Salivary miR-93 and miR-200a as post-radiotherapy biomarkers in head and neck squamous cell carcinoma

  • Authors:
    • Thomas Greither
    • Freya Vorwerk
    • Matthias Kappler
    • Matthias Bache
    • Helge Taubert
    • Thomas Kuhnt
    • Jeremias Hey
    • Alexander W. Eckert
  • View Affiliations

  • Published online on: June 28, 2017     https://doi.org/10.3892/or.2017.5764
  • Pages: 1268-1275
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Abstract

Head and neck squamous cell carcinoma is the 6th most malignant tumor entity worldwide and has exhibited a 5-year mortality of approximately 50% for the last fifty years. For the therapy monitoring and successful management of this tumor entity new and easily accessible biomarkers are greatly needed. The aim of the study was to determine whether and to what extent microRNAs, a class of small regulatory RNAs, are detectable in saliva post-radiation therapy. The expression and feasibility as therapy monitoring marker of the microRNAs were analyzed by RT-qPCR in 83 saliva samples from 33 patients collected at several time points pre-, during and post-radiotherapy treatment. Ten head and neck squamous cell carcinoma- or radiation-associated microRNAs (miR-93, miR-125a, miR-142-3p, miR-200a, miR-203, miR-213, let-7a, let-7b, let-7g and let-7i) were analyzed. All were detectable to a different extent in the saliva of the patients. miR-93 and miR-200a were significantly higher expressed 12 months post-radiotherapy than at baseline (p=0.047 and p=0.036). These results point towards miR-93 and miR-200a as biomarkers for the treatment monitoring post-radiation of head and neck squamous cell carcinoma.

Introduction

Head and neck cancer is the term given to a variety of malignant tumors that develop in the oral cavity, laryngeal, pharynx and salivary glands. They are predominantly squamous cell carcinomas. Head and neck squamous cell carcinoma (HNSCC) is the 6th most common malignancy worldwide (1). The incidence rates in the world are higher in the most developed countries (2). It was estimated that there were approximately 550,000 new head and neck cancer cases in the world in 2008. The expected number of deaths was approximately 300,000. Despite progress in therapeutic procedures, patients with HNSCC have a high risk of early locoregional relapse. The five-year survival rate for HNSCC has shown only modest improvement over the last decades (3,4). Most of them are oral squamous cell carcinomas (OSCC) (5). Not only the delayed detection but also the difficulties to monitor the treatment and outcome are responsible for the high morbidity rate of HNSCC. Therefore, early detection of disease progression remains a challenging task mainly due to the lack of adequate biomarkers.

A variety of promising biomarkers has been described, nearly all of them can be detected immunohistochemically (6). In addition, saliva is preferentially studied for such biomarkers, because it has many advantages in terms of collection, storage, shipping, and voluminous sampling; all of these processes can be carried out very economically compared with serum or urine. All investigations focus on an early detection of OSCC (7). Moreover, salivary biomarkers are of great value for differentiation of an OSCC from potentially malignant oral disorders (8). However, the main advantages of saliva as a diagnostic tool for HNSCC is that oral cancer cells are immersed in the salivary milieu. Therefore saliva provides more direct information regarding the disease status. Saliva bears different biological components potentially capable for diagnosis and monitoring of HNSCC including the small nucleic acids designated as microRNAs (9). Several studies indicated the potential of saliva miRNAs for early oral cancer diagnosis (1013).

MicroRNAs (miRNAs) are small (18–25 bp) non-coding RNAs of endogenous origin, which regulate gene expression post-transcriptionally by translation inhibition and increased decay of their target mRNAs. They recognize their target mRNA by binding of 6 nucleotide sequences in the 3′-UTR (‘seed’ sequence), which is specific for each individual microRNA species. To date, 2,588 individual microRNA sequences have been identified in human (miRBase database, release 21: June 2014), which are estimated to regulate the expression of 60% of human protein-coding genes (14). MicroRNAs are essential regulators of cell proliferation, differentiation and apoptosis (reviewed in refs. 1517). MiRNAs were recently shown to be abundant and stable in different body fluids such as serum, urine or saliva (1820). Furthermore, altered expression of several microRNAs has already been described to be associated with the genesis and/or progression of oral cancer.

Among others, miR-93, miR-125a, miR-142-3p, miR-200a, miR-203, miR-213 (designated by actual miRBase terminology as miR-181a-3p), were found to be associated with HNSCC. miR-93, miR-125a, miR-142-3p and miR-200a were concordantly expressed in saliva of 12 HNSCC patients and 12 healthy controls (21). Furthermore, miR-125a and miR-200a expression was significantly lower in the saliva of a cohort of 50 HNSCC patients than in corresponding healthy controls (21). MicroRNA miR-203 was significantly downregulated in 23 samples of oral cavity SCC compared to control tissue (22). MicroRNA miR-213 was upregulated >3.0-fold in patients samples of squamous cell carcinoma of the tongue (23). Furthermore, miR-213 targets Nanog mRNA in a subpopulation of CD34+ cells in peripheral blood, driving differentiation of components of the immune system (24). Despite their global role in oncogenic cell transformation members of the let-7 family (let-7a, let-7b, let-7g and let-7i) have been shown to be associated with radiation sensitivity and therefore may monitor radiotherapy in HNSCC (25). In detail, let-7a and −7b were downregulated by radiation, while let-7g and let-7i were upregulated and inhibition of let-7g by antagomirs led to increased radiosensitivity of lung carcinoma cells (26).

