OY-TES-1 may regulate the malignant behavior of liver cancer via NANOG, CD9, CCND2 and CDCA3: A bioinformatic analysis combine with RNAi and oligonucleotide microarray
- Authors:
- Published online on: February 10, 2015 https://doi.org/10.3892/or.2015.3792
- Pages: 1965-1975
Abstract
Introduction
Surgical resection is the primary mode of choice in the treatment of liver cancer, while the 5-year recurrence rate after resection is as high as 35.4–43.5% (1). The poor prognosis associated with liver cancer has prompted the identification and development of new diagnostic markers and therapeutic strategies. Immunotherapy is a potentially attractive option for patients with liver cancer. Cancer/testis (CT) antigens are potential immunotherapeutic targets in many types of cancers including liver cancer due to their expression pattern, which is restrictively expressed in the testes, yet aberrantly expressed by a variety of malignancies (2–8). OY-TES-1 has been defined as the 23rd member of the CT antigen family, called CT23 (9–12). OY-TES-1 was originally identified to be the human homologue of pro-acrosin binding protein (ACRBP), a tyrosine phosphorylated protein related to capacitation, the sp32 precursor in mouse (13). Spontaneous humoral response against OY-TES-1 has been detected in patients with different tumors including liver cancer (9). An HLA-A24-binding OY-TES-1 peptide recognized by CD8 T cells was identified, and T-cell cytotoxicity was observed against an OY-TES-1 mRNA-expressing lung tumor cell line in vitro (14). The above studies imply that OY-TES-1 is an attractive target for antigen-specific immunotherapy in cancers due to its immunogenic traits in humans (9,14). In another study in ovarian cancer cells, a mitotic spindle protein NuMA was identified as an ACRBP-interacting protein (12). ACRBP depletion resulted in mitotic errors and reduced proliferative fitness that could be rescued by NuMA co-depletion. This indicates that ACRBP could normalize the perturbed mitotic infrastructure responsible for disease-promoting genetic variation. In our previous report, we demonstrated that OY-TES-1 was expressed in human mesenchymal stem cells (MSCs) at both the mRNA and protein levels, and downregulation of OY-TES-1 expression in these MSCs caused cell growth inhibition, cell cycle arrest, apoptosis induction and migration ability attenuation (15). However, whether OY-TES-1 is involved in the biological function of liver cancer remains undetermined. In the present study, we applied bioinformatic analysis combined with a molecular biology assay to investigate the biological function and protein interaction of OY-TES-1 in liver cancer. Our data indicated that OY-TES-1 regulates biological processes of liver cancer cells via NANOG, CD9, CCND2 and CDCA3.
Materials and methods
Motif and domain-domain interaction analysis
The motif analysis of OY-TES-1 protein was performed with SSDB Motif Search in Kyoto Encyclopedia of Genes and Genomes (KEGG) online database (http://www.kegg.jp/). The protein domain interactions were analyzed by DOMINE online database (16) (http://domine.utdallas.edu/cgi-bin/Domine) and the Pfam protein families database (17), respectively. KEGG is a database resource for understanding high-level functions and utilities of the biological system from molecular-level information, particularly large-scale molecular datasets generated by genome sequencing and other high-throughput experimental technologies. With KEGG motif search, a domain of unknown function with peptide fragment usually can be found (18). DOMINE is a database of known and predicted protein domain (domain-domain) interactions, which are predicted by 13 different computational approaches using Pfam domain definitions. DOMINE contains a total of 26,219 domain-domain interactions (among 5,410 domains) out of which 6,634 are inferred from PDB entries, of which 2,989 interactions are high-confidence predictions (HCPs) (16,17).
Co-expressing gene analysis in liver cancer through ONCOMINE
To identify significant OY-TES-1-co-expressing genes in liver cancer, we searched for all relevant, publically available microarray datasets in online cancer microarray gene expression database, ONCOMINE (https://www.ONCOMINE.org/resource/main.html) (19). ONCOMINE database is a bioinformatics initiative aimed at collecting, standardizing, analyzing and delivering cancer transcriptome data to the biomedical research community. The analysis has identified the genes, pathways and networks deregulated across 18,000 cancer gene expression microarrays, spanning the majority of cancer types and subtypes (19). As there are often many hundreds of tumor samples/microarrays within a single multi-array result from co-expressing genes can be analyzed. ONCOMINE database provides a potentially significant list of co-expressing genes, which is important to define pathways in which the gene of interest is involved (20).
Co-expressing gene annotation through gene ontology (GO) annotator
GO annotator uses text-mining methods to extract GO terms from scientific studies and provides this information along with a GO term from an uncurated annotation; thus, it provides not only facts but also their evidence (21). Based on the GO annotation, we searched each proliferation, migration, invasion or apoptosis GO term for the genes with high correlation and frequency to OY-TES-1 co-expression in the GO database.
