HOTAIR upregulates an 18-gene cell cycle-related mRNA network in glioma

  • Authors:
    • Kai Huang
    • Jia Sun
    • Chao Yang
    • Yunfei Wang
    • Bingcong Zhou
    • Chunsheng Kang
    • Lei Han
    • Qixue Wang
  • View Affiliations

  • Published online on: March 7, 2017     https://doi.org/10.3892/ijo.2017.3901
  • Pages: 1271-1278
Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

HOTAIR is a tumor promoting long non-coding RNA (lncRNA) with roles in multiple cancers. However, the role of HOTAIR in glioma has not been well charaterized. Genes that positively correlated with HOTAIR were identified from the Chinese Glioma Genome Atlas and constructed into an interacting network. In total, 18 genes with P-values <0.01 were further extracted and constructed into a subnetwork. Real-time PCR, western blot and immunofluorescence analyses were employed to examine the expression of the genes after HOTAIR overexpression or knockdown. Intracranial glioblastoma multiform (GBM) models were used to test the potential of HOTAIR as a glioma therapy target. It was discovered that the 18 genes that most significantly correlated with HOTAIR expression formed a cell cycle-related mRNA network, which is positively regulated by HOTAIR. Furthermore, HOTAIR knockdown inhibited mouse intracranial GBM model formation. HOTAIR positively regulates a cell cycle-related mRNA network in glioma, and could be a potential therapeutic target for treating glioma.

Introduction

Gliomas are the most common primary brain tumors. The average survival rate of grade III patients is 3–5 years, whereas for GBM patients, the average survival is 12–15 months. Surgical resection, standard chemotherapy and radiation therapy provide little improvement in the outcomes of these patients (1). Thus, further exploration of the molecular mechanism may shed light on the treatment of glioma.

Long non-coding RNAs (lncRNAs) are a type of non-coding RNAs that are longer that 200 nt, and play various roles in diverse biological processes. They can affect expression of downstream genes, alter alternative splicing by hybridizing to pre-mRNA, are involved in structural and organizational roles in the cell and can be processed into small RNAs (24). However, the molecular mechanisms of lncRNA are not completely understood.

HOTAIR is an lncRNA that is much more characterized than other long non-coding transcripts. In developmental processes, HOTAIR silences the expression of the HOXD gene cluster (5). Targeted disruption of HOTAIR leads to gene de-repression and homeotic transformation in mice (6). Deletion of 5′ HOXC genes where HOTAIR locates, leads to malformations in mice, such as clubfoot and vertical talus (7). HOTAIR was first reported as a tumor-promoting lncRNA in breast cancer (8). Increased research indicates that HOTAIR could be a potential biomarker and target in gastric cancer, colon cancer, cervical cancer and glioma (912). Mechanistically, the 5′ domain of HOTAIR binds to the PRC2 complex, while the 3′ domain binds to the LSD1 complex. EZH2 is a major component of the PRC2 complex, which tri-methylates H3K27 markers at the promoter of target genes. High levels of HOTAIR in cancer may inhibit tumor suppressor genes in epigenetic manner (13). Knocking down HOTAIR in glioma has been shown to upregulate NLK, a negative regulator of β-catenin pathway, which depends on the 5′ domain but not the 3′ domain (14). As a cell cycle-associated gene, HOTAIR is a strong predictor of survival in glioma, and is often expressed in classical and mesenchymal subtypes (15).

Accurate control of the cell cycle is essential for DNA synthesis and cell proliferation. Aberrant cell cycle progression is commonly observed in tumors and closely tracks with abnormal expression of cell cycle checkpoint genes. LncRNAs impact the cell cycle in various ways (1618). NcRNACCND1 is a transcriptional regulator that suppresses cyclin D1 and participates in G1 arrest in a DNA damage-dependent manner (19). ANRIL, an antisense lncRNA in the INK4 locus, suppresses p15INK4B expression in a PRC2-dependent manner (20). MALAT1, a nuclear-localized lncRNA, controls the cell cycle via regulating B-MYB (21). Previously, we reported HOTAIR as a cell cycle-associated lncRNA. Herein, we further characterized the regulation mechanisms of HOTAIR.

In the present study, we identified a cell cycle-related mRNA network that is regulated by HOTAIR in glioma cells. Genes in the CGGA database whose expression is positively correlated with HOTAIR were constructed into an interaction network, ranked by connection. The top 18 genes with P-values <0.01 are associated with the cell cycle. In glioma cell lines, HOTAIR upregulated the mRNA expression of network, whereas knocking down HOTAIR inhibited expression of these genes. Finally, we demonstrated that knocking down HOTAIR in U87vIII cells significantly inhibited intracranial tumor growth. These results support the potential of targeting HOTAIR in glioma, and further supported that HOTAIR is the potential therapy target in glioma.

