Home General Interest Bioelectrochemistry of nucleic acids for early cancer diagnostics – analysis of DNA methylation and detection of microRNAs
Article Open Access

Bioelectrochemistry of nucleic acids for early cancer diagnostics – analysis of DNA methylation and detection of microRNAs

  • Martin Bartosik

    Martin Bartosik received his PhD in Biophysics at Masaryk University in Brno, Czech Republic, in 2012. He worked at the Institute of Biophysics (Brno), where he studied the behavior of nucleic acids and proteins on electrode surfaces. Currently, he works as a junior scientist at the Masaryk Memorial Cancer Institute (Brno), where he develops electrochemical bioassays for detection of various cancer biomarkers, including microRNAs or DNA methylation. His doctoral and postdoctoral stays include the Department of Nanoengineering at the University of California, San Diego, where he was engaged in the construction of DNA hybridization chips and arrays, and Departamento de Química Analítica at Universidad Complutense de Madrid, where he participated at the project of microRNA detection.

    EMAIL logo
    and Roman Hrstka

    Roman Hrstka received his PhD in Cellular and Molecular Biology at Masaryk University in Brno, Czech Republic, in 2005. Since 2001, he has been working at the Masaryk Memorial Cancer Institute in Brno. His work is focused predominately on the role of anterior gradient proteins in the biology of cancer cells. His doctoral and postdoctoral stays include Ninewells Hospital, University of Dundee, where he participated at the project focused on detection of p53 isoforms and CR UK, University of Edinburgh, where he contributed to the study of alternative transcription of DAPK-1. He also received EMBO fellowship at Institut de Génétique Moleculaire in Paris where he was engaged in the project dealing with regulation of p53 translation.

Published/Copyright: December 21, 2016
Become an author with De Gruyter Brill

Abstract

Dysregulation of gene expression mechanisms has been observed in many tumors, making their analysis of utmost importance. These mechanisms include DNA methylation, an epigenetic mechanism in which 5-carbon of cytosine becomes methylated, leading to gene silencing, and action of short RNA molecules called microRNAs, which regulate protein synthesis at post-transcriptional level by binding to mRNAs. In this review, we describe major roles of both mechanisms in carcinogenesis, offer an overview of currently used methods for their analysis, and summarize most recent advances in electrochemical-based assays and strategies. Advantages of electrochemistry, including favorable cost, time of experiment, or simple instrumentation, are highlighted, along with current challenges that need to be addressed prior to successful application into clinical routine.

Introduction

Regulation of gene expression plays a critical role in the normal development of organisms, affecting processes such as cell growth, proliferation, differentiation, or apoptosis. Hence, its dysregulation causes severe cellular changes, which over time may result in tumorigenesis and ultimately cancer. There are a number of regulatory pathways and mechanisms occurring in cells, acting at pre-transcriptional level (e.g. DNA methylation or histone acetylation), post-transcriptional level (e.g. effect of small non-coding RNAs), or post-translational level (e.g. glycosylation of proteins). Therefore, better understanding of these processes is vital and their potential utilization in cancer diagnostics and therapy is urgent and highly attractive. In this paper, we focus on the analysis of DNA methylation and detection of microRNAs and cover the progress made in these fields in recent years from an electrochemical (EC) point of view. We show that several interesting ways to analyze DNA methylation status were developed, but more frequent application into real tumor samples is needed. Much more work has been done in the field of miRNA detection, where authors achieved ultralow detection limits with various ingenious strategies. However, a more reliable detection of panel of endogenous miRNAs from tumor cells would be highly beneficial.

DNA methylation

DNA methylation is an epigenetic mechanism in which a methyl group is added to the 5-carbon of cytosine residues in CpG dinucleotides (Figure 1A) via action of DNA methyltransferases (DNMTs). CpG dinucleotides are mostly clustered in gene promoters, and thus methylation of cytosines results in gene silencing, either due to direct inhibition of transcriptional factors or due to activation of histone deacetylases (which deacetylate DNA and thus increase compactness of the DNA, resulting in suppression of transcription). Aberrant DNA methylation of certain regions in DNA is often associated with carcinogenesis. Tumors exhibit both increased methylation (hypermethylation) of tumor suppressor gene promoters (Figure 1B) and global demethylation of the genome, causing re-activation of potentially harmful genes or chromosomal instability (Herman and Baylin 2003). A large number of hypermethylated tumor suppressor promoters were reported, including p16 (Belinsky et al. 1998), BRCA1 (Esteller et al. 2000), glutathione-S-transferase (GST) (Esteller et al. 1998), and O6-methylguanine DNMT (MGMT) (Esteller et al. 1999; Hegi et al. 2005). For instance, Hegi et al. (2005) reported that glioblastoma patients treated with an alkylating drug temozolomide showed longer survival when their MGMT gene promoter was methylated. MGMT gene encodes a DNA-repair protein that removes alkyl groups from the O6 position of guanine. When the gene is silenced by methylation, DNA is not repaired and cancer cells trigger apoptosis. Therefore, DNA methylation status of this gene may be an important determinant of treatment efficacy.

Figure 1: (A) Methylcytosine is formed by an addition of the methyl group (donated from S-adenosyl methionine, SAM) to a 5-carbon of the cytosine, catalyzed by DNA methyltransferase (DNMT) enzymes. (B) Simplified overview of DNA methylation role in the development of cancer. Methylation of CpG islands within a tumor suppressor promoter silences this gene, which results in fewer proteins being synthesized and attenuation of the cell’s protection.
Figure 1:

(A) Methylcytosine is formed by an addition of the methyl group (donated from S-adenosyl methionine, SAM) to a 5-carbon of the cytosine, catalyzed by DNA methyltransferase (DNMT) enzymes. (B) Simplified overview of DNA methylation role in the development of cancer. Methylation of CpG islands within a tumor suppressor promoter silences this gene, which results in fewer proteins being synthesized and attenuation of the cell’s protection.

Demethylation of DNA was observed e.g. in prostate, cervical, or liver cancers (Ehrlich 2002). Regarding the cervical cancer, it was, for example, shown that methylation rate of the gene promoter coding an oncoprotein E6 in HPV-16 genome is the highest in healthy women, and the promoter becomes demethylated in subsequent stages of the disease i.e. from first-stage neoplasias to the final stage of carcinoma (Badal et al. 2003; Hublarova et al. 2009), leading to its increased synthesis. Thus, in a more general sense, methylation frequency of oncogenes is associated with disease progression, making it an interesting predictive biomarker for cancer therapy.

Current methods of DNA methylation analysis

Vast majority of techniques for analysis of DNA methylation are based either on sodium bisulfite reaction or on application of methylation-sensitive restriction enzymes. Sodium bisulfite treatment of DNA converts cytosine to uracil but not the methylcytosine (mC), which results in two different DNA sequences depending on their original methylation status (Figure 2A). This is important, as both C and mC pair with guanine, making conventional hybridization techniques ineffective if some kind of pretreatment is not used. A pioneering work by Herman et al. (1996) introduced methylation-specific PCR (MSP), amplifying bisulfite-treated DNA using primers specially designed either for unmethylated DNA (the primer contained more adenines as template after bisulfite conversion had more uracils) or for methylated DNA (primer with more guanines) (Figure 2B). The method is simple, fast, and still used today; the main drawback is that it is not quantitative enough. Quantification, on the other hand, is provided by MethyLight assays, combining MSP with fluorescent TaqMan probes (Eads et al. 2000; Olkhov-Mitsel et al. 2014). These probes are sequence-specific oligonucleotides with a fluorophore attached at the 5′-end and a quencher moiety located internally or at the 3′-end. During the PCR, the probe is cleaved by the exonuclease activity of DNA polymerase, separating the fluorophore from the quencher, increasing the fluorescence intensity. Usually, two TaqMan probes are used, one, designed for unmethylated site and the other, for methylated site, making the method highly specific.

Figure 2: (A) Sodium bisulfite converts cytosine into uracil (in series of steps), but methylcytosine is not converted. (B) An example of DNA sequences that become modified after bisulfite treatment and subsequent PCR amplification, depending on whether they were originally unmethylated (top) or methylated (bottom).
Figure 2:

(A) Sodium bisulfite converts cytosine into uracil (in series of steps), but methylcytosine is not converted. (B) An example of DNA sequences that become modified after bisulfite treatment and subsequent PCR amplification, depending on whether they were originally unmethylated (top) or methylated (bottom).

Bisulfite pyrosequencing provides information on methylation status of individual cytosines (Tost and Gut 2007), although only in shorter DNA sequences up to 250 bp in length. DNA is first treated with sodium bisulfite and then amplified using primers, of which one is biotin-labeled. This generates double-stranded amplicon with biotin at one end. DNA is then denatured, and biotin-labeled strand is attached to streptavidin magnetic beads, ready for sequencing. During this process, DNA polymerase incorporates deoxynucleotide triphosphates, one type at a time (i.e. either dATP, dCTP, dGTP, or dTTP), into the growing strand of DNA template. The incorporation of dNTPs results in the release of pyrophosphate, which is converted into ATP by sulphurylase, driving subsequent conversion of luciferin to oxyluciferin (catalyzed by luciferase). The amount of light released in this process, proportional to the number of incorporated nucleotides, is detected with camera. Any unconsumed dNTPs are degraded with apyrase so that other dNTP may enter the reaction. Pyrosequencing is especially suitable for identifying methylation status of multiple candidate gene promoters, as demonstrated for genes associated e.g. with acute lymphoblastic leukemia (Kuang et al. 2010) or bladder cancer (Marsit et al. 2010). More recently, a popularity of next-generation sequencing (NGS) platforms helped them to enter also DNA methylation studies, especially regarding genome-wide methylation profiling (Harris et al. 2010).

