Literature DB >> 24932254

High expression of octamer transcription factor 1 in cervical cancer.

Songshu Xiao1, Shan Liao2, Yanhong Zhou2, Bin Jiang1, Yueran Li1, Min Xue1.   

Abstract

Cervical carcinoma is the second most prevalent malignancy in females worldwide. The crucial etiologic factors involved in the development of cervical carcinoma include infection with papillomavirus, and the structural or functional mutation of oncogenes and tumor suppressor genes. The abnormal change of octamer transcription factor 1 (OCT1) is associated with tumor progression and a poor patient survival rate. However, little is known regarding the effect of OCT1 in cervical cancer. In the present study, flow cytometry, western blot analysis and quantitative polymerase chain reaction (qPCR) were peformed to identify differentially expressed OCT1 in cervical cancer tissue and adjacent non-cancerous tissues. The normalized OCT1 gene expression in cervical cancer was 5.98 times higher compared with the adjacent non-cancerous tissues. Western blot analysis and flow cytometry assessed the levels of OCT1 protein. The results of these two differential techniques showed that the protein expression level of OCT1 was greater in cervical cancer tissues, which corresponded with the qPCR results. Finally, as OCT1 is a potential target gene for microRNA (miR)-1467, -1185, -4493 and -3919, their expression levels were analyzed in cervical cancer tissues and adjacent non-cancerous tissues; they were downregulated by ~45% in the cervical cancer samples. The results of the present study showed that OCT1 is highly expressed in cervical cancer tissues and indicated that OCT-1 may be significant in cervical cancer.

Entities:  

Keywords:  cervical cancer; gene expression; octamer transcription factor 1

Year:  2014        PMID: 24932254      PMCID: PMC4049708          DOI: 10.3892/ol.2014.2023

Source DB:  PubMed          Journal:  Oncol Lett        ISSN: 1792-1074            Impact factor:   2.967


Introduction

Cervical carcinoma is the second most prevalent and the fifth most fatal malignancy observed in females worldwide. Furthermore, invasion and metastasis are the predominant causes of cancer-associated mortality (1). Consistent infection with high-risk variations of human papillomavirus (HPV) may cause cervical cancer, however, for the progression from a pre-cancerous disease to an invasive cancer, genetic and epigenetic modifications are required. DNA methylation is an early and recurrent molecular modification in cervical carcinogenesis. Dysregulated activation of numerous genes, including cluster of differentiation 44 and SOX9, has been indicated in cervical cancer, however, the mechanism of its regulation in human cervical cancer cells remains elusive (2–4). It has been shown that inactivation of tumor suppressor genes and activation of oncogenes is significant in carcinogenesis and is caused by the genetic and epigenetic alterations. MicroRNAs (miRs) are closely associated with the incidence and regulation of cervical cancer (5). A previous study evaluated the correlation between the risk of cancer with miRNA single nucleotide polymorphisms and no correlation was determined (6). Thus, the etiology of cervical carcinoma remains poorly understood. Octamer transcription factor 1 (OCT1) is a ubiquitous member of the Pit-Oct-Unc-homeodomain family. OCT1 has been indicated in metabolic control, stress responses and transcription states, and it also regulates normal and pathological stem cell function. A study by Maddox et al (7) demonstrated that a reduced expression of OCT1 by RNA interference results in a reduction of the proportion of aldehyde dehydrogenase 1 (ALDH) (HI) and dye efflux (HI) cells, whereas an increase in OCT1 increases the proportion of ALDH (HI) cells. OCT1 promotes the tumor engraftment frequency and the potential of hematopoietic stem cell engraftment in competitive and serial transplants (7). An additional study revealed that methylation of the OCT1 gene in human esophageal cancer cells is induced by long-term cisplatin exposure, resulting in cisplatin resistance (8). The abnormal change of OCT1 is associated with tumor progression and a poor patient survival rate (9). However, little is known regarding the effect of OCT1 in cervical cancer. In the present study, quantitative polymerase chain reaction (qPCR) was performed to identify differentially expressed OCT1 in cervical cancer and adjacent non-cancerous tissues. Western blot analysis and flow cytometry were conducted to assess the expression levels of OCT1 protein. As OCT1 is a potential miR-1467, -1185, -4493 and -3919 target, OCT1 expression levels were analyzed in cervical cancer tissues and adjacent non-cancerous tissues to assess its involvement in cervical cancer.