Radical surgical resection added with radiation and chemotherapy is the established curative treatment for HNSCC (2729). The post-operative radiotherapy is intended to improve loco-regional control and therefore it is inevitable. Unfortunately, hyposalivation is the most common oral complication of radiation therapy (RT) for head and neck cancer patients (30). In addition to decreased saliva volume, RT also causes changes in saliva consistency, buffering capacity, and pH-value (31). However, in recent years several improvements, such as three-dimensional (3D) conformal radiation therapy (3D-CRT) and intensity-modulated radiation therapy (IMRT) have proven to be capable of sparing the salivary glands and thereby to prevent hyposalivation (32).

Hence, it is still unknown whether and to which extent microRNAs associated with HNSCC and radiosensitivity are detectable in oral fluid during and after radiotherapy and if they may act as salivary biomarkers for tumor monitoring. In this study, we screened a HNSCC- and radiation-associated panel of microRNAs for their feasibility as indicators of a tumor-free state of the oral cavity. It was the aim of the present investigation to analyze the prognostic impact of salivary microRNA levels of miR-93, miR-125a, miR-142-3p, miR-200a, miR-203, miR-213, let-7a, let-7b, let-7g and let-7i in patients receiving 3D-CRT treatment.

Materials and methods

Study population

Saliva samples were collected between 06/2002 and 10/2008 within the scope of our previously described study, wherein we examined the parotid gland recovery after radiotherapy (33). The experimental protocol, consent form, and the present retrospective analysis of the saliva samples were approved by the intern institutional review board, the ethics committee of the Martin-Luther-University Halle-Wittenberg, in accordance to the Helsinki declaration. All patients gave written detailed informed consent.

Treatment planning and determination of the parotid gland doses

All patients received 3D-CRT or IMRT treatment planning as previously described (33). Patients were immobilized with individual thermoplastic head-neck-shoulder masks. The planning goal was, while maintaining a homogeneous dose distribution in the target volumes, to minimize mean dose in the contra-lateral parotid gland. No effort was undertaken to spare the submandibular, the sublingual or minor salivary glands. All patients were treated with continuous conventional fractionation and received 2.0-Gy fractions, 1 fraction per day, 5 fractions per week, for 7 weeks. The mean dose and the partial volumes receiving specified doses were determined for each gland from dose-volume histogram (DVH). Based on an algorithm initially proposed by Lyman the DVHs were transformed to single step DVHs (34). Afterwards, mean doses of the ipsilateral and contralateral parotid glands were calculated for every patient in Gy.

All patients underwent saliva collection at different time points: within one week before radiation treatment (baseline), during treatment and 6 and 12 months after the end of RT. All salivary samples were collected at least one hour after a meal at a standardized time of the day (9:00 am to 11:00 pm). Patients were asked to rinse the mouth and swallow any residual saliva. Then, the patients were instructed to chew on a paraffin pellet (Ivoclar Vivadent, Schaan, Liechtenstein) for 5 min. After 5 min samples were collected with the patients expectorating all saliva into sterile test tubes. The samples were cryopreserved immediately after collection at −80°C.

RNA isolation

Saliva (200 µl) was thawed to room temperature and immediately centrifuged (2000 × g, 10 min) to remove remaining cells and cellular debris. RNA was isolated by phenol/chloroform extraction using TRIzol (Invitrogen, Karlsruhe, Germany) according to the manufacturer's instructions. Briefly, saliva supernatant was mixed with 750 µl of TRIzol reagent and 200 µl of chloroform. After centrifugation, the aequous phase containing the RNA was separated and remaining DNA was digested by 5 units DNase (Qiagen, Hilden, Germany). RNA was precipitated with 500 µl of ethanol overnight and washed several times with ethanol (96% and 70%). RNA concentration was analyzed after elution in 50 µl RNase-free H2O using spectrometry (Eppendorf, Hamburg, Germany).

MicroRNA-specific cDNA synthesis

In this study, saliva expression of the following microRNAs was analyzed using TaqMan microRNA primer kits (Applied Biosystems, Darmstadt, Germany): miR-93, miR-125a, miR-142-3p, miR-200a, miR-203, miR-213, let-7a, let-7b, let-7g, let-7i and U18 snoRNA as reference gene. RNA (10 ng) were applied for each microRNA cDNA synthesis using specific RT primer (Applied Biosystems). RNA was incubated with RNAse Inhibitor, Buffer, dNTPs (20 mM) and MuLV Reverse Transcriptase (Fermentas, St. Leon-Rot, Germany) at 16°C for 30 min and 42°C for 30 min. Afterwards, reverse transcriptase was inactivated by a 5 min 85°C step. cDNA was stored at −20°C upon quantitative real-time analysis.

RT-qPCR analyses

cDNA of each individual patient sample was measured in RT-qPCR on a RotorGene 6000 (LTF Labortechnik, Wasserburg, Germany). For the reaction mix, buffer, dNTPS (20 mM), HotStartTaq-Polymerase (Qiagen) and microRNA-specific TaqMan primer (Applied Biosystems) were applied. Product accumulation was detected in fluorescence increase per cycle and quantified by ∆∆Cq method according to Livak and Schmittgen (35). U18 snoRNA expression served as reference gene.

