Pre-analytical variables in miRNA analysis

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Clinical Biochemistry xxx (2013) xxx–xxx

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CLB-08311; No. of pages: 8; 4C: 2

Contents lists available at SciVerse ScienceDirect

Clinical Biochemistry

j ourna l homepage: www.e lsev ie r .com/ locate /c l inb iochem

Review

Pre-analytical variables in miRNA analysis

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Nils Becker, Christina M. Lockwood ⁎Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA

⁎ Corresponding author at: Department of PatholoMO 63110, USA. Fax: +1 314 362 1461.

E-mail address: [email protected] (C.M. Lo

0009-9120/$ – see front matter © 2013 The Canadian Shttp://dx.doi.org/10.1016/j.clinbiochem.2013.02.015

Please cite this article as: Becker N, Lockwooj.clinbiochem.2013.02.015

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Article history:Received 5 July 2012Accepted 21 February 2013Available online xxxx

Keywords:Pre-analyticalVariablesmiRNAMicroRNACirculatingTissueFFPE

PROMicroRNAs (miRNAs) are short non-coding RNAs that are involved in the regulation of cellular processes and

have been shown to be differentially expressed in neoplasia and other disease states. This rendersmiRNAs prom-ising diagnostic and prognostic biomarkers in tissues and body fluids, especially in blood. However, numerousvariables can influence the detection of miRNAs in the pre-analytical phase and lead to erroneous results. Thisis of particular concern when miRNA profiles are used clinically and alter diagnosis and patient treatment.Since miRNAs have been discovered relatively recently, systematic studies examining pre-analytical variablesare rare. Therefore, this review comprehensively summarizes the current knowledge of pre-analytical variablesthat influence miRNA analysis in general, as well as pre-analytical variables that are specific to the detection ofcirculating miRNAs and tissue miRNAs.

© 2013 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

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Contents

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Common pre-analytical variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

Collection procedures and specimen processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0miRNA extraction and labeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0miRNA stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Individual variance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Drugs and chemicals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

Pre-analytical variables for circulating miRNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Specimen collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Storage and stability of circulating miRNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Blood cell count . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Hemolysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Plasma volume. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Plasma components/polymerase inhibitors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

Pre-analytical variables for tissue miRNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Time ex vivo/warm ischemia time. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Fixative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Storage and stability of tissue miRNAs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Microdissection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Immunohistochemistry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0

gy and Immunology, Washington University School of Medicine, 660 S. Euclid Ave., Campus Box 8118, St. Louis,

ckwood).

ociety of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

d CM, Pre-analytical variables in miRNA analysis, Clin Biochem (2013), http://dx.doi.org/10.1016/

http://dx.doi.org/10.1016/j.clinbiochem.2013.02.015

mailto:[email protected]


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Fig. 1. Pre-analytical variables that are either shared or selectively affect circulating ortissue microRNAs.

Table 1 t1:1

t1:2Common pre-analytical variables.

t1:3Variable Effect References

t1:4miRNA extraction Guanidine/phenol/chloroform andcommercial extraction kits areavailable with significant variabilitybetween different methods. SomeRNA extraction methods are notsuitable for analytes b200 nt.

[16–21]

t1:5miRNA labeling Labeling methods have an importantimpact on miRNA detection and arenot interchangeable.

[21]

t1:6Age Numerous individual factors caninfluence miRNA expression levels.Awareness of the different factors ismore feasible than standardization.

[47]t1:7Diet [26–45]t1:8Exercise [46,47]t1:9Race [48]t1:10Altitude [49]t1:11Drugs and chemicals Certain drugs and a wide variety of

environmental chemicals, includingmetals and cigarette smoke, affectmiRNA levels.

[51–64]

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Introduction

MicroRNAs (miRNAs) are regulatory non-coding RNAs that areinvolved in a multitude of cellular processes, including development,differentiation, proliferation, apoptosis, and metabolism. Due to thewidespread contribution of miRNAs in cellular functions, the detec-tion of miRNAs as biomarkers for diagnostic and prognostic purposeshas attracted enormous interest since their initial discovery in 1993[1]. MiRNAs are differentially regulated in a variety of malignancies,including chronic lymphocytic leukemia, lung, colorectal, breast, pros-tate, ovarian, and pancreatic cancer [2–9], as well as in other diseasestates, such as liver disease and trisomy 21 [10,11]. However, whilemolecular analysis of DNA and larger RNA transcripts is fundamentallyestablished and validated, methodologies for miRNA detection andanalysis are still evolving. Thus, standardization and comparabilityare not only influenced by different analytical techniques but also amultitude of other variables. In addition to variables such as varyingGC content, which also applies to DNA or messenger RNA analysis,miRNA analysis presents further difficulties due to the small size ofmiRNAs (~18–25 nt). Beyond these characteristics, quantification ofmature miRNAs is additionally challenging because mature miRNAsare derived from longer primary and precursor miRNA molecules[12]. Another factor complicating standardization and comparabilitybetween studies is the paucity of systematic studies that investigateinfluencing variables. All of these challenges affect both analytical de-tection, as discussed by Planell-Saquer and Rodicio in this issue ofClinical Biochemistry, as well as pre-analytical considerations. In thisreview, we focus on the pre-analytical phase of miRNA measurementand deliberate common variables as well as variables specific to eithercirculating or tissue miRNAs.