Co-expressing gene literature co-occurrence through COREMINE and PubMed
The OY-TES-1-co-expressing genes with GO terms of cell proliferation, adhesion, migration and apoptosis in liver cancer were fed to a literature co-occurrence tool-COREMINE online tool (http://www.coremine.com/medical/#search) (22). COREMINE medical is a gene/protein database and web-based tool for literature mining. It develops automated extraction of experimental and theoretical knowledge of biomedicine from publicly available gene and text databases to create a gene-to-gene co-citation network for human genes in MEDLINE records (22). The systematic search of the literature was performed with PubMed for studies addressing association among liver cancer, OY-TES-1 and OY-TES-1 interacting proteins.
Oligonucleotide microarray analysis combined with RNAi
OY-T ES-1 was down regulated in the liver cancer cell line BEL-7404 using small interfering RNA (siRNA) with X-tremeGENE siRNA transfection reagent (Roche Diagnostics). OY-TES-1 siRNA and a scrambled siRNA were synthesized by Shanghai GenePharma Co., Ltd. The sequences of the siRNAs and experimental procedure were previously described by Cen et al (15). Total RNA extracted from non-siRNA-treated cells and siRNA-OY-TES-1-treated cells was used for genome-wide expression analysis with the Human Whole Genome 6×44K Microarray (Agilent Technologies, Inc., Santa Clara, CA, USA) according to the manufacturer’s protocol (23). Data quality check and analysis were conducted using SBC analysis system (Agilent Technologies). p-value was calculated when duplicates were used in the experiment, and differentially expressed genes were selected by p-value (<0.05) (24).
Generation of biological interaction network through GeneMANIA
Candidate genes selected from the oligonucleotide microarray assay above were fed into a curated protein interaction network system-GeneMANIA (http://www.genemania.org/), which is a fast web-based tool and database for predicting gene function based on multiple networks derived from different genomic or proteomic data/sources with great accuracy (25). With the GeneMANIA a gene/protein-gene/protein interaction network of OY-TES-1 was generated.
Results
Four motifs were identified in OY-TES-1
Following a search for ‘OY-TES-1’ in the KEGG online database, four motifs, Kazal-1 and −2, PBP-sp32 and TFIIF-α, were found in human OY-TES-1 on the dataset of hsa:84519 (Table I; Fig. 1). The Kazal motif contains two patterns, Kazal-1 and −2. The amino terminal segment of both Kazal motifs can bind to the active site of target proteases resulting in functional inhibition (Table I). The family of Kazal-1 inhibitor proteins inhibits serine peptidases of the S1 family, such as trypsin and elastase (26,27), while the family of Kazal-2 inhibitor proteins inhibits serine peptidases of MEROPS, such as I1, I2, I17 and I31. However, Kazal-like domains are also seen in the extracellular part of agrins, which are unknown to be protease inhibitor (28). TFIIF-α, a subunit of transcription initiation factor IIF, or RNA polymerase II-associating protein 74 (RAP74) is the large subunit of transcription factor IIF. By interacting with the proteins containing interacted motifs as summarized in Table I, TFIIF-α plays an essential role in accurate initiation and stimulates elongation by RNA polymerase II (29). PBP-sp32 is a sperm-specific domain involved in packaging acrosin zymogen into acrosomal matrix (30). In general, OY-TES-1 interacts with the proteins containing TFIIF-α, Kazal-1 and −2 motifs or the proteins containing the interacted motifs of these 3 motifs. Thus, through these interactions, OY-TES-1 may perform its functions in regulating the biological behavior of tumor cells.
 | Table IThe motifs of OY-TES-1 and NANOG, interacted motifs and motif-shared proteins according to database searcha. |
Sixty genes were found to co-express with OY-TES-1 in liver cancer
To investigate OY-TES-1-co-expressing genes in liver cancer, we queried the ONCOMINE database using a concept ‘co-expression genes with OY-TES-1 expression in liver cancer’. There was a list of 5,051 genes in 9 data-sets, namely Liver (Liao)-Cluster ID n9273 (17 genes); Multi-cancer (Beroukhim)-Cluster ID n9385 (85 genes), Cell Line (Rothenberg)-Cluster ID n9276 (207 genes), Cell Line (Wooster 2)-Cluster ID n9229 (209 genes), Cell Line (Barretina 2)-Cluster ID n9313 (229 genes), Liver cancer (Bittner Multi-cancer, 978 genes), Liver cancer (Wooster Cell Line 2, 1,875 genes), Liver cancer (Barretina Cell Line, 1,957 genes) and Liver cancer (Bittner Multi-cancer, 1,957 genes). As listed in Table II, 60 genes were co-expressed with OY-TES-1 at least in 5 of 9 datasets mentioned above, and the correlation between those genes and OY-TES-1 was >0.900.
