Down Regulated Micro RNA-145 as a Marker to Diagnose Breast Cancer in Egypt

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1 Med. J. Cairo Univ., Vol. 84, No. 1, September: , Down Regulated Micro RNA-145 as a Marker to Diagnose Breast Cancer in Egypt OLFAT G. SHAKER, M.D.*; YASSER H. NASSAR, M.D.*; AMR A. ZAHRA, M.D.**; REHAB M. ABD EL-FADEL, M.Sc.** and MOHAMED S. EL-MARZOKI, M.D.*** The Department of Medical Biochemistry & Molecular Biology, Faculty of Medicine, Cairo* & Fayoum** Universities and The Department of General Surgery, Faculty of Medicine, Cairo University*** 1113 countries, which may be attributed to different lifestyle and genetic factors [2]. MiRNAs are small non-coding single-stranded RNAs transcribed from genomic DNA and processed to mature mirnas by Drosha in the nucleus and subsequently Dicer in the cytoplasm. MicroR- NAs (mirnas, mirs) are powerful epigenetic regulators that have an overall inhibitory effect on expression of genes. Its discovery in the 1990s opened a new layer of regulation in understanding cancer development [3,4]. Altered mirna expression is likely to contribute to human disease, including cancer [5]. Amplification or over expression of mirnas can down regulate tumor suppressors or other genes involved in cell differentiation, thereby contributing to tumor formation by stimulating proliferation, angiogenesis and invasion, i.e., they act as oncogenes. Similarly, mirnas can down regulate different proteins with oncogenic activity, i.e., they act as tumor suppressors [6]. Mar-Aguilar et al., [7] found that seven mirnas (mir-10b, mir-21, mir-125b, mir-145, mir-155 mir-191 and mir-382) had different expression patterns in serum of breast cancer patients compared to healthy controls. MiR-145 is concentrated in the nuclear region of myoepithelial cell layer of lobules and ducts and in smooth muscle cells within blood vessels. A noticeable decrease of mir-145 expression was observed in hyperplastic, probable preneoplastic, ducts present in some of the cases examined in tumor tissue, mir-145 expression was dramatically reduced or completely eliminated in epithelial cells Lorenzo et al., [8].

2 1114 Down Regulated Micro RNA-145 as a Marker to Diagnose Breast Cancer in Egypt Subjects and Methods Ethics statement: All human studies have been reviewed by Ethics Committee in Faculty of Medicine, Cairo University which approved this research. Fifty Egyptian females diagnosed as breast cancer according to history taking clinical examination, imaging, and surgical biopsy were included in this study. They were recruited from General Surgery Department, Al-Kasr Al-Eni Hospital, Faculty of Medicine, Cairo University, Cairo, Egypt. Collected in a period from 2012 to Twenty five healthy controls were recruited during routine checkup. Informed consent was obtained from all the subjects enrolled in this study. Group I: (n=25) healthy females as a control group. Group II: (n=50) patients with breast carcinoma. Inclusion criteria: Adult females, age ranged from (37-70) years. No previous treatment with chemotherapy or radiotherapy. Exclusion criteria: Age below 37 and above 70 years. Previous treatment with chemotherapy or radiotherapy. Other malignancy. Sample collection: Fasting blood samples were collected by venipuncture. Blood samples were incubated at 37ºC for 15 minutes then centrifuged at 2000xg for 10 minutes at room temperature; sera were separated and stored at 80ºC till used for quantitation of mirna-145 in serum. Serum mirnas assay: RNA extraction: Total RNA with preserved mirnas was extracted from 200µL serum by mirneasy extraction kit (Qiagen, Valencia, CA, USA) using 1000µL QIAzol lysis reagent and incubated for 5min at RT. Then, 100µL chloroform were added, vortexed for 15sec, and incubated for 2-3min at RT. This was followed by centrifugation at 14000rpm at 4ºC for 15min. The upper watery phase was removed and 0.5 times of its volume (100%) ethanol was added. Seven hundred µl of this mixture were placed in RNeasy mini spin column in 2ml collection tube and cen- trifuged at 10000rpm at RT for 15sec. After the mixture had completely passed the column, seven hundered µl of buffer RWT were added to each column, and again centrifuged at 10000rpm at RT for 15sec. Five hundred µl buffer RPE were added to the column and centrifuged at 10000rpm at RT for 15sec. After this, another 500µL buffer RPE were added to the column and centrifuged at 10000rpm at RT for 2min. The column was placed in a new collection tube then centrifuged at full speed for 2min. The column was