The enzyme-based approach utilizes a class of restriction endonucleases, which specifically recognize and cut DNA only if the cytosine at restriction site is unmethylated; methylation of the cytosine prevents the restriction. The commonly used enzymes include HpaII (cutting at CCGG site), BstUI (CGCG), or HhaI (GCGC). There are also endonucleases that cleave methylated but do not act upon unmethylated DNA e.g. McrBC recognizing two half sites (G/A) mC separated by up to 3 kb (Badal et al. 2003; Hublarova et al. 2009). In both cases, the analyzed DNA sequence must contain the restriction site, which makes this approach dependent on the availability of methylation-sensitive endonucleases. The original Southern blotting analysis of cleaved fragments (Baldwin et al. 2000) is now being replaced with real-time PCR (Bruce et al. 2008), which quantifies amplicons generated only from originally methylated DNA (which was not cleaved). Another technique, Methylation-Sensitive Multiplex Ligation-dependent Probe Amplification (MS-MLPA), combines ligation, restriction, and amplification (Homig-Holzel and Savola 2012; von Kaenel and Huber 2013). In this technique, two oligonucleotide probes designed to adjacently bind to the target sequence are ligated to form a template, which is then PCR amplified using fluorescently labeled primers. PCR products are then separated and quantified with capillary electrophoresis. MS-MLPA utilizes endonucleases to distinguish methylated from unmethylated strands, as the endonuclease will cut only hybrids of unmethylated target sequence strands and the corresponding probes, blocking the PCR amplification of the ligated probes. MLPA probes have unique lengths, allowing detection of different targets in a multiplexed fashion (up to 50 loci in a single reaction is possible). Main drawbacks include semi-quantitative nature and increased time of reaction. Capillary electrophoresis has also been shown to be useful in quantification of mC amount in genomic DNA after its enzymatic hydrolysis into single nucleotides, as cytosine monophosphates were found to migrate faster than methylcytosine monophosphates (Stach et al. 2003; Berdasco et al. 2009).

COBRA (combined bisulfite restriction analysis), as the name implies, combines bisulfite conversion of DNA with restriction digestion (Xiong and Laird 1997). In this method, bisulfite-treated DNA is PCR amplified, resulting in amplicons containing cytosine residues at originally methylated positions or thymine residues at originally unmethylated positions. Subsequent introduction of suitable restriction endonuclease (e.g. BstUI) leads to a cleavage of originally methylated amplicons (having CGCG site) but not unmethylated (TGTG). Separation on gel electrophoresis enables calculation of methylation percentage, determined from a ratio of undigested and digested fragments. Again, the method has been applied also into cancer research e.g. for analysis of hypermethylation of MGMT gene promoter in glioblastomas (Goedecke et al. 2015) or ECRG4 gene promoter in colorectal carcinoma (Goetze et al. 2009).

Bioelectrochemistry in DNA methylation studies

Novel techniques and technologies have recently emerged, becoming potentially useful tools in DNA methylation studies. Electrochemistry is a good example of such emerging technology, providing benefits in terms of simplicity, cost, or analysis time. It also enables miniaturization of the system and parallel measurement of multiple samples at electrode arrays and chips. These attractive features have enabled electrochemistry to enter various fields of biomedical research e.g. detection and analysis of (i) DNA sequences (including bacterial and viral DNAs or mutated genes) (Campuzano et al. 2011; Palecek and Bartosik 2012; Rosario and Mutharasan 2014; Bartosik et al. 2016), (ii) microRNAs (see below), (iii) protein biomarkers (Bertok et al. 2013; Rusling 2013; Palecek et al. 2015), (iv) DNA-protein interactions (Lee et al. 2009; Balintova et al. 2015), (v) protein conformational changes (Palecek et al. 2015), (vi) DNA damage (Hocek and Fojta 2011; Sontz et al. 2012), or (vii) uptake of potential anticancer drugs (Bartosik et al. 2015).

Different EC strategies for analysis of DNA methylation have also been proposed. Perhaps the simplest strategy is direct discrimination of C and mC at the electrode surface, based on their different oxidation potentials (Goto et al. 2010; Wang et al. 2015; Brotons et al. 2016). For instance, Wang et al. (2015) showed that at polypyrrole-functionalized graphene nanowall interface, the potential difference between C and mC peaks within short oligonucleotides is 184 mV, sufficient for their discrimination. Although this approach does not involve restriction enzymes or bisulfite conversion, it requires rather high (micromolar) DNA concentrations. Moreover, it is questionable whether the method can specifically distinguish which cytosine is methylated and which is not.

Several papers reported on EC monitoring of DNMT activity and inhibition by using restriction endonucleases and properly designed DNA sequences (Wu et al. 2012; Muren and Barton 2013; Deng et al. 2014b; Furst et al. 2014; Furst and Barton 2015; Li et al. 2015; Zhang et al. 2015). Although the papers differ in choice of endonucleases, DNA sequences, electroactive labels, or even solid substrate, they all share basic idea behind this strategy. Electrode surface (or magnetic beads) was modified with unmethylated DNA duplex (with one strand usually labeled), containing restriction site for selected endonuclease. In the DNMT absence, incubation of the DNA duplex with the endonuclease caused DNA cleavage, removal of the label, and thus decrease of the signal. On the other hand, if the DNMT was present in the sample, DNA duplex has become methylated, resistant to the cleavage, which enabled the labeled duplex to generate EC signal. Although the papers were primarily aimed at monitoring DNMT activity, information whether certain DNA sequence was or was not methylated could be easily drawn. For instance, Barton’s group developed a platform for the detection of human DNMT1 activity from crude lysates of colorectal tumor biopsies, using gold electrode for duplex immobilization and EC measurement, a methylation-specific restriction enzyme BssHII (recognizing GCGCGC sequence), methylene blue as the electrocatalyst, and ferricyanide for amplification of the signal (Figure 3) (Furst et al. 2014; Furst and Barton 2015). They observed increased DNMT1 activity in colorectal tumors over healthy tissue, making it a possible indicator of cancerous transformation, but it should be noted that Western blotting and quantitative reverse transcription PCR (qRT-PCR) did not confirm this finding. Yet this report, one of the few successfully applied into human tumor tissue, represents an important step in development of new EC biosensing technologies, worth further attention. Using a similar approach, Li et al. (2012) employed graphene oxide to enhance assay sensitivity and tested inhibition effects of two anticancer drugs, 5-azacytidine and 5-aza-deoxycytidine, showing a decrease in DNMT activity with increasing inhibitor concentrations.

Figure 3: Electrochemical scheme (left) and platform (right) for the detection of human methyltransferase activity from crude cell lysates. (Left) Overview of electrochemical detection scheme at the electrode. Crude cell lysate is added to the electrode containing the patterned DNA. If methyltransferase (green) is present (blue arrows), the hemimethylated DNA on the electrode is methylated (green dot) by the methyltransferase to a fully methylated duplex; if methyltransferase is not present (red arrows), the hemimethylated DNA is not further methylated. A methylation-specific restriction enzyme, BssHII (purple), is then added, cleaving only hemimethylated duplex, leading to a diminished signal. If the DNA is fully methylated, DNA is not cleaved and the electrochemical signal associated with methylene blue (MB+) binding to DNA remains protected. (Right) The electrochemical detection platform contains two electrode arrays, each with 15 electrodes in a 5×3 array. Reprinted from Furst et al. (2014) with permission from Proceedings of the National Academy of Sciences of the United States of America.
Figure 3:

Electrochemical scheme (left) and platform (right) for the detection of human methyltransferase activity from crude cell lysates. (Left) Overview of electrochemical detection scheme at the electrode. Crude cell lysate is added to the electrode containing the patterned DNA. If methyltransferase (green) is present (blue arrows), the hemimethylated DNA on the electrode is methylated (green dot) by the methyltransferase to a fully methylated duplex; if methyltransferase is not present (red arrows), the hemimethylated DNA is not further methylated. A methylation-specific restriction enzyme, BssHII (purple), is then added, cleaving only hemimethylated duplex, leading to a diminished signal. If the DNA is fully methylated, DNA is not cleaved and the electrochemical signal associated with methylene blue (MB+) binding to DNA remains protected. (Right) The electrochemical detection platform contains two electrode arrays, each with 15 electrodes in a 5×3 array. Reprinted from Furst et al. (2014) with permission from Proceedings of the National Academy of Sciences of the United States of America.

microRNAs – important players in carcinogenesis

Regulation of gene expression occurs also at post-transcriptional level, predominantly by microRNAs – short, non-coding RNAs, which may hybridize with mRNAs and thus block synthesis of corresponding proteins. Discovered in 1993 as small ~22-nt-long transcripts in C. elegans nematode, they were found to have sequences complementary to a sequence element in the 3ʹ-untranslated region of lin-14 mRNA, indicating that lin-4 may be involved in the regulation of its translation via an antisense RNA-RNA interactions (Lee et al. 1993). Since then, the importance of microRNAs has been demonstrated in various fundamental processes, including cell proliferation, differentiation, metabolism, and survival (Bartel 2009). Soon, it became apparent that deregulation of expression of certain microRNAs is closely linked to carcinogenesis (Iorio and Croce 2012; Lin and Gregory 2015). We will not discuss here the biogenesis, mechanism of action, or detailed functions of miRNAs, as these can be found in numerous reviews (e.g. Bartel 2009; Dong et al. 2013). Instead, we would like to briefly summarize miRNAs’ role in cancer, followed by an overview of nonelectrochemical methods, and a more detailed description of several interesting EC-based approaches.

miRNAs role in cancer

Alteration of miRNA expression is a very frequent phenomenon in cancer. MicroRNA genes are often located in chromosomal regions susceptible to amplifications or deletions/mutations, causing miRNAs upregulation or downregulation, respectively. Upregulation of miRNAs targeting tumor suppressor genes leads to a decreased expression of tumor suppressor proteins (favoring tumor formation). Conversely, downregulation of miRNAs targeting proto-oncogenes causes their increased expression (again, favoring tumor formation by increased synthesis of oncoproteins, enhancing thus cell proliferation). These two processes are depicted in Figure 4.

