign="top">1:500</td>
<td align="left" valign="top">Tris EDTA pH 9.0</td>
<td align="left" valign="top">Zymed</td></tr>
<tr>
<td align="left" valign="top">Primary antibody anti-Ki-67</td>
<td align="left" valign="top">Monoclonal</td>
<td align="left" valign="top">1:100</td>
<td align="left" valign="top">EDTA pH 8.0</td>
<td align="left" valign="top">Spring</td></tr>
<tr>
<td align="left" valign="top">Primary antibody anti-GSH</td>
<td align="left" valign="top">Monoclonal</td>
<td align="left" valign="top">1:100</td>
<td align="left" valign="top">Citrate pH 6.0</td>
<td align="left" valign="top">Millipore</td></tr>
<tr>
<td align="left" valign="top">Primary antibody anti-GPX</td>
<td align="left" valign="top">Polyclonal</td>
<td align="left" valign="top">1:1,200</td>
<td align="left" valign="top">Citrate pH 6.0</td>
<td align="left" valign="top">Abcam</td></tr></tbody></table>
<table-wrap-foot><fn id="tfn1-or-30-03-1119">
<p>ER, estrogen receptor; PR, progesterone receptor; HER-2/neu, human epidermal growth factor receptor-2; GSH, glutathione; GPX, glutathione peroxidase.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="tII-or-30-03-1119" position="float">
<label>Table II</label>
<caption>
<p>Mean expression of GSH and GPX and its correlation with clinicopathological characteristics of the breast cancer patients.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom">Clinicopathological factors</th>
<th align="center" valign="bottom">No. of patients n (&#x00025;)</th>
<th align="center" valign="bottom">MOD of GSH</th>
<th align="center" valign="bottom">MOD of GPX</th></tr></thead>
<tbody>
<tr>
<td colspan="4" align="left" valign="top">Patient age (years)</td></tr>
<tr>
<td align="left" valign="top">&#x02003;&#x02265;50</td>
<td align="center" valign="top">16 (25.4)</td>
<td align="center" valign="top">187.8&#x000B1;3.517</td>
<td align="center" valign="top">192.6&#x000B1;2.234</td></tr>
<tr>
<td align="left" valign="top">&#x02003;&lt;50</td>
<td align="center" valign="top">47 (75.6)</td>
<td align="center" valign="top">184.3&#x000B1;3.253</td>
<td align="center" valign="top">194.1&#x000B1;4.240</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.54</td>
<td align="center" valign="top">0.74</td></tr>
<tr>
<td colspan="4" align="left" valign="top">Smoker</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">11 (17.5)</td>
<td align="center" valign="top">188.0&#x000B1;5.177</td>
<td align="center" valign="top">196.7&#x000B1;5.951</td></tr>
<tr>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">52 (82.5)</td>
<td align="center" valign="top">184.3&#x000B1;2.887</td>
<td align="center" valign="top">192.2&#x000B1;2.041</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.58</td>
<td align="center" valign="top">0.38</td></tr>
<tr>
<td colspan="4" align="left" valign="top">Hormone therapy</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">11 (17.5)</td>
<td align="center" valign="top">179.7&#x000B1;4.918</td>
<td align="center" valign="top">195.9&#x000B1;4.863</td></tr>
<tr>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">52 (82.5)</td>
<td align="center" valign="top">186.3&#x000B1;2.842</td>
<td align="center" valign="top">192.3&#x000B1;2.164</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.32</td>
<td align="center" valign="top">0.49</td></tr>
<tr>
<td colspan="4" align="left" valign="top">Lymph node involvement</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Positive</td>
<td align="center" valign="top">13 (20.6)</td>
<td align="center" valign="top">186.2&#x000B1;4.546</td>
<td align="center" valign="top">193.7&#x000B1;4.464</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Negative</td>
<td align="center" valign="top">50 (79.4)</td>
<td align="center" valign="top">184.7&#x000B1;2.992</td>
