Proteomic analysis in endometrial cancer and endometrial hyperplasia tissues by 2D-DIGE technique

Journal Pre-proof Proteomic Analysis in Endometrial Cancer and Endometrial Hyperplasia Tissues by 2D-DIGE Technique Yasin Ceylan, Gurler Akpınar, Emek Doger, Murat Kasap, Nil Guzel, Kubra Karaosmanoglu, Sule Yıldırım Kopuk, Izzet Yucesoy

PII:

S2468-7847(19)30685-3

DOI:

https://doi.org/10.1016/j.jogoh.2019.101652

Reference:

JOGOH 101652

To appear in:

Journal of Gynecology Obstetrics and Human Reproduction

Received Date:

21 May 2019

Accepted Date:

18 October 2019

Please cite this article as: Ceylan Y, Akpınar G, Doger E, Kasap M, Guzel N, Karaosmanoglu K, Kopuk SY, Yucesoy I, Proteomic Analysis in Endometrial Cancer and Endometrial Hyperplasia Tissues by 2D-DIGE Technique, Journal of Gynecology Obstetrics and Human Reproduction (2019), doi: https://doi.org/10.1016/j.jogoh.2019.101652

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Proteomic Analysis in Endometrial Cancer and Endometrial Hyperplasia Tissues by 2D-DIGE Technique Yasin Ceylan1, Gurler Akpınar2, Emek Doger3, Murat Kasap4, Nil Guzel5, Kubra Karaosmanoglu5, Sule Yıldırım Kopuk6, Izzet Yucesoy7

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M.D., Kızıltepe State Hospital, Department of Obstetrics and Gynecology, Mardin, TURKEY

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Assoc. Prof., Kocaeli University School of Medicine, Department of Medical Biology, Kocaeli,

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TURKEY Assoc. Prof., Kocaeli University School of Medicine, Department of Obstetrics and Gynecology,

Kocaeli, TURKEY 4

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Professor, Kocaeli University School of Medicine, Department of Medical Biology, Kocaeli, TURKEY

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M.D., Kocaeli University School of Medicine, Department of Medical Biology, Kocaeli, TURKEY

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and Gynecology, Istanbul, TURKEY 7

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M.D., Sağlık Bilimleri University Umraniye Health and Education Hospital, Department of Obstetrics

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Professor, Kocaeli University School of Medicine, Department of Obstetrics and Gynecology, Kocaeli,

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TURKEY

Correspondence:

Yasin CEYLAN, MD Kızıltepe State Hospital

Mardin, TURKEY Phone: 00 90 (482) 312 39 44 Fax:00 90 (482) 312 72 37 E-mail: [email protected]

INTRODUCTION

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Endometrial cancer (EC) is the most frequent gynecologic cancer and is the 4th common in all woman’s cancers. EC is generally diagnosed in early stages due to its frequent symptom of uterine bleeding and its prognosis is quite good. Although progression to invasive

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cancer and advanced stages is rare, the prognosis proceeds poor in some cases and worldwide

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74000 deaths are seen annually due to EC. The reasons for these deaths are delayed diagnosis, inefficiency the estimate the prognosis of the disease and associated treatment failures and an

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poor response to chemotherapy and hormonotherapy[1]. Considering these, there is need for the discovery of new biomarkers that can be used as therapeutic targets for both diagnosis and

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treatment purposes.

Proteomics studies may show the changes in the level of tissue protein expression in

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different disease conditions and are especially used in the identification of bio-indicators that are exploited to determine the response of the diseases to diagnosis, prognosis and

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treatment[2]. Although proteomics studies in cancer cases up to now have succeeded to associate some proteins with the disease, such studies have not been able to clearly define the relationship between the disease and its molecular pathophysiology due to the insufficiencies in experimental approaches, ethnicity differences and the variations in interpreting the data from mass spectrometers.

The purpose of this study was to monitor the changes at the protein level during transition of the healthy endometrial tissue to a cancerous state. To achieve this purpose tissue samples from EC patients and from healthy counterparts were collected and subjected to high resolution two-dimensional difference gel electrophoresis (DIGE). The comparative analysis of the DIGE gels revealed the presence of differentially regulated proteins which were identified by MALDI-TOF/TOF spectrometry. The identified proteins were subjected to

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bioinformatics analysis to determine their potential as molecular therapeutic targets.