Patients and methods

Tumor samples

In total, 10 participants were recruited for the present study from The Third Xiangya Hospital, Central South University (Changsha, China). Consent forms were obtained from the individual patients and experimental protocols were approved by the Institutional Review Board of The Third Xiangya Hospital. The 10 participants were Chinese females with histologically-confirmed cervical cancer (Table I). Cervical cancer tissues and adjacent non-cancerous tissues were collected and each biopsy sample was divided into two sections; one was submitted for routine histological diagnosis and the remaining section was used for qPCR, western blot and flow cytometric analysis.
Table I

Characteristics of female cervical cancer patients diagnosed with squamous cell cancer.

Sample no.Age, yearsHPV typeaLaborersb
16016,53,58No
24616No
34918Yes
44716No
5496No
64316No
74816No
84016No
94616No
106016Yes

HPV types are defined according to the study by Walboomers et al.

Subsistence farmers and farm labourers are listed as in China they show a higher incidence of cervical cancer than other occupations.

HPV, human papillomavirus.

RNA extraction and qPCR analysis

Total RNA was extracted from the biopsy samples using a RNeasy kit (Qiagen, Carlsbad, CA, USA) according to the manufacturer’s instructions. The total RNA samples (1 μg) were used to generate cDNA. The PCR reaction was conducted following the reverse transcription reaction. All qPCR reactions were repeated at least three times with varying numbers of extension cycles to avoid false results. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) served as an endogenous control for normalization. The sequences of the primers used for qPCR were as follows: Forward, 5′-cctgcctcgtcatgattttt-3′ and reverse, 5′-acgaatgtggggtacagctc-3′ for OCT1; and forward, 5′-cgaccactttgtcaagctca-3′ and reverse, 5′-actgagtgt ggcagggactc-3′ for GAPDH. The expression of mRNA was assessed by evaluating the threshold cycle (CT) values. The CT values were normalized with the expression levels of GAPDH and the relative amount of mRNA specific to each of the target genes was calculated using the 2−ΔΔCT method (10–12).

Western blot analysis

Protein from the biopsy samples was prepared using lysis buffer. The protein concentrations were determined using the bicinchoninic acid (Pierce Chemical, Rockford, IL, USA) protein assay method. The extracts containing 50 μg protein were separated in 10% SDS-PAGE gels and electroblotted onto nitrocellulose membranes (Hyclone Laboratories, Logan, UT, USA). The membranes were blocked using Tris-buffered saline and Tween 20 (25 mM Tris-HCl, 150 mM NaCl, pH 7.5, and 0.05% Tween 20) containing 5% non-fat milk followed by an overnight incubation at 4°C with primary antibodies (rabbit anti-OCT1 antibody, 1:500; Santa Cruz Biotechnology, Inc., Santa Cruz, CA, USA). Following three washes with PBS, the membranes were incubated with the horseradish peroxidase-conjugated secondary antibodies (1:2,000; Santa Cruz Biotechnology, Inc.) and the specific signals were visualized using an enhanced chemiluminescence detection system (Universal Hood II, Molecular Imager ChemiDoc XRS+, Bio-Rad, Hercules, CA, USA). The anti-GAPDH antibody (1:3000; Santa Cruz Biotechnology, Inc.) served as a loading control.