Common pre-analytical variables

Pre-analytical variables are a common source for erroneous ormisleading laboratory test results [13–15]. Although a significantsource of pre-analytical error, general laboratory issues such as sam-ple identification are beyond the scope of this review and have beencomprehensively discussed by Bonini et al. and Lippi et al. [13,14].In the relatively undeveloped field of miRNA analysis, general guide-lines for specimen collecting and handling have not been universallyimplemented and many variables are still under investigation. To fur-ther complicate this matter, studies frequently employ different pro-tocols encompassing varying extraction techniques and sampletreatments. These factors confound the comparability of results in ad-dition to analytical and post-analytical differences. They also hinderthe implementation of miRNA analysis as a reliable and reproduciblemeans to aid in the diagnosis and prognosis of a variety of malignan-cies and other diseases.

The pre-analytical variables of miRNA analysis of blood and otherbody fluids that are similar to analysis of tissue miRNA will bediscussed in this common chapter. Variables more specific to circulat-ing or tissue miRNA will be discussed in the corresponding chapters.Fig. 1 summarizes these two specific groups of variables as well asthe common variables, which are listed in more detail in Table 1.

Collection procedures and specimen processing

While the collection procedures and specimen processing harbor amultitude of variables that affect miRNA analysis, most are specific toeither circulating or tissue derived miRNAs and will therefore bediscussed in the associated chapters.

miRNA extraction and labeling

After the collection and processing of fluids or tissues for miRNAanalysis, miRNAs must be extracted from the specimen. A number of

Please cite this article as: Becker N, Lockwood CM, Pre-analytical variablej.clinbiochem.2013.02.015

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ROmethods for total RNA and miRNA preparation are currently available.

They can be generally grouped into guanidine/phenol/chloroform(GPC) extraction on the one hand, and commercial isolation kits thatare either column or bead based on the other hand. Most extractiontechniques are comparable within a single method; however, severalgroups have comparedmethods and demonstrated significant variationbetween different preparation methods. Some commercial isolationtechniques that have been used are not suitable for extracting RNAssmaller than 200 nt, which encompasses miRNAs. Doleshal et al. exam-ined the efficacy of five commercially available kits by comparing Abso-lutely RNA FFPE Kit (Stratagene), High Pure FFPE RNA Micro Kit(Roche), PureLink FFPE RNA Isolation Kit (Invitrogen), RecoverAllTotal Nucleic Acid Isolation Kit (Ambion), and RNeasy FFPE Kit (Qiagen)[16]. They observed 5- to 20-fold decreases in miRNA levels as mea-sured by qRT-PCR when starting with equivalent total RNA input de-rived from three of the extraction kits (Absolutely RNA FFPE Kit, HighPure FFPE RNA Micro Kit, and PureLink FFPE RNA Isolation Kit). Theremaining two kits, RecoverAll Total Nucleic Acid Isolation and RNeasyFFPE, were more consistent, demonstrating an average RNA yield thatwas 1.7 times higher. Within these two kits, the RecoverAll TotalNucleic Acid Isolation Kit was more reproducible than the RNeasyFFPE Kit. Using qRT-PCR, they showed that the levels of miR-24 andmiR-103 were approximately two-fold higher with miRNA from theRecoverAll kit, while the level of miR-191 was comparable. Using adifferent set of three methods for RNA extraction, Ach et al. compared

