Circulating and tissue miR-100 acts as a potential diagnostic biomarker for cervical cancer

Abstract

BACKGROUND:

MicroRNAs (miRNA) are promising biomarkers for cancer diagnosis and prognosis; miR-100 expression is decreased in cervical cancer tissues.

OBJECTIVE:

To determine whether miR-100 is a useful biomarker for early cervical cancer diagnosis.

METHODS:

Total RNA was extracted from the sera of 34 healthy controls (HC), 64 cervical intraepithelial neoplasia patients (CIN), and 46 cervical cancer patients (CC). miR-100 expression levels were measured with quantitative real-time PCR. Correlations between clinicopathological factors and miR-100 expression levels were also assessed. The cut-off value for miR-100 was calculated from the Receiver Operating Characteristic (ROC) curve.

RESULTS:

Relative expression levels of miR-100 in serum were 1.84 $\pm$ 1.72, 3.93 $\pm$ 2.52, and 5.32 $\pm$ 3.39 in CC, CIN, and HC, respectively; it was significantly lower in CC ( $p<$ 0.001). The area under the ROC curve was 0.879 and the cut-off value was 2.451. miR-100 expression levels were significantly higher in metastasis cases that were lymph node negative than positive ( $p<$ 0.05). CC patients with miR-100 expression levels below the cut-off value tended to have a poor prognosis.

CONCLUSIONS:

Serum miR-100 may be a useful diagnostic biomarker for CC, and for predicting lymph node metastasis and disease free survival in CC patients.

Keywords

Diagnosis miRNA prognosis tumor marker

1. Introduction

Cervical cancer (CC) is a major cause of mortality in women; approximately 311,000 women worldwide die of this disease every year [1]. Human papillomavirus (HPV) infection is the leading cause of CC [2]. CC is histologically divided into two types: squamous cell carcinoma (SCC), which arises from cervical intraepithelial neoplasia (CIN), and adenocarcinoma, which arises from intraepithelial adenocarcinoma [3]. Based on the relative risk of cervical cancer, CIN1 and CIN2-3 are regarded as low-grade and high-grade CIN, respectively [4]. SCC antigen in blood is a well-known tumor marker for CC, and a tumor-associated antigen of SCC [5]. However, this marker rarely shows an increase in early stage cancers [6].

MicroRNAs (miRNAs) have been drawing attention as novel regulatory molecules for genomic information [7]. MiRNAs are short chain RNAs, approximately 20–25 bases, that do not directly code for proteins but rather regulate various physiological activities in living organisms by suppressing the expression of target mRNAs [7]. Many miRNAs are involved in the downregulation of target mRNAs in various biological processes [8]. MiRNAs bind mainly to the 3’-untranslated region (UTR) of target mRNAs and restrain their translation [8]. In addition, miRNAs play roles in both promoting and suppressing the tumors because they strongly influence the expression of tumor oncogenes and suppressor genes. A single miRNA can have many targets; it is possible that miRNAs regulate about one-third of human genes [9]. The function of miRNA expression in cancer cells is not completely clear. Nevertheless, previous studies have reported that various diseases, including cancers, are accompanied by changes in miRNA expression patterns [10]. Thus, miRNAs are regarded as promising biomarkers in cancer diagnosis and treatment.

Altered miRNA expression in CC lesions is partially related to chromosomal alternations. In a previous study, decreased miR-100 and miR-125 expression in CIN and CC samples was found to be associated with a chromosomal loss [11]. Li et al. have shown that miR-100 expression in CC tissues, which is associated with cell proliferation, apoptosis, and the cell cycle, was reduced [10]. Moreover, miR-100 was found to be hypo-expressed in advanced cervical small cell carcinoma tissue samples [12]. MiRNAs embedded in small exosome granules were found to stably exist in extracellular body fluids, such as saliva, serum, and urine [13]. Moldovan et al. described a quantitative real-time PCR (qRT-PCR)-based method to analyze circulating miRNAs in exosomes from serum [14]. The miR-9, miR-192, and miR-205 expression levels were elevated in serum and tissue samples of CC patients [15]. Serum miRNAs may this serve as biomarkers for diagnosis or prognosis of patients with CC.