Figure 4: Two alternative routes to carcinogenesis involving microRNA deregulation. (Left) Overexpression of miRNA regulating tumor suppressor gene leads to its decreased expression, resulting in fewer tumor suppressor proteins to protect the cell. (Right) Downregulated expression of miRNA regulating oncogene (i.e. gene coding an oncoprotein, which supports cell proliferation and division) is not present in sufficient amounts, and thus increased number of oncoproteins is synthesized.
Figure 4:

Two alternative routes to carcinogenesis involving microRNA deregulation. (Left) Overexpression of miRNA regulating tumor suppressor gene leads to its decreased expression, resulting in fewer tumor suppressor proteins to protect the cell. (Right) Downregulated expression of miRNA regulating oncogene (i.e. gene coding an oncoprotein, which supports cell proliferation and division) is not present in sufficient amounts, and thus increased number of oncoproteins is synthesized.

Croce’s group was among the first who linked miRNA deregulation to carcinogenesis. They found that a DNA region frequently deleted in chronic lymphocytic leukemia does not code for a protein but rather for two miRNA sequences, miR-15a and miR-16-1, which became downregulated (Calin et al. 2002). This stimulated further research focused on miRNA roles in cancer, with thousands of papers published each year. miRNAs might play several roles in connection with cancer diagnostics and treatment. First, they represent potentially useful biomarkers for early cancer diagnostics. As an example, a panel of miRNAs was reported for lung cancer already 1–2 years before its development, which could help to select individuals for further surveillance (Boeri et al. 2011). Interestingly, miRNAs were also shown to help in identifying the origin of poorly differentiated tumors, which already metastasized to different sites, indicating that primary tumors maintain a unique miRNA signatures (Lu et al. 2005). Moreover, monitoring selected miRNA levels as predictors of response to therapies might be of great value. For instance, inhibition of overexpressed miR-21 and miR-200b increased sensitivity towards gemcitabine treatment of cholangiocarcinoma (Meng et al. 2006) and inhibition of miR-221 and/or miR-222 sensitized breast cancer cells to tamoxifen-induced cell growth arrest and apoptosis (Zhao et al. 2008).

Perhaps the most visionary but also the most challenging is to use miRNAs as therapeutic tools, usually involving either construction of oligonucleotides (so-called antagomiRs) inhibiting oncogenic miRNAs or reintroduction of downregulated tumor suppressor miRNAs, miRNA mimics, into the cancer cells and tissues (known as miRNA replacement therapy). Yan et al. (2011) tested anti-miR-21 and showed inhibited growth and migration of MCF-7 and MDA-MB-231 cells in vitro and tumor growth in nude mice, providing potential therapeutic applications in breast cancer treatment. However, the questions regarding the stability of miRNAs in vivo, the effectivity of the delivery to target organs, or potentially severe side effects remain to be answered (Bertoli et al. 2015).

Table 1 shows just a few of many microRNA sequences that were found to be either overexpressed or underexpressed in various tumors.

Table 1:

Examples of commonly deregulated miRNAs in cancer.

miRNASequenceAssociated cancerUpregulation/downregulationReferences
let-7a,b,c7a: ugagguaguagguuguauagu u

7b: ugagguaguagguuguguggu u

7c: ugagguaguagguuguauggu u
Liver, lung, prostateDown(Barh et al. 2010)
miR-15/1615a: uag cag cacauaaugguuugu g

16: uag cag cacguaaauauuggc g
Chronic lymphocytic leukaemia (CLL)Down(Aqeilan et al. 2009)
miR-34augg cag ugucuuagcugguug uCLL, hepatocellular, melanoma, prostateDown(Misso et al. 2014)
miR-125125a: ucccugaga ccc uuuaaccugugaBreast, hepatocellularDown(Banzhaf-Strathmann and Edbauer 2014)
miR-21uagcuuaucagacugauguug aBreast, CLL, colon, liver, ovary, pancreas, prostateUp(Virginija and Thomas 2010)
miR-26auucaaguaauccaggauaggc uLungUp(Liu et al. 2012)
miR-155uuaaugcuaaucgugauagggguBreast, colon, lungUp(Mattiske et al. 2012)
miR-205uccuucauuccaccg gag ucu gBladder, lungUp(Qin et al. 2013)
miR-221/222221: agcuacauugucugcuggguuuc

222: agcuacaucuggcuacugggu
Breast, glioblastoma, prostateUp(Chen et al. 2013)

All miRNA sequences were human mature sequences obtained from miRBase (mirbase.org).

Nonelectrochemical techniques

Due to so many important biological roles of miRNAs, there is no surprise that a plethora of techniques for miRNA detection has been developed or modified from already existing techniques to better meet the specific needs of miRNA detection. One such requirement is specificity, which is critical as members of miRNA family often exhibit highly similar sequences, differing in only one or two nucleotides. In addition, miRNAs represent only a minor fraction (~0.01%) of total RNA extracted from biological samples, and thus highly sensitive assays are required (Hunt et al. 2015).

Conventional techniques used in miRNA detection comprise Northern blotting (NB), microarrays, or qRT-PCR. In NB, which has been used since the very beginning of miRNA research, electrophoretic separation of RNA molecules with different lengths is followed by their transfer to a positively charged membrane and hybridization of miRNAs with DNA probes labeled with either 32P radioisotopes or with haptens (e.g. digoxigenin for subsequent chemiluminescence detection). In terms of sensitivity, NB does not particularly excel in comparison with other methods and requires relatively high input amounts of the RNA. Certain modifications of NB settings have led to an improved sensitivity e.g. application of locked nucleic acids (LNA) probes instead of DNA probes (improving also mismatch recognition) (Válóczi et al. 2004) or cross-linking of the RNA to the membrane via 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide chemistry (avoiding UV irradiation of miRNAs), coupled to a ligation step that joins together miRNA and labeled DNA probe (Wu et al. 2014).

Microarrays rely on miRNA hybridization with complementary DNA probes attached to a solid substrate; it is worth noting that it is usually miRNA that is enzymatically labeled. A major advantage is the ability of parallel analysis of hundreds of miRNAs due to distinct localization of individual probes to specific spots within the solid substrate, making the method truly high-throughput. On the other hand, microarrays suffer from being a semi-quantitative technique, requiring another type of validation to quantify expression. Moreover, as different miRNA sequences exhibit different melting temperatures (Tm), hybridization of many miRNAs in parallel would inherently require individual Tm settings for each miRNA/probe duplex in order to obtain high specificity, a task hardly achievable on microarray plates. Again, many modifications to address the above-mentioned challenges were suggested, based e.g. on (i) the application of the Klenow fragment of DNA polymerase I for extension of unmodified miRNAs (hybridized to DNA probes) with biotinylated adenosines and detection via fluorophore-conjugated streptavidin (in so-called RNA-primed, array-based Klenow enzyme, or RAKE assay) (Nelson et al. 2004), (ii) biotin-labeled structure-specific RNA binding protein recognizing array-captured miRNAs (Lee et al. 2010), or (iii) short fluorophore-linked Universal Tag oligonucleotides selectively captured by the target-bound probes via base-stacking effects (SHUT assay) (Duan et al. 2011).

One of the most popular techniques for validating and accurately quantifying miRNAs is qRT-PCR. The first step is a reverse transcription of RNA into cDNA. Due to a short miRNA length, comparable to that of a primer, ingenious strategies must have been developed to make RT more effective e.g. application of stem-loop primers (Chen et al. 2005) or incorporation of poly(A) tail (Shi et al. 2012). Once the cDNA is generated, qPCR may proceed using miR-specific and universal qPCR primer set and TaqMan probes for detection of amplicons. The method is highly sensitive and specific but remains laborious and is especially demanding on quality of the input material (as degradations or impurities result in errors that are amplified during PCR) (Hunt et al. 2015). It has been recently used for analysis of circulating miRNA in serum and plasma (Kroh et al. 2010; Zhu et al. 2014a). However, careful optimization and standardization are still needed to obtain reliable results.

Bioelectrochemistry of miRNAs

EC analysis of RNA has started long before the first papers on microRNA appeared. These early papers reported e.g. polarographic discrimination of dsRNA and ssRNA (Palecek and Doskocil 1974), determination of picomole levels of RNA in a mixture of DNA using differential pulse voltammetry (Palecek and Fojta 1994), or trace measurements of RNA using potentiometric stripping analysis at carbon paste electrodes (Wang et al. 1995). Nowadays, majority of EC assays on RNA focus on miRNA detection, often referred to as biosensors, which are a fruitful area of study with many different strategies available. These vary e.g. in a choice of the solid support on which hybridization happens (electrode, magnetic beads, etc.), a type of label or reporter attached to one of the DNA probes, or employed EC technique (amperometry, voltammetry, impedance spectroscopy, etc.). There are many reviews on EC detection of miRNAs available in the literature, providing more detailed view on research strategies, detection limits, EC techniques, etc. (Palecek and Bartosik 2012; Hamidi-Asl et al. 2013; Campuzano et al. 2014a; Lautner and Gyurcsanyi 2014; Hunt et al. 2015; Keshavarz et al. 2015; Labib and Berezovski 2015). This is not surprising given the fact that almost 200 papers appeared in the last few years on this topic. Here, we wish to briefly describe major challenges in miRNA detection and give some examples how they can be addressed.