MATERIALS AND METHODS

The study was approved by the local ethical board and conducted at Kocaeli

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University Faculty of Medicine in the Gynecology Department, between September 2014– August 2015. The informed consents were obtained from each patient. Thirty cases who

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underwent dilatation and curettage (D&C) due to abnormal uterine bleeding and postmenopausal bleeding complaints and reported to have “benign endometrial changes

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(BEC)”, “complex atypical endometrial hyperplasia (CAEH)” and “endometrioid type adenocarcinoma (EA)” were included in this study. Of the 30 cases studied, total abdominal

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hysterectomy and bilateral salpingo-oophorectomy (TAH/BSO) were conducted on 10, TAH/BSO/pelvic lymph node dissection (PLND) was conducted on 4, and TAH/BSO/pelvic-

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paraaortic lymph node dissection (PPLND)/Omentectomy was conducted on 16. For all cases,

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uterus frozen-sections were sent to pathology for examination. During frozen-section examination, endometrial samples were taken from the patients for proteomics analysis and were immediately frozen in liquid nitrogen. The samples were kept at -80C until the analysis day.

Six study groups were created based on the pathology reports. BEC (Group 1, n=7), complex CAEH (Group 2 n=2), stage IA EA (Group 3 n=5), stage IB EA (Group 4 n=5), stage II EA (Group 5, n= 3) and stage III EA (Group 6, n=5).(Table 1)

Sample Preparation and Protein extraction Tissue samples minced on ice and washed with ice-cold washing buffer (10 mMTrisHCl, pH 7.0, 250 mM sucrose) was lysed in DIGE lysis buffer (7 M urea, 2 M thiourea, 4%

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CHAPS w/v, 30mMtris-HCl,pH 8.5) via homogenizer system with 0.5 mm stainless steel beads (Next Advance, USA). The soluble protein fraction was obtained by centrifugation at 20.000 ×g for 30 min at 4°C and the protein concentration was determined by using modified Lowry assay (BioRad, USA). The soluble protein containing supernatants were stored at

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−80°C.

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Preparation of the pooled samples

Equal amount of protein from each sample was combined into a single tube and the

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protein concentration of the pooled sample was measured. The measured protein concentration was compared with the calculated protein concentration to validate that the

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samples were correctly pooled. Further validation was achieved using SDS-PAGE followed by visual examination of the protein profiles.

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Minimal protein labeling and DIGE

Pooled protein samples were labeled with DIGE-specific Cy2, Cy3, or Cy5 in the dark

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according to the instructions provided by the manufacturer (Life Tech, USA) (Table 2). The labelling reactions were stopped by adding 1.0 μl of 10 mM lysine. Cy3-, Cy5-, and Cy2labeled protein samples were then combined (total 150 μg of protein) for 2D-DIGE analysis. The sample volume was brought to 250 μl with the DIGE sample buffer (7 M urea, 2 M thiourea, 4% CHAPS w/v, 20 mMDTT,pH 8.5) and the samples were then applied to 17 cm

IPG strip (Bio-Rad, USA) by passive rehydrated overnight at 20 °C. First and second dimension separations of DIGE strips were performed similarly as in 2DE experiments.

Image analysis of DIGE gels

The DIGE gels were visualized withVersaDoc4000 MP (BioRad, USA) by using three different light sources spot detection was performed with PDQuest Advance Analysis Software (BioRad, USA). Differentially regulated spots were selected and picked from a

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preparative 2D gel was prepared using a total of 1mg of protein (which was formed by pooling equal amounts of protein samples). All selected spots were cut by automated spot cutting tool, ExQuest spot cutter (BioRad, USA), and disposed into 96-well plates for further

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Protein identification by MALDI-TOF/TOF

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identification.

Protein identification experiments were performed at Kocaeli University DEKART

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Proteomics Laboratory by using ABSCIEX MALDI-TOF/TOF 5800 system (Applied Biosystems, Framingham, MA, USA). Protein identification is based on the protocol

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previously published [3]. In gel tryptic digestion was performed by using an in-gel digestion kit following the recommended protocol by the manufacturer (Pierce, USA).

