Background
MicroRNAs (miRNAs) are small, noncoding RNAs (~20–22 nucleotides) that have critical functions in various biological processes [
1]. These naturally occurring miRNAs function by binding to target mRNAs, resulting in the degradation or translational inhibition of the mRNA, based upon the degree of complementarity with it. First described in 1993 in the nematode
Caenorhabditis elegans [
2], to date, thousands of miRNAs have been cloned in higher eukaryotes and a number have been shown to play a role in cell proliferation, apoptosis, growth and morphogenesis [
3‐
5]. At present, dysregulation of miRNAs has been shown to be involved in tumor initiation and progression.
The explosion of data on miRNAs and cancer has put them in the spotlight over the past few years. Numerous studies have highlighted the suspected role of miRNAs in tumorigenesis and have established that profiling of these miRNAs represents an informative method for determining developmental lineage and the differentiation state of various malignancies. The initial connection of miRNAs and cancer was elucidated in leukemia and hematological malignancies, later spurring interest in solid malignancies. For example, one of the first lines of evidence for direct involvement of miRNAs in cancer was the finding that miR-15 and miR-16 are located within a 30 kb deletion in chronic lymphocytic leukemia (CLL), and that both genes were deleted or underexpressed in most cases of this cancer [
6]. Abnormal expression of microRNAs has been found in a variety of solid tumors, including colon, breast, lung, thyroid, glioblastomas, prostate, lymphomas, ovarian, hepatocellular, cervical, and pancreatic carcinomas [
7‐
17].
Comparatively, oral cancer has received very little attention in this area of genome profiling. It is identified as a significant public health threat worldwide because its treatment often produces dysfunction and distortions in speech, mastication and swallowing, dental health, and even in the ability to interact socially. It is one of the 10 most frequent cancers in human males worldwide, with about two thirds of all cases occurring in developing countries [
18]. The most common type of oral cancer is squamous cell carcinoma. At present, the management of oral squamous cell carcinoma (OSCC) includes combinations of surgery, radiotherapy, and chemotherapy [
19]. Despite improvements in these therapies, the 5-year survival rate has not improved significantly and remains at about 50% [
20]. In clinical practice, treatment planning and prognosis for patients with OSCC are mainly based on the TNM classification. TNM classification provides significant diagnostic information concerning the tumor, but does not give the clinician sufficient therapeutic biological information, such as the metastatic potential or the sensitivity or resistance of the tumor to radiotherapy and chemotherapy [
21]. There is an urgent need for diagnostic methods for distinguishing high-risk patients from other patients in order that optimal managements can be applied.
As such, some of the urgent priorities in this field are the need to identify and elucidate novel genes or pathways that may choreograph this disease. In the present study, by using the miRNA microarray technique, we have measured the relative expression of microRNAs in 7,12-dimethyl-benz- [a]-anthrance (DMBA)-induced OSCC in Syrian hamster. We hope that it can contribute to early diagnosis and treatment of this malignancy.
Discussion
Since Sally first established the DMBA-induced oral carcinogenesis model in the cheek pouch of Syrian hamster in 1954, it has become a classic animal model of OSCC [
29]. In this study, we successfully constructed this animal model of OSCC using tri-weekly applications of a 5% solution of DMBA in acetone onto the cheek pouch of Syrian hamsters over about a 12-week period.
For models like the hamster model for OSCC, microarray assay provides a powerful tool for analyzing both miRNA expression patterns and quantitative expression levels, as it profiles thousands of genes simultaneously. This technology is much more efficient than the now outmoded and time-consuming methods used in earlier work, and is becoming the broadest miRNA research tool available [
30]. We used a newly designed microarray platform specific for the analysis of the expression of some 924 mammalian miRNAs. The platform and assay are similar in many respects to other spotted oligonucleotide microarray designs, but have several important differences in application [
24]. First, a modified spotting buffer and an advanced hybridization system were used in this study. These measures have both previously shown to result in large improvements in the local signal intensity and global signal uniformity, as well as in the elimination of the doughnut spots commonly seen on spotted oligonucleotide arrays. These improvements are believed to be due to better blocking of the slide surface chemistry [
31]. A detailed assessment of the quality control and reproducibility of this new miRNA microarray platform has been published [
32]. Using miRNA microarray analysis, we evaluated miRNA expression profiles of OSCC and normal cheek mucosa tissues, and identified seventeen miRNAs that were up-regulated and down-regulated in cancer tissues compared with normal tissues. In addition, hsa-miR-338, mmu-miR-762, and mmu-miR-126-5p were not apparently altered in any of the tumors.
