meta-analysis

1. Vol.:(0123456789)
Molecular Diagnosis & Therapy
https://doi.org/10.1007/s40291-019-00440-y
SYSTEMATIC REVIEW
Prognostic Value of MicroRNAs in Stage II Colorectal Cancer Patients:
A Systematic Review and Meta‑Analysis
Shanthi Sabarimurugan1
· Madurantakam Royam Madhav2
· Chellan Kumarasamy3
· Ajay Gupta4
· Siddharta Baxi5
·
Sunil Krishnan6
· Rama Jayaraj7
© Springer Nature Switzerland AG 2020
Abstract
Background We performed a systematic review and meta-analysis to identify and underline multiple microRNAs (miRNAs)
as biomarkers of disease prognosis in stage II colorectal cancer (CRC) patients.
Methods and analysis This systematic review and meta-analysis study was conducted according to Preferred Reporting Items
for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The required articles were collected from online biblio-
graphic databases from January 2011 to November 2019 with multiple permutation keywords. Quantitative data synthesis
was based on a meta-analysis with pooled data to observe and analyse the outcome measures and effect estimates by using
the random effect model. The subgroup analysis was performed from demographic characteristics and the available data.
Results Eighteen articles were included in this study, 16 of which were incorporated for meta-analysis to examine the stage
II CRC prognosis with up- and downregulated miRNA expressions. The pooled hazard ratio (HR) for death in stage II CRC
patients was 1.90 (95% confidence interval 1.63–2.211), with a significant p value. A subgroup analysis based on up- or
downregulated miRNA expression individually and any deregulated miRNA was also associated with a worse prognosis.
The subgroup analysis included parameters such as age, gender, stage II and III combined patients’ survival and the repeti-
tive miRNAs (miR21, miR215, miR143-5p, miR106a and miR145) individually.
Conclusion MicroRNAs play a significant role in determining prognosis in stage II CRC patients, with upregulation of
miR21, miR215, miR143-5p and miR106a, in particular, portending a worse prognosis. These miRNAs could be considered
for further evaluation as biomarkers of prognosis and to guide the decision to administer adjuvant chemotherapy.
1 Introduction
Colorectal cancer (CRC), originating from the colon or rec-
tal lining, is the third most common cancer worldwide; it is
also a major cause of mortality from cancer, with cancer-
related deaths exceeding half a million per year [1]. Austral-
ian bowel cancer statistics suggest an annual incidence of
16,682 new cases (12.4%) and an annual mortality of 4114
(8.6%) associated with CRC [2]. CRC is categorised into
four stages based on submucosal invasion (stage I), pen-
etration of the outer colonic wall (II), lymph node invasion
(III) and metastasis (IV). Stage III and IV have an adverse
prognosis and are treated by advanced targeted therapy/
chemotherapy [3]. Stage II CRC is potentially curable by
surgical resection, but a significant number of stage II CRC
patients can develop recurrence [4]. 40–50% of recurrences
become apparent within the first year after the initial surgi-
cal resection [5]. While chemotherapy reduces the risk of
death from recurrence, it engenders additional toxicity for
the large proportion of patients who do not have a high risk
of recurrence. The current standard of care is to recommend
adjuvant chemotherapy for patients with high-risk disease,
but the definition of high risk is nebulous and primarily
limited to clinical and pathological characteristics and not
molecular characteristics.
MicroRNAs (miRNAs) play a significant role in CRC
carcinogenesis. miRNA dysregulation contributes to the ini-
tiation and progression of CRC [6]. A spectrum of dysregu-
lated miRNAs in cancer tissue correlates with CRC genesis,
progression and therapeutic response [7]. Studies also have
examined the use of circulating serum miRNA and faecal
Electronic supplementary material The online version of this
article (https​://doi.org/10.1007/s4029​1-019-00440​-y) contains
supplementary material, which is available to authorized users.
* Rama Jayaraj
Rama.Jayaraj@cde.edu.au
Extended author information available on the last page of the article

2. S. Sabarimurugan et al.
miRNA expression as non-invasive markers for early detec-
tion of CRC [8, 9]. There are only a few systematic reviews
and meta-analyses on the role of miRNA in CRC [10−13].
By focusing on a subset of all CRCs—those with stage II
disease—this study addresses a clinically relevant question
of which patients have a poor prognosis. In turn, this allows
for personalised CRC therapy, wherein adjuvant chemo-
therapy is recommended only for patients with the highest
likelihood of recurrence, thereby sparing low-risk patients
the toxicity associated with unnecessary chemotherapy.
1.1 Rationale
1.1.1 The Importance of the Issue
While stage I disease is easily treated with surgery alone,
stage II and III cancers are associated with lower cure rates.