Intracellular protein level detection by fluorescence-activated cell sorting (FACS)

Single-cell suspensions of cervical cancer tissues or adjacent non-cancerous tissues were prepared. Enzymatic digestion was incubated at 37°C until full digestion had occurred, with oscillations every 10–15 min prior to passing the sample through a 70-μm cell strainer. The resulting cell suspension was centrifuged (Eppendorf 5417C; Eppendorf, Engelsdorf, Germany) at 500 × g for 10 min and resuspended in saline. The cells were fixed in 500 μl paraformaldehyde 4% in Dulbecco’s phosphate-buffered saline (D-PBS) for 20 min at room temperature. Subsequent to washing in D-PBS, the cells were permeabilized with detergents (Triton X-100). The cells were washed twice with D-PBS, and the single-cell suspensions were stained and incubated at 4°C for 30 min with fluorescein isothiocyanate (FITC)-conjugated OCT-1 (Biorbyt, Cambridge, UK). Isotype controls were performed with an FITC-conjugated rabbit anti-human igG negative control (Biorbyt). All antibodies were used according to manufacturer’s instructions. The cells were washed twice and examined by FACS using a MoFlo™ XDP High-Performance Cell Sorter (Beckman Coulter, Miami, FL, USA). Data were acquired and analyzed using Summit v5.2 software (Becton Dickinson, Franklin Lakes, NJ, USA).

Expressions analysis of miR-1467, -1185, -4493 and -3919 in cervical cancer

The total RNA was extracted from the biopsy samples with the RNeasy kit according to the manufacturer’s instructions. cDNA was synthesized from 2 mg total RNA with moloney murine leukemia virus (M-MLV) Reverse Transcriptase (Promega Corporation, Madison, WI, USA) in 25 ml [2 mg total RNA, 400 mM reverse transcription primer oligo(dT)18 for random primers for U6 rRNA and miR-1467, -1185, -4493 and -3919 specific primers (Bulge-Loop™ miRNA qPCR Primers; RiboBio, Co., Ltd., Guangzhou, China) for miRNA, 4 U/ml M-MLV, 1 U/ml inhibitor and 0.4 mM dNTP mix]. qPCR was carried out with the reagents of a Sybr green I mix (Takara Bio, Co., Inc., Dalian, China) in a 20-ml reaction volume (10 ml Sybr green I mix, 200 mM forward and reverse primer and 2 ml cDNA template) on an MJ Opticon Monitor Chromo4™ instrument (Bio-Rad, Hercules, CA, USA) using the following protocol: 95°C for 20 sec and 40 cycles of 95°C for 10 sec, 60°C for 20 sec and 70°C for 1 sec. Data analysis were performed using the 2−ΔΔCT method (10–12).

Statistical Analysis

Differences of non-parametric variables were analyzed by Fisher’s exact test using EPI software (EPI Info, version 3.2.2; www.CDC.gov/epiinfo/). Differences of the quantitative variables between groups were analyzed by Student’s t-test using the SPSS 11.0 program (SPSS, Inc., Chicago, IL, USA) and P<0.05 was considered to indicate a statistically significant difference.

Results

Detection of mRNA expression levels of the OCT1 gene in cervical cancer

In the present study, all 10 cervical cancer tissues samples were squamous cell cancer. There was a 90% (9/10) infection rate of HPV 16 or 18. Other HPV types included HPV 6, 53, and 58. In addition, there were 20% peasants (2/10; Table I) (13). To detect the mRNA expression levels of the OCT1 gene in cervical cancer and the adjacent non-cancerous tissues, 10 samples of each were selected to perform qPCR of the OCT1 gene. The data were analyzed using the 2−ΔΔCT method and the fold change in the expression of the OCT1 gene relative to the internal control gene, GAPDH, was analyzed. The expression of the OCT1 gene was higher in the cervical cancer samples compared with the adjacent non-cancerous tissues (Table II, Fig. 1) and the normalized OCT1 gene expression in cervical cancer was upregulated by 5.98 fold (Fig. 1A). The results of agarose gel electrophoresis of qPCR for the OCT1 and GAPDH genes in cervical cancer and the adjacent non-cancerous tissues is shown in Fig. 1B and C.
Table II

Identification of the mRNA expression level of the OCT1 gene in cervical cancer and adjacent non-cancerous tissues by qPCR.