Recently, there have been several studies regarding miRNA expression profiles of various tumor types and the general finding was that overall microRNA expression could differentiate normal versus cancerous tissues [
7‐
17]. Among these previous studies, some miRNAs expression levels were similar to those found in the present study. These results are summarized in Table
2. Lu et al. has demonstrated the use of microRNA signatures as an important advance in cancer diagnosis. Their work indicated that microRNA-based identification of cancers was superior in terms of correctly diagnosing cancer of unknown primaries when compared to mRNA classification [
33].
Hundreds of miRNAs have been identified in recent years and miRNA functional identification has become one of the most active research fields in biology. However, only a limited number of miRNAs has yet been defined functionally through overexpression, misexpression, and
in vitro knockdown [
34]. Recently, several studies have indicated that increased or decreased miRNA levels play a critical role in head and neck carcinogenesis. Using miRNA microarray analysis, Chang et al. identified seven miRNAs that were up-regulated (mir-21, let-7, 18, 29c, 142-3p, 155, and 146b) and one miRNA that was down-regulated (mir-494) in HNSCC primary tissue and cell lines. Moreover, they demonstrated that cytochrome c release was decreased by mir-21 knockdown, which suggested mir-21 inhibited several mRNAs that then led to a cascade of events that prevented apoptosis and increased cellular proliferation [
35]. In addition, Tran et al. identified 54 commonly expressed miRNA genes, which included 31 up-regulated and 23 down-regulated miRNAs. The profiling data represented nine cell lines from four different anatomical head and neck sites [
36]. In comparison to these previous studies, the expression tendency of four miRNAs (hsa-miR-21, hsa-miR-155, hsa-miR-200b, and hsa-miR-221) were found to be similar in our study. The similarity in expression of hsa-miR-21 in previous and our studies in head and neck squamous cell carcinoma and cancer cell lines is of particular interest. These findings, in conjunction with our study, demonstrate that miR-21 may play a critical role in head and neck carcinogenesis. This miRNA should therefore become a focus for the development of anti-microRNA preclinical therapeutic strategies for OSCC abrogation in the future.
Considering only the highly conserved microRNAs that were common in both humans and hamsters, we used the TargetScan program to check if the SAM-retrieved microRNAs were conservative types. In addition to mmu-miR-762 and mmu-miR-126-5p, fifteen other microRNAs were found highly conserved in most vertebrates. At present, mmu-miR-762 and mmu-miR-126-5p are not known to have been reported in any tumors.
Since miRNAs can function as oncogenes or as tumor suppressor genes, they provide a logical therapeutic target for cancer treatment [
37]. Modified anti-miRNA oligonucleotides (AMOs) have been used by many groups to inhibit miRNAs with oncogenic properties. For example, Chan et al. successfully applied 2'-O-methyl- and DNA/LNA-mixed oligonucleotides to specifically knockdown miR-21, in order to investigate the potential contribution of this miRNA in the regulation of apoptosis-associated genes in glioblastoma cell lines [
38]. Thus, to supplement and/or enhance the function of tumor suppressor miRNAs due to a deletion or a loss of function mutation, a therapeutic approach could entail exogenous delivery of corrective synthetic miRNAs in the form of double-stranded miRNA mimics [
39]. Takamizawa et al. found that enforced expression of let-7 in the lung adenocarcinoma cell line A549 inhibited lung cancer cell growth
in vitro. This holds promise that let-7 may be useful in treatment of lung cancer or in enhancing currently available treatments [
40]. The microRNA field is rapidly developing, and the functions and signaling pathways of increasingly greater numbers of miRNAs are being carefully studied. The activation or silencing of miRNAs identified in the present study and in previous studies could prove pivotal in the design of therapeutic strategies for OSCC treatment in the future, although we are presently far from that point.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
In our study, all authors have contributed significantly, and that all authors are in agreement with the content of the manuscript. Each author's contribution to the paper:TY: First author, background literature search, data analysis, development of final manuscript
XYW: Corresponding author, research instruction, data analysis, development of final manuscript. RGG: background literature search, data analysis. AL: research instruction, development of final manuscript. SY: research instruction, background literature search. YTC: data analysis, background literature search. YMW: research instruction, development of final manuscript. CMW: research instruction, data analysis. XZY: background literature search, data analysis.