Despite the success of curative surgery for localised disease,
20–25% of stage II patients can develop recurrence and die
from the disease [14]. It is established that CRC patients
with stage III disease benefit from adjuvant chemotherapy,
whereas such benefit in stage II patients has remained an
area of controversy [15]. For example, a disease-free sur-
vival (DFS) benefit from adding oxaliplatin has been demon-
strated for stage III disease, whereas the efficacy in stage II
CRC remains less clear [16]. The primary surgical resection
in stage II CRC is intended to be curative. However, 20–25%
develop recurrent disease leading to subsequent death from
the disease within 5 years after the primary surgery [17]. It
is not possible to differentiate the survival outcome between
stage II CRC patients based on traditional clinicopatholog-
ical factors alone [18]. Hence, it is essential to find new
individual-based, genetic biomarkers that can categorise
patient survival and outcomes in stage II CRC.
1.1.2 How Will the Study Address the Issue?
Studies have explored all stages of CRC collectively, but
there is insufficient data on stage II CRC. Hence, we chose
to focus on studies which have analysed the relationship
between the efficacy of adjuvant chemotherapy and miRNA
expression and its impact on the prognosis of stage II CRC
patients by total meta-analysis and subgroup analysis. We
also verify and validate specific miRNA as novel biomarkers
prognostic of treatment outcomes in stage II CRC thereby
allowing for personalised treatment decision-making by cli-
nicians caring for these patients. This is germane to clinical
practice because adjuvant chemotherapy, with its attendant
risk of toxicity, is recommended only for patients at high risk
of recurrence, a poorly defined subset currently.
2 Methods
This review is registered with PROSPERO (registration no.
CRD42017080631). See Sabarimurugan et al. for informa-
tion on the protocol for the review and meta-analysis [19].
2.1 Search Strategy
The research study followed the Preferred Reporting Items
for Systematic Reviews and Meta-Analyses (PRISMA)
guidelines [20]. A comprehensive search strategy has been
developed to obtain suitable peer-reviewed literature. It was
used to conduct searches in the Cochrane Library, EMBASE,
Google Scholar, PubMed, Scopus, and Web of Science data-
bases. The strategy revolves around a few specific keywords
(stage II CRC, miRNA, survival, prognosis, upregulation
and downregulation), which were used in multiple combina-
tions to form search strings to allow for a thorough search
of the databases for all relevant studies. Google Scholar,
though not a bibliographic database, was used to improve the
quality of the search results. Research lists of articles pass-
ing the initial screening process were also used as auxiliary
sources to improve the search strategy. The reference lists
of the collected studies were manually searched to increase
the robustness of the search results further.
2.2 Study Selection
Screening of relevant papers according to the selection
criteria after a blind search of titles and abstracts was per-
formed by two independent co-authors. Only articles meet-
ing all inclusion criteria were included for analysis. If any
Key Points
This is the first systematic review and meta-analysis to
investigate the prognostic significance of microRNA
(miRNA) in stage II colorectal cancer in a large cohort,
among which miR21, miR215, miR143-5p and miR106a
were associated with worse prognosis in stage II colorec-
tal cancer patients.
We conducted subgroup analyses for age, gender and
stage II/III exclusively, along with analyses for multiple
repeated individual miRNA to better know the prognos-
tic effect in colorectal cancer patients.
Given our results miRNA could be considered a predic-
tive biomarker in stage II colorectal cancer, and further
research is needed with a view to slowing the recurrence
rate.

3. Prognostic Value of MicroRNAs in Stage II Colorectal Cancer
discrepancies arose between the two co-authors, a third co-
author was involved in the process to scrutinise the papers
and adjudicate whether a manuscript was to be included in
the final article selection or not.
2.3 Selection Criteria
2.3.1 Inclusion Criteria
The inclusion criteria were as follows: (1) articles that dis-
cussed the survival outcomes of stage II CRC patients; (2)
studies that published the prognostic significance along with
stage III patients; (3) studies that performed hazard analysis
with recorded hazard ratios (HRs), associated 95% confi-
dence intervals (CIs) and p values; (4) studies that analysed
prognosis evaluation by Kaplan–Meier (KM) analysis; (5)
studies that annotated the clinicopathological characteristics
of stage II CRC patients; (6) studies that described upregu-
lation and downregulation of miRNA expression in stage
II CRC patients; (7) studies that were appropriate for the
PRISMA guidelines for systematic review and meta-analy-
sis; and (8) studies published between 2011 and 2018.
2.3.2 Exclusion Criteria
(1) Studies focused on other stages except stage II and III
were eliminated from analysis. (2) Duplicate data were
rejected if the same data had been used in multiple publica-
tions. (3) Data sources consisting of primarily subjective
analysis, with no primary data or method of analysis, were
excluded. (4) Non-English articles were excluded. (5) Arti-
cles which were published in a conference or as a letter to
the editor were eliminated. (6) Non–full-text articles were
not included. (7) Studies reporting a patient number of less
than 30 were excluded. (8) Unpublished materials and thesis
interpretation were eliminated.