During biogenesis, a mature ~21–23-nt miRNA is formed from its longer intermediates, pri-miRNA (1–3 kilobases) and pre-miRNA (60–100 bases), possessing the same sequence motif as mature miRNA. When working with cell lysates or other real samples, these intermediates present in the sample may also become captured by complementary DNA, leading to false negatives. An interesting strategy to avoid this is to use viral protein p19, which specifically binds and sequesters only short RNA duplexes. Campuzano et al. developed a magnetosensor for detection of endogenous miR-21 (playing a role in variety of cancers) in total RNA extracted from cancer cells and human breast-tumor specimens without PCR amplification and sample preprocessing (Figure 5A) (Campuzano et al. 2014b; Torrente-Rodriguez et al. 2014) and also reported dual amperometric sensor for simultaneous detection of miR-21 and miR-205 (Torrente-Rodriguez et al. 2015). Similarly, Labib et al. (2013) described a so-called HPD sensor based on hybridization (H), p19 protein binding (P), and protein displacement (D) and applied the sensor for detection of five miRNAs i.e. miR-21, miR-32, miR-122, miR-141, and miR-200.

Figure 5: Examples of EC-based assays for miRNA detection. (A) Strategy based on p19 protein, which selectively captures RNA/RNA hybrids, in this case, a miRNA of interest hybridized with a properly designed RNA probe labeled with biotin. Subsequent addition of streptavidin/peroxidase generate EC signal, measured at screen-printed carbon electrodes (shown right). (B) Osmium-based approach. Biotinylated capture probes (black) immobilized at the streptavidin magnetic beads (SMB) hybridize with six-valent osmium-labeled miRNA complementary to the probe (green), followed by stringent washing to remove interfering molecules and by a release of the captured miRNA into solution. Labeled miRNA is then adsorbed at the electrode surface and transferred into the blank electrolyte for EC measurement. Reprinted from Bartosik et al. (2014a) with permission from Wiley. (C) Reaction of Os(VI)L with ribose at the 3′-end of the RNA molecule. The Os(VI)L complexes do not react with nucleic acid bases or deoxyribose. L is nitrogenous ligand e.g. 2,2′-bipyridine, temed, etc.
Figure 5:

Examples of EC-based assays for miRNA detection. (A) Strategy based on p19 protein, which selectively captures RNA/RNA hybrids, in this case, a miRNA of interest hybridized with a properly designed RNA probe labeled with biotin. Subsequent addition of streptavidin/peroxidase generate EC signal, measured at screen-printed carbon electrodes (shown right). (B) Osmium-based approach. Biotinylated capture probes (black) immobilized at the streptavidin magnetic beads (SMB) hybridize with six-valent osmium-labeled miRNA complementary to the probe (green), followed by stringent washing to remove interfering molecules and by a release of the captured miRNA into solution. Labeled miRNA is then adsorbed at the electrode surface and transferred into the blank electrolyte for EC measurement. Reprinted from Bartosik et al. (2014a) with permission from Wiley. (C) Reaction of Os(VI)L with ribose at the 3′-end of the RNA molecule. The Os(VI)L complexes do not react with nucleic acid bases or deoxyribose. L is nitrogenous ligand e.g. 2,2′-bipyridine, temed, etc.

Another challenge in miRNA detection is its short length, making a traditional way of using two DNA oligo probes rather ineffective, as the oligos would have to be very short. One way out of it is to use a ligase. Here, two short DNA strands adjacently hybridize to the miRNA of interest, forming a duplex with a gap between the DNA strands. Then T4 DNA ligase is usually applied, which acts upon the duplex by covalently joining 3′-hydroxyl group of one DNA strand with the adjacent 5′-phosphate group of the second DNA strand (Cheng et al. 2014; Zhu et al. 2014b). This creates one longer DNA oligo, with one end originally attached to the solid substrate and the other end labeled for generating signal. The strategy was used e.g. for simultaneous detection of miR-155 and miR-27b (overexpressed in breast cancer) in a single-tube experiment (Zhu et al. 2014b). Magnetic beads were modified with capture DNA probes for both miRNAs, while PbS and CdS quantum dots served as labels for miR-155 and miR-27b, respectively, reaching fM detection limits. Similar work was reported for let-7b detection, using biotinylated DNA probe and a conjugate of streptavidin and alkaline phosphatase (Cheng et al. 2014). Authors applied the system to the cell lysates and obtained good correlation with qRT-PCR when monitoring content of let-7b extracted from HeLa, MCF-7, and A549 cancer cells.

Above, we mentioned that good specificity (i.e. ability to capture only target sequences and not mismatches) is a very important feature of any miRNA assay. One option to achieve high specificity is to use structural analogs of DNA-locked nucleic acids (LNA) and peptide nucleic acids (PNA) as capture probes. LNA contains methylene bridge between 2′-O and 4′-C on ribose, locking it in 3′-endo conformation. This causes increased rigidity of LNA and thus elevated melting temperatures of resulting duplex (Lautner and Gyurcsanyi 2014), leading to an increased hybridization affinity to DNA and RNA. Moreover, LNA exhibits improved mismatch discrimination. PNA also possesses improved hybridization affinity towards DNA or RNA, but for a different reason. It contains neutral peptide backbone instead of a negatively charged phosphate backbone, thus no repulsion between hybridizing strands occurs. Both analogs were applied also in miRNA assays, such as in LNA-based strategy for miR-21 detection, which successfully discriminated perfect duplex from single- and triple-base mismatches (Yin et al. 2012), or when PNA probes were used to distinguish let-7b from let-7a and let-7c miRNAs (Deng et al. 2014a). Wang et al. proposed an interesting strategy based on the so-called Y-junction, in which two capture probes were designed to partially hybridize with each other, resulting in a lower Tm of the duplex. Flanking (unhybridized) ends of these probes (having sequences complementary to the target miRNA) formed in the miRNA presence a longer duplex made of three strands having a “Y” shape, with substantially higher Tm. As hybridization occurred at the thermally controlled electrode, hybridization temperature could be set to retain perfect Y-shaped duplexes but to melt mismatches (Wang et al. 2013). Our approach to address specificity issues was also based on applying higher temperature, namely, on a precise determination of Tm of perfect or mismatched duplexes (with Tm decreasing in the order perfect duplex>single mismatch>double mismatch) and on choosing elevated hybridization temperature in such a way that perfect duplexes were retained while mismatches were renatured (Bartosik et al. 2014a; Bartosik et al. 2014b). In this strategy, we used complexes of six-valent osmium and bipyridine [Os(VI)bipy] to create adducts with miRNA, which were then electrochemically detected at mercury-based electrodes (including solid amalgam electrodes). Due to a catalytic nature of the signal, we reached subnanomolar detection limits (Bartosik et al. 2013). Using this quick, simple procedure, labeled miRNAs were hybridized with biotinylated capture probe attached to the streptavidin magnetic beads, and target miRNA was detected in total RNA samples isolated from human cancer cells (Figure 5B) (Bartosik et al. 2014b). Later, by employing so-called adsorptive transfer stripping technique, in which working electrode was dipped into a microliter-sized drop for direct adsorption of miRNA, we achieved increased sensitivity and decreased sample consumption, enabling detection of nanogram quantities of miRNA present in 500-fold excess of total RNA (Bartosik et al. 2014a).

Perhaps the highest emphasis is currently put on sensitivity. Investigators developed a myriad of assays that focus on pushing detection limits as low as possible. These strategies were many times reviewed, so we will only briefly describe the most recent advances made in the last 2 years. Ma et al. (2016) reported so-called isothermal strand-displacement polymerase reaction, in which miRNA served as a displaceable strand during the primer extension. In short, magnetic beads were first modified with a molecular beacon consisting of ssDNA probe with a sequence complementary to the miRNA. After miRNA hybridized to the probe, a primer has bound to the flanking end of the probe, triggering the amplification reaction catalyzed by phi29 DNA polymerase with a strong displacement activity. This released miRNA into the solution, while new DNA strand containing biotin-labeled cytosines has been synthesized, ready for interaction with streptavidin-alkaline phosphatase conjugate required for subsequent EC measurement. Moreover, released miRNA could bind to another beacon, triggering new amplification reaction, and thus few miRNA molecules ultimately translated into an increased amount of biotin-labeled DNA amplicons, providing a limit of detection of 9 fM. A relatively simple impedance-based protocol has been proposed by Zhang et al. (2016), employing capture-probe modified magnetic beads and duplex-specific nuclease, which preferably cleaves DNA in DNA/RNA hybrids but not ssDNA itself. In the absence of miRNA, no cleavage occurred and the probes, which remained at the magnetic beads, formed a compact negatively charged layer with an increased charge-transfer resistance. On the other hand, miRNA presence caused a digestion of the DNA probes, removing the negatively charged layer, which led to appreciable smaller charge-transfer resistance. Limit of detection was 60 aM, and the method was employed to detect miR-21 in human serum samples of breast cancer patients. Another interesting approach comprised 3D tetrahedron DNA structure made of four DNA probes immobilized at the surface of a gold electrode, coupled with a hybridization chain reaction (Ge et al. 2014). After the tetrahedron was formed, target miRNA hybridized with one of the probes protruding into the solution, followed by an addition of two separate biotin-labeled DNA hairpins. miRNA served as an initiator, opening the first hairpin structure (hairpin 1) to create a duplex. Opened (linearized) hairpin 1 then exposed a new single-stranded region that opened hairpin 2, which in turn opened another hairpin 1, etc., resulting in a chain reaction until the hairpin supply became exhausted (Evanko 2004). As both hairpins were labeled with biotin, the growing chain could accommodate multiple streptavidin-peroxidase conjugates, leading to an increased sensitivity.