Nine OY-TES-1 co-expressing genes may regulate biological processes
As the 60 genes identified above showed a correlation with OY-TES-1, we further predicted their function through GO annotator and COREMINE online tool search. As listed in Table III, we identified 9 genes: CD9 molecule (CD9), cyclin D2 (CCND2), CD27 molecule (CD27), cell division cycle-associated protein (CDCA3), inhibitor of growth family, member 4 (ING4), lymphotoxin-β receptor (LTBR), homeobox transcription factor Nanog (NANOG), nucleolar protein 2 homolog (NOP2) and tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A). These genes are involved in cell proliferation, adhesion, migration and/or apoptosis.
Eight OY-TES-1 co-expressing genes are co-occurring in liver cancer
According to the above search, 9 of the co-expressing OY-TES-1 genes are involved in the biological behavior of cells, but whether they are related to liver cancer remains unknown. Thus, these 9 genes and OY-TES-1 were further fed to COREMINE online tool search using ‘liver carcinoma’ as a key word. As shown in Fig. 2, co-occurrence with liver cancer was demonstrated for OY-TES-1 and 8 of the 9 genes except for CDCA3, and these 8 genes also co-occur with each other. Among those 8 genes, CD27, ING4, LTBR and TNFRSF1A are known to be involved in apoptosis; CD27 negatively regulates the apoptotic process (31–34), while ING4 (35–37), LTBR (38) and TNFRSF1A (39) positively regulate the apoptotic process. CD9 is also considered to regulate migration and adhesion of cells (40,41). In addition, CD9 and ING4 are thought to negatively regulate cell proliferation (35,44). The others, CCND2 (45–51), NANOG (52–54) and NOP2 (55,56), positively regulate cell proliferation. With regard to CDCA3, a G1 phase controlling gene which prevents G1 arrest, there is no current literature that shows that it is involved in liver cancer. However, considering that CDCA3 has a high expression frequency and a high co-expression correlation with OY-TES-1 in liver cancer datasets, further investigation of CDCA3 is needed. To date, there is no report of the involvement of OY-TES-1 in apoptosis, migration, adhesion and cell proliferation of liver cancer. We here demonstrated that OY-TES-1 is co-expressed with 9 genes (CD9, CCND2, ING4, CDCA3, NANOG, NOP2, CD27, LTBR and TNFRSF1A) with a high correlation and frequency, inferring that OY-TES-1 may be involved in the cell adhesion/migration regulated by CD9, cell proliferation mediated by CD9, CCND2, ING4, CDCA3, NANOG and NOP2, and apoptosis modulated by CD27, ING4, LTBR and TNFRSF1A in liver cancer, respectively.
Four candidate genes are significantly altered by OY-TES-1 downregulation
As the above results identified 9 OY-TES-1-co-expressing genes with functions of cell proliferation, adhesion, migration and/or apoptosis, we further screened an oligonucleotide microarray following OY-TES-1 down-regulation in a liver cancer cell line. It was found that a total of 8,870 genes were significantly altered (p<0.05) in the siRNA-OY-TES-1-treated cell as compared with the control. Notably, these 9 OY-TES-1 co-expressing genes (CD9, CCND2, CDCA3, NANOG, ING4, NOP2, CD27, LTBR and TNFRSF1A) revealed a differential expression profile. CD9, CCND2 and CDCA3 were upregulated, whereas NANOG was downregulated. Another 5 genes had no expression change (p>0.05, Table IV). Furthermore, after searching the motif of CD9, CCND2, CDCA3 and NANOG in SSDB, DOMINE and Pfam database, an interacted motif of Kazal-2 contained in OY-TES-1, homeobox, was found in human NANOG on the dataset of hsa:79,923 (Table I; Fig. 1). Therefore, NANOG may be considered as the most likely candidate protein interacting with OY-TES-1 in liver cancers.
| Table IVExpression profile of OY-TES-1 co-expressing candidate genes and their interacing genes by OY-TES-1 suppression in the cell line BEL-7404a. |
OY-TES-1 may be functionally related to NANOG, CD9, CCND2 and CDCA3 by various interactions
Due to the unclear functions of OY-TES-1 and its co-expressing proteins, OY-TES-1, NANOG, CDCA3, CD9 and CCND2 were fed into GeneMANIA to predict their functions and interactions. As shown in Fig. 3, OY-TES-1, NANOG, CD9, CCND2 and CDCA3 were co-expressed, co-localized, physically and genetically interacted, and/or shared protein domains and pathways with each other and a number of other proteins, such as CCND3, CDK4, CDK6, CD44, ITGA2, ITGA3, ITGB1, ESRRB, EGR1, PITX2, REST, CDKN2C and WEE1 (Table V). Therefore, it can be suggested that OY-TES-1, NANOG, CDCA3, CD9 and CCND2 may be functionally related. Although OY-TES-1 was considerably less interactive with other proteins involving in cell proliferation, adhesion, migration and apoptosis in comparing the results, it contains a Kazal-2 domain that could bind with the homeobox domain shared by NANOG and PITX2. Thus, we added interactions between OY-TES-1, NANOG and PITX2, and predicted these interactions with cell proliferation, adhesion, motility and apoptosis in liver cancer. Based on the annotated functions in accordance with the GeneMANIA network, OY-TES-1, NANOG, CD9, CCND2 and CDCA3, along with other proteins listed in Table V, may play important roles in the regulation of cell adhesion, the cell cycle, kinase activity, apoptosis (or anoikis) and DNA binding.