2.4 Data Extraction and Management
The data collected from the included articles were tabulated
in the Microsoft Excel sheet framework after extracting the
information from figures and tables as well. The extracted
data elements of this meta-analysis study included the fol-
lowing: author name and publication year, country, size of
population, cohort characteristics of the study population
(age, sex and period of study), tumour anatomic location,
upregulated/ downregulated/deregulated miRNAs, and HR
estimates with 95% CI for overall survival (OS), DFS, and
disease-specific survival (DSS).
2.5 Quality Appraisal and Assessment of Bias
Two reviewers evaluated the quality of the selected studies.
The quality assessment template for observational cohort
and cross-sectional studies from the National Heart, Lung
and Blood Institute (NHLBI) [21] was applied to all studies
screened to verify and validate the quality of the articles, as
described previously [22]. The checklist was used to ensure
that all selected studies maintained a baseline standard qual-
ity, satisfying the core requirements of the study. Two inde-
pendent reviewers scored the studies as good, fair or poor.
2.6 Assessment of Heterogeneity
Comprehensive meta-analysis (CMA) software was used to
perform the meta-analysis to generate forest plots using the
HRs and associated 95% CIs of OS, DFS and DSS, obtained
from the selected studies. The results of effect size and its
impact are essential for the meta-analysis evaluation [23].
The meta-analysis utilised the random effect model to study
heterogeneity, which is based on the Higgins I2
statistic and
Cochran’s Q test. The I2
statistic heterogeneity levels of 25%,
50% and 75% were tentatively assigned as low, moderate and
high heterogeneity, respectively. Cochran’s Q test was con-
sidered as a secondary heterogeneity detection tool. Since
the I2
statistic and Q test alone are not sufficient, because of
the lack of a threshold effect [24, 25], we also performed
the tau squared (τ2
) test. The forest plots generated were
analysed to elucidate the outcome effects and effect esti-
mates of different miRNAs in determining patient survival in
stage II CRC. If there was sufficient clinical data, subgroup
analysis based on age, gender, miRNA and risk factors was
performed to produce a better resolution of the outcome
effect observed from the total meta-analysis.
2.7 Publication Bias
In any systematic review and meta-analysis study, publica-
tion bias can significantly influence the results obtained [26].
Many tools such as funnel plot, Classic and Orwin scale
[27], Egger’s intercept [28], Begg and Mazumdar rank cor-
relation test [29], and Duval and Tweedie’s test can address
this bias, to some extent [30]. Funnel plot measures the study
size, which is on the vertical axis, as a function of effect
size, which is on the horizontal axis. This inverted funnel
plot displays whether the study is biased or unbiased based
on the regular appearance of the plot [22]. Funnel plot and
Egger’s test, considered to be the gold standard for assess-
ment of any publication bias [31], were performed. Begg and
Mazumdar rank tests were conducted between intervention
effect (Kendall’s tau b) and standard error [32].

4. S. Sabarimurugan et al.
2.8 Subgroup Analysis
Subgroup analysis was performed based on the available
additional information from the selected studies to provide
better resolution of the effect of miRNAs on survival out-
comes observed in the total meta-analysis. Many previous
studies have conducted subgroup analysis as lineage strength
from a total meta-analysis [22, 33]. In this study, the sub-
group analysis was performed on repeated miRNA expo-
sure detection [34] and important demographic and clinical/
pathological characteristics [35] if proper information was
available from the collected articles.
3 Results
3.1 Search Results
The studies were selected from six online bibliographical
databases, Cochrane, EMBASE, Google Scholar, PubMed,
Scopus and Web of Science. The process of retrieving
articles yielded 6836 articles after the initial search. The
collected articles were uploaded in endnote and duplicates
were removed (n = 1450), and based on the title screening,
a further 4127 articles were removed, with 1259 articles
being included for further assessment. On completion of
the assessment process, 1035 articles were excluded since
they were not relevant to the topic (letters to the editor, con-
ference abstracts, thesis reports, review articles and non-
English articles).
From 224 available articles, a complete full-text search
was done, and 114 articles had improper prognosis results,
had a sample size of 30, or did not report miRNA expres-
sion data with either KM or HR. One hundred and ten arti-
cles discussed CRC in terms of survival and prognosis;
however, among these, 93 studies were removed because
of the stage II patients’ prognosis results being mixed with
stages other than stage III. Since this study aims to elucidate
the survival outcome impact on stage II cases alone, the
other studies were found to be unsuitable. We collated a final
total of 18 studies for systematic review and meta-analysis
evaluation [14, 17, 36–51]. The schematic representation of
the selection process is illustrated in Fig. 1. Among these
selected articles, only six studies discussed stage II and stage
III CRC prognosis. These studies were included to avoid
excluding any stage II published studies, and a subgroup
analysis was performed after decoupling stage II patient data
to produce better clarity on survival impact.