Conclusions

Both DNA methylation and microRNAs represent important gene regulation mechanisms, which, when dysregulated, increase a risk of carcinogenesis. To make it more complicated, it appears that there is an association between DNA methylation and microRNA deregulation. CpG methylation of miRNA genes may contribute to their altered expression levels (Suzuki et al. 2012), and conversely, miRNAs themselves can regulate the expression of components of the epigenetic machinery i.e. DNMTs (Iorio and Croce 2012), making the topic even more interesting.

Electrochemistry entered these fields of study rapidly and intensively, producing a great deal of papers each year (especially on miRNA detection). Many EC strategies were developed, each possessing not only strengths but also weaknesses. The main challenges, including selectivity, reproducibility, and stability of modified electrodes, are currently being addressed. However, much more work need to be done regarding the analysis of biological material from patients and strict validation of newly developed assays with already existing methods. This is not an easy task, but several reports from recent years, as described in this review, demonstrated the feasibility of this approach.

About the authors

Martin Bartosik

Martin Bartosik received his PhD in Biophysics at Masaryk University in Brno, Czech Republic, in 2012. He worked at the Institute of Biophysics (Brno), where he studied the behavior of nucleic acids and proteins on electrode surfaces. Currently, he works as a junior scientist at the Masaryk Memorial Cancer Institute (Brno), where he develops electrochemical bioassays for detection of various cancer biomarkers, including microRNAs or DNA methylation. His doctoral and postdoctoral stays include the Department of Nanoengineering at the University of California, San Diego, where he was engaged in the construction of DNA hybridization chips and arrays, and Departamento de Química Analítica at Universidad Complutense de Madrid, where he participated at the project of microRNA detection.

Roman Hrstka

Roman Hrstka received his PhD in Cellular and Molecular Biology at Masaryk University in Brno, Czech Republic, in 2005. Since 2001, he has been working at the Masaryk Memorial Cancer Institute in Brno. His work is focused predominately on the role of anterior gradient proteins in the biology of cancer cells. His doctoral and postdoctoral stays include Ninewells Hospital, University of Dundee, where he participated at the project focused on detection of p53 isoforms and CR UK, University of Edinburgh, where he contributed to the study of alternative transcription of DAPK-1. He also received EMBO fellowship at Institut de Génétique Moleculaire in Paris where he was engaged in the project dealing with regulation of p53 translation.

Acknowledgments

The authors wish to acknowledge support from projects GACR 14-24931P, MEYS-NPSI-LO1413, and MH CZ-DRO (MMCI, 00209805).

References

Aqeilan, R. I.; Calin, G. A.; Croce, C. M. MiR-15a and miR-16-1 in cancer: discovery, function and future perspectives. Cell Death. Differ.2009, 17, 215–220.10.1038/cdd.2009.69Search in Google Scholar PubMed

Badal, V.; Chuang, L. S. H.; Tan, E. H. H.; Badal, S.; Villa, L. L.; Wheeler, C. A.; Li, B. F. L.; Bernard, H. U. CpG methylation of human papillomavirus type 16 DNA in cervical cancer cell lines and in clinical specimens: genomic hypomethylation correlates with carcinogenic progression. J. Virol.2003, 77, 6227–6234.10.1128/JVI.77.11.6227-6234.2003Search in Google Scholar

Baldwin, R. L.; Nemeth, E.; Tran, H.; Shvartsman, H.; Cass, I.; Narod, S.; Karlan, B. Y. BRCA1 promoter region hypermethylation in ovarian carcinoma: a population-based study. Cancer Res.2000, 60, 5329–5333.Search in Google Scholar

Balintova, J.; Spacek, J.; Pohl, R.; Brazdova, M.; Havran, L.; Fojta, M.; Hocek, M. Azidophenyl as a click-transformable redox label of DNA suitable for electrochemical detection of DNA-protein interactions. Chem. Sci.2015, 6, 575–587.10.1039/C4SC01906GSearch in Google Scholar

Banzhaf-Strathmann, J.; Edbauer, D. Good guy or bad guy: the opposing roles of microRNA 125b in cancer. Cell Commun. Signal2014, 12, 30.10.1186/1478-811X-12-30Search in Google Scholar PubMed PubMed Central

Barh, D.; Malhotra, R.; Ravi, B.; Sindhurani, P. MicroRNA let-7: an emerging next-generation cancer therapeutic. Curr. Oncol.2010, 17, 70–80.10.3747/co.v17i1.356Search in Google Scholar PubMed PubMed Central

Bartel, D. P. MicroRNAs: target recognition and regulatory functions. Cell2009, 136, 215–233.10.1016/j.cell.2009.01.002Search in Google Scholar PubMed PubMed Central

Bartosik, M.; Durikova, H.; Vojtesek, B.; Anton, M.; Jandakova, E.; Hrstka, R. Electrochemical chip-based genomagnetic assay for detection of high-risk human papillomavirus DNA. Biosens. Bioelectron.2016, 83, 300–305.10.1016/j.bios.2016.04.035Search in Google Scholar PubMed

Bartosik, M.; Hrstka, R.; Palecek, E.; Vojtesek, B. Adsorptive transfer stripping for quick electrochemical determination of microRNAs in total RNA samples. Electroanalysis2014a, 26, 2558–2562.10.1002/elan.201400449Search in Google Scholar

Bartosik, M.;Hrstka, R.;Palecek, E.; Vojtesek, B. Magnetic bead-based hybridization assay for electrochemical detection of microRNA. Anal. Chim. Acta2014b, 813, 35–40.10.1016/j.aca.2014.01.023Search in Google Scholar PubMed

Bartosik, M.; Koubkova, L.; Karban, J.; Stastna, L. C.; Hodik, T.; Lamac, M.; Pinkas, J.; Hrstka, R. Electrochemical analysis of a novel ferrocene derivative as a potential antitumor drug. Analyst2015, 140, 5864–5867.10.1039/C5AN00958HSearch in Google Scholar

Bartosik, M.; Trefulka, M.; Hrstka, R.; Vojtesek, B.; Palecek, E. Os(VI)bipy-based electrochemical assay for detection of specific microRNAs as potential cancer biomarkers. Electrochem. Commun.2013, 33, 55–58.10.1016/j.elecom.2013.04.009Search in Google Scholar

Belinsky, S. A.; Nikula, K. J.; Palmisano, W. A.; Michels, R.; Saccomanno, G.; Gabrielson, E.; Baylin, S. B.; Herman, J. G. Aberrant methylation of p16(INK4a) is an early event in lung cancer and a potential biomarker for early diagnosis. Proc. Natl. Acad. Sci. USA1998, 95, 11891–11896.10.1073/pnas.95.20.11891Search in Google Scholar PubMed PubMed Central

Berdasco, M. A.; Fraga, M. F.; Esteller, M. In DNA Methylation: Methods and Protocols. Humana Press: Totowa, 2009; pp. 23–34.10.1007/978-1-59745-522-0_2Search in Google Scholar PubMed

Bertok, T.; Katrlik, J.; Gemeiner, P.; Tkac, J. Electrochemical lectin based biosensors as a label-free tool in glycomics. Microchim. Acta2013, 180, 1–13.10.1007/s00604-012-0876-4Search in Google Scholar PubMed PubMed Central

Bertoli, G.; Cava, C.; Castiglioni, I. MicroRNAs: new biomarkers for diagnosis, prognosis, therapy prediction and therapeutic tools for breast cancer. Theranostics2015, 5, 1122–1143.10.7150/thno.11543Search in Google Scholar PubMed PubMed Central

Boeri, M.; Verri, C.; Conte, D.; Roz, L.; Modena, P.; Facchinetti, F.; Calabrò, E.; Croce, C. M.; Pastorino, U.; Sozzi, G. MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer. Proc. Natl. Acad. Sci. USA2011, 108, 3713–3718.10.1073/pnas.1100048108Search in Google Scholar PubMed PubMed Central

Brotons, A.; Vidal-Iglesias, F. J.; Solla-Gullon, J.; Iniesta, J. Carbon materials for the electrooxidation of nucleobases, nucleosides and nucleotides toward cytosine methylation detection: a review. Anal. Meth.2016, 8, 702–715.10.1039/C5AY02616DSearch in Google Scholar

Bruce, S.; Hannula-Jouppi, K.; Lindgren, C. M.; Lipsanen-Nyman, M.; Kere, J. Restriction site-specific methylation studies of imprinted genes with quantitative real-time PCR. Clin. Chem.2008, 54, 491–499.10.1373/clinchem.2007.098491Search in Google Scholar PubMed

Calin, G. A.; Dumitru, C. D.; Shimizu, M.; Bichi, R.; Zupo, S.; Noch, E.; Aldler, H.; Rattan, S.; Keating, M.; Rai, K.; Rassenti, L.; Kipps, T.; Negrini, M.; Bullrich, F.; Croce, C. M. Frequent deletions and down-regulation of microRNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc. Natl. Acad. Sci. USA2002, 99, 15524–15529.10.1073/pnas.242606799Search in Google Scholar PubMed PubMed Central