| Table VThe biologic process annotated functions of OY-TES 1-co-expressing proteins and their interacting proteins in the GeneMANIA network. |
Discussion
Functional prediction of genes/proteins based on bioinformatic analysis is a feasible and valuable technique for the mining of gene/protein functions, and many large-scale networks of protein interactions within the cell have made it possible to multi-dimensionally study the functions in the context of a network (57). Thus, mining and exploring potentially OY-TES-1-interacting genes via bioinformatic methods would be a first, necessary, feasible and reasonable way to reveal its function in liver cancer. Based on the motif, co-expression profile, GO and literature co-occurrence analysis, we found 60 genes to be co-expressing with OY-TES-1 in liver cancer, and 9 out of 60 of these genes are involved in cell proliferation, adhesion (migration) and/or apoptosis. OY-TES-1 and 8 out of 9 genes were found to co-occur in liver cancer, and these 8 genes co-occur with each other. Furthermore, with RNAi and oligonucleotide microarray analysis, we confirmed that, of these 9 genes, expression of CD9, CCND2 and CDCA3 was significantly increased, and NANOG was markedly decreased. The expression levels of the other 5 genes did not change when OY-TES-1 was suppressed in liver cancer cells (p>0.05, Table IV). GeneMANIA network analysis demonstrated that OY-TES-1, NANOG, CD9, CCND2 and CDCA3 were co-expressed, co-localized, physically and genetically interacted and/or shared protein domains and pathways with each other (Fig. 3). Annotated functions (Table V) suggested that OY-TES-1 may participate in tumor cell proliferation, migration, invasion and apoptosis through regulation of CCND2, CDCA3, CD9 and NANOG.
Both CCND2 and CDCA3 are G1 phase controlling genes. CCND2 overexpression is associated with the tumorigenesis and progression of various types of cancers including liver cancers by affecting the cell cycle, particularly in the G1 phase (G1 cell cycle transition) with G1 CCND2/cyclin-dependent kinase (CDK)4 (or 6) complexes (58–61). Exhibiting a difference with CCND2, CDCA3 can increase the capacity of proliferation by preventing G1 arrest via decreased expression of the CDK inhibitor (CDKI) (62,63). In the present study, downregulation of OY-TES-1 in BEL-7404 cells was accompanied by an increase in CCND2 and CDCA3 as well as their interacting genes CCND3 and CDK6 (p<0.05, Table IV, Fig. 3), which are able to accelerate cell proliferation by promoting G1/S transition, CDK activity regulation or cyclin/CDK complex formation (60,61,64). However, as a negative regulator of entry into mitosis (G2 to M transition) (65), WEE1 was significantly increased (p<0.05) (Table IV, Fig. 3); the other cell cycle involved genes CD4 and CDKN2C were not altered (data not shown). Therefore, it is reasonable to infer that downregulation of OY-TES-1 may accelerate the cell cycle and promote proliferation in liver cancer cells through increased expression of CCND2, CDCA3 and their interacing genes CCND3 and CDK6.
CD9 and NANOG are also thought to be associated with the malignant behavior of cells. The absence and low expression of CD9 in small cell lung cancer may contribute to the highly invasive and metastatic phenotype, while ectopic expression of CD9 reduced cell proliferation and motility, attenuated metastasis (66,67) and promoted apoptosis (68,69). Therefore, CD9 has been regarded as an important tumor progression suppressor (70). To date, there is paucity in the research of the correlation between CD9 and liver cancer. As regard to NANOG, it is one of the most important core markers of cancer stem cells (CSCs) due to its capacity to maintain pluripotency, regulate proliferation and prevent differentiation (71,72). NANOG-positive CSCs in liver cancer exhibit drug resistance and a high capacity for tumor invasion and metastasis (73,74). The same situation is present in other cancers. For example, upregulation of NANOG enhances malignant behaviors in esophageal cancer (52,75); adversely, its downregulation causes inhibitive effects on ovarian and gastric cancer (76). Here, we demonstrated that suppression of OY-TES-1 in a cancer cell line significantly increased expression of CD9 and its interacting genes (CD44, ITGA2, ITGB1 and ITGA5), which negatively regulate proliferation and migration in cancer cells (40–43). Meanwhile, we also found a decrease in NANOG and elevation in EGR1 which interacts with NANOG (Fig. 4; Table IV). EGR1 is thought to be a cancer suppressor (77). There was no change in the other genes listed in Table V, which are involved in cell differentiation and proliferation and are related with CD9 or NANOG. Notably, in the present study downregulation of OY-TES-1 in liver cancer cells caused two opposite effects, namely, promotion of cell proliferation with increase in CCND2 and CDCA3, and inhibition of cell proliferation with CD9 upregulation and NANOG downregulation. Therefore, it was speculated that OY-TES-1 may play multiple roles in liver cancer. Experiments should be conducted to elucidate the function of OY-TES-1 with CD9, NANOG, CCND2, CDCA3 and their interacted proteins in the future.