Statistical evaluation

Data were analyzed using SPSS software version 20 (IBM Inc., Chicago, IL, USA). Differences in microRNA expression between the patients groups were visualized by box-plots and analyzed by non-parametric tests (Mann-Whitney U test, Kruskal-Wallis test), and bivariate correlation analyses according to Spearman-Rho. P-values <0.05 were considered statistically significant.

Results

Longitudinal saliva samples were available for 17 patients: 3 women and 14 men (42 samples, termed Coh 1). Overall mean age was 57.8 years (range: 38–79 years). There were 4 patients with oropharyngeal squamous cell carcinomas, 5 patients with oral squamous cell carcinoma, and 8 patients with laryngeal squamous cell carcinoma. The majority were advanced tumors with regional node involvement at the time of treatment. None had distant metastases, whereas it was unknown in two subjects (Table I). On average, patients received a mean dose of 27.7 Gy of the contralateral parotid gland.

Table I.

Patient demographics and tumor statistics.

Table I.

Patient demographics and tumor statistics.

SubjectGenderAge (yrs.)Tumor siteStage

  1Female69Oral, sccT1N0Mx
  2Male63Laryngeal, sccT3N0M0
  3Male68Oral, sccT3N0M0
  4Male56Laryngeal, sccT2N2aM0
  5Male48Oropharynegeal, sccT3N1M0
  6Male55Laryngeal, sccT2N0M0
  7Male63Laryngeal, sccT1N1M0
  8Female51Oral, sccT2N0M0
  9Male40Oral, sccT2N0Mx
10Male38Oral, sccT1N1M0
11Male58Oropharynegeal, sccT2N2bM0
12Male78Laryngeal, sccT2N2aM0
13Male54Oropharynegeal, sccT3N0M0
14Male64Laryngeal, sccT3N2cM0
15Female47Laryngeal, sccT2N2bM0
16Male57Oropharynegeal, sccT2N2bM0
17Male79Laryngeal, sccT2N1M0

Additional saliva samples at non-fixed intervals were collected from 16 patients: 3 women and 13 men (41 samples, termed Coh 0), which were analysed only for the determination of the effects of cryopreservation on the stability of microRNAs.

Measurement of saliva microRNAs

We were able to isolate RNA in detectable amounts from every saliva sample analyzed (Coh 0 + 1). In 95% of the samples analyzed, RNA concentrations ranged from 50 to 180 ng/µl. Expression levels of the selected microRNAs were measurable in the saliva samples to a different extent. miR-93 expression could be detected in 79 samples (95.2%), miR-125a in 71 samples (85.5%), miR-142-3p in 70 samples (84.3%), miR-200a in 80 samples (96.4%), mir-203 in 67 samples (80.7%), miR-213 in 73 samples (88.0%), let-7a in 78 samples (94.0%), let-7b in 68 samples (81.9%), let-7g in 56 samples (67.5%) and let-7i in 80 samples (96.4%). U18 snoRNA was detectable in each saliva sample and was used as reference gene.

MicroRNA expression between the single species was significantly different, ranging from a median relative expression of 58.3 (∆∆Cq value) for miR-93 to a median relative expression of 0.0005 (∆∆Cq value) for let-7g. The specific median relative expression values were as follows: miR-93: 0.583, let-7b: 0.103, miR-213: 0.018, miR-125a: 0.011, let-7i: 0.009, miR-142-3p: 0.0032, miR-203: 0.0028, miR-200a: 0.00004, let-7a: 0.00004, let-7g: 0.000005, respectively (Fig. 1).

In bivariate correlation analyses according to Spearman-Rho, especially miR-93 expression exhibited several highly significant associations to other microRNA expression levels, namely miR-125a, miR-142-3p, miR-203, miR-213, let-7a and b (all positive correlations, Table II). On the other hand, miR-213 and let-7i expression levels as well as let-7a and let-7g expression levels were significantly negatively correlated (rs= −0.31 and rs= −0.39, p=0.005 and p=0.0003, respectively), indicating that there is no general microRNA overexpression in saliva of HNSCC patients.

Table II.

Bivariate correlation analyses according to Spearman-Rho.

Table II.

Bivariate correlation analyses according to Spearman-Rho.

miR correlationsrsp-valuen

miR-93 expressionmiR-125a expression0.340.00283
miR-142-3p expression0.52 6.4×10−783
miR-203 expression0.410.000183
miR-213 expression0.310.00583
let-7a expression0.340.00283
let-7b expression0.310.00583
miR-125a expressionmiR-213 expression0.370.00183
miR-213 expressionlet-7a expression0.410.000183
let-7i expression−0.310.00583
let-7a expressionlet-7g expression−0.390.000383

[i] miR-93 expression exhibited multiple positive correlations to several microRNAs. rS, Spearman-Rank coefficient.

MicroRNA expression pre- and post-radiotherapy

A subset of our cohort with comparable samples (Coh 1) was analyzed for distinct miRNA expression changes in our selected microRNA panel between baseline sample and post-treatment samples. MicroRNAs miR-142-3p (16 of 25 samples), miR-93 (15 of 25 samples) and miR-125a (15 of 25 samples) exhibited an increased level after radiotherapy, while microRNAs let-7a (17 of 25 samples) and let-7i (13 of 25 samples) showed a decrease in their expression after radiotherapy (Fig. 2). However, a consistently down- or up-regulated microRNA could not be identified in this first attempt.

