Open Access

miR‑592 acts as an oncogene and promotes medullary thyroid cancer tumorigenesis by targeting cyclin‑dependent kinase 8

Corrigendum in: /10.3892/mmr.2021.12312

  • Authors:
    • Ting Liu
    • Jingjing Meng
    • Yu Zhang
  • View Affiliations

  • Published online on: July 30, 2020     https://doi.org/10.3892/mmr.2020.11392
  • Pages: 3316-3326
  • Copyright: © Liu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Medullary thyroid carcinoma (MTC) is a relatively rare subtype of thyroid cancer, accounting for 5‑10% of all cases of thyroid cancer worldwide. Due to the current lack of knowledge regarding the tumorigenesis of MTC, the clinical treatment of MTC remains a challenge. It has been reported that microRNAs (miRNAs) regulate the progression of MTC; however, the regulatory network of miRNAs and the exact underlying mechanisms are not completely understood. In the present study, an miRNA expression profile (GSE40807), consisting of 80 samples, was downloaded and analyzed using Gene Expression Omnibus‑2R to identify differentially expressed miRNAs between MTC and normal samples. miR‑592 expression levels were significantly increased in MTC tissues and cell lines compared with normal tissues and cell lines. Patients with high miR‑592 expression levels exhibited a less favorable prognosis compared with patients with low miR‑592 expression. The results suggested that miR‑592 overexpression promoted TT and MZ‑CRC‑1 cell proliferation in vitro. In addition, miR‑592 negatively regulated cyclin‑dependent kinase 8 (CDK8) via targeted binding in MTC cells. Moreover, co‑transfection of CDK8 overexpression plasmid and miR‑592 mimic reversed miR‑592‑mediated MTC cell proliferation. In conclusion, miR‑592 may serve as an oncogene in MTC by decreasing the expression of CDK8, indicating that the miR‑592/CDK8 axis might serve as a promising therapeutic target for MTC.

Introduction

Thyroid cancer is the most common subtype of endocrine cancer worldwide, with an increasing incidence level (1). Thyroid cancer can be divided into multiple subtypes, the majority of which originate from follicular cells. Medullary thyroid cancer (MTC), which accounts for 5–10% of all cases of thyroid cancer, is the only type that originates from parafollicular C cells (2,3). Patients with MTC with an obvious thyroid nodule frequently present with cervical metastases and ~13% present with distant metastases (4,5). The 10-year MTC-specific mortality rate ranges from 13.5–38% worldwide (6). The clinical stage at the time of diagnosis and the probability of complete surgical removal of the tumor are the two most important determinants for the successful treatment of MTC (7). The prognostic factors of patients with MTC who undergo surgical resection include tumor volume, metastases and location, age, calcitonin level and carcinoembryonic antigen doubling times (8). In the last decade, advancements have been made in the diagnosis and therapeutic treatment of human non-MTC; however, the physiopathology of MTC is not completely understood (9,10). Therefore, exploring molecular targets that may improve the accuracy of MTC diagnosis is important.

MicroRNAs (miRNA) are small single-stranded non-coding RNAs, ~22 nucleotides in length, that widely exist in mammalian cells (11,12). Due to the limitations of research technologies, miRNAs were initially considered to be noise of transcription without biological functions (13). Progression in next-generation sequencing has made it possible to identify the expression profiles of miRNAs, thereby allowing their functions during the pathogenesis of various human diseases to be investigated (14). At present, the regulatory role of miRNAs on gene expression has been well demonstrated, with increasing evidence indicating that miRNAs can degrade target mRNAs or repress translation (15). miRNA dysregulation is a critical event during the initiation and progression of tumors (16,17), and recently, it has also been reported that miRNAs are implicated during the tumorigenesis of MTC (18); however, the roles of the majority of miRNAs in MTC are not completely understood.

To identify unique miRNAs associated with the tumorigenesis of MTC, differentially expressed miRNAs in the GSE40807 dataset were assessed using the Gene Expression Omnibus (GEO)2R method. miR-592 expression was increased in MTC samples compared with normal samples, which indicated that miR-592 may serve a role during the tumorigenesis of MTC. It has been previously reported that miR-592 affects the development of various human tumors, including glioma and acute myeloid leukemia, as well as gastric and breast cancer (1922); however, the role and mechanism of miR-592 during MTC is not completely understood. Therefore, the present study aimed to investigate the physiological functions and potential mechanisms underlying miR-592 during MTC tumorigenesis.

