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tors along with Oct4, Sox2, and Lin28. Nanog expression has been detected in different types of tumors, and its expression is a poor prognosis for cancer patients. However, there is no clear evidence that Nanog is functionally involved in tumorigenesis. In this study, we induced overexpression of Nanog in mouse embryonic fibroblast cells and subsequently assessed their morphological changes, proliferation rate, and tumor formation ability. We found that Nanog overexpression induced immortalization of mouse embryonic fibroblast cells (MEFs) and increased their proliferation rate in vitro. We also found that formation of tumors after subcutaneous injection of retroviral-Nanog infected MEFs (N-MEFs) into athymic mouse. Cancer-related genes such as Bmi1 were expressed at high levels in N-MEFs. Hence, our results demonstrate that Nanog is able to transform normal somatic cells into tumor cells.

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span style='font-weight:700;'>Nanog gene expression pattern varies between embryos and between blastomeres during blastocyst formation. In this report, we traced the changes of Nanog expression in each cell in developing preimplantation mouse embryos through time-lapse observation of Nanog-GFP transgenic mouse embryos. The expression pattern of Nanog was classified into four phases depending on the developmental stage. Nanog expression started at very low levels during cleavage stages. It increased stochastically during the morula stage, but its expression level had no clear correlation with future cell fates. After the 32-cell stage, when embryos form the blastocyst cavity, Nanog expression was upregulated mainly in ICM cells while it was repressed in the future primitive endoderm lineage in an FGF signaling-dependent manner in the later stages. These results indicate that there are multiple phases in the transcriptional regulation of Nanog during blastocyst formation.

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of Oct3/4, Nanog and Sox2 were examined using Western blot analysis, RT-PCR or microscopically observed immunofluorescence, and cell morphological changes were observed using HE staining, during the recovery process. RESULTS: Oct3/4, Nanog and Sox2 were not detectable in normal tracheal epithelium. After treatment with 5-FU, the normally proliferating tracheal epithelium desquamated and only a few cells in G0 phase of the cell cycle were left on the basement membrane and Oct3/4, Nanog and Sox2 could be observed at this time. Thereafter, the number of Oct3/4-, Nanog- and Sox2-positive cells increased gradually. When the cells differentiated into ciliate cells, mucous cells or basal cells, and restored pseudostratified mucociliary epithelium, the number of Oct3/4-, Nanog- and Sox2-positive cells decreased and gradually disappeared. CONCLUSIONS: G0 phase cells with resistance to 5-FU damage expressed Oct3/4, Nanog and Sox2. This indicated that these cells were undifferentiated, but had the ability to terminally differentiate into downstream-type cells. They possessed stem cell properties. The results are consistent with Oct3/4, Nanog and Sox2-expressing cells being considered as tracheal stem cells.

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uripotency, while those with low levels are more likely to undergo differentiation. Using a cell line with a fluorescence tag for Nanog enables measurements of the distribution of Nanog in an ES cell culture in a stationary state or after a perturbation. In order to model the dynamics of the system, we assume that the distribution of Nanog-GFP for single cells shows distinct attractor steady states of Nanog levels, with individual cells moving between these states stochastically. The addition of synthetic inhibitors of signal transduction induces strong shifts in the distribution of Nanog. In particular, the addition of Chiron and PD03, inhibitors for the ERK and GSK3 signalling pathways, induces a high level of Nanog. In this study, we placed ES cells in different culture conditions, including the above inhibitors, and recorded the change in Nanog-GFP distribution over several days. In order to interpret the measurements of Nanog levels, we propose a new stochastic modelling strategy for the dynamics of the system not requiring detailed knowledge of regulatory or signalling mechanisms, while still capturing the stochastic and the deterministic components of the stochastic dynamical system. Despite its relative simplicity, the model provides an insight into key features of the cell population under various conditions, including the level of noise and occupancy and location of attractor steady states, without the need for strong assumptions about the underlying cellular mechanisms. By applying the model to our experimental data, we infer the existence of three stable steady states for Nanog levels, which are the same in all the different conditions of the cell-culture medium. Noise, on the other hand, and the proportion of cells in each steady state are subject to large shifts. Surprisingly, the isolated effects of PD03 and Chiron on noise and dynamics of the system are quite different from their combined effect. Our results show that signalling determines the occupancy of each state, with a particular role for GSK3 in the regulation of the noise across the population.

