The Role of Circular RNAs in Pancreatic Ductal Adenocarcinoma and Biliary-Tract Cancers

Abstract

Pancreatic Ductal Adenocarcinoma (PDAC) and biliary-tract cancers (BTC) often present at a late stage, and consequently patients have poor survival-outcomes. Circular RNAs (circRNAs) are non-coding RNA molecules whose role in tumourigenesis has recently been realised. They are stable, conserved and abundant, with tissue-specific expression profiles. Therefore, significant interest has arisen in their use as potential biomarkers for PDAC and BTC. High-throughput methods and more advanced bioinformatic techniques have enabled better profiling and progressed our understanding of how circRNAs may function in the competing endogenous RNA (ceRNA) network to influence the transcriptome in these cancers. Therefore, the aim of this systematic review was to describe the roles of circRNAs in PDAC and BTC, their potential as biomarkers, and their function in the wider ceRNA network in regulating microRNAs and the transcriptome. Medline, Embase, Scopus and PubMed were systematically reviewed to identify all the studies addressing circRNAs in PDAC and BTC. A total of 32 articles were included: 22 considering PDAC, 7 for Cholangiocarcinoma (CCA) and 3 for Gallbladder Cancer (GBC). There were no studies investigating Ampullary Cancer. Dysregulated circRNA expression was associated with features of malignancy in vitro, in vivo, and ex vivo. Overall, there have been very few PDAC and BTC tissues profiled for circRNA signatures. Therefore, whilst the current studies have demonstrated some of their functions in these cancers, further work is required to elucidate their potential role as cancer biomarkers in tissue, biofluids and biopsies.

Full text

cancers
Review
The Role of Circular RNAs in Pancreatic Ductal
Adenocarcinoma and Biliary-Tract Cancers
Christopher Limb 1, Daniel S. K. Liu 2, Morten T. Veno 3, Eleanor Rees 2, Jonathan Krell 2,
Izhar N. Bagwan 4, Elisa Giovannetti 5,6, Hardev Pandha 7, Oliver Strobel 8,
Timothy A. Rockall 1and Adam E. Frampton 1,2,7,9,*
1Minimal Access Therapy Training Unit (MATTU), Royal Surrey County Hospital NHS Foundation Trust,
Guildford, Surrey GU2 7XX, UK; c.limb@surrey.ac.uk (C.L.); t.rockall@nhs.net (T.A.R.)
2Division of Cancer, Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital
campus, Du Cane Road, London W12 0NN, UK; daniel.liu08@imperial.ac.uk (D.S.K.L.);
e.rees@imperial.ac.uk (E.R.); j.krell@imperial.ac.uk (J.K.)
3Omiics ApS, Åbogade 15, 8200 Aarhus N, Denmark; mtv@inano.au.dk
4Department of Histopathology, Royal Surrey County Hospital NHS Foundation Trust, Guildford,
Surrey GU2 7XX, UK; izhar.bagwan@nhs.net
5Department of Medical Oncology, Amsterdam UMC VUmc, 1007 MB Amsterdam, The Netherlands;
elisa.giovannetti@gmail.com
6Fondazione Pisana Per La Scienza, 56017 San Giuliano Terme PI, Italy
7Department of Clinical and Experimental Medicine, Faculty of Health and Medical Sciences, The Leggett
Building, University of Surrey, Guildford, Surrey GU2 7WG, UK; h.pandha@surrey.ac.uk
8Department of General, Visceral, and Transplantation Surgery, University of Heidelberg, Im Neuenheimer
Feld 110, 69120 Heidelberg, Germany; Oliver.Strobel@med.uni-heidelberg.de
9
HPB Surgical Unit, Royal Surrey County Hospital NHS Foundation Trust, Guildford, Surrey GU2 7XX, UK
*Correspondence: a.frampton@imperial.ac.uk or adam.frampton@surrey.ac.uk; Tel.: +44-207-594-2125
Received: 22 September 2020; Accepted: 26 October 2020; Published: 4 November 2020


Simple Summary:
Pancreatic and biliary tract cancers often present with non-specific symptoms,
resulting in diagnosis at a late stage. This may be too late for curative surgery. Earlier detection
and characterisation may guide treatment options and increase survival. Natural “circles” of RNA
(circRNAs) are shown to regulate cancer-related genes, and act as cancer “biomarkers”. Recent
research has shown that circRNAs are both abundant and stable, both of which are desirable
characteristics for clinically useful biomarkers. In this systematic review, we describe the roles of
circRNAs in pancreatic and biliary tract cancers, summarise the current published research and
explore their utility as a biomarker. A total of 32 articles were included: 22 considering Pancreatic
Cancer, 7 for Bile Duct Cancer and 3 for Gallbladder Cancer. CircRNA proved an exciting prospect
as a biomarker for these cancers and future work should continue to develop and expand this field
of research.
Abstract:
Pancreatic Ductal Adenocarcinoma (PDAC) and biliary-tract cancers (BTC) often present at
a late stage, and consequently patients have poor survival-outcomes. Circular RNAs (circRNAs) are
non-coding RNA molecules whose role in tumourigenesis has recently been realised. They are stable,
conserved and abundant, with tissue-specific expression profiles. Therefore, significant interest has
arisen in their use as potential biomarkers for PDAC and BTC. High-throughput methods and more
advanced bioinformatic techniques have enabled better profiling and progressed our understanding
of how circRNAs may function in the competing endogenous RNA (ceRNA) network to influence the
transcriptome in these cancers. Therefore, the aim of this systematic review was to describe the roles
of circRNAs in PDAC and BTC, their potential as biomarkers, and their function in the wider ceRNA
network in regulating microRNAs and the transcriptome. Medline, Embase, Scopus and PubMed
were systematically reviewed to identify all the studies addressing circRNAs in PDAC and BTC.
Cancers 2020,12, 3250; doi:10.3390/cancers12113250 www.mdpi.com/journal/cancers

Cancers 2020,12, 3250 2 of 29
A total of 32 articles were included: 22 considering PDAC, 7 for Cholangiocarcinoma (CCA) and 3 for
Gallbladder Cancer (GBC). There were no studies investigating Ampullary Cancer. Dysregulated
circRNA expression was associated with features of malignancy
in vitro
,
in vivo
, and ex vivo. Overall,
there have been very few PDAC and BTC tissues profiled for circRNA signatures. Therefore, whilst
the current studies have demonstrated some of their functions in these cancers, further work is
required to elucidate their potential role as cancer biomarkers in tissue, biofluids and biopsies.
Keywords:
biomarker; pancreatic cancer; pancreatic ductal adenocarcinoma; biliary tract cancer;
circular RNA; circrna; circRNAs
1. Narrative Review
1.1. Introduction
The incidence of pancreatic ductal adenocarcinoma (PDAC) has been increasing over the past
three decades. Currently, almost 10,000 new cases are diagnosed each year in the UK, which is
almost equal to the number of deaths related to PDAC [
1
]. In contrast to advances seen in many
other cancers, the 5-year overall survival (OS) in PDAC has remained poor, with the most recent
national data reporting ~5% 5-year survival in the UK, and 9% in the United States of America [
1
,
2
].
This is in part due to the late stage at presentation seen in 8 out of 10 patients, allowing an attempt
at curative surgical intervention in only 20%. Similarly, patients with biliary tract cancers (BTC),
such as cholangiocarcinoma (CCA), gallbladder (GBC) and ampullary carcinoma, have generally
poor 5-year OS, at 5%, 17%, 21%, respectively [
1
,
3
]. Presentation of pancreaticobiliary malignancies
is often non-specific, with features including abdominal and back pain, weight loss, fatigue and
bloating. An earlier and more accurate diagnosis has the potential to identify these cancers at a lower
stage, which would improve the opportunity for curative treatment, and increase survival. Therefore,
the research community has been focused on identifying novel molecular biomarkers to improve
diagnostic certainty, predict response to treatment, prognosticate, stratify, and develop targets for
anti-cancer therapies.
The role of circRNAs has been demonstrated in various conditions, for example, diabetes [
4
]
and Alzheimer’s disease [
5
], along with a number of cancers [
6
,
7
]. More recently their role in
pancreaticobiliary cancers has been investigated, including PDAC, GBC and CCA. To date, there
has been no research into circRNAs in ampullary cancer. In these tumours, differential expression
of circRNAs may allow the discovery of several biomarkers. Developing an understanding of the
role of circRNAs in these cancers and their regulation of gene expression, molecular pathways and
protein production may also allow their utilisation as therapeutic targets. Expanding RNA profiling
and array databases, deep sequencing techniques and evolving bioinformatics have allowed “in silico”
mapping of circRNA competing endogenous RNA networks, attempting to hypothesise their
in vivo
mechanisms of action in various diseases.
In this narrative and systematic review, we describe the characteristics, biogenesis and biological
mechanisms of action of circRNAs. We then perform a systematic review aiming to describe original
research into candidate circRNA molecules: all studies quantifying and considering the clinical
implications of circRNAs dysregulation in PDAC and other biliary malignancies will be included.
This will be discussed in the context of the wider literature, with a focus on their demonstrated
molecular mechanisms and potential clinical utilisation.
1.2. Circular RNAs
The vast majority of RNA molecules do not take part in protein translation and are therefore termed
“non-coding” RNAs; this family accounts for 95% of the RNA pool [
8
,
9
]. This is a heterogeneous group

Cancers 2020,12, 3250 3 of 29
including “short” molecules such as microRNAs (miRNAs), and small interfering RNAs; and “long”
molecules termed long non-coding RNAs (lncRNAs), including circular RNAs (circRNAs). Much of
the earlier work considering the role of non-coding RNA molecules focused on miRNA, such as lin-4
identified in the early 1990s [
10
], however, there has been increasing interest in circRNAs. CircRNAs
were first found in viroids [
11
], and subsequently, hepatitis delta virus [
12
], before data demonstrated a
widespread presence endogenous in human cells [
13
,
14
]. Next-generation sequencing approaches had
been used for transcriptome studies (RNA-seq), but in the early days of RNA-seq these relied on mRNA
enrichment by poly-A purification, which excludes circRNAs. Maturation of RNA-seq techniques
to sequence non-poly-A RNA aided the detection of circRNAs. Early study of these molecules was
limited by a lack of awareness as typical RNA amplification did not preserve circularity resulting in
linear molecules, unidentifiable as circRNAs [
15
]. However, since these molecules were first recognised
as single-stranded transcripts with a “scrambled” exon order [
16
], there has been increasing interest in
their regulatory role in a number of human diseases with an increasing focus on cancer [17,18].
1.3. Characteristics
The inherent structure of circRNA results in a deficiency of 5
0
to 3
0
polarity and a lack of a
polyadenylated tail [
19
]. This affords resistance against RNase R among other exoribonucleases and
endoribonucleases [
20
], resulting in a relatively stable molecule. This circular structure has been shown
to result in an extended half-life compared to its linear homologs, which can be over double in some
described cases [21,22].
As circRNAs typically do not code for a protein molecule and initially had no clear function
they were thought to be a by-product of typical post-transcriptional mRNA modification: formed
by “mis-splicing” or indistinguishable from RNA lariats [
23
–
25
]. Despite this initial misconception,
the majority of circRNAs have shown conservation across species, and it is now clear that they
serve a number of genetic and molecular functions, and in some cases are found significantly more
abundant than their linear counterparts [
21
]. Furthermore, they demonstrate tissue and development
stage-dependent expression. For example, Memczak et al. described that a number of nematode
circRNAs are specifically expressed in oocytes, but found to be absent in some cell embryos [
15
].
This provides evidence that circRNAs are not by-products of post-transcriptional mRNA processing,
but that their production is a regulated process with specific molecular functions [
13
,
21
]. Further
evidence of tissue-specific functionality is that dysregulation of specific circRNAs can result in both
oncogenic and tumour suppressive features in a tissue-dependent manner [
26
]. It is now suggested
that their inherent inertia and stability, including in response to stimulation from molecules such as
EGFR [22], make functions related to longer-term processes, such as cell differentiation, more likely.
1.4. Biogenesis and Degradation
CircRNAs are formed during the post-transcriptional process of splicing pre-messenger RNA
(pre-mRNA), where the canonical pathway typically excludes introns to form mature messenger
RNA molecules as covalently linked exons. Back-splicing of pre-mRNA transcripts occurs with
the formation of covalent bonds between a downstream 5
0
splice donor site and an upstream 3
0
acceptor site (Figure 1) [
19
,
27
]. One genetic location can generate both linear and circular RNAs, with
data demonstrating a genetic correlation between linear and circular isoforms in 98% of cases [
22
].
Alternative splicing mechanisms have been shown to give rise to exonic (most common), intronic and
intergenic circRNAs [
28
]. This process appears to be largely intron determined and to predominantly
occur co-transcriptionally at the level of the gene [
29
,
30
]. Exon regions, or 5
0
UTR sequences, are
more prevalent in circRNAs, present in 80% of these molecules [
31
], and may occur as multi-exonic,
single exonic and exon-intronic varieties [6].

Cancers 2020,12, 3250 4 of 29
Cancers 2020, 12, x FOR PEER REVIEW 4 of 29
repeats has been shown to attenuation circRNA generation in vitro [33]. Alu repeats themselves pose
an unpredictable mutagenic risk and enzymes such as DHX9 and adenosine deaminase (ADAR) play
an important regulatory role in circRNAs biogenesis through destabilising intron pairing [34,35].
Alternative mechanisms in the literature for circRNA biogenesis include other intron-pairing motifs
such as quaking (QKI) [36] and muscleblind (MBL/MBNL1) [29] or the involvement of exon containing
lariat precursors [37].
Figure 1. In typical canonical splicing (up), introns are excluded from immature pre-messenger RNA
with covalent bonds forming between exons, the mature messenger RNA is completed with a 5′ cap
and 3′ polyA tail; In circRNA biogenesis (down), a “back-splice” junction is formed between the 5′
splice donor site and an upstream 3′ acceptor site to form a circular molecule. Typical pathways
Figure 1.
In typical canonical splicing (up), introns are excluded from immature pre-messenger RNA
with covalent bonds forming between exons, the mature messenger RNA is completed with a 5
0
cap and
3
0
polyA tail; In circRNA biogenesis (down), a “back-splice” junction is formed between the 5
0
splice
donor site and an upstream 3
0
acceptor site to form a circular molecule. Typical pathways include (
a
)
reverse complementary nucleotide sequences in flanking introns, typically long Alu repeats, (
b
) RNA
binding protein-mediated, and through lariat precursors, which may be a result of (
c
) exon skipping
and (
d
) introns evading degradation; A variety of mature circRNA molecules can form from a single
pre-messenger RNA sequence, including (
i
) multi-exonic, (
ii
) single exonic, (
iii
) exon-intronic, and (
iv
)
intronic isoforms; Proposed endogenous functions are highlighted.
The predominant mechanism for spliceosomal circRNA biogenesis relies on the presence of
a reverse-complementary RNA sequence within introns flanking a potential circRNA [
32
]. Exons
associated with circRNAs are commonly associated with long flanking intronic sequences and repetitive
Alu elements, which are thought to facilitate circularisation by base-pairing and decreasing the distance
between potential back-splicing sites [
21
,
29
]. Furthermore, the deletion of flaking Alu repeats has been