s in miRNA analysis, Clin Biochem (2013), http://dx.doi.org/10.1016/



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phenol/guanidinium (TRIzol, Invitrogen) to miRNeasy (Qiagen) andmirVana (Life Technologies) and showed that most miRNA levelswere comparable as measured by microarray [17]. However, a smallgroup of up to ten miRNAs consistently had at least 2-fold differentialexpression that was confirmed by qPCR. When miRNAs were extractedwith TRIzol, miR-29b, miR-33 and miR-219 were consistently de-creased, while miR-149, miR-328, miR-574, and miR-766 displayedhigher levels in mirVana preps. Overall, they found that the degree ofvariability in hybridization to microarrays was highest when using dif-ferent extraction methods, followed by different extractions using thesame method, and lowest for different hybridization days while usingthe same extraction. Votavova et al. similarly compared a GPC methodto the High Pure RNA Paraffin Kit (Roche) and demonstrated lower Ctvalues of beta-2 microglobulin (B2M) when miRNA was extractedfrom formalin-fixed paraffin-embedded tissue (FFPE) by the commer-cial kit [18]. As part of their study on various challenges in circulatingmiRNA analysis, McDonald et al. also compared four commercialmiRNA extraction kits measuring four miRNAs with RT-qPCR [19].Their data showed that the mirVana PARIS kit (Life Technologies) hadthe highest mean yield of miR-15b and miR-16 and the second highestyield of miR-24 and cel-miR-39 when compared to miRNeasy Mini Kit(Qiagen), mirPremier microRNA Isolation Kit (Sigma), and High PuremiRNA Isolation Kit (Roche). For miR-24 and cel-miR-39, themiRNeasyMini Kit had the highest mean yield. Of all four kits, the High PuremiRNA Isolation Kit had the lowest variability. Wang et al. extendedthe analysis of extraction methods to include different detectionmethods. They examined the effect of extractionmethodwhenmiRNAswere measured by both microarray and Northern blot [20]. Their datashowed the highest correlation when a phenol/chloroform extractionmethod (Trizol LS total or Stratagene total RNA kit) was performed.

More recently, Dahlgaard et al. assessed different RNA extractionmethods as well [21]. Their findings concluded that the HighPure andRecoverAll purification kits differed in the detected miRNA signalswith RecoverAll having a higher yield. These findings were consistentwith thepreviouslymentioned study fromDoleshal et al. [16]. However,Dahlgaard et al. were further able to show that different labelingmethods for microarrays, such as the FlashTag Biotin labeling kit(Affymetrix) and FlashTag Biotin HSR labeling kit (Affymetrix), havean even greater impact on the detection of miRNAs as quantified bymi-croarray, which clearly indicated that the two labeling methods are notinterchangeable. Interestingly, this effect was so profound that miRNAslabeled with the same kit were more similar between two different pa-tients than miRNAs from the same sample that were labeled with twodifferent kits.

miRNA stability

A crucial factor in the pre-analytical phase is the analyte stability,particularly in the context of an RNA species. Fortunately, miRNAshave several unique attributes that make them well-suited to labora-tory measurement. One of these is their size, which is so small thatchallenges inherent in longer RNA analytes, such as crosslinking andfragmentation stemming from formalin fixation, do not arise [22].In addition, miRNAs appear to be more stable than messenger RNAduring storage, which was initially attributed to the observationthat miRNAs are not subject to endogenous RNase degradation [23].This, however, was found to be incorrect when synthesized miRNAwas shown to be degraded by RNAse. Therefore, it was originally pos-tulated that miRNAs escape degradation by being encapsulated inmembrane-bound vesicles like exosomes. However, later experi-ments showed that the majority of circulating miRNAs are not associ-ated with vesicles, but rather copurify with the argonaute 2 (Ago2)ribonucleoprotein complex [24,25]. This protein complex appears toconfer much of the miRNA protection from RNases. These findingsled to the hypothesis that extracellular miRNAs are largely remnantsof dead cells that remain highly stable in the Ago2 complex [25].


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Aside from the protection by the protein complex, the stability ofmiRNA largely depends on the storage conditions, as well as speci-men type and handling, such as formalin-fixation or freezing. Sincethey are largely specimen-specific, these variables will be discussedin the corresponding chapters.

Individual variance

Another extremely important variable, and undoubtedly the leaststandardizable, is the individual itself. Since miRNAs are deeplyentwined in regulatory networks, their levels are prone to influenceby both intra-individual and external factors, including diet, exercise,age, race, and even altitude, all of which will be discussed in thischapter.

A wide variety of dietary components have been examined in re-spect to their epigenetic influence. All-trans-retinoic acid (ATRA) isthe most biologically active form of vitamin A. Due to the sensitivityof acute promyelocytic leukemia (APL) to ATRA, its effect on miRNAexpression was examined in human APL cell lines and the miRNAprofile was altered by ATRA treatment [26,27]. In addition, 1,25-hydroxyvitamin D was shown to downregulate miR-181a and miR-181b [26,27] while 25-hydroxyvitamin D altered miR-182 expres-sion [28]. Vitamin Ewas also found to changemiR-182 expression [29].MiR-122 was found to be influenced by folate [30], which alsochanged miR-222 expression levels [31].

In addition to vitamins, a number of other dietary components havebeen investigated. This includes selenium, which has been shown to af-fect most members of themiR-34 family [32] in prostate cancer cells. Ina rat model, Davidson et al. showed that polyunsaturated fatty acidsaltered miRNA expression in carcinogen-induced colon cancer [32].Chartoumpekis et al. demonstrated in mice that several miRNAs havedifferent expression patterns in obese mice after long-term high-fatdiet compared to control mice [33]. Amultitude of other dietary constit-uents have been found to influencemiRNA expression profiles. These in-clude polyphenols such as proanthocyanidins [34], curcumin [35,36],resveratrol [37,38], catechins [39], and ellagitannin [40], as well asisoflavones [41–45], indoles [41,42] and several other compounds.