CT, means ± standard deviation

SamplenGAPDHOCT1ΔΔΔFolda
Cervical cancer1016.56±1.3227.47±1.5110.91±0.84−2.58±0.635.98
Non-cancerous tissues1016.23±1.2529.72±1.6713.49±0.92

Mean fold change in expression of the target gene, OCT1, relative to the internal control gene, GAPDH, was calculated using the 2−ΔΔCT equation previously adopted by Livak et al (10): ΔΔCT = (CTTarget - CTGAPDH)cervical cancer - (CTTarget - CTGAPDH)control. At least three replicates of each reaction were performed.

CT, threshold cycle; qPCR, quantitative polymerase chain reaction; OCT1, octamer transcription factor 1; GAPDH, glyceraldehyde-3-phosphate dehydrogenase.

Figure 1

Differential expression of the OCT1 gene in cervical cancer and the adjacent non-cancerous tissues. (A) Normalized OCT1 gene expression in cervical cancer was 5.98 times higher (*fold change) compared with the adjacent non-cancerous tissues. (B and C) The results of agarose gel electrophoresis of qPCR for OCT1 and GAPDH genes in cervical cancer (lanes 1, 3, 5, 7 and 9) and the adjacent non-cancerous tissues (lanes 2, 4, 6, 8 and 10). OCT1, octamer transcription factor 1; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; qPCR, quantitative polymerase chain reaction.

Western blot analysis of protein expression levels of the OCT1 gene in cervical cancer

To determine whether the OCT1 gene was expressed at a higher level in cervical cancer compared with the adjacent non-cancerous tissues, the protein expression levels of OCT1 were further examined by western blot (Fig. 2). In comparison with the adjacent non-cancerous tissues, the expression level was identified to be greater in cervical cancer tissues, which corresponded with the qPCR results. These results identified that OCT1 is highly expressed in cervical cancer.
Figure 2

Expression levels of the OCT1 protein in cervical cancer and the adjacent non-cancerous tissues. In total, (lanes A, C, E and G) four cervical cancer and (lanes B, D, F and H) four of the adjacent non-cancerous tissues were selected to detect the expression levels of OCT1 protein by western blot analysis. Data are representative of three independent experiments. OCT1, octamer transcription factor 1; GAPDH, glyceraldehyde-3-phosphate dehydrogenase.

FACS analysis of protein expression levels of the OCT1 gene in cervical cancer

To further identify that OCT1 is highly expressed in cervical cancer tissues, the protein expression levels of OCT1 in cervical cancer tissues and the adjacent non-cancerous tissues were examined by FACS (Fig. 3). In comparison with the adjacent non-cancerous tissues, the expression level was greater in the cervical cancer tissues. This corresponds with the qPCR results and further identifies that OCT1 is highly expressed in cervical cancer tissue.
Figure 3

Analysis of the protein expression levels of OCT1 in psoriasis by FACS. The expression levels of the OCT1 protein were tested by FACS in 10 cervical cancer and adjacent non-cancerous tissues. (A) Adjacent non-cancerous and (B) cervical cancer tissues sample. The green, red and purple colors show the results of samples dyed with FITC-conjugated OCT1 antibody, FITC-conjugated rabbit anti-human IgG negative control and FITC-conjugated OCT1 antibody, respectively. Data are representative of three independent experiments. OCT1, octamer transcription factor 1; FACS, fluorescence-activated cell sorting; FITC, fluorescein isothiocyanate.

Expression of miR-1467, -1185, -4493 and -3919 is downregulated in cervical cancer

As OCT1 is a potential miR target, the open access programs, TargetScan (http://www.targetscan.org/), PicTar (http://pictar.mdc-berlin.de/) and miRBase (http://mirbase.org/index.shtml), were used to predict the targets of miR-1467, -1185, -4493 and -3919. The endogenous expressions of miR-1467, -1185, -4493 and -3919 were compared between the cervical cancer tissues and adjacent non-cancerous tissues by qPCR. As shown in Table III, the expression of miR-1467, -1185, -4493 and -3919 were downregulated by ~45% in the cervical cancer tissues. These results indicate that OCT1 may be a putative target for cervical cancer.
Table III

Identification of the expression levels of miR-1467, -1185, -4493, and -3919 in cervical cancer and adjacent non-cancerous tissues.