3.2 Study Characteristics
The study characteristics of each study are elaborated in
Table 1. The characteristics table lists the first author, year
of publication, ethnicity, patient details, survival outcome,
stage of cancer and spread location, assay type and list of
miRNAs along with tumor, nodes, metastases (TNM) sta-
tus. Eighteen full-text articles, published between 2011
and 2019, were included in this study. The selected studies
were reported from Egypt, China, the USA, the UK, Spain,
Denmark, Norway, Israel and Japan. A total of 4613 stage
II CRC patients across all included studies were included
in this systematic review and meta-analysis. Among them,
2465 patients were males and 2148 were females. miRNA
expression was quantified via real-time quantitative poly-
merase chain reaction (qRT-PCR), miRNA sequencing,
microarray, in-situ hybridisation and miRNA profiling in the
included studies. Among the selected 18 studies, six studies
reported prognosis with the combined results of stage II and
stage III CRC patients.
3.3 Meta‑Analysis of Survival Outcome
3.3.1 Does miRNA Expression Affect Survival Outcome?
Eighteen studies with 46 individual cohorts were included in
evaluating the prognostic significance of miRNAs in stage II
CRC patients. The pooled data displayed high heterogene-
ity (I2
− 75.72%, p = 0.000), with the combined effect size
metric being 1.904, 95% CI 1.633–2.211, with p 0.05 by
the random effect model. The observed results were found
to be statistically significant, as demonstrated in Fig. 2. The
pooled HR indicated that miRNA expression increases the
likelihood of death in stage II CRC patients by 90%.
A total of 47 miRNAs have been studied in this meta-
analysis from 18 different studies. Amongst these 18 studies,
the upregulated and downregulated miRNAs were evaluated
as individual cohorts, in which ten studies reported miR-
NAs as downregulated and 37 studies reported miRNAs
as upregulated. miR143-5p, miR145, miR137, miR126,
miR320, miR21, miR34a-5p and miR4772-3p were assessed
in multiple studies or multiple cohorts and were, therefore,
chosen as unique miRNAs for subgroup analysis. From the
ten downregulated miRNAs, three studies demonstrated
increased patient survival, and seven studies associated
miRNA expression with a worse prognosis. The pooled
effect size of downregulated miRNAs was an HR value of
1.475, 95% CI 0.932–2.332, at p value 0.05, which was
a statistically non-significant result. Overall, lower miRNA
expression was associated with poor prognosis and indicated
an increased likelihood of death, by 47%.
The highly expressed upregulated miRNAs across 37
included cohorts were found to be miR29a, miR21, miR20a-
5p, miR103a-3p, miR106b-5p, miR143-5p, miR21-5p,
miR106a, miR215, miR498, miR103a, miR17-3p, miR181c,
miR148a, miR27a-3p, miR31-5p, miR181a-5p, miR30b-
5p, miR30d-5p, miR146a-5p, miR23a-3p, miR150-5p,

5. Prognostic Value of MicroRNAs in Stage II Colorectal Cancer
miR210-3p, miR25-3p, miR196a-5p, miR148a-3p, miR222-
3p, miR30c-5p, miR223-3p, miR5010-3p, miR5100,
miR656-3p and miR671-3p. Among these highly expressed
miRNAs, miR29a alone indicated improved patient sur-
vival, whereas all other miRNAs were associated with worse
prognosis in stage II CRC patients. The pooled effect size
of upregulated miRNA prognosis was HR 1.963, 95% CI
1.675–2.299, with a significant p value. From this subgroup
analysis on miRNA deregulation, we concluded that both
increased and decreased miRNA expression portend a poor
prognosis for stage II CRC patients and leads to an increased
likelihood of death, by 96.3%.
3.3.2 Does the Effect Size Vary Across the Studies?
The Q value was 185.3 with 45 degrees of freedom (df), with
a statistically significant p value. Since the observed effect
size does not have a significant variance, we proceeded to
examine the difference by estimation of I2
statistics. The
I2
statistic depicts the proportion of the observed variance
attributable to variations in specific effect sizes rather than
sampling error. Here, I2
was 75.72%. τ2
, which measures
variance of actual effect sizes in log units, was 0.164. tau,
which quantifies the standard deviation of actual effects, was
0.405.
