extfieldsofstudy: Biology Medicine

s2fieldsofstudy: Biology Medicine

text:
Correlation of MicroRNA-16, MicroRNA-21 and MicroRNA-101 Expression with Cyclooxygenase-2 Expression and Angiogenic Factors in Cirrhotic and Noncirrhotic Human Hepatocellular Carcinoma

Background Hepatocellular carcinoma (HCC) is a classical example of inflammation-linked cancer and is characterized by hypervascularity suggesting rich angiogenesis. Cycloxygenase-2 (COX-2) is a potent mediator of inflammation and is considered to upregulate angiogenesis. The aims of the study are (1) to analyze expression of Cox-2 mRNA, Cox-2 protein, miR-16, miR-21 and miR-101 in HCC and adjacent liver parenchyma in cirrhotic and noncirrhotic liver, (2) to investigate the relation between COX-2 expression, miR-21 expression and angiogenic factors in these tissues and (3) to investigate the association between miR-16 and miR-101 and COX-2 expression. Methods Tissue samples of HCC and adjacent liver parenchyma of 21 noncirrhotic livers and 20 cirrhotic livers were analyzed for COX-2 expression at the mRNA level (qRT-PCR) and at the protein level by Western blot and immunohistochemistry. Gene expression of VEGFA, VEGFR1, VEGFR2, Ang-1, Ang-2 and Tie-2 were correlated with COX-2 levels. miR-16, miR-21 and miR-101 gene expression levels were quantified in HCC tumor tissue. Results COX-2 mRNA and protein levels were lower in HCC as compared to adjacent liver parenchyma both in cirrhotic and noncirrhotic liver. COX-2 protein localized mainly in vascular and sinusoidal endothelial cells and in Kupffer cells. At the mRNA level but not at the protein level, COX-2 correlated with mRNA levels of angiogenic factors VEGFR1, Ang-1, and Tie2. miR-21 expression was higher in cirrhotic tissues versus noncirrhotic tissues. MiR-101 expression was lower in cirrhotic versus noncirrhotic adjacent liver parenchyma. None of the miRNAs correlelated with COX-2 expression. miR-21 correlated negatively with Tie-2 receptor in adjacent liver parenchyma. Conclusions In human HCC, COX-2 mRNA but not COX-2 protein levels are associated with expression levels of angiogenic factors. MiR-21 levels are not associated with angiogenic molecules. MiR-16 and miR-101 levels do not correlate with COX-2 mRNA and protein levels.

Introduction
More than 80% of hepatocellular carcinomas (HCC) are associated with chronic infection caused by hepatitis B or C virus [1]. In well-developed countries with a high incidence of obesity and diabetes mellitus the risk of developing HCC rises proportionally with increasing body mass index and the duration of diabetes [2,3]. These conditions are frequently associated with non-alcoholic steatohepatitis (NASH) [4,5]. The common denominator in viral hepatitis associated liver diseases and NASH is presumed to be the chronic inflammation leading to fibrosis and cirrhosis and ultimately to HCC. HCC is thus one of the classical examples of inflammation-linked cancer [6]. The cyclooxygenase-2 (COX-2)-prostanoid pathway plays a pivotal role in inflammation and in the pathophysiology of liver diseases like cirrhosis and HCC [7]. COX-2 is an inducible immediate-early gene originally found to be induced by various stimuli including mitogens, cytokines and growth factors [8]. COX-2 might favor tumor growth by various mechanisms including stimulation of angiogen-esis, evasion of apoptosis and propensity to metastatic behavior and invasion. COX-2 inhibitors can block these mechanisms by various pathways and selective COX-2 inhibitors have been evaluated for their effect on HCC cell growth and invasion using animal models of hepatocarcinogenesis [9,10].
HCC can also arise in noncirrhotic livers with normal histology and no signs of inflammation or viral hepatitis. A common characteristic of both types of HCC is hypervascularity. The occurrence of both types of HCC in humans offers a unique opportunity to study the possible relation between inflammation and angiogenesis, in which angiogenic characteristics can be analyzed in the presence (cirrhotic HCC) or absence (noncirrhotic HCC) of chronic inflammation. Unraveling of the underlying mechanisms might lead to more efficacious treatment modalities both for (chemo)prevention and possibly also for treatment of already established HCC.
The aim of the present study is to investigate the correlation of COX-2 expression with the expression of angiogenic factors in human HCC in cirrhotic and noncirrhotic livers. We investigated gene and protein expression levels of COX-2 and correlated these to gene expression levels of VEGF-A, VEGFR-1 (Flt-1) and VEGFR-2 (KDR), and Angiopoietin (Ang)-1, Ang-2, and their receptor Tie-2 in HCC, adjacent liver parenchyma and normal liver parenchyma. The cellular localization of COX-2 was studied by immunohistochemistry. Several papers highlighted the role of microRNAs (miRNAs) in the control of COX-2 transcription. MiRNAs are small noncoding RNAs that control gene expression at the posttranscriptional level. Their role in HCC has recently been reviewed [11]. Especially miR-21, miR-101 and miR-16 seem to be relevant for the present study. MiR-21 is an oncogene with high expression levels in various cancers including HCC. Additionally, miR-21 is strongly related to angiogenesis [12,13]. Furthermore, accumulating evidence links miR-21 to inflammation [14][15][16] including the necroinflammation in the liver which ultimately results in liver cirrhosis [17]. In contrast, miR-101 is considered a tumor suppressor gene and its expression was inversely correlated with COX-2 expression in colon cancer and gastric cancer [18,19]. Another miRNA shown to inhibit COX-2 expression is miR-16. In several hepatoma cell lines an inverse relation between miR-16 and COX-2 was found [20].The same authors describe a negative correlation between COX-2 protein and miR-16 expression in seven human HCC and paired nontumoral liver biopsies.
The study aimed at analysing (1) the correlation between COX-2 expression and angiogenic factors, (2) the correlation between COX-2 expression and miR-101/miR-16 and (3) the correlation between angiogenic factors and miR-21 in cirrhotic and noncirrhotic HCC, both in tumor tissue and adjacent liver parenchyma.

Patients and Methods
All (anonymised) tissue samples were processed according to national guidelines. According to the Dutch law no approval of an Institutional Review Board is necessary for investigations using archival materials of previously resected tissue specimens. Tissue samples of 41 HCC patients were included; 21 noncirrhotic HCC obtained from partial liver resection specimens and 20 cirrhotic HCC obtained from liver explants after liver transplantation. Clinicopathological characteristics of the patients are summarised in Table 1. A sample of adjacent, non-tumorous liver tissue was also included in the study. None of the HCC patients underwent previous treatments like local ablation, chemoembolisation or chemotherapy.
Samples from histological normal livers (n = 8), obtained from surplus donor liver or partial liver resection for benign disorders, were used as a reference and not for statistical comparisons. HCCs were graded according to the Edmonson classification and COX-2 mRNA level and protein expression was compared among the three classes.

MiRNA analysis
Expression levels of miR-16, miR-21 and miR-101 were determined by qRT-PCR using RNU49 as housekeeping gene with miRNA qRT-PCR assays (Applied Biosystems, Foster City, USA) as described previously [22]. Reverse transcription (RT) primers specific for a miRNA and RNU49 were multiplexed in 15 ml RT reactions containing 1 ml of each RT primer. The miRNA levels were normalized to the RNU49 levels. Mean cycle threshold (C t ) values for all genes were quantified with the SDS software (version 2.1). Relative expression levels were calculated as 2 2DCt .

Western blot
Western blotting was performed as described previously using mouse anti-COX-2, 1:500 (BD Biosciences Pharmingen, #610204) [21]. Quantification of the signals detected was done by relating COX-2 to b-actin control. The bands of COX-2 protein located at about 70 kDa as expected according to the datasheet of the antibody.

Immunohistochemical examination of COX-2 expression
Four mm tissue sections were deparaffinized and treated with 0.08% H 2 O 2 for 30 min to block endogenous peroxidase. Slides were incubated with mouse anti-COX-2 (BD Biosciences Pharmingen, #610204) 1:50, diluted in 1%BSA/PBS, at 4uC overnight followed by incubation with horseradish peroxidaseconjugated rabbit anti-mouse Ig and goat anti-rabbit Ig (DAKO), both 1:100 diluted in 1%BSA/1% albumin/PBS. Diaminobenzidin was used to develop the staining reaction and nuclear counterstaining was performed with haematoxylin. A sample of a human colonic adenocarcinoma was included as a positive control.

Correlation between COX-2 protein and mRNA level
Pearson correlation coefficients were calculated for COX-2 mRNA and COX-2 protein separately for HCC and liver parenchyma. We calculated the COX-2 protein:COX-2 mRNA ratio for each individual case; this method has been used for identification of the strength of correlation of mRNA expression and protein level of individual genes by Pradet et al [23].
Correlation of COX-2 and miR-21 with Ang-2:Ang1 ratio Although in many tumors both Ang-1 and Ang-2 are elevated, the angiogenic state of hypervascular tumors is characterized by an overexpression of Ang-2 in relation to Ang-1 thus creating a shift in the Ang-2:Ang-1 ratio in favor of Ang-2 [24]. A higher Ang2:Ang1 ratio was also encountered in human HCC [24]. Therefore we analyzed the correlation between COX-2, miR-21and the Ang-2:Ang-1 gene expression ratio.

Statistical analysis
Quantitative data were expressed as median and interquartile range (IQR). Expression of COX-2 mRNA, COX-2 protein, miR-16, miR-21 and miR-101 were compared using a two-tailed Mann-Whitney-U test (non-related samples) in cirrhotic versus noncirrhotic liver of HCC and adjacent parenchyma separately. The Wilcoxon test (related samples) was used for comparison of HCC with adjacent parenchyma in cirrhotic and noncirrhotic liver separately. For correlation statistics, values were normalised by log (base 10) transformation. Pearson correlation coefficients were calculated between COX-2 and the angiogenic factors, between miR-21 and the angiogenic factors and between miR-101 and miR-16 and both COX-2 mRNA and COX-2 protein. A pvalue ,0.05 was considered significant.