Materials and methods

Microarray dataset

The MTC-associated miRNA GEO dataset GSE40807, consisting of 80 samples, was downloaded from the GEO database (www.ncbi.nlm.nih.gov/geo) (23). Differentially expressed miRNAs in GSE40807 were identified using GEO2R.

MTC tumor samples

A total of 20 paired cancer and normal tissue specimens (distance from tumor margin, 5 cm) were collected from patients with MTC (mean age, 66.53±12.48 years; 8 female patients and 12 male patients) who were diagnosed at the Affiliated Wuhan Central Hospital of Tongji Medical College between March 2015 and October 2019. Tissue samples were stored in liquid nitrogen until further analysis. The present study was approved by the Ethics Committee of The Affiliated Wuhan Central Hospital of Tongji Medical College, Huazhong University of Science and Technology. Written informed consent was obtained from each participant. The basic clinicopathological features of the 20 patients with MTC are presented in Table I. Moreover, the number of patients with different pathological grade, tumor size, T stage, N stage, M stage and TNM stage was determined.

Table I.

Basic clinicopathological features of patients with MTC.

Table I.

Basic clinicopathological features of patients with MTC.

ParametersPatients with MTC (n=20)
Age, years66.53±12.48
Sex, male/female12/8
Pathological grade
  Well differentiation4 (20%)
  Moderate differentiation13 (65%)
  Poor differentiation3 (15%)
Tumor size, cm
  <511 (55%)
  ≥59 (45%)
T stage, n (%)
  T14 (20)
  T22 (10)
  T35 (25)
  T49 (45)
N stage, n (%)
  N012 (60)
  N1a3 (15)
  N1b2 (10)
  N1c1 (5)
  N2a1 (5)
  N2b1 (5)
M stage, n (%)
  M019 (95)
  M1a1 (5)
TNM stage, n (%)
  II3 (15)
  IIA8 (40)
  IIIB5 (25)
  IIIC3 (15)
  IVA1 (5)

[i] MTC, medullary thyroid cancer.

Cell lines

The immortalized normal thyroid follicular NThy-ori-3.1 cell line, and the MTC TT and MZ-CRC-1 cell lines were purchased from the American Type Culture Collection. Cells were cultured in RPMI-1640 (Gibco; Thermo Fisher Scientific, Inc.) containing 10% fetal bovine serum (Gibco; Thermo Fisher Scientific, Inc.) at 37°C and 5% CO2.

RNA transfection

miR-592 mimic (5′-UGUAGUAGCGUAUAACUGUGUU-3′), scramble mimic (5′-UUCUCCGAACGUGUCACGUTTACGUGACACGUUCGGAGAATT-3′) and the CDK8 plasmid were designed and obtained from Shanghai GenePharma Co., Ltd. TT and MZ-CRC-1 cells were seeded (1×105 cells/well) into 6-well plates and cultured at 37°C for 8 h. Subsequently, cells were transfected with 200 µl mimic (100 nM) or scramble (100 nM) or 1 µg plasmid using Lipofectamine® 3000 (Invitrogen; Thermo Fisher Scientific, Inc.), according to the manufacturer's protocol. At 48 h post-transfection, cells were used for subsequent experiments.

RNA extraction and quantitative real-time PCR (RT-qPCR) assay

Total RNA was extracted from MTC tissue samples and cells using TRIzol® reagent (Invitrogen; Thermo Fisher Scientific, Inc.). RNA quality was determined using a NanoDrop 2000c spectrophotometer (Thermo Fisher Scientific, Inc.). Total RNA (3 µg) was reverse transcribed into cDNA using the Bestar qPCR RT kit (DBI Bioscience; cat. no. DBI-2220). The temperature protocol used for reverse transcription was 37°C for 15 min and 98°C for 5 min. Subsequently, qPCR was performed using the Bestar qPCR MasterMix (DBI Bioscience) and an ABI 7500 system (Applied Biosystems; Thermo Fisher Scientific, Inc.), according to the manufacturer's protocol. The following thermocycling conditions were used for qPCR: 95°C for 2 min; 95°C for 10 sec, 60°C for 34 sec, 72°C for 30 sec; and the solubility curve was obtained at 98°C. The primers used for qPCR are presented in Table II. miRNA and mRNA expression levels were quantified using the 2−∆∆Cq method (24) normalized to the internal reference genes U6 and GAPDH, respectively.

