Circulating U2 Small Nuclear RNA Fragments as a Novel Diagnostic Tool for Patients with Epithelial Ovarian Cancer

Circulating U2 small nuclear RNA fragments as a noveldiagnostic biomarker for pancreatic and colorectaladenocarcinoma

Alexander Baraniskin1,2*, Stefanie N€opel-Dunnebacke1,2*, Maike Ahrens3*, Steffen Grann Jensen4*, Hannah Z€ollner1*,

Abdelouahid Maghnouj1, Alexandra Wos1, Julia Mayerle5, Johanna Munding6, Dennis Kost1, Anke Reinacher-Schick2,

Sven Liffers6, Roland Schroers2, Ansgar M. Chromik7, Helmut E. Meyer3, Waldemar Uhl7, Susanne Klein-Scory2,

Frank U. Weiss5, Christian Stephan3, Irmgard Schwarte-Waldhoff2, Markus M. Lerch5, Andrea Tannapfel6,

Wolff Schmiegel2, Claus Lindbjerg Andersen4 and Stephan A. Hahn1

1 Department of Molecular Gastrointestinal Oncology, Ruhr-University Bochum, Bochum, Germany2 Department of Internal Medicine, Knappschaftskrankenhaus, Ruhr-University Bochum, Bochum, Germany3Medical Proteom-Center, Bioinformatics/Biostatistics, Ruhr-University Bochum, Bochum, Germany4 Depatment of Molecular Medicine, Aarhus University Hospital, Aarhus N, Denmark5 Department of Internal Medicine A, Ernst-Moritz-Arndt University of Greifswald, Greifswald, Germany6 Institute of Pathology, Ruhr-University Bochum, Bochum, Germany7 Department of Visceral and General Surgery, St. Josef Hospital, Ruhr-University Bochum, Bochum, Germany

Improved non-invasive strategies for early cancer detection are urgently needed to reduce morbidity and mortality. Non-coding

RNAs, such as microRNAs and small nucleolar RNAs, have been proposed as biomarkers for non-invasive cancer diagnosis.

Analyzing serum derived from nude mice implanted with primary human pancreatic ductal adenocarcinoma (PDAC), we

identified 15 diagnostic microRNA candidates. Of those miR-1246 was selected based on its high abundance in serum of

tumor carrying mice. Subsequently, we noted a cross reactivity of the established miR-1246 assays with RNA fragments

derived from U2 small nuclear RNA (RNU2-1). Importantly, we found that the assay signal discriminating tumor from controls

was derived from U2 small nuclear RNA (snRNA) fragments (RNU2-1f) and not from miR-1246. In addition, we observed a

remarkable stability of RNU2-1f in serum and provide experimental evidence that hsa-miR-1246 is likely a pseudo microRNA.

In a next step, RNU2-1f was measured by qRT-PCR and normalized to cel-54 in 191 serum/plasma samples from PDAC and

colorectal carcinoma (CRC) patients. In comparison to 129 controls, we were able to classify samples as cancerous with a

sensitivity and specificity of 97.7% [95% CI 5 (87.7, 99.9)] and 90.6% [95% CI 5 (80.7, 96.5)], respectively [area under the

ROC curve 0.972]. Of note, patients with CRC were detected with our assay as early as UICC Stage II with a sensitivity of

81%. In conclusion, this is the first report showing that fragments of U2 snRNA are highly stable in serum and plasma and

may serve as novel diagnostic biomarker for PDAC and CRC for future prospective screening studies.

Key words: pancreatic ductal adenocarcinoma, colorectal, carcinoma, hsa-miR-1246, diagnosis, serum, RNU2-1, U2 snRNA

Abbreviations: AUC: area under the curve; CI: confidence interval; CRC: colorectal carcinoma; Ct: cycle threshold; miRNA: microRNA;

PDAC: pancreatic ductal adenocarcinoma; qRT-PCR: quantitative reverse transcription polymerase chain reaction; ROC: receiver operating

characteristic

Additional Supporting Information may be found in the online version of this article.

*A.B., S.N.-P., M.A., S.G.J. and H.Z. contributed equally to this work.

Grant sponsor: Bundesministerium fur Bildung und Forschung; Grant number: 01GS08118; Grant sponsor: Deutsche Krebshilfe; Grant

number: 70-2988; Grant sponsor: Heinrich und Alma Vogelsang Stiftung, Germany, The Danish National Advanced Technology

Foundation; Grant number: 007-2009-2; Grant sponsor: Ministry of Science, North Rhine-Westphalia, Germany; Grant number: PURE;

Grant sponsor: Alfried-Krupp-von-Bohlen-und-Hahlbach-Foundation (Graduate Schools Tumour Biology and Free Radical Biology),

Deutsche Krebshilfe/ Dr. Mildred-Scheel-Stiftung; Grant number: 109102; Grant sponsor: Deutsche Forschungsgemeinschaft; Grant

numbers: DFG GRK840-E3/E4, MA 4115/1-2/3, NI 1297/1-1; Grant sponsor: Federal Ministry of Education and Research; Grant numbers:

BMBF GANI-MED 03152061A, BMBF 0314107; Grant sponsor: European Union; Grant numbers: EU-FP-7: EPC-TM, EU-FP7-REGPOT-

2010-1

DOI: 10.1002/ijc.27791

History: Received 13 Mar 2012; Accepted 24 Jul 2012; Online 21 Aug 2012

Correspondence to: Stephan A. Hahn, Ruhr-University Bochum, Molecular GI-Oncology (MGO), Universitaetsstrabe 150, 44780 Bochum,

Germany, Tel.:[þ49-(0)-234-32-29282], Fax: [þ49-(0)-234-32-14674], E-mail: [email protected]

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Int. J. Cancer: 132, E48–E57 (2013) VC 2012 UICC

International Journal of Cancer

IJC

Despite significant improvements in surgery and pharmaco-therapy the prognosis of advanced gastrointestinal cancers,such as pancreatic ductal adenocarcinoma (PDAC) and colo-rectal cancer (CRC), remains dismal. In both cancer types,reliable disease detection in early stages represents an impor-tant clinical challenge. Since robust tumor markers for earlycancer detection are not available for both PDAC and CRC,identification of novel biomarkers is a central research goal.Serum levels of CA19-9, currently the most widely used diag-nostic marker for PDAC, are hampered by a low sensitivityand specificity for PDAC.1 In recent years, additional serummarkers such as CEACAM1, MIC-1, TIMP-1, osteopontinand many others have been suggested for PDAC diagnosis,but none of them has managed to enter clinical routine.2–5

Detection of early cancer currently provides the only chancefor cure which is illustrated by the fact that five-year survivalrates reach 24% if the tumor is localized and small (<2 cm).6

Unfortunately, the detection of early stage PDAC provedchallenging and has not been achieved to date.

Unlike pancreatic carcinoma, early CRC can be cured bysurgery and adjuvant chemotherapy in many patients, butthe outcome of advanced CRC disease remains poor. In addi-tion, an efficient tool for the early detection of CRC exists,namely colonoscopy. Colonoscopy, albeit considered an inva-sive diagnostic method, was shown to be able to reduce CRCmortality and most CRC-related deaths via detection ofearly-stage cancer and precancerous lesions.7 Unfortunately,the compliance rates for colonoscopy screening are stillrather low.8 Consequently, also for CRC detection, non-inva-sive diagnostic methods are highly desirable. Several non-invasive screening tests, including fecal occult-blood testing(FOBT) and stool DNA test, have been available for years forCRC.9 However, none of these methods have been estab-lished as well-accepted screening tools, because of their lowsensitivity.10

In the past, several DNA-, RNA- and protein-basedblood tests have been explored for early detection of cancerincluding PDAC and CRC. However, the vast majority ofthese tests have been abandoned for various reasons such asimpaired reproducibility, poor specificity and sensitivity aswell as instability of the target molecules in peripheralblood. Recently, it has been shown that analysis of non-cod-ing RNAs (ncRNAs) circulating in peripheral blood has thepotential to overcome some of the previous limitations.NcRNAs include small nucleolar RNAs (snoRNAs), micro-RNAs (miRNAs), piwi-associated RNAs, small Cajal body-

specific RNAs (scaRNAs) and small nuclear RNAs(snRNAs). To date, primarily miRNAs have been evaluatedfor diagnostic purposes. The main advantage of miRNAsare their proven high stability and abundance in serum orplasma, and the availability of high specific and sensitivedetection assays for the majority of the human miRNAs.Furthermore, Mitchell et al. showed that miRNAs originat-ing from the tumor are indeed present in the circulationand stable for a prolonged time.11 Additional work has pro-vided evidence, that binding to proteins such as Argo-naute2, NPM1 or HDL,12–15 or to some extent their inclu-sion in microvesicles16–18 are likely to be the key to theprotection of miRNAs from degradation and thus high sta-bility in serum and plasma.

A number of studies have addressed miRNA detection inserum, plasma or whole blood of colorectal or pancreaticcancer patients in order to develop miRNA-based bio-markers.19–29 With two exceptions,23,27 the reported miRNAbiomarkers reached only modest levels of sensitivity andspecificity, both for PDAC and CRC, hampering their clinicalutility. Apart from miRNAs, there is currently only one avail-able report, indicating that another ncRNA family member,the so called snoRNAs, can also be detected in patient plasmaand may serve as diagnostic cancer biomarker for non-small-cell lung cancer.30 For other ncRNAs, a diagnostic utility forcancer detection has not been demonstrated.

Here sera from mice carrying human PDAC xenografttumors were successfully used for the identification of cir-culating miRNAs. In subsequent analyses, we found thatthe miRNA showing the best discriminatory value betweencancer and healthy controls was in fact fragmented humanU2 snRNA. snRNAs, including U2 snRNA, have so farnot been shown to have biomarker potential for cancer.U2 snRNA, together with several proteins forms the U2small nuclear ribonucleoprotein (snRNP), which plays akey role in the splicing of pre-mRNA catalyzed by thespliceosome.31 The spliceosome is a large dynamic macro-molecular machinery, which assembles by the highly coor-dinated, sequential association of four small nuclear RNPs(snRNPs), among them U2 snRNP. Together with U6, U2forms part of the RNA network that brings the reactivesites into close proximity of the pre-mRNA and is thus atthe catalytic core of the spliceosome. The splicing-activeU2 snRNP additionally contains the heteromeric splicingfactors SF3a and SF3b. Interestingly, rare missense muta-tions in SF3B1 and SF3A1 have been described in

What’s new?