<td align="center" valign="top">192.5&#x000B1;2.249</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.81</td>
<td align="center" valign="top">0.80</td></tr>
<tr>
<td colspan="4" align="left" valign="top">Histological grade</td></tr>
<tr>
<td align="left" valign="top">&#x02003;I</td>
<td align="center" valign="top">3 (4.7)</td>
<td align="center" valign="top">175.5&#x000B1;21.50</td>
<td align="center" valign="top">191.0&#x000B1;5.000</td></tr>
<tr>
<td align="left" valign="top">&#x02003;II</td>
<td align="center" valign="top">50 (79.4)</td>
<td align="center" valign="top">184.0&#x000B1;2.837</td>
<td align="center" valign="top">192.2&#x000B1;2.301</td></tr>
<tr>
<td align="left" valign="top">&#x02003;III</td>
<td align="center" valign="top">10 (15.9)</td>
<td align="center" valign="top">190.9&#x000B1;5.360</td>
<td align="center" valign="top">194.9&#x000B1;3.650</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.30</td>
<td align="center" valign="top">0.51</td></tr>
<tr>
<td colspan="4" align="left" valign="top">Clinical stage</td></tr>
<tr>
<td align="left" valign="top">&#x02003;I</td>
<td align="center" valign="top">4 (6.3)</td>
<td align="center" valign="top">175.3&#x000B1;8.686</td>
<td align="center" valign="top">204.0&#x000B1;13.320</td></tr>
<tr>
<td align="left" valign="top">&#x02003;II</td>
<td align="center" valign="top">48 (76.2)</td>
<td align="center" valign="top">185.4&#x000B1;3.112</td>
<td align="center" valign="top">192.6&#x000B1;2.207</td></tr>
<tr>
<td align="left" valign="top">&#x02003;III</td>
<td align="center" valign="top">9 (14.3)</td>
<td align="center" valign="top">185.4&#x000B1;5.373</td>
<td align="center" valign="top">188.9&#x000B1;5.832</td></tr>
<tr>
<td align="left" valign="top">&#x02003;IV</td>
<td align="center" valign="top">2 (3.2)</td>
<td align="center" valign="top">195.5&#x000B1;0.500</td>
<td align="center" valign="top">199.5&#x000B1;0.500</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.75</td>
<td align="center" valign="top">0.51</td></tr>
<tr>
<td colspan="4" align="left" valign="top">Median tumor diameter (cm)</td></tr>
<tr>
<td align="left" valign="top">&#x02003;&gt;3 cm</td>
<td align="center" valign="top">13 (20.6)</td>
<td align="center" valign="top">186.9&#x000B1;4.190</td>
<td align="center" valign="top">196.8&#x000B1;3.211</td></tr>
<tr>
<td align="left" valign="top">&#x02003;&#x02264;3 cm</td>
<td align="center" valign="top">50 (79.4)</td>
<td align="center" valign="top">184.5&#x000B1;3.022</td>
<td align="center" valign="top">192.0&#x000B1;2.329</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.69</td>
<td align="center" valign="top">0.32</td></tr>
<tr>
<td colspan="4" align="left" valign="top">Estrogen receptor</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Positive</td>
<td align="center" valign="top">46 (73)</td>
<td align="center" valign="top">188.1&#x000B1;2.089</td>
<td align="center" valign="top">191.4&#x000B1;2.484</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Negative</td>
<td align="center" valign="top">17 (27)</td>
<td align="center" valign="top">176.4&#x000B1;7.285</td>
<td align="center" valign="top">197.2&#x000B1;2.671</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.03<xref rid="tfn2-or-30-03-1119" ref-type="table-fn">a</xref></td>
<td align="center" valign="top">0.19</td></tr>
<tr>
<td colspan="4" align="left" valign="top">Progesterone receptor</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Positive</td>
<td align="center" valign="top">37 (58.7)</td>
<td align="center" valign="top">188.3&#x000B1;2.330</td>
<td align="center" valign="top">189.4&#x000B1;2.870</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Negative</td>
<td align="center" valign="top">26 (41.3)</td>