Exercise can also influence circulating miRNA levels. Radom-Aizikand coworkers examined exercise-induced changes in miRNA profilesin peripheral bloodmononuclear cells of youngmen [46]. Bymicroarrayanalysis, they observed changes in 34 miRNAs, many of which are in-volved in inflammatory processes. Bridging exercise and age variables,Drummond et al. showed that a subset of miRNAs have higher expres-sion in older versus younger men at rest whereas resistant exercisewith an anabolic stimulus altered expression of primary and maturemiRNAs predominantly in younger men [47]. Te et al. investigatedmiRNA expression profiles in lupus nephritis and found different ex-pression patterns in samples from African-Americans and Americansof European ancestry [48]. Chen et al. showed that high altitude leadsto changes in the miRNA expression profile [49]. While several ofthese findings need to be further validated to confirm the observations,they nonetheless illustrate the vast influences underlying miRNA pro-files. In order to compile the myriad interactions of external factorswith miRNAs, a database was recently proposed by Yang et al. [50].

Drugs and chemicals

Environmental chemicals (ECs), including smoking-related expo-sures, can also lead to altered miRNA concentrations. Schembri et al.showed that miR-218 levels in primary bronchial epithelium are de-creased after cigarette smoke exposure [51]. Interestingly, Marczyloet al. investigated the effect of smoking on miRNA expression remotefrom the pulmonary system, namely in human spermatozoa, andfound 28 miRNAs to be significantly differentially expressed, ten ofwhich had validated targets [52]. Given the altered expression pro-files of miRNAs in cancer, it is perhaps unsurprising that numerous




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studies investigating the effect of anti-cancer drugs onmiRNA profilesin human cancer cells similarly showed differential expression of cer-tain miRNAs [53–56].

Moreover, numerous environmental chemicals have been shownto affect miRNA expression levels. These chemicals include variousmetals, such as arsenic [31,57], cadmium and lead [58], aluminum[59,60], particulate matter [58,61], as well as bisphenol A (BPA) [62]and diethylstilbestrol [63].

In a computational study, Wu and Song performed a genome wideassociation analysis investigating the interactions between ECs andmiRNAs. They revealed a large network of interactions between 407miRNAs and 497 ECs, which they were able to further subclassifyinto 14 groups [64]. Overall, numerous miRNAs appear to be proneto external influences in the form of chemical exposure.

Pre-analytical variables for circulating miRNAs

Circulating miRNAs have increasingly been touted as promisingbiomarkers, especially for certain types of cancer. The general pre-mise behind them is that tumors ‘secrete’ tumor-specific miRNAs,which can be detected in readily accessible body fluids, such asblood. Despite studies that are very encouraging, reliable measure-ment of circulating miRNAs bears some inherent challenges and re-quires careful standardization of pre-analytical variables in additionto the ones already described in the previous chapter. The detectionof circulating miRNAs can be influenced by several variables, includ-ing the collection method along with specimen processing, storageconditions, and the composition of the specimen (Table 2).

Specimen collection

In a recent study, Kim et al. examined the influence of different bloodcollection tubes on the detection of miRNAs in plasma [65]. They com-pared Vacutainer tubes (BD Diagnostics) containing EDTA, heparin,sodium citrate, sodium fluoride/potassiumoxalate (NaF/KOx), or no an-ticoagulant and measured miRNAs by qPCR. Their data suggests thatheparin tubes exhibit the lowest levels of both miR-16 and miR223,with occasional improvement upon heparinase treatment. For miR-16,serum and EDTA tubes showed comparable results slightly above hepa-rin tubes while both citrate and NaF/KOx tubes yielded significantly

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Table 2Pre-analytical variables affecting circulating miRNAs.

Variable Effect References

Specimen collection Different additives in blood collection tubesalter miRNA detection. Plasma appears tohave a higher miRNA content than serum.Further studies are needed for thecollection of other body fluids.

[19,23,65]

Storage and stability Circulating miRNAs are stable for anextended time when stored at −20 °C or−80 °C and for a short time at RT or 4 °C.There is conflicting data about the effectof freeze-thaw cycles.

[19,23,66–69]

Blood cell counts Different blood cell counts can significantlychange the miRNA expression profile ofcirculating miRNAs.

[70–72]

Hemolysis miRNAs present in blood cells can falselyelevate levels in hemolyzed specimens.

[19,72,73,77]

Plasma volume An optimal input amount is necessary formiRNA detection as lower or higher inputscan change results secondary to low inputmiRNA or high inhibitor concentrations.

