Glioma is the most frequent type of primary malignant brain tumors and 70% cases are at advanced-grade when diagnosed, which is the most aggressive and common brain tumor.[1–3] Currently, gliomas were divided into 4 grades according to the World Health Organization (WHO) grading scale, which is based on the cytologic features and malignant degrees: pilocytic astrocytoma (I), diffuse astrocytoma (II), anaplastic astrocytoma (III), and glioblastoma (IV).[4–6] The precise grading of glioma is important for designing therapy strategies, evaluating prognosis, and monitoring the response to therapies. Glioma mainly derives from neuroepithelial tissues and is of high mortality and morbidity, accounting for about 40% to 50% of intracranial cancers and approximately 1.5% of whole body tumors.[8,9] Because of ineffective therapies and the infiltrative development patterns, the survival rate of glioma patients is relatively low. In addition, the poor prognosis and high mortality are considered to be associated with late diagnosis of glioma.[10,11] Therefore, it is of great importance to find novel biomarkers for the early diagnosis of glioma.
Rho-associated coiled-coil containing protein kinase (ROCK) is the downstream regulator of RhoA and participates in regulating the effects of RhoA on cell adhesion, smooth muscle contraction, cell motility, and apoptosis.[12,13] ROCK is initially identified as a serine/threonine protein kinase that binds to guanosine triphosphate (GTP)-bound RhoA.[14,15] Rho-associated protein kinase 1 (ROCK1) is an isoform of ROCK and consists of a kinase domain, an N-terminal region, a PH domain, a coiled-coil domain, and a C-terminal domain.[16,17]ROCK1 acts as an oncogene and is involved in a wide range of progressions, including cell migration, metastasis, and invasion.[18,19] Moreover, ROCK1 was highly expressed in various tumor tissues and tumor cell lines, including osteosarcoma, gastric cancer, lung cancer, and prostate cancer.[19–22] However, no reports were directly studied the expression and diagnostic value of ROCK1 in glioma.
In the present study, we attempted to determine the presence of ROCK1 mRNA in glioma and assess its relationship with diagnosis of glioma patients.
2 Materials and methods
2.1 Patients and samples
Serum samples were taken from 126 glioma patients and 53 healthy blood donors in Tianjin Medical University General Hospital. Among the 126 glioma patients, there were 56 males and 70 females, who were grouped using the tumor-node-metastasis (TNM) stage. Their clinical parameters were recorded at diagnosis time and summarized in Table 1. None of the patients received any chemotherapy or radiotherapy before blood collection. The healthy controls were prospectively recruited from the medical examination center of the same hospital, and they were matched with cases in age and gender. Our present study was authorized by the Ethic Committee of Tianjin Medical University General Hospital. Informed consents were provided by all participants.
2.2 Serum specimens
After 12 hours overnight fasting, 5 mL peripheral blood samples were collected from all the participants using VP-AS109K Vacutainer tubes (Terumo Corporation, Tokyo, Japan). The blood samples were incubated for 30 minutes at room temperature then centrifuged at 1500 × g for 10 minutes to isolate serum samples. Subsequently, the serum specimens were centrifuged at 20,000 × g for 10 minutes under 4°C condition to remove cell debris, and then maintained at −80°C until use.
2.3 Quantitative real-time polymerase chain reaction (qRT-PCR)
Total RNA was extracted from 200 μL serum using Trizol reagent (Invitrogen, Carlsbad, CA). 2% agarose gel electrophoresis (AGE) was used to detect the integrity of the obtained RNA samples, and the purity of RNA sample was estimated using Nanodrop 2000 (Thermo Fisher Scientific, Wilmington, DE). In AGE images, the complete RNA exhibited clear 28 s and clear 18 s bands, moreover, the brightness ratio of 28 s band to 18 s band was nearly 2:1. OD A260/A280 ratio of 1.8 to 2.0 suggested the high purity of the RNA sample, without the contamination of DNA or protein. The first stand of cDNA was synthesized by PrimerScriptTM RT reagent kit (Takara, Kyoto, Japan). Then real-time PCR was conducted using Power SYBR-Green PCR Master Mix (Applied Biosystems, Foster City, CA) in the ABI Prism 7500 Sequence Detector System Applied Biosystems (Foster City, CA). The used specific primer sequences were as follows: ROCK1: Forward 5’-AACATGCTGCTGGATAAATCTGG-3’; Reverse 5’-TGTATCACATCGTACCATGCCT-3’; GAPDH: Forward 5’-AAGACCTTGGGCTGGGACTG-3’; Reverse 5’-ACCAAATCCGTTGACTCCGA-3’. GAPDH was employed as an internal control. The amplification was carried out in a 20 μL volume containing 1 μL cDNA, 10 μL 2 × SYBR Green Supermix, 2 μL qRT-PCR primers, and 7 μL ddH2O. The reaction sets were as followed: 50°C 2 minutes and 95°C 10 minutes, followed by 40 cycles of 95°C for 30 s and finally 60°C for 1 minutes. The data were shown as cycle threshold (Ct). The levels of ROCK1 mRNA were normalized to GAPDH, and calculated using the formula of 2−ΔΔCt. Each experiment was performed 3 times.