<td align="center" valign="top">1802&#x000B1;5.106</td>
<td align="center" valign="top">198.0&#x000B1;2.160</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.11</td>
<td align="center" valign="top">0.03 <xref rid="tfn2-or-30-03-1119" ref-type="table-fn">a</xref></td></tr>
<tr>
<td colspan="4" align="left" valign="top">HER-2/neu</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Positive</td>
<td align="center" valign="top">41 (65)</td>
<td align="center" valign="top">188.1&#x000B1;2.199</td>
<td align="center" valign="top">193.1&#x000B1;2.447</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Negative</td>
<td align="center" valign="top">22 (35)</td>
<td align="center" valign="top">178.8&#x000B1;6.180</td>
<td align="center" valign="top">192.6&#x000B1;3.389</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.08</td>
<td align="center" valign="top">0.90</td></tr>
<tr>
<td colspan="4" align="left" valign="top">p53</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Positive</td>
<td align="center" valign="top">44 (69.8)</td>
<td align="center" valign="top">184.4&#x000B1;3.353</td>
<td align="center" valign="top">194.8&#x000B1;2.322</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Negative</td>
<td align="center" valign="top">19 (30.2)</td>
<td align="center" valign="top">186.4&#x000B1;3.747</td>
<td align="center" valign="top">188.7&#x000B1;3.606</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.73</td>
<td align="center" valign="top">0.16</td></tr>
<tr>
<td colspan="4" align="left" valign="top">Ki-67 cell proliferation index</td></tr>
<tr>
<td align="left" valign="top">&#x02003;High</td>
<td align="center" valign="top">30 (47.6)</td>
<td align="center" valign="top">185.3&#x000B1;4.526</td>
<td align="center" valign="top">194.2&#x000B1;2.878</td></tr>
<tr>
<td align="left" valign="top">&#x02003;Low</td>
<td align="center" valign="top">33 (52.4)</td>
<td align="center" valign="top">183.9&#x000B1;2.680</td>
<td align="center" valign="top">191.8&#x000B1;2.724</td></tr>
<tr>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.78</td>
<td align="center" valign="top">0.54</td></tr></tbody></table>
<table-wrap-foot><fn id="tfn2-or-30-03-1119">
<label>a</label>
<p>Significant value as determined by Student&#x02019;s t-test.</p></fn><fn id="tfn3-or-30-03-1119">
<p>GSH, expression of glutathione; GPX, glutathione peroxidase; MOD, mean optical density; HER-2/neu, human epidermal growth factor receptor-2.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="tIII-or-30-03-1119" position="float">
<label>Table III</label>
<caption>
<p>Association of GSH and GPX expression and treatment and clinical outcome of the breast cancer patients.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom">Group</th>
<th align="left" valign="bottom">Clinical outcome</th>
<th align="center" valign="bottom">No. of patients n (&#x00025;)</th>
<th align="center" valign="bottom">MOD of GSH</th>
<th align="center" valign="bottom">MOD of GPX</th></tr></thead>
<tbody>
<tr>
<td align="left" valign="top">Total Group</td>
<td colspan="4" align="left" valign="top">Local recurrence</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">6 (9.5)</td>
<td align="center" valign="top">179.7&#x000B1;3.412</td>
<td align="center" valign="top">196.3&#x000B1;9.315</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">57 (90.5)</td>
<td align="center" valign="top">185.5&#x000B1;2.778</td>
<td align="center" valign="top">192.3&#x000B1;2.004</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.50</td>
<td align="center" valign="top">0.56</td></tr>
<tr>
<td align="left" valign="top"/>
<td colspan="4" align="left" valign="top">Metastasis</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">23 (36.5)</td>
<td align="center" valign="top">186.8&#x000B1;3.030</td>
