A three mirnas signature predicts survival in cervical cancer using bioinformatics analysis

ABSTRACT Growing evidences showed that a large number of miRNAs were abnormally expressed in cervical cancer tissues and played irreplaceable roles in tumorigenesis, progression and

metastasis. The aim of the present study was to identify the differential miRNAs expression between cervical cancer and normal cervical tissues by analyzing the high-throughput miRNA data

downloaded from TCGA database. Additionally, we evaluated the prognostic values of the differentially expressed miRNAs and constructed a three-miRNA signature that could effectively predict

patient survival. According to the cut-off criteria (_P_ < 0.05 and |log2FC| > 2.0), a total of 78 differentially expressed miRNAs were identified between cervical cancer tissues and

matched normal tissues, including 37 up-regulated miRNAs and 41 down-regulated miRNAs. The Kaplan-Meier survival method revealed the prognostic function of the three miRNAs (miRNA-145,

miRNA-200c, and miRNA-218-1). Univariate and multivariate Cox regression analysis showed that the three-miRNA signature was an independent prognostic factor in cervical cancer. The

functional enrichment analysis suggested that the target genes of three miRNAs may be involved in various pathways related to cancer, including MAPK, AMPK, focal adhesion, cGMP-PKG, wnt, and

mTOR signaling pathway. Taken together, the present study suggested that three-miRNA signature could be used as a prognostic marker in cervical cancer. SIMILAR CONTENT BEING VIEWED BY

OTHERS IDENTIFICATION AND VALIDATION OF A MIRNA-BASED PROGNOSTIC SIGNATURE FOR CERVICAL CANCER THROUGH AN INTEGRATED BIOINFORMATICS APPROACH Article Open access 17 December 2020 MIRNA

EXPRESSION PROFILING AND EMERGENCE OF NEW PROGNOSTIC SIGNATURE FOR ORAL SQUAMOUS CELL CARCINOMA Article Open access 31 March 2021 IMPACT OF THREE MIRNA SIGNATURE AS POTENTIAL DIAGNOSTIC

MARKER FOR TRIPLE NEGATIVE BREAST CANCER PATIENTS Article Open access 08 December 2023 INTRODUCTION According to the world cancer statistics, cervical cancer is the fourth most common cancer

affecting women globally and the second most common cancer in developing areas1, 2, with an estimated global incidence of 530,000 new cases and 270,000 deaths annually3. The preventive

vaccination and organized screening programs are critical in identifying the cervical cancer before it enters advanced stages. Moreover, the treatments are often less effective in advanced

stages compared with early interventions4. Thus, understanding of the molecular mechanisms of cervical cancer development and identification of novel biomarkers are required for the early

detection and treatment of cervical cancer. MicroRNAs (miRNAs), a key component of the noncoding RNA family, are approximately 18–25 nucleotides that involved in the post-transcriptional

regulation of gene expression5. It has been shown that miRNAs are aberrantly expressed in various types of malignancies and function either as oncogenes or tumor suppressors6. Accumulating

evidence has demonstrated that miRNAs regulated various carcinogenesis processes including cell maturation7, cell proliferation8, migration, invasion8, autophagy8, apoptosis9, and

metastasis10. Therefore, miRNAs have a large potential to serve as promising markers in the diagnosis, prognosis, and personalized targeted therapies. Although a number of miRNAs have been

identified in predicting the clinical outcome in cervical cancer, there exists inconsistence in previous studies. This may due to the small sample size, heterogeneous histological subtype,

different detection platforms, and various data processing methods. The Cancer Genome Atlas Project (TCGA) is a National Cancer Institute effort to profile at least 20 different tumor types

using genomic platforms and to make raw and processed data available to all researchers11. The TCGA released a large number of miRNA sequencing data for cervical cancer patients. The aim of

the present study was to identify the differential miRNAs expression between cervical cancer tissues and matched normal cervical tissues by analyzing the high-throughput miRNA data

downloaded from TCGA database. Additionally, we evaluated the prognostic value of the differential expressed miRNAs and constructed a three-miRNA signature that could effectively predict

patient survival. Furthermore, we analyzed the pathway and function of the target genes of three miRNAs, which may provide novel insights into understanding the underlying molecular

mechanism of cervical cancer. RESULTS IDENTIFICATION OF DIFFERENTIALLY EXPRESSED MIRNAS IN CERVICAL CANCER In the present study, a total of 254 samples were enrolled in this study, including