Table II.

Sequences of primers used for reverse transcription-quantitative PCR.

Table II.

Sequences of primers used for reverse transcription-quantitative PCR.

GeneSequence (5′-3′)
GAPDHF: TGTTCGTCATGGGTGTGAAC
R: ATGGCATGGACTGTGGTCAT
miR-592F: CCATGACATTGTGTCAATATGCGA
R: CGTCATGATGTTGCGTCACC
SCGB2A2F: GAACACCGACAGCAGCA
R: TCTCCAATAAGGGGCAGCC
U6F: CTCGCTTCGGCAGCACA
R: AACGCTTCACGAATTTGCGT
LINC00632F: CACGCCTGTTATCCC
R: CAACCTCCGCCTCTT
CREB3L3F: CAGTCAGCTCAAGAAAGCAGG
R: TGGTTCTGGGCAGTACACG
OR4F4F: ATAGCCATGGGCTTTGACAG
R: TGGGACCACAGAAGGGTAAG
CCDC149F: CTCTCCAAGGAGCTGGACAC
R: TCCAAGCCTTTGCTGAAGTT
CDK8F: GCCGGTTGTCAAATCCCTTAC
R: TGTGACTGCTGTCTTGATTCCCT

[i] miR, microRNA; F, forward; R, reverse; SCGB2A2, secretoglobin family 2A member 2; LINC00632, long intergenic non-protein coding RNA 632; CREB3L3, cAMP responsive element binding protein 3 like 3; OR4F4, olfactory receptor family 4 subfamily F member 4; CCDC149, coiled-coil domain containing 149; CDK8, cyclin-dependent kinase 8.

Data analysis

The data used for the analysis of miR-592 or CDK8 expression and the overall survival of patients with high and low miR-592 or CDK8 expression were downloaded from starBase (version 3; starbase.sysu.edu.cn/panCancer.php). Kaplan-Meier plots (www.kmplot.com) was applied to analyze the association between overall survival and miR-592 or CDK8 expression in patients with MTC. Kalpan-Meier plots were compared using the log-rank test.

Western blotting

Total protein was extracted from transfected TT and MZ-CRC-1 cells using RIPA buffer (cat. no. R0278; Sigma-Aldrich; Merck KGaA). Total protein was quantified using a BCA kit (Pierce; Thermo Fisher Scientific, Inc.). Subsequently, proteins (30 µg) were separated via 10% SDS-PAGE and transferred to nitrocellulose membranes (EMD Millipore). Following blocking with 5% skim milk at room temperature for 1.5 h, the membranes were incubated at 4°C overnight with anti-CDK8 (1:1,000; cat. no. ab224828; Abcam) and anti-GAPDH (1:2,000; cat. no. ab8245; Abcam) primary antibodies. Following washing with PBS, the membranes were incubated with anti-mouse or anti-rabbit horseradish peroxidase-conjugated secondary antibodies (cat. nos. SC-2005 and SC-2004, respectively) at room temperature for 1 h. Protein bands were visualized using ECL Plus reagent (Beyotime Institute of Biotechnology). GAPDH was used as the loading control. Protein expression levels were quantified using Quantity One software (version 4.62; Bio-Rad Laboratories, Inc.).

MTT assay

TT and MZ-CRC-1 cell viability was determined using the MTT assay at 12, 24, 36 and 72 h post-transfection. Briefly, MTC cells in the exponential growth phase were collected and seeded (3×104 cells/well) into 96-well plates. Following incubation at 37°C for 8 h, 20 µl MTT solution was added to each well and incubated at 37°C for 4 h. Subsequently, 200 µl DMSO (cat. no. D4540; Sigma-Aldrich; Merck KGaA) was added to each well at room temperature for 15 min. The absorbance of each well was determined at a wavelength of 490 nm using a microplate reader.