[65]

Plasma components Polymerase inhibitors co-precipitate withmiRNAs and alter miRNA detection.Phenol/chloroform extraction and silicaadsorption potentially remove theseinhibitors.

[65]


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higher amounts. When analyzing miR-223, they demonstrated thatthe use of either EDTA or citrate tubes resulted in slightly elevatedmiRNA levels. However, NaF/KOx again improved the yield significantlyrelative to EDTA or citrate tubes. Interestingly, serum exhibited a widerange of resulting miR-223 levels. In a separate experiment, theyadded sodium fluoride and potassium oxalate to serum or EDTA plasmaand assessed at miR-16 levels. They surprisingly showed that the addi-tion of NaF and KOx to frozen samples from different collection tubesdoubled the detection of miR-16 in plasma collected using EDTA, andtripled the detection in serum. In their study, NaF and KOx appearedto work synergistically, as they did not show significantly increased de-tection by themselves.

Storage and stability of circulating miRNAs

Unlike most solid tissue specimens, samples for circulatingmiRNAs are not fixed by chemical means, such as formalin, but ratherstored at temperatures low enough to significantly decrease RNAseactivity, and therefore prevent RNA degradation. Interestingly, in anearly study from 2007, Bravo et al. reported profound instability ofmiRNAs when stored at −80 °C for as little as three days aftermirVANA or TRIzol extraction whereas messenger RNAs were stablefor over three weeks when stored under the same conditions [66].However, these findings have not been replicated and have no conflictwith other reports. In a separate study from the same year, Potucekand Conrad confirmed that miRNAs from murine tissue lysates usingthe mirVANA miRNA Extraction Kit are stable when stored in frozenstates [67]. Similarly, Mitchell et al. [23] demonstrated that plasmastorage at room temperature for up to 24 h had minimal effect on se-lect miRNAs as measured by qRT-PCR. Mraz et al. also examinedmiRNA stability when stored at −80 °C and did not observe any deg-radation [68]. In fact, they analyzed a panel of 29 miRNAs in storedRNA samples after TRIzol extraction, which remained stable over acourse of 10 months. Similarly, isolated miRNAs showed no evidenceof degradation, and neither did cDNAs after being stored at −20 °Cin RNase free water. McDonald et al. [19] showed that plasma hashigher miRNA levels of miR-15b, miR-16, and miR-24 than serum,which differs from the results byMitchell et al. [23]. However, removalof the subcellular and cellular components from plasma resulted inmiRNA amounts comparable to serum. Additionally, their datashows that serum miRNAs were stable for up to 72 h when refriger-ated at 4 °C or frozen at −20 °C. Similar to Mitchell et al., they con-firmed the stability of miRNAs for 24 h when the serum was kept atroom temperature. In a more recent study, Grasedieck et al. [69] ex-amined the stability of miRNAs after long-term storage at −80 °Cand −20 °C. Their data showed that storage of serum for 2–4 yearsat −20 °C had only minimal effects on the total amount of miRNAswithminor changes in individual miRNAs, though they observed a sig-nificant decrease after 6 years of storage that was even more pro-nounced after 10 years. They also showed that repeated freeze–thawcycles led to a significant decrease in miRNAs when compared to con-tinuous storage at−80 °C. This, however, stands in contrast to the re-port from Mitchell et al. who demonstrated by qRT-PCR that selectmiRNAs, miR-15b, miR-16, and miR-24, showed minimal changes forup to eight freeze–thaw cycles [23]. However, these two papers useddifferent methods of extraction as well as different methods of quan-tification. Further studies on the impact of freeze–thaw cycles wouldbe useful to clarify their effect on total and individual miRNA levels.

Blood cell count

Beyond collection and storage, specimen composition can influencemiRNA detection, including differences in the blood cell count. Witweret al. investigated the effect of CD4 cell counts in peripheral blood ofHIV positive patients on miRNA expression levels and found positivecorrelation between CD4 counts with miR-150, miR29a, miR-31, and




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Table 3 t3:1

t3:2Pre-analytical variables affecting tissue miRNAs.

t3:3Variable Effect References

t3:4Time ex vivo Although the time between excisionand fixation/freezing can alter miRNAlevels, no systematic studies havebeen published.

t3:5Fixative Formalin-fixation does not affectmiRNAs to the same degree as DNAand larger RNA products. Despitepartial loss, FFPE shows miRNA levelscomparable to frozen tissue. Severalformalin-free fixatives do not impactmiRNA detection.

[16,85–89]

t3:6Storage and stability While levels of particular miRNAsmight be altered by long term storageof FFPE blocks, miRNA profiles aregenerally reliable even after severalyears of storage. Pre-cut slides canbe stored for a few days withoutimpacting miRNA detection.

[86,88,90,91]

t3:7Microdissection Microdissection itself does not influencemiRNA levels. However, cresyl violetstaining and additional proteinase Ktreatment improves miRNA detection.