251 cervical cancer tissues and 3 matched normal tissues. The detailed clinical characteristics include diagnosis at age, metastasis, lymph node status, stage, T stage, histological type,

pregnancy numbers, and smoking history category (Table 1). According to the cut-off criteria (_P_ < 0.05 and |log2FC| > 2.0), a total of 78 differentially expressed miRNAs were

identified between cervical cancer tissues and matched normal tissues, including 37 up-regulated and 41 down-regulated miRNAs (Table S1). In order to prove the _P_ value and |log2FC| whether

conform to logic with different test, we present the result as Volcano plot (Fig. 1). Unsupervised hierarchic cluster analysis revealed that cervical cancer tissues could be distinguished

from normal tissues based on differentially expressed miRNAs patterns (Figure S1). IDENTIFICATION OF THREE MIRNAS ASSOCIATED WITH OS IN CERVICAL CANCER To identify the miRNAs which would be

potentially associated with overall survival of cervical cancer patients, we evaluated the association between miRNAs expression and patients’ survival using Kaplan-Meier curve and Log-rank

test. The results showed that one miRNA (miR-200c) was negatively correlated with overall survival (OS), and two miRNAs (miR-145 and miR-218-1) were positively related to OS (Fig. 2). The

association between three miRNAs and clinical features was evaluated in cervical cancer patients (Table 2). The results showed that miR-145 was significantly associated with metastasis (_P_ 

= 0.033) and T stage (_P_ < 0.001); miR-218-1 was associated with stage (_P_ = 0.004), T stage (_P_ = 0.001), and histological type (_P_ < 0.001). No significant difference was found

between miR-200c and clinical features (_P_ > 0.05). PROGNOSTIC VALUE OF THREE MIRNAS SIGNATURE RISK SCORE IN CERVICAL CANCER We constructed a prognostic signature by integrating the

expression profiles of three miRNAs and corresponding estimated regression coefficient. Then, we calculated a risk score for each patient, and ranked them according to increased score. Thus,

a total of 251 patients were classified into a high risk group (n = 125) and a low risk group (n = 126) according to the median risk score. Survival analysis was performed using the

Kaplan-Meier method with a Log-rank statistical test. The result showed that patients in high risk group have significantly worse OS than patients in low risk group (_P_ < 0.001, Fig. 3).

Taking into account the following clinical features: age, metastasis, lymph node status, stage, T stage, histological type, pregnancy number, and smoking history category, univariate and

multivariate Cox regression analysis were used to test the effect of the three-miRNA signature (high risk vs. low risk) on OS. In univariate analysis, age (HR = 0.562, _P_ = 0.037), lymph

node status (HR = 2.567, _P_ = 0.010), stage (HR = 2.511, _P_ = 0.001), T stage (HR = 4.640, _P_ < 0.001), and three-miRNA signature (HR = 2.574, _P_ < 0.001) were associated with OS

in cervical cancer patients. In multivariate analysis, the three-miRNA signature (HR = 2.183, _P_ = 0.028) was showed to be an independent prognostic factor in cervical cancer patients

(Table 3). TARGET PREDICTION AND FUNCTION ANALYSIS The target genes of three miRNAs (miR-145, miR-200c, and miR-218-1) were predicted using TargetScan, miRDB, PicTar, and miRanda online

analysis tools. A total of 67 overlapping genes of miR-145, 126 overlapping genes of miR-200c, and 5 overlapping genes of miR-218-1 were identified (Fig. 4). Then, enrichment analysis was

performed to elucidate the biological function of consensus target genes. The KEGG pathways were significantly enriched in MAPK signaling pathway, AMPK signaling pathway, focal adhesion,

cGMP-PKG signaling pathway, wnt signaling pathway, and mTOR signaling pathway. In addition, the GO biological process (BP) terms were mainly enriched in signal transduction, regulation of

cell migration, and regulation of transcription. DISCUSSION With the introduction of vaccination and screening programs, the incidence of mortality associated with cervical cancer in

developed areas have dramatically declined in recent decades, but the mortality in developing countries remains high, up to 87% of cervical cancer deaths12,13,14,15. The cervical cancer

patient prognosis would be improved considerably if tumor behavior could be predicted reliably at the time of initial diagnosis. Therefore, understanding the molecular mechanisms of cervical

