A novel serum microRNA-based identification and classification biomarker of human glioma

Abstract

Malignant glioma is one of the most common primary brain tumors that develop via multiple pathways and gene deregulation. MicroRNAs are involved in human cancer development and progression, and their serum expression profiles of glioma patients may be useful for classifying cancers. However, the profile and molecular mechanism of serum microRNAs for human glioma are poorly understood. Thus, it is crucial to analyze microRNA expression in human glioma serum to identify molecular subclasses and early stage of glioma. In this study, we performed microRNA alteration that contributes to glioma profile via analysis of The Cancer Genome Atlas RNA sequencing data and other independent Gene Expression Omnibus microarray data. We identified the glioma-associated novel microRNA as a key regulator of human glioma development and progression. The putative novel miR-1825 was validated by real-time polymerase chain reaction and its expression was significantly decreased in the serum of glioma patients compared with healthy controls. Patients with high miR-1825 expression had a longer survival rate. Interestingly, we found that miR-1825 expression levels were dependent on tumor size and pathological grading in glioma patients, but not associated with other factors including age and T classification. MicroRNA–Gene Ontology network indicated that miR-1825 may play an important role in the development of human glioma including apoptosis, cell proliferation, and invasion. In vitro assays of miR-1825 inhibit U87 cell proliferation and invasion and induce apoptosis. Furthermore, we provide evidence that the tumor-suppressive microRNA miR-1825 controls KLF2 expression. Reporter gene analyses revealed that both microRNAs directly targeted the 3′-untranslated region of KLF2 messenger RNA. These data demonstrated that miR-1825 expression in serum of human glioma was associated with tumorigenesis and miR-1825 may be used as a biomarker for identification of the pathological grade of glioma.

Keywords

MicroRNA serum biomarker glioma

Introduction

Small non-coding microRNAs (miRNAs) are a type of non-coding RNA that mediates post-transcriptional gene silencing by binding to the 3′-untranslated region of messenger RNA (mRNA).^1–5 Previous studies demonstrated that miRNAs are involved in cancer development and progression, and serum profiles of human cancer patients may be useful for early recognition and effective treatment. MiRNAs play important regulatory roles in various biological processes, including cellular proliferation, apoptosis, angiogenesis, and invasion.^6,7 Many studies have provided evidence that varieties of miRNAs are involved with the initiation and progression of human malignancies. Thus, serum miRNA profiles have been highlighted as new players in tumorigenesis by functioning as tumor suppressors and biomarkers.^8–10

Gliomas make up about 30% of all brain and central nervous system tumors and 80% of all malignant brain tumors.^11–13 Gliomas are further categorized according to their grade, which is determined by pathological evaluation of the tumor. Low-grade gliomas (World Health Organization (WHO) grade II) are well-differentiated (non-anaplastic); these tend to exhibit benign tendencies and portend a better prognosis for the patient. However, they have a uniform rate of recurrence and increase in grade over time, so should be classified as malignant. High-grade (WHO grades III–IV) gliomas are undifferentiated or anaplastic; these are malignant and carry a worse prognosis.^14–16 Despite intense efforts to optimize the treatment of gliomas, the outcomes of high-grade glioma patients are still frustrating. The conventional treatment consists of surgical resection followed by radiotherapy and adjuvant chemotherapy with temozolomide, an oral alkylating agent. The causes and progress of gliomas have been investigated extensively. However, the median survival is 12–15 months, with survival rates of 20% and 5% at 2 and 5 years, respectively.¹⁷

Early recognition and effective treatment are vital for management of human glioma. To conduct a comprehensive characterization of deregulated miRNAs in glioma, we analyzed The Cancer Genome Atlas (TCGA) glioblastoma multiforme and brain lower grade glioma miRNA-seq data and glioma microarray data including GSE25631, GSE41915, and GSE37737 from Gene Expression Omnibus (GEO) datasets. The use of this powerful bioinformatics has resulted in the identification of a novel serum biomarker for human glioma, miR-1825, which plays an important role in the development of human glioma.

Materials and methods

RNA sequencing analysis

Glioma miRNA expression data were downloaded from the TCGA Data Portal (https://gdc-portal.nci.nih.gov/search/s) and GEO dataset (https://www.ncbi.nlm.nih.gov/geo/). Raw data files were normalized at transcript and gene levels by means of the robust multi-array average (RMA) method (RMA workflow). Median levels of transcript expressions were calculated. The BAM files and normalized probe-level intensity files were downloaded from TCGA and GEO databases, respectively.