[91]

t3:8Immunohistochemistry IHC does not impact miRNA detectionin one study, though additional studiesare needed.

[96]


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miR-31*; however, miR-181b was negatively correlated [70]. Althoughdifferent miRNA expression levels were not entirely explained by themere CD4 cell counts, it is clear that subsets of cells in the peripheralblood can alter circulating miRNA expression profiles. This is furthercomplicated by the fact that even different lymphocyte subsets showdifferentmiRNAprofiles [71]. Tomore systematically investigate the in-fluence of blood cell-derived miRNAs on circulating miRNA profiles,Pritchard et al. specifically looked at the presence of circulatingmiRNAsthat serve as biomarkers for solid tumors. They found that roughly 60%of the 79 reported solid tumor biomarkerswere also highly expressed inone or more blood cell types [72]. Their study showed that blood cellcounts and hemolysis, which will be discussed in Hemolysis section,can alter levels of miRNA tumor markers by up to 50-fold. This signifi-cantly confounds interpretation of putative miRNA biomarkers andsuggests that in some studies, miRNA expression may not truly bea measure of the tumor, but rather reflect blood cell count and/orhemolysis.

Hemolysis

Expression of circulating miRNAs can also be profoundly influencedby hemolysis in which blood cells release their miRNAs into the plasma.Hemolysis can either occur in vivo or during preparation of the sampleand is a common occurrence in specimen processing. Kirschner et al.demonstrated that miR-16 and miR-451 are increased by hemolysis[73]. This is particularly noteworthy as miR-16 has been used to nor-malize miRNA profiles from one sample to another [74]. As part oftheir study on blood cell counts, Pritchard et al. also examined the effectof hemolysis on 10 miRNAs and found that RBC-associated miRNAswere increased by 20- to 30-fold in hemolyzed plasma [72]. One ofthese 10 miRNAs was miR-92a, a proposed colon cancer biomarker[75,76]. Hemolysis is relevant in cancer patients because they have anincreased predisposition for hemolytic disorders. These can be groupedinto autoimmune, microangiopathic, and chemotherapy-related hemo-lysis. Regardless of their etiology, this increased risk of hemolysis incancer patients further obscures thismatter [77].McDonald et al. spikednon-hemolyzed serumsampleswith hemolysates from the correspond-ing red blood cells [19]. When they correlated hemoglobin concen-trations, they found that miR-15b, miR-16, and miR-24, which areexpressed in red blood cells [78], were increased in a dose-dependentfashion. At the same time, miR-122, a predominantly liver-specificmiRNA, was not affected by hemolysis.

Plasma volume

An interesting finding by Kim et al. was that titration of plasmasample volumes increased accuracy in quantifying miRNA contents[65]. They demonstrated that the input amount of plasma influencesmiRNA results and that this volume can be too low or too high. Thedecreased accuracies that they observed in lower and higher inputvolumes were hypothesized to stem from two different causes. Ifthe input volume was too low, this also meant that endogenous in-hibitors present in the sample were low; however, there was too littlemiRNA to be accurately detected. Conversely, in high volume input,samples contained sufficient miRNAs, but an excess of inhibitors inthe sample also decreased accuracy. These inhibitors are furtherdiscussed in the following paragraph.

Plasma components/polymerase inhibitors

Since other endogenous blood components co-purify with miRNA,Kim et al. investigated whether plasma components can affect circu-lating miRNA quantitation. Therefore, they spiked PBS, plasma, andwhole blood with isolated miRNAs [65]. They found that whilemiR-16was detectable in PBS after 17 h, it was undetectable in plasmaafter 2 h and in whole blood after 17 h. They further showed that in


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RNA preparations that are extracted with TRIzol alone, the extractcontains inhibitors of reverse transcriptase and/or Taq polymerase.These inhibitors can be removed by phenol/chloroform extractionand silica adsorption, while the use of detergents or ribonuclease in-hibitors did not have a stabilizing effect. These inhibitors could includehemoglobin [79], immunoglobulin G (IgG) [80], and lactoferrin [81],although additional studies are needed to clarify exactlywhat proteinsinterfere with miRNA quantification.

Pre-analytical variables for tissue miRNAs

Unlike circulatingmiRNAs, tissue-basedmiRNAs are typically eval-uated after the specimen has been chemically treated to achieve fixa-tion. The most broadly used method is formalin-fixation followed byparaffin embedding. One of the major advantages of tissue miRNAanalysis is bypassing the surrogate circulating miRNAs by directlyevaluating neoplastic or other diseased tissue. Additionally, tissuethat has been fixed can be stored for several years and potentiallyevaluated much later. However, fixed tissue is also prone to variablesthat could influence miRNA profiles, including warm ischemia time,fixation, and storage (Table 3). Straightforward operator mistakessuch as sampling errors where non-diseased tissue is sampled insteadof diseased tissue will not be discussed in this section.