Materials and methods

Datasets of glioma samples

mRNA expression datasets and the corresponding clinical information were downloaded from the following websites: Chinese Glioma Genome Atlas (CGGA) (http://www.cgga.org.cn), the Cancer Genome Atlas (TCGA) (http://cancergenome.nih.gov), and the REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT) (http://caintegrator.nci.nih.gov/rembrandt/).

Cell line and culture conditions

The human GBM cell lines U87, U87vIII and U251 were used for experiments. U87 and U251 GBM cells were purchased from the ATCC (Manassas, VA, USA). U87 cells were cultured in complete MEM medium, while U251 cells were cultured in complete EMEM medium containing 10% FBS, and incubated at 37°C, 5% CO2. U87vlll cells were stably transfected with a truncated mutant EGFR gene, which can be consistently activated without EGF stimulation. Puromycin (100 ng/ml) was added into U87vIII culture medium to maintain the stability of EGFRvIII.

Reverse transcription (RT)-PCR

To determine mRNA expression, after treatment, the glioma cells were lysed in TRIzol reagent (Sigma-Aldrich, St. Louis, MO, USA). The lysate was well mixed with chloroform and spun for 15 min at 13,000 × g at 4°C. The top aqueous phase, which contains RNA, was collected and mixed with propan-2-ol to precipitate the total RNA, which was used for real-time PCR analysis of mRNA. The cDNA was synthesized from 1 µg of total RNA, using a reverse transcription kit purchased from Promega (Madison, WI, USA), following the manufacturer's protocol. Real-time PCR was performed using a SYBR Green Master Mix from Life Technologies (Carlsbad, CA, USA). Amplification was performed by the DNA Engine Opticon 2 Two-Color Real-time PCR detection system (Bio-Rad Laboratories, Hercules, CA, USA). Relative gene expression was analyzed by 2ΔΔ-Cq method (22). Gene specific primers: HOTAIR-F: ATAGGCAAATGTCAGAGGGTT, HOTAIR-R: TCTTAAATTGGGCTGGGTC; GAPDH-F: GGTGGTCTCCTCTGACTTCAACA, GAPDH-R: GTTGCTGTAGCCAAATTCGTTGT; CCNA2-F: CTCTACACAGTCACGGGACAAAG, CCNA2-R: CTGTGGTGCTTTGAGGTAGGTC; HMMR-F: GGCTGGGAAAAATGCAGAGGATG, HMMR-R: CCTTTAGTGCTGACTTGGTCTGC; FoxM1-F: CCTTCTGGACCATTCACCCC, FoxM1-R: TCACCGGGAACTGGATAGGT; NUSAP1-F: CTGACCAAGACTCCAGCCAGAA, NUSAP1-R: GAGTCTGCGTTGCCTCAGTTGT; ASPM-F: GAGACCTTGGTGGAATACCTGC, ASPM-R: ACGAAGATCCAAAAGCCTTGCAC; CDC6-F: TCCACCAAAGCAAGGCAAGA, CDC6-R: CGATCTGGGACAGCTGTGTT; FANCI-F: GCAAGCTGATGTTCGACTCATGC, FANCI-R: AGGCAGCAGATCAGGTTTTGGC; NCAPG-F: GACGAACAGGAGGTGTCAGACT, NCAPG-R: TGCTGCGGTTTTGGCTCGTCTT; DLGAP5-F: CTCGATCAGCTACTCAAGCAGC, DLGAP5-R: CAGGTCTTCCTTTACTTGGCACC; CHEK1-F: ATCAACTCATGGCAGGGGTG, CHEK1-R: TCCAGCGAGCATTGCAGTAA; CEP55-F: TCG ACCGTCAACATGTGCAGCA, CEP55-R: GGCTCTGTGATGGCAAACTCATG; KIF4A-F: TGCGTGGTCAAGTTT CGGAGTC, KIF4A-R: GCTGTAGGTCAGCAATCTGAGC; HJURP-F: TGAGAATTTGGGGTGGAAGACT, HJURP-R: AGCGGAGTCACACGTACATC; PLK4-F: GACACCTCAGACTGAAACCGTAC, PLK4-R: GTCCTTCTGCAAATCTGGATGGC; CCNB2-F: AGTTCCAGTTCAACCCACCAA, CCNB2-R: TTGCAGAGCAAGGCATCAGA; CENPE-F: GGAGAAAGATGACCTACAGAGGC, CENPE-R: AGTTCCTCTTCAGTTTCCAGGTG; NCAPH-F: GACGAACAGGAGGTGTCAGACT, NCAPH-R: TGCTGCGGTTTTGGCTCGTCTT; AURKB-F: CATCCCAACATCCTGCGTCT, AURKB-R: AGCTCTCCCTTGAGCCCTAA.