Collectively, as shown in Fig. 5, we first report that OY-TES-1 suppression results in significant expression changes of its co-expressing genes, CCND2, CDCA3, CD9 and NANOG. As it contains a Kazal-2-interacting motif, homeobox, NANOG may be considered to be the most likely candidate protein interacting with OY-TES-1 in liver cancer. Thus, the present study may set the stage for further investigation of the role of OY-TES-1 in liver cancer.
Acknowledgements
We thank Ms. Fang Chen, Ms. Chengxiao Chen from Guangxi Medical University for their excellent technical assistance. The present study was supported by the National Natural Science Foundation of China (nos. 81360371, 30760055 and 81360374), the Natural Science Foundation of Guangxi (nos. 2011GXNSFA018275 and 2014GXNSFAA118172), and the Innovative Project for Postgraduate of Guangxi Educational Bureau (nos. YCBZ2013017 and YCSZ2014103).
References
|
Mo QG, Liang AM, Yang NW, et al: Surgery-predominant comprehensive therapy for 134 patients with small hepatocellular carcinoma. Ai Zheng. 22:189–191. 2003.(In Chinese). PubMed/NCBI | |
|
Yoon H, Lee H, Kim HJ, et al: Tudor domain-containing protein 4 as a potential cancer/testis antigen in liver cancer. Tohoku J Exp Med. 224:41–46. 2011. View Article : Google Scholar : PubMed/NCBI | |
|
Song MH, Choi KU, Shin DH, et al: Identification of the cancer/testis antigens AKAP3 and CTp11 by SEREX in hepatocellular carcinoma. Oncol Rep. 28:1792–1798. 2012.PubMed/NCBI | |
|
Xing Q, Pang XW, Peng JR, et al: Identification of new cytotoxic T-lymphocyte epitopes from cancer testis antigen HCA587. Biochem Biophys Res Commun. 372:331–335. 2008. View Article : Google Scholar : PubMed/NCBI | |
|
Zhao L, Mou DC, Leng XS, et al: Expression of cancer-testis antigens in hepatocellular carcinoma. World J Gastroenterol. 10:2034–2038. 2004.PubMed/NCBI | |
|
Pang PH, Chan KT, Tse LY, et al: Induction of cytotoxic T cell response against HCA661 positive cancer cells through activation with novel HLA-A*0201 restricted epitopes. Cancer Lett. 256:178–185. 2007. View Article : Google Scholar : PubMed/NCBI | |
|
Yang XA, Dong XY, Qiao H, et al: Immunohistochemical analysis of the expression of FATE/BJ-HCC-2 antigen in normal and malignant tissues. Lab Invest. 85:205–213. 2005. View Article : Google Scholar | |
|
Yin YH, Li YY, Qiao H, et al: TSPY is a cancer testis antigen expressed in human hepatocellular carcinoma. Br J Cancer. 93:458–463. 2005. View Article : Google Scholar : PubMed/NCBI | |
|
Ono T, Kurashige T, Harada N, et al: Identification of proacrosin binding protein sp32 precursor as a human cancer/testis antigen. Proc Natl Acad Sci USA. 98:3282–3287. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Fan R, Huang W, Xiao SW, et al: OY-TES-1 expression and serum immunoreactivity in hepatocellular carcinoma. World Chi J Digest. 17:3307–3312. 2009.(In Chinese). | |
|
Tammela J, Uenaka A, Ono T, et al: OY-TES-1 expression and serum immunoreactivity in epithelial ovarian cancer. Int J Oncol. 29:903–910. 2006.PubMed/NCBI | |
|
Whitehurst AW, Xie Y, Purinton SC, et al: Tumor antigen acrosin binding protein normalizes mitotic spindle function to promote cancer cell proliferation. Cancer Res. 70:7652–7661. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Kanemori Y, Ryu JH, Sudo M, et al: Two functional forms of ACRBP/sp32 are produced by pre-mRNA alternative splicing in the mouse. Biol Reprod. 88:1052013. View Article : Google Scholar : PubMed/NCBI | |
|
Okumura H, Noguchi Y, Uenaka A, et al: Identification of an HLA-A24-restricted OY-TES-1 epitope recognized by cytotoxic T-cells. Microbiol Immunol. 49:1009–1016. 2005. View Article : Google Scholar : PubMed/NCBI | |
|
Cen YH, Guo WW, Luo B, et al: Knockdown of OY-TES-1 by RNAi causes cell cycle arrest and migration decrease in bone marrow-derived mesenchymal stem cells. Cell Biol Int. 36:917–922. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Yellaboina S, Tasneem A, Zaykin DV, et al: DOMINE: a comprehensive collection of known and predicted domain-domain interactions. Nucleic Acids Res. 39:D730–D735. 2011. View Article : Google Scholar : | |
|
Finn RD, Bateman A, Clements J, et al: Pfam: the protein families database. Nucleic Acids Res. 42:D222–D230. 2014. View Article : Google Scholar : | |
|