Non-coding RNAs hold significant promise as biomarkers for noninvasive early cancer detection, but their utility has not yet

been demonstrated. Here, fragments of the non-coding U2 small nuclear RNA (RNU2) were found to be highly preserved and

abundant in serum and plasma from pancreatic ductal adenocarcinoma and colorectal cancer patients. Reliable detection of

the fragments, particularly for UICC stage II colorectal cancers, suggests that RNU2 may be a valuable screening marker for

these cancers.

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Baraniskin et al. E49


pancreatic carcinoma and very recently SF3B1 mutationswere linked to the pathogenesis of myelodysplasticsyndrome.32,33

For the first time, our report shows that U2 snRNA frag-ments can be used for the discrimination of PDAC and CRCpatients from controls with high sensitivity and specificity.

Material and MethodsSample collections

Between 2002 and 2011, consecutive serum and plasma sam-ples (n ¼ 361) were obtained from patients of the Depart-ment of Internal Medicine, Knappschaftskrankenhaus, Ruhr-University Bochum, Germany, from the Colorectal CancerResearch Group, Center for Molecular Clinical CancerResearch Department for Molecular Medicine, Aarhus Uni-versity Hospital, Denmark and from Department of Medi-cine, Ernst-Moritz-Arndt-University, Greifswald, Germany.The local ethical committees had approved sample collec-tions. Written informed consent of all patients and blooddonors was documented according to the local ethics guide-lines. The study was conducted according to the declarationof Helsinki. Additional details on the sample collection suchas diagnoses, clinical staging, age and gender are given in theSupporting Information (Supporting Information Materialand Methods and Tables S2–S7). Blood samples were centri-fuged (10 min, 3,000g, room temperature) within 30 min af-ter collection to remove cells and debris and were stored at�80�C until further processing.

Xenograft tumors derived from early passage humanPDACs (n ¼ 8) were grown in NMRI-nu/nu mice. Serumwas collected via cardiac puncture once tumor size reached 1cm3 and from tumor-free age-matched control mice (n ¼ 8).The tissue collection was performed according to a protocolapproved by the ethics committee of the Ruhr-UniversityBochum (permission no. 3534-09 and 2392-04). All pancre-atic specimen included in this study were reviewed by a pa-thologist (J.M.). Animal experiments were performed accord-ing to the guidelines of the local Animal Use and CareCommittees.

RNA isolation

Total RNA was extracted using a mirVana RNA isolationkit (Ambion, Austin, TX) according to the manufacturer’sinstructions. Briefly, serum or plasma samples were thawedon ice and 170 ll (human samples) or 300 ll (mouse sam-ples) were diluted with an equal volume of mirVana PARIS�2 denaturing solution and subsequently incubated for 5min on ice. Prior to the incubation step, 25 fmol ofsynthetic Caenorhabditis elegans miRNA-54 (cel-miR-54,Qiagen, Hilden, Germany) were added to each humanserum or plasma sample as a spike in control.11 Molar con-centration of spike in synthetic C. elegans miRNA-54 weredetermined in pilot experiments to reach a Ct value of 21 inour PCR set-up. Subsequently, equal volumes of acidic phe-

nol-chloroform (Ambion) were added to each sampleand centrifuged for 5 min at 10,000g. Next, 3 ll of glycogen(20 mg/ml) (Roche, Mannheim Germany) were added toaqueous phases and mixed with 1.25 volumes of 100% etha-nol. Following passage through a mirVana PARIS columnand washing steps were carried out following the manufac-turer’s protocol. Finally, RNA was recovered in 100 ll ofRNase-free water.

Reverse-transcription and quantification by real-time

polymerase reaction

To quantify the concentration of hsa-miR-29a, -1246 (RNU2-1f), -1290 and cel-miR-54 Qiagen miRNA assays (Qiagen,Hilden, Germany) were used following the manufacturer’sprotocols. In brief, 2 ll of total RNA were used for reverse-transcription reactions (37�C for 60 min, followed by 4�C).Real-time PCR was performed using an Opticon 2 systemwith a CFD-3220 Opticon 2 detector (MJ Research, Wal-tham, MA). PCR cycling conditions were composed of aninitial step at 95�C for 15 min followed by 40 cycles of 94�Cfor 15 s, 55�C for 30 s and 70�C for 30 s. Fluorescence wasmeasured at the last step of each cycle. Melting curves wereobtained after each PCR run and showed single PCR prod-ucts. Data from the qRT-PCR were analyzed using OpticonMonitor Analysis software (version 2.01, MJ Research). AllcDNA samples, non-RT (without reverse transcriptase) andno-template controls were assayed in duplicate. Mean cyclethreshold (Ct) values and deviations between the duplicateswere calculated for all samples. Ct value deviations above 0.5between replicates were repeated. We chose to use a syntheticmiRNA, cel-54, not present in human serum as a referencemolecule for normalization, and determined the linear corre-lation between the logarithm of the amount of input syn-thetic miRNA and the cycle threshold value on qRT-PCR forboth RNU2-1f and cel-54 (Supporting Information Fig. 1).From these analyses, we determined the amount of spike insynthetic cel-54 miRNA to be well in the linear amplificationrange of the assay. The amount of RNU2-1f was normalizedrelative to the amount of cel-miR-54 (Ct ¼ Ct(cel-miR-54) –Ct(RNU2-1f)).