COX-2 expression in HCC and adjacent liver parenchyma in cirrhotic and noncirrhotic liver
HCC tumor tissue in both cirrhotic and noncirrhotic liver demonstrated a lower COX-2 expression compared to adjacent parenchyma, both at the mRNA ( Figure 1A) and protein level ( Figure 1B). Median COX-2 mRNA level in the tumor in noncirrhotic liver was about tenfold lower than in tumor-adjacent liver parenchyma (p,0.001). In cirrhotic liver, HCC tumor had a six-fold lower COX-2 mRNA content than adjacent parenchyma (p,0.001). Protein levels of COX-2 were approximately 370 fold lower in HCC in noncirrhotic liver as compared to adjacent liver parenchyma (p = 0.033). In cirrhotic liver, HCC tumor had a 30% lower COX-2 protein level (p = 0.020) than adjacent parenchyma. A comparison between COX-2 mRNA and COX-2 protein expression in cirrhotic versus noncirrhotic HCC tumor tissue revealed no differences ( Figures 1A and 1B). COX-2 staining in HCC was mainly found in endothelial cells lining the sinusoid-like spaces in the tumor but less conspicuous than in vascular endothelial cells at the interface between tumor and adjacent liver parenchyma. (Figure 2) As a positive control of COX-2 immunohistochemical staining we included a colon carcinoma sample which was strongly positive (Figure 2 insert). No difference was found in COX-2 mRNA level and protein expression between tumors with Edmonson grade 1, grade 2 or grade 3 (p.0.35).
COX-2 mRNA and COX-2 protein expression in tumoradjacent liver parenchyma was comparable in cirrhotic and in noncirrhotic liver and in the same range as normal liver parenchyma ( Figures 1A and 1B). COX-2 staining was observed in both vascular and sinusoidal endothelial cells as well as in Kupffer cells in normal liver and in parenchyma adjacent to HCC. No expression was found in hepatocytes or in cholangiocytes ( Figure 2).
Although median COX-2 expression in HCC was less than in the surrounding parenchyma, individual cases demonstrated variable results as can also be seen in representative Western blots of COX-2 ( Figure 3).

Correlation of COX-2 gene expression and protein level with angiogenic factors in HCC tumor tissue
Of the six analysed angiogenic factors, VEGFR1, Ang-1 and Tie-2 revealed a significant correlation with COX-2 mRNA levels in HCC tumor tissue both in noncirrhotic and cirrhotic liver (Table 2). Additionally, a correlation between COX-2 mRNA and VEGFR2 mRNA was observed in HCC in noncirrhotic liver only (r = .78, p,0.001). No significant correlations were obtained between the angiogenic factors and COX-2 protein in HCC tumor tissue. Moreover, also the Ang-2:Ang-1 gene expression ratio did not show any correlation with COX-2 expression ( Table 2).

Correlation of COX-2 gene expression and protein level with angiogenic factors in adjacent liver parenchyma
We found no significant correlation between COX-2 mRNA levels and any of the angiogenic factors in tumor-adjacent liver parenchyma, except for Ang-1 in adjacent cirrhotic liver ( Table 2). None of the mRNA levels of the angiogenic factors in adjacent parenchyma correlated significantly with COX-2 protein.

Correlation of COX-2 mRNA expression and COX-2 protein level
No correlation was found between COX-2 mRNA expression and COX-2 protein level neither in HCC tumor tissue nor in adjacent parenchyma (p.0.13). Calculation of the COX-2 protein:COX-2 mRNA ratio revealed a range from ,1 to .35,000 in HCC tumor tissue and from 100 to .7,000 in liver parenchyma. These results suggest that post-transcriptional mechanisms are responsible for the highly variable COX-2 protein levels. Figure 1C shows the relative expression of miR-16 in normal liver, tumor adjacent liver and in cirrhotic and noncirrhotic HCC tumor tissue. No statistically significant differences were found between any of these tissues. Also no correlation between miR-16 expression and either COX-2 mRNA or COX-2 protein was found.

MiR-21 expression in HCC and liver parenchyma and correlation with angiogenic factors
Relative expression levels of miR-21 were higher in cirrhotic tissues -both in HCC tumor tissue and adjacent liver parenchymaas compared to HCC and parenchyma in non-cirrhotic tissues ( Figure 1D). Furthermore, HCC in cirrhotic liver revealed a higher expression of miR-21 versus adjacent liver parenchyma. Analyzing the correlation between miR-21 expression and the angiogenic factors revealed no correlations except for a negative correlation (r = 2.76, p = 0.046) between miR-21 expression and the Tie-2 receptor in adjacent cirrhotic liver parenchyma.

MiR-101 expression in HCC and liver parenchyma and correlation with Cox-2 expression
Relative expression levels of miR-101 were lower in adjacent liver parenchyma in cirrhotic liver as compared to adjacent parenchyma in non-cirrhotic liver ( Figure 1E). MiR-101 expression did not correlate with COX-2 expression neither at the mRNA level nor at the protein level.

Discussion
In this study we analyzed the expression of COX-2, miR-101 and miR-16 -both with COX-2 inhibiting effects-and miR-21with pro-angiogenic and pro-inflammatory effects-in relation to expression of various angiogenic factors in human HCC in cirrhotic and noncirrhotic liver. The chronic inflammation in cirrhotic liver provides a prosperous environment for development of HCC and because of the interaction between inflammation and angiogenesis we analysed the above mentioned molecules in two groups of patients; those with HCC in a cirrhotic liver and in patients with HCC in a noncirrhotic liver. The main finding of this study is that although at mRNA level COX-2 expression correlates positively with mRNA expression of the Ang-1/Tie-2 axis in both cirrhotic and noncirrhotic HCC, no such a correlation was encountered at the COX-2 protein level. As a possible explanation for this discrepancy we investigated the role of miR-101 and miR-16 in HCC tumor tissue and adjacent parenchyma. We found that  neither miR-101 nor miR-16 had a correlation with COX-2 mRNA or COX-2 protein.
In prostate cancer cell lines it was demonstrated that miR-101 inhibits COX-2 by translational repression via binding to the 39 untranslated region (UTR) of COX-2 mRNA [25]. In colon cancer cell lines a discrepancy was encountered between COX-2 protein levels and COX-2 mRNA expression; of six miRNAs examined only miR-101 demonstrated an inverse relation with the COX-2 protein/mRNA ratio in these cell lines [18]. The same authors investigated human primary colorectal cancer specimens and liver metastases and found the same inverse relation. In a series of 30 patients with gastric cancer more advanced tumor stages were associated with lower miR-101 expression which was inversely related to COX-2 mRNA expression [19]. All these data provide support for a possible role of miR-101 as a negative regulator of COX-2 protein expression and therefore we analyzed this interaction also in the HCC tumor tissue. However, we could not corroborate these findings since our data showed no inverse correlation between COX-2 and miR-101 in HCC.
MiR-21 is an important oncomir in many cancers and also in HCC tumor tissue [26,27]. MiR-21 plays a role in angiogenesis as was demonstrated in experiments with cell lines as well as in human cancer [12,13]. In prostate cancer cell lines inhibition of miR-21 was associated with a less aggressive phenotype via inhibition of tumor growth and invasiveness [28]. Of the miRNAs analysed in our study, the most prominent differences were encountered in miR-21 expression. MiR-21 revealed the highest expression in HCC in cirrhotic liver and also adjacent cirrhotic liver parenchyma showed a higher miR-21 expression as compared to noncirrhotic adjacenct liver parenchyma. This differential expression, however, did not translate into significant correlations with the studied angiogenic factors, except for a negative correlation with the Tie-2 receptor in liver parenchyma only. This adds support to the idea that clinically overt HCCdespite a different parenchymal background-share several molecular characteristics, which is in accordance with previous findings in which no differences were found between HCC in cirrhotic versus noncirrhotic livers with respect to endothelial cell turnover, microvessel density as well as expression of various angiogenic growth factors [29,30]. MiR-21 is rather ubiquitous in health and disease [14,31]. Therefore it is not surprising that upregulation of miR-21 has a pivotal role in many inflammatory processes, like in patients with chronic liver diseases in whom miR-21 serum levels correlated with the severity of liver fibrosis and necroinflammation [17,32].
We found a discordance between COX-2 mRNA and protein level. As a possible explanation for this discrepancy posttranscriptional mechanisms, like transcript decay and translation rate, but also post-translational modifications which determine protein turnover and thereby protein expression levels have been described [33] [34]. In humans highly discrepant results were observed between mRNA and protein expression in a study of human lung adenocarcinomas [35]. Thus, mRNA abundance does not necessarily translate into the detection of the corresponding protein with the currently available techniques and conclusions should be drawn cautiously [23].
The lack of correlation between miR-16, miR-101 and COX-2 expression is in contrast to findings in other tumor types like gastric and colon cancer. We propose two possible explanations for this discrepancy, (1) insufficient expression level of the miRNAs and (2) (tumor)tissue specificity of the miRNAs. It is likely that the expression of miRNAs should be above a -as yet unknownminimum threshold level before they can exert their function [36,37]. Differences in miRNA expression might thus explain differences in functional actvivity. In addition, the overall abundance of all miRNA specific target genes in a given cell also may affect the targeting efficiency. For the analysis at the RNA level total tissue is used, and there might be a discrepancy between cells expressing the miRNA and the COX-2 gene. The current dogma describes that COX-1 is constitutively expressed and COX-2 is only expressed as a result of induction by a wide range of stimuli [38]. In an autopsy study on trauma victims, this concept was seriously questioned, because several healthy tissues, including the normal liver, were shown to express COX-2 [39]. We also found COX-2 expression in normal liver parenchyma; this was comparable to COX-2 expression in liver parenchyma adjacent to HCCs. In parenchyma adjacent to HCC we found that COX-2 expression was even higher than in HCC itself. Our data are in agreement with findings of Morinaga et al. who found a 2.5-fold higher COX-2 mRNA expression in adjacent liver parenchyma as compared to HCC [40]. In their study COX-2 protein expression -determined by immunohistochemistry-seemed to parallel mRNA expression and the authors explained this by inflammatory activity in tumor-adjacent parenchyma. A limitation of our study is that the investigated tumor samples were obtained from clinically overt HCCs and the resulting signature will be rather different from the signature in dysplastic nodules and small -clinically undetectable-HCCs. For instance, COX-2 expression was found to be highest in dysplastic nodules with lower expression levels in more poorly differentiated advanced tumors in human HCC [41]. Another limitation of the study is the relatively low number of included patient samples.
From this study in human HCCs we conclude that COX-2 is expressed to a similar extent in cirrhotic and noncirrhotic adjacent liver parenchyma. Also no differences were found between HCC in cirrhotic and noncirrhotic liver despite the fact that COX-2 mRNA and COX-2 protein was lower in HCC in comparison to adjacent parenchyma. COX-2 mRNA levels both in cirrhotic and noncirrhotic HCC tumor tissue correlated with angiogenic factors. The inverse correlation between miR-101 and COX-2 protein -as found in colorectal cancer by others-was not found in our HCC tumor samples. The described prominent role of miR-21 as a proangiogenic miR could not be substantiated in this study. The clinical usefulness of COX-2 inhibitors especially in the setting of chemoprevention for the development of human HCC can only be based on randomized clinical trials since the precise regulatory mechanisms of COX-2 are far from elucidated.