CT, mean ± standard deviation

miRNASamplenU6amiRNAΔΔΔFolda
miR-1467Cervical cancer1017.14±0.9230.88±1.0813.74±0.930.89±0.110.53
Non-cancerous1017.52±0.8730.37±1.1712.85±1.08
miR-1185Cervical cancer1019.36±0.9431.99±1.2912.63±1.060.77±0.090.59
Non-cancerous1019.58±0.9931.44±1.1811.86±1.03
miR-4493Cervical cancer1018.71±0.8430.72±1.2212.01±0.850.71±0.100.61
Non-cancerous1018.79±0.7930.09±1.2511.30±1.01
miR-3919Cervical cancer1017.28±0.8030.12±1.2712.84±1.010.80±0.140.57
Non-cancerous1018.19±0.8630.23±1.2312.04±1.11

U6 was used as a control.

Expression fold change of miRNA in cervical cancer compared with adjacent non-cancerous tissues.

CT, threshold cycle; miRNA, microRNA.

Discussion

Cervical cancer is the second most common cause of cancer-associated mortality among females worldwide and in China, subsistence farmers and farm labourers show a higher incidence of cervical cancer than other occupations. The development of novel strategies for diagnosis, prognosis and treatment requires consideration. There have been numerous attempts at designing novel therapeutic agents and developing strategies for immunotherapy and gene therapy for the treatment of cervical cancer (14,15). Specific biomarkers are required for the early diagnosis and prediction of metastatic progression and effective therapy. However, there is currently no efficient therapy against cervical cancer and the available treatments have various disadvantages (1,16–21). It has been shown that inactivation of tumor suppressor genes and activation of oncogenes is significant in carcinogenesis, and results from genetic and epigenetic alterations (5,6). However, the etiology of cervical carcinoma remains poorly understood. The OCT1 transcription factor was among one of the first identified members of the POU transcription factor family. Members of this family contain the POU domain, a 160-amino acid region necessary for DNA binding to the octameric sequence ATGCAAAT. Oct-1 controls the transcriptional regulation and affects tumor development (9). The results of the present study showed that the expression levels of the OCT1 gene in cervical cancer was 5.98 times higher compared with adjacent non-cancerous tissues. Furthermore, the protein expression level of OCT1 was shown to be higher in cervical cancer by two differential techniques, western blot analysis and flow cytometry. These results correspond with the results of the qPCR. The expression of miR-1467, -1185, -4493 and -3919 were downregulated by ~45% in the cervical cancer tissues. The results showed that OCT1 was highly expressed in cervical cancer tissues and indicates that OCT-1 is significant in cervical cancer. The significant role of OCT1 in numerous malignancies, except cervical cancer, has been demonstrated by previous studies. Gupta et al (22) demonstrated the expression of human OCT1 in lymphoma cells and the increased susceptibility of the cells to irinotecan and paclitaxel. OCT1 is a coregulator of the androgen receptor (AR) and can be a prognostic factor for prostate cancer, which may lead to the development of a novel therapeutic intervention. OCT1 regulates cell growth of LNCaP cells and is a prognostic factor for prostate cancer (23,24). OCT1 is a negative regulator of enhancer activity mediated by dihydrotestosterone in a subset of AR-occupied regions (ARORs). AROR enrichment for the OCT-binding, TTGGCAAATA-like motif, may indicate a mechanism that maintains correct AR activity at specific ARORs by OCT1, while expanding AR activity in other ARORs. Therefore, OCT1 may be involved in the regulation of prostate development and cancer progression (25,26). A study by Shakya et al (27) demonstrated that OCT1 is an adjustable, bipotential stabilizer of inducible and repressed transcriptional states. In conclusion, the present study demonstrated that OCT1 was highly expressed in cervical cancer tissues and may be significant in cervical cancer. OCT1 is likely to provide a theoretical evidence for elucidating the pathogenesis of cervical cancer if the mechanisms of CD44 regulating OCT1 expression are clarified in cervical cancer.
  27 in total