3.3.3 The Subgroup Variation on Effect Size?
The mean effect size across all studies is modest (HR 1.904,
95% CI 1.633–2.21; Z value 8.437 and corresponding p
value 0.000). It is possible that the mean HR does not vary
by subgroups where all the groups exhibit unfavourable
prognosis in stage II CRC. Therefore, we used the subgroup
analysis to compare the effect size in studies that employed
a high or low expression of miRNAs. The mean risk ratios
in the two groups were found to be 1.475 and 1.963 for
Fig. 1 Schematic representation of study selection and data acquisition

6. S. Sabarimurugan et al.
Table 1 General
characteristics
of
the
included
studies
Study
Population
Study
period
Follow
up
Sample
size
Sample
type
Gender
M/F
Platform
Pathology
Stage
Lymph
node
metastasis
T
stage
miRNA
studied
Endpoint
HR
value
[14]
Egypt
Jan
2004–
Dec
2014
27
months
124
Blood
tissue
samples
64/60
qRT-PCR
Adenocarcinoma-105;
mucinous
adenocar-
cinoma-19
Stage
II
CRC​
NM
T3–T4
miR-498,
miR210,
miR
137,
miR
145,
miR320
DFS,
OS
Yes
[36]
UK
NM
6.08
years
50
Tissue
38/12
qRT-PCR
Extramural
vascular
invasion
Stage
II
CRC​
NM
T2,
T3
T4
miR498,
miR106
miR21
OS,
DFS
Yes
[37]
Spain
Dec
2002–
Jul
2011
NM
69
Tissue
43/26
TaqMan
miRNA
assays
Lymphovascular
invasion,
intestinal
obstruction
or
perforation
Stage
II
colon
cancer
Studied
T3–T4
miR103a,
miR143-5p
and
miR21
DFS
Yes
[38]
China
2002–2010
2–3
years
268
Tissue
170/98
TaqMan
miRNA
assays
Lymphovascular
invasion
Stage
II
III
CRC​
Studied
T3–T4
miR-34a-5p
OS,
DFS
Yes
[39]
Denmark
2003
enrolled
patients
Till
Jan
2010
554
FFPE
tissue
237/317
qPCR
Neuronal
vascular
invasion
Stage
II
colon
cancer
Studied
T3–T4
miR21
RF-CSS,
OS
Yes
[40]
Denmark
2003
enrolled
patients
8.5
years
560
FFPE
tissue
241/319
qPCR
Neuronal
vascular
invasion
Stage
II
colon
cancer
Studied
T3-T4
miR126
RF-CSS,
OS
Yes
[41]
Norway
Jan
2007–
Dec
2011
NM
320
Tissue
162/158
qRT-PCR
Adenocarcinoma
variants
Stage
II
III
colon
cancer
Studied
NM
16
miRNAs
DFS
Yes
[42]
US
Jan
2007
and
Dec
2011
NM
176
Tissue
96/80
miRNA
seq
Adenocarcinoma
variants
Stage
II
colon
cancer
NM
T3-T4
miR5010-3p,
miR-5100,
miR-656-3p
and
miR-
671-3p)
DFS
Yes
[50]
US
NM
NM
34
Tissue
20/14
qRT-PCR
Adenocarcinoma
Stage
II
III
colon
cancer
NM
NM
miR215
OS
No
[51]
Japan
2004–2011
67
months
431
FFPE
fresh
tissue
249/182
miRNA
expres-
sion
analysis
NM
Stage
II
III
CRC​
Studied
T2–T3
T4
8
miRNAs
OS
Yes
[43]
Denmark
2003
enrolled
patients
Till
Jan
2010
520
FFPE
tissue
231/289
In
situ
hybridi-
sation
Neuronal
vascular
invasion
Stage
II
colon
cancer
Studied
T3–T4
miR21
RF-CSS,
OS
Yes
[44]
China
NM
Median
range
32–36
months
175
Serum
113/62
qRT-PCR
NM
Stage
II
III
CRC​
NM
NM
miR-145,
miR-
17-3p
and
miR-106a
DFS
Yes
[45]
US
Sep
2006–
Apr
2011
51
months
84
Blood
53/31
RNA
seq
Cecum/transverse/
descending
colon,
ascending
colon,
sigmoid
Stage
II
III
CRC​
Studied
NM
miR-4772-3p
OS
Yes
[17]
Denmark
NM
NM
197
FFPE
tissue
113/84
In
situ
hybridi-
sation
NM
Stage
II
CRC​
NM
NM
miR21
DFS,
OS
Yes
[46]
China
Till
2012
1 year
110
Tissue
68/42
miRNA
array
Neuronal
vascular
invasion
Stage
II
III
CRC​
NM
NM
miR-148a
DFS,
OS
Yes

7. Prognostic Value of MicroRNAs in Stage II Colorectal Cancer
Table 1 (continued)
Study
Population
Study
period
Follow
up
Sample
size
Sample
type
Gender
M/F
Platform
Pathology
Stage
Lymph
node
metastasis
T
stage
miRNA
studied
Endpoint
HR
value
[47]
Israel
1995
2005
3 years
59
FFPE
tissue
34/25
qRT-PCR
NM
Stage
II
colon
cancer
Studied
NM
miR-29a
DFS
Yes
[48]
Japan
Jan
2003–
Dec
2009
18–127
months
147
FFPE
tissue
102/45
Microarray
Venous
invasion
Stage
II
CRC​
Studied
NM
miR-181c
OS
Yes
[49]
China
Jun
2000,
Jun
2008
Till
death
or
at
last
visit
report
735
FFPE
tissue
431/304
Microarray
Lymphovascular
invasion
Stage
II
colon
cancer
Studied
T3–T4
6
miRNAs
DFS
Yes
DFS
disease-free
survival,
FFPE
formalin-fixed
paraffin-embedded,
NM
not
mentioned,
OS
overall
survival,
qRT-PCR
real-time
quantitative
polymerase
chain
reaction,
RF-CSS
recurrence-free
cancer-specific
survival
downregulated and upregulated miRNAs, respectively. From
the results, we conclude that the miRNA expression corre-
lates with worse prognosis in stage II CRC patients. The Q
value of the differences was 1.335 with 1 df, and the p value
was 0.248.