2.4 Statistical analysis
All data analyses were performed using SPSS version 18.0 (SPSS Inc., Chicago, IL), and the figures were plotted by GraphPad Prism version 5.0 (GraphPad, San Diego, CA). It was considered as statistical significance if P was less than 0.05. The expression levels of ROCK1 were shown as mean±standard deviation (SD), and their comparison between glioma patients and healthy controls was carried out using student t test. Chi-square test was adopted to compare the relationship of ROCK1 expression and clinical factors of glioma patients. Receiver operating characteristics (ROC) analysis was performed to evaluate the diagnostic value of ROCK1 through calculating the sensitivity, specificity and area under the curve (AUC) in glioma.
3.1 Up-regulation of ROCK1 mRNA in serum samples collected from glioma
Quantitative Real-time PCR was performed to measure the presence of ROCK1 mRNA in serum collected from glioma and healthy controls. The serum level of ROCK1 mRNA in glioma was 4.11 ± 0.96, while that in the controls was only 2.41 ± 1.00. It could be concluded that ROCK1 mRNA was obviously increased in serum collected from glioma compared to the controls (Fig. 1, P <.05).
3.2 Relationship between ROCK1 expression and clinical factors
The included glioma patients were divided into high expression group (n = 84) and low expression group (n = 32) according to their median serum ROCK1 mRNA levels. Chi-square test was used to illustrate the association between ROCK1 and clinical parameters of glioma patients. The result showed that high ROCK1 mRNA level was significantly correlated with preoperative Karnofsky Performance Status (KPS) score (P = .024) and WHO grade (P = .029). However, no obvious relationship was found between ROCK1 expression and gender (P = .216), neurological disorders (P = .102), family history (P = .125) or cigarette smoking (P = .478) (Table 1).
3.3 Diagnostic accuracy of serum ROCK1 in glioma
The ROC curve was profiled to assess the potential significance of serum ROCK1 mRNA levels in diagnosis of glioma. As shown in Figure 2, the sensitivity and specificity were 88.89% and 79.25%, respectively, with an optimal cutoff point of 3.025. Besides, the AUC was 0.881, indicating that ROCK1 was a diagnostic marker for glioma (P <.0001, 95% CI = 0.829–0.933).
Glioma is a tumor that occurs in neural ectoderm. It is difficult to completely remove by surgical resection because of high invasion and metastasis, and glioma is not sensitive to radiotherapy or chemotherapy. The cause of glioma is complex, which may be related to the chemical carcinogens, ionizing radiation, and heredity. Besides, changes of these factors drive abnormal expression of cancer-related genes, including activation of oncogenes, and inactivation of anti-oncogenes. So far, various biomarkers and signaling pathways involved in cell progression and tumorigenesis have been studied in glioma. Wang et al showed that microRNA (miR)-132 enhanced the activation of transforming growth factor-β (TGF-β) signaling via suppressing SMAD7 in glioma cells. Cheng et al. revealed that miR-218 was an efficient and novel marker for prognosis of glioma patients. Wang et al reported that RAB34 was related with progression and prognosis of glioma. What is more, Zhang et al investigated the function of ROCK1 on the proliferation and metastasis grade of glioma, and the results revealed that up-regulation of ROCK1 played important roles in the carcinogenesis, progression, and invasion of glioma, Thus it attracted great interest to value the clinical role of ROCK1 in glioma patients.
ROCK1, a key downstream effector of the small GTPase RhoA, is a serine/threonine kinase and mediates various cellular responses, including cell proliferation, growth, and apoptosis via microtubule network organization and effects on the cytoskeleton.[28,29] Aberrant expression of ROCK1 has been observed in several cancers and proved to be related to the tumor development and progression. Zhang et al demonstrated that over-expression of ROCK1 was found in laryngeal squamous cell carcinoma. Chen et al explained that the expression of ROCK1 in the myolytic left atrial myocytes of mitral regurgitation (MR) patients was significantly higher than the controls. In addition, ROCK1 has been studied as a biological marker in various diseases. Smit et al claimed that ROCK1 was a potential drug target for BRAF mutant melanoma. Akagi et al showed that ROCK1 was a novel prognostic biomarker for vulvar cancer. In the present study, the attention was paid on the expression of ROCK1 in glioma and its relationship with diagnosis of glioma.