Cancers 2020,12, 3250 5 of 29
shown to attenuation circRNA generation
in vitro
[
33
]. Alu repeats themselves pose an unpredictable
mutagenic risk and enzymes such as DHX9 and adenosine deaminase (ADAR) play an important
regulatory role in circRNAs biogenesis through destabilising intron pairing [
34
,
35
]. Alternative
mechanisms in the literature for circRNA biogenesis include other intron-pairing motifs such as
quaking (QKI) [
36
] and muscleblind (MBL/MBNL1) [
29
] or the involvement of exon containing lariat
precursors [37].
As circRNAs lack 3
0
and 5
0
ends degradation, requires an initiating step of internal cleavage,
for which a number of pathways have been identified. Primary sequence-dependent degradation can
be Ago2/miR-671 mediated, as demonstrated in ciRS-7 (Cdr1as) [
38
], or mediated by an RNase P/MRP
complex, which is able to act on m
6
A motifs after specific RBPs recruitment [
39
]. However, these
mechanisms do not differentiate between linear and circular isoforms, and thus, they are not selective
for circRNAs. Selective dysregulation of highly structured circRNAs has been shown to be mediated
by the RBPs Regulator of nonsense transcripts 1 (UPF1) and Ras GTPase-activating protein-binding
protein 1 (G3BP1), dependent on features of the 3
0
untranslated region structure formed by specific
base pairing [
40
]. Additionally, stimulation with Polyinosinic:polycytidylic acid and viral infection
have both been shown to initiate RNase L mediated degradation, although the mechanisms remain
unclear [
41
]. This controlled, and structure dependant degradation is essential for circRNA cellular
homeostasis, supporting their importance in cellular function. Some evidence suggests a role for the
discrete granular structures related to circRNAs, including P-bodies, Glutamate (GLU) bodies and
stress granules, however, these require further research [42].
1.5. Biological Functions
1.5.1. Competing Endogenous RNA Network
One of the principal mechanisms through which circRNAs have been proposed to regulate
biological mechanisms is labelled “miRNA sponging”. This describes a regulatory axis between
non-coding RNA molecules and mRNA termed the competing endogenous RNA (ceRNA)
network [13,14,43]
. MiRNAs are widely implicated, these small non-coding RNA molecules,
21–25 nucleotides long [
44
], act to regulate gene expression of mRNA. They function through
mechanisms including molecular destabilisation, RNA cleavage and altered configuration, which
reduces translational efficacy [
45
]. Through conserved segments termed miRNA response elements
(MREs), circRNAs are able to interact with miRNA and attenuate their function, leading to a
circRNA-miRNA-mRNA regulatory axis located in the cytoplasm [
46
–
48
]. Hansen et al. described over
70 conserved miR-7 target sites on ciRS-7 (Cdr1as) which allowed it to act as a competing endogenous
RNA molecule and suppress the action of miR-7 [
14
]. This interaction is expected to be facilitated by
other well-known RNA associated proteins involved in the RNA-induced silencing complex (RISC)
such as Argonaute2 (AGO2) and this is the basis for AGO2 RNA immunoprecipitation (RIP) assays to
examine circRNA and miRNA binding. However, the ceRNA hypothesis is not without controversy,
with analysis of annotated circRNAs finding very few circRNA with more miRNA binding sites than
expected by chance [
49
] and the levels of target sites required to demonstrate competing miRNAs
may be exaggerated in some models to the extent that they are not physiologically relevant [
50
].
Furthermore, the function of circRNA is likely to be more complex, as an example the opposite effect
to “sponging” has been found for circRNA ciRS-7 (Cdr1as), which has been reported to stabilise and
transport miR-7, increasing its potency in suppressing related genes [51].
1.5.2. Interaction with RNA-Binding Proteins (RBPs)
As mentioned, circRNAs can function as a direct miRNA sponge assisted by AGO2, one of the
RBPs, but circRNAs can also act in an indirect way on mRNA transcription through RBPs, or compete
with mRNA to combine with RBPs, to influence mRNA translation. Examples include circANRIL
(circular isoform of the Antisense Non-coding RNA In the INK4 Locus), which was shown
in vitro
to

Cancers 2020,12, 3250 6 of 29
control ribosomal RNA maturation by binding to a domain of Pescadillo Ribosomal Biogenesis Factor
1 (PES1), thereby preventing pre-rRNA binding and exonuclease-mediated rRNA maturation [
52
].
Other examples of RBPs shown to be influenced by circRNAs include Mannan-binding lectin [
15
],
Rice Telomere-Binding Protein 1 (RTBP1) [
53
], Caspase-3 [
54
] and HuR [
55
]. It is also thought that
circRNAs can associate with the U1 small nuclear ribonucleic protein (snRNP) in conjunction with
RNA polymerase II in the nucleus, through which it is able to promote host gene transcription [
15
,
56
].
Furthermore, some varieties of circRNA are thought to influence gene expression through direct
interaction with RNA polymerase II alone [
56
]. Intronic circRNAs in particular have little enrichment
for miRNA target sites, lacking recognisable MREs, and so are not expected to have any role in
protein production. The majority of these circRNAs accumulate in the nucleus, at sites of transcription,
demonstrated through fluorescence in situ hybridisation (FISH) assays, and appear to promote genetic
transcription with knockdown resulting in reduced expression of parental genes [23,57].
1.5.3. Protein and Peptide Regulation
In the post-transcriptional setting, circRNAs share exons with linear isoforms. Spliceosomal
mediated generation actively competes with canonical linear splicing. This may limit the production
of linear homologs and has the potential to promote alternate “exon lacking” variants which may
have attenuated or absent biological function [
29
]. For example, circRNAs that contain the translation
initiation site may competitively sequester this from linear homologs and limit potential protein
production, this has been termed the “mRNA trap” [
58
]. This may be of particular importance in cancer,
where an imbalance in canonical and non-canonical splicing may influence the balance of key tumour
suppressor and oncogene related proteins to promote tumourigenesis. This negative correlation
requires further evaluation, and it should be noted that evidence suggests a positive correlation in
most cases, likely as a result of upstream gene modulation [33].
The direct translation of circRNAs into proteins, however, remains controversial [
59
]. It has been
demonstrated that a small number of circRNAs contain an internal ribosomal entry site (IRES), which
allows the potential for translation [
60
,
61
]. There is mounting evidence to support circRNAs translation
with a large number of “cap independent” protein coding sequences identified in the genome [
15
].
Circ-ZNF609 is an example that has been identified in eukaryote cells and proposed to translate into a
protein. It contains a start-to-stop codon reading frame that could go through the process of translation,
interestingly this complete sequence is generated through circularisation and so not present on related
linear RNA molecules [
62
]. Additionally, ribo-circRNA UTR-dependant protein synthesis has been
proposed and rolling circular amplification has been demonstrated
in vitro
[
63
]. M
6
A motifs are widely
prevalent in circRNAs and likely to have a role in regulating protein synthesis, demonstrating the
ability to enable and accelerate this process in vitro [64].
1.5.4. Pseudogene Generation
CircRNAs have been proposed as a source of non-colinear pseudogenes (i.e., a circRNA-derived
pseudogene would have an exon–exon junction in a reversed order) [
63
]. Retro-transcription and
insertion into the host genome have the potential to alter the cellular genomic composition and
subsequent gene expression. Although this potential function of circRNAs has been demonstrated
within the human genome, the biological relevance and role remain unclear.
1.6. CircRNA Research Techniques
1.6.1. CircRNA Sequencing and Profiling
One of the biggest challenges in the study of circRNAs has been identification and differentiation
from other non-coding RNA molecules. Early recognition has been driven through identification
of the “back-spliced” sequences [
16
]. One limitation of this technique, however, is inappropriate
identification of an apparent back-spliced sequence, generated through another cellular mechanism

Cancers 2020,12, 3250 7 of 29
such as reverse transcriptase template switching or tandem DNA duplication [
58
]. Specific approaches
to differentiate these such as targeting enzymatic degradation via the 3
0
polyadenylation tail and
gel electrophoresis, augmented by increased cross-linking may allow more accurate assessment.
In addition, weak hydrolysis and targeted RNase H degradation can allow the linearization of
circRNAs for further evaluation.
CircRNA profiling can be broadly divided into two techniques: tissue microarray or RNA
sequencing. Tissue microarray is a high throughput technique in which specific circRNA junction
sequences are identified to quantify expression. The Arraystar human CircRNA array (Arraystar
TM
)
investigates for 13,617 circRNAs and was utilised by two studies comparing circRNAs expression in
PDAC and para-cancerous tissue. These two projects identified 351 (fold change of >1.5) and 289 (fold
change of 2) dysregulated circRNAs expression profiles respectively as potential targets for future
investigation. The results were submitted to the Gene Expression Omnibus under numbers GSE69362 (6
paired samples) [
65
] and GSE79634 (20 paired samples) [
66
]. Other probe-based platforms, for example,
NanoString, have been utilised by researchers to investigate other malignancies, however, are currently
limited to custom-made plates with a small number of circRNAs targets. As microarray and other
probe-based detection methods identify specific predefined back-spliced sequences, identification
and quantification of specific circRNAs are good, however, circRNAs that are not included in the
target dataset will be ignored. Deeper RNA sequencing is able to describe the wider landscape of
RNA expression and each study has the potential to identify novel circRNAs that are dysregulated in
PDAC [
67
], but is not without limitations in the circRNA field. Problems include technical artefacts
leading to false positives, difficulties with maintaining high algorithmic sensitivity with low read
counts in computational workflows, the use of initial RNase fragmentation, and complex data output
which requires significant computational and bioinformatics analysis [68].
After identification of specific candidate circRNAs, the expression can be quantified via Real-Time
quantitative Polymerase Chain Reaction (RT-qPCR). To achieve this, outward-facing primers are utilised
with a complementary nucleotide sequence to the “back-splice” [
69
]. This is relatively inexpensive,
however false high readings be generated where multiple isomers exist for a single back-splice
event [
70
]. Sanger sequencing can also be utilised in experimental validation, and allows differentiation
between species of circRNA isoforms. Quantification after treatment with RNAse R can be used to
demonstrate resistance to degradation, supporting evidence of circularity in candidate molecules [
20
].
RNA research techniques can be limited by RNA degradation, although meticulous handling in an
RNase-free environment and minimisation of pre-analytical time from sample to bench can limit this to
an extent. This impact may be further attenuated when working with circRNAs, due to their increased
stability, and resistance to enzymatic degradation. Currently, the majority of circRNAs research utilises
fresh frozen tissue samples, although some researchers have considered the role of alternate tissue
sources. Indeed, one study considered the potential of fresh frozen paraffin-embedded (FFPE) tissue
samples [
71
]. This study compared FFPE and fresh tissues, finding a good correlation of circRNA
expression between each type, and that differential circRNAs were able to positively identify tumour
samples in both cases. Of note, in this study, fresh tissue samples demonstrated a higher number of
differentially expressed circRNAs. This is important, as although fresh frozen tissue samples may
currently appear to be the most effective approach, collecting a large number of samples (especially
those with specific features) is not always feasible, and so efforts to characterise circRNAs in archived
FFPE samples may hold potential value.
1.6.2. Bioinformatics
The ability for researchers to identify potential ceRNA networks through complementary binding
sites has advanced significantly with the expansion of publicly available sequence databases and
bioinformatic technology. CircInteractome (https://circinteractome.nia.nih.gov) is one web tool that
has been developed to explore circRNA structure and potential interaction with RNA binding proteins
(RBPs) and miRNA within the ceRNA network [
61
]. This tool takes data from a number of different

Cancers 2020,12, 3250 8 of 29
sources, including RBP binding sites identified by cross-linking immunoprecipitation (CLIP) techniques
and potential miRNA target sequences incorporated in the TargetScan algorithm, to map potential
circRNAs interactions. Interestingly this had demonstrated significantly more complementary binding
sites for both RBPs and miRNA than would be expected through chance, supporting the ceRNA theory.
This is one technique through which RBPs, such as Quaking and DHX9, have been hypothesised to
have a regulatory role in circRNA expression [34,72].
Other tools commonly used in the understanding of the ceRNA network include StarBase (for
RBP interactions) and Arraystar’s homemade miRNA prediction software, miRanda and StarBase (for
miRNA and mRNA interactions) [
73
]. Identification of dysregulated circRNAs has allowed studies
to utilise techniques such as dual-luciferase reporter assays to validate these relationships
in vitro
.
In addition to mapping ceRNA networks, the progression of this technology in web tools such as
CircInteractome has advanced research techniques by facilitating the development of junction primers
for specific circRNA identification and designing specific siRNA molecules able to competitively inhibit
and silence circRNA function.
Publicly available datasets such as Gene Ontology (GO) and the Kyoto Encyclopaedia of Genes
and Genomes (KEGG) allow evaluation of potential interplay between ceRNA networks and known
genetic and molecular pathways [65,74,75]. GO analysis can be used to hypothesis the enrichment of
ceRNA networks for features such as RNA splicing, cell cycle and cell signalling [
75
]. Association
of circRNAs with specific biological functions, in particular those that may be related to features of
malignancy, may help to understand the clinical impact of dysregulation. In addition, GO analysis has
allowed the identification of a wide panel of transcription factors, including the oncogenes p53 and
MYC, that may be implicated in the regulation of circRNAs [
75
]. KEGG analysis allows consideration
of potential influence on molecular and signalling pathways such as WNT and autophagy and their
related protein molecules, which again may help to develop an understanding of their role in cancer [
76
].
The visualisation of these relationships can be integrated and conceptualised through software such as
Cytoscape [77].
2. Results
2.1. Studies Included
The defined search strategy identified 270 articles of which 129 duplicates were excluded.
At title/abstract screening 62 articles were excluded as clearly unrelated to the study question or
excluded article type. On full-text review, a further 47 articles were excluded that did not present
unique data with adequate candidate evaluation. No additional studies were identified through the
reference review. Therefore, 32 articles were included in this systematic review: 22 PDAC, 7 CCA and
3 GBC. This is summarised in Figure 2.
2.2. Circular RNA Expression
Twenty studies validating circRNAs expression in PDAC were included, all of which utilised
real-time quantitative polymerase chain reaction (RT-qPCR) to evaluate (Table 1). A total of 22 circRNAs
were evaluated of which 19 were upregulated and 3 downregulated.
Bioinformatic techniques were utilised by 20 groups to evaluate the relationship of circRNAs
molecules in the ceRNA network, demonstrating a number of complementary miRNA binding sites to
hypothesis regulatory roles over molecules and molecular pathways (Table 2).