Western blot analysis

Protein lysates were prepared as follows: after treatment, cells were washed twice with cold PBS, scraped and lysed in ice-cold RIPA buffer (Solarbio, Beijing, China). Lysate was sonicated for 20 cycles, and microcentrifuged for 15 min at 4°C. The supernatant was transferred to a new test tube and stored at 20°C. The protein samples were resolved by SDS-PAGE and transferred onto PVDF membranes (Milipore, Darmstadt, Germany). The membranes were then incubated with the following antibodies: anti-FoxM1 (Cell Signaling Technology, Danvers, MA, USA), anti-CEP55 (Abcam, Cambridge, UK) and GAPDH (Proteintech, Wuhan, China). Antibody-labeled protein bands on the PVDF membranes were detected using a G:BOX F3 (Syngene, Cambridge, UK).

Immunofluorescence analysis

U87 cells were seeded onto the coverslips and transfected with negative control or Lenti-HOTAIR virus (GeneChem, Shanghai, China) for 48 h. Then, they were fixed in 4% paraformaldehyde for 30 min. The cells or sections were permeabilized with 0.1% Triton-X 100 for 10 min, followed by blocking with 3% BSA for 1 h in RT. Immunofluorescence staining was conducted with antibodies against CEP55 (Abcam, 1:100) and CENPE (Abcam, 1:100). The cells were washed with PBS and incubated with Alexa Fluor 633 or Alexa Fluor 594 (Life Technologies) secondary antibodies. Nuclei were stained using DAPI and the cells were visualized using FV-1200 laser scanning confocal microscope.

Mouse glioma intracranial model and treatment

U87vIII cells were transfected with either a negative control or Lenti-si-HOTAIR virus. An indicated number of cells in suspension were injected stereotactically into the brain of 4-week-old BALB/c-nu mice. The mice were sacrificed at day 14.

Histological analysis

The xenograft samples were collected at day 14 after tumor implantation, and were subjected to Hematoxylin and eosin (H&E) staining. Sections (5 µm) were cut, dehydrated, deparaffinized, and rehydrated. H&E staining was performed according to the standard protocols. All images were captured via microscopy (Olympus, Tokyo, Japan). The protocol for the animal study was approved by the Animal Ethics Committee of Tianjin Medical University.

Statistical analysis

Statistical analysis was performed using the SPSS Graduate Pack, version 11.0, statistical software (SPSS). Data are presented as means ± SEM of three independent experiments or means ± SD performed in triplicate. One-way ANOVA was used for comparison among the different groups. A P-value of 0.05 was considered to indicate a statistically significant difference.

Results

Identification of a cell cycle-related mRNA network positively correlated with HOTAIR

Although variety of lncRNAs have been described in recent years, the functions of lncRNA are still not completely characterized. To profile lncRNAs in glioma, cluster analysis was employed using the CGGA database, which includes 220 glioma samples and 5 normal brain samples. There are 90 lncRNAs that have different patterns of expression between low-grade and high-grade gliomas. There are 31 lncRNAs downregulated in high-grade glioma, while 59 lncRNAs were upregulated (FDR <0.05, fold >1.5) (Fig. 1). It is possible that the main alteration of lncRNA expression occurs during malignant progression from low-grade glioma to GBM, indicating an important role of lncRNA in glioma progression. HOTAIR is among the lncRNAs in the high expressin module of the heat map, which is consistent with a previous study (15). HOTAIR is a cell cycle-associated oncogene in glioma (11), however, further research is still needed to demonstrate its role in gliomagenesis.

To profile the function of HOTAIR, genes positively correlated with HOTAIR were selected by Pearson correlation coefficients (R>0.3, P<0.05) (Fig. 2A). In total, 244 HOTAIR correlated genes formed a complex network, in which they correlated with each other according to literature, databases or experiments. Genes with P-values <0.01 were extracted from the HOTAIR positive gene network, as they are more significantly correlated with HOTAIR (Fig. 2B). The correlation degrees of the 18 genes are greater than 25, and all of them interact with each other. Overall, 215 of the 244 genes in network are directly correlated with these 18 genes, implying a key role of this 18-gene network. The cluster analysis of these genes according to HOTAIR expression in the CGGA, REMBRANDT and TCGA databases further confirmed the positive correlation expression pattern of these 18 genes with HOTAIR (Fig. 2C–E). Bioinformatic analysis revealed that the upregulation of 17 of them (except CCNB2) corresponds with clinical stage glioma (Table I). Kaplan-Meier survival analysis further indicated a negative correlation between the expression level of 17 genes and the survival rate in high-grade glioma. Fig. 2F–M depicts four genes with the most significant P-values from the Kaplan-Meier survival analysis. Of these 18 genes, 15 genes play roles in cell cycle regulation, including CCNA2, FoxM1, CEP55, CENPE. FANCI and CDC6 are genes regulating DNA replication and repair, which may influence the cell cycle indirectly. Thus, we identified these mRNAs as a cell cycle-related network that positively correlated with HOTAIR.