In a more robust statistical encounter, we evaluated whether there is a significantly different expression of one or several microRNAs before (n=21), during (n=31) or after (n=31) radiotherapy without stratification according to the individual patients. In Mann-Whitney U tests, there was no significant alteration between during and post-treatment samples in the expression of the microRNAs tested (p-values ranging from p=0.14 for miR-200a and p=0.2 for miR-93 to p=0.97 for miR-203).

MicroRNA let-7i exhibited an increase in salivary expression during radiotherapy in comparison to the levels before radiotherapy (p=0.058, Mann-Whitney U test) and decreased after treatment in comparison to the levels during radiotherapy (p=0.12, Mann-Whitney U test; Fig. 3A). However, Kruskal-Wallis analyses of the distribution of the specific microRNA expression between the phases pre-, during and post-radiotherapy revealed an attenuation for let-7i (p=0.87), whereas miR-200a remains unequally distributed over the different treatment phases and increases after radiotherapy (p=0.04, Fig. 3B).

Longitudinal distribution of microRNA expression post radiotherapy

Next, we evaluated the statistical distribution of relative expression levels of the selected microRNAs according to the individual patients with saliva samples from defined time points post-radiotherapy - baseline (n=17), 6 months post-therapy (n=14), and 12 months post-therapy (n=8). Of note, especially median miR-93 relative expression increases post-therapy in a time-dependent manner (Fig. 4). In Kruskal-Wallis analyses, no significant alterations of relative microRNA expression distribution were detected over the three time points (ranging from p=0.09 for miR-200a to p=0.98 for let-7i). Comparing miR-93 and miR-200a expression at baseline (n=17) with those at 12 months of post-therapy (n=8), both microRNAs were significantly higher expressed (p=0.047 and p=0.036 in Mann-Whitney U test, respectively).

MicroRNA expression in association to functional saliva gland parameter

Taking into account, that saliva production and secretion after radiotherapy is heavily dependent on saliva gland regeneration, we included the different saliva flow rates (in ml saliva/minute) of the patients at the different time points of collection (by calculating the ratio of microRNA expression/saliva flow rate) in our analyses. Noteworthy, in bivariate correlation according to Spearman-Rho miR-93 and let-7g expression were both associated to saliva flow rate (miR-93: rs= −0.337; p=0.036; let-7g: rs=0.334; p=0.037). The formerly detected associations between microRNA expression and time point of collection (baseline against 12 months post-treatment) remained after inclusion of saliva flow rates (p=0.049 for miR-93 and p=0.012 for miR-200a in Mann-Whitney U tests, respectively). However, in bivariate correlation analyses miR-93 expression was significantly positively correlated to miR-125a (rs=0.59; p=0.000077), miR-142-3p (rs=0.46; p=0.003) and let-7b (rs=0.44; p=0.005), while miR-200a expression was only significantly correlated to let-7a expression (rs=0.37; p=0.02). Furthermore, in a Kruskal-Wallis test the miR-200a expression/saliva flow ratio was significantly differently expressed at the end of treatment and 6 and 12 months after radiotherapy (p=0.036).

Discussion

The result of this study indicate that salivary microRNAs associated with HNSCC and radiosensitivity stay detectable in oral fluid during and after 3D-CRT. Therefore, salivary miRNA analysis still represents a potentially promising approach to monitor therapy response and recurrence of HNSCC in patients treated with radiotherapy. Firstly, we detected a significant increased expression of miR-200a comparing expression at baseline with that at 12 months post-radiotherapy. miR-200a is significantly less expressed in the saliva of OSCC patients in comparison to healthy controls and is considered as putative marker for tumor monitoring (21). Furthermore, low expression of miR-200a is associated with a worse outcome for ovarian carcinoma (36) and cervical cancer patients (37). In terms of pro-oncogenic action, decreased expression of miR-200a promotes the acceleration of meningioma cell growth (38) or the epithelial-mesenchymal transition and invasive potential of anaplastic thyroid carcinoma cells (39). miR-200a overexpression induced inhibition of nasopharyngeal carcinoma cell line growth via translation inhibition of ZEB2 and CTNNB1, while downregulation of miR-200a triggers the epithelial-mesenchymal transition of nasopharyngeal carcinoma cell lines also by ZEB2 activation (40). The increase of miR-200a detected in our cohort was significant in saliva samples at 12 months after end of treatment and may be a hint for wound healing processes and the return to a physiological state.

Furthermore, we detected a significant increased expression of miR-93. miR-93 is also significantly less expressed in the saliva of OSCC patients in comparison to healthy controls and it is a member of the miR-106b-25 cluster. miR-93 plays a role in cell proliferation and anchorage-independent cell growth in hepatocellular carcinoma by regulating for instance the transcription factor E2F1 (41) or the tumor suppressor gene FUS1 (42). In addition, miR-93 promotes tumor growth and angiogenesis in cocultured glioblastoma cell lines, pointing towards the oncogenic potential of the miR-106b-25 cluster (43). On the other hand, miR-93 overexpression inhibits proliferation and colony formation in colon cancer cells (44) and acts differentially in several osteosarcoma cell lines (45). In gastric adenocarcinoma, elevated expression of miR-93 was detected and high miR-93 expression was significantly associated with an advanced disease stage and a decreased survival (46). Moreover, downregulated miR-93 expression was detected in gastric carcinoma, and low miR-93 expression was significantly correlated with an advanced tumor stage and an unfavorable outcome for patients (47). Altogether, these facts show a multi-faceted role of miR-93 in tumor genesis and progression. In our study, miR-93 re-induction and increased expression during post-treatment follow-up was demonstrated, a hint toward tumorsuppressive action of miR-93 in HNSCC progression.