<td align="center" valign="top">196.5&#x000B1;3.379</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">40 (63.5)</td>
<td align="center" valign="top">183.9&#x000B1;3.617</td>
<td align="center" valign="top">190.9&#x000B1;2.389</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.59</td>
<td align="center" valign="top">0.17</td></tr>
<tr>
<td align="left" valign="top"/>
<td colspan="4" align="left" valign="top">Death due to disease</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">20 (32)</td>
<td align="center" valign="top">183.5&#x000B1;3.549</td>
<td align="center" valign="top">199.1&#x000B1;2.867</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">43 (68)</td>
<td align="center" valign="top">185.7&#x000B1;3.354</td>
<td align="center" valign="top">190.1&#x000B1;2.459</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.68</td>
<td align="center" valign="top">0.03<xref rid="tfn4-or-30-03-1119" ref-type="table-fn">a</xref></td></tr>
<tr>
<td align="left" valign="top">Group I</td>
<td colspan="4" align="left" valign="top">Local recurrence</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">5 (13.5)</td>
<td align="center" valign="top">180.4&#x000B1;4.082</td>
<td align="center" valign="top">203.2&#x000B1;6.111</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">32 (86.5)</td>
<td align="center" valign="top">184.1&#x000B1;4.326</td>
<td align="center" valign="top">192.3&#x000B1;2.705</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.74</td>
<td align="center" valign="top">0.14</td></tr>
<tr>
<td align="left" valign="top"/>
<td colspan="4" align="left" valign="top">Metastasis</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">14 (38)</td>
<td align="center" valign="top">181.6&#x000B1;4.223</td>
<td align="center" valign="top">196.3&#x000B1;4.908</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">23 (62)</td>
<td align="center" valign="top">184.8&#x000B1;5.556</td>
<td align="center" valign="top">192.3&#x000B1;2.808</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.68</td>
<td align="center" valign="top">0.44</td></tr>
<tr>
<td align="left" valign="top"/>
<td colspan="4" align="left" valign="top">Death due to disease</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">13 (35)</td>
<td align="center" valign="top">179.3&#x000B1;4.033</td>
<td align="center" valign="top">201.6&#x000B1;3.362</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">24 (65)</td>
<td align="center" valign="top">185.9&#x000B1;5.393</td>
<td align="center" valign="top">189.5&#x000B1;3.163</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.41</td>
<td align="center" valign="top">0.02<xref rid="tfn4-or-30-03-1119" ref-type="table-fn">a</xref></td></tr>
<tr>
<td align="left" valign="top">Group II</td>
<td colspan="4" align="left" valign="top">Local recurrence</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">1 (5)</td>
<td align="center" valign="top">176.0&#x000B1;0.000</td>
<td align="center" valign="top">158.0&#x000B1;0.000</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">18 (95)</td>
<td align="center" valign="top">185.1&#x000B1;4.195</td>
<td align="center" valign="top">193.1&#x000B1;4.009</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">-</td>
<td align="center" valign="top">-</td></tr>
<tr>
<td align="left" valign="top"/>
<td colspan="4" align="left" valign="top">Metastasis</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">6 (31.5)</td>
<td align="center" valign="top">196.8&#x000B1;3.311</td>
<td align="center" valign="top">200.2&#x000B1;5.382</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">13 (68.5)</td>
<td align="center" valign="top">179.9&#x000B1;4.954</td>
<td align="center" valign="top">187.2&#x000B1;5.384</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.03<xref rid="tfn4-or-30-03-1119" ref-type="table-fn">a</xref></td>