Cancers 2020,12, 3250 9 of 29
Cancers 2020, 12, x FOR PEER REVIEW 8 of 29
supporting the ceRNA theory. This is one technique through which RBPs, such as Quaking and
DHX9, have been hypothesised to have a regulatory role in circRNA expression [34,72].
Other tools commonly used in the understanding of the ceRNA network include StarBase (for
RBP interactions) and Arraystar’s homemade miRNA prediction software, miRanda and StarBase
(for miRNA and mRNA interactions) [73]. Identification of dysregulated circRNAs has allowed
studies to utilise techniques such as dual-luciferase reporter assays to validate these relationships in
vitro. In addition to mapping ceRNA networks, the progression of this technology in web tools such
as CircInteractome has advanced research techniques by facilitating the development of junction
primers for specific circRNA identification and designing specific siRNA molecules able to
competitively inhibit and silence circRNA function.
Publicly available datasets such as Gene Ontology (GO) and the Kyoto Encyclopaedia of Genes
and Genomes (KEGG) allow evaluation of potential interplay between ceRNA networks and known
genetic and molecular pathways [65,74,75]. GO analysis can be used to hypothesis the enrichment of
ceRNA networks for features such as RNA splicing, cell cycle and cell signalling [75]. Association of
circRNAs with specific biological functions, in particular those that may be related to features of
malignancy, may help to understand the clinical impact of dysregulation. In addition, GO analysis
has allowed the identification of a wide panel of transcription factors, including the oncogenes p53
and MYC, that may be implicated in the regulation of circRNAs [75]. KEGG analysis allows
consideration of potential influence on molecular and signalling pathways such as WNT and
autophagy and their related protein molecules, which again may help to develop an understanding
of their role in cancer [76]. The visualisation of these relationships can be integrated and
conceptualised through software such as Cytoscape [77].
2. Results
2.1. Studies Included
The defined search strategy identified 270 articles of which 129 duplicates were excluded. At
title/abstract screening 62 articles were excluded as clearly unrelated to the study question or
excluded article type. On full-text review, a further 47 articles were excluded that did not present
unique data with adequate candidate evaluation. No additional studies were identified through the
reference review. Therefore, 32 articles were included in this systematic review: 22 PDAC, 7 CCA and
3 GBC. This is summarised in Figure 2.
Figure 2. Flow-diagram for study selection.
270 articles identified through database search (60 Medline, 97
Embase, 80 Pubmed, 33 Scopus)
129 duplicates removed
141 titles/abstracts screened
79 full-texts reviewed
32 unique studies included:
22 PDAC
7CCA
3 GBC
62 titles/abstracts excluded
47 full-texts excluded
Exclusion reasons:
32 review articles
13 no laboratory/clinical evaluation
of candidate molecule
2 no validation experiment
Figure 2. Flow-diagram for study selection.
Table 1.
Summary of differentially expressed circRNAs evaluated in Pancreatic Ductal Adenocarcinoma
(PDAC). * All studies evaluated PDAC patient samples except hsa_circ_100782 which was evaluated in
PDAC cell lines alone.
Author Year Cancer Type circRNA Expression in PDAC Samples Association with Features of
Malignancy Demonstrated
Chen G. at al. [78] * 2017 PDAC hsa_circ_100782 Upregulated In vitro and in vivo
Yang F. et al. [79] 2017 PDAC hsa_circ_0006988 Upregulated Clinical data
An Y. et. al. [80] 2018 PDAC hsa_circ_0099999
(circZMYM2) Upregulated In vitro and in vivo
Zhu P. et al. [81] 2018 PDAC hsa_circ_0006215 Upregulated In vitro
Li J. et al. [82] 2018 PDAC circ-IARS Upregulated In vitro, in vivo and clinical data
Li Z. et al. [47] 2018 PDAC circ-PDE8A Upregulated In vitro, in vivo and clinical data
Jiang Y. et al. [83] 2018 PDAC hsa_circ_0001649 Downregulated In vitro and clinical data
Qu S. et al. [46] 2019 PDAC hsa_circ_0005397
(circ-RHOT1) Upregulated In vitro
Xu Y. et al. [84] 2019 PDAC hsa_circ_0030235 Upregulated In vitro and clinical data
Hao L. et al. [54] 2019 PDAC hsa_circ_0007534 Upregulated In vitro, in vivo and clinical data
Liu L. et al. [85] 2019 PDAC ciRS-7 (Cdr1as) Upregulated In vitro and clinical data
Yang J. et al. [86] 2019 PDAC hsa_circ_0007334 Upregulated In vitro
Yao J. et al. [87] 2019 PDAC circLDLRAD3 Upregulated In vitro and in vivo
Chen Y. et al. [88] 2019 PDAC circASH2L Upregulated In vitro, in vivo and clinical data
Xing C. et al. [89] 2019 PDAC circADAM9 Upregulated In vitro, in vivo and clinical data
Zhang X et al. [48] 2020 PDAC hsa_circ_001653 Upregulated In vitro, in vivo and clinical data
Liu Y. et al. [90] 2020 PDAC circHIPK3 Upregulated In vitro and in vivo
Wong C. et al. [91] 2020 PDAC circFOXK2 Upregulated In vitro and in vivo
Guo X. et al. [92] 2020 PDAC hsa_circ_0009065
(circBFAR) Upregulated In vitro and in vivo
Kong Y. et al. [93] 2020 PDAC hsa_circ_0086375
(circNFIB1) Downregulated In vitro, in vivo and clinical data
Guo W. et al. [94] 2020 PDAC hsa_circ_0013912 Upregulated In vitro, in vivo and clinical data
Zhang X. et al. [95] 2020 PDAC hsa_circ_001587 Downregulated In vitro, in vivo and clinical data

Cancers 2020,12, 3250 10 of 29
Table 2. Summary of investigated circRNAs in PDAC with proposed ceRNA network.
circRNA Expression in
PDAC Tissue
Expression in
Cell Lines miRNA Implicated Molecules and Pathways
hsa_circ_100782 −Upregulated miR-124 IL6/STAT3
hsa_circ_0099999
(circZMYM2) Upregulated −miR-335-5p JMJD2C
hsa_circ_0006215 Upregulated −miR-378a-3p SERPINA4
circ-IARS Upregulated Upregulated
(and exosomes) miR-122 ZO-1, RhoA, F-actin
circ-PDE8A Upregulated Upregulated miR-338 MACC1/MET
hsa_circ_0005397 (circ-RHOT1) Upregulated Upregulated miR-26b; miR-125a,
miR-330; miR-382 −
hsa_circ_0030235 Upregulated Upregulated miR-1253; miR-1294 −
hsa_circ_0007534 Upregulated Upregulated miR-625; miR-892b −
ciRS-7 (Cdr1as) Upregulated −miR-7 EGF/STAT3
hsa_circ_0007334 Upregulated −miR-144-3p; miR-577 MMP7
circ-LDLRAD3 Upregulated Upregulated miR-137-3p Pleiotrophin
circASH2L Upregulated Upregulated miR-34a Notch 1
circADAM9 Upregulated Upregulated miR-217 PRSS3
hsa_circ_001653 Upregulated Upregulated miR-377 HOXC6
circHIPK3 Upregulated Upregulated miR-330-5p RASSF1
circFOXK2 Upregulated Upregulated miR-942
YBX1 and hnRNPK; NUF2 and PDXK
hsa_circ_0009065
(circBFAR) Upregulated Upregulated miR-34b-5p MET
hsa_circ_0086375 (circNFIB1) Downregulated Downregulated miR-486-5p PIK3R1/VEGF-C
hsa_circ_0013912 Upregulated Upregulated miR-7-5p −
hsa_circ_001587 Downregulated Downregulated miR-223 SLC4A4
2.3. In Vitro and In Vivo Characteristics
CircRNA expression in PDAC cell lines generally correlates with the differential expression
demonstrated in tissue samples. Furthermore, cell studies have allowed quantification of the impact
of differentially expressed circRNAs with cellular features of malignancy (i.e., proliferation and
colony formation, invasion and migration and apoptosis) (Table 3). In those circRNAs found to be
overexpressed in PDAC, ectopic or stimulated overexpression generally enhances features of malignancy
such as proliferation, viability, migration and invasion whilst inhibiting apoptosis; while silencing
and reducing expression attenuates those features of malignancy. In one study, this was supported
through measuring markers of proliferation (i.e., c-Myc and cyclin D1), along with markers of invasion
and metastasis (i.e., vimentin and E-cadherin) [
94
]. Conversely, where under expression has been
associated with malignancy, ectopic expression has been shown to inhibit colony-forming ability and
proliferation, whilst promoting apoptosis. Co-transfection rescue experiments were performed, and
returning circRNA expression to control levels was universally shown to reverse this effect. One study
found that silencing hsa_circ_001653, demonstrated to be upregulated in PDAC, resulted in decreased
angiogenic capacity, vascular length and the number of vascular branches; with overexpression giving
the opposite results [
48
]. Overexpression of hsa_circ_001587, shown to be downregulated in PDAC,
resulted in reduced tube formation suggesting inhibition of angiogenic capacity [
95
]. Silencing had the
opposite effect.
Animal studies have demonstrated that PDAC cells in which implicated circRNAs are
overexpressed are associated with increased tumour size and evidence of metastatic disease,
while silencing results in a reduction of tumour size and growth (Table 4).

Cancers 2020,12, 3250 11 of 29
Table 3. Summary table of cellular functions of circRNAs in PDAC. * All investigated circRNAs were
found to be upregulated in PDAC except hsa_circ_0001649 and hsa_circ_0086375 (circNFIB1), which
were found to be downregulated. “
↑
” indicates an increase; “
↓
” indicates a decrease; “
←→
” indicates
no significant difference demonstrated; and “−“ indicates this measure was not reported.
circRNA Study Type Proliferation/Viability Migration Invasion Apoptosis
hsa_circ_100782
Silencing of upregulated
circRNA
↓ − − −
hsa_circ_0099999 ↓ − ↓ ↑
hsa_circ_0006215 ←→ ↓ − −
circ-IARS − ↓ − −
hsa_circ_0005397 (circ-RHOT1) ↓ ↓ ↓ −
hsa_circ_0030235 ↓ − − ↑
hsa_circ_0007534 ↓ ↓ ↓ ↑
ciRS-7 (Cdr1as) ↓ − ↓ −
hsa_circ_0007334 − − − −
circ-LDLRAD3 ↓ ↓ ↓ −
hsa_circ_001653 ↓ − ↓ ↑
circHIPK3 ↓ ↓ ↓ ↑
circFOXK2 ↓ ↓ ↓ ↑
hsa_circ_0009065
(circBFAR) ↓ ↓ ↓ −
hsa_circ_0013912 ↓ ↓ ↓ ↑
hsa_circ_0099999
Overexpression of
upregulated circRNA
↑ − ↑ ↓
hsa_circ_0006215 ↑ ↑ − ↑
circ-IARS − ↑ − −
circ-PDE8A − ↑ ↑ −
hsa_circ_0030235 ↑ ↑ − ↓
hsa_circ_0007534 ↑ ↑ ↑ ↓
circASH2L ↑ ↑ ↑ −
circADAM9 ↑ ↑ ↑ −
hsa_circ_001653 ↑ − ↑ ↓
circFOXK2 ↑ ↑ ↑ −
hsa_circ_0009065
(circBFAR) ↑ ↑ ↑ −
hsa_circ_0086375 (circNFIB1) Silencing of downregulated
circRNA *
− ↑ − −
hsa_circ_001587 ↑ ↑ ↑ −
hsa_circ_0001649 Overexpression of
downregulated circRNA *
↓ − − ↑
hsa_circ_0086375 (circNFIB1) − ↓ − −
hsa_circ_001587 ↓ ↓ ↓ −
Table 4.
Function of circRNAs in PDAC identified in animal studies. * All circRNAs were upregulated
in PDAC, except for hsa_circ_0086375 (circNFIB1) and hsa_circ_001587, which were downregulated.
circRNA Animal Method Findings
hsa_circ_100782 Nude mice circRNA knockdown Decreased tumour size
hsa_circ_0099999 Nude mice circRNA knockdown Decreased tumour size
circ-IARS Nude mice circRNA overexpression Increased tumour size and metastatic disease
circ-PDE8A Nude mice circRNA overexpression
Increased peripheral blood exosomal GFP signals
hsa_circ_0007534 Nude mice circRNA knockdown Decreased tumour size
circ-LDLRAD3 Nude mice circRNA knockdown Decreased tumour size and weight
circASH2L Nude mice circRNA overexpression Increased tumour size and metastatic disease
circADAM9 Nude mice circRNA knockdown Decreased tumour size and weight
hsa_circ_001653 Nude mice circRNA knockdown Decreased tumour size and weight
circHIPK3 Nude mice circRNA knockdown Decreased tumour size and weight
circFOXK2 Nude mice circRNA knockdown Decreased tumour size and metastasis
hsa_circ_0009065
(circBFAR) Nude mice circRNA overexpression Increased tumour size
hsa_circ_0086375 (circNFIB1) Nude mice circRNA knockdown * Increased lymph node metastasis
hsa_circ_0013912 Nude mice circRNA knockdown Decreased tumour size and weight
hsa_circ_001587 Nude mice circRNA overexpression * Decreased tumour size and weight
circRNA knockdown * Increased tumour size and weight

Cancers 2020,12, 3250 12 of 29
2.4. Clinical Disease Characteristics
Given the potential mechanisms and cellular effects that are described, it is not surprising to
find that the dysregulation of implicated circRNAs in PDAC is associated with poor prognostic
features and ultimately shortened survival time (Table 5). No association has been demonstrated
between circRNAs expression and demographics such as age, sex and tumour location in any study.
No association has been found with carcinoembryonic antigen (CEA); one study found a positive
correlation with Carbohydrate antigen 19-9 (CA 19-9) [
79
]. Dysregulation of investigated circRNAs has
been most closely associated with lymphatic and vascular invasion, metastatic disease, decrease cellular
differentiation, duodenal invasion and stage. It must be noted that it is not clear from the current
data whether abnormal circRNAs expression is a cause or result of advancing disease, although in
some examples multivariate analysis has suggested it is an independent prognostic factor for reduced
overall and disease-free survival [
92
,
96
]. Interestingly, in some studies, circRNA dysregulation is more
strongly correlated than all other clinical features, including stage and lymphatic spread, with reduced
overall and disease-free survival at multivariate analysis [84,93].
2.5. Results for Biliary Tract Malignancies
Less work has been undertaken to explore the role of circRNAs in other biliary malignancies,
although studies investigating both CCA and GBC have been published. A total of 7 studies considering
CCA, and 3 considering GBC were identified (Table 6).
Within CCA, the circRNA hsa_circ_0005230 has been demonstrated to be upregulated in cancer
tissue compared to control, and correlated with increased tumour size, lymphatic spread and disease
stage [
97
]. Its action was proposed to be through sponging miR-1238 and miR-1299, validated through
dual-luciferase reporting assay. Silencing reduced the malignant features, including proliferation,
migration and invasion, while increasing apoptosis in cell studies; ectopic expression to cells had
the opposite effect. In animal studies, hsa_circ_0005230 downregulation reduced metastatic deposits.
This same group demonstrated that hsa_circ_0001649 was conversely downregulated in CCA compared
to control [
98
]. Although the mechanism for this was not clear, downregulation was associated
with increased tumour size and decrease cellular differentiation. In cellular studies circRNAs
silencing resulted in increased proliferation, colony formation and migration with increased apoptosis,
overexpression had the opposite effect. In animal studies overexpression was able to reduce tumour
size. The expression of ciRS-7 (Cdr1as), which is known to interact with miR-7, has been demonstrated
to be unregulated in CCA and is positively associated with lymphatic spread, stage and recurrence
along with reduced survival time [
96
]. Further work demonstrated its association with the features
of malignancy
in vitro
and
in vivo
[
99
]. This study however suggested miR-641 as an additionally
clinically relevant target, reporting 10 complementary binding sites after bioinformatical analysis and
proposing its function through action on the AKT/mTOR pathway. The expression of hsa_circ_0000284
has been found to be upregulated in CCA tissue and exosomes [
100
]. This molecule was found to be
associated with proliferation, migration and invasion in CCA cell lines and knockdown resulted in
reduced tumour size and metastatic disease
in vivo
. It is proposed to function through modulation
of the mir-637/LY6E regulatory axis. Furthermore, this work proposed that exosomes were a critical
method for hsa_circ_0000284 dissemination, found to be secreted from CCA cells and to induce
features of migration and proliferation in local normal cells. A large study recently identified the
upregulation of hsa_circ_102064 in CCA tissue and in extracellular vesicles (EVs) from both serum
and bile [
101
]. The upstream gene for the circRNA in ERBB2, and alternative circRNA from this site
has previously been implicated in the gallbladder and gastric cancer [
33
,
102
] and so this was named
cholangiocarcinoma associated circular RNA 1 (circ-CCAC1) by the authors. Serum dysregulation
was broadly associated with an increased number of tumours, lymph node metastasis and advanced
TNM stage. Furthermore, hsa_circ_102064 was associated with vascular invasion in perihilar CCA;
tumour size in distal CCA; and poorer prognosis and recurrence in intrahepatic CCA, in which
upregulation was also an independent prognostic marker. Silencing resulted in reduced features of