We searched the literature for miRNAs that were downregulated in cervical cancer tissues and identified three candidate miRNAs: miR-34a, miR-100, and miR-125 [10, 11]. We measured the expression of each miRNA in the sera of 10 cervical cancer patients using RT-PCR, and miR-100, whose expression was the most downregulated, was chosen for further study. In this study, miR-100 expression levels in serum and cervical tissues were measured to determine whether miR-100 could be useful in the diagnosis and prognosis of CC.

2. Materials and methods

2.1 Clinical samples

The research protocol was approved by the Institutional Review Board of Tokyo Medical University (approval no. 930). This study was conducted according to the Declaration of Helsinki. From April 2010 to April 2012, 144 patients took part in this study at the Tokyo Medical University Hospital; of these individuals, 46 were patients with CC, 64 were patients, with CIN, and 34 were healthy controls (HC). Among HCs, patients with a history of uterine malignancy were excluded. Patients with CC were staged using the International Federation of Gynecology and Obstetrics (FIGO) staging system for CC. Patient backgrounds were obtained through interviews. Informed consent was obtained from all individuals participating in the study. A 10-mL volume of blood samples was collected from individuals before surgery, chemotherapy, and radiation therapy at Tokyo Medical University Hospital. Cervical tissues were collected from the patients who had had a biopsy or hysterectomy. CIN and CC were diagnosed by histopathological examinations.

2.2 Laser capture microdissection

Cervical tissue blocks were cut into 5- $\mu$ m sections by a gynecopathologist. Sections were stained with hematoxylin and eosin. Next, laser capture microdissection (LCM) was used to isolate groups of cells from cervical tissues; normal cervical epithelium, CIN, CC cells, and adjacent non-cancerous cells were obtained.

2.3 Serum preparation and total RNA extraction

Blood samples were centrifuged at 3000 rpm for 5 min and separated into blood cells and serum. Serum was stored at $-$ 70 ${}^{\circ}$ C. Total RNA in the serum was isolated using ISOGEN-LS (Nippon Gene Co., Tokyo, Japan) according to the manufacturer’s instructions. Briefly, 250 $\mu$ L of serum was homogenized in 750 $\mu$ L of ISOGEN-LS, followed by addition of 200 $\mu$ L chloroform [16]; then, samples were centrifuged at 12000 rpm for 15 min. After additional chloroform extraction and precipitation with isopropanol, RNA samples were eluted with 20 $\mu$ L of nuclease-free water. For tissues samples, total RNA was isolated from cells of approximate sections using the RNeasy Micro Kit (Qiagen, Hilden, Germany), similar to the serum samples, after centrifugation.

Table 1
Characteristics of the 144 study participants

Histological type
	CC ( $n=$ 46)	CIN1 ( $n=$ 14)	CIN2 ( $n=$ 18)	CIN3 ( $n=$ 32)	HC ( $n=$ 34)
Age	49.0 $\pm$ 14.0 (28–88)	34.0 $\pm$ 6.7 (27–50)	35.0 $\pm$ 9.2 (19–54)	34.0 $\pm$ 5.2 (26–44)	42.0 $\pm$ 10.9 (24–69)
SCC	37
Adenocarcinoma	9
Non-smoking	37	11	12	29
Smoking	9	3	6	3

CC: cervical cancer; CIN1: cervical intraepithelial neoplasia grade 1; CIN2: cervical intraepithelial neoplasia grade 2; CIN3: cervical intraepithelial neoplasia grade 3; HC: healthy controls; SCC: squamous cell carcinoma.