<td align="center" valign="top">0.15</td></tr>
<tr>
<td align="left" valign="top"/>
<td colspan="4" align="left" valign="top">Death due to disease</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">5 (26)</td>
<td align="center" valign="top">189.2&#x000B1;8.789</td>
<td align="center" valign="top">190.0&#x000B1;5.030</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">14 (74)</td>
<td align="center" valign="top">183.0&#x000B1;4.555</td>
<td align="center" valign="top">191.7&#x000B1;5.532</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.51</td>
<td align="center" valign="top">0.86</td></tr>
<tr>
<td align="left" valign="top">Group III</td>
<td colspan="4" align="left" valign="top">Local recurrence</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">0 (0)</td>
<td align="center" valign="top">-</td>
<td align="center" valign="top">-</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">7 (100)</td>
<td align="center" valign="top">193.3&#x000B1;2.168</td>
<td align="center" valign="top">195.3&#x000B1;4.412</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">-</td>
<td align="center" valign="top">-</td></tr>
<tr>
<td align="left" valign="top"/>
<td colspan="4" align="left" valign="top">Metastasis</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">3 (43)</td>
<td align="center" valign="top">191.0&#x000B1;2.309</td>
<td align="center" valign="top">195.0&#x000B1;11.060</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">4 (57)</td>
<td align="center" valign="top">195.0&#x000B1;3.391</td>
<td align="center" valign="top">195.5&#x000B1;2.630</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.41</td>
<td align="center" valign="top">0.96</td></tr>
<tr>
<td align="left" valign="top"/>
<td colspan="4" align="left" valign="top">Death due to disease</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;Yes</td>
<td align="center" valign="top">2 (28.5)</td>
<td align="center" valign="top">196.0&#x000B1;1.000</td>
<td align="center" valign="top">205.0&#x000B1;12.00</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;No</td>
<td align="center" valign="top">5 (71.5)</td>
<td align="center" valign="top">192.2&#x000B1;2.956</td>
<td align="center" valign="top">191.4&#x000B1;3.641</td></tr>
<tr>
<td align="left" valign="top"/>
<td align="left" valign="top">&#x02003;P-value</td>
<td align="center" valign="top"/>
<td align="center" valign="top">0.47</td>
<td align="center" valign="top">0.18</td></tr></tbody></table>
<table-wrap-foot><fn id="tfn4-or-30-03-1119">
<label>a</label>
<p>Significant value as determined by Student&#x02019;s t-test.</p></fn><fn id="tfn5-or-30-03-1119">
<p>GSH, expression of glutathione; GPX, glutathione peroxidase; MOD, mean optical density.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="tIV-or-30-03-1119" position="float">
<label>Table IV</label>
<caption>
<p>Results of the multivariate logistic regression analysis.</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="bottom">Variables</th>
<th align="center" valign="bottom">OR</th>
<th align="center" valign="bottom">95&#x00025; CI</th>
<th align="center" valign="bottom">P-value</th></tr></thead>
<tbody>
<tr>
<td align="left" valign="top">Age &#x02265;50 years</td>
<td align="center" valign="top">918.55</td>
<td align="center" valign="top">0.99&#x02013;851,872.18</td>
<td align="left" valign="top">0.05<xref rid="tfn6-or-30-03-1119" ref-type="table-fn">a</xref></td></tr>
<tr>
<td align="left" valign="top">Smoker</td>
<td align="center" valign="top">2.30</td>
<td align="center" valign="top">0.00&#x02013;6,851.12</td>
<td align="left" valign="top">0.83</td></tr>
<tr>
<td align="left" valign="top">Large tumor size (&gt;3 cm)</td>
<td align="center" valign="top">1.32</td>