Table I

The cell cycle-related mRNA network that positively correlated with HOTAIR.

Table I

The cell cycle-related mRNA network that positively correlated with HOTAIR.

GenesDegreesSurvival in HGG (P-value) UniProtKB/Swiss-Prot
CCNA2420.0004Controlling the cell cycle at the G1/S (start) and the G2/M (mitosis) transitions
HMMR340.0018Phosphorylation of a number of proteins, including PTK2/FAK1
FoxM1320.0032Regulates the expression of cell cycle genes essential for DNA replication and mitosis
NUSAP1320.0011Organization of mitotic spindle microtubules around them
ASPM310.0002Mitotic spindle regulation and coordination of mitotic processes
CDC631<0.0001Initiation of DNA replication
FANCI310.0001Repairing of DNA double-strand breaks by homologous recombination
NCAPG31<0.0001Conversion of interphase chromatin into mitotic-like condense chromosomes
DLGAP5300.0026Cell cycle regulator and key regulator of adherens junction integrity
CHEK1290.0059Binding to and phosphorylating CDC25A, CDC25B and CDC25C
CEP55280.0016Mitotic exit and cytokinesis
KIF4A280.0117Mitotic chromosomal positioning and bipolar spindle stabilization
HJURP270.0334Incorporation and maintenance of histone H3-like variant CENPA at centromeres
PLK427<0.0001Central role in centriole duplication
CCNB2260.0646Controlling the cell cycle at the G2/M (mitosis) transition
CENPE26<0.0001Maintenance of chromosomal stability
NCAPH260.0032Regulatory submit of the condensing complex
AURKB250.0077Key regulator of mitosis
HOTAIR upregulates a cell cycle-related mRNA network in vitro

To further test if this mRNA network could be upregulated by HOTAIR in vitro, we transfected a tetracycline-inducible HOTAIR expression lenti virus. Real-time PCR analysis indicated that genes in this network were upregulated when HOTAIR expression was induced by doxycycline in U87 (Fig. 3A) and U251 (Fig. 3B) cells. EGFRvIII is an aggressive EGFR mutation type in glioma. We knocked down HOTAIR in U87vIII cells by Lenti-si-HOTAIR and discovered that this network was downregulated by inhibiting HOTAIR (Fig. 3C). FoxM1 is a key transcription factor that regulates the expression of cell cycle genes (23,24). CEP55 and CENPE, which are important regulators of mitosis, impact survival rate very significantly in high-grade glioma (HGG) (24,25). Thus, we representatively chose FoxM1, CEP55 and CENPE from the network to further examine the influence of HOTAIR on these genes and the proteins they code. Western blot analysis indicated that HOTAIR could upregulate FoxM1 and CEP55 in U87 cells, while Lenti-si-HOTAIR-treatment inhibited expression of these proteins in U87vIII cells (Fig. 3D). Immunofluorescence staining further confirmed the upregulation of CEP55 (Fig. 3E) and CENPE (Fig. 3F) in U87 cells. Thus, we demonstrated that this cell cycle-related mRNA network is positively regulated by HOTAIR.

Targeting HOTAIR inhibits glioma progression

EGFR is a receptor tyrosine kinase that is frequently amplified and mutated in several cancers. EGFRvIII is one such mutation commonly found in GBM patients, and it contributes to the malignant progression of the disease (26). Knocking down HOTAIR significantly inhibited the cell cycle-related mRNA network in U87vIII cells. Thus, we targeted HOTAIR in U87vIII intracranial GBM mouse models. U87vIII cells (2×105) could form orthotopic tumors in mice in 14 days. However, after lenti-si-HOTAIR treatment, there was no macroscopic tumor formation even after the injection of 8×105 cells (Fig. 4A). These results indicated that knocking down HOTAIR could control U87vIII tumor formation within 2 weeks. Our bioinformatic analysis of the CGGA database further indicated that HOTAIR expression is upregulated in high-grade glioma (Fig. 4B), and high levels of HOTAIR are correlated with poor outcome in glioma (Fig. 4C) and HGG (Fig. 4D). These results indicated that HOTAIR could be a potential therapeutic target in glioma, especially for GBM.

Discussion

In the present study, we demonstrated that HOTAIR regulates a cell cycle-related mRNA network in glioma. Genes in this network are distributed throughout the cell cycle (Fig. 5). When leaving G0 phase to enter into mitosis, healthy cells check the integrity of chromosomes and proteins required for replication. CCNA2, CCNB2 and CHEK1 promote this cell cycle checkpoint (2729). During mitosis, the localization of centrosomes and spindles is well organized to perform accurate separation of the two daughter cells. NCAPH, CENPE, KIF4A, CEP55, NUSAP1 and ASPM participate in mitotic spindle regulation and mitotic processes (25,3034). FoxM1 and AURKB are key regulators of mitosis (3537). Thus, HOTAIR may regulate the cell cycle in glioma by impacting both checkpoint proteins and functional proteins during multiple mitosis steps.