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'>Nanog is not sufficient to induce spontaneous tumors in mice but can promote metastasis of established tumors by activating the expression of metastatic genes. The expression of Nanog in mouse skin activates tumor suppressor p53, leading to the differentiation of epidermal stem cells. In the absence of p53, Nanog induces spontaneous squamous cell carcinoma, identifying a novel role of Nanog in tumorigenesis. Therefore, the induction of p53 and differentiation in Nanog-expressing skin suppresses the tumorigenic activities of Nanog, which include the induction of DNA double-stranded break damage. Notably, Nanog interacts with the KRAB-associated protein 1 (KAP1) and inhibits its sumoylation activity, impairing KAP1-mediated chromatin remodeling, which is important for efficiently activating DNA damage response. In summary, Nanog is an oncogene with multiple roles in promoting tumorigenesis and metastasis.

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stem (ES) cells. We found that both GLI3 and GLI1 bind to the pluripotency factor NANOG. The ectopic expression of NANOG inhibits GLI1-mediated transcriptional responses in a dose-dependent fashion. In differentiating ES cells, the presence of NANOG reduces the transcriptional response of cells to HH. Finally, we found thatGli1andNanogare co-expressed in ES cells at high levels. We propose that NANOG acts as a negative feedback component that provides stem cell-specific regulation of the HH pathway.

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markers Oct-4 and Nanog in oral cancer is yet to be studied in detail. Therefore, we have investigated the correlation among Oct-4, Nanog, and beta-catenin in oral squamous cell carcinoma, which, in turn, could provide valuable insight into its prognostic significance. METHODS: The immunohistochemical analysis was performed for 60 cases of oral cancer to study the expression pattern of Oct-4, Nanog, and beta-catenin. Whereas immunofluorescence analysis was used to investigate the co-localization of beta-catenin with Oct-4 and Nanog in oral carcinoma tissues and H314 cell line. Finally, co-immunoprecipitation analysis was used to study the possible interaction between beta-catenin and Oct-4 in oral carcinoma cells. RESULTS: beta-catenin, Oct-4, and Nanog showed significant correlation with lymph node metastasis, stage, grade, and prognosis in oral squamous cell carcinoma. Interestingly, a significant positive correlation was found among the expression of Oct-4, Nanog, and beta-catenin. Moreover, the interaction between beta-catenin and Oct-4 was observed in oral cancer. CONCLUSION: The positive correlation among Oct-4, Nanog, and beta-catenin suggests their coordinated role in maintaining proliferation in oral carcinoma cells. The interaction between beta-catenin and Oct-4 may be a crucial event in oral carcinogenesis. On the other hand, beta-catenin, Oct-4, and Nanog could be used as independent prognostic markers of oral squamous cell carcinoma.

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NANOG possesses protumorigenic attributes. In addition to promoting self-renewal and long-term proliferative potential of stem-like cancer cells, NANOG-mediated oncogenic reprogramming may underlie clinical manifestations of malignant disease. In this review, we examine the molecular origin, expression, biological activities, and mechanisms of action of NANOG in various malignancies. We also consider clinical implications such as correlations between NANOG expression and cancer prognosis and/or response to therapy. We surmise that NANOG potentiates the molecular circuitry of tumorigenesis, and thus may represent a novel therapeutic target or biomarker for the diagnosis, prognosis, and treatment outcome of cancer. Finally, we present critical pending questions relating NANOG to cancer stem cells and tumor development.

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nical stage I/II (T1-2N0M0) tongue squamous cell carcinoma (TSCC) typically undergo partial glossectomy; however, development of delayed neck metastasis (DNM) tends to reduce their survival. In the present study, we aimed to determine the CSC markers in the SP of HNSCC cells along with their functions in cellular behaviors, and to clarify the association of these markers with DNM. METHODS: Flow cytometry was applied to isolate SP from main population (MP) in HNSCC cells. The expression of the CSC markers was examined by semi-quantitative RT-PCR and immunocytochemistry. In vitro proliferation, migration, and invasion assays were performed to assess cellular behaviors. Clinicopathological factors and immunohistochemical expressions of Oct3/4 and Nanog were evaluated using surgical specimens from 50 patients with stage I/II TSCC. RESULTS: SPs were isolated in all three cell lines examined. Expression levels of Oct3/4 and Nanog were higher in SP cells than MP cells. Additionally, cell migration and invasion abilities were higher in SP cells than MP cells, whereas there was no difference in proliferation. Univariate analysis showed that expression of Oct3/4 and Nanog, vascular and muscular invasion, and mode of invasion were significantly correlated with DNM. Multivariate logistic regression revealed that Oct3/4 expression (risk ratio = 14.78, p = 0.002) and vascular invasion (risk ratio = 12.93, p = 0.017) were independently predictive of DNM. Regarding the diagnostic performance, Oct3/4 showed the highest accuracy, sensitivity, and NPV of 82.0 %, 61.5 %, and 86.8 %, respectively, while vascular invasion showed the highest specificity and PPV of 94.6 % and 71.4 %, respectively. CONCLUSION: These results suggest that Oct3/4 and Nanog represent probable CSC markers in HNSCC, which contribute to the development of DNM in part by enhancing cell motility and invasiveness. Moreover, along with vascular invasion, expression of Oct3/4 can be considered a potential predictor for selecting patients at high risk of developing DNM.