<td align="center" valign="top">0.05&#x02013;33.00</td>
<td align="left" valign="top">0.86</td></tr>
<tr>
<td align="left" valign="top">Lymph node involvement</td>
<td align="center" valign="top">31.62</td>
<td align="center" valign="top">0.39&#x02013;2517.38</td>
<td align="left" valign="top">0.12</td></tr>
<tr>
<td align="left" valign="top">Staging III or IV</td>
<td align="center" valign="top">460.42</td>
<td align="center" valign="top">1.33&#x02013;15,8371.26</td>
<td align="left" valign="top">0.03<xref rid="tfn7-or-30-03-1119" ref-type="table-fn">b</xref></td></tr>
<tr>
<td align="left" valign="top">Histological grade III</td>
<td align="center" valign="top">0.01</td>
<td align="center" valign="top">0.00&#x02013;86.94</td>
<td align="left" valign="top">0.32</td></tr>
<tr>
<td align="left" valign="top">ER positivity</td>
<td align="center" valign="top">14.97</td>
<td align="center" valign="top">0.42&#x02013;525.45</td>
<td align="left" valign="top">0.13</td></tr>
<tr>
<td align="left" valign="top">PR positivity</td>
<td align="center" valign="top">0.007</td>
<td align="center" valign="top">0.00&#x02013;1.73</td>
<td align="left" valign="top">0.07</td></tr>
<tr>
<td align="left" valign="top">HER-2/neu negativity</td>
<td align="center" valign="top">11.26</td>
<td align="center" valign="top">0.33&#x02013;378.73</td>
<td align="left" valign="top">0.17</td></tr>
<tr>
<td align="left" valign="top">Cell proliferation (Ki-67 positivity)</td>
<td align="center" valign="top">66.57</td>
<td align="center" valign="top">0.75&#x02013;5,905.44</td>
<td align="left" valign="top">0.06<xref rid="tfn6-or-30-03-1119" ref-type="table-fn">a</xref></td></tr>
<tr>
<td align="left" valign="top">p53 positivity</td>
<td align="center" valign="top">0.018</td>
<td align="center" valign="top">0.00&#x02013;1.56</td>
<td align="left" valign="top">0.07</td></tr>
<tr>
<td align="left" valign="top">Chemotherapy</td>
<td align="center" valign="top">15.22</td>
<td align="center" valign="top">0.05&#x02013;4,337.16</td>
<td align="left" valign="top">0.34</td></tr>
<tr>
<td align="left" valign="top">Radiotherapy</td>
<td align="center" valign="top">0.12</td>
<td align="center" valign="top">0.00&#x02013;5.31</td>
<td align="left" valign="top">0.27</td></tr>
<tr>
<td align="left" valign="top">Metastasis</td>
<td align="center" valign="top">1,397.97</td>
<td align="center" valign="top">7.90&#x02013;247,365.34</td>
<td align="left" valign="top">0.006<xref rid="tfn7-or-30-03-1119" ref-type="table-fn">b</xref></td></tr>
<tr>
<td align="left" valign="top">Local recurrence</td>
<td align="center" valign="top">57,817.26</td>
<td align="center" valign="top">0.98&#x02013;3,390,813,161.68</td>
<td align="left" valign="top">0.05<xref rid="tfn6-or-30-03-1119" ref-type="table-fn">a</xref></td></tr>
<tr>
<td align="left" valign="top">High GSH expression</td>
<td align="center" valign="top">0.16</td>
<td align="center" valign="top">0.001&#x02013;14.42</td>
<td align="left" valign="top">0.43</td></tr>
<tr>
<td align="left" valign="top">High GPX expression</td>
<td align="center" valign="top">117.26</td>
<td align="center" valign="top">0.68&#x02013;19,969.60</td>
<td align="left" valign="top">0.06<xref rid="tfn6-or-30-03-1119" ref-type="table-fn">a</xref></td></tr></tbody></table>
<table-wrap-foot><fn id="tfn6-or-30-03-1119">
<label>a</label>
<p>Trend toward significance;</p></fn><fn id="tfn7-or-30-03-1119">
<label>b</label>
<p>statistically significant value.</p></fn><fn id="tfn8-or-30-03-1119">
<p>OR, odds ratio; CI, confidence interval; ER, estrogen receptor; PR, progesterone receptor; HER-2/neu, human epidermal growth factor receptor-2; GSH, glutathione; GPX, glutathione peroxidase.</p></fn></table-wrap-foot></table-wrap></floats-group></article>