let-7 family was demonstrated as clearly oncogenic transformation associated in several tumor entities such as lung cancer (48), gastric cancer (49) and breast cancer (50). The tumor suppressor roles of let-7 family in HNSCC were consistently demonstrated across studies. let-7 family is also a crucial modulator of stemness and HNSCC progression (51). In this study, the let-7 family members were not clearly correlated with HNSCC treatment follow-up. Only let-7i showed a weak significant association with the application of ionizing radiation within the radiation therapy. However, this could be due to the diverging expression patterns and sometimes synonymous functions of this microRNA family.

These findings were limited by several factors. Most samples had a storage time over more than 5 years at −80°C and had not been stored by specialized protocols or additives. Extensive degradation of samples over time might be possible. However, in the light of several mostly forensic approaches it is likely that degradation was minimal. MicroRNA miR-15b, miR-16 and miR-24 have been proven to be stable in plasma at room temperature for at least 24 h, although introduction of a synthetic microRNA showed high RNAse activity (52). Furthermore, the analyzed microRNAs were still stable after samples underwent up to 5 freeze-thaw cycles (52). Stabilization of microRNA patterns in human whole saliva for up to two days at room temperature was achieved by specialized protocols (53). Noteworthy, mRNA detection of saliva-specific marker in dried saliva stains stored at ambient temperature for up to 6 years and microRNA detection in saliva stains stored at the same conditions up to 1 year was possible in a forensic context (19,54).

Another limitation of the present study is the high standard deviations of the microRNA expression levels due to the small sample size. Thus, prospective analyses in an extended cohort are needed. Furthermore, the patients are only a subpopulation of patients from a previous study with a mean dose of 27.7 Gy of the contralateral parotid gland.

In conclusion, in this study we have shown for the first time that tumor monitoring with salivary microRNAs remains possible even in the radiation-related changes of saliva compounds. In addition to the results of Salazar and coworkers (55) we also developed a reliable method to isolate salivary miRNA at different times under radiotherapy of OSCC. Analysis of salivary microRNA expression in HNSCC patients after RT might potentially yield monitor markers, urgently asked for in the existing literature (56). Salivary miR-200a and miR-93 both were identified to be differentially expressed after radiotherapy and further validation of their role as well as other HNSCC-associated microRNAs such as miR-31 (57) in disease progression is warranted. Furthermore, larger studies about the potential of these microRNAs as tumor or therapy markers even in multicenter studies are possible, as we were able to show a stable detection of microRNA patterns after long-time storage at −80°C.

Acknowledgements

We wish to thank Gabriele Thomas and Katrin Theile for excellent technical support. The study involving the collection of HNSCC patient saliva samples was supported by the German Cancer Aid e.V. grant no. 106386 and grant no. 108429. This study was supported by a Wilhelm-Roux Grant of the Medical Faculty of the Martin-Luther-University Halle-Wittenberg (no. 23/03) to J.H.

References

1 

Curado MP and Boyle P: Epidemiology of head and neck squamous cell carcinoma not related to tobacco or alcohol. Curr Opin Oncol. 25:229–234. 2013.PubMed/NCBI

2 

Sturgis EM and Cinciripini PM: Trends in head and neck cancer incidence in relation to smoking prevalence: An emerging epidemic of human papillomavirus-associated cancers? Cancer. 110:1429–1435. 2007. View Article : Google Scholar : PubMed/NCBI

3 

Mork J: Forty years of monitoring head and neck cancer in Norway - no good news. Anticancer Res. 18:3705–3708. 1998.PubMed/NCBI

4 

Brunin F, Mosseri V, Jaulerry C, Point D, Cosset JM and Rodriguez J: Cancer of the base of the tongue: Past and future. Head Neck. 21:751–759. 1999. View Article : Google Scholar : PubMed/NCBI

5 

Listl S, Jansen L, Stenzinger A, Freier K, Emrich K, Holleczek B, Katalinic A, Gondos A and Brenner H: GEKID Cancer Survival Working Group: Survival of patients with oral cavity cancer in Germany. PLoS One. 8:e534152013. View Article : Google Scholar : PubMed/NCBI

6 

Eckert AW, Kappler M, Schubert J and Taubert H: Correlation of expression of hypoxia-related proteins with prognosis in oral squamous cell carcinoma patients. Oral Maxillofac Surg. 16:189–196. 2012. View Article : Google Scholar : PubMed/NCBI

7 

Michailidou E, Tzimagiorgis G, Chatzopoulou F, Vahtsevanos K, Antoniadis K, Kouidou S, Markopoulos A and Antoniades D: Salivary mRNA markers having the potential to detect oral squamous cell carcinoma segregated from oral leukoplakia with dysplasia. Cancer Epidemiol. 43:112–118. 2016. View Article : Google Scholar : PubMed/NCBI