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s. We report that exposure of breast cancer cells to hypoxia stimulated hypoxia-inducible factor (HIF)-1a- and HIF-2a-dependent expression of AlkB homolog 5 (ALKBH5), an m(6)A demethylase, which demethylated NANOG mRNA, which encodes a pluripotency factor, at an m(6)A residue in the 3'-UTR. Increased NANOG mRNA and protein expression, and the breast cancer stem cell (BCSC) phenotype, were induced by hypoxia in an HIF- and ALKBH5-dependent manner. Insertion of the NANOG 3'-UTR into a luciferase reporter gene led to regulation of luciferase activity by O2, HIFs, and ALKBH5, which was lost upon mutation of the methylated residue. ALKBH5 overexpression decreased NANOG mRNA methylation, increased NANOG levels, and increased the percentage of BCSCs, phenocopying the effect of hypoxia. Knockdown of ALKBH5 expression in MDA-MB-231 human breast cancer cells significantly reduced their capacity for tumor initiation as a result of reduced numbers of BCSCs. Thus, HIF-dependent ALKBH5 expression mediates enrichment of BCSCs in the hypoxic tumor microenvironment.

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on pluripotency factors sex-determining region Y-box 2 (SOX2), Nanog homeobox (NANOG), and octamer-binding protein 4 (OCT4) in the endometrium of reproductive-age women with and without ovarian endometriosis. METHODS: We recruited 26 women with laparoscopy-diagnosed ovarian endometriosis (endometriosis group) and 16 disease-free women (control group) to the study. Endometrial and endometriotic samples were collected. SOX2, NANOG, and OCT4 expression were analyzed with quantitative real-time polymerase chain reaction, western blotting, and immunohistochemistry. RESULTS: Compared to the control group, SOX2 mRNA and protein expression was significantly higher in the eutopic endometrium of participants in the endometriosis group. In the endometriosis group, SOX2 and NANOG mRNA and protein expression were significantly increased in ectopic endometrium compared with eutopic endometrium; there was a trend towards lower OCT4 mRNA expression and higher OCT4 protein expression in ectopic endometrium. CONCLUSIONS: The transcription pluripotency factors SOX2 and NANOG were overexpression in ovarian endometriosis, their role in pathogenesis of endometriosis should be further studied.

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regulation of the involved genes. The reported modulation of some of these genes led us to hypothesize that some of them could be regulated by the transcription factors critical for self-renewal and pluripotency in embryonic stem cells (ESCs) and in induced pluripotent stem cells (iPSCs). In this work, we studied the expression profile of multiple genes involved in antioxidant defense systems in both ESCs and iPSCs. We found that Manganese superoxide dismutase gene (Mn-Sod/Sod2) was repressed during diverse differentiation protocols showing an expression pattern similar to Nanog gene. Moreover, Sod2 promoter activity was induced by Oct4 and Nanog when we performed a transactivation assay using two different reporter constructions. Finally, we studied Sod2 gene regulation by modulating the expression of Oct4 and Nanog in ESCs by shRNAs and found that downregulation of any of them reduced Sod2 expression. Our results indicate that pluripotency transcription factors positively modulate Sod2 gene transcription.

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/span> is induced by Toll-like receptor 4 (TLR4) signaling via phosphorylation of E2F1 and that downregulation of Nanog slows down hepatocellular carcinoma (HCC) progression induced by alcohol western diet and hepatitis C virus protein in mice. NANOG ChIP-seq analyses reveal that NANOG regulates the expression of genes involved in mitochondrial metabolic pathways required to maintain tumor-initiating stem-like cells (TICs). NANOG represses mitochondrial oxidative phosphorylation (OXPHOS) genes, as well as ROS generation, and activates fatty acid oxidation (FAO) to support TIC self-renewal and drug resistance. Restoration of OXPHOS activity and inhibition of FAO renders TICs susceptible to a standard care chemotherapy drug for HCC, sorafenib. This study provides insights into the mechanisms of NANOG-mediated generation of TICs, tumorigenesis, and chemoresistance through reprogramming of mitochondrial metabolism.