Campuzano, S.; Kuralay, F.; Lobo-Castanon, M. J.; Bartosik, M.; Vyavahare, K.; Palecek, E.; Haake, D. A.; Wang, J. Ternary monolayers as DNA recognition interfaces for direct and sensitive electrochemical detection in untreated clinical samples. Biosens. Bioelectron.2011, 26, 3577–3583.10.1016/j.bios.2011.02.004Search in Google Scholar PubMed PubMed Central

Campuzano, S.; Pedrero, M.; Pingarron, J. M. Electrochemical genosensors for the detection of cancer-related miRNAs. Anal. Bioanal. Chem.2014a, 406, 27–33.10.1007/s00216-013-7459-zSearch in Google Scholar PubMed

Campuzano, S.; Torrente-Rodriguez, R. M.; Lopez-Hernandez, E.; Conzuelo, F.; Granados, R.; Sanchez-Puelles, J. M.; Pingarron, J. M. Magnetobiosensors based on viral protein p19 for microRNA determination in cancer cells and tissues. Angew. Chem. Int. Ed.2014b, 53, 6168–6171.10.1002/anie.201403270Search in Google Scholar PubMed

Chen, C.; Ridzon, D. A.; Broomer, A. J.; Zhou, Z.; Lee, D. H.; Nguyen, J. T.; Barbisin, M.; Xu, N. L.; Mahuvakar, V. R.; Andersen, M. R.; Lao, K. Q.; Livak, K. J.; Guegler, K. J. Real-time quantification of microRNAs by stem–loop RT–PCR. Nucleic Acids Res.2005, 33, e179.10.1093/nar/gni178Search in Google Scholar PubMed PubMed Central

Chen, W.-X.; Hu, Q.; Qiu, M.-T.; Zhong, S.-L.; Xu, J.-J.; Tang, J.-H.; Zhao, J.-H. miR-221/222: promising biomarkers for breast cancer. Tumor Biol.2013, 34, 1361–1370.10.1007/s13277-013-0750-ySearch in Google Scholar PubMed

Cheng, F.-F.; Zhang, J.-J.; He, T.-T.; Shi, J.-J.; Abdel-Halim, E. S.; Zhu, J.-J. Bimetallic Pd-Pt supported graphene promoted enzymatic redox cycling for ultrasensitive electrochemical quantification of microRNA from cell lysates. Analyst2014, 139, 3860–3865.10.1039/C4AN00777HSearch in Google Scholar

Deng, H.; Shen, W.; Ren, Y.; Gao, Z. A highly sensitive microRNA biosensor based on hybridized microRNA-guided deposition of polyaniline. Biosens. Bioelectron.2014a, 60, 195–200.10.1016/j.bios.2014.04.023Search in Google Scholar PubMed

Deng, H.; Yang, X.; Yeo, S. P. X.; Gao, Z. Highly sensitive electrochemical methyltransferase activity assay. Anal. Chem.2014b, 86, 2117–2123.10.1021/ac403716gSearch in Google Scholar PubMed

Dong, H.; Lei, J.; Ding, L.; Wen, Y.; Ju, H.; Zhang, X. MicroRNA: function, detection, and bioanalysis. Chem. Rev.2013, 113, 6207–6233.10.1021/cr300362fSearch in Google Scholar PubMed

Duan, D.; Zheng, K.-X.; Shen, Y.; Cao, R.; Jiang, L.; Lu, Z.; Yan, X.; Li, J. Label-free high-throughput microRNA expression profiling from total RNA. Nucleic Acids Res.2011, 39, e154.10.1093/nar/gkr774Search in Google Scholar PubMed PubMed Central

Eads, C. A.; Danenberg, K. D.; Kawakami, K.; Saltz, L. B.; Blake, C.; Shibata, D.; Danenberg, P. V.; Laird, P. W. MethyLight: a high-throughput assay to measure DNA methylation. Nucleic Acids Res.2000, 28, e32.10.1093/nar/28.8.e32Search in Google Scholar PubMed PubMed Central

Ehrlich, M. DNA methylation in cancer: too much, but also too little. Oncogene2002, 21, 5400–5413.10.1038/sj.onc.1205651Search in Google Scholar PubMed

Esteller, M.; Corn, P. G.; Urena, J. M.; Gabrielson, E.; Baylin, S. B.; Herman, J. G. Inactivation of glutathione S-transferase P1 gene by promoter hypermethylation in human neoplasia. Cancer Res.1998, 58, 4515–4518.Search in Google Scholar

Esteller, M.; Hamilton, S. R.; Burger, P. C.; Baylin, S. B.; Herman, J. G. Inactivation of the DNA repair gene O-6-methylguanine-DNA methyltransferase by promoter hypermethylation is a common event in primary human neoplasia. Cancer Res.1999, 59, 793–797.Search in Google Scholar

Esteller, M.; Silva, J. M.; Dominguez, G.; Bonilla, F.; Matias-Guiu, X.; Lerma, E.; Bussaglia, E.; Prat, J.; Harkes, I. C.; Repasky, E. A.; Gabrielson, E.; Schutte, M.; Baylin, S. B.; Herman, J. G. Promoter hypermethylation and BRCA1 inactivation in sporadic breast and ovarian tumors. J. Natl. Cancer Inst.2000, 92, 564–569.10.1093/jnci/92.7.564Search in Google Scholar PubMed

Evanko, D. Hybridization chain reaction. Nat. Meth.2004, 1, 186–187.10.1038/nmeth1204-186aSearch in Google Scholar

Furst, A. L.; Barton, J. K. DNA electrochemistry shows DNMT1 methyltransferase hyperactivity in colorectal tumors. Chem. Biol.2015, 22, 938–945.10.1016/j.chembiol.2015.05.019Search in Google Scholar PubMed PubMed Central

Furst, A. L.; Muren, N. B.; Hill, M. G.; Barton, J. K. Label-free electrochemical detection of human methyltransferase from tumors. Proc. Natl. Acad. Sci. USA2014, 111, 14985–14989.10.1073/pnas.1417351111Search in Google Scholar PubMed PubMed Central

Ge, Z.; Lin, M.; Wang, P.; Pei, H.; Yan, J.; Sho, J.; Huang, Q.; He, D.; Fan, C.; Zuo, X. Hybridization chain reaction amplification of microRNA detection with a tetrahedral DNA nanostructure-based electrochemical biosensor. Anal. Chem.2014, 86, 2124–2130.10.1021/ac4037262Search in Google Scholar PubMed

Goedecke, S.; Muehlisch, J.; Hempel, G.; Fruehwald, M. C.; Wuensch, B. Quantitative analysis of DNA methylation in the promoter region of the methylguanine-O-6-DNA-methyltransferase gene by COBRA and subsequent native capillary gel electrophoresis. Electrophoresis2015, 36, 2939–2950.10.1002/elps.201500242Search in Google Scholar PubMed

Goetze, S.; Feldhaus, V.; Traska, T.; Wolter, M.; Reifenberger, G.; Tannapfel, A.; Kuhnen, C.; Martin, D.; Mueller, O.; Sievers, S. ECRG4 is a candidate tumor suppressor gene frequently hypermethylated in colorectal carcinoma and glioma. BMC Cancer2009, 9, 447.10.1186/1471-2407-9-447Search in Google Scholar PubMed PubMed Central

Goto, K.; Kato, D.; Sekioka, N.; Ueda, A.; Hirono, S.; Niwa, O. Direct electrochemical detection of DNA methylation for retinoblastoma and CpG fragments using a nanocarbon film. Anal. Biochem.2010, 405, 59–66.10.1016/j.ab.2010.06.004Search in Google Scholar PubMed

Hamidi-Asl, E.; Palchetti, I.; Hasheminejad, E.; Mascini, M. A review on the electrochemical biosensors for determination of microRNAs. Talanta2013, 115, 74–83.10.1016/j.talanta.2013.03.061Search in Google Scholar PubMed

Harris, R. A.; Wang, T.; Coarfa, C.; Nagarajan, R. P.; Hong, C.; Downey, S. L.; Johnson, B. E.; Fouse, S. D.; Delaney, A.; Zhao, Y.; Olshen, A.; Ballinger, T.; Zhou, X.; Forsberg, K. J.; Gu, J.; Echipare, L.; O’Geen, H.; Lister, R.; Pelizzola, M.; Xi, Y.; Epstein, C. B.; Bernstein, B. E.; Hawkins, R. D.; Ren, B.; Chung, W.-Y.; Gu, H.; Bock, C.; Gnirke, A.; Zhang, M. Q.; Haussler, D.; Ecker, J. R.; Li, W.; Farnham, P. J.; Waterland, R. A.; Meissner, A.; Marra, M. A.; Hirst, M.; Milosavljevic, A.; Costello, J. F. Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications. Nat. Biotech2010, 28, 1097–1105.10.1038/nbt.1682Search in Google Scholar PubMed PubMed Central

Hegi, M. E.; Diserens, A.; Gorlia, T.; Hamou, M.; de Tribolet, N.; Weller, M.; Kros, J. M.; Hainfellner, J. A.; Mason, W.; Mariani, L.; Bromberg, J. E. C.; Hau, P.; Mirimanoff, R. O.; Cairncross, J. G.; Janzer, R. C.; Stupp, R. MGMT gene silencing and benefit from temozolomide in glioblastoma. New Engl. J. Med.2005, 352, 997–1003.10.1056/NEJMoa043331Search in Google Scholar PubMed