transferred to new 1.5ml collection tube and 50µL RNase-free water was pipetted directly onto the column and centrifuged for 1min. at 10000rpm to elute RNA. Reverse Transcription (RT): Reverse transcription kits made specifically for accurate analysis of the chosen mirnas from serum samples was used. Reverse transcription was carried out on 5ng of total RNA in a final volume of 20µL RT reactions (incubated for 60 min at 37ºC, 5min at 95ºC, and then maintained at 4ºC) using the mirneasy serum/plasma Reverse Transcription Kit (Qiagen, Valencia, CA, USA) according to the manufacturer's instructions. Microarray platform and quantitative PCR (qpcr): Expressions of mature mirnas, were evaluated by qrt-pcr analysis according to the manufacturer's protocol. The housekeeping mirna SNORD68 was used as an endogenous control. For real time PCR, 5 µl of diluted RT products (cdna template) was mixed with SYBR Green Master Mix (Qiagen, Valencia, CA, USA) in a final volume of 25µL and added to a custom 96 well plate miscript mirna PCR arrays which is enriched with mirna forward and reverse-mirna-specific primer. The plate was sealed with optical thin wall 8-cap strips. Realtime PCR reactions were performed using an Applied Biosystems 7500 Real Time PCR System (Foster city, CA, USA) with the following conditions: 95ºC for 15min, followed by 40 cycles at 94ºC for 15s, and 55ºC for 30s and 70ºC for 34s. The Cycle Threshold (CT) is defined as the number of cycles required for the fluorescent signal to cross the threshold in real-time PCR. Expression of mirnas was reported as ACt value. The ACt was calculated by subtracting the CT values of mirna SNORD68 from the CT values of the target mirnas. As there is an inverse correlation between ACt and mirna expression level, lower ACt values were associated with increased mirna. The resulting normalized ACt values were used in calculating relative expression values by using 2 A(Ct), these values are directly related to the mirna expression levels. The 2 AA(Ct) method

3 Olfat G. Shaker, et al of was used to determine relative-quantitative levels of individual mirnas. Statistical analysis: - Data was coded and entered using the statistical package SPSS version Data was summarized using mean, standard deviation and range for quantitative variables, and frequencies (number of cases) and relative frequencies (percentages) for categorical variables. - Comparison of quantitative variables was done using the nonparametric Kruskal-Wallis when comparing more than 2 groups and using the nonparametric Mann-Whitney U test when comparing 2 groups. - For comparing categorical data, Chi square ( x 2 ) test was performed. Exact test was used instead when the expected frequency is less than 5. - Receiver Operator Characteristic (ROC) curves were derived and Area-Under-the Curve (AUC) analysis was performed to get the best cutoff value of mirna-145 in serum. p-value <0.05 was taken as statistically significant. Results The current study was conducted on fifty Egyptian females with breast cancer with age (37-70 years). Twenty five healthy females with matched age, served as a control group. Group I: (n=25) healthy females as a control group. Group II: (n=50) patients with breast carcinoma. Table (1): Description of breast cancer groups. Table (2): Comparison between breast cancer patients and controls as regards gene expression of mirna 145 in serum. Variables Control Breast cancer group p- value Mean SD Mean SD mirna <0.001* (Relative ratio) Table (2) shows a significant difference between patients and controls as regards gene expression of mirna-145 (p=<0.001). The mirna-145was significantly lower in breast cancer patients than controls. Table (3): Relationship between gene expression of mirna- 145 in serum and pathological data of tumor in patient group. Variables Mean Standard deviation p- value T: T * T N: N N2+N M: M ZERO ER/PR: Negative Positive Tumor type: Invasive ductal Invasive lobular T: Tumor, N: Lymph Node, M: Metastasis. Variables Percent % Table (3) shows a significant difference between Family history: T2 and T3 patients as regard gene expression of No 44 mirna-145 in serum (p=0.047*). And no significant difference between serum mirna-145 level Yes 56 and other pathological data of tumor in patient group. T (tumor size): T2 T3 N (nodal affection): N1 N2 N3 M (metastasis): M1 M zero ER/PR (estrogen/progesterone receptors): Negative Positive Tumor type: Invasive ductal Invasive lobular Sensitivity ROC Curve Specificity Fig. (1): Detection of breast cancer cases using mirna-145.