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imited. In this study, we measured ROR in 61 paired cancerous and noncancerous tissue samples by qRT-PCR and investigated the biological role of ROR on the phenotypes of pancreatic cancer stem cells (PCSCs) in vitro and in vivo. The effects of ROR on PCSCs were studied by RNA interference approaches in vitro and in vivo. Insights of the mechanism of competitive endogenous RNAs (ceRNAs) were gained from bioinformatic analysis, luciferase assays and RNA binding protein immunoprecipitation. The positive ROR/Nanog interaction was identified and verified by immunohistochemistry assay. Compared with adjacent non-tumor tissues, ROR was up-regulated in most tumor tissues. Knockdown of ROR by RNA interference in PCSCs inhibited proliferation, induced apoptosis and decreased migration. Moreover, ROR silencing resulted in significantly decreased tumourigenicity of PCSCs in nude mice than controls. In particular, ROR may act as a ceRNA, effectively becoming a sink for miR-145, thereby activating the derepression of core transcription factors Nanog. In conclusions, we demonstrated that decreased ROR expression could inhibit cell proliferation, invasion, and tumourigenicity by modulating Nanog. Therefore, ROR is a potential novel prognostic marker to predict the clinical outcome of pancreatic cancer patients after surgery and may be a rational target for therapy.

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liver tumors containing tumor-initiating stem-like cells (TICs) that express NANOG. We investigated whether the TLR4 signals to NANOG to promote the development of TICs and tumorigenesis in mice placed on a Western diet high in cholesterol and saturated fat (HCFD). METHODS: We expressed HCV-NS5A from a transgene (NS5A Tg) in Tlr4-/- (C57Bl6/10ScN), and wild-type control mice. Mice were fed a HCFD for 12 months. TICs were identified and isolated based on being CD133+, CD49f+, and CD45-. We obtained 142 paraffin-embedded sections of different stage HCCs and adjacent nontumor areas from the same patients, and performed gene expression, immunofluorescence, and immunohistochemical analyses. RESULTS: A higher proportion of NS5A Tg mice developed liver tumors (39%) than mice that did not express HCV NS5A after the HCFD (6%); only 9% of Tlr4-/- NS5A Tg mice fed HCFD developed liver tumors. Livers from NS5A Tg mice fed the HCFD had increased levels of TLR4, NANOG, phosphorylated signal transducer and activator of transcription (pSTAT3), and TWIST1 proteins, and increases in Tlr4, Nanog, Stat3, and Twist1 messenger RNAs. In TICs from NS5A Tg mice, NANOG and pSTAT3 directly interact to activate expression of Twist1. Levels of TLR4, NANOG, pSTAT3, and TWIST were increased in HCC compared with nontumor tissues from patients. CONCLUSIONS: HCFD and HCV-NS5A together stimulated TLR4-NANOG and the leptin receptor (OB-R)-pSTAT3 signaling pathways, resulting in liver tumorigenesis through an exaggerated mesenchymal phenotype with prominent Twist1-expressing TICs.

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lf-renewal and pluripotency of stem cells as well as cancer invasiveness, tumor cell proliferation, motility and drug-resistance. Understanding the underlying mechanisms of Nanog evolution and regulation can lead to future advances in treatment of cancers. Recent integration of machine learning models with genetics has provided a powerful tool for knowledge discovery and uncovering evolutionary pathways. Herein, sequences of 47 Nanog genes from various species were extracted and two datasets of features were computationally extracted from these sequences. At the first dataset, 76 nucleotide acid attributes were calculated for each Nanog sequence. The second dataset was prepared based on the 10,480 repeated nucleotide sequences (from 5 to 50bp lengths). Then, various data mining algorithms such as decision tree models were applied on these datasets to find the evolutionary pathways of Nanog diversion. Attribute weighting models were highlighted features such as the frequencies of AA and GC as the most important genomic features in Nanog gene classification and differentiation. Similar findings were obtained by tree induction algorithms. Results from the second database showed that some short sequence strings, such as ACTACT, TCCTGA, CCTGA, GAAGAC, and TATCCC can be effectively used to identify Nanog genes in various species. The outcomes of this study, for the first time, unravels the importance of particular genomic features in Nanog gene evolution paving roads toward better understanding of stem cell development and human targeted disorder therapy.