miRNA expression analyses and data processing

Total RNAs isolated from 300 ll of mouse serum (n ¼ 6 ofeither group) were hybridized to the human microRNAMicroarray (G4471A Human, Amadid 29297, Sanger 14,Agilent Technologies, Boelingen, Germany). MicroRNAlabeling, hybridization and washing were carried out accord-ing to the manufacturer’s instructions. Images of hybridizedmicroarrays were acquired with a DNA microarray scanner(Agilent G2505B) and features were extracted using the Agi-lent Feature Extraction image analysis software (AFE) ver-sion A.10.7.3.1 with default protocols and settings. The geneexpression data from our study have been deposited in theNCBI Gene Expression Omnibus (GEO) database (accessionnumber GSE34052.

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E50 Circulating U2 snRNA fragments, a novel diagnostic biomarker


Data analyses

The AFE algorithm generates a single intensity measure foreach microRNA, referred to as the total gene signal (TGS),which was used for further data analyses using the GenSpringGX software package version 11.5.1. AFE-TGS were normal-ized by the quantile method. Subsequently, data were filteredon normalized expression values. Only entities where at least1 out of 12 samples had values within the selected cutoff(75th–100th percentile) were further included in the dataanalysis process.

Statistics

The first step in our analysis was a groupwise comparison ofmeasured miRNA serum levels in tumor carrying mice andcontrol mice, respectively. We conducted two-sided two sam-ple t-tests per variable, assuming equal variances using Gen-Spring GX software package version 11.5.1. The p-valueswere adjusted for multiple testing according to Benjaminiand Hochberg [FDR]34 and results were considered statisti-cally significant at adjusted p-values below 0.05. Furthermore,only miRNAs with fold change � 1.5 in the microarray anal-yses were considered worthy of more in-depth analyses.

The resulting top candidate RNU2-1f was evaluatedwith the statistical software R (version 2.13.1 [R], http://

www.R-project.org/) and in particular the packages pROCand PropCIs. The former computes receiver operatingcharacteristic (ROC) curves and the area under the curve(AUC) whereas the latter provides Clopper-Pearson [KI] CIsfor sensitivity, specificity and predictive values. ROC curvesand the AUC were analyzed to assess the feasibility of usingRNU2-1f concentrations as diagnostic tools for detectingcolorectal or pancreatic cancer. Based on the ROC curve, wedetermined the optimal cutoff concentration to classify anobservation cancerous or healthy. We decided to optimizeYouden’s index [cut],35 which is equivalent to the maximiza-tion of the sum of sensitivity and specificity. To prevent over-fitting effects, we divided our data into a training and a testset. The optimal classification cutoff is determined on thetraining set and the quantities of interest are assessed on theindependent test data.

ResultsDiscovery of a candidate miRNA blood biomarker for

pancreatic cancer in xenografted mice and validation

in mouse sera

The overall strategy and study design to identify novelmiRNA-based biomarkers are illustrated in Figure 1. SerummiRNA expression data were collected from six xenograftedand six control mice using Agilent miRNA microarrays(G4471A Human, Sanger 14). Following array processing,normalization and filtering of the raw array data, the pairwisecomparison (fold change � 1.5) identified 21 differentiallyexpressed miRNAs (15 increased and 6 decreased) in serumof PDAC carrying mice compared to tumor free control mice(Supporting Information Table 1). Only miRNAs with anincreased serum concentration in tumor carrying mice wereconsidered potential biomarker candidates. From our list of15 candidates, we chose two miRNAs for validation via qRT-PCR based on their exclusive and robust (normalized gTotal-ProbeSignal >12) expression in tumor bearing mice (miR-1290 and miR-1246) and one miRNA (miR-29a) based on itsrobust expression only. The remaining miRNAs were consid-ered suboptimal candidates, because they generally onlyreached low mean signal levels in tumor sera (mean normal-ized gTotalProbeSignal � 6, Supporting Information Table1). All three miRNAs were validated successfully via qRT-PCR in mouse sera (Supporting Information Fig. 2). Interest-ingly, the lack of expression of miR-1246 in the control mice,already suggested by the very low array hybridization signal(mean normalized gTotalProbeSignal 6.4, Supporting Infor-mation Table 1), was confirmed via qRT-PCR (mean Ct30.2), indicating that the miR-1246 detected in the carcinomacarrying mice is originating from the human carcinoma.