cancer development and identification of novel biomarkers are needed. In the present study, a total of 78 differentially expressed miRNAs were identified, and three of them were associated

with overall survival in cervical cancer patients. The three-miRNA (miR-145, miR-200c, and miR-218-1) signature was established and was identified to be an independent prognostic factor for

cervical cancer patients. Moreover, we screened the target genes of these three miRNAs, and predicted the enrichment pathways and biological functions of target genes using bioinformatics

methods. In the last decade, MiRNAs, as the master modulators of multiple biological and pathological processes, are a hot research topic in the field of cancer development. Mounting

evidence has demonstrated that miRNAs established a complex combinatorial system of gene expression and pathway regulation, as well as prognostic indicators and therapeutic targets in

different cancers, including cervical cancer16, 17. Previous studies have demonstrated that many miRNAs are crucial for the initiation, progression and metastasis of cervical cancer by

regulating various processes, including cancer cell proliferation, differentiation, apoptosis, adhesion, cell cycle arrest, migration and invasion18. To date, several studies had identified

a number of miRNAs with prognostic values, such as miR-15519, miR-425-5p20, miR-196a21, miR-50322, miR-26b23, miR-33524, miR-325, miR-21526, miR-22427, and so on. However, previous studies

were based on small sample size, sample types, different detection platforms, various assay methods, and relatively limited numbers of miRNAs. In the present study, we analyzed

high-throughput data, and identified that two down-regulated miRNAs (miR-145and miR-218-1) and one up-regulated miRNA (miR-200c) were associated with clinical outcome of cervical cancer

patients. Zhou X, _et al_. reported miRNA-145 inhibits tumorigenesis and invasion of cervical cancer stem cells by inducing cancer stem cell (CSC) differentiation through down-regulation of

the stem cell transcription factors that maintain CSC pluripotency28. Sathyanarayanan A, _et al_. suggested that miRNA-145 modulates epithelial-mesenchymal transition (EMT) and suppresses

proliferation, migration and invasion by targeting SIP1 in human cervical cancer cells29. Previous article has also reported human papillomaviruses (HPV) oncoproteins E6 and E7 could

suppress miR-145 expression30. Moreover, miR-218, as a tumor suppressor, was strongly down-expressed and related to proliferation, apoptosis and invasion in cervical cancer31. Yamamoto N,

_et al_. demonstrated that miR-218, acting as a tumor suppressor in cervical cancer, inhibited cancer cell migration and invasion by targeting focal adhesion pathways in cervical squamous

cell carcinoma32. In addition, HPV16 E6 promoted EMT and invasion in cervical cancer via the repression of miR-218, while miR-218 inhibited EMT and invasion in cervical cancer by targeting

Scm-like with four MBT domains 1 (SFMBT1) and defective in cullin neddylation 1, domain containing 1 (DCUN1D1)33. MiR-200c, a member of miR-200 family, located on chromosome 12p1334.

MiR-200c was confirmed to be down-regulated in human breast cancer stem cells, and up-regulated in ovarian cancer, lung cancer, gastric cancer, pancreatic cancer, colorectal cancer, and

gastric cancer35, suggesting its complexity role in cancer as it can act either as oncogene or tumor suppressor depending on the origin of cancer. Our results showed that miR-200c was

up-regulated in cervical cancer, and may be as an oncogene in development of cervical cancer. Furthermore, miR-145 was significantly associated with metastasis and T stage; miR-218-1 was

associated with stage, T stage, and histological type, indicating miR-145 and miR-218-1 were involved in the progression of cervical cancer. But, no significant difference was found between

miR-200c and clinical features. TCGA database does not provide completed cell differentiation (Grade), HPV infection, CIN stage, FIGO stage, and so on. Maybe, miRNA-200c was related to other

factors. The future study will focus on this point, and investigate the function of miRNA-200c in cervical cancer. In the present study, we found that miR-145, miR-200c, and miR-218-1 were

differentially expressed, and significantly associated with overall survival in cervical cancer patients. While efficacy of a single marker was limited, multi-markers based model may provide

more powerful information for the prognosis prediction of patients. We constructed three-miRNA signature, and the results suggested that the three-miRNA signature (high risk and low risk)

predicted survival well, and was an independent prognostic factor in cervical cancer. To gain a deep insight into the molecular functions of three miRNAs, we predicted the target genes and

analyzed the related pathways and GO annotations. Abnormal signaling pathways play crucial roles in the pathogenesis and progression of cervical cancer. We found that three miRNAs could

regulate several key signaling pathways, including MAPK signaling pathway, AMPK signaling pathway, focal adhesion, cGMP-PKG signaling pathway, wnt signaling pathway, and mTOR signaling

pathway. Accumulating evidence has demonstrated that activation of MAPK signaling pathway is important in cervical cancer progression, invasion, and metastasis36. Yung M. M., _et al_.