Ten genes [HMMR (38), FoxM1 (39), ASPM (40), CDC6 (41), NCAPG (42), CHEK1 (43), CEP55 (44), HJURP (45), CENPE (42), ARUKB (46)] in this network are reported to promote glioma, through regulating the cell cycle and chemoresistance in glioma. Although the other genes have not yet been deeply studied in glioma, their expression is positively correlated with clinical grade glioma (Table I), which makes them potential therapeutic targets. Moreover, they participate in tumor progression in several cancers, including lung cancer and breast cancer (4752). This evidence further confirmed the tumor-promoting role of HOTAIR in glioma and other cancers. Our results indicated that HOTAIR performs its carcinogenesis effort not only by inhibiting tumor-suppressor genes, but also by promoting expression of various oncogenes. This is the first report that HOTAIR could positively regulate a complex oncogene mRNA network, which further profiled the function of HOTAIR. However, the mechanism of up regulation of this network by HOTAIR remains to be explored. This up regulation could either be directly executed by HOTAIR, or be the cascading effort of network interactions.

In conclusion, we report for the first time that HOTAIR could positively regulate a complex oncogene mRNA network, which contributes to the further characterization of the functions of HOTAIR in glioma.

Acknowledgments

This study was supported by the National Key Research and Development Plan (2016YFC0902502), the China National Natural Scientific Fund (81572932), the Tianjin National Natural Scientific Fund (16JCYBJC27400) and the Tianjin Medical University General Hospital Incubation Fund (ZYYFY2014028).

References

1 

Kalpathy-Cramer J, Gerstner ER, Emblem KE, Andronesi OC and Rosen B: Advanced magnetic resonance imaging of the physical processes in human glioblastoma. Cancer Res. 74:4622–4637. 2014. View Article : Google Scholar : PubMed/NCBI

2 

Gloss BS and Dinger ME: The specificity of long noncoding RNA expression. Biochim Biophys Acta. 1859:16–22. 2016. View Article : Google Scholar

3 

Yoon JH, Kim J and Gorospe M: Long noncoding RNA turnover. Biochimie. 117:15–21. 2015. View Article : Google Scholar : PubMed/NCBI

4 

St Laurent G, Wahlestedt C and Kapranov P: The Landscape of long noncoding RNA classification. Trends Genet. 31:239–251. 2015. View Article : Google Scholar : PubMed/NCBI

5 

Rinn JL, Kertesz M, Wang JK, Squazzo SL, Xu X, Brugmann SA, Goodnough LH, Helms JA, Farnham PJ, Segal E, et al: Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell. 129:1311–1323. 2007. View Article : Google Scholar : PubMed/NCBI

6 

Li L, Liu B, Wapinski OL, Tsai MC, Qu K, Zhang J, Carlson JC, Lin M, Fang F, Gupta RA, et al: Targeted disruption of Hotair leads to homeotic transformation and gene derepression. Cell Rep. 5:3–12. 2013. View Article : Google Scholar : PubMed/NCBI

7 

Alvarado DM, McCall K, Hecht JT, Dobbs MB and Gurnett CA: Deletions of 5′ HOXC genes are associated with lower extremity malformations, including clubfoot and vertical talus. J Med Genet. 53:250–255. 2016. View Article : Google Scholar : PubMed/NCBI

8 

Gupta RA, Shah N, Wang KC, Kim J, Horlings HM, Wong DJ, Tsai MC, Hung T, Argani P, Rinn JL, et al: Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature. 464:1071–1076. 2010. View Article : Google Scholar : PubMed/NCBI

9 

Jing L, Yuan W, Ruofan D, Jinjin Y and Haifeng Q: HOTAIR enhanced aggressive biological behaviors and induced radio-resistance via inhibiting p21 in cervical cancer. Tumour Biol. 36:3611–3619. 2015. View Article : Google Scholar

10 

Liu XH, Sun M, Nie FQ, Ge YB, Zhang EB, Yin DD, Kong R, Xia R, Lu KH, Li JH, et al: Lnc RNA HOTAIR functions as a competing endogenous RNA to regulate HER2 expression by sponging miR-331-3p in gastric cancer. Mol Cancer. 13:922014. View Article : Google Scholar : PubMed/NCBI

11 

Zhang K, Sun X, Zhou X, Han L, Chen L, Shi Z, Zhang A, Ye M, Wang Q, Liu C, et al: Long non-coding RNA HOTAIR promotes glioblastoma cell cycle progression in an EZH2 dependent manner. Oncotarget. 6:537–546. 2015.