Of note, in the course of our experiments we noted across reactivity of the miR-1246 assay with sequence frag-ments of the human U2 snRNA. The details of these experi-ments are described below and led to the conclusion that themeasured signal was largely not derived from miR-1246 butfrom fragments of RNU2-1 (RNU2-1f).

Figure 1. An overview of the study design is shown. Microarray

analysis was performed on a set of mouse sera for biomarker

discovery. The top candidate RNU2-1f was analyzed in a large

series of serum and plasma samples and following exclusion of

UICC Stage I CRC and adenoma, statistical analyses were

performed to define the RNU2-1f assay characteristics.

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MiR-1246 qRT-PCR is cross reactive with U2 snRNA

sequence fragments

The mature miR-1246 has previously been reported to beexpressed in lung, breast, colorectal and ovarian carcinomasas well as in osteosarcoma cell lines.36 We sought to confirmand extend these data to colon and pancreatic carcinoma celllines. The Qiagen qRT-PCR assay generated PCR fragmentsof roughly the expected size using RNA preparations frompatient serum, serum from xenografted mice as well as fromsupernatants of cell lines. Surprisingly no such PCR productwas generated using cell lysates from a panel of colon andpancreatic carcinoma cell lines (Supporting InformationFig. 3). However, a larger PCR product, 180 bp in size, wasdetected in all cell lysates at high levels. We cloned this PCRproduct and sequence analysis revealed that it perfectlymatched the RNU2-1 sequence in the NCBI database (NCBI

Reference Sequence: NR_002716.3). Importantly, we notedthat the entire mature miR-1246 sequence is comprisedwithin the human U2 snRNA sequence (Fig. 2). Thus, wesought to determine the origin of the PCR products inpatient sera that are generated by the Qiagen miR-1246 assay.We cloned the products and sequenced 129 PCR fragmentsin total, derived from control and cancer patient sera (Fig. 2).Twenty-nine fragments displayed perfect homology with themature miR-1246 or the corresponding sequence withinRNU2-1, whereas two products were 1 or 2 bp shorter. Themajority (98/129) of these cloned PCR fragments, however,displayed extensions by one to seven base pairs at the3-prime end which in all instances were complementary tothe U2 snRNA sequence but not to pre-miR-1246. We alsocloned and sequenced PCR products from the Qiagen miR-16 and -196a assays (data not shown). In all instances wefound either the mature sequence as deposited in miRBase orsequence variants consistent with described isomiRs (http://galas.systemsbiology.net/cgi-bin/isomir/find.pl). Next, wecloned a 346 bp fragment of the primary miR-1246 into alentiviral expression vector and assessed its functionality in ahuman pancreatic carcinoma cell line (Supporting Informa-tion Fig. 4). We noted that, albeit the primary transcriptcould be detected in the vector transduced cells, no func-tional mature miRNA was produced in this experimental set-ting, suggesting that processing of the pri-miR-1246 to themature miR-1246 may not occur in human cells.

In summary, our data show that RNU2-1 fragments(RNU2-1f) are present in patient serum and in supernatantfrom cancer cell lines and are detected by the Qiagen miR-1246 assay. Furthermore, neither RNU2-1 fragments normature miR-1246 are present at a detectable level in wholecell lysates of colon and pancreatic carcinoma cell lines.Lastly, end-point PCR analysis with primer pairs specific forthe precursor form of miR-1246 revealed that pre-miRNA-1246 is also not expressed in these cell lines (Supporting In-formation Fig. 5).

Figure 2. Distribution of identified RNU2-1f fragments in patient sera. Upon cloning of PCR products derived from the Qiagen miR-1246

qRT-PCR assay the indicated sequence fragments were identified at the given frequencies. Common sequence region between human

mature miR-1246 and RNU2-1 is shown in bold letters. Sequence mismatches between RNU2-1 and the precursor miR-1246 are marked

with asterisks.

Figure 3. Box plots depicting the distribution of the Ct(cel-54) �Ct(RNU2-1f) assay data for the various groups included in our

analyses. Assay cutoff of �2.995 is indicted by the broken line.

Legend: PDAC, pancreatic ductal adenocarcinoma; CRC, colorectal

carcinoma; C, colon carcinoma; R, rectal carcinoma; CRC I–IV, UICC

Stages I–IV CRC; HC, healthy controls; DC, diseased controls; CRP,

c-reactive protein.