Kumar B, Sharma D, Sharma P, et al: Proteomic analysis of Mycobacterium tuberculosis isolates resistant to kanamycin and amikacin. J Proteomics. 94:68–77. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Rhodes DR, Kalyana-Sundaram S, Mahavisno V, et al: Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia. 9:166–180. 2007. View Article : Google Scholar : PubMed/NCBI | |
|
Wilson BJ and Giguère V: Identification of novel pathway partners of p68 and p72 RNA helicases through Oncomine meta-analysis. BMC Genomics. 8:4192007. View Article : Google Scholar : PubMed/NCBI | |
|
Li Z, Ma B, Lu M, et al: Construction of network for protein kinases that play a role in acute pancreatitis. Pancreas. 42:607–613. 2013. View Article : Google Scholar | |
|
Melaiu O, Cristaudo A, Melissari E, et al: A review of transcriptome studies combined with data mining reveals novel potential markers of malignant pleural mesothelioma. Mutat Res. 750:132–140. 2012. View Article : Google Scholar | |
|
Smith IM, Glazer CA, Mithani SK, et al: Coordinated activation of candidate proto-oncogenes and cancer testes antigens via promoter demethylation in head and neck cancer and lung cancer. PLoS One. 4:e49612009. View Article : Google Scholar : PubMed/NCBI | |
|
Suyama T, Shiraishi T, Zeng Y, et al: Expression of cancer/testis antigens in prostate cancer is associated with disease progression. Prostate. 70:1778–1787. 2010.PubMed/NCBI | |
|
Warde-Farley D, Donaldson SL, Comes O, et al: The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 38:W214–W220. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Williamson MP, Marion D and Wüthrich K: Secondary structure in the solution conformation of the proteinase inhibitor IIA from bull seminal plasma by nuclear magnetic resonance. J Mol Biol. 173:341–359. 1984. View Article : Google Scholar : PubMed/NCBI | |
|
Laskowski M Jr, Kato I, Ardelt W, et al: Ovomucoid third domains from 100 avian species: isolation, sequences, and hypervariability of enzyme-inhibitor contact residues. Biochemistry. 26:202–221. 1987. View Article : Google Scholar : PubMed/NCBI | |
|
Schlott B, Wöhnert J, Icke C, et al: Interaction of Kazal-type inhibitor domains with serine proteinases: biochemical and structural studies. J Mol Biol. 318:533–546. 2002. View Article : Google Scholar : PubMed/NCBI | |
|
Funk JD, Nedialkov YA, Xu D and Burton ZF: A key role for the α1 helix of human RAP74 in the initiation and elongation of RNA chains. J Biol Chem. 277:46998–47003. 2002. View Article : Google Scholar : PubMed/NCBI | |
|
Baba T, Niida Y, Michikawa Y, et al: An acrosomal protein, sp32, in mammalian sperm is a binding protein specific for two proacrosins and an acrosin intermediate. J Biol Chem. 269:10133–10140. 1994.PubMed/NCBI | |
|
Hase H, Kanno Y, Kojima H, et al: CD27 and CD40 inhibit p53-independent mitochondrial pathways in apoptosis of B cells induced by B cell receptor ligation. J Biol Chem. 277:46950–46958. 2002. View Article : Google Scholar : PubMed/NCBI | |
|
Shi JY, Gao Q, Wang ZC, et al: Margin-infiltrating CD20+ B cells display an atypical memory phenotype and correlate with favorable prognosis in hepatocellular carcinoma. Clin Cancer Res. 19:5994–6005. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Wang XD, Wang L, Ji FJ, et al: Decreased CD27 on B lymphocytes in patients with primary hepatocellular carcinoma. J Int Med Res. 40:307–316. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Yang ZQ, Yang ZY, Zhang LD, et al: Increased liver-infiltrating CD8+FoxP3+ regulatory T cells are associated with tumor stage in hepatocellular carcinoma patients. Hum Immunol. 71:1180–1186. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Zhang X, Xu LS, Wang ZQ, et al: ING4 induces G2/M cell cycle arrest and enhances the chemosensitivity to DNA-damage agents in HepG2 cells. FEBS Lett. 570:7–12. 2004. View Article : Google Scholar : PubMed/NCBI | |
|
Doyon Y, Cayrou C, Ullah M, et al: ING tumor suppressor proteins are critical regulators of chromatin acetylation required for genome expression and perpetuation. Mol Cell. 21:51–64. 2006. View Article : Google Scholar : PubMed/NCBI | |
|
Li X, Cai L, Chen H, et al: Inhibitor of growth 4 induces growth suppression and apoptosis in glioma U87MG. Pathobiology. 76:181–192. 2009. View Article : Google Scholar : PubMed/NCBI | |
|