12 

Kogo R, Shimamura T, Mimori K, Kawahara K, Imoto S, Sudo T, Tanaka F, Shibata K, Suzuki A, Komune S, et al: Long noncoding RNA HOTAIR regulates polycomb-dependent chromatin modification and is associated with poor prognosis in colorectal cancers. Cancer Res. 71:6320–6326. 2011. View Article : Google Scholar : PubMed/NCBI

13 

Spitale RC, Tsai MC and Chang HY: RNA templating the epigenome: Long noncoding RNAs as molecular scaffolds. Epigenetics. 6:539–543. 2011. View Article : Google Scholar : PubMed/NCBI

14 

Zhou X, Ren Y, Zhang J, Zhang C, Zhang K, Han L, Kong L, Wei J, Chen L, Yang J, et al: HOTAIR is a therapeutic target in glioblastoma. Oncotarget. 6:8353–8365. 2015. View Article : Google Scholar : PubMed/NCBI

15 

Zhang JX, Han L, Bao ZS, Wang YY, Chen LY, Yan W, Yu SZ, Pu PY, Liu N, You YP, et al Chinese Glioma Cooperative Group: HOTAIR, a cell cycle-associated long noncoding RNA and a strong predictor of survival, is preferentially expressed in classical and mesenchymal glioma. Neuro Oncol. 15:1595–1603. 2013. View Article : Google Scholar : PubMed/NCBI

16 

McInerny CJ: Cell cycle regulated transcription: From yeast to cancer. F1000Res. 5:52016. View Article : Google Scholar

17 

Visconti R, Della Monica R and Grieco D: Cell cycle checkpoint in cancer: A therapeutically targetable double-edged sword. J Exp Clin Cancer Res. 35:1532016. View Article : Google Scholar : PubMed/NCBI

18 

Bucher N and Britten CD: G2 checkpoint abrogation and checkpoint kinase-1 targeting in the treatment of cancer. Br J Cancer. 98:523–528. 2008. View Article : Google Scholar : PubMed/NCBI

19 

Wang X, Arai S, Song X, Reichart D, Du K, Pascual G, Tempst P, Rosenfeld MG, Glass CK and Kurokawa R: Induced ncRNAs allosterically modify RNA-binding proteins in cis to inhibit transcription. Nature. 454:126–130. 2008. View Article : Google Scholar : PubMed/NCBI

20 

Kotake Y, Nakagawa T, Kitagawa K, Suzuki S, Liu N, Kitagawa M and Xiong Y: Long non-coding RNA ANRIL is required for the PRC2 recruitment to and silencing of p15 (INK4B) tumor suppressor gene. Oncogene. 30:1956–1962. 2011. View Article : Google Scholar

21 

Tripathi V, Shen Z, Chakraborty A, Giri S, Freier SM, Wu X, Zhang Y, Gorospe M, Prasanth SG, Lal A, et al: Long noncoding RNA MALAT1 controls cell cycle progression by regulating the expression of oncogenic transcription factor B-MYB. PLoS Genet. 9:e10033682013. View Article : Google Scholar : PubMed/NCBI

22 

Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) method. Methods. 25:402–408. 2001. View Article : Google Scholar

23 

Kwok CT, Leung MH, Qin J, Qin Y, Wang J, Lee YL and Yao KM: The Forkhead box transcription factor FOXM1 is required for the maintenance of cell proliferation and protection against oxidative stress in human embryonic stem cells. Stem Cell Res (Amst). 16:651–661. 2016. View Article : Google Scholar

24 

Barger CJ, Zhang W, Hillman J, Stablewski AB, Higgins MJ, Vanderhyden BC, Odunsi K and Karpf AR: Genetic determinants of FOXM1 overexpression in epithelial ovarian cancer and functional contribution to cell cycle progression. Oncotarget. 6:27613–27627. 2015. View Article : Google Scholar : PubMed/NCBI

25 

Xu ZY, Ma XS, Qi ST, Wang ZB, Guo L, Schatten H, Sun QY and Sun YP: Cep55 regulates spindle organization and cell cycle progression in meiotic oocyte. Sci Rep. 5:169782015. View Article : Google Scholar : PubMed/NCBI

26 

Zheng Q, Han L, Dong Y, Tian J, Huang W, Liu Z, Jia X, Jiang T, Zhang J, Li X, et al: JAK2/STAT3 targeted therapy suppresses tumor invasion via disruption of the EGFRvIII/JAK2/STAT3 axis and associated focal adhesion in EGFRvIII-expressing glioblastoma. Neuro Oncol. 16:1229–1243. 2014. View Article : Google Scholar : PubMed/NCBI