extfieldsofstudy: Chemistry Medicine

s2fieldsofstudy: Biology Chemistry

text:
Inhibition of Catalase by Tea Catechins in Free and Cellular State: A Biophysical Approach

Tea flavonoids bind to variety of enzymes and inhibit their activities. In the present study, binding and inhibition of catalase activity by catechins with respect to their structure-affinity relationship has been elucidated. Fluorimetrically determined binding constants for (−)-epigallocatechin gallate (EGCG) and (−)-epicatechin gallate (ECG) with catalase were observed to be 2.27×106 M−1 and 1.66×106 M−1, respectively. Thermodynamic parameters evidence exothermic and spontaneous interaction between catechins and catalase. Major forces of interaction are suggested to be through hydrogen bonding along with electrostatic contributions and conformational changes. Distinct loss of α-helical structure of catalase by interaction with EGCG was captured in circular dichroism (CD) spectra. Gallated catechins demonstrated higher binding constants and inhibition efficacy than non-gallated catechins. EGCG exhibited maximum inhibition of pure catalase. It also inhibited cellular catalase in K562 cancer cells with significant increase in cellular ROS and suppression of cell viability (IC50 54.5 µM). These results decipher the molecular mechanism by which tea catechins interact with catalase and highlight the potential of gallated catechin like EGCG as an anticancer drug. EGCG may have other non-specific targets in the cell, but its anticancer property is mainly defined by ROS accumulation due to catalase inhibition.

The ability of flavonoids to bind and inhibit some vital cellular enzymes leading to suppression of cell proliferation is being investigated widely [18][19][20][21][22]. EGCG is known to bind to proteins like salivary proline-rich proteins, fibronectin, fibrinogen and histidine rich glycoproteins [23]. Caseins and lactoglobulins are milk proteins which rendered the antioxidant activity of tea polyphenols upon binding with catechins [24][25][26][27]. EGCG binds to Bcl-2 proteins with inhibition constant (K i ) 0.33-0.49 mM and to vimentin and G3BP1 with dissociation constant (K d ) 3.3 nM and 0.4 mM, respectively [28][29][30]. In the present study, binding of catechins to catalase -an enzyme which maintains the cellular ROS levels is followed fluorimetrically and thermodynamically characterized.
Catalase is an antioxidant oligomeric enzyme (MW 2,40,000) with four identical subunits arranged tetrahedrally [31][32][33]. Each subunit consists of a single polypeptide chain that associates with a prosthetic group, ferric protoporphyrin IX [34]. It is a very important enzyme in protecting cells from oxidative damage by ROS. Drugs bind to enzymes and elicit enzyme inhibition; one such example is catalase inhibition by wogonin led to H 2 O 2 accumulation and cytotoxicity in cancer cells through H 2 O 2mediated NF-kB suppression and apoptosis activation [35]. Similarly, EGCG at concentrations between 5-20 mM also inhibited phosphorylation of JNK, JUN, MEK1, MEK2 in JB6 epidermal cell lines [36]. In MCF7 breast cancer cell lines, cyclin dependent kinase 2 (CDK2) and CDK4 were reported to be inhibited by 30 mM EGCG [37]. In KYSE 510 human esophageal cancer cells, EGCG inhibited DNA methyltransferase with K i 7 mM [38]. All these enzymes have relevance in cancer prevention. Inhibition of human cancer cell growth by tea polyphenols has been observed in H1299, H661, HT-29, H441 and breast cancer cell lines at IC 50 values between (20-75 mg/ml) [39]. Catalase is another cellular enzyme whose interaction with microsystin, a cyanotoxin drug, decreases its enzymatic action [40]. Here its inhibition in K562 cancer cells is reported and its relevance in cancer is demonstrated by the suppression of cell viability. The study also highlights the influence of structure of the catechins on the inhibition of catalase activity by catechins.
As endogenously formed ROS are important in promoting carcinogenesis, tea polyphenols may have important role in quenching them and also tea polyphenols being redox active can under go auto-oxidation and produce ROS in media and in mitochondria [41,42]. This makes activity of tea polyphenols in cancer prevention very complex which needs active investigation. Changes in ROS population are expected manifestation of catalase inhibition and have been followed to monitor the enzyme activity on EGCG treatment.

Cell culture
K562 (human chronic myeloid leukemia cell line) was procured from NCCS, Pune and grown in RPMI 1640 supplemented with 10% FBS, 100 U/ml of penicillin and 100 mg/ml of streptomycin in 25 cm 2 T-flasks (Nunc, Roskilde, Denmark) with vented caps and incubated at 37uC in a humidified atmosphere of 5% CO 2 in air.

Fluorescence spectroscopy
Fluorescence spectra were recorded using a Perkin Elmer fluorescence spectrophotometer (LS-55) equipped with 150 W Xenon flash lamp and using fluorescence-free quartz cell of 1 cm path length. The widths of excitation and emission slits were set to 5 nm, and scan speed (100 nm/min), excitation voltage were kept constant for each data set. Quantitative analysis of the potential interaction between catechins and catalase was performed by the fluorimetric titration technique. Briefly, solution of catalase (5610 27 M, as calculated using molar extinction coefficient of 3.24610 5 M 21 s 21 at 405 nm for catalase) in 50 mM phosphate buffer of pH 7.4 was titrated in cuvette by successive additions of individual catechin solution aliquots from a stock of 5610 27 M. Fluorescence emission spectra were recorded in the wavelength range of 290-450 nm upon excitation at 280 nm when catalase samples were titrated with catechins. All experiments were carried out at room temperature. Fluorescence intensity was measured at 340 nm of protein emission spectra. Fluorescence spectra of individual catechins in buffer were recorded as blanks under the same experimental conditions and subtracted from the corresponding sample to correct the fluorescence background.

Isothermal titration calorimetry (ITC)
The energetics of the binding of catechins to catalase was studied by ITC using a MicroCal ITC 200 , (Northampton, MA, USA). All solutions were degassed under vacuum (140 mbar, 10 min) on the MicroCal's Thermovac unit to eliminate air bubble formation inside the calorimeter cell. Briefly, the calorimeter syringe was filled with a concentrated solution of catechins (10 mM each). Successive injections of this solution into 1 mM solution of catalase in the calorimeter cell were effected from the rotating syringe with constant stirring of the solution. The titration and analysis were performed through Origin 7 software provided with the unit.

Circular dichroism (CD) spectroscopy
All the CD experiments were carried out on a Jasco-815 automatic spectropolarimeter (Jasco International Co., Ltd. Hachioji, Japan) equipped with a peltier cuvette holder and temperature controller PFD425 L/15. The catalase concentration and path length of the cuvette used were 1 mM and 0.1 cm, respectively. The instrument parameters were set at scanning speed of 50 nm/min, bandwidth of 1.0 nm and sensitivity of 100 milli degree. The molar ellipticity values are expressed in terms of mean residue molar ellipticity, in units of deg. cm 2 dmol 21 .

Inhibition of catalase activity
Absorption spectrophotometer (Varian, CARY 100 Bio, USA) was used to determine pure catalase activity (cell free). Briefly, 900 ml of H 2 O 2 (0.036%) was taken in quartz cell of 1 cm path length and its absorbance was recorded at 240 nm. To the solution, 100 ml of catalase (50 U/ml) was added and the decrease in absorbance was recorded at 10 s interval. This experiment was performed in presence 50 mM each of four catechins and 3-AT separately to evaluate the inhibitory effect of catechins on catalase activity, after 1 h incubation.
Estimation of cellular catalase activity was carried out by suspending K562 cells (5610 4 for each sample) in 1 ml of PBS along with four catechins and 3-AT (50 mM each) separately and incubated at 37uC for 2 hours. Later, each sample was centrifuged and washed twice with PBS. The final pellet was suspended in 200 ml lysis buffer and kept on ice for 30 min. The lysate was then used in the same protocol used for evaluation of pure catalase activity.

Analysis of cell viability
Cell viability of K562 cells was quantified by MTT based colorimetric assay as described elsewhere [43]. Briefly, cells were rinsed with PBS and 0.5 mg/ml MTT was added into each sample. The mixture was incubated at 37uC for an additional 3 h. At the end of incubation period, the medium containing MTT was removed and the pellet was dissolved in 200 ml DMSO. Absorbance was measured at a wavelength of 570 nm. Cell viability was expressed as a percentage of the control culture.

Measurement of intracellular ROS
Intracellular ROS were estimated by using the DCFDA fluorescent probe [9]. Intracellular H 2 O 2 and other peroxides can oxidize DCFDA to highly fluorescent compound dichlorofluorescein (DCF). K562 cells were incubated at 37uC in absence and presence of EGCG (12.5 -100 mM) for 24 h. Cells were again incubated with 10 mM DCFDA at 37uC for an additional 30 min, and then washed twice with PBS. Finally the fluorescence intensity of DCF was measured with an excitation wavelength of 485 nm and emission wavelength of 530 nm.

Statistical analysis
Data were analyzed by Origin Software (Version 8) for Windows. The statistical analysis of the samples was undertaken using Student's t-test. All data reported are means 6 standard deviations for three independent experiments, unless otherwise noted.

Quenching of catalase fluorescence by catechins
Catalase shows a fluorescence emission peak at 340 nm with the excitation wavelength at 280 nm, mainly due to the presence of tryptophan and tyrosine residues [44]. This emission peak exhibited progressive decrease in intensity on addition of catechins suggesting interaction between catalase and catechins (  ITC directly measures the heat released during a chemical reaction. ITC can reveal the stoichiometry, enthalpy free energy, and entropy changes that occur over the course of a reaction [45,46]. Data obtained from the titration are presented by the series of peaks corresponding to each injection. Usually, this representation is transformed into the apparent heat change between two injections as a function of the titrant ratio by means of integration of power differential with regard to time. ITC has been used mainly to quantify interactions in various biochemical systems [47][48][49]. ITC has been used in the present study to determine binding affinity and other thermodynamic parameters of catechins-catalase interaction. Representative isothermal calorimetric heat profiles for the binding of catechins-catalase interaction, at physiological pH and 25uC are shown in Figure 4 (A-D). The data were corrected for the heat of dilution of catechins, which was determined in a separate set of experiments under identical conditions. The titration and analysis were performed using one-site binding model through Origin 7 software provided with the unit. The thermodynamic parameters recorded for the binding of catechins (10 mM each) with catalase (1 mM) are summarized in Table 1. From Figure 4 it is observed that the titration of catalase with all the four catechins yield negative heat deflections. EC, EGC, ECG, and EGCG bind to catalase with binding constants 2.13610 5 , 1.92610 5 , 6.36610 5 , and 8.19610 5 M 21 , respectively, as determined by the following equation: DG = 2RT ln K, where DG is the free energy, R and T are the gas constant and temperature, respectively, K is the binding constant.