2.4 Determination of miR-100 expression with quantitative PCR

MiRNAs were quantified using TaqMan MicroRNA Assays (Applied Biosystems, Foster City, CA, USA) with modifications and miRNA-specific stem-loop primers [17] (hsa-mir-100; Applied Biosystems). First, each miRNA was specifically converted into cDNA, according to the manufacturer’s protocol, using TaqMan miRNA RT-Kit with a stem-loop RT-primer and the Applied Biosystems 9800 Fast Thermal Cycler. Second, qRT-PCR was performed for miR-100, using RT-primers with Universal Master Mix, on the Applied Biosystems StepOnePlus ${}^{\text{TM}}$ Real-Time PCR System (Life Technologies Corporation, Carlsbad, CA, USA). The reaction protocol for qPCR was as follows: 95 ${}^{\circ}$ C for 2 min, followed by 50 cycles of 95 ${}^{\circ}$ C for 15 sec and 60 ${}^{\circ}$ C for 1 min. Each sample was analyzed in duplicate. The cycle thresholds (Ct) of patients with CC or CIN, and HCs, were accounted and normalized using miR-16, the most commonly used endogenous control miRNA for qRT-PCR [13]. The miR-100 expression levels in patients with CC or CIN, compared to HC, were quantified using the comparative cycle threshold ( $C_{T}$ ) method. The $\Delta C_{T}$ value was calculated by subtracting the average CT value of control miR-16 of each sample from the CT value of each mature RNA reaction. The $-\Delta\Delta\text{Ct}$ value was calculated as described previously [16]. MiR-100 expression was normalized using the 2 ${}^{-\Delta\Delta\text{Ct}}$ method [16, 17].

The miR-100 expression profile was used for creating a Receiver Operating Characteristic (ROC) curve, a graphical plot of the true positive rate versus the false positive rate. The cut-off value of miR-100 expression was calculated by ROC analysis.

2.5 Statistical analysis

The “EZR” Software was used to perform statistical analysis of the causal relation between the patient background and miR-100 expression pattern [18]. The expression levels of miR-100 were presented as mean $\pm$ standard deviation (SD). The Kruskal-Wallis test and Welch’s $t$ -test were carried out to analyze the statistical discrepancy among groups. $P$ values $<$ 0.05 were considered statistically significant. Overall and disease-free survival curves were generated using the Kaplan-Meier method and compared using the log-rank test.

3. Results

3.1 Characteristics of the study subjects

Table 1 summarizes the characteristics of the study participants. Out of the 46 patients with CC, four had stage IA, 21 had stage IB, four had stage IIA, 10 had stage IIB, three had stage III, and four had stage IV (Table 2). Of the 64 patients with CIN, 14 were CIN1, 18 were CIN2, and 32 were CIN3.

Table 2
Relationship between serum miR-100 expression and clinicopathological factors

		$n$	miR-100	$p$ -value
			(mean $\pm$ SD)
Stage	I	25	2.14 $\pm$ 2.11	0.93 ${}^{*}$
	II	14	1.48 $\pm$ 1.11
	III	3	1.54 $\pm$ 1.06
	IV	4	1.42 $\pm$ 0.92
SCC		37	1.71 $\pm$ 1.69	0.36 ${}^{**}$
Adenocarcinoma		9	2.42 $\pm$ 1.95
pT	1	21	2.50 $\pm$ 2.23	0.004 ${}^{**}$
	2	12	0.88 $\pm$ 0.55
pN	0	27	2.13 $\pm$ 2.15	0.01 ${}^{**}$
	1	8	0.98 $\pm$ 0.36
Vascular invasion	Negative	16	1.81 $\pm$ 1.62	0.90 ${}^{**}$
	Positive	19	1.89 $\pm$ 2.18
Recurrence risk	Low	11	2.52 $\pm$ 2.76	0.71 ${}^{*}$
	Middle	8	1.98 $\pm$ 2.01
	High	16	1.34 $\pm$ 0.87

${}^{*}$ Kruskal-Wallis Test. ${}^{**}$ Welch’s $t$ -test. pN: pathological Node; pT: pathological Tumor category; category; SCC: squamous cell carcinoma. A $p$ -value $<$ 0.05 is statistically significant.

3.2 Decreased miR-100 expression level in the serum of CC subjects

We examined whether there was a difference in miR-100 expression levels in the sera of patients with CC or CIN, and HC. MiR-100 concentrations were measured in 46 patients with CC, patients with 64 CIN subjects, and 34 HC. The miR-100 expression levels were significantly downregulated in sera of patients with CC, but not CIN, when compared with those of HC ( $P<$ 0.001 and $P>$ 0.05, respectively; Fig. 1). miR-100 expression level was significantly downregulated in sera of patients with CC compared with that of those with CIN ( $P<$ 0.01; Fig. 1). The median serum miR-100 expression levels were 4.123, 3.214, and 1.452 in HC, and CIN and CC patients, respectively.