Before

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deposition onto a MALDI plate, the digested peptide mixes were desalted with a 10 μL ZipTipC18 (Millipore, USA) and eluted with the matrix solution containing 10mg/mL α-

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Cyano-4-hydroxycinnamic acid before spotting onto the MALDI target plate. The TOF spectra were recorded in the positive ion reflector mode with a mass range from 400 to 2000 Da. Each spectrum was the cumulative average of 2000 laser shots. The spectra were calibrated with the trypsin auto digestion ion peaks m/z (842.510 and 2211.1046) as internal standards. Ten of the strongest peaks of the TOF spectra per sample were chosen for MS/MS analysis. All of the PMFs were searched in the MASCOT version 2.5 (Matrix Science) by

using a streamline software, ProteinPilot (ABSCIEX, USA), with the following criteria: National Center for Biotechnology Information nonredundant (NCBInr); species restriction to H. sapiens; enzyme of trypsin; at least five independent peptides matched; at most one missed cleavage site; MS tolerance set to ±50 ppm and MS/MS tolerance set to ±0.4 Da; fixed modification being carbamidomethyl (Cys) and variable modification being oxidation (Met); peptide charge of 1+ and being monoisotopic. Only significant hits, as defined by the MASCOT probability analysis (p< 0.05), were accepted.

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Statistical and Bioinformatics analysis Quantitative results were expressed as means ± standard deviation. Two-sample t-tests assuming unequal variances were used for the statistical analyses (SPSS version 20.0, IBM

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Corporation, Armonk, NY, USA). p < 0.05 was considered to indicate statistical significance. Protein-protein interaction network of the identified proteins was constructed with the

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online analysis tool STRING v10[4]. Classifications, biological processes, molecular

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Released

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functions were predicted by using a freely available classification system PANTHER (version 2016.07.5,http://www.pantherdb.org/),

(http://www.ncbi.nlm.nih.gov/pubmed) and

Swiss-Prot/TrEMBL

NCBI annotations

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(http://www.expasy.org/). Assignment of biological processes and subsequent construction of networks were done using the Ingenuity software (Ingenuity Systems, www.ingenuity.com).

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RESULTS

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The protein samples, labelled with Cy2, Cy3 and Cy5, were combined and subjected to 2-DE gel electrophoresis to determine the differentially regulated protein spots among the samples (Figure1). The differentially regulated protein spots were cut from an analytical gel and identified by MALDI-TOF/TOF (Table3). The positions of each of the identified protein spots were verified on the gels and presented on Figure 2.

Comparative analysis of protein extracts prepared from tissue samples obtained from stage IA EA with the protein extracts prepared from tissue samples obtained from the BEC showed that GRP78, GSTP1, ACTG, PDIA3, ENOA proteins were up regulated in stage IA EA while ALBU down was regulated. Similarly, when comparative analysis of protein extracts prepared from tissue samples obtained from stage IB EA were compared with the protein extracts prepared from tissue samples obtained from BEC, GSTP1, ACTB, ACTG, K2C8, ANXA1 and ENOA proteins

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were up regulated while TRFE was down regulated.

Additional comparative analysis was performed with protein extracts prepared from

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tissue samples obtained from stage II EA with protein extracts prepared from tissue samples obtained from the BEC tissue. GSTP1 and PDIA3 were up-regulated in stage II EA samples.

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Also, when protein extracts prepared from tissue samples obtained from the stage III

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EA were compared with the healthy controls, GSTP1, ACTB, K2C8, PDIA3, TRFE and ENOA were up regulated in the stage III EA tissues.

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Finally, protein extracts prepared from tissue samples obtained from the CAEH were compared with the healthy controls, HSPB1, EF-Tu and IDHC proteins were upregulated in

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the CAEH tissues.

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The distribution of the spot densities identified during comparative analysis were depicted in Figure 3a. The proteins whose expressions were induced in all the malign samples and in the

CAEH samples were compared as well. The expression levels of CALR, RSSA, ACTB, K2C8, UAP56(DDX39B), SODC, PSME1, PDIA3, ANXA1, CAH1, IDHC, PPIA and PPIB proteins displayed significant differential regulation. It was observed that the SODC was

down regulated in all EC groups while CAH1 and PPIB were down regulated only in the stage IA EA. The distribution of the intensities of the identified protein spots among the groups, were given in Figure3b. DISCUSSION Although it has been proposed that the proteomics analysis in EC is more informative and convenient than genomic and transcriptomic analyses, the information on this subject are

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still limited[5].The 2D-DIGE coupled with MALDI TOF/TOF-MS has the capacity to identify proteins that are at very low levels and differentially regulated in tissues. The present study aimed at revealing the changes in protein profiles at an early and an advanced stages.