Catechin induced conformational changes in catalase
CD allows investigation of the conformational changes that occur in a protein upon ligand binding [50]. The CD spectra of catalase at pH 7.4 in the absence and in the presence of EGC, EC, ECG, EGCG, and 3-AT at 25uC are represented in Figure 5 (af). The CD spectra of catalase exhibited two negative bands in the far-UV region at 208 and 220 nm, characteristic of an a-helical structure of protein [51]. The negative band at 208 and 220 nm decreased in intensity with the addition of various catechins, which is indicative of the loss of a-helicity upon interaction. The CD spectra of catalase in presence and absence of catechins were observed to be similar in shape, indicating that the structure of catalase is predominantly a-helical [52]. From the CD spectra, the effect of catechins on the secondary structure of catalase is in the following order: 3-AT.EGCG.ECG.EC.EGC.

Inhibition of catalase activity
The spectroscopic approach for determination of catalase activity on H 2 O 2 degradation showed continuous breakdown of its substrate, H 2 O 2 with time (upto 100 s) at 240 nm. On addition of catechins, a decrease in rate of H 2 O 2 degradation i.e. a decrease in pure catalase activity was observed which is represented in Figure 6A. Catechins with galloyl moiety (ECG and EGCG) reduced catalase activity more than its non-gallated counterparts i.e. EGC and EC. However, Inhibition by EGCG is the closest to inhibition by known catalase inhibitor 3-AT. The order of inhibition of catalase activity was found to be 3-AT.EGCG. ECG.EC.EGC. The same experiment with cellular catalase in K562 cells revealed inhibition of cellular catalase activity in the presence of catechins ( Figure 6B). The trend of inhibition in this condition was observed to be similar to that of pure catalase. The double reciprocal plot or Lineweaver-Burk plot shows that the inhibition of catalase by EGCG is of uncompetitive type (Figure 7). The y-intercept i.e. 1/V 0 value for uninhibited and inhibited catalase were found to be 0.0081 and 0.3635 mM 21 min, respectively.

MTT assay for cell viability
The concentration (IC 50 ) at which the K562 cell survivability was reduced to 50% was calculated for EGCG and 3-AT by MTT based cell viability assay. The IC 50 value obtained for EGCG and 3-AT was 54.5 mM and 10.5 mM, respectively.  (Figure 8).

Discussion
Catechins are antioxidants ubiquitously found in green tea and among them EGCG shows highest antioxidant activity that may have therapeutic applications in cancer treatment. EGCG functions as a powerful antioxidant, preventing oxidative damage in healthy cells, but also as an anti-angiogenic and antitumor agent and as a modulator of tumor cell response to chemotherapy. However, neither pro-oxidant nor antioxidant activities have yet been clearly established to occur in vivo in humans [53]. Natural polyphenols are reported to be good inhibitors of human dihydrofolate reductase (DHFR) could explain the epidemiological data on their prophylactic effects for certain forms of cancer and open a possibility for the use of natural and synthetic polyphenols in cancer chemotherapy [54].
Fluorescence quenching experiments demonstrated that the ester bond containing tea polyphenols EGCG and ECG are effective inhibitors of DHFR with K d of 0.9 and 1.8 mM, respectively, while polyphenols lacking the ester bond containing galloyl moiety (e.g., EGC and EC) did not bind to this enzyme [54]. The binding constant of EGCG to catalase was determined fluorimetrically to be 2.27610 6 M 21 (K d of 0.44 mM). Other catechins were not as effective as EGCG establishing the influence of galloyl moiety for efficient binding. The binding efficiency is attributed to the eight phenolic groups of EGCG which serve as hydrogen bond donors. Involvement of positive charge on the carbon atom of the ester bond with the electronegative groups of amino acid residues like histidine also contributes towards efficient binding. Here it can be reasoned that at this concentration of EGCG it can also bind to other non-specific targets in vivo due to the presence of OH groups. To this end, it can be emphasized that binding to catalase inhibits its activity and increases the ROS population which eventually triggers apoptosis. It is known that 3-AT (an efficient inhibitor of catalase) binds with histidine residue (His75) near heme group of catalase forming a non-coplanar adduct (very close to Tyr358). Loss in fluorescence intensity of catalase suggests involvement of EGCG cation with histidine anion (pKa = 6.5) [55] near tyrosine residue (Tyr358) of active site [56]. This identification of the important structural features responsible for inhibition will provide valuable information for designing new inhibitors.
ITC provides valuable information on biomacromoleculeligand interactions [57,58]. This technique measures the heat released or absorbed (DH) when the macromolecule binds to  [40], which is lower than catalase-EGCG complex. Microcystin binding to catalase was reported to influence its physiological functions and conformation [40]. Binding is stronger with EGCG and more changes are observed in catalase-catechins complexes. Loss of a-helix is identified in the CD spectra by the decrease in negative peak at 222 nm and 208 nm (signature peaks of a-helix) on addition of EGCG as shown in Figure 5. Gain in bsheet is observed from the increase in negative peak at 218 nm against 222 nm for a-helix. These conformational changes in catalase secondary structure on interaction with catechins influence its active site and physiological functions, rendering it inactive in scavenging ROS.
In the present study, the physiological changes are demonstrated by the inhibition of catalase activity by catechins. EGCG is observed to inhibit more efficiently than ECG and other nongallated catechins. From the decay curves as shown in Figure 6, it is inferred that the rate of H 2 O 2 degradation is reduced by catechins in cell free ( Figure 6A) and cellular state ( Figure 6B). From the Lineweaver-Burk plot (Figure 7), it is evident that the maximum inhibition of catalase is achieved by EGCG. The plot also demonstrates uncompetitive type of inhibition suggesting that EGCG binds to catalase at a site other than the active site. As a consequence, the uncompetitive inhibitor (here EGCG) lowers the measured maximum velocity (V max ) and also decreases apparent K m value [59]. This inhibition in catalase activity results in   accumulation of ROS as illustrated in Figure 8. Higher levels of ROS create oxidative stress which is detrimental to cellular integrity.
The IC 50 value for suppression of cell viability in K562 cells on EGCG treatment is determined to be 54.5 mM (or 27 mg/ml). Inhibition of human cancer cell growth by tea polyphenols has been observed in H1299, H661, HT-29, H441 and breast cancer cell lines at IC 50 values between 20-75 mg/ml [39]. Higher EGCG concentration is required in the cell to elicit cellular response than its K d value to catalase. Here it can be emphasized that suppression of cancer cell viability is not envisaged only by catalase inhibition but other pathways contribute to it. EGCG is capable of generating H 2 O 2 in solution by auto-oxidation which contributes to oxidative stress. Superoxide is also reported to be generated in EGCG containing solutions [60]. In such conditions, inhibition of catalase by EGCG further increase the oxidative stress triggering apoptosis and eventually leading to cell death. These phenomena can be therapeutically used for cancer prevention. These revelations suggest that a balance between all the major activities of EGCG like antioxidants, pro-oxidants and enzyme inhibitors leads to cellular suppression, which is again cell specific. Inhibition of cellular enzymes by catechins has found major pharmacological applications as anticancer drugs [61]. Addition of methyl groups to ECG enhanced binding to DHFR and is a new approach to find novel inhibitors from natural resources [54]. A concentration of 27 mg/ml is high for EGCG to be bioavailable by tea consumption. Here EGCG is then treated as drug that can be delivered in various forms; one of which could be nano-formulations.

Conclusion
The efficacy of EGCG to bind with catalase and render its activity in cancer cells definitely represents a fascinating tool in the field of oncology. The present work sheds light on the critical structural features of galloylated catechins and identifies probable mechanism by which they inhibit catalase. These findings provide guidance for designing efficient catalase inhibitors. However, a cancer cell death event is an endpoint of several pathways and further studies in this context are in progress to completely understand the role of catechins in anticancer therapy. This study also demonstrates that natural polyphenols could be used as 'guide compounds' for development of new anticancer drugs.


s2fieldsofstudy: Biology Psychology

text:
Monkey Pulvinar Neurons Fire Differentially to Snake Postures

There is growing evidence from both behavioral and neurophysiological approaches that primates are able to rapidly discriminate visually between snakes and innocuous stimuli. Recent behavioral evidence suggests that primates are also able to discriminate the level of threat posed by snakes, by responding more intensely to a snake model poised to strike than to snake models in coiled or sinusoidal postures (Etting and Isbell 2014). In the present study, we examine the potential for an underlying neurological basis for this ability. Previous research indicated that the pulvinar is highly sensitive to snake images. We thus recorded pulvinar neurons in Japanese macaques (Macaca fuscata) while they viewed photos of snakes in striking and non-striking postures in a delayed non-matching to sample (DNMS) task. Of 821 neurons recorded, 78 visually responsive neurons were tested with the all snake images. We found that pulvinar neurons in the medial and dorsolateral pulvinar responded more strongly to snakes in threat displays poised to strike than snakes in non-threat-displaying postures with no significant difference in response latencies. A multidimensional scaling analysis of the 78 visually responsive neurons indicated that threat-displaying and non-threat-displaying snakes were separated into two different clusters in the first epoch of 50 ms after stimulus onset, suggesting bottom-up visual information processing. These results indicate that pulvinar neurons in primates discriminate between poised to strike from those in non-threat-displaying postures. This neuronal ability likely facilitates behavioral discrimination and has clear adaptive value. Our results are thus consistent with the Snake Detection Theory, which posits that snakes were instrumental in the evolution of primate visual systems.