Figure 1.

Serum miR-100 expression levels in patients with cervical cancer (CC), patients with cervical intraepithelial neoplasia (CIN), and healthy controls (HC), as determined with qRT-PCR. This graph illustrates that the miR-100 expression level was significantly downregulated in sera of patients with CC in comparison to that in HC, but not in the sera of patients with CIN.

Figure 2.

Graph indicating the receiver operating characteristic (ROC) curve. The ROC curve shows that serum miR-100 expression levels could distinguish patients with cervical cancer (CC) from healthy controls (HC), with an AUC of 0.879. With the cut-off at 2.451, miR-100 had 91.2% FPF and 80.4% TPF for patients with CC compared to HC.

The ROC curve showed that serum miR-100 levels were able to distinguish between patients with and HC; the area of ROC was 0.879 (95% confidence interval, 0.7976–0.9609; Fig. 2). The cut-off value was calculated from the ROC curve to be 2.451 (relative expression level), at which the sensitivity of miR-100 to CC was 91.2% and specificity was 80.4% in comparison to the healthy subjects.

3.3 Expression level of serum miR-100 in patients with different stages of CC

The expression levels of serum miR-100 in each group were as follows: HC, 4.1225; CIN1 group, 4.0055; CIN2 group, 3.1205; CIN3 group, 2.9905; CC stage IA group, 1.00575; stage IB group, 1.466; stage IIA group, 0.747; stage IIB group, 1.12; stage III group, 1.829; and stage IV group, 1.418 (Fig. 3). The median serum miR-100 expression levels decreased as the CC stage progressed. No significant difference was found in the histological type between squamous cell carcinoma and adenocarcinoma (Table 2). However, there was a significant difference in lymph node metastasis ( $P<$ 0.01, Mann-Whitney test). The median serum miR-100 expression level was 0.98 in patients with CC who had a positive lymph node metastasis, and 2.13 in those who had a negative lymph node metastasis.

Figure 3.

Serum miR-100 expression levels in patients with cervical cancer (CC) or cervical intraepithelial neoplasia (CIN) at each stage. This chart illustrates that the median expression level of serum miR-100 decreased as the CC stage progressed (healthy group: 4.1225, CIN1 group: 4.0055, CIN2 group: 3.1205, CIN3 group: 2.9905, cervical cancer stage IA group: 1.0058, stage IB group: 1.466, stage IIA group: 0.747, stage IIB group: 1.12, stage III group: 1.829, and stage IV group: 1.418).

Figure 4.

Graph indicating the expression level of miR-100 in normal cervical epithelium ( $n=$ 10), cervical intraepithelial neoplasia (CIN) tissues ( $n=$ 20), and cervical cancer (CC) tissues ( $n=$ 20). The expression level of miR-100 was significantly lower in the tissues of patients with CC in comparison to those of healthy controls ( $P<$ 0.01). The median tissue miR-100 expression level was 4.220 in healthy controls ( $n=$ 10), 3.415 in patients with CIN ( $n=$ 20), and 0.936 in patients with CC ( $n=$ 20).

Figure 5.

Expression of miR-100 in cervical intraepithelial neoplasia (CIN) ( $n=$ 10) and cervical cancer (CC) tissues ( $n=$ 10) tended to be downregulated as compared to that in the adjacent non-cancerous tissues. The median tissue miRNA-100 expression level was 1.383 in the CIN tissues ( $n=$ 10), 3.449 in the adjacent non-cancerous tissues of same patients with CIN ( $n=$ 10), 1.500 in CC tissues ( $n=$ 10), and 6.510 in the adjacent non-cancerous tissues of the same patients with CC ( $n=$ 10).

Figure 6.

Kaplan-Meier plots of overall survival and disease-free survival curves according to the status of serum miR-100 expression. Individuals with an miR-100 expression level under 2.451 ( $n=$ 37) showed significantly worse recurrence than those with an miR-100 expression level over 2.451 ( $n=$ 9) ( $p=$ 0.0396, log-rank test).