Colony formation assay

For the cell colony formation assay, at 24 h post-transfection, TT and MZ-CRC-1 cells were seeded (3×103 cells/dish) into 35 mm culture dishes containing RPMI-1640 and cultured for two weeks at 37°C with 5% CO2 and 95% O2. The visible colonies were fixed in 4% paraformaldehyde at room temperature for 10 min and stained with 10% Giemsa solution (cat. no. G4507; Sigma-Aldrich; Merck KGaA) at room temperature for 10 min. Subsequently, the number of colonies was manually counted using a light microscope (magnification, ×10).

Cell cycle analysis

TT and MZ-CRC-1 cells in the exponential growth phase were collected and fixed using ethanol (75%) overnight at 4°C. Cells were washed with pre-cooled PBS to remove the excessive ethanol and stained with 200 µl PI at 37°C for 30 min. Subsequently, cells were stained with 100 µl RNaseA staining buffer (BD Pharmingen) at room temperature for 20 min. Cell cycle was detected by flow cytometry using a FACSCalibur flow cytometer (BD Biosciences). The number of cells in G0/G1, S and G2/M phases was calculated using ModFit software (version 4.1; Verity Software House, Inc.).

Functional analysis

The functional roles of miR-592 target genes were analyzed using the Database for Annotation, Visualization and the Integrated Discovery (DAVID; version 6.8; david.ncifcrf.gov/home.jsp). In addition, integration of the Gene Ontology (GO) (24,25) and Kyoto Encyclopedia of Genes and Genomes (KEGG) (2628) databases was performed.

Dual-luciferase reporter assay

The target genes of miR-592 were identified by TargetScan (version 7.1; www.targetscan.org/vert_71) and the interaction between miR-592 and CDK8 was verified using StarBase (version 2.0; starbase.sysu.edu.cn). The interaction between miR-592 and CDK8 in MTC cells was examined using a dual-luciferase reporter assay. The wild-type (WT) and mutant (Mut) CDK8 3′-untranslated region (UTR) containing miR-592 complementary sequences were cloned into the pGL3 vector (Promega Corporation) to form CDK8-WT and CDK8-Mut luciferase plasmids, respectively. TT and MZ-CRC-1 cells (1×105 cells/well) were plated in a 6-well plate and cultured for 8 h. Subsequently, cells were co-transfected with 100 ng CDK8-WT or 100 ng CDK8-Mut and 20 nM miR-592 mimic or 20 nM scramble mimic using Lipofectamine® 3000 (Invitrogen; Thermo Fisher Scientific, Inc.) according to the manufacturer's protocol. Following incubation at 37°C for 48 h, luciferase activities were detected using the Dual-Luciferase Assay System (Promega Corporation), according to the manufacturer's protocol. Firefly luciferase activity was normalized to Renilla luciferase activity.

Gene regulatory network

Based on previous studies (2931), the gene regulatory network of CDK8 was analyzed and identified using GENEVESTIGATOR® (genevestigator.com/gv).

Statistical analysis

Data are presented as the mean ± SD. Statistical analyses were performed using GraphPad Prism software (version 7; GraphPad Software, Inc.). Differences between two groups were analyzed using the paired (comparisons between paired and normal tissue samples) or unpaired (other data) Student's t-test. Differences among multiple groups were analyzed using one-way ANOVA with Tukey's post hoc test. P<0.05 was considered to indicate a statistically significant difference.