Cancers 2020,12, 3250 13 of 29
proliferation, migration and invasion
in vitro
. Depletion attenuated xenograft size and metastatic
disease
in vivo
. Hsa_circ_102064 demonstrated the ability to enter cells via extracellular vesicles (EVs)
where it resulted in increased vascular permeability and induced angiogenesis. This circRNA was
proposed to act through sponging of miR-514a-5p, a predominantly cytoplasmic miRNA, resulting
in the upregulation of YY1 and activation of its downstream transcription factor CAMLG. It was
also demonstrated to sequester the RBP E2H2, increasing vascular permeability through modulating
SH3GL2/ZO-1/Occludin signalling. Throughout these studies, CCA location within the biliary tract
was not statistically associated with candidate circRNAs expression.
With regards to GBC, the circRNA hsa_circ_0008234, or circFOXP1, demonstrated increased
expression in cancer compared to controls [
53
]. Higher expression was associated with the lymphatic
spread and TNM stage. High expression was an independent risk factor for reduced survival. Increased
expression was associated with increased proliferation, invasion and migration, shortened cell cycle
and reduced apoptosis in cell studies; and increased tumour growth in animal studies. The opposite
findings were demonstrated after silencing. This was suggested to be dependent on its regulatory
“sponge” function of miR-370. This controls the development of the protein PKLR, and this relationship
was validated through the dual-luciferase reporting assay. PKLR appears to have a vital role in the
Warburg effect, aerobic glycolysis which drives cellular proliferation, invasion and migration in cancers
such as this. Hsa_circ_0008234 knockdown resulting in its features of reduced lactate, pyruvate and
extracellular acidosis with increased oxygen consumption. In another study, hsa_circ_0000284 was
demonstrated to be overexpressed in two patient-derived cell lines compared to controls [
26
]. Silencing
resulted in reduced proliferation and colony-forming ability with increased apoptosis; transfection
to increase expression has the opposite effect. This is proposed to act through its interaction with
miR-124, known to act on ROCK1 (rho-associated protein kinase 1) and CDK6. Finally, circERBB2
demonstrated upregulation in GBC tissue and a statistical association between overexpression and
shorter survival was identified [
33
]. Laboratory study demonstrated the suppression of circERBB2 to
attenuate the proliferation of GBC cell lines and reduce tumour size on mouse xenografts. Although a
number of miRNA binding sites were identified in this molecule these were of small frequency and not
clearly associated with tumour related molecular pathways. This team proposes that circERBB2 acts
through regulating RNA polymerase I mediated ribosome 45 s synthesis at the nucleus, a characteristic
rate-limiting step on tumorigenesis. CircERBB2 was found to be enriched in the nucleus and appeared
to regulate nucleolar localisation of PA2G4, a key RNA-binding protein involved in ribosomal assembly.

Cancers 2020,12, 3250 14 of 29
Table 5.
Summary table of clinical characteristics seen with differential circRNA expression in PDAC. “
↑
” indicates an increase; “
↓
” indicates a decrease; “
←→
”
indicates no significant difference demonstrated; and “−“ indicates this measure was not reported.
circRNA Direction of Dysregulation Sample Assessed Tumour Size Duodenal
Invasion
Neural
Invasion
Lymphatic
Spread
Vascular
Spread
Metastatic
Disease
Stage
(TNM)
Differentiation
Grade
Survival
Time
hsa_circ_0006988 Upregulated Tissue ←→ − − ↑ ↑ ←→ ←→ − −
hsa_circ_0006988 Upregulated Plasma ←→ − − ↑ ↑ ←→ − − −
circ-IARS Upregulated Tissue ←→ ←→ ↑ ←→ ↑ ↑ ↑ − ↓
circ-PDE8A Upregulated Tissue ←→ ←→ ←→ ↑ ←→ ←→ ↑ ←→ ↓
circ-PDE8A Upregulated Plasma exosome ←→ ↑ ←→ ←→ ↑ ↑ ↑ ←→ ↓
hsa_circ_0001649 Downregulated Tissue − − − ←→ − − ↑ ↓ ↓
hsa_circ_0030235 Upregulated Tissue − − − ↑ − − ↑ ←→ ↓
hsa_circ_0007534 Upregulated Tissue − − − ↑ − − ↑ ←→ −
ciRS-7 (Cdr1as) Upregulated Tissue ←→ − − ↑ ↑ − − − −
circASH2L Upregulated Tissue ←→ ←→ ←→ ↑ ←→ ←→ ↑ ←→ ↓
circADAM9 Upregulated Tissue − − − ↑ − − ↑ − ↓
hsa_circ_001653 Upregulated Tissue −−−−−−−−↓
hsa_circ_0009065
(circBFAR) Upregulated Tissue ←→ − − ←→ − − ↑ ←→ ↓
hsa_circ_0086375 (circNFIB1) Downregulated Tissue ←→ − − ↑ − − ↑ ←→ ↓
hsa_circ_0013912 Upregulated Tissue ←→ − − ↑ − − ↑ − −
hsa_circ_0086375 (circNFIB1) Downregulated Tissue − − − ↑ − − − ↑ ↓

Cancers 2020,12, 3250 15 of 29
Table 6. Summary of differentially expressed circRNAs investigated in biliary tract cancers.
Author YearCancer
Type circRNA Expression in
Tumour Tissue
Ass Association with Features of
Malignancy Evaluated
Xu Y et al. [98]
2018
CCA hsa_circ_0001649 Down In vitro, in vivo and clinical data
Jiang X et al. [96]
2018
CCA ciRS-7 (Cdr1as) Up Clinical data
Kai D et al. [26]
2018
GBC hsa_circ_0000284
(or circHIPK3) Up In vitro
Xu Y et al. [97]
2019
CCA circ_0005230 Up In vitro, in vivo and clinical data
Wang et al. [53]
2019
GBC hsa_circ_0008234
(or circFOXP1) Up In vitro, in vivo and clinical data
Lu Q and Fang T [103]
2019
CCA circSMARCA5 Down In vitro and clinical data
Huang X et al. [33]
2019
GBC circERBB2 Up In vitro, in vivo and clinical data
Wang S et al. [100]
2019
CCA hsa_circ_0000284 Up In vitro and in vivo
Li D et al. [99]
2020
CCA ciRS-7 (Cdr1as) Up In vitro and in vivo
Xu Y et al. [101]
2020
CCA hsa_circ_102064 (or
circ-CCAC1) Up In vitro, in vivo and clinical data
3. Discussion
3.1. Biological Role of circRNA in PDAC
Molecular pathways and proteins that are associated with the development of the malignant
features in PDAC are demonstrated to be part of dysregulated circRNAs ceRNA networks (Table 2).
Various mechanisms are proposed for their function in driving carcinogenesis, predominantly through
modification of the local tumour microenvironment. These include promoting dysregulation of the
cell cycle, enhancing migratory and invasive capacity, attenuating the immune response, promoting
endothelial-mesenchymal translation (EMT) and enabling resistance to chemotherapy.
3.1.1. Increasing Cell Proliferation
Enhanced proliferation can be achieved through a number of mechanisms, including resistance
to apoptosis. A number of molecular pathways regulate the cell cycle including EGFR/STAT and
PI
3
K/AKT, with evidence that these can be influenced by circRNAs. EGFR is an upstream regulator and
activator of a number of pathways associated with the development of malignancy, including the Signal
Transducers and Activators of Transcription (STATs). Activated STAT may then stimulate specific
oncogenes, leading to the development of malignancy. CircRNAs are shown to have a regulatory
role, for example, ciRS-7 (Cdr1as) is able to promote the EGFR/STAT3 pathway through suppression
of miR-7 in the ceRNA network [
85
]. In the PI
3
K/AKT pathway, PI
3
K is activated through ligand
binding, which phosphorylates AKT, again promoting cellular proliferation. This pathway has been
implicated in the growth and progression of PDAC with emerging evidence that circRNAs play a
role in its regulation [
74
]. HOXC6, previously implicated in both breast and prostate cancer, has an
important role in regulating cellular development, including differentiation, apoptosis, signalling and
subsequent angiogenesis. Hsa_circ_001653 has been proposed to have a regulatory role over this
protein through the ceRNA network, interacting with miR-377 and AGO2, demonstrating the ability to
influence biological activity in vitro [48].
3.1.2. Enhancing Tumour Invasion and Metastasis
The integrity of the cellular micro-environment, including cell–cell interactions and extracellular
matrix, is key to homeostasis. Both interruption of the endothelial barrier and disruption of the
extracellular membrane permit cellular dissemination, synonymous with the features of invasion and
metastasis in malignancy. Circ-IRAS has been implicated in the development of tumour invasion
and metastasis through attenuating the cell tight junction barrier. Attenuation of miR-122 within the

Cancers 2020,12, 3250 16 of 29
ceRNA network results in increased RhoA activity with subsequent increase in F-actin and decrease
ZO-1 tight membrane proteins. This results in increased endothelial monolayer permeability [82].
In addition to acting through the “miRNA sponge” studies have associated circRNA protein
binding with the progression of malignancy, for example between circFOXK2 and both YBX1 and
hnRNPK [
91
]. The formation of this complex promotes the increased activity of the oncogenes NUF2
and PDXK
in vitro
. This increases the invasive and metastatic potential of PDAC cells through
attenuation of cell adhesion and dysregulation of mRNA splicing. Other proposed protein interactions
include the extracellular matrix protein MMP7, which plays an active role in extracellular matrix
degradation [
86
,
98
]. Furthermore, local desmoplasia is a critical feature in PDAC and may be driven
by proteins that can form complexes with circRNAs such as COL1A1 [
86
]. These mechanisms are also
relevant in the context of exosomes, which may contain oncogenic circRNAs.
3.1.3. Promoting Angiogenesis and Lymphangiogenesis
Angiogenesis is critical in both physiological and pathological states [
104
]. It is a route of
nutritional support, which may include oxygenation, along with the removal of waste products, for
example, carbon dioxide. Overexpression of vascular angiogenic factors, such as vascular endothelial
growth factor A (VEGFA), is associated with rapid growth in tumour cells [
105
]. Pan-cancer analysis has
demonstrated the circRNA ciRS-7 (Cdr1as) is correlated with increased cancer-associated endothelial
cells coupled with pathological angiogenesis [
106
]. Within PDAC, overexpression of Circ-ASH2L has
been proposed to stimulate angiogenesis through the upregulation of the Notch 1 pathway, in turn
stimulating downstream VEGFa activity [
88
]. CircADAM9 has also been proposed to modulate
VEGF activity through attenuating the inhibitory effect of miR-217 on serine protease 3 (PRSS3) [
89
].
This oncogene is associated with advanced features in PDAC [
107
] and is thought to affect through
ERK/VEGF stimulation. Additionally, EGFR may also have a role in ERK related pathways; it is able to
phosphorylate MAPK via tyrosine kinase to promote ERK activation [108].
Lymph node dissemination, enhanced by lymphangiogenesis, is one pathway though to
be responsible for rapid spread and metastasis in PDAC [
109
]. Current research suggests that
downregulation of hsa_circ_0086375 (circNFIB1), shown to be downregulated in PDAC, may support
this mechanism.
In vitro
suppression of hsa_circ_0086375 resulted in increased tube formation and
migratory capacity of PDAC cells, with the converse true after overexpression [
93
]. Furthermore,
this study demonstrated that hsa_circ_0086375 expression was negatively associated with lymphatic
vessel density and was lower in metastatic tumour cells in the lymph nodes, when compared to PDAC
tissue, suggesting this circRNA may enable migration of tumour cells.
3.1.4. Attenuating the Immune Response
Both CircUBAP and hsa_circ_0000977 have been hypothesised to promote malignancy in PDAC
through attenuation of the host immune system [
74
,
110
]. CircUBAP is able to bind and inhibit miR-494,
which in turn attenuates its action on CXCR4 and ZEB1. This is proposed to result in preventing T
cell tumour infiltration and limiting antigen presentation, resulting in impaired tumour recognition
and therefore enabling tumour escape mechanisms. Alternatively, hsa_circ_0000977 was proposed to
facilitate immune escape by limiting Natural Killer (NK) cell activity. Hsa_circ_000977 was shown to
be upregulated in the presence of hypoxia, and through miR-153 sponging able to modulate HIF1A
mediated immune escape through upregulation of HIF1A and ADAM10.
3.1.5. Epithelial to Mesenchymal Transition and Cancer Stem Cells
Current research has demonstrated a relationship between circRNAs and the process of epithelial
to mesenchymal transition (EMT). Definable, and typically increased, regulation of many circRNAs has
been demonstrated in cells that have been induced to go through this process [
36
]. EMT is characterised
by a loss of cellular polarity and impaired cell–cell interactions, resulting in the development of
migratory and invasive cellular characteristics, key features of malignancy. The transforming growth

Cancers 2020,12, 3250 17 of 29
factor
β
(TGF-
β
) growth factor family is considered the main inducer of EMT, and one typical signalling
pathway includes the phosphorylation and activation of the SMAD (Small body size and Mothers
Against Decapentaplegic) related proteins [
111
]. EMT is regulated by a number of mechanisms
including transcription factors, for example, the Zinc finger proteins SNAIL and ZEB1 (Zinc finger
E-box-binding homeobox 1), and more recently microRNA molecules, for example, miR-200 and
miR-34 [
111
].
In vitro
results now support a relationship between dysregulated circRNAs and EMT,
such as circHIPK3 and hsa_circ_0013912, along with downregulation of epithelial markers, such as
E-cadherin [90,94].
Identification of cancer stem cells (CSCs) can be achieved by evaluation for surface markers, such as
CD44 and CD133, via immunostaining, or by performing sphere formation assays and
in vivo
tumour
initiation assays. CircRNAs have been shown to maintain CSCs through a variety of mechanisms,
such as WNT and Notch signalling regulation [
112
]. CircFOXP1, for example, is able to promote
tumorigenesis and stem cell phenotype through modulation of EFGR and WNT pathways, via sponging
miR-17-3p and miR-127-5p [
113
]. Both
in vitro
and
in vivo
studies have supported this hypothesis,
finding that the silencing of circFOXP1 impaired cellular differentiation. These features are strongly
associated with resistance to chemotherapeutic agents. In bladder and lung cancer, circRNAs have
been shown to promote self-renewal which is a typical property of CSCs, and some candidates, such as
circASXL1 and circHIPK3, have been proposed as markers of CSCs [63].
3.1.6. Chemotherapy Resistance
Gemcitabine resistance is one of the principal challenges in providing effecting chemotherapy
for advanced PDAC. Although the underlying mechanisms remain unclear, previous work has
demonstrated that overexpression of some members of the ceRNA network is associated with
chemotherapy resistance in PDAC, driving the loss of miR-410-3p [
114
]. More recent data have
implicated the differential expression of specific circRNAs in chemotherapy-resistant PDAC and
CCA cells, including ciRS-7, circHIPK3 and circSMARCA5 [
85
,
90
,
103
]. The expression profile of
circRNAs between PDAC cell lines, with and without gemcitabine resistance, has been shown to differ
significantly [
115
,
116
]. Furthermore, for the two most dysregulated candidates, this dysregulation
was shown to persist when comparing plasma samples from patients, and was able to predict clinical
response to gemcitabine compared to non-responders [
116
]. Cells overexpressing ciRS-7 (CDR1as)
are thought to demonstrate increased gemcitabine resistance as a result of impaired regulation of
EGFR/STAT3 signalling pathway [
85
]. Conversely, the downregulation of circ_SMARCA5 is associated
with increased gemcitabine/cis-platin resistance in CCA [
103
]. The function of its host gene, SMARCA5,
includes protecting the DNA against damage and DNA repair; and so, a reduction in circ_SMARCA5
has been postulated to represent a loss of this function. The upregulation of circHIPK3 is evident in
gemcitabine resistance PDAC cell lines [
90
]. This is proposed to negatively regulate RASSF1 through
sponging miR-330-5p; knockdown results in attenuation of the features of malignancy.
3.2. Clinical Utilisations of circRNAs
These studies clearly demonstrate significant differential expression of certain circRNAs molecules
in pancreatic and biliary tract tumours compared to normal tissues. Furthermore, this differential
expression can persist in both serum and circulating exosomes. Both
in vivo
and
in vitro
, specific
circRNA expression has been associated with features of malignancy. These data, along with increasing
evidence that these molecules are abundant and stable, demonstrate the significant potential for
utilisation of circRNAs as biomarkers in PDAC and BTC as diagnostics and prognostics, with the
potential for developing future predictive and therapeutic applications. Therapeutic applications
would be related to their individual biological roles, including their relationship with the features of
malignancy, and any association with the development of chemotherapeutic resistance.