3.4 MiR-100 expression levels in cervical tissues

The miR-100 expression levels were significantly higher in the tissues of HC than in those of patients with CC ( $P<$ 0.01; Fig. 4). The median tissue miRNA-100 expression level was 4.220 in the HC ( $n=$ 10), 3.415 in patients with CIN ( $n=$ 20), and 0.936 in patients with CC ( $n=$ 20). Additionally, miR-100 expression tended to be downregulated in CC and CIN tissues as compared to that in adjacent non-cancerous tissues (Fig. 5). The median tissue miRNA-100 expression level was 1.383 in the CIN tissues ( $n=$ 10), 3.449 in the adjacent non-cancerous tissues of same patients with CIN ( $n=$ 10), 1.500 in CC tissues ( $n=$ 10), and 6.510 in the adjacent non-cancerous tissues of the same patients with CC ( $n=$ 10).

3.5 Survival and serum miR-100

Kaplan-Meier curve indicated that disease-free survival (DFS) in patients with miR-100 expression level under 2.451 was significantly worse than that of patients with miR-100 level over 2.451 ( $p=$ 0.0396, log-rank test; Fig. 6). In addition, overall survival (OS) of the former group tended to be lower than that of the latter group ( $p=$ 0.0700, log-rank test).

4. Discussion

Some biomarkers can permit early detection of cancers, and contribute to improving the survival rate. Early cancer biomarkers are thus highly important for diagnosis and prognosis of cancers. SCC antigen is a tumor marker for cervical SCC; however, the SCC antigen level is not often upregulated in the early stages of CC [19]. Many clinicians have been looking for new effective biomarkers for early CC detection.

Altered microRNA expression is observed in CC and precancerous lesions. A systematic review showed that miR-21 and miR-29a are the most frequently decreased miRNAs during CC progression [20]. In a meta-analysis, miR-100 rs1834306 was not found to be associated with CC development; however, this meta-analysis included only two studies related to miR-100 [21]. Li et al. showed that reduced miR-100 expression is associated with CC development by abolishing the inhibition of the target gene polo-like kinase 1 (PLK1), which likely accrues relatively late in carcinogenesis [22]. The miR-100 gene is present on Chromosome 11q24.1 (http://www.mirbase.org/). Some reports have demonstrated some miR-100 functions. Decreased miR-100 expression has been reported in various cancer tissues. MiR-100 can suppress CC, epithelial ovarian cancers, and nasopharyngeal cancer tissues by targeting PLK1 [22, 23, 24]. PLK1, a key regulator of many stages of mitosis [25], and is highly expressed in many cancers [26, 27]. Previous studies have shown that the overexpression of PLK1 results in cell proliferation, apoptosis, metastasis, and chemoresistance in human cancers [28, 29]. Additionally, miR-100 may suppress gastric cancer by regulating the expression of CXCR7. Cao et al. showed that miR-100 directly targets CXCR7 through the 3’-UTR of CXCR7, which includes a putative binding site of miR-100. CXCR7 might be a downstream target for miR-100 in gastric cancer [30]. In patients with CC, CXCR7 expression was found to be correlated with disease recurrence and prognosis [31].

The discovery of circulating miRNAs has brought great scientific progress in recent years. Circulating exosomal miRNAs have been realized to be useful biomarkers for cancer patients, because of their non-invasive approach and high stability [32]. Circulating miRNA profiles are believed to be unique to each cancer type, and reflect the primary tumor focus [33]. Several studies have revealed the usefulness of serum miRNAs as potential biomarkers that may aid in detection of cancer. It has been reported that the expression levels of serum miR-100 are correlated with different cancers, such as colorectal and lung cancers [34]. Serum miRNAs may be useful biomarkers in cancer diagnosis, and decrease the frequency of invasive biopsies. In this study, we first used qRT-PCR to examine the serum miR-100 expression in HC, and in patients with CIN and CC. The serum miR-100 expression was highest in HC, intermediate in patients with CIN, and lowest in patients with CC. Furthermore, serum miR-100 expression level was higher in patients with low-grade CIN than those with high-grade CIN. As the CC stage progressed, the miR-100 expression level tended to decrease. Furthermore, reduced serum miR-100 levels were related to positive lymph node metastasis and time to relapse. These results indicate that serum miR-100 may be useful in predicting CC progression and prognosis.