Results

miR-592 expression is increased during MTC

To identify miRNAs that may contribute to the tumorigenesis of MTC, differentially expressed miRNAs in the GSE40807 dataset were analyzed using GEO2R. The relative expression of miR-592 was significantly increased in MTC samples compared with normal samples (P<0.05; Fig. 1A). To further investigate the expression of miR-592 during MTC, miR-592 expression levels were examined in 20 paired MTC and corresponding normal samples using RT-qPCR. miR-592 expression levels were significantly increased in MTC samples compared with normal samples (P<0.001; Fig. 1B). Moreover, miR-592 expression levels were significantly increased in metastatic MTC samples compared with non-metastatic samples (P<0.001; Fig. 1C). In addition, the expression levels of miR-592 in MTC cell lines were assessed. The results indicated that miR-592 expression was also significantly increased in TT and MZ-CRC-1 cells compared with NThy-ori 3.1 cells (P<0.001; Fig. 1D). Furthermore, the starBase analysis suggested that miR-592 expression levels were increased in MTC samples compared with normal samples (Fig. 1E). The starBase analysis results also indicated that overall survival was not significantly different between patients with MTC with high and low miR-592 expression (Fig. 1F). However, the Kaplan-Meier survival curves demonstrated that patients with high miR-592 expression exhibited a significantly less favorable prognosis compared with patients with low miR-592 expression (P=0.034; Fig. 1G). Collectively, the results indicated that miR-592 may serve a role during MTC tumorigenesis.

miR-592 overexpression facilitates MTC cell proliferation

To investigate the precise functions of miR-592 during MTC tumor development, TT and MZ-CRC-1 cells were transfected with miR-592 mimic. Subsequently, cell proliferation, viability and cell cycle distribution were assessed using MTT, colony formation and flow cytometry assays. The miR-592 mimic group exhibited significantly increased miR-592 expression levels compared with the scramble mimic group in both TT and MZ-CRC-2 cells, which indicated that miR-592 mimic transfection was successful (P<0.05; Fig. 2A and B). miR-592 overexpression significantly increased TT and MZ-CRC-1 cell viability compared with the scramble group (P<0.05; Fig. 2C and D). miR-592 overexpression also significantly increased the colony formation rate compared with the scramble group in both TT and MZ-CRC-1 cells (P<0.05; Fig. 2E and F). Moreover, miR-592 overexpression significantly decreased the number of cells in the G0/G1 phase and significantly increased the number of cells in the S phase compared with the scramble group in both TT and MZ-CRC-1 cells (P<0.05; Fig. 2G and H). The results suggested that miR-592 overexpression promoted MTC cell proliferation.

Significantly enriched GO terms and KEGG pathways of miR-592

The target genes of miR-592 were identified by TargetScan and categorized into biological process (BP), cellular component (CC) and molecular function (MF) GO categories via DAVID analysis (Fig. 3A-C). Moreover, the target genes were functionally assessed by KEGG analysis, which indicated that the target genes were associated with several pathways, including the ‘Wnt signaling pathway’, ‘ErbB signaling pathway’, ‘insulin signaling pathway’, ‘N-Glycan biosynthesis’ and ‘Adherens junction’ (Fig. 3D). Moreover, the mRNA expression levels of multiple miR-592 target genes in miR-592 mimic-transfected TT and MZ-CRC-1 cells were assessed by RT-qPCR. miR-592 overexpression significantly decreased CDK8 expression levels compared with the scramble mimic group in both TT and MZ-CRC-1 cells (P<0.05; Fig. 3E and F); therefore, CDK8 was selected for further analysis.

miR-592 binds to and negatively regulates CDK8 in MTC cells

To determine whether CDK8 was regulated by miR-592 in MTC cells, the mRNA expression levels of CDK8 in miR-592 mimic-transfected TT and MZ-CRC-1 cells were measured by RT-qPCR. Compared with the scramble mimic group, the expression levels of CDK8 were significantly decreased in miR-592 mimic-transfected TT and MZ-CRC-1 cells (Fig. 4A). Moreover, it was predicted that CDK8 3′-UTR possessed an miR-592 binding site (Fig. 4B). Subsequently, a dual-luciferase reporter assay was performed in TT and MZ-CRC-1 cells to verify the interaction between miR-592 and CDK8. The luciferase activities of TT and MZ-CRC-1 cells co-transfected with miR-592 mimic and CDK8-WT were significantly decreased compared with TT and MZ-CRC-1 cells co-transfected with scramble mimic and CDK8-WT. The luciferase activities of TT and MZ-CRC-1 cells co-transfected with miR-592 mimic and CDK8-Mut were not significantly different compared with TT and MZ-CRC-1 cells co-transfected with scramble mimic and CDK8-Mut (P<0.05; Fig. 4C and D). In addition, CDK8 expression levels in 510 MTC samples and 58 normal samples obtained from the starBase database were assessed. CDK8 expression was downregulated in MTC samples compared with normal samples (Fig. 4E). There was no significant difference in the survival rate of patients with MTC with high and low CDK8 expression (Fig. 4F and G). Furthermore, a negative correlation between the expression levels of miR-592 and CDK8 in MTC was identified using starBase (Fig. 4H).