1.  Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

Authors:  K J Livak; T D Schmittgen
Journal:  Methods       Date:  2001-12       Impact factor: 3.608

2.  Oct1 is a switchable, bipotential stabilizer of repressed and inducible transcriptional states.

Authors:  Arvind Shakya; Jinsuk Kang; Jeffrey Chumley; Matthew A Williams; Dean Tantin
Journal:  J Biol Chem       Date:  2010-11-04       Impact factor: 5.157

3.  Terrein induces apoptosis in HeLa human cervical carcinoma cells through p53 and ERK regulation.

Authors:  Yuwarat Porameesanaporn; Wanlaya Uthaisang-Tanechpongtamb; Faongchat Jarintanan; Suchada Jongrungruangchok; Benjamas Thanomsub Wongsatayanon
Journal:  Oncol Rep       Date:  2013-02-15       Impact factor: 3.906

4.  Long-term cisplatin exposure promotes methylation of the OCT1 gene in human esophageal cancer cells.

Authors:  Rui Lin; Xiaoli Li; Jiansheng Li; Lianfeng Zhang; Feng Xu; Yanjun Chu; Jichang Li
Journal:  Dig Dis Sci       Date:  2012-10-06       Impact factor: 3.199

5.  Human organic cation transporter 1 is expressed in lymphoma cells and increases susceptibility to irinotecan and paclitaxel.

Authors:  Shivangi Gupta; Gerald Wulf; Maja Henjakovic; Hermann Koepsell; Gerhard Burckhardt; Yohannes Hagos
Journal:  J Pharmacol Exp Ther       Date:  2011-12-27       Impact factor: 4.030

6.  Oct1 regulates cell growth of LNCaP cells and is a prognostic factor for prostate cancer.

Authors:  Daisuke Obinata; Ken-ichi Takayama; Tomohiko Urano; Taro Murata; Jinpei Kumagai; Tetsuya Fujimura; Kazuhiro Ikeda; Kuniko Horie-Inoue; Yukio Homma; Yasuyoshi Ouchi; Satoru Takahashi; Satoshi Inoue
Journal:  Int J Cancer       Date:  2011-05-28       Impact factor: 7.396

Review 7.  HPV vaccine: an overview of immune response, clinical protection, and new approaches for the future.

Authors:  Luciano Mariani; Aldo Venuti
Journal:  J Transl Med       Date:  2010-10-27       Impact factor: 5.531

8.  Identification of tyrosine phosphoproteins in signaling pathway triggered TGF-a by using functional proteomics technology.

Authors:  Lin Ruan; Guo-Liang Wang; Yan Chen; Hong Yi; Can-E Tang; Peng-Fei Zhang; Mao-Yu Li; Cui Li; Fang Peng; Jian-Ling Li; Zhu-Chu Chen; Zhi-Qiang Xiao
Journal:  Med Oncol       Date:  2010-01-05       Impact factor: 3.064

9.  Network motifs in the transcriptional regulation network of cervical carcinoma cells respond to EGF.

Authors:  Su Fang Wu; Wen Yan Qian; Jia Wen Zhang; Yong Bin Yang; Yuan Liu; Yu Dong; Zhen Bo Zhang; Ya Ping Zhu; You Ji Feng
Journal:  Arch Gynecol Obstet       Date:  2012-11-28       Impact factor: 2.344

10.  Epigenetic alterations in preneoplastic and neoplastic lesions of the cervix.

Authors:  Kathleen P Saavedra; Priscilla M Brebi; Juan Carlos S Roa
Journal:  Clin Epigenetics       Date:  2012-08-31       Impact factor: 6.551

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  16 in total

Review 1.  The Oct1 transcription factor and epithelial malignancies: Old protein learns new tricks.