Cancers 2020,12, 3250 18 of 29
3.2.1. Diagnostic Biomarkers
Consideration of circRNAs as biomarkers has been undertaken in a variety of gastrointestinal
cancers. One meta-analysis included 13 cancer studies: 7 gastric, 5 hepatocellular and 1 colorectal,
demonstrating an area under the Receiver Operating Curve (AUC) of 0.81 for single circRNA
candidates, with a corresponding sensitivity of 0.72, and specificity of 0.77 [
117
]. Its positive likelihood
was 3.09, and negative likelihood 0.37 with a diagnostic odds ratio of 8.38. Hsa_circ_0006988 has been
specifically investigated as a candidate blood-based biomarker in PDAC, demonstrating an AUC of
0.67 [
79
]. However, the results from this study demonstrated a lower sensitivity and specificity of
this circRNA molecule, compared to the standard biomarker, carbohydrate associated Antigen (CA)
19-9. Interestingly, the AUC in combination with CA 19-9 was greater than either biomarker alone.
This highlights the importance of a multimodal approach to diagnostics, suggesting that circRNAs
may be useful for investigating patients lacking the Lewis antigen, with A- B- blood types, in whom
CA 19-9 will not be elevated. Furthermore, in addition to considering circRNA expression alongside
traditional tumour markers, one group has demonstrated that the diagnostic value of circRNAs can be
improved when assessing combinatorial circRNA expression [
118
]. This was shown in gastric cancer,
where it was demonstrated that a pooled AUC of 0.97, with a sensitivity of 0.89 and a specificity of
0.94 could be achieved. The diagnostic performance improved significantly when using a circRNA
“signature” expression, compared to a single circRNA candidate, and the authors concluded that a
pooled expression has better performance and potential for cancer diagnostics. This avenue is yet to be
explored in PDAC.
One limitation when using tissue for diagnostics is the invasive nature of sample collection, and
this is typically obtained at the time of surgery when the diagnosis is already clear. This has led to
the consideration of other potential sites of interest, including saliva, shown to be relevant in other
malignancies [
119
], both cyst fluid and cytology obtained during fine needle aspiration (FNA) and
plasma/serum samples. There has been no research in the context of PDAC investigating circRNAs
expression in saliva samples, nor those obtained at FNA, however, there has been interest in the
potential for plasma or serum samples to be utilised. CircRNAs have been demonstrated to be enriched
in plasma samples for PDAC [
15
], and in other malignancies, they have been demonstrated to have a
reliable ability for diagnosis [
118
], and there has also been promising work investigating the role of
circRNAs in exosomes and other EVs.
Both plasma and serum are easy to isolate from peripheral blood samples, with defined standard
operating procedures [
120
]. Two studies investigating plasma circRNAs expression in PDAC have
demonstrated a demonstrating significant, and correlative, dysregulation of candidate circRNAs in
both tissue and plasma samples [
79
,
116
]. This highlights the potential of plasma or serum measurement
of circRNAs, however, important methodological information was lacking, and neither of these studies
reported the quality or quantity of total RNA extracted from each blood sample for analysis, or their
techniques for validation.
Extracellular vesicles (EVs) are a compartment that is received increasing attention. Exosomes
are 40–150nm sized EVs generated from the plasma membrane of cells as part of the endosome
pathway [
121
]. These structures are formed of a lipid bilayer and found present in the systemic
circulation. They are one means of communication between tumour cells and their microenvironment,
including endothelial and immune cells, and can regulate tumour genesis and malignancy through an
effect on angiogenesis, inflammation and the host immune response. Exosomes have the ability to both
contain and deliver genetic information [
122
]. It has been demonstrated that circRNAs are abundant
in exosomes, with a 2–6 times higher circ-linear RNA ratio, for some examples, than found in cells; and
exosomes containing circRNAs have demonstrated the ability to pass through PDAC cell walls
in vitro
demonstrating this mechanism for circRNAs release [
47
,
123
]. Increased circRNAs abundance could
be a passive result of their increased degradation time, however, it has been suggested that active
enrichment of exosomal circRNAs may also occur. Exosomal circRNAs are not only abundant, but
also independent of the intracellular expression [
124
]. Thus, cellular exosomal release can be both

Cancers 2020,12, 3250 19 of 29
active and passive, and in some cases attenuated by molecular pathways associated with differentially
expressed circRNAs [82].
The profile of exosomal circRNAs expression has been described in one study that sequenced
RNA in 14 serum samples (GSE100232) [
125
]. This study describes abundant circRNAs in circulating
exosomes, along with other RNA molecules, and highlights the potential of circRNAs as novel
biomarkers. It did note that circRNA expression was of varied distribution, and of low expression in
some cases. Furthermore, the small exosomal volume in serum, and therefore the limited quantity
of circRNAs are challenges for circulating circRNA evaluation. These results were incorporated into
a proactively updated web database, called exoRBase, which describes 58,330 circRNAs sequences,
along with lncRNA and miRNA, from this study, as well as sequencing data for other diseases [
126
].
Considering specific examples, tumour exosomes containing an increased volume of circ-PDE8A
and circ-IRAS were identified in the systemic circulation of PDAC patients. These circRNAs are
overexpressed in PDAC tissue, and have been associated with disease progression, reduced survival
and metastatic disease [
47
,
82
]. Exosomal circRNA expression profiles are altered between PDAC
patients and healthy controls and have been validated in PDAC cells [
127
]. As well as the potential
ability to transport circRNAs between cells locoregionally, it has been suggested that circRNAs in
exosomes may act as a vehicle for miRNA, which may then suppress corresponding gene expression at
distant sites [128].
3.2.2. Prognostic and Predictive Biomarkers
Further to acting as a diagnostic biomarkers, plasma/serum circRNAs level may allow
prognostication of disease and prediction of response to treatments. Thus, dysregulated peripheral
blood circRNA expression has been strongly correlated with tumour factors and survival outcomes
in PDAC, and unlike pathological evaluation, can allow a non-invasive, real-time, assessment of the
tumour transcriptome. This “liquid biopsy” has the potential to allow proactive monitoring of the
disease process, permitting improved recognition of treatment success or failure, and act as a step
towards tailor-made treatments [
129
]. Regular measurement of circRNA expression may offer utility as
an adjunct during follow-up after surgical resection, with the potential to improve early recognition of
recurrent disease. CircRNAs, in particular, have potential as clinically useful blood-based biomarkers,
as their resistance to degradation may allow detection in the context of high circulating RNase in
PDAC [130].
With curative surgical intervention possible in only a limited number of PDAC patients [
1
],
primary chemotherapy is now being investigated. Although chemotherapy improves survival time
in PDAC, its use is limited as cancer develops resistance to the agents used [
131
]. Combinations
of chemotherapeutic agents have offered limited value with significant associated morbidity [
132
].
As described a number of circRNAs have been associated with chemotherapy resistance in PDAC and
BTC [
85
,
90
,
103
]. Furthermore, in addition to potentially acting as biomarkers to predict a patient’s
response to chemotherapy,
in vitro
experiments have raised the possible role of circRNAs as therapeutic
targets for anti-cancer treatments. In the above studies, silencing of implicated circRNAs was able
to generate sensitivity to chemotherapy in previously resistant PDAC cell lines, and overexpression
of downregulated circRNAs was able to increase chemotherapy sensitivity in resistant CCA cell
lines [85,103]. However, these findings were not consistent across all the cell lines investigated.
3.2.3. CircRNAs as Therapeutic Targets
Some circRNAs, such as hsa_circ_0001649, have been demonstrated to generate tumour
suppressive effects, and these offer potential as therapeutic targets [
83
]. Stimulated overexpression
reduced proliferation and colony-forming ability, while increasing apoptosis in PDAC, CCA and GBC
cell lines (see Tables 3and 6). Furthermore, circRNAs have been suggested to have a regulatory
role over angiogenesis, lymphangiogenesis and immune function. A number of circRNAs appear
to regulate EMT and progression of CSCs, which are both critical to supporting the maintenance

Cancers 2020,12, 3250 20 of 29
of “stemness” [
112
]. Furthermore, “stemness” appears to be related to gemcitabine resistance [
133
].
CircRNA dysregulation is seen in gemcitabine resistance, and silencing of implicated circRNAs was
able to restore gemcitabine sensitivity in a resistance cell line [
116
]. With an appropriate technique for
induction, manipulating circRNAs
in vivo
may be able to influence response to chemotherapeutics for
these tumours.
Exosomes and other EVs have been suggested as a possible delivery vehicle for anti-cancer therapy.
In animal models, exosomes have been used to increase the therapeutic index of doxorubicin [
134
],
and their previously described ability to transport non-coding RNA molecules [
121
] may be a novel
therapeutic strategy for delivering cancer-suppressing circRNAs. In addition, several
in vitro
studies
have shown that siRNA molecules have the potential to be delivered using exosomes in order to silence
tumour promoting circRNAs. One group injected PDAC cell lines into nude mice after siRNA silencing
of an upregulated circRNA: this resulted in attenuated tumour development, with a consequent
reduction in tumour size. Conversely forced overexpression of hsa_circ_0001649, which has reduced
expression in CCA, resulted in a similar tumour size reduction effect in animal studies [
98
]. These data
demonstrate that circRNAs have the potential as therapeutic targets, and the development of tools
such as CircInteractome [
61
] has improved the ability to develop siRNAs able to selectively silence
circRNAs of interest.
3.3. Future Research
At present, the circRNA component of the transcriptome has only been assessed in a limited
number of PDAC tissue samples. PDAC is a heterogeneous disease characterised by multiple genetic
abnormalities, often present in many core signalling pathways [
135
], and so the differential expression
seen in these limited samples may not be representative of the non-coding transcriptome. Although
validation and investigation have been undertaken in 26 described candidates (see Tables 1and 6),
this number is only a small proportion of the known circRNAs, and so investigation of other candidates
may reveal additional clinical utility. With regards to CCA, a recent study undertaking high-throughput
whole transcriptome sequencing in tissues hypothesised a further ceRNA network comprising of
miR-144-3p, and 7 upregulated, and 10 downregulated circRNAs [
136
]. This miRNA has already been
implicated in PDAC [
86
], and in this study, functional enrichment analyses suggest a downstream
effect on the spliceosome, as well as on RNA processing and transport. This is one avenue that is
opened for further work. Furthermore, the majority of circRNA work in PDAC has been undertaken
by research groups based in China, with all tissue samples taken from Asian patients. It is not known
to what degree circRNAs expression profiles differ between ethnic groups, and so these findings may
not be generalisable to the Western world. “In Silico” and bioinformatical techniques have enabled
contextualisation of circRNAs into predicted networks, however, it is important to be aware that
hypothetical relationships require sound experimental interrogation.
Researchers have also considered the differential circRNA expression in other clinically useful
samples other than tissue (i.e., blood and biofluids), however these avenues require further exploration.
Blood sampling in particular may offer a simple, and non-invasive approach to investigating
PDAC, potentially allowing real-time assessment of response to cancer treatment. However, only
a limited number of circRNAs have been investigated in PDAC as blood-based biomarkers to
date [47,79,82,116,127]
. Other potentially useful biofluids for the discovery of circRNA biomarkers
include bile, pancreatic cyst fluid and saliva. Differential circRNAs expression has been demonstrated
in saliva for other malignancies [
119
]. In the context of pancreaticobiliary disease, bile and pancreatic
cyst fluid can be obtained during standard clinical investigation at the time of endoscopic retrograde
cholangio-pancreatography (ERCP) and endoscopic ultrasound (EUS), respectively. All current
research has considered circRNAs expression as a diagnostic biomarker, however, these molecules
may have further utility in prognosticating outcomes, predicting response to cancer treatments, and
monitoring for disease progression or recurrence (e.g., after chemotherapy or surgical resection).
Furthermore, it is important to recognise that PDAC is a heterogeneous disease process, and can

Cancers 2020,12, 3250 21 of 29
develop from pre-malignant conditions (e.g., Intraductal Papillary Mucinous Neoplasms (IPMN) and
chronic pancreatitis). Future work may consider the ability for circRNAs to differentiate between
subtypes of PDAC, and predict the chance of malignant transformation of pre-malignant conditions.
The circRNA field is currently suffering from a lack of naming convention. In the early days of
whole-transcriptome-based circRNA studies (from 2013 to 2015), circBase was the primary database
supporting circRNA research [
137
], and as such circBase IDs were the preferred method for the
identification of specific circRNAs. However, circBase has only seen minor updates after this initial
period and is now no longer a comprehensive source of circRNA annotation. Other circRNA databases
have subsequently arisen, such as CIRCpedia [
138
], and CircAtlas [
139
], which are now more up
to date. However, each database implements its own circRNA ID. Even more worrying is the
division of the circRNA field between sequencing-based studies, and Arraystar microarray-based
studies (https://www.arraystar.com/), the latter implementing its own circRNA naming conventions.
Arraystar does not offer the complete annotations for their circRNA probe set that would be needed to
systematically compare sequencing data and microarray data, which effectively promotes a division of
the circRNA field into microarray studies and sequencing studies.
Finally, the utility of circRNAs for liquid biopsy requires consideration in the context of other
relevant biomarkers, including circulating tumour cells (CTCs), cell-free DNA, and other RNA
molecules [
140
–
142
]. In addition, future studies should specifically consider the presence and utility of
circRNAs in different compartments, including whole blood, plasma, serum, platelets, exosomes/EVs,
and secretosomes.
4. Systematic Review Methodology
This systematic review was performed in keeping with the PRISMA guidelines. This review is
based on previous study results and so no ethical approval or consent was required. This review was
registered on the National Institute for Health Research (NIHR) PROSPERO database, identification
number CRD42019156889.
4.1. Search
Medline, Embase, Scopus and PubMed were interrogated without limit on the time period with the
following search strategy on the 16 April 2020. Both Title/Abstract and Medical Subject Heading (MeSH)
were utilised (where available) for article identification, search strategy outlined below. Non-English
and duplicated articles were excluded at this stage. Authors CL and AF performed title and abstract
screening and for all identified articles, followed by full-text review. In addition, a manual search of
identified reviews and referencing was performed to identify any additional relevant studies.
(Circular RNA OR circRNA) AND (Biliary tract cancer OR pancreatic ductal adenocarcinoma OR
cholangiocarcinoma OR ampullary carcinoma OR Gallbladder carcinoma). For each term, common
synonyms and MeSH headings were incorporated.
4.2. Eligibility Criteria
Articles types excluded at screening were those retracted, reviews, editorials, book chapters and
conference abstracts. Additionally, those clearly not in the context biliary cancer or unrelated to the
subject of interest were excluded.
On full text review inclusion required quantification of circRNA expression in the context of
biliary tract cancer and evaluation against the feature of malignancy
in vitro
,
in vivo
or in the context
of clinical outcomes.
4.3. Data Collection
Authors CL and AF performed data collection independently against a predefined database. After
initial data collection, both authors undertook further data collection. For each article, the circRNA of
interest was recorded along with related miRNA, mRNA, technique through which expression and