Herman, J. G.; Baylin, S. B. Mechanisms of disease: gene silencing in cancer in association with promoter hypermethylation. New Engl. J. Med.2003, 349, 2042–2054.10.1056/NEJMra023075Search in Google Scholar PubMed

Herman, J. G.; Graff, J. R.; Myohanen, S.; Nelkin, B. D.; Baylin, S. B. Methylation-specific PCR: a novel PCR assay for methylation status of CpG islands. Proc. Natl. Acad. Sci. USA1996, 93, 9821–9826.10.1073/pnas.93.18.9821Search in Google Scholar PubMed PubMed Central

Hocek, M.; Fojta, M. Nucleobase modification as redox DNA labelling for electrochemical detection. Chem. Soc. Rev.2011, 40, 5802–5814.10.1039/c1cs15049aSearch in Google Scholar PubMed

Homig-Holzel, C.; Savola, S. Multiplex ligation-dependent probe amplification (MLPA) in tumor diagnostics and prognostics. Diagn. Mol. Pathol.2012, 21, 189–206.10.1097/PDM.0b013e3182595516Search in Google Scholar PubMed

Hublarova, P.; Hrstka, R.; Rotterova, P.; Rotter, L.; Coupkova, M.; Badal, V.; Nenutil, R.; Vojtesek, B. Prediction of human papillomavirus 16 E6 gene expression and cervical intraepithelial neoplasia progression by methylation status. Int. J. Gynecol. Cancer2009, 19, 321–325.10.1111/IGC.0b013e31819d8a5cSearch in Google Scholar PubMed

Hunt, E. A.; Broyles, D.; Head, T.; Deo, S. K. MicroRNA detection: current technology and research strategies. Annu. Rev. Anal. Chem.2015, 8, 217–237.10.1146/annurev-anchem-071114-040343Search in Google Scholar PubMed

Iorio, M. V.; Croce, C. M. MicroRNA dysregulation in cancer: diagnostics, monitoring and therapeutics. A comprehensive review. EMBO Mol. Med.2012, 4, 143–159.10.1002/emmm.201100209Search in Google Scholar PubMed PubMed Central

Keshavarz, M.; Behpour, M.; Rafiee-pour, H.-A. Recent trends in electrochemical microRNA biosensors for early detection of cancer. RSC Adv.2015, 5, 35651–35660.10.1039/C5RA01726BSearch in Google Scholar

Kroh, E. M.; Parkin, R. K.; Mitchell, P. S.; Tewari, M. Analysis of circulating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR (qRT-PCR). Methods2010, 50, 298–301.10.1016/j.ymeth.2010.01.032Search in Google Scholar

Kuang, S.-Q.; Bai, H.; Fang, Z.-H.; Lopez, G.; Yang, H.; Tong, W.; Wang, Z. Z.; Garcia-Manero, G. Aberrant DNA methylation and epigenetic inactivation of Eph receptor tyrosine kinases and ephrin ligands in acute lymphoblastic leukemia. Blood2010, 115, 2412–2419.10.1182/blood-2009-05-222208Search in Google Scholar

Labib, M.; Berezovski, M. V. Electrochemical sensing of microRNAs: avenues and paradigms. Biosens. Bioelectron.2015, 68, 83–94.10.1016/j.bios.2014.12.026Search in Google Scholar

Labib, M.; Khan, N.; Ghobadloo, S. M.; Cheng, J.; Pezacki, J. P.; Berezovski, M. V. Three-mode electrochemical sensing of ultralow microRNA levels. J. Am. Chem. Soc.2013, 135, 3027–3038.10.1021/ja308216zSearch in Google Scholar

Lautner, G.; Gyurcsanyi, R. E. Electrochemical detection of miRNAs. Electroanalysis2014, 26, 1224–1235.10.1002/elan.201400055Search in Google Scholar

Lee, J. M.; Cho, H.; Jung, Y. Fabrication of a structure-specific RNA binder for array detection of label-free microRNA. Angew. Chem. Int. Ed.2010, 49, 8662–8665.10.1002/anie.201004000Search in Google Scholar

Lee, P. E.; Demple, B.; Barton, J. K. DNA-mediated redox signaling for transcriptional activation of SoxR. Proc. Natl. Acad. Sci. USA2009, 106, 13164–13168.10.1073/pnas.0906429106Search in Google Scholar

Lee, R. C.; Feinbaum, R. L.; Ambros, V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell1993, 75, 843–854.10.1016/0092-8674(93)90529-YSearch in Google Scholar

Li, W.; Liu, X.; Hou, T.; Li, H.; Li, F. Ultrasensitive homogeneous electrochemical strategy for DNA methyltransferase activity assay based on autonomous exonuclease III-assisted isothermal cycling signal amplification. Biosens. Bioelectron.2015, 70, 304–309.10.1016/j.bios.2015.03.060Search in Google Scholar PubMed

Li, W.; Wu, P.; Zhang, H.; Cai, C. Signal amplification of graphene oxide combining with restriction endonuclease for site-specific determination of DNA methylation and assay of methyltransferase activity. Anal. Chem.2012, 84, 7583–7590.10.1021/ac301990fSearch in Google Scholar PubMed

Lin, S.; Gregory, R. I. MicroRNA biogenesis pathways in cancer. Nat. Rev. Cancer2015, 15, 321–333.10.1038/nrc3932Search in Google Scholar PubMed PubMed Central

Liu, B.; Wu, X.; Liu, B.; Wang, C.; Liu, Y.; Zhou, Q.; Xu, K. MiR-26a enhances metastasis potential of lung cancer cells via AKT pathway by targeting PTEN. Biochim Biophys Acta2012, 1822, 1692–1704.10.1016/j.bbadis.2012.07.019Search in Google Scholar PubMed

Lu, J.; Getz, G.; Miska, E. A.; Alvarez-Saavedra, E.; Lamb, J.; Peck, D.; Sweet-Cordero, A.; Ebert, B. L.; Mak, R. H.; Ferrando, A. A.; Downing, J. R.; Jacks, T.; Horvitz, H. R.; Golub, T. R. MicroRNA expression profiles classify human cancers. Nature2005, 435, 834–838.10.1038/nature03702Search in Google Scholar PubMed

Ma, W.; Situ, B.; Lv, W.; Li, B.; Yin, X.; Vadgama, P.; Zheng, L.; Wang, W. Electrochemical determination of microRNAs based on isothermal strand-displacement polymerase reaction coupled with multienzyme functionalized magnetic micro-carriers. Biosens. Bioelectron.2016, 80, 344–351.10.1016/j.bios.2015.12.064Search in Google Scholar PubMed

Marsit, C. J.; Houseman, E. A.; Christensen, B. C.; Gagne, L.; Wrensch, M. R.; Nelson, H. H.; Wiemels, J.; Zheng, S.; Wiencke, J. K.; Andrew, A. S.; Schned, A. R.; Karagas, M. R.; Kelsey, K. T. Identification of methylated genes associated with aggressive bladder cancer. PLoS One2010, 5, e12334.10.1371/journal.pone.0012334Search in Google Scholar PubMed PubMed Central

Mattiske, S.; Suetani, R. J.; Neilsen, P. M.; Callen, D. F. The oncogenic role of miR-155 in breast cancer. Cancer Epidemiol. Biomarkers Prev.2012, 21, 1236–1243.10.1158/1055-9965.EPI-12-0173Search in Google Scholar PubMed

Meng, F.; Henson, R.; Lang, M.; Wehbe, H.; Maheshwari, S.; Mendell, J. T.; Jiang, J.; Schmittgen, T. D.; Patel, T. Involvement of human microRNA in growth and response to chemotherapy in human cholangiocarcinoma cell lines. Gastroenterology2006, 130, 2113–2129.10.1053/j.gastro.2006.02.057Search in Google Scholar PubMed

Misso, G.; Di Martino, M. T.; De Rosa, G.; Farooqi, A. A.; Lombardi, A.; Campani, V.; Zarone, M. R.; Gulla, A.; Tagliaferri, P.; Tassone, P.; Caraglia, M. Mir-34: a new weapon against cancer? Mol. Ther. Nucleic Acids2014, 3, e194.10.1038/mtna.2014.47Search in Google Scholar PubMed PubMed Central

Muren, N. B.; Barton, J. K. Electrochemical assay for the signal-on detection of human DNA methyltransferase activity. J. Am. Chem. Soc.2013, 135, 16632–16640.10.1021/ja4085918Search in Google Scholar PubMed PubMed Central

Nelson, P. T.; Baldwin, D. A.; Scearce, L. M.; Oberholtzer, J. C.; Tobias, J. W.; Mourelatos, Z. Microarray-based, high-throughput gene expression profiling of microRNAs. Nat. Methods2004, 1, 155–161.10.1038/nmeth717Search in Google Scholar PubMed

Olkhov-Mitsel, E.; Zdravic, D.; Kron, K.; van der Kwast, T.; Fleshner, N.; Bapat, B. Novel multiplex MethyLight protocol for detection of DNA methylation in patient tissues and bodily fluids. Sci. Rep.2014, 4, 4432.10.1038/srep04432Search in Google Scholar

Palecek, E.; Bartosik, M. Electrochemistry of nucleic acids. Chem. Rev.2012, 112, 3427–3481.10.1016/S1871-0069(05)01003-7Search in Google Scholar

Palecek, E.; Doskocil, J. Pulse-polarographic analysis of double-stranded RNA. Anal. Biochem.1974, 60, 518–530.10.1016/0003-2697(74)90262-0Search in Google Scholar