27 

Loukil A, Cheung CT, Bendris N, Lemmers B, Peter M and Blanchard JM: Cyclin A2: At the crossroads of cell cycle and cell invasion. World J Biol Chem. 6:346–350. 2015. View Article : Google Scholar : PubMed/NCBI

28 

Gong D and Ferrell JE Jr: The roles of cyclin A2, B1, and B2 in early and late mitotic events. Mol Biol Cell. 21:3149–3161. 2010. View Article : Google Scholar : PubMed/NCBI

29 

Carrassa L and Damia G: Unleashing Chk1 in cancer therapy. Cell Cycle. 10:2121–2128. 2011. View Article : Google Scholar : PubMed/NCBI

30 

Cabello OA, Eliseeva E, He WG, Youssoufian H, Plon SE, Brinkley BR and Belmont JW: Cell cycle-dependent expression and nucleolar localization of hCAP-H. Mol Biol Cell. 12:3527–3537. 2001. View Article : Google Scholar : PubMed/NCBI

31 

Vitre B, Gudimchuk N, Borda R, Kim Y, Heuser JE, Cleveland DW and Grishchuk EL: Kinetochore-microtubule attachment throughout mitosis potentiated by the elongated stalk of the kinetochore kinesin CENP-E. Mol Biol Cell. 25:2272–2281. 2014. View Article : Google Scholar : PubMed/NCBI

32 

Mazumdar M, Sundareshan S and Misteli T: Human chromo-kinesin KIF4A functions in chromosome condensation and segregation. J Cell Biol. 166:613–620. 2004. View Article : Google Scholar : PubMed/NCBI

33 

Chou HY, Wang TH, Lee SC, Hsu PH, Tsai MD, Chang CL and Jeng YM: Phosphorylation of NuSAP by Cdk1 regulates its interaction with microtubules in mitosis. Cell Cycle. 10:4083–4089. 2011. View Article : Google Scholar : PubMed/NCBI

34 

Higgins J, Midgley C, Bergh AM, Bell SM, Askham JM, Roberts E, Binns RK, Sharif SM, Bennett C, Glover DM, et al: Human ASPM participates in spindle organisation, spindle orientation and cytokinesis. BMC Cell Biol. 11:852010. View Article : Google Scholar : PubMed/NCBI

35 

Goldenson B and Crispino JD: The aurora kinases in cell cycle and leukemia. Oncogene. 34:537–545. 2015. View Article : Google Scholar

36 

Nunes Bastos R, Gandhi SR, Baron RD, Gruneberg U, Nigg EA and Barr FA: Aurora B suppresses microtubule dynamics and limits central spindle size by locally activating KIF4A. J Cell Biol. 202:605–621. 2013. View Article : Google Scholar : PubMed/NCBI

37 

Wierstra I: The transcription factor FOXM1 (Forkhead box M1): Proliferation-specific expression, transcription factor function, target genes, mouse models, and normal biological roles. Adv Cancer Res. 118:97–398. 2013. View Article : Google Scholar : PubMed/NCBI

38 

Tilghman J, Wu H, Sang Y, Shi X, Guerrero-Cazares H, Quinones-Hinojosa A, Eberhart CG, Laterra J and Ying M: HMMR maintains the stemness and tumorigenicity of glioblastoma stem-like cells. Cancer Res. 74:3168–3179. 2014. View Article : Google Scholar : PubMed/NCBI

39 

Zhang N, Wei P, Gong A, Chiu WT, Lee HT, Colman H, Huang H, Xue J, Liu M, Wang Y, et al: FoxM1 promotes β-catenin nuclear localization and controls Wnt target-gene expression and glioma tumorigenesis. Cancer Cell. 20:427–442. 2011. View Article : Google Scholar : PubMed/NCBI

40 

Horvath S, Zhang B, Carlson M, Lu KV, Zhu S, Felciano RM, Laurance MF, Zhao W, Qi S, Chen Z, et al: Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target. Proc Natl Acad Sci USA. 103:17402–17407. 2006. View Article : Google Scholar : PubMed/NCBI

41 

Stangeland B, Mughal AA, Grieg Z, Sandberg CJ, Joel M, Nygård S, Meling T, Murrell W, Vik Mo EO and Langmoen IA: Combined expressional analysis, bioinformatics and targeted proteomics identify new potential therapeutic targets in glioblastoma stem cells. Oncotarget. 6:26192–26215. 2015. View Article : Google Scholar : PubMed/NCBI

42 

Liang ML, Hsieh TH, Ng KH, Tsai YN, Tsai CF, Chao ME, Liu DJ, Chu SS, Chen W, Liu YR, et al: Downregulation of miR-137 and miR-6500-3p promotes cell proliferation in pediatric high-grade gliomas. Oncotarget. 7:19723–19737. 2016.PubMed/NCBI