8 

Gleber-Netto FO, Yakob M, Li F, Feng Z, Dai J, Kao HK, Chang YL, Chang KP and Wong DT: Salivary biomarkers for detection of oral squamous cell carcinoma in a Taiwanese population. Clin Cancer Res. 22:3340–3347. 2016. View Article : Google Scholar : PubMed/NCBI

9 

Fábryová H and Celec P: On the origin and diagnostic use of salivary RNA. Oral Dis. 20:146–152. 2014. View Article : Google Scholar : PubMed/NCBI

10 

Wiklund ED, Gao S, Hulf T, Sibbritt T, Nair S, Costea DE, Villadsen SB, Bakholdt V, Bramsen JB, Sørensen JA, et al: MicroRNA alterations and associated aberrant DNA methylation patterns across multiple sample types in oral squamous cell carcinoma. PLoS One. 6:e278402011. View Article : Google Scholar : PubMed/NCBI

11 

Brinkmann O and Wong DT: Salivary transcriptome biomarkers in oral squamous cell cancer detection. Adv Clin Chem. 55:21–34. 2011. View Article : Google Scholar : PubMed/NCBI

12 

Liu CJ, Lin SC, Yang CC, Cheng HW and Chang KW: Exploiting salivary miR-31 as a clinical biomarker of oral squamous cell carcinoma. Head Neck. 34:219–224. 2012. View Article : Google Scholar : PubMed/NCBI

13 

Matse JH, Yoshizawa J, Wang X, Elashoff D, Bolscher JG, Veerman EC, Bloemena E and Wong DT: Discovery and prevalidation of salivary extracellular microRNA biomarkers panel for the noninvasive detection of benign and malignant parotid gland tumors. Clin Cancer Res. 19:3032–3038. 2013.PubMed/NCBI

14 

Friedman RC, Farh KK, Burge CB and Bartel DP: Most mammalian mRNAs are conserved targets of microRNAs. Genome Res. 19:92–105. 2009. View Article : Google Scholar : PubMed/NCBI

15 

Guarnieri DJ and DiLeone RJ: MicroRNAs: A new class of gene regulators. Ann Med. 40:197–208. 2008. View Article : Google Scholar : PubMed/NCBI

16 

Stefani G and Slack FJ: Small non-coding RNAs in animal development. Nat Rev Mol Cell Biol. 9:219–230. 2008. View Article : Google Scholar : PubMed/NCBI

17 

Hunter P: The great leap forward. Major evolutionary jumps might be caused by changes in gene regulation rather than the emergence of new genes. EMBO Rep. 9:608–611. 2008. View Article : Google Scholar : PubMed/NCBI

18 

Hanson EK, Lubenow H and Ballantyne J: Identification of forensically relevant body fluids using a panel of differentially expressed microRNAs. Anal Biochem. 387:303–314. 2009. View Article : Google Scholar : PubMed/NCBI

19 

Zubakov D, Boersma AW, Choi Y, van Kuijk PF, Wiemer EA and Kayser M: MicroRNA markers for forensic body fluid identification obtained from microarray screening and quantitative RT-PCR confirmation. Int J Legal Med. 124:217–226. 2010. View Article : Google Scholar : PubMed/NCBI

20 

Weber JA, Baxter DH, Zhang S, Huang DY, Huang KH, Lee MJ, Galas DJ and Wang K: The microRNA spectrum in 12 body fluids. Clin Chem. 56:1733–1741. 2010. View Article : Google Scholar : PubMed/NCBI

21 

Park NJ, Zhou H, Elashoff D, Henson BS, Kastratovic DA, Abemayor E and Wong DT: Salivary microRNA: Discovery, characterization, and clinical utility for oral cancer detection. Clin Cancer Res. 15:5473–5477. 2009. View Article : Google Scholar : PubMed/NCBI

22 

Boldrup L, Coates PJ, Wahlgren M, Laurell G and Nylander K: Subsite-based alterations in miR-21, miR-125b, and miR-203 in squamous cell carcinoma of the oral cavity and correlation to important target proteins. J Carcinog. 11:182012. View Article : Google Scholar : PubMed/NCBI

23 

Wong TS, Liu XB, Wong BY, Ng RW, Yuen AP and Wei WI: Mature miR-184 as potential oncogenic microRNA of squamous cell carcinoma of tongue. Clin Cancer Res. 14:2588–2592. 2008. View Article : Google Scholar : PubMed/NCBI

24 

Mintz PJ, Saetrom P, Reebye V, Lundbaek MB, Lao K, Rossi JJ, Gaensler KM, Kasahara N, Nicholls JP, Jensen S, et al: MicroRNA-181a* targets Nanog in a subpopulation of CD34 (+) cells isolated from peripheral blood. Mol Ther Nucleic Acids. 1:e342012. View Article : Google Scholar :

25 

Weidhaas JB, Babar I, Nallur SM, Trang P, Roush S, Boehm M, Gillespie E and Slack FJ: MicroRNAs as potential agents to alter resistance to cytotoxic anticancer therapy. Cancer Res. 67:11111–11116. 2007. View Article : Google Scholar : PubMed/NCBI

26 

Boyerinas B, Park S-M, Hau A, Murmann AE and Peter ME: The role of let-7 in cell differentiation and cancer. Endocr Relat Cancer. 17:F19–F36. 2010. View Article : Google Scholar : PubMed/NCBI