reported that activation of AMP-activated protein kinase (AMPK), a metabolic sensor, hampers cervical cancer cell growth through blocking the Wnt/β-catenin signaling activity37. The

transformation of HPV expressing human keratinocytes requires activation of the Wnt pathway and that this activation may serve as a screening tool in HPV-positive populations to detect

malignant progression38. Moreover, it has been well established that the PI3K/Akt/mTOR signaling pathway plays a crucial role in cervical cancer development39, and inhibition of mTOR kinase

activity suppress tumor growth40. Therefore, further molecular investigations are needed to confirm these predictions, and it can provide new therapeutic interventions in cervical cancer.

Taken together, we identified three-miRNA signature as a potential prognostic predictor for cervical cancer patients. Further studies are needed to validate our findings in large sample

size, and further function investigation are also required to explore the molecular mechanism of these miRNAs in cervical cancer progression. MATERIALS AND METHODS DATA PROCESSING The raw

sequencing data and clinical information were downloaded from TCGA database (https://cancergenome.nih.gov/). The inclusion criteria were set as follows: (1) the sample with both miRNA

sequencing data and clinical information; (2) the sample with prognosis information. Finally, a total of 254 samples were enrolled in this study, including 251 cervical cancer tissues and 3

matched normal tissues. The detailed clinical characteristics and differentially expressed miRNAs were list in Table S2. The miRNA sequencing data were processed using R language package.

The differentially expressed miRNAs between cervical cancer and normal tissues were analyzed by limma package in R. The fold changes (FCs) in the expression of individual miRNA were

calculated and differentially expressed miRNAs with log2|FC| > 2.0 and _P_ < 0.05 were considered to be significant. ASSOCIATION OF DIFFERENTIALLY EXPRESSED MIRNAS AND PATIENT

PROGNOSIS The differentially expressed miRNA profiles were normalized by log2 transformed. The prognostic value of each differentially expressed miRNA was evaluated using Kaplan-Meier curve

and Log-rank method. The miRNAs that were significantly associated with overall survival were identified as prognostic miRNAs, and then subjected to a binary logistic regression analysis.

Subsequently, a prognostic miRNA signature was constructed, and the miRNA signature could calculate a risk score for each cervical cancer patient. With the miRNA signature, cervical cancer

patients were classified into high risk and low risk groups using the median risk score. Then, the differences in patients’ survival between the high risk group and low risk group were

evaluated by Kaplan-Meier method. THE TARGET GENE PREDICTION OF PROGNOSTIC MIRNA SIGNATURE The target genes of prognostic miRNAs were predicted using TargetScan (http://www.targetscan.org/),

miRDB (http://www.mirdb.org/miRDB/), PicTar (http://pictar.mdc-berlin.de/), and miRanda (http://www.microrna.org/) online analysis tools. To further enhance the bioinformatics analysis

reliability, the overlapping target genes were identified using Venn diagram. Then, the overlapping genes were analyzed by The Database for Annotation, Visualization and Integrated Discovery

(DAVID) bioinformatics tool (https://david.ncifcrf.gov/). DAVID is a web-based online bioinformatics resource that aims to provide a comprehensive set of functional annotation tools for the

investigators to understand the biological mechanisms associated with large lists of genes/proteins41. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway

enrichment analyses were then performed for the target genes. The _P_-value < 0.05 and gene count ≥ 3 were set as the cut-off criteria. STATISTICAL ANALYSIS The data were expressed as

mean ± standard deviation (SD). The expression levels of miRNAs in cervical cancer and matched normal tissues were analyzed by unpaired _t_ test. The chi-square and _t_ tests were performed

to assess the relationship between miRNA expression and clinical features. Kaplan-Meier survival analysis and univariate/multivariate Cox proportional hazard regression analysis were carried

out to compare each miRNA (low vs. high level) and prognostic miRNA signature (low vs. high risk). _P_ value less than 0.05 was considered as statistical significant. The statistical

analysis was performed using IBM SPSS Statistics software program version 22.0 (IBM Corp., NY, USA). REFERENCES * Catarino, R., Petignat, P., Dongui, G. & Vassilakos, P. Cervical cancer

screening in developing countries at a crossroad: Emerging technologies and policy choices. _World J Clin Oncol_ 6, 281–290 (2015). Article  PubMed  PubMed Central  Google Scholar  * Ferlay,