CDK8 overexpression reverses miR-592-mediated MTC cell proliferation

Subsequently, whether CDK8 was associated with miR-592-mediated MTC cell proliferation was investigated by co-transfecting TT and MZ-CRC-1 cells with miR-592 mimic and a CDK8 overexpression plasmid. Co-transfection of TT and MZ-CRC-1 cells with miR-592 mimic and the CDK8 overexpression plasmid reversed miR-592 mimic-mediated downregulation of CDK8 expression (P<0.05; Fig. 5A-D). The results of the colony formation assay indicated that miR-592 mimic and CDK8 overexpression plasmid co-transfection significantly decreased miR-592 mimic-induced colony formation of TT and MZ-CRC-1 cells (P<0.05; Fig. 5E and F). miR-592 overexpression decreased the number of cells in the G0/G1 phase and increased the number of cells in the S phase in both TT and MZ-CRC-1 cells; however, co-transfection of miR-592 mimic and CDK8 overexpression plasmid reversed miR-592 overexpression-induced effects on cell cycle distribution (P<0.05; Fig. 5G and H). The results indicated that CDK8 overexpression reversed the miR-592-mediated effects on MTC cell proliferation.

CDK8 interaction network and the mechanism of miR-592/CDK8 axis in MTC

To understand the regulatory network underlying CDK8 during MTC, CDK8-associated genes were identified using GENEVESTIGATOR and the top 30 CDK-8-associated genes are presented in Fig. 6A. Collectively, the results suggested that miR-592 overexpression promoted MTC tumorigenesis by downregulating CDK8 expression (Fig. 6B).

Discussion

During the past few decades, the expression profiles of miRNAs in different subtypes of thyroid cancer have been analyzed (32). A large number of mammalian miRNAs are upregulated in thyroid tumors, such as miR-650 (33), miR-340-5p (34), miR-424-5p (35) and miR-155 (36); while a number of miRNAs have been reported to be downregulated, such as miR-26a (37), miR-215 (38), miR-34a (39) and miR-206 (40). In addition, a previous study indicated that the expression levels of numerous miRNAs exhibit significant differences in MTC (41).

At present, MTC accounts for <10% of all cases of thyroid cancer worldwide, and only a small number of studies have been conducted to examine the expression profiles and biological functions of miRNAs during MTC tumorigenesis (42). The first MTC-associated microarray analysis of miRNA expression was conducted by Nikiforova et al (26) in 2008 using two MTC specimens. Hereditary MTC (hMTC) and sporadic MTC (sMTC) are the two subtypes of MTC that account for 25 and 75% of MTC cases, respectively. A subsequent study demonstrated that the expression levels of miR-183 and miR-375 were increased, while miR-9 expression levels were decreased in sMTC samples compared with hMTC samples using a miRNA microarray analysis in 19 patients with MTC, including 7 hMTC and 12 sMTC cases (43). Moreover, it was also demonstrated that miR-183 and miR-375 upregulation were closely associated with lateral lymph node metastases, representing two promising biomarkers for MTC prognosis (43). Recently, a large miRNA microarray profiling study was conducted to identify differentially expressed miRNAs in MTC, and the results also validated that miR-375 and miR-10a were upregulated, while miR-455 was downregulated in MTC samples compared with normal samples (44). To further investigate the regulatory network and functions of miRNAs during MTC, an miRNA microarray was performed in the present study to analyze differentially expressed miRNAs between MTC and normal samples in the GSE40807 dataset, which was downloaded from the GEO database. Among the differentially expressed miRNAs, miR-592 exhibited a high fold-change; therefore, it was selected for subsequent functional analysis. In the last few years, miR-592 has been reported to be involved in the development of several different types of human cancer (20,45). For example, high expression of miR-592 was demonstrated to be associated with colorectal cancer tumorigenesis and poor prognosis (46,47), miR-592 exhibits an oncogenic effect on prostate cancer cells by repressing Forkhead box O3A (48) and miR-592 facilitates the proliferation, migration and invasion of gastric cancer (49). Therefore, it was speculated that miR-592 may serve as a carcinogenic marker for different types of cancer. Nevertheless, the role of miR-592 in MTC has not been previously reported. In the present study, the RT-qPCR results indicated that miR-592 expression was upregulated in MTC tissue samples and cell lines compared with normal tissue samples and cell lines, and miR-592 overexpression promoted TT and MZ-CRC-1 cell proliferation. To the best of our knowledge, the present study was the first study to suggest that miR-592 may serve an oncogenic role during MTC.