Cancers 2020,12, 3250 22 of 29
relationships were validated;
in vitro
study outcomes;
in vivo
study outcomes; along with associated
clinical tumour and patient evaluation.
4.4. Results Reporting
Meta-analysis was not performed. Data are presented in the subgroups of Pancreatic Ductal
Adenocarcinoma and then other biliary tract malignancies.
5. Conclusions
Of all the non-coding RNA molecules, the abundance, stability and tissue specific expression
patterns of circRNAs lend them to use in diagnostics, prognostics and molecular-targeted therapies
for various diseases including PDAC. These features have only recently been realised, and so it is
unsurprising that circRNAs have received increased attention over the past few years. The differential
expression profile of circRNAs in malignancies such as PDAC has now been demonstrated, with
validation of several molecules of interest. The majority of investigated circRNAs in PDAC are
upregulated and are associated with malignant cellular processes such as proliferation, invasion and
metastasis. The proposed oncogenic mechanism is predominantly through competitive inhibition
of miRNAs, frequently termed “miRNA sponge”, through the ceRNA network. Other proposed
mechanisms include interaction with RBPs, protein and peptide regulation, and pseudogene generation.
It is ultimately likely to be through a range of actions dependant on the specific circRNA molecules
in question, with further work required to expand this understanding. Bioinformatic analysis has
enhanced our ability to understand the interaction of circRNAs within genetic and molecular pathways,
but has also served to illustrate the complexity of these networks.
Like any investigation, the consideration and implementation of circRNAs as biomarkers for PDAC
must proceed with caution. Despite the demonstrated significance in diagnostics and prognostics,
there is still large room for error. The role of circRNAs must be considered in the wider context of
each disease stage, and the treatments given. Ultimately, the future of PDAC diagnosis, prognosis and
treatment is likely to be planning individualised care to each patient, and although research is starting
to granulate the role of circRNAs and the ceRNA network in PDAC, it is clear that there is still a long
way to go. Future research should continue to map out the differential circRNA expression profiles
in PDAC, and establish how deregulated circRNAs are associated with tumour and clinical features.
This should be expanded to include clinically useful samples such as blood, biopsies and biofluids.
Evaluation of specific circRNAs that may have a role in diagnosis and prognostication should continue
to be evaluated alone, and as a panel, as well as in combination with other diagnostic tests, including
established tumour markers.
Author Contributions:
Conceptualization, A.E.F., C.L.; methodology, A.E.F., C.L.; data collection, C.L., A.E.F.;
formal analysis, C.L., A.E.F., D.S.K.L., J.K., E.R.; writing—original draft preparation, C.L.; writing—review and
editing, C.L., A.E.F., D.S.K.L., J.K., E.R., M.T.V., I.N.B., O.S., H.P., T.A.R., E.G.; supervision, A.E.F., H.P., T.A.R. All
authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Acknowledgments:
We would like to acknowledge the contribution towards design and implementation of
search strategy by Stephen Phillips, Clinical Librarian at the Royal Surrey County Hospital.
Conflicts of Interest: The authors declare no conflict of interest.
References
1.
UK CR. Pancreatic and Biliary Tract Cancer Statistics. 2020. Available online: https://www.cancerresearchuk.
org/(accessed on 10 October 2020).
2.
Siegel, R.L.; Miller, K.D.; Jemal, A. Cancer statistics, 2020. CA Cancer J. Clin.
2020
,70, 7–30. [CrossRef]
[PubMed]

Cancers 2020,12, 3250 23 of 29
3.
Coupland, V.H.; Kocher, H.M.; Berry, D.P.; Allum, W.; Linklater, K.M.; Konfortion, J.; Moller, H.; Davies, E.A.
Incidence and survival for hepatic, pancreatic and biliary cancers in England between 1998 and 2007.
Cancer Epidemiol. 2012,36, 207–214. [CrossRef] [PubMed]
4.
Xu, H.; Guo, S.; Li, W.; Yu, P. The circular RNA Cdr1as, via miR-7 and its targets, regulates insulin transcription
and secretion in islet cells. Sci. Rep. 2015,5, 12453. [CrossRef] [PubMed]
5.
Lukiw, W.J. Circular RNA (circRNA) in Alzheimer’s disease (AD). Front. Genet.
2013
,4, 307. [CrossRef]
[PubMed]
6.
Lee, E.C.S.; Elhassan, S.A.M.; Lim, G.P.L.; Kok, W.H.; Tan, S.W.; Leong, E.N.; Tan, S.H.; Chan, E.W.L.;
Bhattamisra, S.K.; Rajendran, R.; et al. The roles of circular RNAs in human development and diseases.
Biomed. Pharmacother. 2019,111, 198–208. [CrossRef] [PubMed]
7.
Tang, Q.; Hann, S.S. Biological roles and mechanisms of circular RNA in human cancers. Oncol. Targets Ther.
2020,13, 2067–2092. [CrossRef]
8.
Derrien, T.; Johnson, R.; Bussotti, G.; Tanzer, A.; Djebali, S.; Tilgner, H.; Guernec, G.; Martin, D.; Merkel, A.;
Knowles, D.G.; et al. The GENCODE v7 catalog of human long noncoding RNAs: Analysis of their gene
structure, evolution, and expression. Genome. Res. 2012,22, 1775–1789. [CrossRef] [PubMed]
9.
Djebali, S.; Davis, C.A.; Merkel, A.; Dobin, A.; Lassmann, T.; Mortazavi, A.; Tanzer, A.; Lagarde, J.; Lin, W.;
Schlesinger, F.; et al. Landscape of transcription in human cells. Nature 2012,489, 101–108. [CrossRef]
10.
Lee, R.C.; Feinbaum, R.L.; Ambros, V.; The, C. elegans heterochronic gene lin-4 encodes small RNAs with
antisense complementarity to lin-14. Cell 1993,75, 843–854. [CrossRef]
11.
Sanger, H.L.; Klotz, G.; Riesner, D.; Gross, H.J.; Kleinschmidt, A.K. Viroids are single-stranded covalently
closed circular RNA molecules existing as highly base-paired rod-like structures. Proc. Natl. Acad. Sci. USA
1976,73, 3852–3856. [CrossRef]
12.
Kos, A.; Dijkema, R.; Arnberg, A.C.; van der Meide, P.H.; Schellekens, H. The hepatitis delta (delta) virus
possesses a circular RNA. Nature 1986,323, 558–560. [CrossRef]
13.
Memczak, S.; Jens, M.; Elefsinioti, A.; Torti, F.; Krueger, J.; Rybak, A.; Maier, L.; Mackowiak, S.D.;
Gregersen, L.H.; Munschauer, M.; et al. Circular RNAs are a large class of animal RNAs with regulatory
potency. Nature 2013,495, 333–338. [CrossRef]
14.
Hansen, T.B.; Jensen, T.I.; Clausen, B.H.; Bramsen, J.B.; Finsen, B.; Damgaard, C.K.; Kjems, J. Natural RNA
circles function as efficient microRNA sponges. Nature 2013,495, 384–388. [CrossRef]
15.
Memczak, S.; Papavasileiou, P.; Peters, O.; Rajewsky, N. Identification and characterization of circular RNAs
as a new class of putative biomarkers in human blood. PLoS ONE
2015
,10, e0141214. [CrossRef] [PubMed]
16.
Nigro, J.M.; Cho, K.R.; Fearon, E.R.; Kern, S.E.; Ruppert, J.M.; Oliner, J.D.; Kinzler, K.W.; Vogelstein, B.
Scrambled exons. Cell 1991,64, 607–613. [CrossRef]
17.
Tufekci, K.U.; Oner, M.G.; Meuwissen, R.L.J.; Genc, S. The role of microRNAs in human diseases. Methods Mol.
Biol. 2014,1107, 33–50. [CrossRef]
18.
Fabian, M.R.; Sonenberg, N.; Filipowicz, W. Regulation of mRNA translation and stability by microRNAs.
Annu. Rev. Biochem. 2010,79, 351–379. [CrossRef] [PubMed]
19. Chen, L.-L.; Yang, L. Regulation of circRNA biogenesis. RNA Biol. 2015,12, 381–388. [CrossRef] [PubMed]
20. Cortés-López, M.; Miura, P. Emerging functions of circular RNAs. Yale J. Biol. Med. 2016,89, 527–537.
21.
Jeck, W.R.; Sorrentino, J.A.; Wang, K.; Slevin, M.K.; Burd, C.E.; Liu, J.; Marzluff, W.F.; Sharpless, N.E. Circular
RNAs are abundant, conserved, and associated with ALU repeats. RNA 2013,19, 141–157. [CrossRef]
22.
Enuka, Y.; Lauriola, M.; Feldman, M.E.; Sas-Chen, A.; Ulitsky, I.; Yarden, Y. Circular RNAs are long-lived and
display only minimal early alterations in response to a growth factor. Nucleic Acids Res.
2016
,44, 1370–1383.
[CrossRef]
23.
Wilusz, J.E.; Sharp, P.A. Molecular biology. A circuitous route to noncoding RNA. Science
2013
,340, 440–441.
[CrossRef]
24.
Cocquerelle, C.; Mascrez, B.; Hetuin, D.; Bailleul, B. Mis-splicing yields circular RNA molecules. FASEB J.
Off. Publ. Fed. Am. Soc. Exp. Biol. 1993,7, 155–160. [CrossRef] [PubMed]
25.
Qu, S.; Yang, X.; Li, X.; Wang, J.; Gao, Y.; Shang, R.; Sun, W.; Dou, K.; Li, H. Circular RNA: A new star of
noncoding RNAs. Cancer Lett. 2015,365, 141–148. [CrossRef]
26.
Kai, D.; Yannian, L.; Yitian, C.; Dinghao, G.; Xin, Z.; Wu, J. Circular RNA HIPK3 promotes gallbladder cancer
cell growth by sponging microRNA-124. Biochem. Biophys. Res. Commun. 2018,503, 863–869. [CrossRef]

Cancers 2020,12, 3250 24 of 29
27.
Starke, S.; Jost, I.; Rossbach, O.; Schneider, T.; Schreiner, S.; Hung, L.-H.; Bindereif, A. Exon circularization
requires canonical splice signals. Cell Rep. 2015,10, 103–111. [CrossRef]
28.
Haddad, G.; Lorenzen, J.M. Biogenesis and function of circular RNAs in health and in disease. Front. Pharmacol.
2019,10, 428. [CrossRef] [PubMed]
29.
Ashwal-Fluss, R.; Meyer, M.; Pamudurti, N.R.; Ivanov, A.; Bartok, O.; Hanan, M.; Evantal, N.; Memczak, S.;
Rajewsky, N.; Kadener, S. circRNA biogenesis competes with pre-mRNA splicing. Mol. Cell
2014
,56, 55–66.
[CrossRef]
30.
Bentley, D.L. Coupling mRNA processing with transcription in time and space. Nat. Rev. Genet.
2014
,15,
163–175. [CrossRef]
31.
Li, Z.; Huang, C.; Bao, C.; Chen, L.; Lin, M.; Wang, X.; Zhong, G.; Yu, B.; Hu, W.; Dai, L.; et al. Exon-intron
circular RNAs regulate transcription in the nucleus. Nat. Struct. Mol. Biol.
2015
,22, 256–264. [CrossRef]
[PubMed]
32.
Zhang, X.-O.; Wang, H.-B.; Zhang, Y.; Lu, X.; Chen, L.-L.; Yang, L. Complementary sequence-mediated exon
circularization. Cell 2014,159, 134–147. [CrossRef] [PubMed]
33.
Huang, X.; He, M.; Huang, S.; Lin, R.; Zhan, M.; Yang, D.; Shen, H.; Xu, S.; Cheng, W.; Yu, J.; et al.
Circular RNA circERBB2 promotes gallbladder cancer progression by regulating PA2G4-dependent rDNA
transcription. Mol. Cancer 2019,18, 166. [CrossRef]
34.
Aktas, T.; Avsar, I.I.; Maticzka, D.; Bhardwaj, V.; Pessoa, R.C.; Mittler, G.; Manke, T.; Backofen, R.; Akhtar, A.
DHX9 suppresses RNA processing defects originating from the Alu invasion of the human genome. Nature
2017,544, 115–119. [CrossRef]
35.
Ivanov, A.; Memczak, S.; Wyler, E.; Torti, F.; Porath, H.T.; Orejuela, M.R.; Piechotta, M.; Levanon, E.Y.;
Landthaler, M.; Dieterich, C.; et al. Analysis of intron sequences reveals hallmarks of circular RNA biogenesis
in animals. Cell Rep. 2015,10, 170–177. [CrossRef]
36.
Conn, S.J.; Pillman, K.A.; Toubia, J.; Conn, V.M.; Salmanidis, M.; Phillips, C.A.; Roslan, S.; Schreiber, A.W.;
Gregory, P.A.; Goodall, G.J. The RNA binding protein quaking regulates formation of circRNAs. Cell
2015
,
160, 1125–1134. [CrossRef] [PubMed]
37.
Barrett, S.P.; Wang, P.L.; Salzman, J. Circular RNA biogenesis can proceed through an exon-containing lariat
precursor. Elife 2015,4, e07540. [CrossRef]
38.
Hansen, T.B.; Wiklund, E.D.; Bramsen, J.B.; Villadsen, S.B.; Statham, A.L.; Clark, S.J.; Kjems, J.
miRNA-dependent gene silencing involving Ago2-mediated cleavage of a circular antisense RNA. EMBO J.
2011,30, 4414–4422. [CrossRef]
39.
Park, O.H.; Ha, H.; Lee, Y.; Boo, S.H.; Kwon, D.H.; Song, H.K.; Kim, Y.K. Endoribonucleolytic cleavage of
m(6)A-containing RNAs by RNase P/MRP complex. Mol. Cell 2019,74, 494–507. [CrossRef]
40.
Fischer, J.W.; Busa, V.F.; Shao, Y.; Leung, A.K.L. Structure-mediated RNA decay by UPF1 and G3BP1. Mol. Cell
2020,78, 70–84. [CrossRef]
41.
Liu, C.-X.; Li, X.; Nan, F.; Jiang, S.; Gao, X.; Guo, S.-K.; Xue, W.; Cui, Y.; Dong, K.; Ding, H.; et al. Structure and
degradation of circular RNAs regulate PKR activation in innate immunity. Cell
2019
,177, 865–880. [CrossRef]
42.
Guo, Y.; Wei, X.; Peng, Y. Structure-mediated degradation of CircRNAs. Trends Cell Biol.
2020
,30, 501–503.
[CrossRef]
43.
Salmena, L.; Poliseno, L.; Tay, Y.; Kats, L.; Pandolfi, P.P. A ceRNA hypothesis: The rosetta stone of a hidden
RNA language? Cell 2011,146, 353–358. [CrossRef]
44. Ambros, V. The functions of animal microRNAs. Nature 2004,431, 350–355. [CrossRef]
45.
Filipowicz, W.; Bhattacharyya, S.N.; Sonenberg, N. Mechanisms of post-transcriptional regulation by
microRNAs: Are the answers in sight? Nat. Rev. Genet. 2008,9, 102–114. [CrossRef]
46.
Qu, S.; Hao, X.; Song, W.; Niu, K.; Yang, X.; Zhang, X.; Shang, R.; Wang, Q.; Li, H.; Liu, Z. Circular RNA
circRHOT1 is upregulated and promotes cell proliferation and invasion in pancreatic cancer. Epigenomics
2019,11, 53–63. [CrossRef]
47.
Li, Z.; Yanfang, W.; Li, J.; Jiang, P.; Peng, T.; Chen, K.; Zhao, X.; Zhang, Y.; Zhen, P.; Zhu, J.; et al.
Tumor-released exosomal circular RNA PDE8A promotes invasive growth via the miR-338/MACC1/MET
pathway in pancreatic cancer. Cancer Lett. 2018,432, 237–250. [CrossRef]
48.
Zhang, X.; Li, H.; Zhen, T.; Dong, Y.; Pei, X.; Shi, H. Hsa_circ_001653 Implicates in the development
of pancreatic ductal adenocarcinoma by regulating microRNA-377-Mediated HOXC6 Axis. Mol Ther.
Nucleic Acids 2020. [CrossRef]