Introduction
Biologically threatening stimuli are known to elicit fast and vigorous reactions from most animals, including freezing, darting, rapid retreat, alarm calls, and defensive attacks. Such responses were likely selected for over evolutionary time because animals that behaved in ways that helped them avoid threatening stimuli would have survived longer than those that did not. Before these reactions occur, however, the threatening stimuli must be detected, and this can be achieved through one or more of the senses. Rodents for example, can detect the scents of snakes and other predators and avoid areas where those predators have recently been [1,2]. In the case of primates, the olfactory sense has been reduced over evolutionary time with concomitant expansion of the visual sense. It has been argued that predation pressure from snakes constituted a strong source of selection that directly favored expansion of the visual system of primates at the expense of the olfactory system [3,4]. Snakes that had gapes large enough to eat mammals evolved shortly before the primate lineage evolved, and venomous snakes have been a threat to anthropoid primates since their divergence from prosimians approximately 60 million years [4]. Primate visual systems are wellsuited for clearly seeing objects in the lower visual field within peripersonal space, where the risk from snakes is usually greatest [4,5].
Wild primates and both fatal and snake-naïve laboratory-reared primates exhibit strong behavioral responses toward snakes [6][7][8][9][10]. Recently, both human and non-human primates have also been found to exhibit strong visual responses toward snakes. In humans, adults, children, and even infants are able to visually detect images of snakes faster than nonthreatening targets both in color and grayscale images [11][12][13][14][15]. Japanese macaques (Macaca fuscata) respond in a similar manner [16]. Snake images also receive attentional priority compared to other stimuli. They draw attention away from neutral targets (i.e., a bird) when their images are included against a background of other neutral objects, especially under high perceptual load, i.e., under conditions that simulate the cluttered natural environments in which snakes are often found [17].
A specific neuronal circuit for innate visual recognition of threatening stimuli such as snakes has been proposed that includes a fast, automatic, subcortical pathway involving the superior colliculus and the pulvinar nucleus in the thalamus [3,4,[18][19][20]. Several behavioral and neurophysiological studies support this model. For instance, monkeys with bilateral neurotoxic lesions of the superior colliculus readily approached food located in a center of a coiled snake model, while monkeys with sham lesions avoided the food [21]. In humans, complete unilateral loss of the pulvinar induced deficits of recognition of emotional expressions while a sparing of the medial and posterior pulvinar did not [22]. When people were shown images of fear faces so quickly that they were not consciously aware of them, both the superior colliculus and pulvinar were activated [23].
In a study to investigate the neuronal basis of the ability of primates to visually detect snakes quickly and automatically, Le et al. [24] found neurons in the medial and dorsolateral pulvinar of Japanese macaques that responded more strongly and quickly to snake images than to images of faces and hands of macaques, and to simple geometric shapes. Interestingly, the response characteristics of these pulvinar neurons were well correlated with those in the superior colliculus except that response latencies were shorter in the superior colliculus [25,26] as might be expected if the visual route for detecting threatening stimuli goes first to the superior colliculus and then to the pulvinar (see above).
Recently, there has been interest in identifying the specific cues provided by snakes that enable primates to visually detect them so rapidly. Snakes have a number of qualities shared by no other animals, including an elongated, limbless, scaled body that can change shape depending at times on the degree of their intent to strike and thus, on the degree of threat. LoBue and DeLoache [27] found that humans were unable to detect coiled snakes more quickly than other coiled objects. Moreover, elongated snakes were not detected more quickly than flowers. They suggested that the unique ability of snakes to coil upon themselves is the critical stimulus for rapid detection. Unfortunately, they did not control for the level of threat. A study of rhesus macaques (M. mulatta) found that a sinusoidal snake model (most similar to an elongated snake) elicited weaker responses than a coiled snake model, as would be expected if a coiled shape is the critical cue. However, a snake model that was partially exposed and revealing only a slight curve elicited stronger responses than a coiled snake model, suggesting that posture per se is less important than the information that can be gleaned from it. A snake poised to strike reveals a greater or more immediate threat than a coiled, sinusoidal, or elongated snake, and indeed, a snake model poised to strike in a threat posture elicited the strongest responses from the monkeys [28]. Children with no experience with snakes also visually detected photos of snakes in threat posture faster than those of snakes not poised to strike [29]. These findings suggest that primates are sensitive to variation in the level of threat revealed by snakes in different positions, with elongated or sinusoidal snakes being least threatening, coiled snakes intermediate, and snakes poised to strike most threatening.
Taking these behavioral and neurological findings together, we predicted that pulvinar neurons would respond preferentially to images of snakes in threatening postures compared to less threatening postures in bottom-up visual processing. To test this prediction, 3 photos of snakes in threat displays with open mouths and 3 photos of snakes in less threatening postures were presented to Japanese macaques in a delayed non-matching to sample (DNMS) task. Here, we report that pulvinar neurons discriminate postural cues of snakes that are linked to their level of threat, consistent with behavioral studies [28,29].

Subjects
Two adult (1 female and 1 male) Japanese macaques, weighing 7.0-8.8 kg, were used in this experiment. Each monkey was individually housed in indoor each cage (0.865 m60.710 m60.880 m) on a 12-hr on/12-hr off lighting schedule with food available ad libitum. The monkeys were deprived of water in their home cage and received juice as a reward during training and recording sessions. Supplemental water and vegetables were given after each day's session. To assess the monkeys' health, their weight was routinely monitored. The monkeys were treated in strict compliance with the United States Public Health Service Policy on Human Care and Use of Laboratory Animals, the National Institutes of Health Guide for the Care and Use of Laboratory Animals, and the Guidelines for the Care and Use of Laboratory Animals of the University of Toyama. This study was approved by the Committee for Animal Experiments and Ethics at the University of Toyama (Permit Number: A2013MED-46). Environmental enrichment (toys) was provided daily, and all surgery was performed under anesthesia, and all efforts were made to minimize suffering. No monkeys were sacrificed. The animals' health status was monitored throughout the experiment, and kept in a good condition for the animals to perform the task correctly (see below).

Experimental setup
The monkey sat in a monkey chair 68 cm away from the center of a 19-inch computer display for behavioral tasks during the training and recording sessions in a shielded room. The CRT monitor was set so that its center was on the same horizontal plane as the monkey's eyes. The monkey chair was equipped with a responding button, which was positioned so that the monkey could easily manipulate it. An infrared charge-coupled device (CCD) camera for eyemovement monitoring was firmly attached to the chair by a steel rod. During training and recording sessions, the monkey's eye position was monitored with 33 ms time resolution by an eye-monitoring system [30]. The juice reward was accessible to the monkey through a small spout controlled by an electromagnetic valve. A visual stimulus generator (ViSaGe MKII Visual Stimulus Generator, Cambridge Research Systems, UK) controlled the electromagnetic valve, the timing of visual stimuli onset. Figure 1A shows the stimulus set, consisting of 3 photos of snakes in openmouthed, threat display and 3 in closed-mouth, non-threat-displaying postures. All images are of live venomous vipers. We used color images because previous studies reported that color facilitates detection of snakes [13,31] and we wanted to simulate snakes as closely as they appear in nature. The stimuli were 256 digitized RGB color-scale images with their resolution of 2706270 pixels. Stimuli were presented on a black background of 0.7 cd/m 2 with their centers at the center of the display. The luminance of each stimulus was determined by measuring luminance of the circular area (radius, 6.35 cm) including each stimulus inside the circle by means of a luminance meter (BM-7A; Topcon, Tokyo). The luminance of these color stimuli was similar (6.005-6.445 cd/m 2 ) [luminous intensity (total luminance) ranged from38.432 to 41.248mcd]. These stimuli were displayed on a CRT monitor with a resolution of 6406480 pixels, and the size of the stimulus area was 5-765-7˚.

Visual stimuli
Our procedures follow those in Le et al. [24]. In that study, however, pulvinar neurons were not examined for postural differences.

Behavioral tasks
The monkeys were trained to perform a sequential delayed non-matching-tosample task (DNMS) that required the discrimination of the visual stimuli ( Figure 1A and B) [24]. As illustrated in Figure 1B, the task was initiated by a buzzer tone. Then, a fixation cross was appeared in the center of the display. When the monkeys fixated on the cross for 1.5 s within 0.5-1.0˚window, a sample stimulus was presented for 500 ms (sample phase). The control phase was defined as the 100-ms period before the sample phase. Then, after an interval of 1.5 s, the same stimulus appeared again for 500 ms between 1 and 4 times (selected randomly for each trial). Finally, a new stimulus was presented (target phase). When the target appeared, the monkey was required to press a button within 2 s in order to receive a juice reward (0.8 mL). When the monkey failed to respond correctly during the target phase or to press the button before the target phase, the trials were aborted and a 620-Hz buzzer tone was presented. The intertrial intervals (ITI) lasted15-25 s ( Figure 1B).

Training and surgery
The monkeys were trained to perform DNMS task for 3 h/day, 5 day/week. The monkeys reached a 96% correct-response rate after 3 months training. After completion of this training period, a head-restraining device (a U-shaped plate made of epoxy resin) was attached to the skull under aseptic conditions [32,33]. Subjects were initially anesthetized with a combination of medetomidine hydrochloride (0.5 mg/kg, i.m.) and ketamine hydrochloride (5 mg/kg, i.m.), and anesthesia was maintained by sodium pentobarbital (25 mg/kg, i.m.). For each monkey, the U-shaped plate was anchored with dental acrylic to titanium bolts that were inserted into the skull. We also implanted a reference pin, the location of which was based on the zero coordinates defined in the stereotaxic atlas of the brain of M. fuscata individuals [34]. During surgery, heart and respiratory functions and rectal temperature were monitored (LifeScope 14; Nihon Kohden Corporation, Tokyo, Japan). A blanket heater was used to keep body temperature at 36¡0.5˚C. Antibiotics were administered topically and systemically for 1 week after the surgery in order to prevent infection. Two weeks after surgery, each monkey was retrained while the head was painlessly fixed to the stereotaxic apparatus with the head-restraining device. The performance criterion (.90%) was again attained within 2 weeks.

Stereotaxic localization of the pulvinar for recording
Before recording from the pulvinar in each hemisphere, a tungsten marker (diameter: 500 mm) was inserted near the target area under anesthesia, and threedimensional magnetic resonance imaging (3-D MRI) scans of the monkey head were performed. The 3-D pictures of the monkey brain with the marker were reconstructed by computer rendering. Three-dimensional stereotaxic coordinates of the target area were determined in reference to the marker in the 3-D reconstructed brain [35]. Since the recording from the two monkeys is in progress, the two monkeys are alive in the present time, and pulvinar neurons were stereotaxically plotted on the 3-D reconstructed brain [24].