As far as we know, this is the first study to probe miR-100 expression levels and its clinical significance, in patients with CC. However, stage IIA had lower expression than stage IIB, III and IV as shown in Fig. 3. One possible cause is the small population at each stage of cervical cancer. Therefore, it is necessary in the future to expand the study with more cases and analyze the expression level of serum miR-100 at each stage of cervical cancer. There were three positive lymph node metastases cases in stage IIA, which may have contributed to the low serum miR-100 levels in this experimental group. Using LCM (not just a follow-up test), this study showed that miR-100 expression level is decreased in CC tissues. In addition, the expression pattern of miR-100 tended to be increased in the surrounding noncancerous lesions in comparison with CC and CIN lesions. These results suggest that miR-100 may have a role in the progression of CIN to CC. Furthermore, the reduced expression of miR-100 in CC tissues may lead to decreased expression of serum miR-100 in CC. Mahdieh et al. showed that the expression level of serum miR-192 was upregulated in CC tissues [16]. This result suggests that circulating miRNAs in blood reflect cancer origin-specific expression signatures.

Limitations of this study include low sample size and selection bias of healthy individuals. Blood samples and cervical tissues were collected only once, and it is unclear whether treatment for CC or CIN affects miR-100 expression levels.

In conclusion, we found that miR-100 in serum and tissue was downregulated in parallel in patients with CC. Serum miR-100 may be a useful biomarker in the diagnosis of CC, especially in the prediction of lymph node metastasis and prognosis. Further studies are needed to completely investigate the function of miR-100 in CC. Serum miR-100 may possibly not only be a predictive marker for CC, but also a marker for determining the efficacy of treatment for cervical cancer by observing the temporal changes in serum miR-100 expression levels after treatment.

Footnotes

Acknowledgments

This work was supported by the Grants-in-Aids (Grant no. 24592533) from the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT) and the Third-Term Comprehensive Control Research for Cancer and Research on Biological Markers for New Drug Development (Grant no. 201118007B) conducted by the Ministry of Health, Labour and Welfare of Japan (MHLW). We would like to thank Editage (www.editage.com) for English language editing.

Author contributions

Conception: Zenta Yamanaka, Kazuyoshi Kato.

Interpretation or analysis of data: Akina Yamanaka, Toru Sasaki.

Preparation of the manuscript: Zenta Yamanaka.

Revision for important intellectual content: Zenta Yamanaka, Hirotaka Nishi.

Supervision: Hirotaka Nishi.

References

Arbyn

Weiderpass

Bruni

Sanjose

S.D.

Saraiya

Ferlay

et al., Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis, Lancet Glob Health 8(2) (2020), 191–203. doi: 10.1016/S2214-109X(19)30482-6.

Bosch

FX.

Lorincz

, Muñoz

Meijer

C.J.

and Shah

K.V.

, The causal relation between human papillomavirus and cervical cancer, J Clin Pathol 55(4) (2002), 244–265. doi: 10.1136/jcp.55.4.244.

Pisani

Bray

and Parkin

D.M.

, Estimates of the world-wide prevalence of cancer for 25 sites in the adult population, Int J Cancer 97(1) (2002), 72–81. doi: 10.1002/ijc.1571.

McCredie

M.R.

Sharples

K.J.

Paul

Baranyai

Medley

Jones

R.W.

et al., Natural history of cervical neoplasia and risk of invasive cancer in women with cervical intraepithelial neoplasia 3: a retrospective cohort study, Lancet Oncol 9(5) (2008), 425–434. doi: 10.1016/S1470-2045(08)70103-7.

Kato

and Torigoe

, Radioimmunoassay for tumor antigen of human cervical squamous cell carcinoma, Cancer 40(4) (1977), 1621–1628. doi: 10.1002/1097-0142(197710)40: 4<1621::aid-cncr2820400435>30.co;2-i.

Kato

, Squamous cell carcinoma antigen, in: S. Sell, ed, Serological Cancer Markers, Humana Press: Totowa; 1992, pp. 437–451.

Lee

R.C.