43 

Tang Y, Dai Y, Grant S and Dent P: Enhancing CHK1 inhibitor lethality in glioblastoma. Cancer Biol Ther. 13:379–388. 2012. View Article : Google Scholar : PubMed/NCBI

44 

Wang G, Liu M, Wang H, Yu S, Jiang Z, Sun J, Han K, Shen J, Zhu M, Lin Z, et al: Centrosomal Protein of 55 regulates glucose metabolism, proliferation and apoptosis of glioma cells via the Akt/mTOR signaling pathway. J Cancer. 7:1431–1440. 2016. View Article : Google Scholar : PubMed/NCBI

45 

Valente V, Serafim RB, de Oliveira LC, Adorni FS, Torrieri R, Tirapelli DP, Espreafico EM, Oba-Shinjo SM, Marie SK, Paçó-Larson ML, et al: Modulation of HJURP (Holliday Junction-Recognizing Protein) levels is correlated with glioblastoma cells survival. PLoS One. 8:e622002013. View Article : Google Scholar : PubMed/NCBI

46 

Diaz RJ, Golbourn B, Shekarforoush M, Smith CA and Rutka JT: Aurora kinase B/C inhibition impairs malignant glioma growth in vivo. J Neurooncol. 108:349–360. 2012. View Article : Google Scholar : PubMed/NCBI

47 

Takashima S, Saito H, Takahashi N, Imai K, Kudo S, Atari M, Saito Y, Motoyama S and Minamiya Y: Strong expression of cyclin B2 mRNA correlates with a poor prognosis in patients with non-small cell lung cancer. Tumour Biol. 35:4257–4265. 2014. View Article : Google Scholar : PubMed/NCBI

48 

Shubbar E, Kovács A, Hajizadeh S, Parris TZ, Nemes S, Gunnarsdóttir K, Einbeigi Z, Karlsson P and Helou K: Elevated cyclin B2 expression in invasive breast carcinoma is associated with unfavorable clinical outcome. BMC Cancer. 13:12013. View Article : Google Scholar : PubMed/NCBI

49 

Kim DH, Park SE, Kim M, Ji YI, Kang MY, Jung EH, Ko E, Kim Y, Kim S, Shim YM, et al: A functional single nucleotide polymorphism at the promoter region of cyclin A2 is associated with increased risk of colon, liver, and lung cancers. Cancer. 117:4080–4091. 2011. View Article : Google Scholar : PubMed/NCBI

50 

Moore NL, Edwards DP and Weigel NL: Cyclin A2 and its associated kinase activity are required for optimal induction of progesterone receptor target genes in breast cancer cells. J Steroid Biochem Mol Biol. 144:471–482. 2014. View Article : Google Scholar : PubMed/NCBI

51 

Taniwaki M, Takano A, Ishikawa N, Yasui W, Inai K, Nishimura H, Tsuchiya E, Kohno N, Nakamura Y and Daigo Y: Activation of KIF4A as a prognostic biomarker and therapeutic target for lung cancer. Clin Cancer Res. 13(22 Pt 1): 6624–6631. 2007. View Article : Google Scholar : PubMed/NCBI

52 

Wang H, Lu C, Li Q, Xie J, Chen T, Tan Y, Wu C and Jiang J: The role of Kif4A in doxorubicin-induced apoptosis in breast cancer cells. Mol Cells. 37:812–818. 2014. View Article : Google Scholar : PubMed/NCBI

Related Articles

Journal Cover

April-2017
Volume 50 Issue 4

Print ISSN: 1019-6439
Online ISSN:1791-2423

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Huang K, Sun J, Yang C, Wang Y, Zhou B, Kang C, Han L and Wang Q: HOTAIR upregulates an 18-gene cell cycle-related mRNA network in glioma. Int J Oncol 50: 1271-1278, 2017
APA
Huang, K., Sun, J., Yang, C., Wang, Y., Zhou, B., Kang, C. ... Wang, Q. (2017). HOTAIR upregulates an 18-gene cell cycle-related mRNA network in glioma. International Journal of Oncology, 50, 1271-1278. https://doi.org/10.3892/ijo.2017.3901
MLA
Huang, K., Sun, J., Yang, C., Wang, Y., Zhou, B., Kang, C., Han, L., Wang, Q."HOTAIR upregulates an 18-gene cell cycle-related mRNA network in glioma". International Journal of Oncology 50.4 (2017): 1271-1278.
Chicago
Huang, K., Sun, J., Yang, C., Wang, Y., Zhou, B., Kang, C., Han, L., Wang, Q."HOTAIR upregulates an 18-gene cell cycle-related mRNA network in glioma". International Journal of Oncology 50, no. 4 (2017): 1271-1278. https://doi.org/10.3892/ijo.2017.3901