Electrophysiological procedures and data acquisition
After the monkeys relearned the DNMS task at a rate greater than 85% correct, we commenced daily recording of neuronal activity during the DNMS task. Neuronal activity was recorded from each hemisphere in both subjects. A glass-insulated tungsten microelectrode (0.8-1.5 MV at 1 kHz) was stereotaxically inserted into the pulvinar vertically to the orbitomeatal plane in a stepwise fashion by a pulse motor-driven manipulator (SM-21; Narishige Scientific Instrument Lab, Tokyo, Japan). Only neuronal activities with a signal-to-noise ratio greater than 3:1 were recorded. The analog signals of the neuronal activities, the triggers for visual stimuli, juice rewards, button pressing, and the X-Y coordinates of eye position were digitized at a 40-kHz sampling rate and stored in a computer through a multichannel acquisition processor (MAP; Plexon Inc., Dallas, TX, USA) system. The digitized neuronal activities were isolated into single units by their waveform components using the Offline Sorter program (Plexon Inc.). Superimposed waveforms of the isolated units were drawn in order to assess the variability throughout the recording sessions and then transferred to the NeuroExplorer program (Nex Technologies, Littleton, MA, USA) for further analysis.

Analysis of basic characteristics of pulvinar neurons
Spike sorting was performed with the off-line sorter program for cluster analysis (Off-line sorter, Plexon Inc.). Each cluster was checked manually in order to ensure that the cluster boundaries were well separated and that the waveform shapes were consistent with the action potentials. For each isolated cluster, an autocorrelogram was constructed, and only units with refractory periods greater than 1.2 ms were used for further analyses. Finally, superimposed waveforms of the isolated units were drawn in order to check the consistency of the waveforms. In addition, all pulvinar neurons were analyzed by autocorrelograms. The autocorrelograms indicated that the refractory periods of the all pulvinar neurons were greater than 2 ms throughout the recording sessions, which indicates that the isolated spikes were recorded from single neurons.
We analyzed single neuronal activity during the following 2 periods: 100 ms before (pre) and 500 ms after (post) the onset of stimulus presentation in the sample phase. The baseline firing-rate was defined as the mean firing rate during the 100-ms pre period. Significant excitatory or inhibitory responses to each stimulus were defined by a Wilcoxon signed-rank (WSR) test (p,0.05 for statistical significance) of the neuronal activity between the 100-ms pre and the 500-ms post periods. In order to investigate the temporal changes in the neuronal responses, the 500-ms post period was further divided into ten 50-ms epochs. The mean neuronal firing rate was calculated for each of these epochs. The response magnitude was defined as follows: the mean firing rate in each epoch minus the mean firing rate during the 100-ms pre period. Each neuron was categorized based on a t-test (P,0.05), in which response magnitudes to all 3 snakes in threat display were compared with those to all 3 snakes in non-threat-displaying postures. For this analysis, two peri-event histograms for the two categories of snakes were constructed using the entire set of data for all trials and all stimuli. ''Threat'' neurons were defined as such if the response magnitudes to the snakes in threat display were larger than those to the snakes in non-threat-displaying postures (P,0.05). ''Non-threat'' neurons were defined as such if the response magnitudes to the snakes in non-threat-displaying postures were larger than those to the snakes in threat display (P,0.05). Equal neurons were defined as such if there was no significant difference in response magnitudes between the categories of snakes (P.0.05). Furthermore, in each neuron, mean response magnitudes to the snakes in threat display and snakes in non-threat-displaying postures were computed. Then, grand averaged response magnitudes over all responsive neurons to snakes in threat display and snakes in non-threat-displaying postures were compared by paired t-tests (p,0.05).
In addition, we analyzed the response latency to each visual stimulus. For each neuron, 1 peri-event histogram was constructed with the entire set of data for all trials and all stimuli. Neuronal response latency was defined as the interval from the onset of stimulus presentation to the time at which the neuronal firing rate exceeded the mean ¡2 SD of the baseline firing-rate. Averaged response latencies over all responsive neurons to the snakes in threat display and snakes in nonthreat-displaying postures were compared by paired t-tests (p,0.05). All data were expressed as mean ¡ SEM.

Multidimensional Scaling analysis (MDS)
Multidimensional scaling (MDS) is a method that is used to simplify the analysis of relationships that exist within a complex array of data. MDS constructs a geometric representation of the data in order to show the degree of the relationship between stimuli that are represented by the data matrix (see Young and Hamer [36] for more details). MDS has been used to examine stimulus relationships with data matrices representing neural activity in response to the particular stimulus array (i.e., snakes, monkey and human faces, monkey hands, eye-and face-like patterns, and simple geometrical figures) [24][25][26]. In the present study, the 6 visual stimuli were used to elicit neuronal activity in the pulvinar.
Data matrices of neural activity in a 7866 array derived from the 82 visually responsive neurons were generated. Euclidean distances as dissimilarity between all possible pairs of 2 visual stimuli were calculated by using the visual responses of the 82 pulvinar neurons. Then, the MDS program (PROXSCAL procedure, SPSS statistical package, version 16) positioned the visual stimuli in the 2dimensional space with the distances between the stimuli representing the original relationships (i.e., Euclidean distances in the present study) [37,38]. Finally, the clusters of the visual stimuli were evaluated by discriminant analysis.

Characteristic of pulvinar neuronal responses to snakes
Of 821 neurons recorded, 115 neurons responded to the visual stimuli. Of these neurons, 78 neurons were tested with all stimuli in this experiment. From this 78neuron subset, 45 neurons responded more strongly to snakes in threat display (threat neurons) (t-test, P,0.05), 24 neurons responded more strongly to snakes in non-threat-displaying postures (non-threat neurons) (t-test, P,0.05), and 9 neurons showed no difference between these two kinds of the stimuli (equal neurons) (t-test, P.0.05). Statistical analysis indicated that there was a significant difference in the ratios of these 3 types of neurons [x 2 -test, x 2 (2)525.0, P53.45610 26 ]. Post-hoc tests indicated that the ratio of the ''threat'' neurons was significantly greater than that of the ''non-threat'' neurons (Ryan's method with adjusted significance level, P50.016). Furthermore, mean response magnitudes were significantly greater to snakes in threat display than to snakes in non-threat-displaying postures (paired t-test, t(77)53.056, P50.003) ( Fig. 2A). There was no significant difference in response latencies to the snakes between the threat displays and non-threat-displaying postures (55.3¡4.7 and 56.2¡4.7 ms, respectively, paired t-test, t(51)50.424, P50.673) (Fig. 2B).

Multi-dimensional scaling analysis
The data sets of response magnitudes of the 78 visually responsive pulvinar neurons in epochs 1 (0-50 ms) and 2 (50-100 ms) after stimulus onset were subjected to multidimensional scaling (MDS) analysis (Fig. 3). After measurement of R 2 and stress value for up to four dimensions, two-dimensional space showed the best results. In the two-dimensional spaces, R 2 values of epochs 1 and 2 were 0.94098 and 0.98019, respectively. In both epochs, two clusters, one for snakes in threat displays and another for snakes in non-threat-displaying postures, were recognized. Discriminant analyses showed that correct percent of discrimination was 100% in both epochs (p50.01 and p50.013, respectively).

Locations of pulvinar neurons
The pulvinar neurons that responded to the visual stimuli were located at the medial and dorsolateral parts of the pulvinar, consistent with our earlier study [24].

Discussion
We found here that neurons in the medial and dorsolateral pulvinar responded more strongly to snakes with open-mouthed threat displays compared with snakes with non-threat-displaying postures. In addition, the MDS results indicated that threat-displaying snakes were separated from non-threat-displaying snakes as early as epoch 1. Snakes threatening to strike are more dangerous than those in other postures [39,40], and monkeys apparently perceive this because they react behaviorally most strongly to snakes poised to strike, less to coiled snakes, and least to sinusoidal snakes [28]. In a previous study, we found that pulvinar neurons responded more strongly and more quickly to snakes compared with faces and hands of monkeys and simple geometrical patterns [24]. Our present results, together with previous research, suggest that the pulvinar plays an important role not only in detecting snakes but also in assessing the degree of threat posed by them. There is an urgency from snakes preparing to strike that requires immediate and focused attention if one is to avoid being bitten. An important function of the pulvinar is in filtering out irrelevant visual stimuli [41]. The greater response magnitudes in pulvinar neurons that we found to snakes poised to strike may assist in focusing the primate's visual attention on the snake.
Response latencies to snakes in general are shorter compared with other stimuli [24,25,42]. Nevertheless, here we found no significant differences in response latencies between snakes with and without threat displays. In nature, snakes often rely on ambush to kill their prey. By definition, ambushing requires predators to remain undetected until they strike. Many snakes have evolved coloration and patterns that help to camouflage them, and their narrow, limbless bodies allow them to blend among the background vegetation, reducing their detectability and making it challenging even for primates to see them [4,43]. If ambush predators are detected and monitored, they lose the element of surprise and are much less dangerous. While it is not necessary to detect snakes from far away, it would be beneficial for their primate prey to detect them before they prepare to strike. There was no significant difference between response latency to threatening snakes and snakes in non-threat-displaying postures (paired t-test, t(51)50.424, P50.673). In contrast, mean response magnitudes to snakes in threat display were significantly larger than to non-threat-displaying snakes. ** significant difference (paired t-test, t(77)53.056, P50.003). Columns and error bars indicate means with SEM. Indeed, as snakes can strike quickly, the ability to detect them within striking range regardless of their posture may be crucial for avoiding potentially deadly snakebites. It should be noted, however, that the snake images were presented in the central visual field, where differences in behavioral response latencies among stimuli are less than those in the peripheral visual field in humans [44]. Further studies are required to investigate neuronal responses to snake images presented in the peripheral visual fields.
In summary, this study contributes new neurophysiological evidence that further supports that the pulvinar in primates is highly responsive to snake visual stimuli [24]; population activity of neurons in the medial and dorsolateral pulvinar of Japanese macaques differentiates between snakes presenting a greater threat from those presenting a lesser threat as early as 50 ms after stimulus onset. This fast visual information processing suggests that snake images are processed in a bottom-up visual pathway to the pulvinar. The ability to quickly detect snakes visually and selectively focus on them while also quickly cueing in on their level of threat from their posture would appear to have clear a evolutionary benefit. Our results are thus consistent with the Snake Detection Theory, which argues that snakes provided a novel selective pressure that contributed importantly to the origin of primates and the evolution of the their visual system [3,4].


text:
SOX2 and cancer: current research and its implications in the clinic

SOX2 is a gene that encodes for a transcription factor belonging to the SOX gene family and contains a high-mobility group (HMG) domain, which permits highly specific DNA binding. Consequently, SOX2 functions as an activator or suppressor of gene transcription. SOX2 has been described as an essential embryonic stem cell gene and moreover, a necessary factor for induced cellular reprogramming. SOX2 research has only recently switched focus from embryogenesis and development to SOX2’s function in disease. Particularly, the role of SOX2 in cancer pathogenesis has become of interest in the field. To date, studies have shown SOX2 to be amplified in various cancer types and affect cancer cell physiology via involvement in complicated cell signaling and protein-protein interactions. Recent reviews in this field have highlighted SOX2 in mammalian physiology, development and pathology. In this review, we comprehensively compile what is known to date about SOX2’s involvement in cancer biology, focusing on the most recent findings in the fields of cellular signaling and cancer stem cells. Lastly, we underscore the role of SOX2 in the clinic and highlight new findings, which may provide novel clinical applications for SOX2 as a prognostic marker, indicator of metastasis, biomarker or potential therapeutic target in some cancer types.