J. _et al_. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. _Int J Cancer_ 136, E359–386 (2015). Article  CAS  PubMed  Google Scholar  *

Lahue, B. J., Baginska, E., Li, S. S. & Parisi, M. Health technology assessment on cervical cancer screening, 2000–2014. _Int J Technol Assess Health Care_ 31, 171–180 (2015). Article 

PubMed  PubMed Central  Google Scholar  * Subramanian, S. _et al_. Cost of cervical cancer treatment: implications for providing coverage to low-income women under the Medicaid expansion for

cancer care. _Womens Health Issues_ 20, 400–405 (2010). Article  PubMed  Google Scholar  * Chen, L. & Kang, C. miRNA interventions serve as ‘magic bullets’ in the reversal of

glioblastoma hallmarks. _Oncotarget_ 6, 38628–38642 (2015). PubMed  PubMed Central  Google Scholar  * Hou, L. K. _et al_. Association of microRNA-33a Molecular Signature with Non-Small Cell

Lung Cancer Diagnosis and Prognosis after Chemotherapy. _PLoS One._ 12, e0170431 (2017). Article  PubMed  PubMed Central  Google Scholar  * Winter, J., Jung, S., Keller, S., Gregory, R. I.

& Diederichs, S. Many roads to maturity: microRNA biogenesis pathways and their regulation. _Nat Cell Biol_ 11, 228–234 (2009). Article  CAS  PubMed  Google Scholar  * Shenoy, A. &

Blelloch, R. H. Regulation of microRNA function in somatic stem cell proliferation and differentiation. _Nat Rev Mol Cell Biol_ 15, 565–576 (2014). Article  CAS  PubMed  PubMed Central 

Google Scholar  * Otsuka, K. & Ochiya, T. Genetic networks lead and follow tumor development: microRNA regulation of cell cycle and apoptosis in the p53 pathways. _Biomed Res Int._ 2014,

749724 (2014). Article  PubMed  PubMed Central  Google Scholar  * Munding, J. B. _et al_. Global microRNA expression profiling of microdissected tissues identifies miR-135b as a novel

biomarker for pancreatic ductal adenocarcinoma. _Int J Cancer_ 131, E86–95 (2012). Article  CAS  PubMed  Google Scholar  * Chandran, U. R. _et al_. TCGA Expedition: A Data Acquisition and

Management System for TCGA Data. _PLoS One._ 11, e0165395 (2016). Article  PubMed  PubMed Central  Google Scholar  * Arbyn, M. _et al_. Worldwide burden of cervical cancer in 2008. _Ann

Oncol._ 22, 2675–2686 (2011). Article  CAS  PubMed  Google Scholar  * Torre, L. A. _et al_. Global cancer statistics, 2012. _CA Cancer J Clin_ 65, 87–108 (2015). Article  PubMed  Google

Scholar  * Jemal, A. _et al_. Global cancer statistics. _CA Cancer J Clin_ 61, 69–90 (2011). Article  PubMed  Google Scholar  * Saslow, D. _et al_. American Cancer Society, American Society

for Colposcopy and Cervical Pathology, and American Society for Clinical Pathology screening guidelines for the prevention and early detection of cervical cancer. _CA Cancer J Clin_ 62,