4 1116 Down Regulated Micro RNA-145 as a Marker to Diagnose Breast Cancer in Egypt As regards the ROC curve, AUC=. 8 10, the best cutoff value for detection of cancer for mirna- 145=0.795 with sensitivity 74% and specificity 100%. Area under curve p- value Lower Bound Asymptotic 95% confidence interval Upper Bound Discussion One in eight women will be diagnosed with breast cancer in their lifetime. It is the second leading cause of death in women, with >40,000 deaths annually. Although the incidence and mortality rates of breast cancer in western countries have decreased or at least been stable over the last few decades, both rates are increasing in many developing countries [1]. In women with very dense breast tissue, sensitivity of screening mammograms can be as low as 40 to 50% [9]. Magnetic Resonance Imaging (MRI) of the breast and breast ultrasound could improve cancer detection in these cases, but these imaging techniques are not routinely used for BC screening [10]. For this reason, our aim is searching for noninvasive markers to detect breast cancer. MicroRNAs (mirnas, mir) are approximately 22 nucleotides long, endogenous, single-stranded, non-protein-coding RNA molecules that regulate gene expression at the posttranscriptional level. Since their discovery in 1993, mirnas have caused worldwide interest due to their characteristic function and modes of action, providing a new understanding of the central dogma of molecular biology which is DNA is transcripted to form RNA which translated to form protein [11]. Micro RNA have been reported in a wide variety of organisms ranging from single-cell algae to humans, suggesting that Micro RNA is a critical cellular regulatory element [12]. The level of mirnas altered during inflammatory reaction and tumorigenesis indicate that cancerassociated mirnas in the circulation may originate from the immunologic system or tumor, and that dysregulation of mirnas may be an important link between immunity and cancer [13]. MiR-145 is down regulated in atherosclerosis where mir-145 controls differentiation of smooth muscle cells [14]. Li et al., [15] found significante down regulation of micro RNA mir- 145 in Ductal Carcinoma in Situ (DCIS). MiR-145 is known as a tumor suppressor in many human cancers, it has an inhibitory role in tumoral angiogenesis, cell growth and invasion and tumor growth and it may play an important inhibitory role in breast cancer [16]. Our study group included 50 females (37-70 year old) with breast cancer, and 25 age matched healthy females as a control group. The cancer group showed 56% with previous family history of breast cancer, 70% with T2 and 30% T3, 8% with N1, 62% with N2 and 30% N3, 40% with M 1 and 60% M zero, 84% ER/PR negative and 90% are invasive ductal and 10% are invasive lobular. Our results showed significant down regulation of serum level of mir-145 in cases of breast cancer (mean value=0.59) compared to normal control (mean value= 1.09), (p-value=<.00 1). These results are confirmed with Ng et al., [17] results, who examined 260 patient s with breast cancer and 117 controls and found that 8 mirnas (mir- 16, mir- 2 1, mir-27a, mir- 150, mir- 19 1, mir-200c, mir- 210, mir-451) were up-regulated and only mir- 145 was down-regulated (p<0.05). Li et al., [15] used mirna microarray and real time PCR, and analyzed the mirna expression profile in 21 DCIS(ductal carcinoma in situ) tissue sample and the corresponding normal tissues. MiR- 145 and (mir-10b, mir-125b, mir-132, mir-154-3p, mir-382-5p and mir-409-3p) were found to be significantly deregulated in DCIS. However Mar-Aguilar et al., [7] results showed that mir- 145 was significantly higher in BC (breast cancer) serum than controls. Our results showed a significant relation between the gene expression of mirna-145 in serum and tumor size (p=0.047*). Meanwhile, there was no significant relation between the gene expression of mirna- 145 in serum and node state, metastatic state, Estrogen and Progesterone Receptor (ER/PR) state and tumor type in patients. Iorio et al., [18] evaluated mirna expression profiles of neoplastic breast tissues. They found that mir-145 were down-regulated in breast cancer and failed to relate its level with pathological data of tumor except for proliferative index ( p=0.0136). ROC curve analysis for mir-145 showed that AUC= , the best cutoff value for detection of