Introduction
The SOX family is a group of related transcription factors that have demonstrated their importance in developmental and stem cell biology. In 1990, pioneering research discovered the mammalian testis-determining factor and the gene was termed Sry due to its corresponding location in the sex-determining region on the Y-chromosome [1,2]. Sry contains a distinctive high-mobility group (HMG) domain, which permits precise DNA recognition and binding. Proteins that contain the HMG domain with amino acid similarity of 50% or higher to the HMG domain of Sry are termed SOX (abbreviation for Sry-related HMG box) proteins [3][4][5]. Known functions of these proteins range from regulation of embryonic development and stem cell maintenance to homeostasis in adult tissues [6].
In 1994, the SOX2 gene, one of the SOX family members, was discovered and characterized in humans [7].
The SOX2 gene is located on chromosome 3q26.3-q27, belongs to the SOXB1 group and encodes for a protein consisting of 317 amino acids ( Figure 1A) [7,8]. SOX2 is comprised of three main domains: N-terminal, HMG and transactivation domain ( Figure 1B). SOX2 research thus far has heavily emphasized its crucial role in stem cell maintenance, lineage fate determinant and a necessary factor to reprogram somatic cells back towards pluripotency [5,9,10]. In disease, SOX2 alterations have been associated with developmental maladies, such as anophthalmia-esophageal-genital (AEG) syndrome, which occurs when there is a heterozygous mutation of SOX2 that leads to abnormal development of ectodermal and endodermal tissues [11]. Aside from developmental diseases, accruing research has strongly associated SOX2 with cancer.
Here, we consolidate SOX2's role in cancer and provide a comprehensive overview of the field, focusing on the latest research that has implicated SOX2 in cancer biology and in the clinic. SOX2 has been shown to be associated with numerous cancer types, even described in some cases as an oncogene, and controls cancer cell physiology via promoting oncogenic signaling and maintaining cancer stem cells. Lastly, we investigate recent work that has highlighted the role of SOX2 in the clinic, particularly its influence on prognosis, therapy resistance and potential therapeutic interventions.

SOX2 and cancer biology: current research SOX2 amplification in cancer
Tumor development occurs when a cell accumulates genetic alterations that modify normal cell cycle progression. There are several means of genetic aberrations including gene deletions or gene amplification. Gene amplification is defined as a copy number increase of a particular chromosomal region. SOX2 amplification is due to multiplication of the 3q26.3 gene locus [12,13]. SOX2 amplification has previously been found in several cancer types including glioblastoma, small-cell lung cancer (SCLC) and many forms of squamous cell carcinoma (SCC) [12,[14][15][16][17][18][19][20]. A summary of SOX2 amplification in various cancer types with corresponding references can be found in Table 1.
The latest SOX2 studies have focused on the coamplification of SOX2 with other critical genes. Justilien and colleagues revealed the co-amplification of two oncogenes, PRKCI and SOX2, is responsible for the cancer stem cell phenotype seen in lung squamous cell carcinoma (LSCC) [61]. Moreover, another study performed FISH analysis in 447 resected non-small cell lung cancer (NSCLC) tissue samples and SOX2 amplification was associated with increased gene copy number of FGFR1 and PI3KCA genes [62].

SOX2's involvement in cancer cell physiology varies between cancer types
As described by Hanahan and Weinberg, cancer is a disease characterized by determined hallmarks some of which are: sustained proliferative signaling, activation of invasion and metastasis, and evasion of cell death [73]. Studies have strongly associated SOX2 to these respective cancer hallmarks and thus far SOX2 has been shown to promote cellular proliferation (breast, prostate, pancreatic and cervical cancers) [21,28,57,58], evade apoptotic signals (prostate, gastric cancer and NSCLC) [37,58,63] and promote invasion, migration and metastasis (melanoma, colorectal, glioma, gastric, ovarian There is large homology between the SOXB1 group and they all contain three major domains: N-terminal, HMG and C-terminal domain. (B) SOX2 protein domains play several functional roles. The HMG domain of SOX2 remains fairly conserved between homo sapiens, Mus musculus and Danio rerio (Swiss-Prot: P48431, P48432, Q6P0E1). The HMG domain also serves as potential binding sites for protein partners. Moreover, nuclear import signals (NIS) and nuclear export signals (NES) bind to the HMG domain regulating SOX2 itself. Lastly the transactivation domain functions as the region responsible for promoter binding, which in turn leads to activation or repression of target genes.
cancer and hepatocellular carcinoma) [15,29,47,49,55]. We summarized SOX2 amplification and resulting alterations in cellular functions in all cancer types in Table 1 and showed examples of SOX2's role in oncogenic signaling in Figure 2. Below we highlight a few functional examples of SOX2 in cancer before we review the latest SOX2 research in different aspects of cancer physiology including: cellular proliferation, apoptosis and invasion/migration/ metastasis. For a complementary and closer examination into SOX2 and oncogenic signaling, protein-protein interactions and miRNAs see review by Liu et al. [74].
Cellular proliferation is tightly regulated by SOX2 in many cancer types. SOX2 knockdown in pancreatic cancer cells resulted in cell growth inhibition through cell cycle arrest, not apoptosis, via the transcriptional induction of p21 Cip1 and p27 Kip1 [57]. When SOX2 was overexpressed, cell proliferation was promoted through cyclinD3 (CCND3) transcriptional induction and allowed further S-phase entry ( Figure 2B) [57]. Recently, Hütz and colleagues confirmed this in gastric cancer [37]. SOX2 was functionally inhibited via cellular transfection with a tetracycline-inducible C-terminally truncated version of SOX2, termed dnSOX2. Despite lacking the transactivation domain, dnSOX2 could bind SOX2 recognition sites on DNA and compete with wild-type SOX2. This inhibition led to the decrease in cellular proliferation in AZ-521 cells and further analysis using a RNA gene expression microarray, revealed an upregulation of p21 and downregulation of Δp63 (splice variant of p63) [37]. Additionally, Fang and colleagues found in LSCC, SOX2-silencing inhibited cellular proliferation via the upregulation of BMP4 [64]. After performing chromatin SOX2 has been shown to be amplified and functionally relevant in various cancer types. SOX2 in cancer functions through multiple mechanisms that vary depending on the cancer type. However, in most cases, SOX2 has been shown to increase cell proliferation, invasion, migration, metastasis and self-renewal of CSCs. In addition, some of these phenotypes have been linked to particular oncogenic pathways, including WNT/β-CATENIN, EGFR, mTOR and HH signaling. ↑ = Promotes/Improves. ↓ = Suppresses/Inhibits. ↑↓ = Conflicting research. Pancreatic [26] Pancreatic [26] Pancreatic [26] Breast [61] LSCC [21] Invasion/ Migration immunoprecipitation and luciferase experiments, SOX2 was found to transcriptionally repress the BMP4 promoter. The authors therefore suggest that BMP4 is playing a tumor suppressor role in LSCC, while SOX2 repression of BMP4 transcription causes cell growth [64]. It's important to note that the involvement of SOX2 in cell proliferation has been controversially discussed in colorectal and gastric cancer [30,31,37,38]. The contradictory effect of SOX2 in cell proliferation suggests that SOX2 plays a differential role depending on the type of cancer ( Figure 2B). SOX2 also plays an important role in evading apoptotic signals. In prostate cancer, in vitro and in vivo xenograft experiments using DU145 SOX2-overexpressing cells in NOD/SCID mice revealed that SOX2 caused an increase in apoptotic resistance by decreasing store-operated Ca 2+ entry via repressing ORAI1 expression ( Figure 2) [58]. Equivalently, upon silencing of SOX2 in NSCLC cell lines, apoptosis was induced [63]. Hütz and colleagues, in addition to proliferation analysis, investigated apoptosis using, caspase 3/7 assays performed in AZ-521 gastric cancer cells [37]. After 48 hours of SOX2 inhibition, nearly 60% of cells were apoptotic compared to only 20 -40% of the control cells [37]. These studies prove SOX2's involvement in apoptosis inhibition and therefore in direct promotion of uncontrolled cell growth.

SOX2
Finally, research has indicated that SOX2 is a novel regulator of cell invasion, migration and metastasis. For example in melanoma, SOX2 knockdown in A2058 cells resulted in a 4.5-fold decrease in invasion in vitro and adopted this phenotype via the upregulation of matrix metalloproteinase (MMP)-3 [49]. Likewise in colorectal cells, SOX2 was involved in cellular migration and invasion in vitro, but mediated these effects through MMP-2 [29]. This invasive phenotype was also confirmed in malignant glioma, since siRNA-mediated downregulation of SOX2 resulted in a significant decrease in migration and invasion capabilities [15]. Moreover SOX2 overexpression in the SOX2-negative glioma cell line U-87 resulted in a significant increase in the number of migratory and invasive cells [15]. Numerous gain and loss of function studies in several cancer types (gastric cancer, ovarian cancer and hepatocellular carcinoma) reinforced the link between SOX2 and cellular invasion and migration [15,37,47,55]. Recently, Yang and colleagues showed SOX2's involvement in promoting invasion and migration in laryngeal cancer cells through the induction of MMP-2 and the PI3K/AKT/mTOR pathway (Figure 2A) [48].