Time ex vivo/warm ischemia time

Numerous studies have shown that extraction of nucleic acidsfrom fresh or snap-frozen tissue is optimal; however, tissues fixedin formalin and embedded in paraffin represent the most widelyavailable source for retrospective studies. While the prospect of ana-lyzing tumor or diseased tissue is promising, one major caveat is theintervening time between specimen excision and the final fixation.The time ex vivo before fixation can be quite substantial, especiallyfor large specimens, complicated surgeries, or specimens that are dif-ficult to fix, i.e. bone, and this a variable that is difficult to gauge. Noformal study appears to have been performed that systematically ex-amines miRNA profiles with respect to varying time after excision be-fore the specimen underwent fixation. However, miRNA profiles maybe altered in ischemic, yet unfixed and not frozen tissue.




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Fixative

Although numerous fixative agents are available, the vast majorityof pathologic specimens are currently fixed in 10% neutral bufferedformalin and then paraffin embedded. This treatment enables longterm storage of tissue blocks. Formalin fixation crosslinks proteinsand nucleic acids, producing superior histology. Purification of nucleicacids from formalin-fixed tissue requires treatment to hydrolyzecrosslinked proteins and render the DNA or RNAmore accessible, ulti-mately yielding lower quality nucleic acids that are frequently shorterthan 600 bp in length [82,83]. The very short length of miRNAs makesthem less sensitive to formalin fixation [84]. As Nelson et al. showed,miRNA can in fact be isolated and analyzed from formalin-fixed paraf-fin embedded tissue (FFPE) [85]. While this was not unexpected, itwas still unclear if miRNA profiles after fixation correlate with freshfrozen tissue profiles. In order to address this, Szafranska et al. evalu-ated the correlation of matched frozen and FFPE samples after 6 or24 hour fixation, and were able to show very similar expression pro-files in 377 investigated miRNAs [86]. However, there was partialloss of 5 to 8.6% of the number of detectedmiRNAs in FFPE samples re-gardless of their fixation time. Similarly, Xi et al. examined the effect offormalin-fixation and paraffin-embedding and compared FFPE sam-ples to fresh frozen samples via high throughput locked nucleicacid-based miRNA assays [87]. They found that there were no signifi-cant differences in the expression of select miRNAs in colorectal carci-nomaswhen comparing FFPE to fresh frozen. In addition, they showedthat different formalin fixation times do not impact the stability ofmiRNAs when examined with real-time qRT-PCR. As expected, thecorrelation of miRNA profiles in FFPE and fresh frozen tissue wasmuch greater than that of messenger RNA profiles. In another study,Bovell et al. also showed thatmiRNA profiles from FFPE samples corre-latedwell with fresh-frozen samples and that formalin fixation did notsignificantly alter the stability of miRNAs [88]. Doleshal et al. exam-ined the correlation between frozen and FFPE samples for miR-24,miR-103, and miR-191 and found significantly lower expression ofall three miRNAs in FFPE samples compared to frozen samples. Ex-pression of these three miRNAs was lower in FFPE samples whenboth RNeasy and RecoverAll kits were used for extraction [16].

While formalin remains the most universally used fixative in thevast majority of clinical laboratories, several novel reagents havebeen developed, largely in an attempt to improve some of the short-comings of formalin fixation. Therefore, Arzt et al. evaluated selectformalin-free tissue fixations, FineFix, RCL-2 and HOPE, with respectto their effect on miRNA quantity, quality, and integrity. They demon-strated that neither of these formalin-free fixations improved themiRNA quantification [89].

Storage and stability of tissue miRNAs

One of the major benefits of FFPE tissue is the ability to store tissueblocks for many years. Thus, a considerable tissue repository has beencreated by pathology laboratories that includes countless patient sam-ples.While this vast archivemay bemined to resolve innumerable sci-entific questions, one of the main variables with respect to miRNAanalysis is how long FFPE tissue can be stored and still producehigh-quality results. Addressing this question, Szafranska et al. quan-tified miRNA in stored mouse and human FFPE specimens using mi-croarray analysis and selected qPCR confirmation [86]. They foundthat one year-old FFPE samples had miRNA profiles with high concor-dance to their corresponding frozen samples. Furthermore, olderspecimens stored for 7 and 11 years retained relatively similar pro-files, though the correlationwas lower. They also noted that the differ-ence in expression profiles was largely attributed to a decreasingnumber of probes that were detected with longer storage. Whileabout 60% of miRNAs were detected in frozen tissue and 53% weredetected after fixation, only 38% remained detectable after 10 years