27 

Pignon JP, Bourhis J, Domenge C and Designé L: Chemotherapy added to locoregional treatment for head and neck squamous-cell carcinoma: Three meta-analyses of updated individual data. MACH-NC Collaborative Group. Meta-Analysis of Chemotherapy on Head and Neck Cancer. Lancet. 355:949–955. 2000. View Article : Google Scholar : PubMed/NCBI

28 

Shah JP and Gil Z: Current concepts in management of oral cancer - surgery. Oral Oncol. 45:394–401. 2009. View Article : Google Scholar : PubMed/NCBI

29 

Forastiere AA, Goepfert H, Maor M, Pajak TF, Weber R, Morrison W, Glisson B, Trotti A, Ridge JA, Chao C, et al: Concurrent chemotherapy and radiotherapy for organ preservation in advanced laryngeal cancer. N Engl J Med. 349:2091–2098. 2003. View Article : Google Scholar : PubMed/NCBI

30 

Cooper JS, Fu K, Marks J and Silverman S: Late effects of radiation therapy in the head and neck region. Int J Radiat Oncol Biol Phys. 31:1141–1164. 1995. View Article : Google Scholar : PubMed/NCBI

31 

Möller P, Perrier M, Ozsahin M and Monnier P: A prospective study of salivary gland function in patients undergoing radiotherapy for squamous cell carcinoma of the oropharynx. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 97:173–189. 2004. View Article : Google Scholar : PubMed/NCBI

32 

Hey J, Setz J, Gerlach R, Janich M, Sehlleier S, Schaller HG, Gernhardt CR and Kuhnt T: Parotid-gland-sparing 3D conformal radiotherapy in patients with bilateral radiotherapy of the head and neck region - results in clinical practice. Oral Oncol. 45:e11–e17. 2009. View Article : Google Scholar : PubMed/NCBI

33 

Hey J, Setz J, Gerlach R, Janich M, Hildebrandt G, Vordermark D, Gernhardt CR and Kuhnt T: Parotid gland-recovery after radiotherapy in the head and neck region - 36 months follow-up of a prospective clinical study. Radiat Oncol. 6:1252011. View Article : Google Scholar : PubMed/NCBI

34 

Lyman JT and Wolbarst AB: Optimization of radiation therapy, IV: A dose-volume histogram reduction algorithm. Int J Radiat Oncol Biol Phys. 17:433–436. 1989. View Article : Google Scholar : PubMed/NCBI

35 

Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) method. Methods. 25:402–408. 2001. View Article : Google Scholar : PubMed/NCBI

36 

Hu X, Macdonald DM, Huettner PC, Feng Z, El Naqa IM, Schwarz JK, Mutch DG, Grigsby PW, Powell SN and Wang X: A miR-200 microRNA cluster as prognostic marker in advanced ovarian cancer. Gynecol Oncol. 114:457–464. 2009. View Article : Google Scholar : PubMed/NCBI

37 

Hu X, Schwarz JK, Lewis JS Jr, Huettner PC, Rader JS, Deasy JO, Grigsby PW and Wang X: A microRNA expression signature for cervical cancer prognosis. Cancer Res. 70:1441–1448. 2010. View Article : Google Scholar : PubMed/NCBI

38 

Saydam O, Shen Y, Würdinger T, Senol O, Boke E, James MF, Tannous BA, Stemmer-Rachamimov AO, Yi M, Stephens RM, et al: Downregulated microRNA-200a in meningiomas promotes tumor growth by reducing E-cadherin and activating the Wnt/beta-catenin signaling pathway. Mol Cell Biol. 29:5923–5940. 2009. View Article : Google Scholar : PubMed/NCBI

39 

Braun J, Hoang-Vu C, Dralle H and Hüttelmaier S: Downregulation of microRNAs directs the EMT and invasive potential of anaplastic thyroid carcinomas. Oncogene. 29:4237–4244. 2010. View Article : Google Scholar : PubMed/NCBI

40 

Xia H, Ng SS, Jiang S, Cheung WK, Sze J, Bian XW, Kung HF and Lin MC: miR-200a-mediated downregulation of ZEB2 and CTNNB1 differentially inhibits nasopharyngeal carcinoma cell growth, migration and invasion. Biochem Biophys Res Commun. 391:535–541. 2010. View Article : Google Scholar : PubMed/NCBI

41 

Li Y, Tan W, Neo TW, Aung MO, Wasser S, Lim SG and Tan TM: Role of the miR-106b-25 microRNA cluster in hepatocellular carcinoma. Cancer Sci. 100:1234–1242. 2009. View Article : Google Scholar : PubMed/NCBI

42 

Du L, Schageman JJ, Subauste MC, Saber B, Hammond SM, Prudkin L, Wistuba II, Ji L, Roth JA, Minna JD, et al: miR-93, miR-98, and miR-197 regulate expression of tumor suppressor gene FUS1. Mol Cancer Res. 7:1234–1243. 2009. View Article : Google Scholar : PubMed/NCBI

43 

Fang L, Deng Z, Shatseva T, Yang J, Peng C, Du WW, Yee AJ, Ang LC, He C, Shan SW, et al: MicroRNA miR-93 promotes tumor growth and angiogenesis by targeting integrin-β8. Oncogene. 30:806–821. 2011. View Article : Google Scholar : PubMed/NCBI