147–172 (2012). Article  PubMed  PubMed Central  Google Scholar  * Iorio, M. V. & Croce, C. M. MicroRNA dysregulation in cancer: diagnostics, monitoring and therapeutics. A comprehensive

review. _EMBO Mol Med_ 4, 143–159 (2012). Article  CAS  PubMed  PubMed Central  Google Scholar  * Hausser, J. & Zavolan, M. Identification and consequences of miRNA-target

interactions–beyond repression of gene expression. _Nat Rev Genet_ 15, 599–612 (2014). Article  CAS  PubMed  Google Scholar  * Nagamitsu, Y. _et al_. Profiling analysis of circulating

microRNA expression in cervical cancer. _Mol Clin Oncol_ 5, 189–194 (2016). PubMed  PubMed Central  Google Scholar  * Fang, H., Shuang, D., Yi, Z., Sheng, H. & Liu, Y. Up-regulated

microRNA-155 expression is associated with poor prognosis in cervical cancer patients. _Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie_ 83, 64–69 (2016). Article  CAS

  Google Scholar  * Sun, L. _et al_. MicoRNA-425-5p is a potential prognostic biomarker for cervical cancer. _Annals of clinical biochemistry_ 54, 127–133 (2017). Article  PubMed  Google

Scholar  * Liu, P., Xin, F. & Ma, C. F. Clinical significance of serum miR-196a in cervical intraepithelial neoplasia and cervical cancer. _Genetics and molecular research: GMR_ 14,

17995–18002 (2015). Article  CAS  PubMed  Google Scholar  * Yin, Z. L. _et al_. Reduced expression of miR-503 is associated with poor prognosis in cervical cancer. _European review for

medical and pharmacological sciences_ 19, 4081–4085 (2015). PubMed  Google Scholar  * Luo, M., Shen, D., Wang, W. & Xian, J. Aberrant expression of microRNA-26b and its prognostic

potential in human cervical cancer. _International journal of clinical and experimental pathology_ 8, 5542–5548 (2015). CAS  PubMed  PubMed Central  Google Scholar  * Wang, C. & Jiang,

T. MicroRNA-335 represents an independent prognostic marker in cervical cancer. _Tumour biology: the journal of the International Society for Oncodevelopmental Biology and Medicine_ 36,

5825–5830 (2015). Article  CAS  Google Scholar  * Wang, N., Zhou, Y., Zheng, L. & Li, H. MiR-31 is an independent prognostic factor and functions as an oncomir in cervical cancer via

targeting ARID1A. _Gynecologic oncology._ 134, 129–137 (2014). Article  CAS  PubMed  Google Scholar  * Liang, H., Li, Y., Luo, R. Y. & Shen, F. J. MicroRNA-215 is a potential prognostic

marker for cervical cancer. Journal of Huazhong University of Science and Technology. Medical sciences = Hua zhong ke ji da xue xue bao. Yi xue Ying De wen ban = Huazhong keji daxue xuebao.

_Yixue Yingdewen ban_ 34, 207–212 (2014). CAS  Google Scholar  * Shen, S. N. _et al_. Upregulation of microRNA-224 is associated with aggressive progression and poor prognosis in human

cervical cancer. _Diagnostic pathology_ 8, 69 (2013). Article  CAS  PubMed  PubMed Central  Google Scholar  * Zhou, X., Yue, Y., Wang, R., Gong, B. & Duan, Z. MicroRNA-145 inhibits

tumorigenesis and invasion of cervical cancer stem cells. _Int J Oncol_ (2017). * Sathyanarayanan, A., Chandrasekaran, K. S. & Karunagaran, D. microRNA-145 modulates

epithelial-mesenchymal transition and suppresses proliferation, migration and invasion by targeting SIP1 in human cervical cancer cells. _Cell Oncol (Dordr)_ (2016). * Gunasekharan, V. &

Laimins, L. A. Human papillomaviruses modulate microRNA 145 expression to directly control genome amplification. _J Virol._ 87, 6037–6043 (2013). Article  CAS  PubMed  PubMed Central 

Google Scholar  * Kogo, R. _et al_. The microRNA-218~Survivin axis regulates migration, invasion, and lymph node metastasis in cervical cancer. _Oncotarget_ 6, 1090–1100 (2015). Article 

PubMed  Google Scholar  * Yamamoto, N. _et al_. Tumor suppressive microRNA-218 inhibits cancer cell migration and invasion by targeting focal adhesion pathways in cervical squamous cell

carcinoma. _Int J Oncol_ 42, 1523–1532 (2013). CAS  PubMed  PubMed Central  Google Scholar  * Jiang, Z. _et al_. MicroRNA-218 inhibits EMT, migration and invasion by targeting SFMBT1 and