3.4 Publication Bias
Publication bias analysis was conducted to study the effect of
publication bias on the results of this study. Figure 3 displays
the funnel plot results. The asymmetric nature of the plot
indicates the presence of bias. From the plot, it is apparent
that the smaller studies appear towards the bottom of the
funnel plot, and the more extensive studies appear towards
the top of the graph, with clustering near the mean effect
size. Figure 4 displays the funnel plot with imputed studies.
The overall results of publication bias are depicted in Table 2
(see the electronic supplementary material).
3.5 Subgroup Analysis
Subgroup analysis was performed to increase the resolution
of the findings of the total meta-analysis and focus on spe-
cific miRNA and other parameters to better elucidate their
prognostic effect while ameliorating factors that may lead to
heterogeneity. We analysed various subgroups such as age,
gender, tumour location, lymph node metastasis, repeated
miRNA exposures from various studies, and the combina-
tion of stage II and III patients. The subgroup analysis of
heterogeneity and hypothesis results are tabulated collec-
tively in Table 3 (see the electronic supplementary material).
3.5.1 Subgroup Analysis of Age
A total of 11 studies [17, 37−42, 44, 46, 49, 51] were
included in the age-based subgroup analysis of stage II CRC
patients. The effect size metric of HR calculated using the
fixed effect model at different age levels across 17 studies
was 1.074, 95% CI 1.015–1.136, with a significant p value.
Although the range of the age groups from each cohort var-
ied amongst studies, the rough estimation of the effect of age
could be analysed. The risk ratio results demonstrate that
age does not adversely affect the prognosis in stage II CRC
patients. The Q value of this analysis was 60.39, with 16 df
and an I2
of 73.50, which displays 73% heterogeneity. The
τ2
was 0.004, with a tau value of 0.059 at 0 variances. The
forest plot for the impact of age of stage II CRC patients on
outcomes is shown in Fig. 5.
3.5.2 Subgroup Analysis of Gender
Gender, an essential parameter in any subgroup analysis,
may provide crucial additional information while assessing

8. S. Sabarimurugan et al.
biological effects. Subgroup analysis of gender was con-
ducted from 11 different studies [17, 39−44, 46, 49, 51]. The
overall effect size of the gender variable was associated with
worse prognosis, with an HR of 1.345, 95% CI 1.199–1.508,
with a significant p value of 0.000 and a Z value of 5.063
by the random effect model, which is displayed in Fig. 6.
The Q value was 8.103, with 1 df, and displayed a 29.78% I2
variance. The combined genders had an HR of 1.182, 95%
CI 1.023–1.367, with a p value of 0.023, whereas the male
gender group had an HR of 1.668, 95% CI 1.383–2.013, with
a p value of 0.000. These individual subgroups demonstrate
that gender was associated with worse prognosis in stage II
CRC patients.
3.5.3 Subgroup Analysis of miRNA in Stage II/III Patients
The total overall meta-analysis (Fig. 1) depicts the impact
of survival outcome on stage II CRC patients. Since stage
II and III are more prone to recurrence and often reported
together as non-metastatic cancers, we evaluated them
together as well. A total of six studies were included in this
meta-analysis [38, 42, 44−46, 50]. The results are displayed
Fig. 2 Forest plot of the prognostic value of miRNAs in stage II CRC
patients. The pooled HRs of HR values of stage II CRC prognostic
data were analysed using CMA software (version 3.3.070, USA). The
black diamond represents the combined effect estimate of survival
for stage II CRC patients randomly assigned to miRNA evaluation.
The line with the red square indicates the effect size of miRNA of the
selected study cohorts with a 95% confidence interval. A risk ratio
of more than 1 indicates an increased likelihood of patient survival,
whereas a risk ratio 1 suggests a reduced likelihood of patient
survival. ‘Favours Survival’ refers to better survival, and ‘Favours
Death’ indicates worse survival. CMA comprehensive meta-analysis,
CRC​colorectal cancer, HR hazard ratio, miRNA microRNA

9. Prognostic Value of MicroRNAs in Stage II Colorectal Cancer
in Fig. 7. The total effect size of the HR and 95% CI values
were 2.851 and 1.912–4.251, respectively, with a p value of
0.000. The I2
value was 50%, and the Q value was 19.956,
with 8 df and a tau of 0.460. In total, 11 miRNAs involved
in the meta-analysis were miR341-5p, miR215, miR106a,
miR145, miR17-3p, miR5010-3p, miR-5100, miR-656-3p,
miR-671-3p, miR4772-3p and miR148a. Among these,
except miR145, all the miRNAs were associated with a
worse prognosis and increased risk of death in stage II and
III CRC patients. Additional studies need to be analysed to
better understand the impact of miRNAs on the treatment
outcomes of stage II and III CRC patients.