Feinbaum

R.L.

and Ambros

, The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14, Cell 75(5) (1993), 843–854. doi: 10.1016/0092-8674(93)90529-y.

Lytle

J.R.

Yario

T.A.

and Steitz

J.A.

, Target mRNAs are repressed as efficiently by microRNA-binding sites in the 5’ UTR as in the 3’ UTR, Proc Natl Acad Sci U S A 104(23) (2007), 9667–9672. doi: 10.1073/pnas.0703820104.

Lewis

B.P.

Burge

C.B.

and Bartel

D.P.

, Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets, Cell 120(1) (2005), 15–20. doi: 10.1016/j.cell.2004.12.035.

10.

and Xie

, Reduced miR-34a expression in normal cervical tissues and cervical lesions with high-risk human papillomavirus infection, Int J Gynecol Cancer 20(4) (2010), 597–604. doi: 10.1111/IGC.0b013e3181d63170.

11.

Wilting

S.M.

Snijders

P.J.

Verlaat

Jaspers

van de Wiel

M.A.

van Wieringen

W.N.

Meijer

G.A.

Kenter

G.G.

le Sage

Agami

Meijer

C.J.

and Steenbergen

R.D.

, Altered microRNA expression associated with chromosomal changes contributes to cervical carcinogenesis, Oncogene 32(1) (2013), 106–116. doi: 10.1038/onc.2012.20.

12.

Huang

Lin

J.X.

Y.H.

Zhang

M.Y.

Wang

H.Y.

and Zheng

, Downregulation of six microRNAs is associated with advanced stage, lymph node metastasis and poor prognosis in small cell carcinoma of the cervix, PLoS One 7(3) (2012), e33762. doi: 10.1371/journal.pone.0033762.

13.

Valadi

Ekström

Bossios

Sjöstrand

Lee

JJ.

and Lötvall

J.O.

, Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells, Nat Cell Biol 9(6) (2007), 654–659. doi: 10.1038/ncb1596.

14.

Moldovan

Batte

Wang

Wisler

and Piper

, Analyzing the circulating microRNAs in exosomes/extracellular vesicles from serum or plasma by qRT-PCR, Methods Mol Biol 1024 (2013), 129–145. doi: 10.1007/978-1-62703-453-1_10.

15.

Farzanehpour

Mozhgani

S.H.

Jalilvand

Faghihloo

Akhavan

Salimi

et al., Serum and tissue miRNAs: potential biomarkers for the diagnosis of cervical cancer, Virol J 16(1) (2019), 116. doi: 10.1186/s12985-019-1220-y.

16.

Ohyashiki

Umezu

Yoshizawa

Ito

Ohyashiki

Kawashima

et al., Clinical impact of down-regulated plasma miR-92a levels in non-Hodgkin’s lymphoma, PLoS One 6(2) (2011), e16408. doi: 10.1371/journal.pone.0016408.

17.

Schrauder

M.G.

Strick

Schulz-Wendtland

Strissel

P.L.

Kahmann

Loehberg

C.R.

et al., Circulating micro-RNAs as potential blood-based markers for early stage breast cancer detection, PLoS One 7(1) (2012), e29770. doi: 10.1371/journal.pone.0029770.

18.

Kanda

, Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics, Bone Marrow Transplant 48(3) (2013), 452–458. doi: 10.1038/bmt.2012.244.

19.

Nagamitsu

Nishi

Sasaki

Takaesu

Terauchi

and Isaka

, Profiling analysis of circulating microRNA expression in cervical cancer, Mol Clin Oncol 5(1) (2016), 189–194. doi: 10.3892/mco.2016.875.

20.

Pardini

De Maria

Francavilla

Di Gaetano

Ronco

and Naccarati

, MicroRNAs as markers of progression in cervical cancer: a systematic review, BMC Cancer 18(1) (2018), 696. doi: 10.1186/s12885-018-4590-4.

21.

Shang

Sun

Braun

and Tong

, Association between miR-124 rs531564 and miR-100 rs1834306 polymorphisms and cervical cancer: a meta-analysis, Eur J Gynaecol Oncol 40(6) (2019), 925–931. doi: 10.12892/ejgo4993.2019.

22.

B.H.

Zhou

J.S.

Cheng

X.D.