Authors:  Karina Vázquez-Arreguín; Dean Tantin
Journal:  Biochim Biophys Acta       Date:  2016-02-10

2.  Involvement of transcription factor Oct-1 in the regulation of JAK-STAT signaling pathway in cells of Burkitt lymphoma.

Authors:  E V Pankratova; A G Stepchenko; I D Krylova; T N Portseva; S G Georgieva
Journal:  Dokl Biochem Biophys       Date:  2016-07-15       Impact factor: 0.788

3.  Increased level of Oct-1 protein in tumor cells modulates cellular response to anticancer drugs.

Authors:  T N Portseva; E V Pankratova; A G Stepchenko; S G Georgieva
Journal:  Dokl Biochem Biophys       Date:  2016-09-07       Impact factor: 0.788

4.  The Emergence of a New Isoform of POU2F1 in Primates through the Use of Egoistic Mobile Genetic Elements.

Authors:  B M Lyanova; A P Kotnova; A A Makarova; Yu V Ilyin; S G Georgieva; A G Stepchenko; E V Pankratova
Journal:  Dokl Biochem Biophys       Date:  2022-05-10       Impact factor: 0.834

5.  Transcription factor Oct-1 stimulates the release of Mts1/S100A4 protein by the cancer cells.

Authors:  T N Portseva; A V Brechalov; E A Dukhanina; A G Stepchenko; E V Pankratova; S G Georgieva
Journal:  Dokl Biochem Biophys       Date:  2016-05-20       Impact factor: 0.788

6.  FBXW12, a novel F box protein-encoding gene, is deleted or methylated in some cases of epithelial ovarian cancer.

Authors:  Elsa De La Chesnaye; Juan Pablo Méndez; Ricardo López-Romero; María De Los Angeles Romero-Tlalolini; María Dolores Vergara; Mauricio Salcedo; Sergio R Ojeda
Journal:  Int J Clin Exp Pathol       Date:  2015-09-01

7.  Quantifying mRNA and microRNA with qPCR in cervical carcinogenesis: a validation of reference genes to ensure accurate data.

Authors:  Maria da Conceição Gomes Leitão; Eliane Campos Coimbra; Rita de Cássia Pereira de Lima; Mariléa de Lima Guimarães; Sandra de Andrade Heráclio; Jacinto da Costa Silva Neto; Antonio Carlos de Freitas
Journal:  PLoS One       Date:  2014-11-03       Impact factor: 3.240

8.  Elevated OCT1 participates in colon tumorigenesis and independently predicts poor prognoses of colorectal cancer patients.

Authors:  Yu-Peng Wang; Guo-He Song; Jian Chen; Chao Xiao; Chao Li; Lin Zhong; Xing Sun; Zhao-Wen Wang; Gui-Long Deng; Fu-Dong Yu; Ying-Ming Xue; Hua-Mei Tang; Zhi-Hai Peng; Xiao-Liang Wang
Journal:  Tumour Biol       Date:  2015-10-04

9.  Different N-terminal isoforms of Oct-1 control expression of distinct sets of genes and their high levels in Namalwa Burkitt's lymphoma cells affect a wide range of cellular processes.

Authors:  Elizaveta V Pankratova; Alexander G Stepchenko; Tatiana Portseva; Vladic A Mogila; Sofia G Georgieva
Journal:  Nucleic Acids Res       Date:  2016-07-12       Impact factor: 16.971

10.  Stilbenoids remodel the DNA methylation patterns in breast cancer cells and inhibit oncogenic NOTCH signaling through epigenetic regulation of MAML2 transcriptional activity.

Authors:  Katarzyna Lubecka; Lucinda Kurzava; Kirsty Flower; Hannah Buvala; Hao Zhang; Dorothy Teegarden; Ignacio Camarillo; Matthew Suderman; Shihuan Kuang; Ourania Andrisani; James M Flanagan; Barbara Stefanska
Journal:  Carcinogenesis       Date:  2016-04-28       Impact factor: 4.944

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