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Lack of discrimination of loop design qRT-PCR between

miR-1246 and RNU2-1f

Two papers applying loop design qRT-PCR strategies havepreviously reported significant levels of the mature miR-1246in various cell lines.36,37 Likewise, using the TaqMan miR-1246 assay, which is also based on a loop design, we alsoobtained low Ct values in the range of 14–20 in various

cancer cell lines (data not shown). Based on our sequencingdata as shown above, we expected that the majority of RNAtemplates in the miR-1246 loop design cDNA synthesis wereRNU2-1 fragments. To experimentally address this hypothe-sis, we performed cDNA synthesis and miR-1246 TaqManamplification with a number of synthetic oligonucleotidemolecules, namely the mature miR-1246 sequence as well asmolecules extended at the 30 end by 1, 10 and 30 basepairsinto either the miR-1246 precursor or the RNU2-1 sequence.The one bp extension of the template had barely any effect(Supporting Information Fig. 6). Similar data were reportedby Lee et al. for isomiRs.38 As expected, the longer extensionsdid reduce amplification efficiencies, but not to the extentthat abundant molecules such as U2 RNA would becomeundetectable. From these data we conclude that loop designqRT-PCRs are not suitable to reliably discriminate betweenmiR-1246 and RNU2-1f. Furthermore, positive loop designqRT-PCR signals from cell lysates are likely only derivedfrom RNU2-1f and not from miR-1246.

Stability of endogenous RNU2-1f in human serum

The fact that RNU2-1f can be readily detected in patient se-rum and plasma and that its level does not change upon pro-longed storage of the blood at room temperature (SupportingInformation Fig. 7) suggested that RNU2-1f are similar stablein blood as miRNAs. It was previously shown that miRNAsare stable in plasma either because they are components ofribonucleoprotein complexes or embedded within membranevesicles such as exosomes.12–15 To unravel the basis for thisobserved RNU2-1f stability, we performed a protease diges-tion protocol previously applied to distinguish between thesetwo possibilities. We found that RNU2-1f stability resembledthe stability of a ‘‘vesicle type’’ let-7a miRNA upon protease

Figure 5. qRT-PCR data distribution using Ct(cel-54) � Ct(RNU2-1f) assay separated by training and test set for PDAC, CRC and UICC Stage

II CRC. Dotted line indicates threshold of �2.995. Mean values are indicated by horizontal lines.

Figure 4. Receiver operator characteristic curve plots for training

data (gray lines) and test data (black lines). The 95% CIs of

sensitivity and specificity are visualized with a black box. The

diagonal dashed line is random chance. The boundaries of the

confidence intervals clearly exceed random chance for the

independent test set. Legend: TPR, true positive rate; FPR, false

positive rate; AUC, area under the curve.

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treatment, whereas argonaute-bound miR-16 was highly sus-ceptible to protease treatment (Supporting Information Fig.8).13 In addition, we also observed resistance of RNU2-1f to-ward nuclease treatment as previously described for miRNAs(Supporting Information Fig. 8).12

Apoptosis induction raises abundance of RNU2-1f

We hypothesized that the highly stable RNU2-1f could orig-inate from a vesicle-like structure such as apoptotic bodies.Therefore, we induced apoptosis in HCT116 and Panc1 cellsvia curcumin treatment. In line with our previous tests ofRNU2-1f in a series of pancreatic and colorectal carcinomacell line supernatants (Supporting Information Fig. 3B),RNase insensitive RNU2-1f was readily detectable undernormal growth conditions (Cts between 21 and 22).Furthermore, its abundance was markedly increased incurcumin treated cells (Supporting Information Fig. 9). Tofurther corroborate this finding, annexin V positive extracel-lular vesicles likely produced during apoptosis wereenriched from the supernatant derived from HCT116 cellsusing an immune-affinity purification strategy. Again,RNU2-1f was readily detectable in this preparation (Ct 25)and its level was 16-fold increased following curcumin treat-ment (data not shown).

Detection of human pancreatic and colorectal carcinoma

based on RNU2-1f prevalence in serum or plasma

Having validated the tumor specific release of RNU2-1f inour mouse xenograft model, we sought to determine whetherthis new RNU2-1f biomarker candidate could be used in thehuman setting. Apart from PDAC, the tumor type in ouroriginal discovery strategy, we also included CRC, because itis the most frequent gastrointestinal cancer type and it is