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Li et al., have conducted two proteomics studies that compared EC and endometrial intraepithelial neoplasia cases with their healthy counterparts. They have concluded that

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epidermal fatty acid binding protein (E-FABP), calcyphosine (CAPS) and cyclophilin A

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might be important biomarkers for diagnosis, prognosis and response to treatment in EC and that survival decreased in cases where the CAPS level increased[5,6]. In two other similar studies, EC cases were compared with healthy endometrial tissues, Maxwell et al.[7] reported

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that the change in the expressions of ANXA-1 (annexin1), ANXA-2, PRDX-1 (peroxiredoxin1), PRDX-3, PRDX-4, PRDX-5, PRDX-6, and COX-2 (cytochrome c-oxidase

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subgroup2) were notable. Yoshizaki et al.[8] reported that the proteinEC-1 up regulated

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significantly while the proteinEC-2 down regulated in EC cases indicating that these two proteins might be potential biomarkers for the diagnosis of EC. Teng et al.[9] determined that PKM2 and HSPA5 levels were higher in advance stage cancer cases during their analysis of the tissue samples from early stage and advanced stage EC and from healthy control tissues. In the present study, when the endometrial protein expressions of healthy cases and the CAEH cases were compared, it was observed that the proteins K2C8, UAP56, GRP78,

ENOA, ACTB, GSTP1, PSME1, CALR, PPIA, PDIA3, IDHc were up regulated in EC tissues. On the other hand, the SOD1 level decreased as the cancer stage advanced. When EC and CAEH tissues were compared, it was observed that K2C8 and UAP56 were up regulated as the stage advanced while CAH1 and PPIB were down regulated in stage 1A samples although were up regulated in stage advanced. Among these indicators, the proteins that showed the closest correlation with advanced stage cancer were K2C8, UAP56, and GRP78. Similar to the present study, the increase in K2C8 level in EC was shown by

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immunohistochemical studies[10]. The UAP56 expression increases in ovary and lung tumors and decreases in testis and skin tumors[11]. The present study is the first one that provided the first evidence for the increase in UAP56 in parallel to the increase in EC stage. In various

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studies, the expression of GRP78 was shown to be up regulated and the up regulation was

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associated with metastasis and drug resistance[12,13,14]. Cali et al. determined that the expression of GRP78 level in neoplastic endometrium tissues clearly rised compared to the

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healthy group [14]. Luvsandagva et al. reported that GRP78 level was higher in grade 1 and 2 EA cases which were positive for estrogen receptor compared to grade 3 cases which were

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negative for estrogen receptor [15]. Similar to all these studies, in the present study, significantly high GRP78 levels were detected in cases of stage IA and stage III in

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comprasion to the control groups. We predicted that GRP78 was a promising biomarker candidate since similar results have been obtained in other studies.

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In studies investigating GSTP1 expression in EC cases, Chan et al. report that the

expression decreased in cancer cases compared to non-cancerous cases [16]. On the contrary, Yokoyama et al. and Fiolka et al. GSTP1 reported significant increase in expression in metastatic cases with advanced stage [17,18]. PSME1 has an activator role in the control of immune response, decreases in cervical carcinoma and hepatocellular carcinoma and increases in esophagus cancer [19,20]. In the present study, the PSME1 expression level was

high in all stages in the EA samples compared to the CAEH samples. However, no significant change was found in the present study when comparisons were made with the normal endometrium tissue. Although it is known that CALR expression is more in the estrogen-exposed endometrium then progesterone-exposed endometrium, the expression of CALR is less prominent in EA cases [21,22]. In our case, CALR expression in cancerous tissue was higher then in CAEH samples. However, a decrease was observed in the level of CALR expression

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at advanced stages. Considering that the CALR protein is a highly conserved endoplasmic reticulum protein that plays an important role in immunogenic cell death such as apoptosis, the decrease in its level was expected since cancer cells are resistant to apoptosis. It is our

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proposal that augmented CALR activity may be used to induce apoptosis in cancer cells.