Patients and RNA isolation

The blood samples of this study contained 57 human gliomas and 57 age-matched healthy controls who were enrolled from March 2012 to May 2013 at the Suining Central Hospital. The clinical characteristics of the glioma patients are described in detail in Table 1. Blood samples (3 mL) were obtained from the elbow vein from fasting subjects without anticoagulant. After centrifugation at 5000 r/min for 7 min, the supernatant was retained in cryopreservation tubes and stored at −80°C until use. For quantitative real-time polymerase chain reaction (qRT-PCR), each subject provided 300 µL of serum. Serum total RNA was extracted by miRCURY™ RNA Isolation Kit—Biofluids (Exiqon, Denmark) according to the manufacturer’s instructions.

Table 1.

Correlation between the clinicopathological features and expression of CAPG protein.

Characteristics	CAPG (%)		p value
	Low expression	High expression
Age (years)			0.735
<45	10 (10.0)	7 (74.4)
≥45	17 (7.7)	3 (77.78)
Tumor size			0.025
<3	7 (22.3)	5 (77.7)
≥3	23 (74.4)	2 (25.5)
Pathological grading			0.012
I	6 (21.4)	3 (87.5)
II	12 (9.0)	2 (79.6)
III	13 (9.6)	1 (91.0)
T classification			0.751
T1	1 (27.7)	6 (72.3)
T2	7 (40.4)	5 (59.6)
T3	9 (41.6)	7 (58.4)
N classification			0.052
N0	7 (36.9)	9 (63.1)
N1–3	17 (45.4)	14 (54.6)

Chi-square test (*p < 0.05).

qRT-PCR assay

Reverse transcription of miRNA was carried out with the Serum/Plasma Focus microRNA PCR Panel, 96 well (V4.CFX), and mRNA was reverse transcribed into complementary DNA (cDNA) using PrimeScript RT Reagent Kit with gDNA Eraser (TaKaRa, Japan). The qRT-PCR assay was performed using the SYBR Premix ExTaqII (TLi RNaseH Plus; TaKaRa) with a CFX96 Real-Time PCR Detection System (Bio-Rad, USA). Relative RNA expression was calculated by the 2-DDCt method after normalizing expression levels of KLF2 mRNA to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA and miRNA to RNU6B.

Cell proliferation and apoptosis assays

Cell proliferation ability was examined using a Cell Counting Kit 8 (CCK-8; Dojindo, Japan). U87 cells transfected with control or miR-1825 mimics were harvested 48 h after transfection by trypsinization. After the double staining with fluorescein isothiocyanate (FITC)-Annexin V and propidium iodide (PI), the cells were analyzed with a flow cytometer.

Luciferase reporter assays

HEK293 cells, seeded into six-well plates, were cotransfected with 1 mg of the reporter gene constructs (pKLF2-3.0, pKLF2-3.1, pKLF2-3.2, and pKLF2-3.0 Mut) and 2.5 nmol/L of miScript miRNA mimics. After 48 h, cells were lysed and analyzed for Renilla and Firefly luciferase activity using the dual-luciferase assay system (Promega, Madison, USA). Each transfectant was assayed in triplicates. Activity of Renilla luciferase was normalized to Firefly luciferase.

Statistical analysis

For microarray analysis, differentially expressed genes were confirmed using a p value threshold and false discovery rate (FDR) analysis. The threshold of truly significant miRNA was taken to be p value less than 0.05 and FDR value less than 0.05. The statistical analysis was performed with the software of SPSS version 18.0 for Windows. All the data were expressed as mean ± standard deviation (SD). The statistical significance was evaluated by analysis of variance (ANOVA) or two-tailed t-test, and the results were considered significant at a p value less than 0.05.

Results

MiR-1825 is specifically down-expressed in serum of human glioma

To identify differently expressed miRNAs that are involved in glioma tumorigenesis, we used an integrative analysis of TCGA glioblastoma multiforme and brain lower grade glioma miRNA-seq data and glioma microarray data including GSE25631, GSE41915, and GSE37737 from GEO datasets. We identified 175 miRNAs deregulated in the TCGA data, 77 in GSE25631 datasets, and 57 in GSE41915/GSE37737 datasets (fold change > 4.0, q < 0.05; Figure 1(a)). We selected three miRNAs that showed decreased expression as these miRNAs may be used as biomarkers for early diagnosis or therapeutic targets (Figure 1(b)). Then, we detected the expression levels of three miRNAs in 17 pairs of glioma and age-matched healthy control serums using qRT-PCR. We found that the expression of miR-1825 was significantly decreased in glioma serum as compared with healthy controls (Figure 1(c)). The expression of MiR-1825 was further validated in 57 patients with other cancers including 15 liver cancer patients, 15 breast cancer patients, 17 gastric cancer patients, and 10 cervical cancer patients (Figure 1(d)). The results showed that the expressions of miR-1825 were significantly decreased in glioma patients as compared with other cancer patients.