DCUN1D1 in cervical cancer. _Oncotarget_ 7, 45622–45636 (2016). PubMed  PubMed Central  Google Scholar  * Korpal, M., Lee, E. S., Hu, G. & Kang, Y. The miR-200 family inhibits

epithelial-mesenchymal transition and cancer cell migration by direct targeting of E-cadherin transcriptional repressors ZEB1 and ZEB2. _J Biol Chem_ 283, 14910–14914 (2008). Article  CAS 

PubMed  PubMed Central  Google Scholar  * Shao, Y. _et al_. Prognostic role of tissue and circulating microRNA-200c in malignant tumors: a systematic review and meta-analysis. _Cell Physiol

Biochem_ 35, 1188–1200 (2015). Article  CAS  PubMed  Google Scholar  * Li, W. _et al_. Non-thermal plasma inhibits human cervical cancer HeLa cells invasiveness by suppressing the MAPK

pathway and decreasing matrix metalloproteinase-9 expression. _Sci Rep_ 6, 19720 (2016). Article  ADS  CAS  PubMed  PubMed Central  Google Scholar  * Yung, M. M., Chan, D. W., Liu, V. W.,

Yao, K. M. & Ngan, H. Y. Activation of AMPK inhibits cervical cancer cell growth through AKT/FOXO3a/FOXM1 signaling cascade. _BMC Cancer._ 13, 327 (2013). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Uren, A. _et al_. Activation of the canonical Wnt pathway during genital keratinocyte transformation: a model for cervical cancer progression. _Cancer Res._ 65,

6199–6206 (2005). Article  PubMed  Google Scholar  * Feng, T. _et al_. Growth factor progranulin promotes tumorigenesis of cervical cancer via PI3K/Akt/mTOR signaling pathway. _Oncotarget_

7, 58381–58395 (2016). PubMed  PubMed Central  Google Scholar  * Li, S. _et al_. The mTOR inhibitor AZD8055 inhibits proliferation and glycolysis in cervical cancer cells. _Oncol Lett_ 5,

717–721 (2013). CAS  PubMed  Google Scholar  * Jiao, X. _et al_. DAVID-WS: a stateful web service to facilitate gene/protein list analysis. _Bioinformatics._ 28, 1805–1806 (2012). Article 

CAS  PubMed  PubMed Central  Google Scholar  Download references ACKNOWLEDGEMENTS The study was supported and funded by the National Science Foundation of China (No. 81301835). We

acknowledge the staff members in Bioinformatics Department in China Medical University. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Bioinformatics, Key Laboratory of Cell

Biology, Ministry of Public Health and Key Laboratory of Medical Cell Biology, Ministry of Education, College of Basic Medical Science, China Medical University, Shenyang, China Bin Liang 

& Tianjiao Wang * Department of Clinical Laboratory, No. 202 Hospital of PLA, Shenyang, China Yunhui Li Authors * Bin Liang View author publications You can also search for this author

inPubMed Google Scholar * Yunhui Li View author publications You can also search for this author inPubMed Google Scholar * Tianjiao Wang View author publications You can also search for this

author inPubMed Google Scholar CONTRIBUTIONS Liang B. wrote the main manuscript and prepared all figures, Liang B. and Li Y. collect the data and performed the statistical analysis, and

Wang T. performed the bioinformatics analysis. CORRESPONDING AUTHOR Correspondence to Bin Liang. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare that they have no competing

interests. ADDITIONAL INFORMATION PUBLISHER'S NOTE: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. ELECTRONIC

SUPPLEMENTARY MATERIAL SUPPLEMENTARY INFORMATION TABLE S2 RIGHTS AND PERMISSIONS OPEN ACCESS This article is licensed under a Creative Commons Attribution 4.0 International License, which

permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to

the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless

indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or

exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Reprints

and permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Liang, B., Li, Y. & Wang, T. A three miRNAs signature predicts survival in cervical cancer using bioinformatics analysis. _Sci Rep_

7, 5624 (2017). https://doi.org/10.1038/s41598-017-06032-2 Download citation * Received: 20 February 2017 * Accepted: 06 June 2017 * Published: 17 July 2017 * DOI:

https://doi.org/10.1038/s41598-017-06032-2 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get shareable link Sorry, a shareable link is not

currently available for this article. Copy to clipboard Provided by the Springer Nature SharedIt content-sharing initiative