Cancers 2020,12, 3250 25 of 29
49.
Guo, J.U.; Agarwal, V.; Guo, H.; Bartel, D.P. Expanded identification and characterization of mammalian
circular RNAs. Genome Biol. 2014,15, 409. [CrossRef] [PubMed]
50.
Denzler,R.; Agarwal, V.; Stefano, J.; Bartel, D.P.; Stoffel, M. Assessing the ceRNA hypothesis with quantitative
measurements of miRNA and target abundance. Mol. Cell 2014,54, 766–776. [CrossRef]
51.
Piwecka, M.; Glažar, P.; Hernandez-Miranda, L.R.; Memczak, S.; Wolf, S.A.; Rybak-Wolf, A.; Filipchyk, A.;
Klironomos, F.; Cerda Jara, C.A.; Fenske, P.; et al. Loss of a mammalian circular RNA locus causes miRNA
deregulation and affects brain function. Science 2017,357, eaam8526. [CrossRef] [PubMed]
52.
Holdt, L.M.; Stahringer, A.; Sass, K.; Pichler, G.; Kulak, N.A.; Wilfert, W.; Kohlmaier, A.; Herbst, A.;
Northoff, B.H.; Nicolaou, A.; et al. Circular non-coding RNA ANRIL modulates ribosomal RNA maturation
and atherosclerosis in humans. Nat. Commun. 2016,7, 12429. [CrossRef] [PubMed]
53.
Wang, S.; Zhang, Y.; Cai, Q.; Ma, M.; Jin, L.Y.; Weng, M.; Zhou, D.; Tang, Z.; Wang, J.D.; Quan, Z. Circular
RNA FOXP1 promotes tumor progression and Warburg effect in gallbladder cancer by regulating PKLR
expression. Mol. Cancer 2019,18, 145. [CrossRef] [PubMed]
54.
Hao, L.; Rong, W.; Bai, L.; Cui, H.; Zhang, S.; Li, Y.; Chen, D.; Meng, X. Upregulated circular RNA circ_0007534
indicates an unfavorable prognosis in pancreatic ductal adenocarcinoma and regulates cell proliferation,
apoptosis, and invasion by sponging miR-625 and miR-892b. J. Cell Biochem.
2019
,120, 3780–3789. [CrossRef]
55.
Abdelmohsen, K.; Panda, A.C.; Munk, R.; Grammatikakis, I.; Dudekula, D.B.; De, S.; Kim, J.; Noh, J.H.;
Kim, K.M.; Martindale, J.L.; et al. Identification of HuR target circular RNAs uncovers suppression of
PABPN1 translation by CircPABPN1. RNA Biol. 2017,14, 361–369. [CrossRef] [PubMed]
56.
Geng, X.; Jia, Y.; Zhang, Y.; Shi, L.; Li, Q.; Zang, A.; Wang, H. Circular RNA: Biogenesis, degradation,
functions and potential roles in mediating resistance to anticarcinogens. Epigenomics
2020
,12, 267–283.
[CrossRef] [PubMed]
57.
Zhang, Y.; Zhang, X.-O.; Chen, T.; Xiang, J.-F.; Yin, Q.-F.; Xing, Y.-H.; Zhu, S.; Yang, L.; Chen, L.-L. Circular
intronic long noncoding RNAs. Mol. Cell. 2013,51, 792–806. [CrossRef]
58.
Jeck, W.R.; Sharpless, N.E. Detecting and characterizing circular RNAs. Nat. Biotechnol.
2014
,32, 453–461.
[CrossRef]
59. Schneider, T.; Bindereif, A. Circular RNAs: Coding or noncoding? Cell Res. 2017,27, 724–725. [CrossRef]
60.
Chen, C.Y.; Sarnow, P. Initiation of protein synthesis by the eukaryotic translational apparatus on circular
RNAs. Science 1995,268, 415–417. [CrossRef]
61.
Dudekula, D.B.; Panda, A.C.; Grammatikakis, I.; De, S.; Abdelmohsen, K.; Gorospe, M. CircInteractome:
A web tool for exploring circular RNAs and their interacting proteins and microRNAs. RNA Biol.
2016
,13,
34–42. [CrossRef]
62.
Legnini, I.; Di Timoteo, G.; Rossi, F.; Morlando, M.; Briganti, F.; Sthandier, O.; Fatica, A.; Santini, T.;
Andronache, A.; Wade, M.; et al. Circ-ZNF609 is a circular RNA that can be translated and functions in
myogenesis. Mol. Cell 2017,66, 22–37. [CrossRef]
63.
Dong, R.; Zhang, X.-O.; Zhang, Y.; Ma, X.-K.; Chen, L.-L.; Yang, L. CircRNA-derived pseudogenes. Cell Res.
2016,26, 747–750. [CrossRef]
64.
Feng, Z.; Meng, S.; Zhou, H.; Xu, Z.; Tang, Y.; Li, P.; Liu, C.; Huang, Y.; Wu, M. Functions and potential
applications of circular RNAs in cancer stem cells. Front. Oncol. 2019,9, 500. [CrossRef]
65.
Li, H.; Hao, X.; Wang, H.; Liu, Z.; He, Y.; Pu, M.; Zhang, H.; Yu, H.; Duan, J.; Qu, S. Circular RNA Expression
profile of pancreatic ductal adenocarcinoma revealed by microarray. Cell Physiol. Biochem.
2016
,40, 1334–1344.
[CrossRef]
66.
Guo, S.; Xu, X.; Ouyang, Y.; Wang, Y.; Yang, J.; Yin, L.; Ge, J.; Wang, H. Microarray expression profile analysis
of circular RNAs in pancreatic cancer. Mol. Med. Rep. 2018,17, 7661–7671. [CrossRef]
67.
Seimiya, T.; Otsuka, M.; Iwata, T.; Tanaka, E.; Sekiba, K.; Shibata, C.; Moriyama, M.; Nakagawa, R.;
Maruyama, R.; Koike, K. Aberrant expression of a novel circular RNA in pancreatic cancer.
J. Hum. Genet. 2020
.
[CrossRef]
68.
Szabo, L.; Salzman, J. Detecting circular RNAs: Bioinformatic and experimental challenges. Nat. Rev. Genet.
2016,17, 679–692. [CrossRef]
69.
Barrett, S.P.; Salzman, J. Circular RNAs: Analysis, expression and potential functions. Development
2016
,143,
1838–1847. [CrossRef]
70.
Zheng, Y.; Ji, P.; Chen, S.; Hou, L.; Zhao, F. Reconstruction of full-length circular RNAs enables isoform-level
quantification. Genome Med. 2019,11, 2. [CrossRef]

Cancers 2020,12, 3250 26 of 29
71.
Zhang, F.; Zhao, X.; Dong, H.; Xu, J. circRNA expression analysis in lung adenocarcinoma: Comparison of
paired fresh frozen and formalin-fixed paraffin-embedded specimens. Biochem. Biophys. Res. Commun.
2018
,
500, 738–743. [CrossRef]
72.
Thangaraj, M.P.; Furber, K.L.; Gan, J.K.; Ji, S.; Sobchishin, L.; Doucette, J.R.; Nazarali, A.J. RNA-binding
protein quaking stabilizes Sirt2 mRNA during oligodendroglial differentiation. J. Biol. Chem.
2017
,292,
5166–5182. [CrossRef]
73.
Riffo-Campos,
Á
.L.; Riquelme, I.; Brebi-Mieville, P. Tools for sequence-based miRNA target prediction:
What to choose? Int. J. Mol. Sci. 2016,17, 1987. [CrossRef]
74.
Zhao, R.; Ni, J.; Lu, S.; Jiang, S.; You, L.; Liu, H.; Shou, J.; Zhai, C.; Zhang, W.; Shao, S.; et al.
CircUBAP2-mediated competing endogenous RNA network modulates tumorigenesis in pancreatic
adenocarcinoma. Aging 2019,11, 8484–8501. [CrossRef]
75.
Zhou, J.-Z.; Hu, M.-R.; Diao, H.-L.; Wang, Q.-W.; Huang, Q.; Ge, B.-J. Comprehensive analysis of differentially
expressed circRNAs revealed a ceRNA network in pancreatic ductaladenocarcinoma. Arch. Med. Sci. 2019,
15, 979–991. [CrossRef] [PubMed]
76.
Wei, D.-M.; Jiang, M.-T.; Lin, P.; Yang, H.; Dang, Y.-W.; Yu, Q.; Liao, D.-Y.; Luo, D.-Z.; Chen, G. Potential ceRNA
networks involved in autophagy suppression of pancreatic cancer caused by chloroquine diphosphate:
A study based on differentiallyexpressed circRNAs, lncRNAs, miRNAs and mRNAs. Int. J. Oncol.
2019
,54,
600–626. [CrossRef]
77.
Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N.S.; Wang, J.T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T.
Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res.
2003,13, 2498–2504. [CrossRef]
78.
Chen, G.; Shi, Y.; Zhang, Y.; Sun, J. CircRNA_100782 regulates pancreatic carcinoma proliferation through
the IL6-STAT3 pathway. Oncol. Targets Ther. 2017,10, 5783–5794. [CrossRef]
79.
Yang, F.; Liu, D.-Y.; Guo, J.-T.; Ge, N.; Zhu, P.; Liu, X.; Wang, S.; Wang, G.-X.; Sun, S.-Y. Circular RNA
circ-LDLRAD3 as a biomarker in diagnosis of pancreatic cancer. World J. Gastroenterol.
2017
,23, 8345–8354.
[CrossRef]
80.
An, Y.; Cai, H.; Zhang, Y.; Liu, S.; Duan, Y.; Sun, D.; Chen, X.; He, X. circZMYM2 Competed endogenously
with miR-335-5p to regulate JMJD2C in pancreatic cancer. Cell Physiol. Biochem.
2018
,51, 2224–2236.
[CrossRef]
81.
Zhu, P.; Ge, N.; Liu, D.; Yang, F.; Zhang, K.; Guo, J.; Liu, X.; Wang, S.; Wang, G.; Sun, S. Preliminary
investigation of the function of hsa_circ_0006215 in pancreatic cancer. Oncol. Lett.
2018
,16, 603–611.
[CrossRef]
82.
Li, J.; Li, Z.; Jiang, P.; Peng, M.; Zhang, X.; Chen, K.; Liu, H.; Bi, H.; Liu, X.; Li, X. Circular RNA IARS
(circ-IARS) secreted by pancreatic cancer cells and located within exosomes regulates endothelial monolayer
permeability to promote tumor metastasis. J. Exp. Clin. Cancer Res. 2018,37, 177. [CrossRef]
83.
Jiang, Y.; Wang, T.; Yan, L.; Qu, L. A novel prognostic biomarker for pancreatic ductal adenocarcinoma:
Hsa_circ_0001649. Gene 2018,675, 88–93. [CrossRef]
84.
Xu, Y.; Yao, Y.; Gao, P.; Cui, Y. Upregulated circular RNA circ_0030235 predicts unfavorable prognosis in
pancreatic ductal adenocarcinoma and facilitates cell progression by sponging miR-1253 and miR-1294.
Biochem. Biophys. Res. Commun. 2019,509, 138–142. [CrossRef]
85.
Liu, L.; Liu, F.-B.; Huang, M.; Xie, K.; Xie, Q.-S.; Liu, C.-H.; Shen, M.-J.; Huang, Q. Circular RNA ciRS-7
promotes the proliferation and metastasis of pancreatic cancer by regulating miR-7-mediated EGFR/STAT3
signaling pathway. Hepatobiliary Pancreat. Dis. Int. 2019. [CrossRef]
86.
Yang, J.; Cong, X.; Ren, M.; Sun, H.; Liu, T.; Chen, G.; Wang, Q.; Li, Z.; Yu, S.; Yang, Q. Circular RNA
hsa_circRNA_0007334 is predicted to promote MMP7 and COL1A1 expression by functioning as a miRNA
sponge in pancreatic ductal adenocarcinoma. J. Oncol. 2019,2019, 7630894. [CrossRef] [PubMed]
87.
Yao, J.; Zhang, C.; Chen, Y.; Gao, S. Downregulation of circular RNA circ-LDLRAD3 suppresses pancreatic
cancer progression through miR-137-3p/PTN axis. Life Sci. 2019, 116871. [CrossRef]
88.
Chen, Y.; Li, Z.; Zhang, M.; Wang, B.; Ye, J.; Zhang, Y.; Tang, D.; Ma, D.; Jin, W.; Li, X.; et al. Circ-ASH2L
promotes tumor progression by sponging miR-34a to regulate Notch1 in pancreatic ductal adenocarcinoma.
J. Exp. Clin. Cancer Res. 2019,38, 466. [CrossRef]