Figure 1.

MiR-1825 is down-expressed in serum of human glioma. (a) Hierarchical clustering analysis of miRNAs that were differentially expressed in glioma patients and normal control from TCGA and GEO dataset. (b) Overlap of deregulated miRNAs in TCGA data and GEO datasets. (c) MiR-1825 expression was analyzed by qRT-PCR in the serum of glioma and age-matched healthy controls (n = 17). (d) Analyses of miR-1825 expression levels in serum of liver cancer, breast cancer, gastric cancer, and cervical cancer (**p < 0.01).

MiR-1825 expression is correlated with glioma progression and poor prognosis

To investigate miR-1825 expression with respect to human glioma progression, the miR-1825 expression in blood samples of 37 human glioma and 37 age-matched healthy controls was examined by qRT-PCR analysis. As shown in Figure 2(a), miR-1825 serum expression level was significantly reduced in glioma cancer patients compared with healthy controls. All patients were divided into high and low miR-1825 expression level groups according to the median value. Kaplan–Meier survival analysis showed that the overall survival rates for the high miR-1825 expression level group were lower than those in the low miR-1825 expression level group (Figure 2(b)). Interestingly, we found that miR-1825 expression levels were dependent on tumor size (p = 0.025) and pathological grading (p = 0.012) in glioma patients, but not associated with other factors including age and T classification as shown in Table 1. Kaplan–Meier survival analysis showed that low miR-1825 expression also predicts shorter overall survival of glioma patients (Table 1). These data showed that miR-1825 might act as tumor-suppressive factor during the glioma progression.

Figure 2.

Expression levels of the miR-1825 (a) in serum of human glioma patients (n = 37) and healthy controls (n = 37) by RT-PCR validation. (b) Kaplan–Meier survival analysis of overall survival in glioma patients based on miR-1825 expression from TCGA datasets.

Co-expression miRNA-gene-network analysis

To investigate the biological mechanism and functions of miR-1825, its target genes were predicted by starBase, TargetScan, miRBase, and miRanda. The results showed 31 target genes for miR-1825 (Figure 3(a)). We performed Gene Ontology (GO) enrichment analyses and constructed a miRNA-gene network which indicates the pivotal regulatory functions of miR-1825 and their target genes. Gene networks were constructed as shown in Figure 4(a). Furthermore, we built a miRNA-GO network to understand the key mechanism of miR-1825 (Figure 3(b)). These data indicated that miR-1825 may play an important role in the development of human glioma including apoptosis, cell proliferation, and invasion.

Figure 3.

Construction of co-expression miRNA-gene-network. (a) MiRNA–gene network. Circular nodes represent genes, and square nodes represent miRNAs. (b)The top five key genes in the network were KLF2, PRSS8, DDX3X, TSHZ2, and KCNH1.

Figure 4.

MiR-1825 inhibits cell proliferation and invasion and induces apoptosis. (a) Transfection efficiency of miR-1825 was verified by qRT-PCR. (b) CCK-8 assays were used to determine the cell viability of control or miR-1825 mimics–transfected U87 cells. (c) Transwell assays showed that miR-1825 over-expression inhibits cell invasion. (d) Flow cytometry analysis of the effect of miR-1825 on cell apoptosis (**p < 0.01).

MiR-1825 inhibits cell proliferation and invasion and induces apoptosis

To investigate the function of miR-1825 in regulating cancer cell phenotype, we first transfected specific miR-1825 mimics into U87 cells. Transfection efficiency was verified by qRT-PCR (Figure 4(a)). Cell counting assays showed that over-expression of miR-1825 impaired cell proliferation (Figure 4(b)). As our GO and pathway results showed that miR-1825 exerts a tumor-suppressive effect, we determined whether miR-1825 was involved in the regulation of cell apoptosis by performing flow cytometry. We found that over-expression of miR-1825 significantly induced glioma cell apoptosis (Figure 4(d)). Transwell invasion assays showed that over-expression of miR-1825 dramatically decreased cell invasion (Figure 4(c)).