quite common for a number of available diagnostic markersthat they are indicative for more than one specific cancertype. A small pilot study with 10 serum samples each, fromCRC and PDAC patients as well as from healthy controlsRNU2-1f proved to differentiate cancer from controls (datanot shown). As a result we set up a comprehensive analysiswith a cohort of 361 serum and plasma samples (80 PDAC,132 CRC, 20 colon adenomas and 129 controls) to morethoroughly assess the variability in RNU2-1f abundanceamong the various disease and control groups (Fig. 3, Sup-porting Information Fig. 10 and Tables 2–7). Because bothserum and plasma samples are included in our study, a com-parison of the RNU2-1f abundance in plasma and serumsamples for both cancers and controls was performed in thesamples where both serum and plasma were available (Sup-porting Information Fig. 12). This comparison revealed nostatistical difference, neither between the controls nor theUICC Stage II carcinoma samples, which was also reflectedby similar mean expression values for cancer and controlsamples in both sets (Supporting Information Fig. 11). Thesedata indicate, in agreement to the strong correlation reportedby Mitchell et al. for miRNAs, that RNU2-1f abundance isalso largely similar in both serum and plasma, and thus bothsources can be used for testing RNU2-1f in patients. Fromthe subsequent statistical analyses we excluded the 20 ade-noma and 21 Stage I CRC cases because the RNU2-1f levelsin their plasma were not different from the prevalence meas-ured in controls (Fig. 3). The remaining cohort of 320 sam-ples were randomly assigned to a training set (N ¼ 213) anda test set (N ¼ 107) maintaining the proportion of healthyand diseased subjects in the overall study population. Bymaximizing the sum of sensitivity and specificity (Youden’sindex), we derived a threshold of �2.995 for the Ct(cel-54) �Ct(RNU2-1f) assay for the training set samples. We appliedthis model and threshold to the independent test set samplesto derive unbiased performance estimates (Supporting Infor-mation Table 8). The threshold dichotomizes diagnostic callsas follows: a score greater or equal than �2.995 classifies asample as cancerous (diagnostic positive), whereas a scoreless than to �2.995 classifies a sample as non-cancerous(diagnostic negative). Our results show sensitivity and speci-ficity to be 97.7% [95% CI ¼ (87.7, 99.9)] and 90.6% [95%CI ¼ (80.7, 96.5)], respectively, with an area under the ROCcurve of 0.972 (Fig. 4). In a next step, we analyzed the per-formance characteristics of our classifier on our test set forCRC and PDAC separately. Figure 5 shows the overall betterperformance of the assay for PDAC and still a very good sep-aration of CRC from controls. This performance is reflectedby the fact that our assay correctly classified 24/25 (96%)PDAC samples and 34/39 (87.2%) CRC (UICC Stages II–IV)samples contained in the test set. Combining the data fromthe training and test set and using the established diagnosticcutoff resulted in the correct classification of 78/80 (97.5%)PDAC samples and 92/111 (82.8%) CRC (UICC StagesII–IV) samples (Fig. 5).

Figure 6. Decline of RNU2-1f abundance following surgical

treatment. RNU2-1f levels were monitored via qRT-PCR in three

PDAC (Patients 1–3) and CRC patients (Patients 4–6.) at the

indicated time points following surgical resection of the tumor. In

all cases RNU2-1f abundance dropped below the diagnostic

threshold of �2.995 (dashed line).

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Influence of ‘‘other’’ diseases and age on RNU2-1f

abundance in serum

Since our control collection did not only contain healthy personsbut also patients who were hospitalized for other diseases as can-cer, we were able to ask whether other diseases, including acuteor chronic inflammation, could lead to a false positive test resultin our analysis. As a surrogate marker for inflammatory activity,we used the c-reactive protein (CRP). As shown in Figure 3, nei-ther the healthy control (HC; Supporting Information Table 7)or diseased control (DC, Supporting Information Tables 5 and6) state nor the CRP level (Supporting Information Tables 5 and6) had a strong influence on the mean normalized Ct value forRNU2-1f. In addition, the abundance of RNU2-1f is not age-dependent as shown in Supporting Information Figure 9 for ourcontrol cohort.

Detection of human Stage II colorectal carcinoma based on

RNU2-1f abundance in serum

An important finding of our analyses is the fact that CRCscan be detected via RNU2-1f as early as the UICC Stage II.The use of our test set and cutoff resulted in a correct classi-fication of 17 of our 21 Stage II CRC samples (Fig. 5). Thisresult is in line with our observation that altogether (trainingand test set) 34 of 42 (81%) UICC Stage II carcinomas wereabove our threshold of �2.995 (Fig. 5) and therefore cor-rectly classified as cancer.

RNU2-1f abundance drops rapidly following surgical

treatment

The serum bank in some instances comprised follow-up sam-ples from cancer patients. For three patients, we were able tocompare RNU2-1f levels upon tumor diagnosis and at days30 or 200 after surgery; all of them showed a strong declineto normal levels. In addition, we were able to prospectivelycollect serum samples within a 5–14 days period followingsurgical resection of the tumor; all three again display adecline of RNU2-1f levels below the diagnostic thresholdwithin this time period (Fig. 6).

DiscussionSince the discovery that ncRNAs, such as miRNAs, are highlystable in the blood, the search for ncRNAs able to discrimi-nate healthy from cancer patients and/or provide prognosticinformation, such as likelihood for disease progression oreven treatment response, are an important focus in ncRNAresearch. Making use of a xenograft cancer model for pancre-atic carcinoma, we identified ncRNA fragments derived fromU2-snRNA (herein called RNU2-1f) to be released fromPDAC into the mouse serum. These initial experiments sug-gested RNU2-1f to be a promising diagnostic marker for ablood-based test. Subsequently, we could separate PDAC andCRC patients from control subjects with high sensitivity andspecificity by means of qRT-PCR quantification of serumRNU2-1f. Furthermore, for CRCs RNU2-1f abundance