3.5.4 Subgroup Analysis of Repeated miRNAs
from Different Studies
Five individual miRNAs were noted independently in mul-
tiple studies to correlate with survival outcomes in stage II
CRC. These are included in a subgroup analysis: miR21,
miR215, miR143-5p, miR106a and miR145. The descrip-
tions of the miRNA subgroups are as follows:
3.5.4.1 miR21 miR21 plays a vital role in prognosis in
many cancers. The significance of miR21 as a predictor
of survival outcomes in stage II CRC patients was noted
in our study as well. Four articles from the selected stud-
ies have discussed the significant role of miR21 in stage
II CRC patients [14, 17, 36, 39, 43]. The selected studies
have reported upregulation of miR21 as a poor prognostic
indicator, except for Hansen et al. [39], who reported down-
regulated miR21 as being a poor prognostic indicator. The
forest plot displayed an HR of 1.223, 95% CI 1.010–1.482,
with a p value of 0.040 (Fig. 8). The Z value was 2.058, and
two-tailed p values were 0.040 to accept the null hypothesis.
The τ2
was 0.000 and variance was 0.001. The Q value was
15.260, with an I2
of 67%. These results suggest that upreg-
ulation of miR21 is likely associated with poor prognosis.
3.5.4.2 miR215 Three studies outlined the role of miR215
in defining prognosis in stage II CRC [37, 49, 50]. The
analysis included 839 patients from the selected three stud-
ies and documented HR and 95% CI values of 2.067 and
1.597–2.675, respectively, with a p value of 0.0000, which
Fig. 3 Funnel plot of studies correlating the overall patient survival
and miRNA expression. The funnel plot measures the study size
standard error and precision on the vertical axis and function of effect
size on the horizontal axis. The dots represent the individual study,
and most of this area contains regions of high significance, albeit
with publication bias defined by the asymmetry noted. This suggests
that smaller studies which appear at the bottom are more likely to be
published when they have larger than average effects and spreads on
the right side of the plot, making them more likely to meet the crite-
rion for statistical significance due to non-even distribution of studies.
miRNA microRNA

10. S. Sabarimurugan et al.
Fig. 4 Funnel plot with observed and imputed studies. Large studies
appear outside the funnel and tend to cluster on one side of the funnel
plot. Smaller studies appear toward the top of the graph since there is
more sampling variation in effect size estimates in the smaller studies,
which will be dispersed across a range of values
Fig. 5 Subgroup analysis of age in stage II CRC. The black diamond
represents the estimate of survival of age in association with miRNA
expression in stage II CRC patients. The red line with the red square
indicates the effect size of age of the selected study cohorts, with a
95% confidence interval; the central black line delineates where the
effect favours death or survival, respectively. CRC​colorectal cancer,
miRNA microRNA

11. Prognostic Value of MicroRNAs in Stage II Colorectal Cancer
is statistically significant. The results indicate a correlation
between upregulation of miRNA215 and poor prognosis
in stage II CRC patients, matching the forest plot analy-
sis connoting worse prognosis. The forest plot results are
displayed in Figure 9 (see the electronic supplementary
material).
Fig. 6 Subgroup analysis of gender in stage II CRC. The lowest black
diamond represents the overall estimate of survival of gender in asso-
ciation with miRNA expression in stage II CRC patients. The red line
with the red square indicates the effect size of gender of the selected
study cohorts, with a 95% confidence interval; the central black line
delineates where the effect favours death or survival, respectively.
CRC​colorectal cancer, miRNA microRNA
Fig. 7 Subgroup analysis of stage II/III CRC patients. The black dia-
mond represents the estimate of survival of miRNA expression in
stage II/III CRC patients. The red line with the red square indicates
the effect size of disease stage of the selected study cohorts, with a
95% confidence interval; the central black line delineates where the
effect favours death or survival, respectively. CRC​colorectal cancer,
miRNA microRNA

12. S. Sabarimurugan et al.
3.5.4.3 miR143‑5p Two articles studied miR143-5p [37,
49] and were included in the subgroup analysis. Caritg et al.
reported an association between downregulated miR143-5p
and poor outcomes, whereas Zhang et al. noted upregulation
of this miRNA being a poor prognostic indicator in three
cohorts: an internal testing cohort, a training set, and an
independent validation cohort. Caritg et al. noted upregula-
tion of miR143-5p associated with a good prognosis. The
HR and CI values were 1.645 and 1.081–2.504, respec-
tively, with a p value of 0.020 by the random effect method,
which is displayed in Figure 10 (see the electronic supple-
mentary material). The Q value was 5.315, with 3 df and
an I2
of 43.55%. The tau values were 0.27, and tau variance
was 0.022.