MiR-1825 repressing KLF2 expression by binding to 3′-UTR

To address the mechanism of miR-1825 involved in the regulation of human glioma, we screened the conserved miR-1825-binding sites. The TargetScan database predicted binding of miR-1825 to the 3′-UTR of KLF2 (Figure 5(a)). KLF2 has been identified as tumor suppressors by inducing cell-cycle arrest and apoptosis upon ectopic expression in malignant cells. To determine the role of miR-1825 in the regulation of KLF2 expression, we generated reporter gene constructs, fusing the KLF2 3′-UTR downstream and two deletion variants to a luciferase reporter gene; the construct was named as pKLF2-3.0/3.1/3.2. These reporter constructs were then transfected into HEK293 cells together with miR-1825 mimics. Transfection of pKLF2-3.0 and pKLF2-3.1 in combination with the miR-1825 mimics revealed a clear reduction in luciferase activity for miR-1825 and reduced reporter gene expression (Figure 5(b)). In contrast, miR-1825 did not negatively influence the activity of the pKLF2-3.3 construct lacking the predicted miR-1825 binding site (Figure 5(c)). Furthermore, we constructed the miR-1825 seed sequence–binding site mutation, resulting in pKLF2-3.1 Mut (Figure 5(d)). Consistent with this mutation, the negative effect of miR-1825 mimics on reporter gene expression was abrogated.

Figure 5.

MiR-1825 binds to the 3′-UTR of KLF2 mRNA. (a) Scheme of the KLF2 3′-UTR containing luciferase constructs (pKLF2-3.0, pKLF2-3.1, and pKLF2-3.2). The black dot indicates the location of the predicted miR-1825 binding site. (b) Plasmid reporter gene constructs were cotransfected with the indicated control or miR-1825 mimics into HEK293 cells. After 48 h, lysates from transfectants were analyzed for luciferase activity. (c) A point mutation was introduced into the KLF2 3′-UTR of pKLF2-3.1 to destroy the predicted miR-1825 binding motif. The mutated plasmid was designated pKLF2-3.0 Mut. (d) Luciferase activity of pKLF2-3.0 Mut is not affected by transfection of control or miR-1825 mimics (*p < 0.05).

Discussion

MiRNAs are small non-coding RNAs that regulate gene expression and multiple cellular processes including cell proliferation, stem cell differentiation, and epithelial–mesenchymal transition.^18–20 Malignant glioma is a common cancer with very poor prognosis due to its invasiveness, tumor heterogeneity, and resistance to chemotherapy. Depending on the genes targeted, miRNAs can act as tumor suppressors or oncogenes. Recent evidence shows deregulated expression of miRNAs in human glioma, including upregulation of miR-215, miR-296, and miR-486 and downregulation of miR-376 and miR-182.^21–23 Efforts are focused on characterizing the molecular biomarker of these tumors to diagnose them and define new targets amenable to therapy. So, early diagnosis and effective treatments are vital for management of human glioma. Previous studies have reported a network of interacting tumor biomarkers specifically disrupted in glioblastoma that include neurofibromatosis type 2 (NF2) and Na/H exchanger-3 regulatory factor-1 (NHERF1). Comprehensive analysis of miRNA expression between glioma patients and healthy controls will help us to better understand the roles of miRNAs in the development of the disease as well as to find novel biomarkers for human glioma diagnosis and prognosis for individualized therapy.^24,25

In this study, we aimed at miRNAs expression profile using TCGA glioblastoma multiforme and brain lower grade glioma miRNA-sequence data and glioma microarray datasets. We selected three miRNAs that showed decreased expression as these miRNAs may be used as biomarkers for early diagnosis or therapeutic targets. The expression of MiR-1825 was further validated in 57 patients with other cancers, including 15 liver cancer patients, 15 breast cancer patients, 17 gastric cancer patients, and 10 cervical cancer patients. We demonstrated that the expressions of miR-1825 were significantly decreased in glioma patients as compared with other cancer patients. MiR-1825 serum expression level was significantly reduced in glioma cancer patients compared with healthy controls. All patients were divided into high and low miR-1825 expression level groups according to the median value. Kaplan–Meier survival analysis showed that the overall survival rates for the high miR-1825 expression level group were lower than those in the low miR-1825 expression level group. Interestingly, we found that miR-1825 expression levels were dependent on tumor size and pathological grading in glioma patients. MiRNA-GO-network indicated that miR-1825 may play an important role in the development of human glioma, including apoptosis, cell proliferation, and invasion. In vitro assays of miR-1825 inhibit U87 cell proliferation and invasion and induce apoptosis. Furthermore, we provide evidence that the tumor-suppressive miRNA miR-1825 controls KLF2 expression. Reporter gene analyses revealed that both miRNAs directly targeted the 3′-UTR of KLF2 mRNA.

In conclusion, our study provide profiling the miRNAs expression signatures by analyzing a cohort of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. MiR-1825 is the first one to be selected as a potential biomarker to glioma progression and define new targets amenable to therapy.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Health and Family Planning Commission research of Sichuan province (no. 150245).