paralleled the tumor stage. Our additional finding thatRNU2-1f levels drop rapidly following surgical removal ofthe tumor together with our data from the animal modelshowing that RNU2-1f is only present in the circulation oftumor bearing mice, suggest that the rise in the RNU2-1fabundance in the blood stream of cancer patients is causedeither in part or completely by RNU2-1f release from the tu-mor mass. We also observed a high stability of RNU2-1f inserum toward nuclease and a partial stability toward protein-ase treatment, suggesting that RNU2-1f is not protected byits binding to a protein such as Argonaute2, as shown formany miRNAs, but is more likely protected by its inclusioninto a vesicle-like structure.13 A likely vesicle structure couldbe apoptotic bodies, which contain RNPs (includingU2-snRNA), and are released into peripheral blood via thecompromised capillary network characteristic of tumortissues.39,40 Our finding that whole cell lysates of in vitro cul-tured cancer cells did not contain RNU2-1 fragments at aPCR detectable level, whereas conditioned media from thesame cells contain abundant RNU2-1 fragments, is consistentwith the hypothesis that apoptosis and the production of ve-sicular blebs is required to enrich the cell culture media withRNU2-1 fragments. Furthermore, we were able to markedlyraise RNase resistant RNU2-1f abundance by inducing apo-ptosis in an in vitro system and were able to show thatRNU2-1f is contained in the annexin V positive extracellularvesicle fraction, likely produced during apoptotic processingsteps. These data support a link between apoptosis andRNU2-1f biogenesis. They also add weight to the hypothesis,that apoptotic bodies are one likely carrier of RNU2-1f, butnevertheless don’t exclude other possible vesicular carrier sys-tems for RNU2-1f such as exosomes. In addition, the highprevalence of RNU2-1 fragments which were, according toour sequencing data, only by a few base pairs longer than theso called Sm protein binding region, suggests that this regionof the U2-snRNA molecule is less amenable, i.e. during theapoptotic snRNP degradation process. Sm proteins form aheteroheptameric ring structure surrounding this sequenceregion and thus may protect it from degradation.41 Clearly,more work is required to fully characterize the mechanism ofRNU2-1 processing to RNU2-1f and its release into thebloodstream.

Another important aspect of our study was the discoverythat currently established assays for miR-1246 are cross-reac-tive with RNU2-1 fragments. Furthermore, in contrast to thepublished literature, our qRT-PCR data suggest that miR-1246 is generally not expressed or at best at a very low copynumber in cancer cell lines.36,37 Lastly, expressing a transcriptcontaining a relevant part of the primary miR-1246 sequencefailed to generate functional miR-1246 in a pancreatic carci-noma cell line. This is consistent with reports classifyingmiR-1246 as a pseudo-miRNA precursor.42,43

The high sensitivity and specificity for detecting pancreaticcancer shown here for RNU2-1f puts this marker in the toprank of currently published diagnostic markers for PDAC.

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Only plasma levels of miR-18a and the combination of twomiRNAs (miR-16 and -196a) with CA19-9 were described toreach a similar performance.23,27 Importantly, the latter com-bination was also able to detect 85.2% of Stage I PDACs,whereas CA19-9 detected only 55.6% in the same collec-tion.27 The number of Stage I PDACs was too low in ourstudy population to evaluate the accuracy of the RNU2-1fassay in the setting of early PDAC. However, RNU2-1f abun-dance in the sera of the three Stage I and the three Stage IIPDACs included in our study reached in all instances thediagnostic threshold set for PDAC. Sera from patients withchronic pancreatitis (CP), a known risk factor for PDACwere not included in our sample. Therefore, we are currentlycollecting sera both from patients with Stage I PDAC or CPto address the question whether RNU2-1f alone or in combi-nation with other miRNAs or biomarkers such as CA19-9have the potential to identify early stage PDAC (i.e., tumorsize < 1 cm) and possibly also precursor lesions and to sepa-rate CP from PDAC. Lastly, it will be interesting to testpatients with jaundice in different clinical settings such asCP, choledocholithiasis and PDAC in order to address theinfluence of jaundice on our RNU2-1f assay performance.

Patients with UICC Stage II CRC treated by surgery with-out any adjuvant chemotherapy exhibit a cure rate reaching

87%.44 Under these circumstances, it is remarkable that ourRNU2-1f assay was able to correctly identify the majority ofCRCs as early as UICC Stage II, suggesting it to be a potentialnew non-invasive screening tool for detecting early CRCs witha good prognosis in the setting where the patient doesn’tchoose to undergo screening colonoscopy. Similar rates fordetecting an early CRC stage have to date not been reportedby non-invasive blood-based diagnostic strategies. We alsofound that the number RNU2-1f released by smaller CRCs (<1 cm) or adenomas into the circulation is not sufficiently highto be detected in the blood stream above the background ofcontrol serum. Recently, miRNA analyses have been shown tobe feasible also in stool.45,46 Together with the observed releaseof RNU2-1f from tumor cells with its high stability in serum,it seems plausible to test RNU2-1f abundance in patient stoolto hopefully improve detection rates toward Stage I CRC and/or adenomas. Lastly, our observed decline in RNU2-1f abun-dance following surgical treatment suggests that RNU2-1f mayalso serve as a marker for early therapy response predictionusing chemo and radiation therapy regimen. Altogether, ourstudy provides the rationale for future investigations of RNU2-1f as a diagnostic biomarker in large prospective clinical stud-ies of CRC and PDCA risk groups and to compare its per-formance with currently used non-invasive tests.

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