44 

Yu XF, Zou J, Bao ZJ and Dong J: miR-93 suppresses proliferation and colony formation of human colon cancer stem cells. World J Gastroenterol. 17:4711–4717. 2011. View Article : Google Scholar : PubMed/NCBI

45 

Montanini L, Lasagna L, Barili V, Jonstrup SP, Murgia A, Pazzaglia L, Conti A, Novello C, Kjems J, Perris R, et al: MicroRNA cloning and sequencing in osteosarcoma cell lines: Differential role of miR-93. Cell Oncol (Dordr). 35:29–41. 2012. View Article : Google Scholar : PubMed/NCBI

46 

Chen L, Jiang M, Yuan W and Tang H: Prognostic value of miR-93 overexpression in resectable gastric adenocarcinomas. Acta Gastroenterol Belg. 75:22–27. 2012.PubMed/NCBI

47 

Xiao ZG, Deng ZS, Zhang YD, Zhang Y and Huang ZC: Clinical significance of microRNA-93 downregulation in human colon cancer. Eur J Gastroenterol Hepatol. 25:296–301. 2013. View Article : Google Scholar : PubMed/NCBI

48 

Johnson SM, Grosshans H, Shingara J, Byrom M, Jarvis R, Cheng A, Labourier E, Reinert KL, Brown D and Slack FJ: RAS is regulated by the let-7 microRNA family. Cell. 120:635–647. 2005. View Article : Google Scholar : PubMed/NCBI

49 

Li X, Zhang Y, Zhang Y, Ding J, Wu K and Fan D: Survival prediction of gastric cancer by a seven-microRNA signature. Gut. 59:579–585. 2010. View Article : Google Scholar : PubMed/NCBI

50 

Yu F, Yao H, Zhu P, Zhang X, Pan Q, Gong C, Huang Y, Hu X, Su F, Lieberman J, et al: let-7 regulates self renewal and tumorigenicity of breast cancer cells. Cell. 131:1109–1123. 2007. View Article : Google Scholar : PubMed/NCBI

51 

Tu HF, Lin SC and Chang KW: MicroRNA aberrances in head and neck cancer: Pathogenetic and clinical significance. Curr Opin Otolaryngol Head Neck Surg. 21:104–111. 2013. View Article : Google Scholar : PubMed/NCBI

52 

Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O'Briant KC, Allen A, et al: Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA. 105:10513–10518. 2008. View Article : Google Scholar : PubMed/NCBI

53 

Patel RS, Jakymiw A, Yao B, Pauley BA, Carcamo WC, Katz J, Cheng JQ and Chan EK: High resolution of microRNA signatures in human whole saliva. Arch Oral Biol. 56:1506–1513. 2011. View Article : Google Scholar : PubMed/NCBI

54 

Zubakov D, Kokshoorn M, Kloosterman A and Kayser M: New markers for old stains: Stable mRNA markers for blood and saliva identification from up to 16-year-old stains. Int J Legal Med. 123:71–74. 2009. View Article : Google Scholar : PubMed/NCBI

55 

Salazar C, Nagadia R, Pandit P, Cooper-White J, Banerjee N, Dimitrova N, Coman WB and Punyadeera C: A novel saliva-based microRNA biomarker panel to detect head and neck cancers. Cell Oncol (Dordr). 37:331–338. 2014. View Article : Google Scholar : PubMed/NCBI

56 

Murdoch-Kinch CA, Russo N, Griffith S, Braun T, Eisbruch A and D'Silva NJ: Recovery of salivary epidermal growth factor in parotid saliva following parotid sparing radiation therapy: A proof-of-principle study. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 111:64–70. 2011. View Article : Google Scholar : PubMed/NCBI

57 

Liu CJ, Kao SY, Tu HF, Tsai MM, Chang KW and Lin SC: Increase of microRNA miR-31 level in plasma could be a potential marker of oral cancer. Oral Dis. 16:360–364. 2010. View Article : Google Scholar : PubMed/NCBI

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August-2017
Volume 38 Issue 2

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Online ISSN:1791-2431

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Copy and paste a formatted citation
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Spandidos Publications style
Greither T, Vorwerk F, Kappler M, Bache M, Taubert H, Kuhnt T, Hey J and Eckert AW: Salivary miR-93 and miR-200a as post-radiotherapy biomarkers in head and neck squamous cell carcinoma. Oncol Rep 38: 1268-1275, 2017
APA
Greither, T., Vorwerk, F., Kappler, M., Bache, M., Taubert, H., Kuhnt, T. ... Eckert, A.W. (2017). Salivary miR-93 and miR-200a as post-radiotherapy biomarkers in head and neck squamous cell carcinoma. Oncology Reports, 38, 1268-1275. https://doi.org/10.3892/or.2017.5764
MLA
Greither, T., Vorwerk, F., Kappler, M., Bache, M., Taubert, H., Kuhnt, T., Hey, J., Eckert, A. W."Salivary miR-93 and miR-200a as post-radiotherapy biomarkers in head and neck squamous cell carcinoma". Oncology Reports 38.2 (2017): 1268-1275.
Chicago
Greither, T., Vorwerk, F., Kappler, M., Bache, M., Taubert, H., Kuhnt, T., Hey, J., Eckert, A. W."Salivary miR-93 and miR-200a as post-radiotherapy biomarkers in head and neck squamous cell carcinoma". Oncology Reports 38, no. 2 (2017): 1268-1275. https://doi.org/10.3892/or.2017.5764