5 Olfat G. Shaker, et al cancer is mirna-145=0.795 with sensitivity 74% and specificity 100%. This is near to Ng et al., [17] ROC curve analyses which showed that mir-145 could differentiate BC from healthy control with an Area Under the Curve (AUC) is (95% CI ). While, Mar-Aguilar et al., [7] showed in their ROC curve analysis that the best cutoff value for detection of cancer for mirna-145 is with sensitivity 88.90% and specificity 80.00%. Conclusions: 1- A significant difference between patients and controls as regards gene expression of mirna- 145 (down-regulated) in serum, this mirnas can be used as novel biomarker to diagnose breast cancer patients. 2- The best cutoff value of mirna-145 for detection of cancer is with sensitivity 74% and specificity 100% and values below this cutoff value is more probably cancer. References 1- JEMAL A., BRAY F., CENTER M.M., FERLAY J., WARD E. and FORMAN D.: Global cancer statistics. CA Cancer J. Clin., 61 (2): 69-90, RENNERT G.: Breast cancer. In: Freedman L., et al., editors. Cancer Incidence in Four Member Countries (Cyprus, Egypt, Israel, and Jordan) of the Middle East Cancer Consortium (MECC) Compared with US SEER. Bethesda: National Cancer Institute (NIH).; 6: 5873, AMBROS V.: The functions of animal micrornas. Nature.; 431 (7006): 350-5, BARTEL D.P.: MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell, 116 (2): , SASSEN S., MISKA E.A. and CALDAS C.: MicroRNAimplications for cancer. Virchows Arch., 452 (1): 1-10, SHENOUDA S.K. and ALAHARI S.K.: MicroRNA function in cancer: Oncogene or a tumor suppressor? Cancer Metastasis Rev., 28 (3-4): , MAR-AGUILAR F., MENDOZA-RAMÍREZ J.A., MALAGÓN-SANTIAGO I., ESPINO-SILVA P.K., SAN- TUARIO-FACIO S.K., RUIZ-FLORES P., RODRÍGUEZ- PADILLA C. and RESÉNDEZ-PÉREZ D.: Serum Circulating microrna Profiling for Identification of Potential Breast Cancer Biomarkers. Dis. Markers, 34 (3): 163-9, LORENZO F. SEMPERE, METTE CHRISTENSEN, ASLI SILAHTAROGLU, MADS BAK, CATHERINV. HEATH, GARY SCHWARTZ, WENDY WELLS, SAKA- RI KAUPPINEN and CHARLES N. COLE: Altered MicroRNA Expression Confined to Specific Epithelial Cell Subpopulations in Breast Cancer. Cancer Res., 67 (24): , BRITTON P., WARWICK J., WALLIS M.G., O'KEEFFE S., TAYLOR K., SINNATAMBY R., BARTER S., GASKARTH M., DUFFY S.W. and WISHART G.C.: Measuring the accuracy of diagnostic imaging in symptomatic breast patients: Team and individual performance, Br. J. Radio., 85 (1012): , D'ORSI C.J. and NEWELL M.S.: On the frontline of screening for breast cancer. Semin. Oncol., 38: , LI M., LI J., DING X., HE M. and CHENG S.Y.: Micro- RNA and cancer. A.A.P.S. J.,12: , ZHAO L., KIM Y., DINH T.T. and CHEN X.: MiR172 regulates stem cell fate and defines the inner boundary of APETALA3 and PISTILLATA expression domain in Arabidopsis floral meristems. Plant. J., 51 (5): 840-9, MA R., JIANG T. and KANG X.: Circulating micrornas in cancer: Origin, function and application. J. Exp. Clin. Cancer Res., 31 (1): 38, WEI Y., NAZARI-JAHANTIGH M., NETH P., WEBER C. and SCHOBER A.: Arterioscler Thromb. Vasc. Biol., 33 (3): , LI S., MENG H., ZHOU F., ZHAI L., ZHANG L., GU F., FAN Y., LANG R., FU L., GU L. and QI L.: MicroR- NA-132 is frequently down-regulated in Ductal Carcinoma In Situ (DCIS) of breast and acts as a tumor suppressor by inhibiting cell proliferation. Pathol. Res. Pract., 209 (3): , ZOU C., XU Q., MAO F., LI D., BIAN C., LIU L.Z., JIANG Y., CHEN X., QI Y., ZHANG X., WANG X., SUN Q., KUNG H.F., LIN M.C., DRESS A., WARDLE F., JIANG B.H. and LAI L.: MiR-145 inhibits tumor angiogenesis and growth by N-RAS and VEGF. Cell Cycle, 11 (11): , NG E.K., LI R., SHIN V.Y., JIN H.C., LEUNG C.P., MA E.S., PANG R., CHUA D., CHU K.M., LAW W.L., LAW S.Y., POON R.T. and KWONG A.: Circulating micrornas as Specific Biomarkers for Breast Cancer Detection. PLoS One, 8 (1): E53141, IORIO M.V., FERRACIN M., LIU C.G., VERONESE A., SPIZZO R., SABBIONI S., MAGRI E., PEDRIALI M., FABBRI M., CAMPIGLIO M., MÉNARD S., PALAZZO J.P., ROSENBERG A., MUSIANI P., VOLINIA S., NENCI I., CALIN G.A., QUERZOLI P., NEGRINI M. and CROCE C.M.: MicroRNA gene expression deregulation in human breast cancer. Cancer Res., 7065: , 2005.

6 1118 Down Regulated Micro RNA-145 as a Marker to Diagnose Breast Cancer in Egypt