References

Tang

Liu

Wang

. Interaction of hsa-miR-381 and glioma suppressor LRRC4 is involved in glioma growth. Brain Res 2011; 1390: 21–32.

Krell

Stebbing

Frampton

. The role of TP53 in miRNA loading onto AGO2 and in remodelling the miRNA-mRNA interaction network. Lancet 2015; 385(Suppl 1): S15.

Baumann

. Plant cell biology: mobile miRNAs for stem cell maintenance. Nat Rev Mol Cell Biol 2013; 14(3): 128.

Pereira

Rodrigues

Borralho

. Delivering the promise of miRNA cancer therapeutics. Drug Discov Today 2013; 18(5–6): 282–289.

Ahmad

Bao

. Epigenetic regulation of miRNA-Cancer Stem Cells nexus by Nutraceuticals. Mol Nutr Food Res 2014; 58(1): 79–86.

Wei

Wang

Zhou

. MicroRNA-146a contributes to SCI recovery via regulating TRAF6 and IRAK1 expression. BioMed Res Int 2016; 2016: 4013487.

Flemming

. Heart failure: targeting miRNA pathology in heart disease. Nat Rev Drug Discov 2014; 13(5): 336.

Zhou

Cao

Zhu

. Phage-mediated counting by the naked eye of miRNA molecules at attomolar concentrations in a Petri dish. Nat Mater 2015; 14(10): 1058–1064.

Song

Walentek

Sponer

. MiR-34/449 miRNAs are required for motile ciliogenesis by repressing cp110. Nature 2014; 510(7503): 115–120.

10.

Creasey

Zhai

Borges

. MiRNAs trigger widespread epigenetically activated siRNAs from transposons in Arabidopsis. Nature 2014; 508(7496): 411–415.

11.

Van Meir

Hadjipanayis

Norden

. Exciting new advances in neuro-oncology: the avenue to a cure for malignant glioma. CA Cancer J Clin 2010; 60(3): 166–193.

12.

Buckner

Chakravarti

Curran

Radiation plus chemotherapy in low-grade glioma. N Engl J Med 2016; 375(5): 490–491.

13.

Ducray

Marie

Sanson

. IDH1 and IDH2 mutations in gliomas. N Engl J Med 2009; 360(21): 2248–2249; author reply 2249.

14.

Markert

. The role of early resection vs biopsy in the management of low-grade gliomas. JAMA 2012; 308(18): 1918–1919.

15.

Quail

Bowman

Akkari

. The tumor microenvironment underlies acquired resistance to CSF-1R inhibition in gliomas. Science 2016; 352(6288): aad3018.

16.

Friedmann-Morvinski

Bushong

. Dedifferentiation of neurons and astrocytes by oncogenes can induce gliomas in mice. Science 2012; 338(6110): 1080–1084.

17.

Ying

Shen

Zhan

. A stabilized peptide ligand for multifunctional glioma targeted drug delivery. J Control Release 2016; 243: 86–98.

18.

Berindan-Neagoe

Monroig Pdel

Pasculli

. MicroRNAome genome: a treasure for cancer diagnosis and therapy. CA Cancer J Clin 2014; 64(5): 311–336.

19.

Cancer Genome Atlas Research Network Brat

Verhaak

. Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas. N Engl J Med 2015; 372(26): 2481–2498.

20.

Janssen

Reesink

Lawitz

. Treatment of HCV infection by targeting microRNA. N Engl J Med 2013; 368(18): 1685–1694.

21.

Zhang

Zou

. miR-215 promotes malignant progression of gastric cancer by targeting RUNX1. Oncotarget 2016; 7(4): 4817–4828.

22.

Wang

Zheng

. miR-296 inhibits proliferation and induces apoptosis by targeting FGFR1 in human hepatocellular carcinoma. FEBS Lett 2016; 590: 4252–4262.

23.

Iwasaki

Yamamoto

Inanaga

. MiR-142-5p and miR-486-5p as biomarkers for early detection of chronic antibody-mediated rejection in kidney transplantation. Biomarkers 2017; 22: 45–54.

24.

Kung

Zaki

Ravi

. Utility of circulating serum miRNAs as biomarkers of early cartilage degeneration in animal models of post-traumatic osteoarthritis and inflammatory arthritis. Osteoarthritis Cartilage 2017; 25: 426–434.

25.

Liu

Wang

Borlak

. Mechanistically linked serum miRNAs distinguish between drug induced and fatty liver disease of different grades. Sci Rep 2016; 6: 23709.