SOX2 and cancer stem cells: current research
Many tumors are derived from a single cell that has undergone malignant transformation through the acquisition of genomic aberrations, e.g. gene amplification, mutations or other mechanisms [75]. Clonal expansion of cells with tumorigenic properties is the next step towards tumor initiation. These selected cells have the ability to evade normal cell cycle checkpoints, rapidly proliferate and invade tissues [73,75]. The orchestration of tumor initiation and maintenance has been shown in some cancers to be driven by cancer stem cells (CSCs), also termed tumor-initiating cells or cancer stem-like cells. These CSCs may acquire tumor-initiating and selfrenewal properties through similar molecular mechanisms governing cellular reprogramming [76]. Evidence has linked induced cellular reprogramming to cancer and led to the assumption that CSCs may arise via a reprogramming-related mechanism [77][78][79]. The reactivation of stem cell-associated markers or pluripotency factors may cause dedifferentiation and a more stem cell-like state [76]. Sussman and colleagues discovered that the ubiquitin-specific protease 22 (USP22) is responsible for controlling the cellular transition from stemness towards differentiation [80]. Moreover they found USP22 represses the SOX2 promoter in order to control the embryonic stem cell transition from self-renewal to differentiation [80] Therefore, not only is SOX2 an essential stem cell marker but its suppression is mandatory for cellular differentiation. For these reasons, SOX2 has been heavily investigated in CSCs in several cancer types.

SOX2 regulates self-renewal and maintenance in cancer stem cell populations
SOX2 has shown to increase CSC markers in ovarian, pancreatic, lung cancer, but research also has proven its function in self-renewal [57,81,82]. Self-renewal capacity of a CSC is critical and enables the maintenance of the CSC subpopulation within a tumor and SOX2 has shown to mediate this in breast, gastric, ovarian, prostate cancer, glioma, osteosarcoma, lung adenocarcinoma (See figure on previous page.) Figure 2 Influence of SOX2 on oncogenic-related processes and transcription. (A) SOX2 is an important regulator of cellular processes related to cancer. Some of these processes include but aren't limited to WNT/β-CATENIN signaling, EMT and JAK/STAT3 signaling. In most cases, SOX2 functions downstream in the nucleus. SOX2's activity leads to further downstream effects and finally alters cellular phenotypes such as cellular survival, invasion and metastasis. (B) SOX2 is typically regulating processes downstream on a transcriptional level. There are several examples of SOX2 influencing cancer phenotypes by repressing or activating particular target genes including EMT promotion via binding to the promoter regions of SNAIL, SLUG and TWIST. Therefore, SOX2 functions in cancer as a key transcription factor. and NSCLC [15,42,54,59,65,66,77,82,83]. Studies in gastric cancer using siRNA-mediated SOX2 knockdown, found reduced spheroid colony formation and increased apoptosis within sphere cells, highlighting the importance of SOX2 in self-renewal capacity [83]. In prostate cancer stem cells, the activation of EGFR signaling increased SOX2 expression and the self-renewal capacity [59]. Singh and colleagues showed similar results in NSCLC, when siRNA-mediated SOX2 knockdown led to a 2.5-fold reduction in sphere formation [65]. Moreover, EGFR/Src/ Akt signaling influenced SOX2 protein expression since during EGFR or SRC inhibition using gefitinib or BIBW, respectively, levels of SOX2 were considerably decreased [65]. Taken together, SOX2 mediates self-renewal of CSCs through EGFR signaling in at least two cancer types and is a major mediator of self-renewal in several cancers through mechanisms that remain unclear.
Recent CSC studies have concentrated on SOX2 and its mechanisms in cancer stem cell maintenance and regulation. Santini and colleagues investigated SOX2 in melanoma initiating cells and Hedgehog-GLI (HH-GLI) signaling [50]. They functionally showed that the ectopic expression of SOX2 in vitro caused enhanced self-renewal capacity in melanoma cells. Moreover, GLI1 and GLI2 downstream transcription factors of HH-GLI Signaling were able to bind to the proximal promoter of SOX2 in primary melanoma cells in chromatin immunoprecipitation (ChIP) studies and therefore SOX2 is regulated by HH signaling [50]. To a similar extent, Justilien and colleagues heavily investigated Hedgehog (Hh) acyltransferase (HHAT) in LSCC and found that not only are PRKCI and SOX2 coamplified and cooperate in LSCC but also SOX2 becomes phosphorylated by Protein Kinase Cι (PKCι) [61]. Next, phosphorylated SOX2 is recruited and required for HHAT expression and therefore maintenance of the stem-cell phenotype. The authors provide evidence that the coamplifcation of both oncogenes is required to activate the PKCi-SOX2-HHAT signaling axis which impels the stem cell phenotype. Further work is being done on establishing PKCι inhibitors for LSCC treatment [61].
Lastly, a recent publication by Favaro and colleagues proved that SOX2 is required for in vitro CSC maintenance in a high-grade oligodendroglioma mouse model [43]. Oligodenrogliomas were generated in mice via the transduction of PDGF-B-IRES-GFP-encoding retrovirus within the brain at embryonic day 14.5. Additionally these embryos carried a homozygous SOX2 flox mutation, which allowed authors to excise SOX2 using lentiviral Cre recombinase virus. Wild-type oligodendroglioma cells from mentioned mouse model were transplanted into the brain of C57/Bl6 mice, which generated lethal tumors. However, when SOX2-deletion cells were transplanted into C57/Bl6 mice they remained tumor free [43]. This elegant study proved the obligatory function of SOX2 in oligodendroglioma tumor initiation. The requirement of SOX2 in oligodendroglioma suggested possible therapeutic intervention.
Correlations between SOX2 and clinical outcome: current research SOX2 has proven its functional role in various aspects of cancer biology. Research on SOX2 has also investigated its importance in the clinic in respect to disease prognosis, relapse, therapy resistance, comprehensive summary in Table 2. The ability to improve reliability of diagnosis or prognosis of a cancer patient can have immense impact on survival and better understanding of the disease. For example, 162 esophageal squamous cancer patients were analyzed for SOX2 and OCT3/4 expression and high expression of both markers was associated with higher histological grade or TNM stage (p < 0.001 for both factors), demonstrating their link to dedifferentiation in these tumors (Table 2) [84]. Furthermore, a significant correlation between high SOX2 levels and decreasing patient survival was shown (p < 0.001) [84]. Recently, Forghanifard and colleagues revealed that stemness state regulators SALL4 and SOX2 are overexpressed in 64 esophageal cancer samples and cooverexpression correlated with depth of tumor invasion and metastasis [85]. Again, contrasting results for SOX2's role in the clinic were highlighted in lung cancer (including NSCLC and SCLC), where SOX2 was correlated to improved survival and better patient outcome [62,67,68,[86][87][88]. These opposing outcomes in the clinic further underscore the differing role of SOX2 in varying cancer types.

SOX2's influence on therapy resistance
Drug resistance has been associated with expression of various pluripotency markers, including NANOG, OCT4 and SOX2, since these genes typically lead to a decrease in differentiation status [68]. In breast cancer, silencing SOX2 not only reduced the size of the CSC population but also restored tamoxifen sensitivity, suggesting tamoxifen resistance is primarily driven by SOX2 in breast CSCs [89]. Recently, Dogan and colleagues investigated SOX2 and EGFR inhibitors in lung adenocarcinoma cell lines [68]. When a SOX2 knockdown using shRNA was performed in HCC827 cells, decreased proliferation was observed along with increased sensitivity to erlotinib. Furthermore, upon the treatment with PI3K/AKT inhibitors, SOX2 expression decreased [68]. Therefore, targeting SOX2 in EGFR-mutant tumors may be therapeutically beneficial; however more direct targeting strategies need to be further developed.

SOX2 and therapy options
Improving cancer therapy options in the clinic remains a priority. SOX2 has shown its potential to become a useful biomarker in the clinic for some cancer types, for both staging tumors and identification of the CSC subpopulations (Table 2). Utilizing SOX2 for cancer therapy may open a window to new therapeutic opportunities. SOX2 does not lend itself for direct therapeutic intervention due to its importance in transcriptional cellular function and targeting SOX2 may have dozens of unwanted complications. However, targeting signals upstream or downstream of SOX2 may prove beneficial in cancer therapy. For example, as mentioned above in NSCLC and prostate CSCs, SOX2 relies heavily on EGFR signaling for mediating self-renewal in CSCs. Currently, anticancer drugs are on the market targeting EGFR, such as gefitinib and erlotinib, and may be useful in inhibiting SOX2's downstream selfrenewal effects, however resistance to these therapies is nearly inevitable and needs to be overcome. Therefore, further targeting SOX2 in EGFR-mutant cancer with PI3K/AKT inhibitors, as shown above in lung adenocarcinoma cell lines, may yield better results [68].
Recently published studies have attempted to tackle SOX2 therapy and its implications. Favaro and colleagues, who performed the oligodenroglioma studies in mice, further examined SOX2 peptides for immunotherapy treatment in mice [43]. The C57BL/6 N mice were injected with wild-type oligodendroglioma cells from established Predicts poor prognosis for preoperative CRT patients Sinonasal SOX2 amplification identifies carcinomas more likely to relapse [71] The role of SOX2 in the clinic has been studied and expression has been correlated to patient survival, prognosis and therapy. SOX2 has been shown to play different roles depending on cancer type and can predict both better and worse outcomes for patients. Moreover, SOX2 has proven its use as a prognostic marker in melanoma, colorectal, gastric and lung cancer.
mouse model and upon vaccination with SOX2 peptides, significant delay in tumor growth was observed [43]. Similarly, Polakova and colleagues developed an experimental DNA vaccine against SOX2 [92]. In this study, C57BL/6 and BALB/c mice were immunized with DNA vaccine and found a significant SOX2-specific activation of lymphocytes. However, when the antitumor effects were examined using TC-1/B7 (derived from lung cancer cell line TC-1) cells the DNA vaccination did not prevent tumor development even though it was able to significantly reduce tumor growth [92].
Conclusion: SOX2 in the future SOX2 has proven not only to be an essential embryonic, reprogramming and development-associated gene but has begun to leave its footprint in the field of oncology. SOX2 is intricately involved in many cancer-associated processes such as cell proliferation, evading cellular apoptosis and metastasis via interactions with EGFR signaling and several other oncogenic pathways and processes. Moreover, current and ongoing SOX2 CSC research has emphasized the importance of investigating early developmental genes, since they may be responsible for selfrenewal of CSCs. Lastly, in clinical settings, SOX2 has shown a heavy influence on patient survival and prognosis. In summary, SOX2 function in cancer has been accentuated in numerous cancer types in and out of the clinic and investigating SOX2's oncogenic course is important for future prognosis, survival of cancer patients and possible therapeutic interventions.

Competing interests
The authors declare that they have no commercial or other competing interests to disclose.

Authors' contributions
The author KW performed the research, writing, and revisions of the manuscript. Additionally, author KW created the figures and tables. The authors KW and JU contributed equally to the revisions of the manuscript and figures. Both authors read and approved the final manuscript.