To further explore the mechanism underlying miR-592 in MTC, the target genes of miR-592 were predicted by bioinformatics followed by functional analysis. CDK8 was identified as a target gene of miR-592, which was negatively regulated by miR-592. Numerous studies have demonstrated that CDK8 serves as a critical oncogenic molecule in various types of human cancer, including colorectal, breast and prostate cancer (5052). Although the majority of studies support the oncogenic role of CDK8, a number of studies have indicated that CDK8 exerts repressive functions in different types of cancer, including colon (53), breast (54,55), pancreatic (56) and non-small cell lung (57) cancer. The context-specific roles of CDK8 in distinct types of human cancer have received increasing interest and there is considerable controversy regarding the development of CDK8-based therapeutics. In the present study, CDK8 overexpression abolished miR-592-mediated effects on MTC cell proliferation, which implied that CDK8 may serve as a tumor suppressor during MTC.

The present study indicated that miR-592 may serve as an oncogene during MTC by decreasing CDK8 expression, providing a novel therapeutic target for MTC treatment. However, the present study had a number of limitations. The effects of miR-592 inhibitors on the functions of MTC, including cell apoptosis, autophagy, migration, invasion and tumor growth in vivo require further investigation. Additionally, the detailed mechanisms underlying the miR-592/CDK8 axis also require further investigation.

Acknowledgements

Not applicable.

Funding

No funding was received.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors' contributions

TL, JM and YZ designed the study, performed the bioinformatics analysis and the experiments. TL and YZ performed the statistical analysis. YZ wrote the manuscript. TL and JM revised the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

The present study was approved by the Ethics Committee of The Affiliated Wuhan Central Hospital of Tongji Medical College, Huazhong University of Science and Technology. Written informed consent was obtained from each participant.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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October-2020
Volume 22 Issue 4

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Spandidos Publications style
Liu T, Meng J and Zhang Y: miR‑592 acts as an oncogene and promotes medullary thyroid cancer tumorigenesis by targeting cyclin‑dependent kinase 8 Corrigendum in /10.3892/mmr.2021.12312. Mol Med Rep 22: 3316-3326, 2020
APA
Liu, T., Meng, J., & Zhang, Y. (2020). miR‑592 acts as an oncogene and promotes medullary thyroid cancer tumorigenesis by targeting cyclin‑dependent kinase 8 Corrigendum in /10.3892/mmr.2021.12312. Molecular Medicine Reports, 22, 3316-3326. https://doi.org/10.3892/mmr.2020.11392
MLA
Liu, T., Meng, J., Zhang, Y."miR‑592 acts as an oncogene and promotes medullary thyroid cancer tumorigenesis by targeting cyclin‑dependent kinase 8 Corrigendum in /10.3892/mmr.2021.12312". Molecular Medicine Reports 22.4 (2020): 3316-3326.
Chicago
Liu, T., Meng, J., Zhang, Y."miR‑592 acts as an oncogene and promotes medullary thyroid cancer tumorigenesis by targeting cyclin‑dependent kinase 8 Corrigendum in /10.3892/mmr.2021.12312". Molecular Medicine Reports 22, no. 4 (2020): 3316-3326. https://doi.org/10.3892/mmr.2020.11392