Zhou

C.Y.

W.G.

and Xie

, Reduced miR-100 expression in cervical cancer and precursors and its carcinogenic effect through targeting PLK1 protein, Eur J Cancer 47(14) (2011), 2166–2174. doi: 10.1016/j.ejca.2011.04.037.

23.

Peng

D.X.

Luo

Qiu

L.W.

Y.L.

and Wang

X.F.

, Prognostic implications of microRNA-100 and its functional roles in human epithelial ovarian cancer, Oncol Rep 27(4) (2012), 1238–1244. doi: 10.3892/or.2012.1625.

24.

Shi

Alajez

N.M.

Bastianutto

Hui

A.B.

Mocanu

J.D.

Ito

et al., Significance of Plk1 regulation by miR-100 in human nasopharyngeal cancer, Int J Cancer 126(9) (2010 May 1), 2036–2048. doi: 10.1002/ijc.24880.

25.

Takaki

Trenz

Costanzo

and Petronczki

, Polo-like kinase 1 reaches beyond mitosis-cytokinesis, DNA damage response, and development, Curr Opin Cell Biol 20(6) (2008), 650–660. doi: 10.1016/j.ceb.2008.10.005.

26.

Schmit

T.L.

Zhong

Nihal

and Ahmad

, Polo-like kinase 1 (Plk1) in non-melanoma skin cancers, Cell Cycle 8(17) (2009), 2697–2702. doi: 10.4161/cc.8.17.9413.

27.

Nappi

T.C.

Salerno

Zitzelsberger

Carlomagno

Salvatore

and Santoro

, Identification of polo-like kinase 1 as a potential therapeutic target in anaplastic thyroid carcinoma, Cancer Res 69(5) (2009), 1916–1923. doi: 10.1158/0008-5472.CAN-08-1693.

28.

Degenhardt

and Lampkin

, Targeting polo-like kinase in cancer therapy, Clin Cancer Res 16(2) (2010), 384–389. doi: 10.1158/1078-0432.CCR-09-1380.

29.

Strebhardt

and Ullrich

, Targeting polo-like kinase 1 for cancer therapy, Nat Rev Cancer 6(4) (2006), 321–330. doi: 10.1038/nrc1841.

30.

Cao

Song

Chen

and Wu

, MicroRNA-100 suppresses human gastric cancer cell proliferation by targeting CXCR7, Oncol Lett 15(1) (2018), 453–458. doi: 10.3892/ol.2017.7305.

31.

Schrevel

Karim

ter Haar

N.T.

van der Burg

S.H.

Trimbos

J.B.

Fleuren

G.J.

et al., CXCR7 expression is associated with disease-free and disease-specific survival in cervical cancer patients, Br J Cancer 106(9) (2012), 1520–1525. doi: 10.1038/bjc.2012.110.

32.

Asano

Matsuzaki

Ichikawa

Kawauchi

Takizawa

Aoki

et al., A serum microRNA classifier for the diagnosis of sarcomas of various histological subtypes, Nat Commun 10(1) (2019), 1299. doi: 10.1038/s41467-019-09143-8.

33.

Kosaka

Iguchi

and Ochiya

, Circulating microRNA in body fluid: a new potential biomarker for cancer diagnosis and prognosis, Cancer Sci 101(10) (2010), 2087–2092. doi: 10.1111/j.1349-7006.2010.01650.x.

34.

Chen

Cai

Yin

Wang

et al., Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases, Cell Res 18(10) (2008), 997–1006. doi: 10.1038/cr.2008.282.

Circulating and tissue miR-100 acts as a potential diagnostic biomarker for cervical cancer

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

2. Materials and methods

2.1 Clinical samples

2.2 Laser capture microdissection

2.3 Serum preparation and total RNA extraction

Table 1 Characteristics of the 144 study participants

2.5 Statistical analysis

3. Results

3.1 Characteristics of the study subjects

Table 2 Relationship between serum miR-100 expression and clinicopathological factors

3.5 Survival and serum miR-100

4. Discussion

Footnotes

Acknowledgments

Author contributions

References

Table 1
Characteristics of the 144 study participants

Table 2
Relationship between serum miR-100 expression and clinicopathological factors