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of storage as FFPE specimens. Interestingly, miR-494 and miR-513,showed a significant increase in the 11 year old samples by 464- and161-fold, respectively, which highlights the need to verify findingswith fresh samples. Of note, all miRNAs that were initially expressedabundantly were detectable after storage while miRNAs expressed atmid or low levels tended to be more prone to detection loss. As men-tioned previously, miRNAs are less prone to degradation thanmessen-ger RNAs. Accordingly, Jung et al. demonstrated that miRNAs can stillbe accurately quantifiedwhen the sample RNA is of lower quality, as instored FFPE tissue, andmessenger RNAmeasurements are not feasible[90]. In addition, they comparedmiRNA quantification of four miRNAsin renal tissue and five miRNAs in prostate tissue from both FFPE sam-ples and fresh frozen samples. Using RT-qPCR for detection, they dem-onstrated that the coefficients of determination (r2) for miRNAs were0.86–0.89 but only 0.28 for messenger RNAs. Bovell et al. specificallyexamined the stability of six miRNAs, miR-20a, miR-21, miR-106a,miR-181b, miR-203, and miR-324-5p, in archived tissue from colorec-tal cancer [88]. They showed that formalin fixation and storage from 6to 28 years had little detrimental effect on miRNA levels and thatthere was good correlation between formalin-fixed and fresh-frozentissue.

Although FFPE tissue is usually stored in block form, occasionallyblank slides are prepared ahead of further analysis. Patnaik et al. in-vestigated that if the storage of these slides influences the level ofmiR-16 as quantified by TaqMan microRNA qRT-PCR (Life Technolo-gies) [91]. They demonstrated that slides can be stored at room tem-perature for one week before microdissection and storage of themicrodissected tissue at room temperature for up to one day beforeextraction without negatively affecting miRNA yield.

Microdissection

Microdissection is a useful means to evaluate miRNA profiles ofspecific cell types or areas within a larger FFPE specimen [92–94].While microdissection itself does not influence miRNA profiles oryield, Patnaik et al. demonstrated that using staining with cresyl vio-let instead of hematoxylin–eosin resulted in a higher yield of miR-16as measured by TaqMan microRNA qRT-PCR (Life Technologies) [91].In addition, overnight digestion with proteinase K improved themiRNA yield as well.

Immunohistochemistry

Immunohistochemistry (IHC) is an important adjunct techniqueto correctly identify particular cell types, in this context especiallyfor microdissection. Interestingly, miRNAs seem to be differently af-fected by immunostains than messenger RNAs. Gjerdrum et al. exam-ined messenger RNA yields in immunostained slides and observed amassive decrease of up to 89% [95]. In contrast to that study, Schusteret al. found consistent miRNA profiles in immunostained colorectalcarcinoma tissue [96]. Since immunostaining slides can be a usefulaid for determining relevant areas in tissue sections, additional stud-ies investigating the influence of different immunostains on miRNAdetection are needed.

Summary

Pre-analytical variables are often responsible for erroneous labo-ratory test results. For miRNA analysis, these variables can be groupedinto common variables or variables specific to circulating miRNAs andto tissue miRNAs. Due to the relative infancy of miRNA analysis,comparatively few studies systematically investigate the effect ofpre-analytical variables.

Common variables that influence both circulating and tissue-basedmiRNAs include miRNA extraction, labeling, and general miRNA stabil-ity.While these factors can be easily analyzed and standardized, there is




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also a wide array of individual as well as environmental variables thatcan influence miRNA levels. Increased awareness of these individualand environmental factors is necessary in order for miRNA analysis toextend beyond a research setting and enter the clinical laboratory.

Circulating miRNAs, while holding great potential because of theireasy accessibility and minimal invasiveness, are prone to a variety ofpre-analytical factors. These entail the collection and specimen pro-cessing, where different vacutainer tubes can lead to different results,the variable effects of storage and freezing conditions, as well as theconfounding factors of cell count and composition and integrity ofthe specimen.

For tissue-based miRNA analysis, little is known about the degra-dation of miRNAs after the specimen is collected and before it isfixed or frozen. However, generally fixation of tissue leads to resultscomparable to fresh-frozen tissue and FFPE tissue can be reliably an-alyzed even several years after storage. More studies are needed in-vestigating the effect of immunostains on miRNA analysis.

Conclusions

The analysis of miRNAs in blood and other fluids as well as tissuespecimens holds great potential for the development of novel assaysas well as advancing our current diagnostic and prognostic laboratorytests. However, as highlighted in this review, pre-analytical variablesmay significantly influence miRNA quantification and caution iswarranted when interpreting results. The lack of standardizationand implementation of new methods is especially challenging forthe development of clinically meaningful and dependable tests. Pro-spective discoveries of miRNAs as biomarkers are very promising. Inorder to successfully translate these discoveries to the clinical labora-tory, a solid understanding of the pre-analytical variables that affectmiRNA quantification is essential.

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