Cancers 2020,12, 3250 27 of 29
89.
Xing, C.; Ye, H.; Wang, W.; Sun, M.; Zhang, J.; Zhao, Z.; Jiang, G. Circular RNA ADAM9 facilitates the
malignant behaviours of pancreatic cancer by sponging miR-217 and upregulating PRSS3 expression.
Artif. Cells Nanomed. Biotechnol. 2019,47, 3920–3928. [CrossRef] [PubMed]
90.
Liu, Y.; Xia, L.; Dong, L.; Wang, J.; Xiao, Q.; Yu, X.; Zhu, H. CircHIPK3 promotes Gemcitabine (GEM)
resistance in pancreatic cancer cells by sponging miR-330-5p and targets RASSF1. Cancer Manag. Res.
2020
,
12, 921–929. [CrossRef]
91.
Wong, C.H.; Lou, U.K.; Li, Y.; Chan, S.L.; Tong, J.H.M.; To, K.-F.; Chen, Y. CircFOXK2 promotes growth and
metastasis of pancreatic ductal adenocarcinoma by complexing with RNA binding proteins and sponging
MiR-942. Cancer Res. 2020,80, 2138–2149. [CrossRef]
92.
Guo, X.; Zhou, Q.; Su, D.; Luo, Y.; Fu, Z.; Huang, L.; Li, Z.; Jiang, D.; Kong, Y.; Li, Z.; et al. Circular RNA
circBFAR promotes the progression of pancreatic ductal adenocarcinoma via the miR-34b-5p/MET/Akt axis.
Mol. Cancer 2020,19. [CrossRef]
93.
Kong, Y.; Li, Y.; Luo, Y.; Zhu, J.; Zheng, H.; Gao, B.; Guo, X.; Li, Z.; Chen, R.; Chen, C. circNFIB1 inhibits
lymphangiogenesis and lymphatic metastasis via the miR-486-5p/PIK3R1/VEGF-C axis in pancreatic cancer.
Mol. Cancer 2020,19. [CrossRef]
94.
Guo, W.; Zhao, L.; Wei, G.; Liu, P.; Zhang, Y.; Fu, L. Blocking circ_0013912 suppressed cell growth, migration
and invasion of pancreatic ductal adenocarcinoma cells
in vitro
and
in vivo
partially through sponging
miR-7-5p. Cancer Manag. Res. 2020,12, 7291–7303. [CrossRef]
95.
Zhang, X.; Tan, P.; Zhuang, Y.; Du, L. Hsa_circRNA_001587 upregulates the expression of SLC4A4 to
inhibit migration and invasion and angiogenesis of pancreatic cancer cells via binding to microRNA.
Gastrointest. Liver Physiol. 2020. Online ahead of print. [CrossRef]
96.
Jiang, X.-M.; Li, Z.-L.; Li, J.-L.; Xu, Y.; Leng, K.-M.; Cui, Y.-F.; Sun, D.-J. A novel prognostic biomarker for
cholangiocarcinoma: CircRNA Cdr1as. Eur. Rev. Med. Pharmacol. Sci. 2018,22, 365–371. [CrossRef]
97.
Xu, Y.; Yao, Y.; Liu, Y.; Wang, Z.; Hu, Z.; Su, Z.; Li, C.; Wang, H.; Jiang, X.; Kang, P.; et al. Elevation of
circular RNA circ_0005230 facilitates cell growth and metastasis via sponging miR-1238 and miR-1299 in
cholangiocarcinoma. Aging (Albany NY) 2019,11, 1907–1917. [CrossRef] [PubMed]
98.
Xu, Y.; Yao, Y.; Zhong, X.; Leng, K.; Qin, W.; Qu, L.; Cui, Y.; Jiang, X. Downregulated circular
RNA hsa_circ_0001649 regulates proliferation, migration and invasion in cholangiocarcinoma cells.
Biochem. Biophys. Res. Commun. 2018,496, 455–461. [CrossRef]
99.
Li, D.; Tang, Z.; Gao, Z.; Shen, P.; Liu, Z.; Dang, X. Circular RNA CDR1as exerts oncogenic properties partially
through regulating miR-641 in cholangiocarcinoma. Mol. Cell Biol. 2020. [CrossRef]
100.
Wang, S.; Hu, Y.; Lv, X.; Li, B.; Gu, D.; Li, Y.; Sun, Y.; Su, Y. Circ-0000284 arouses malignant phenotype
of cholangiocarcinoma cells and regulates the biological functions of peripheral cells through cellular
communication. Clin. Sci. 2019,133, 1935–1953. [CrossRef]
101.
Xu, Y.; Leng, K.; Yao, Y.; Kang, P.; Liao, G.; Han, Y.; Shi, G.; Ji, D.; Huang, P.; Zheng, W.; et al. A novel circular
RNA, circ-CCAC1, contributes to CCA progression, induces angiogenesis, and disrupts vascular endothelial
barriers. Hepatology 2020. [CrossRef]
102.
Li, X.; He, M.; Guo, J.; Cao, T. Upregulation of circular RNA circ-ERBB2 predicts unfavorable prognosis
and facilitates the progression of gastric cancer via miR-503/CACUL1 and miR-637/MMP-19 signaling.
Biochem. Biophys. Res. Commun. 2019,511, 926–930. [CrossRef]
103.
Lu, Q.; Fang, T. Circular RNA SMARCA5 correlates with favorable clinical tumor features and prognosis,
and increases chemotherapy sensitivity in intrahepatic cholangiocarcinoma. J. Clin. Lab. Anal.
2019
,34,
e23138. [CrossRef]
104.
Junttila, M.R.; De Sauvage, F.J. Influence of tumour micro-environment heterogeneity on therapeutic response.
Nat. Cell Biol. 2013,501, 346–354. [CrossRef]
105.
Ma, Z.; Shuai, Y.; Gao, X.; Wen, X.; Ji, J. Circular RNAs in the tumour microenvironment. Mol. Cancer
2020
,
19, 1–22. [CrossRef]
106.
Zou, Y.; Zheng, S.; Deng, X.; Yang, A.; Xie, X.; Tang, H. The role of circular RNA CDR1as/ciRS-7 in regulating
tumor microenvironment: A pan-cancer analysis. Biomolecules 2019,9, 429. [CrossRef] [PubMed]
107.
Jiang, G.; Cao, F.; Ren, G.; Gao, D.; Bhakta, V.; Zhang, Y.; Cao, H.; Dong, Z.; Zang, W.; Zhang, S.; et al. PRSS3
promotes tumour growth and metastasis of human pancreatic cancer. Gut 2010,59, 1535–1544. [CrossRef]
108.
Wang, G.; Kang, M.-X.; Lu, W.-J.; Chen, Y.; Zhang, B.; Wu, Y.-L. MACC1: A potential molecule associated
with pancreatic cancer metastasis and chemoresistance. Oncol. Lett. 2012,4, 783–791. [CrossRef]

Cancers 2020,12, 3250 28 of 29
109.
Pawlik, T.M.; Gleisner, A.L.; Cameron, J.L.; Winter, J.M.; Assumpcao, L.; Lillemoe, K.D.; Wolfgang, C.;
Hruban, R.H.; Schulick, R.D.; Yeo, C.J.; et al. Prognostic relevance of lymph node ratio following
pancreaticoduodenectomy for pancreatic cancer. Surgery 2007,141, 610–618. [CrossRef]
110.
Ou, Z.-L.; Luo, Z.; Wei, W.; Liang, S.; Gao, T.-L.; Lu, Y.-B. Hypoxia-induced shedding of MICA and
HIF1A-mediated immune escape of pancreatic cancer cells from NK cells: Role of circ_0000977/miR-153 axis.
RNA Biol. 2019,16, 1592–1603. [CrossRef]
111.
Wang, S.; Huang, S.; Sun, Y.L. Epithelial-mesenchymal transition in pancreatic cancer: A review.
BioMed Res. Int. 2017,2017, 1–10. [CrossRef]
112.
Lagunas-Rangel, F.A. Circular RNAs and their participation in stemness of cancer. Med. Oncol.
2020
,37,
42–49. [CrossRef] [PubMed]
113.
Cherubini, A.; Barilani, M.; Rossi, R.L.; Jalal, M.M.K.; Rusconi, F.; Buono, G.; Ragni, E.; Cantarella, G.;
Simpson, H.A.R.W.; P
é
ault, B.; et al. FOXP1 circular RNA sustains mesenchymal stem cell identity via
microRNA inhibition. Nucleic Acids Res. 2019,47, 5325–5340. [CrossRef]
114.
Xiong, J.; Wang, D.; Wei, A.; Ke, N.; Wang, Y.; Tang, J.; He, S.; Hu, W.; Liu, X. MicroRNA-410-3p attenuates
gemcitabine resistance in pancreatic ductal adenocarcinoma by inhibiting HMGB1-mediated autophagy.
Oncotarget 2017,8, 107500–107512. [CrossRef]
115.
Xu, C.; Yu, Y.; Ding, F. Microarray analysis of circular RNA expression profiles associated with gemcitabine
resistance in pancreatic cancer cells. Oncol. Rep. 2018,40, 395–404. [CrossRef]
116.
Shao, F.; Huang, M.; Meng, F.; Huang, Q. Circular RNA Signature Predicts Gemcitabine Resistance of
Pancreatic Ductal Adenocarcinoma. Front. Pharmacol. 2018,9, 584. [CrossRef]
117.
Chen, Z.; Zhang, L.; Han, G.; Zuo, X.; Zhang, Y.; Zhu, Q.; Wu, J.; Wang, X. A meta-analysis of the diagnostic
accuracy of circular RNAs in digestive system malignancy. Cell. Physiol. Biochem.
2018
,45, 962–972.
[CrossRef]
118.
Li, J.; Li, H.; Lv, X.; Yang, Z.; Gao, M.; Bi, Y.; Zhang, Z.; Wang, S.; Cui, Z.; Zhou, B.; et al. Diagnostic
performance of circular RNAs in human cancers: A systematic review and meta-analysis. Mol. Genet.
Genom. Med. 2019,7, e00749. [CrossRef]
119.
Bahn, J.H.; Zhang, Q.; Li, F.; Chan, T.-M.; Lin, X.; Kim, Y.; Wong, D.T.; Xiao, X. The landscape of MicroRNA,
Piwi-Interacting RNA, and circular RNA in human saliva. Clin. Chem. 2015,61, 221–230. [CrossRef]
120.
Tuck, M.K.; Chan, D.W.; Chia, D.; Godwin, A.K.; Grizzle, W.E.; Krueger, K.E.; Rom, W.; Sanda, M.; Sorbara, L.;
Stass, S.; et al. Standard operating procedures for serum and plasma collection: Early detection research
network consensus statement standard operating procedure integration working group. J. Proteome Res.
2009,8, 113–117. [CrossRef]
121.
Bai, H.; Lei, K.; Huang, F.; Jiang, Z.; Zhou, X. Exo-circRNAs: A new paradigm for anticancer therapy.
Mol. Cancer 2019,18, 56. [CrossRef]
122.
Valadi, H.; Ekström, K.; Bossios, A.; Sjöstrand, M.; Lee, J.J.; Tvall, J.O.L.O. Exosome-mediated transfer of
mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat. Cell Biol.
2007
,9,
654–659. [CrossRef] [PubMed]
123.
Li, Y.; Zheng, Q.; Bao, C.; Li, S.; Guo, W.; Zhao, J.; Chen, D.; Gu, J.; He, X.; Huang, S. Circular RNA is enriched
and stable in exosomes: A promising biomarker for cancer diagnosis. Cell Res.
2015
,25, 981–984. [CrossRef]
124.
Seimiya, T.; Otsuka, M.; Liu, H.-Y.; Suzuki, T.; Sekiba, K.; Yamagami, M.; Tanaka, E.; Ishibashi, R.; Koike, K.
Circular RNA and exosomes in pancreatic cancer progression. Transl. Cancer Res.
2018
,7, S745–S747.
[CrossRef]
125.
Shengli, L. RNA-seq Reveals Abundant circRNA, lncRNA and mRNA in Blood Exosomes of Patients with
Pancreatic Carcinoma. Available online: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE100232
(accessed on 10 October 2020).
126.
Li, S.; Li, Y.; Chen, B.; Zhao, J.; Yu, S.; Tang, Y.; Zheng, Q.; Li, Y.; Wang, P.; He, X.; et al. exoRBase: A database of
circRNA, lncRNA and mRNA in human blood exosomes. Nucleic Acids Res.
2017
,46, D106–D112. [CrossRef]
127.
Li, Q.; Geng, S.; Yuan, H.; Li, Y.; Zhang, S.; Pu, L.; Ge, J.; Niu, X.; Li, Y.; Jiang, H. Circular RNA expression
profiles in extracellular vesicles from the plasma of patients with pancreatic ductal adenocarcinoma.
FEBS Open Bio 2019,9, 2052–2062. [CrossRef]
128.
Peinado, H.; Zhang, H.; Matei, I.R.; Costa-Silva, B.; Hoshino, A.; Rodrigues, G.; Psaila, B.; Kaplan, R.N.;
Bromberg, J.F.; Kang, Y.; et al. Pre-metastatic niches: Organ-specific homes for metastases. Nat. Rev. Cancer
2017,17, 302–317. [CrossRef] [PubMed]

Cancers 2020,12, 3250 29 of 29
129.
Sole, C.; Arnaiz, E.; Manterola, L.; Otaegui, D.; Lawrie, C.H. The circulating transcriptome as a source of
cancer liquid biopsy biomarkers. Semin. Cancer Biol. 2019,58, 100–108. [CrossRef]
130.
Reddi, K.K.; Holland, J.F. Elevated serum ribonuclease in patients with pancreatic cancer. Proc. Natl. Acad.
Sci. USA 1976,73, 2308–2310. [CrossRef]
131.
A Burris, H.; Moore, M.J.; Andersen, J.; Green, M.R.; Rothenberg, M.L.; Modiano, M.R.; Cripps, M.C.;
Portenoy, R.K.; Storniolo, A.M.; Tarassoff, P.; et al. Improvements in survival and clinical benefit with
gemcitabine as first-line therapy for patients with advanced pancreas cancer: A randomized trial. J. Clin.
Oncol. 1997,15, 2403–2413. [CrossRef]
132.
Von Hoff, D.D.; Ervin, T.; Arena, F.P.; Chiorean, E.G.; Infante, J.; Moore, M.; Seay, T.; Tjulandin, S.A.; Ma, W.W.;
Saleh, M.N.; et al. Increased survival in pancreatic cancer with nab-paclitaxel plus gemcitabine. N. Engl.
J. Med. 2013,369, 1691–1703. [CrossRef]
133.
Gzil, A.; Zar˛ebska, I.; Bursiewicz, W.; Antosik, P.; Grzanka, D.; Szylberg, Ł. Markers of pancreatic cancer
stem cells and their clinical and therapeutic implications. Mol. Biol. Rep. 2019,46, 6629–6645. [CrossRef]
134.
Lyu, D.; Huang, S. The emerging role and clinical implication of human exonic circular RNA. RNA Biol.
2016
,
14, 1000–1006. [CrossRef]
135.
Notta, F.; Chan-Seng-Yue, M.; Lemire, M.; Ilinca, L.; Wilson, G.W.; Connor, A.A.; Denroche, R.E.; Liang, S.-B.;
Brown, A.M.K.; Kim, J.C.; et al. A renewed model of pancreatic cancer evolution based on genomic
rearrangement patterns. Nat. Cell Biol. 2016,538, 378–382. [CrossRef] [PubMed]
136.
Chu, K.-J.; Ma, Y.-S.; Jiang, X.-Q.; Wu, T.-M.; Wu, Z.-J.; Li, Z.-Z.; Wang, J.-H.; Gao, Q.-X.; Yi, B.; Shi, Y.;
et al. Whole-transcriptome sequencing identifies key differentially expressed mRNAs, miRNAs, lncRNAs,
and circRNAs associated with CHOL. Mol. Ther. Nucleic Acids 2020,21, 592–603. [CrossRef]
137.
Glažar, P.; Papavasileiou, P.; Rajewsky, N. circBase: A database for circular RNAs. RNA
2014
,20, 1666–1670.
[CrossRef]
138.
Dong, R.; Ma, X.-K.; Li, G.-W.; Yang, L. CIRCpedia v2: An updated database for comprehensive circular RNA
annotation and expression comparison. Genom. Proteom. Bioinform.
2018
,16, 226–233. [CrossRef] [PubMed]
139.
Wu, W.; Ji, P.; Zhao, F. CircAtlas: An integrated resource of one million highly accurate circular RNAs from
1070 vertebrate transcriptomes. Genome Biol. 2020,21, 1–14. [CrossRef]
140.
Jacobson, R.; Munding, E.; Hayden, D.M.; Levy, M.A.; Kuzel, T.M.; Pappas, S.G.; Masood, A. Levy evolving
clinical utility of liquid biopsy in gastrointestinal cancers. Cancers 2019,11, 1164. [CrossRef]
141.
Kaczor-Urbanowicz, K.E.; Cheng, J.; King, J.C.; Sedarat, A.; Pandol, S.J.; Farrell, J.J.; Wong, D.T.; Kim, Y.
Reviews on current liquid biopsy for detection and management of pancreatic cancers. Pancreas
2020
,49,
1141–1152. [CrossRef]
142.
Luchini, C.; Veronese, N.; Nottegar, A.; Cappelletti, V.; Daidone, M.G.; Smith, L.; Parris, C.; Brosens, L.A.A.;
Caruso, M.G.; Cheng, L.; et al. Liquid biopsy as surrogate for tissue for molecular profiling in pancreatic
cancer: A meta-analysis towards precision medicine. Cancers 2019,11, 1152. [CrossRef]
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