Palecek, E.; Fojta, M. Differential-pulse voltammetric determination of RNA at the picomole level in the presence of DNA and nucleic acid. Anal. Chem.1994, 66, 1566–1571.10.1021/ac00081a033Search in Google Scholar

Palecek, E.; Tkac, J.; Bartosik, M.; Bertok, T.; Ostatna, V.; Palecek, J. Electrochemistry of nonconjugated proteins and glycoproteins. Toward sensors for biomedicine and glycomics. Chem. Rev.2015, 115, 2045–2108.10.1021/cr500279hSearch in Google Scholar PubMed PubMed Central

Qin, A.-Y.; Zhang, X.-W.; Liu, L.; Yu, J.-P.; Li, H.; Emily Wang, S.-Z.; Ren, X.-B.; Cao, S. MiR-205 in cancer: an angel or a devil? Eur. J. Cell Biol.2013, 92, 54–60.10.1016/j.ejcb.2012.11.002Search in Google Scholar PubMed

Rosario, R.; Mutharasan, R. Nucleic acid electrochemical and electromechanical biosensors: a review of techniques and developments. Rev. Anal. Chem.2014, 33, 213.10.1515/revac-2014-0017Search in Google Scholar

Rusling, J. F. Multiplexed electrochemical protein detection and translation to personalized cancer diagnostics. Anal. Chem.2013, 85, 5304–5310.10.1021/ac401058vSearch in Google Scholar PubMed PubMed Central

Shi, R.; Sun, Y.-H.; Zhang, X.-H.; Chiang, V. L. In next-generation microRNA expression profiling technology: methods and protocols. Humana Press: Totowa, 2012; pp. 53–66.10.1007/978-1-61779-427-8_4Search in Google Scholar PubMed

Sontz, P. A.; Muren, N. B.; Barton, J. K. DNA charge transport for sensing and signaling. Acc. Chem. Res.2012, 45, 1792–1800.10.1021/ar3001298Search in Google Scholar PubMed PubMed Central

Stach, D.; Schmitz, O. J.; Stilgenbauer, S.; Benner, A.; Döhner, H.;Wiessler, M.; Lyko, F. Capillary electrophoretic analysis of genomic DNA methylation levels. Nucleic Acids Res.2003, 31, E2.10.1093/nar/gng002Search in Google Scholar PubMed PubMed Central

Suzuki, H.; Maruyama, R.; Yamamoto, E.; Kai, M. DNA methylation and microRNA dysregulation in cancer. Mol. Oncol.2012, 6, 567–578.10.1016/j.molonc.2012.07.007Search in Google Scholar PubMed PubMed Central

Torrente-Rodriguez, R. M.; Campuzano, S.; Lopez-Hernandez, E.; Granados, R.; Sanchez-Puelles, J. M.; Pingarron, J. M. Direct determination of mir-21 in total RNA extracted from breast cancer samples using magnetosensing platforms and the p19 viral protein as detector bioreceptor. Electroanalysis2014, 26, 2080–2087.10.1002/elan.201400317Search in Google Scholar

Torrente-Rodriguez, R. M.; Campuzano, S.; Lopez-Hernandez, E.; Montiel, V. R.-V.; Barderas, R.; Granados, R.; Sanchez-Puelles, J. M.; Pingarron, J. M. Simultaneous detection of two breast cancer-related miRNAs in tumor tissues using p19-based disposable amperometric magnetobiosensing platforms. Biosens. Bioelectron.2015, 66, 385–391.10.1016/j.bios.2014.11.047Search in Google Scholar PubMed

Tost, J.; Gut, I. G. DNA methylation analysis by pyrosequencing. Nat. Protoc.2007, 2, 2265–2275.10.1038/nprot.2007.314Search in Google Scholar PubMed

Válóczi, A.; Hornyik, C.;Varga, N.; Burgyán, J.; Kauppinen, S.; Havelda, Z. Sensitive and specific detection of microRNAs by northern blot analysis using LNA-modified oligonucleotide probes. Nucleic Acids Res.2004, 32, e175.10.1093/nar/gnh171Search in Google Scholar PubMed PubMed Central

Virginija, J.; Thomas, T. MicroRNA-21: From cancer to cardiovascular disease. Curr. Drug Targets2010, 11, 926–935.10.2174/138945010791591403Search in Google Scholar PubMed

von Kaenel, T.; Huber, A. R. DNA methylation analysis. Swiss. Med Wkly.2013, 143, 1–16.Search in Google Scholar

Wang, J.; Cai, X. H.; Wang, J. Y.; Jonsson, C.; Palecek, E. Trace measurements of RNA by potentiometric stripping analysis at carbon paste electrodes. Anal. Chem.1995, 67, 4065–4070.10.1021/ac00118a006Search in Google Scholar

Wang, P.; Han, P.; Dong, L.; Miao, X. Direct potential resolution and simultaneous detection of cytosine and 5-methylcytosine based on the construction of polypyrrole functionalized graphene nanowall interface. Electrochem. Commun.2015, 61, 36–39.10.1016/j.elecom.2015.09.025Search in Google Scholar

Wang, Z.; Zhang, J.; Guo, Y.; Wu, X.; Yang, W.; Xu, L.; Chen, J.; Fu, F. A novel electrically magnetic-controllable electrochemical biosensor for the ultra sensitive and specific detection of attomolar level oral cancer-related microRNA. Biosens. Bioelectron.2013, 45, 108–113.10.1016/j.bios.2013.02.007Search in Google Scholar PubMed

Wu, H.; Liu, S.; Jiang, J.; Shen, G.; Yu, R. A sensitive electrochemical biosensor for detection of DNA methyltransferase activity by combining DNA methylation-sensitive cleavage and terminal transferase-mediated extension. Chem. Commun.2012, 48, 6280–6282.10.1039/c2cc32397dSearch in Google Scholar PubMed

Wu, W.; Gong, P.; Li, J.; Yang, J.; Zhang, G.; Li, H.; Yang, Z.; Zhang, X. Simple and nonradioactive detection of microRNAs using digoxigenin (DIG)-labeled probes with high sensitivity. RNA2014, 20, 580–584.10.1261/rna.042150.113Search in Google Scholar PubMed PubMed Central

Xiong, Z. G.; Laird, P. W. COBRA: a sensitive and quantitative DNA methylation assay. Nucleic Acids Res.1997, 25, 2532–2534.10.1093/nar/25.12.2532Search in Google Scholar PubMed PubMed Central

Yan, L. X.; Wu, Q. N.; Zhang, Y.; Li, Y. Y.; Liao, D. Z.; Hou, J. H.; Fu, J.; Zeng, M. S.; Yun, J. P.; Wu, Q. L.; Zeng, Y. X.; Shao, J. Y. Knockdown of miR-21 in human breast cancer cell lines inhibits proliferation, in vitro migration and in vivotumor growth. Breast Cancer Res.2011, 13, 1–14.10.1186/bcr2803Search in Google Scholar PubMed PubMed Central

Yin, H.; Zhou, Y.; Zhang, H.; Meng, X.; Ai, S. Electrochemical determination of microRNA-21 based on graphene, LNA integrated molecular beacon, AuNPs and biotin multifunctional bio bar codes and enzymatic assay system. Biosens. Bioelectron.2012, 33, 247–253.10.1016/j.bios.2012.01.014Search in Google Scholar PubMed

Zhang, J.; Wu, D.-Z.; Cai, S.-X.; Chen, M.; Xia, Y.-K.; Wu, F.; Chen, J.-H. An immobilization-free electrochemical impedance biosensor based on duplex-specific nuclease assisted target recycling for amplified detection of microRNA. Biosens. Bioelectron.2016, 75, 452–457.10.1016/j.bios.2015.09.006Search in Google Scholar PubMed

Zhang, L.; Wei, M.; Gao, C.; Wei, W.; Zhang, Y.; Liu, S. Label-free electrochemical detection of methyltransferase activity and inhibitor screening based on endonuclease HpaII and the deposition of polyaniline. Biosens. Bioelectron.2015, 73, 188–194.10.1016/j.bios.2015.05.066Search in Google Scholar PubMed

Zhao, J.-J.; Lin, J.; Yang, H.; Kong, W.; He, L.; Ma, X.; Coppola, D.; Cheng, J. Q. MicroRNA-221/222 negatively regulates estrogen receptor alpha and is associated with tamoxifen resistance in breast cancer. J. Biol. Chem.2008, 283, 31079–31086.10.1074/jbc.M806041200Search in Google Scholar PubMed PubMed Central

Zhu, C.; Ren, C.; Han, J.; Ding, Y.; Du, J.; Dai, N.; Dai, J.; Ma, H.; Hu, Z.; Shen, H.; Xu, Y.; Jin, G. A five-microRNA panel in plasma was identified as potential biomarker for early detection of gastric cancer. Br. J. Cancer2014a, 110, 2291–2299.10.1038/bjc.2014.119Search in Google Scholar PubMed PubMed Central

Zhu, W.; Su, X.; Gao, X.; Dai, Z.; Zou, X. A label-free and PCR-free electrochemical assay for multiplexed microRNA profiles by ligase chain reaction coupling with quantum dots barcodes. Biosens. Bioelectron.2014b, 53, 414–419.10.1016/j.bios.2013.10.023Search in Google Scholar PubMed

Received: 2016-6-20
Accepted: 2016-10-20
Published Online: 2016-12-21
Published in Print: 2017-3-1

©2017 Walter de Gruyter GmbH, Berlin/Boston

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Downloaded on 24.12.2025 from https://www.degruyterbrill.com/document/doi/10.1515/revac-2016-0022/html
Scroll to top button