In our study, the underlying role of ROCK1 in glioma diagnosis was assessed through a series of determinations. First, we determined the presence of ROCK1 mRNA in serum samples collected from glioma and healthy controls using the quantitative real-time PCR and the results revealed that serum level of ROCK1 mRNA was increased notably in glioma compared to normal controls, which was in accordance with the previous studies. Besides, high ROCK1 mRNA level was significantly related with preoperative KPS score and WHO grade, indicating ROCK1 might be involved in the progression of glioma. Furthermore, we established the ROC curve to detect the diagnostic value of serum ROCK1 for glioma patients. The results showed that AUC exhibiting a global summary of the diagnostic performance of ROCK1, and the AUC value showed that ROCK1 could discriminate glioma patients from the healthy individuals.
Though the diagnostic performance of ROCK1 in glioma has been investigated in the study, its mechanism on glioma is still unclear. There was a report suggesting that the RhoA/ROCK pathway might be related to abnormal myometrial contractility in obese pregnant women. Hallgren et al demonstrated hat the rho/ROCK signaling pathway was regarded as a sensor of tissue compliance. These may provide us with research interests.
In summary, we explored the diagnostic value of ROCK1 in glioma. Serum ROCK1 mRNA level was significantly higher in glioma than that in the controls and ROCK1 was of great diagnostic significance in glioma. What is more, the precise mechanism of ROCK1 in glioma is still dismal and needs more investigations and efforts in the future work.
Conceptualization: Yunyang Liu, Jianjun Zhang, Dong Wang.
Data curation: Yunyang Liu, Jianjun Zhang, Dong Wang.
Formal analysis: Yunyang Liu, Jianjun Zhang, Dong Wang.
Funding acquisition: Yunyang Liu, Jianjun Zhang, Dong Wang.
Investigation: Yunyang Liu, Jianjun Zhang.
Methodology: Yunyang Liu, Jianjun Zhang, Xinyu Yang.
Project administration: Yunyang Liu, Jianjun Zhang, Dong Wang, Xinyu Yang.
Resources: Yunyang Liu, Jianjun Zhang, Dong Wang, Xinyu Yang.
Software: Yunyang Liu, Jianjun Zhang, Xinyu Yang.
Supervision: Yunyang Liu, Xinyu Yang.
Validation: Xinyu Yang.
Visualization: Xinyu Yang.
Writing – original draft: Yunyang Liu, Jianjun Zhang, Dong Wang.
Writing – review & editing: Yunyang Liu, Jianjun Zhang, Dong Wang.
. Kiang KM, Zhang XQ, Leung GK. Long non-coding rnas: the key players in glioma
pathogenesis. Cancers 2015;7:1406–24.
. Wen PY, Kesari S. Malignant gliomas in adults. New Engl J Med 2008;359:492–507.
. Du W, Pang C, Wang D, et al. Decreased FOXD3 expression is associated with poor prognosis in patients with high-grade gliomas. PLoS One 2015;10:e0127976–87.
. Hueng DY, Tsai WC, Chiou HY, et al. DDX3X biomarker
correlates with poor survival in human gliomas. Int J Mol Sci 2015;16:15578–91.
. Vigneswaran K, Neill S, Hadjipanayis CG. Beyond the World Health Organization grading of infiltrating gliomas: advances in the molecular genetics of glioma
classification. Ann Transl Med 2015;3:95–108.
. Sun J, Liao K, Wu X, et al. Serum microRNA-128 as a biomarker
for diagnosis of glioma
. Int J Clin Exp Med 2015;8:456–63.
. Ryu YJ, Choi SH, Park SJ, et al. Glioma
: application of whole-tumor texture analysis of diffusion-weighted imaging for the evaluation of tumor heterogeneity. PLoS One 2014;9:e108335–48.
. Birner P, Gatterbauer B, Oberhuber G, et al. Expression of hypoxia-inducible factor-1 alpha in oligodendrogliomas: its impact on prognosis and on neoangiogenesis. Cancer 2001;92:165–71.
. Diao J, Xia T, Zhao H, et al. Overexpression of HLA-DR is associated with prognosis of glioma
patients. Int J Clin Exp Pathol 2015;8:5485–90.
. Turner JD, Williamson R, Almefty KK, et al. The many roles of microRNAs in brain tumor biology. Neurosurg Focus 2010;28:1–7.
. Wei X, Chen D, Lv T, et al. Serum microRNA-125b as a potential biomarker
diagnosis. Mol Neurobiol 2016;53:163–70.
. Shi J, Zhang YW, Yang Y, et al. ROCK1
plays an essential role in the transition from cardiac hypertrophy to failure in mice. J Mol Cell Cardiol 2010;49:819–28.