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IDHc is a protein that is involved in glutathione regeneration. The mutations in this protein facilitates cancer development by causing the cell to become more sensitive to

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oxidative stress. In the present study, IDHc levels were significantly up regulated tumor samples in comparison to the CAEH samples. Pejić et al. reported that SOD1 levels, which is

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another free oxygen radical scavenger, decreases in tissues with EA in comprasion to the CAEH samples [23]. In the present study, the expression level of SOD1 was also lower in all

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carcinoma samples when compared to the CAEH samples. However, it is rather difficult to explicitly decide whether this was the causer or the effect in the chain of events leading to

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cancer. This may be related to SOD1 consumption related to increased endogen production of ROS and/or dysfunction of SOD1 due to mutation. Studies provide evidences that excess expression of the ACTG1 gene can lead to cancer development and can increase the migration, invasion and metastasis capacity of cancer cells [24]. Suppression of ACTG1 expression may be used in cancer treatment

preventing the migration, invasion and metastasis capacity of cancer cells [25]. In the present study, when it was compared to the control sample, ACTG1 was up ragulated more during early stages of the tumor, then its level dropped significantly during the advanced stages. The observations we and the other made implicate that the progress of the tumor differentiation may be responsible for the decrease in ACTG1 production. Some studies in the literature deal with the association between CAH isoenzymes CAH 2, CAH 9 and CAH 12 and the development of EC [26,27]. Our findings contributed to

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those studies and demonstrated that except in stage IA, the CAH1 levels was higher in the tumor samples in comparison to the CAEH samples.

It is reported that ANXA1 expression level decreased in cervical, prostate, breast,

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esophagus, B-cell non-Hodgkin’s lymphoma and increased in hepatic cancer, hairy cell

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leukemia, esophagogastric combined adenocarcinomas [28]. In the present study, the level of ANXA1 protein was high in all carcinoma samples when it was compared with the CAEH

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sample. However, down regulation of ANXA1 was also detected in tumoral spread outside the uterus.

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HSPs are cellular proteins that activate the cell in protection from fatal heat shock, UV radiation and various chemicals and that are also known to be associated with estrogen

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receptors (ER). Koya et al. and Zagorianakou et al. reported that the level of HSPB1

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expression was especially high in the CAEH group and that HSPB1 was also expressed in endometrial cancer developed from hyperplasia basis [29,30]. In the present study, a significant up regulation in the level of HSPB1 was observed in the CAEH samples when compared to the control samples. No significant change in HSPB1 level was observed in EA samples. This feature demonstrated that HSP proteins may not be useful in the prognosis prediction and treatment planning of EC.

CONCLUSION In the present study, significant elevations were observed in the levels of K2C8, UAP56, ENOA, ACTB, GRP78, GSTP1, PSME1, CALR, PPIA, PDIA3 and IDHc proteins when comparisons were made among the cancer cases and the healthy and CAEH cases. It is observed that the protein level of SOD1 was down regulated as the cancer stage increased. Our findings suggested that decrease in the level of a protein might be of value as the increase for identification of the cancer stage and establishment of a treatment plan. We determined

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that the induction of CALR activity may be a factor that progresses apoptosis, thus, may be a hope for postoperative new chemotherapy treatment methods. In addition, we determined that the levels of K2C8 and UAP56 as the stage of the adenocarcinoma groups increased when the

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expressions of the K2C8 and UAP56 proteins were compared to that of the CAEH. Moreover,

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when the expressions of the CAH1 and PPIB proteins are compared to CAEH and EA stages, we determined that the CAH1 and PPIB levels decreased in the stage 1A group but increased

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in more advanced stages. Among these indicators, the proteins that had the closest relation to

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Figure 1. 2-DE Gel Electrophoresis Images of After Combination Of Protein Samples Marked with Cy3, Cy5 and Cy2 in Experimental Groups

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Figure 2. 2D Preparative Gel Images and Positions of Spots of Experimental Groups

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3a. Analysis of the Intensity of Protein Spots which Identified in Experiments I, II, III, IV and V

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3b. Analysis of the Intensity of Protein Spots which Identified in Experiment VI

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Table 1. Grouping of patients according to histopathological features

Table 2. Experimental set up for differential minimal Cye labeling of soluble tissue protein extracts for DIGE analysis.

Internal controls were created by mixing equal amount of samples and used for normalization.

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Table 3. Proteins identified by MALDI TOF/TOF-MS analysis