Karabulut B, Karaca B, Atmaca H, et al: Regulation of apoptosis-related molecules by synergistic combination of all-trans retinoic acid and zoledronic acid in hormone-refractory prostate cancer cell lines. Mol Biol Rep. 38:249–259. 2011. View Article : Google Scholar | |
|
Matsuda A, Suzuki Y, Honda G, et al: Large-scale identification and characterization of human genes that activate NF-κB and MAPK signaling pathways. Oncogene. 22:3307–3318. 2003. View Article : Google Scholar : PubMed/NCBI | |
|
Masellis-Smith A and Shaw AR: CD9-regulated adhesion. Anti-CD9 monoclonal antibody induces pre-B cell adhesion to bone marrow fibroblasts through de novo recognition of fibronectin. J Immunol. 152:2768–2777. 1994.PubMed/NCBI | |
|
Leung KT, Chan KY, Ng PC, et al: The tetraspanin CD9 regulates migration, adhesion, and homing of human cord blood CD34+ hematopoietic stem and progenitor cells. Blood. 117:1840–1850. 2011. View Article : Google Scholar | |
|
Powner D, Kopp PM, Monkley SJ, et al: Tetraspanin CD9 in cell migration. Biochem Soc Trans. 39:563–567. 2011. View Article : Google Scholar : PubMed/NCBI | |
|
Kanetaka K, Sakamoto M, Yamamoto Y, et al: Overexpression of tetraspanin CO-029 in hepatocellular carcinoma. J Hepatol. 35:637–642. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Li J and Li G: Cell cycle regulator ING4 is a suppressor of melanoma angiogenesis that is regulated by the metastasis suppressor BRMS1. Cancer Res. 70:10445–10453. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Meyerson M and Harlow E: Identification of G1 kinase activity for cdk6, a novel cyclin D partner. Mol Cell Biol. 14:2077–2086. 1994.PubMed/NCBI | |
|
Yadav S, Pandey A, Shukla A, et al: miR-497 and miR-302b regulate ethanol-induced neuronal cell death through BCL2 protein and cyclin D2. J Biol Chem. 286:37347–37357. 2011. View Article : Google Scholar : PubMed/NCBI | |
|
Zhou J, Tian Y, Li J, et al: miR-206 is down-regulated in breast cancer and inhibits cell proliferation through the up-regulation of cyclinD2. Biochem Biophys Res Commun. 433:207–212. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Zhang L, Liu X, Jin H, et al: miR-206 inhibits gastric cancer proliferation in part by repressing cyclinD2. Cancer Lett. 332:94–101. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Chen BB, Glasser JR, Coon TA, et al: F-box protein FBXL2 targets cyclin D2 for ubiquitination and degradation to inhibit leukemic cell proliferation. Blood. 119:3132–3141. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Igawa T, Sato Y, Takata K, et al: Cyclin D2 is overexpressed in proliferation centers of chronic lymphocytic leukemia/small lymphocytic lymphoma. Cancer Sci. 102:2103–2107. 2011. View Article : Google Scholar : PubMed/NCBI | |
|
Dong Q, Meng P, Wang T, et al: MicroRNA let-7a inhibits proliferation of human prostate cancer cells in vitro and in vivo by targeting E2F2 and CCND2. PLoS One. 5:e101472010. View Article : Google Scholar : PubMed/NCBI | |
|
Darr H, Mayshar Y and Benvenisty N: Overexpression of NANOG in human ES cells enables feeder-free growth while inducing primitive ectoderm features. Development. 133:1193–1201. 2006. View Article : Google Scholar : PubMed/NCBI | |
|
Yang L, Zhang X, Zhang M, et al: Increased Nanog expression promotes tumor development and cisplatin resistance in human esophageal cancer cells. Cell Physiol Biochem. 30:943–952. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Siu MK, Wong ES, Kong DS, et al: Stem cell transcription factor NANOG controls cell migration and invasion via dysregulation of E-cadherin and FoxJ1 and contributes to adverse clinical outcome in ovarian cancers. Oncogene. 32:3500–3509. 2013. View Article : Google Scholar | |
|
Valdez BC, Perlaky L, Saijo Y, et al: A region of antisense RNA from human p120 cDNA with high homology to mouse p120 cDNA inhibits NIH 3T3 proliferation. Cancer Res. 152:5681–5686. 1992. | |
|
Siggers RH and Hackam DJ: The role of innate immune-stimulated epithelial apoptosis during gastrointestinal inflammatory diseases. Cell Mol Life Sci. 68:3623–3634. 2011. View Article : Google Scholar : PubMed/NCBI | |
|
Sharan R, Ulitsky I and Shamir R: Network-based prediction of protein function. Mol Syst Biol. 3:882007. View Article : Google Scholar : PubMed/NCBI | |
|