. Loirand G, Guerin P, Pacaud P. Rho kinases in cardiovascular physiology and pathophysiology. Circ Res 2006;98:322–34.
. Ongusaha PP, Qi HH, Raj L, et al. Identification of ROCK1
as an upstream activator of the JIP-3 to JNK signaling axis in response to UVB damage. Sci Signal 2008;1:ra140–221.
. Leung T, Chen XQ, Manser E, et al. The p160 RhoA-binding kinase ROK alpha is a member of a kinase family and is involved in the reorganization of the cytoskeleton. Mol Cell Biol 1996;16:5313–27.
. Lock FE, Hotchin NA. Distinct roles for ROCK1
and ROCK2 in the regulation of keratinocyte differentiation. PLoS One 2009;4:e8190–6.
. Jacobs M, Hayakawa K, Swenson L, et al. The structure of dimeric ROCK I reveals the mechanism for ligand selectivity. J Biol Chem 2006;281:260–8.
. Xi ZW, Xin SY, Zhou LQ, et al. Downregulation of rho-associated protein kinase 1 by miR-124 in colorectal cancer. World J Gastroenterol WJG 2015;21:5454–64.
. Shin JY, Kim YI, Cho SJ, et al. MicroRNA 135a suppresses lymph node metastasis through down-regulation of ROCK1
in early gastric cancer. PLoS One 2014;9:e85205–14.
. Cui G, Cui M, Li Y, et al. MiR-186 targets ROCK1
to suppress the growth and metastasis of NSCLC cells. Tumour Biol J Int Soc Oncodevelop Biol Med 2014;35:8933–7.
. Liu X, Choy E, Hornicek FJ, et al. ROCK1
as a potential therapeutic target in osteosarcoma. J Orthop Res Off Publ Orthop Res Soc 2011;29:1259–66.
. Brown M, Roulson JA, Hart CA, et al. Arachidonic acid induction of Rho-mediated transendothelial migration in prostate cancer. Br J Cancer 2014;110:2099–108.
. Luo Q, Huang H, Deng Y, et al. Lentivirus-mediated shRNA targeting ZNF217 suppresses cell growth, migration, and invasion of glioma
cells in vitro. Nan Fang yi Xue Xue Bao J South Med Univ 2015;35:1024–7.
. Wang ZH, Zhang QS, Duan YL, et al. TGF-beta induced miR-132 enhances the activation of TGF-beta signaling through inhibiting SMAD7 expression in glioma
cells. Biochem Biophys Res Commun 2015;463:187–92.
. Cheng MW, Wang LL, Hu GY. Expression of microRNA-218 and its clinicopathological and prognostic significance in human glioma
cases. Asian Pacific J Cancer Prevent APJCP 2015;16:1839–43.
. Wang HJ, Gao Y, Chen L, et al. RAB34 was a progression- and prognosis-associated biomarker
in gliomas. Tumour Biol J Int Soc Oncodevelop Biol Med 2015;36:1573–8.
. Zhang P, Lu Y, Liu XY, et al. Knockdown of Rho-associated protein kinase 1 suppresses proliferation and invasion of glioma
cells. Tumour Biol J Int Soc Oncodevelop Biol Med 2015;36:421–8.
. Montefusco MC, Merlo K, Bryan CD, et al. Little ROCK is a ROCK1
pseudogene expressed in human smooth muscle cells. BMC Genet 2010;11:22–31.
. Riento K, Ridley AJ. Rocks: multifunctional kinases in cell behaviour. Nature reviews. Mol Cell Biol 2003;4:446–56.
. Zhang J, He X, Ma Y, et al. Overexpression of ROCK1
and ROCK2 inhibits human laryngeal squamous cell carcinoma. Int J Clin Exp Pathol 2015;8:244–51.
. Chen HC, Chang JP, Chang TH, et al. Enhanced expression of ROCK in left atrial myocytes of mitral regurgitation: a potential mechanism of myolysis. BMC Cardiovasc Dis 2015;15:33–5.
. Smit MA, Maddalo G, Greig K, et al. ROCK1
is a potential combinatorial drug target for BRAF mutant melanoma. Mol Syst Biol 2014;10:772–87.
. Akagi EM, Lavorato-Rocha AM, Maia Bde M, et al. ROCK1
as a novel prognostic marker in vulvar cancer. BMC Cancer 2014;14:822.
. O’Brien M, Carbin S, Morrison JJ, et al. Decreased myometrial p160 ROCK-1 expression in obese women at term pregnancy. Reprod Biol Endocrinol RB&E 2013;11:79–87.
. Hallgren O, Rolandsson S, Andersson-Sjoland A, et al. Enhanced ROCK1
dependent contractility in fibroblast from chronic obstructive pulmonary disease patients. J Transl Med 2012;10:171–82.