Dodurga Y, Oymak Y, Gündüz C, et al: Leukemogenesis as a new approach to investigate the correlation between up regulated gene 4/upregulator of cell proliferation (URG4/URGCP) and signal transduction genes in leukemia. Mol Biol Rep. 40:3043–3048. 2013. View Article : Google Scholar | |
|
Faussillon M, Monnier L, Junien C and Jeanpierre C: Frequent overexpression of cyclin D2/cyclin-dependent kinase 4 in Wilms’ tumor. Cancer Lett. 221:67–75. 2005. View Article : Google Scholar : PubMed/NCBI | |
|
Park TJ, Chun JY, Bae JS, et al: CCND2 polymorphisms associated with clearance of HBV infection. J Hum Genet. 55:416–420. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Takano Y, Kato Y, van Diest PJ, et al: Cyclin D2 overexpression and lack of p27 correlate positively and cyclin E inversely with a poor prognosis in gastric cancer cases. Am J Pathol. 156:585–594. 2000. View Article : Google Scholar : PubMed/NCBI | |
|
Uchida F, Uzawa K, Kasamatsu A, et al: Overexpression of cell cycle regulator CDCA3 promotes oral cancer progression by enhancing cell proliferation with prevention of G1 phase arrest. BMC Cancer. 12:3212012. View Article : Google Scholar : PubMed/NCBI | |
|
Chen J, Zhu S, Jiang N, et al: HoxB3 promotes prostate cancer cell progression by transactivating CDCA3. Cancer Lett. 330:217–224. 2013. View Article : Google Scholar | |
|
Bunt J, de Haas TG, Hasselt NE, et al: Regulation of cell cycle genes and induction of senescence by overexpression of OTX2 in medulloblastoma cell lines. Mol Cancer Res. 8:1344–1357. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Visconti R, Palazzo L, Della Monica R and Grieco D: Fcp1-dependent dephosphorylation is required for M-phase-promoting factor inactivation at mitosis exit. Nat Commun. 3:8942012. View Article : Google Scholar : PubMed/NCBI | |
|
Funakoshi T, Tachibana I, Hoshida Y, et al: Expression of tetraspanins in human lung cancer cells: frequent downregulation of CD9 and its contribution to cell motility in small cell lung cancer. Oncogene. 22:674–687. 2003. View Article : Google Scholar : PubMed/NCBI | |
|
Ovalle S, Gutiérrez-López MD, Olmo N, et al: The tetraspanin CD9 inhibits the proliferation and tumorigenicity of human colon carcinoma cells. Int J Cancer. 121:2140–2152. 2007. View Article : Google Scholar : PubMed/NCBI | |
|
Saito Y, Tachibana I, Takeda Y, et al: Absence of CD9 enhances adhesion-dependent morphologic differentiation, survival, and matrix metalloproteinase-2 production in small cell lung cancer cells. Cancer Res. 66:9557–9565. 2006. View Article : Google Scholar : PubMed/NCBI | |
|
Murayama Y, Miyagawa J, Oritani K, et al: CD9-mediated activation of the p46 Shc isoform leads to apoptosis in cancer cells. J Cell Sci. 117:3379–3388. 2004. View Article : Google Scholar : PubMed/NCBI | |
|
Zheng R, Yano S, Zhang H, et al: CD9 overexpression suppressed the liver metastasis and malignant ascites via inhibition of proliferation and motility of small-cell lung cancer cells in NK cell-depleted SCID mice. Oncol Res. 15:365–372. 2005. | |
|
Kim JS, Kim J, Kim BS, et al: Identification and functional characterization of an alternative splice variant within the fourth exon of human nanog. Exp Mol Med. 37:601–607. 2005. View Article : Google Scholar | |
|
Oh JH, Do HJ, Yang HM, et al: Identification of a putative trans-activation domain in human Nanog. Exp Mol Med. 37:250–254. 2005. View Article : Google Scholar : PubMed/NCBI | |
|
Shan J, Shen J, Liu L, et al: Nanog regulates self-renewal of cancer stem cells through the insulin-like growth factor pathway in human hepatocellular carcinoma. Hepatology. 56:1004–1014. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Sun C, Sun L, Jiang K, et al: NANOG promotes liver cancer cell invasion by inducing epithelial-mesenchymal transition through NODAL/SMAD3 signaling pathway. Int J Biochem Cell Biol. 45:1099–1108. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Du Y, Shi L, Wang T, Liu Z and Wang Z: Nanog siRNA plus Cisplatin may enhance the sensitivity of chemotherapy in esophageal cancer. J Cancer Res Clin Oncol. 138:1759–1767. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Ji W and Jiang Z: Effect of shRNA-mediated inhibition of Nanog gene expression on the behavior of human gastric cancer cells. Oncol Lett. 6:367–374. 2013.PubMed/NCBI | |
|
Yu J, Zhang SS, Saito K, et al: PTEN regulation by Akt-EGR1-ARF-PTEN axis. EMBO J. 28:21–33. 2009. View Article : Google Scholar : |