3.5.4.4 miR106a Two studies, Bullock et al. [36] and Li
et al. [44], reported the role of miR106a on the survival of
stage II CRC patients. The total number of patients enrolled
in the subgroup analysis was 225, and both studies noted
that upregulated miR106a correlated with a poor progno-
sis. The HR and CI values were 2.611 and 1.479–4.611,
respectively, with a p value of 0.001, which is displayed in
Figure 11 (see the electronic supplementary material). The
Q value was 0.257, with an I2
of 0.000, representing no het-
erogeneity. The τ2
variance was 0.057.
3.5.4.5 miR145 Subgroup analysis of miR145 included two
studies [14, 44]. Li et al., noted downregulation of miR145
was associated with a good prognosis, whereas Bahnassy
et al., noted that this was associated with worse prognosis
in stage II CRC patients. However, the overall effect size
of HR was 0.872, 95% CI 0.462–1.646, with a p value of
0.674, suggesting that miR145 was associated with a good
prognosis in stage II CRC patients. In total, 474 patients
were enrolled in this subgroup analysis; more studies are
warranted to fully define the prognostic value of miR145 in
stage II CRC patients. The Cochrane’s Q value was 1.336,
with a 25% I2
statistic and a τ2
of 0.053. The forest plot for
miR145 is displayed in Fig. 12 (see the electronic supple-
mentary material).
3.6 Quality Assessment of Selected Studies
Table 4 (see the electronic supplementary material) outlines
the results of the quality assessment of the selected stud-
ies. Among the 18 studies selected for the meta-analysis, all
were scored as possessing reasonable quality. The score of
‘good’ quality was based mainly on the availability of HR
and 95% CI values.
4 Discussion
We performed a comprehensive systematic review and meta-
analysis study evaluating the prognostic utility of miRNAs
in stage II CRC. Stage II and III are often reported and/or
analysed together as non-metastatic CRC with a predisposi-
tion for recurrence following surgery. Hence, we included an
analysis of these two groups jointly as well. However, our pri-
mary emphasis on stage II CRC reflects the clinical need for
selectively treating only the high-risk subset of these patients
with adjuvant chemotherapy after surgery. By defining this
subset using more than clinicopathological factors, a more
nuanced stratification may be achievable. Therefore, this
study aimed at elucidating the effects of miRNAs as molecu-
lar biomarkers in stage II CRC patients. We conducted this
Fig. 8 Subgroup analysis of miR21. The black diamond represents
the estimate of survival of miR21 expression in stage II colorectal
cancer patients. The red line with the red square indicates the effect
size of miR21 of the selected study cohorts, with a 95% confidence
interval; the central black line delineates where the effect favours
death or survival, respectively

13. Prognostic Value of MicroRNAs in Stage II Colorectal Cancer
analysis using 18 different studies across various ethnicities.
This systematic review and meta-analysis included articles
found by searching multiple databases and by a back search
involving recently published review articles [52–55]. The
association between miRNA expression and the patient
response was determined through systematic review and
meta-analysis evaluation, and the exhaustive results suggest
that miRNAs can drive prognosis in stage II CRC patients
when viewed collectively based on the overall effect size and
when viewed individually on subgroup analysis.
Few systematic reviews and meta-analysis studies have
been published regarding the significance of miRNA as
prognostic markers in CRC patients. These studies note that
(1) different miRNAs are upregulated in each stage of CRC
[11], (2) miR21 is upregulated in all stages of CRC [10],
(3) miR186a/b is upregulated in all the stages of CRC [12],
and (4) tissue miRNA21 is upregulated in various stages of
CRC [13]. The current study evaluating miRNA expression
in stage II CRC patients included 39 miRNAs; five miRNAs
were downregulated (miR126, miR137, miR320, miR34a-
5p and miR4772-3p), and 34 miRNAs were upregulated.
Among these, miR21, miR215, miR106a, miR145 and
miR143-5p were reported in multiple studies. miRNAs play
a significant role in CRC cells either via tumour suppressor
or tumour oncogenic mechanisms, which leads to disease
progression. miRNAs regulate cell migration, cell prolifera-
tion, autophagy and also influence tumour microenviron-
ment collapse through their dysregulation, and the changes
occurring in cells may lead to tumourigenesis. Chen et al.
have reported on the importance of up- and downregulated
miRNA expression in CRC, discussing both oncogenic and
suppressive roles in tumour cell proliferation [54]. There-
fore, this study has demonstrated the significant correlation
miRNA expression (upregulated and downregulated) has
with CRC patient survival outcomes.
Among the 39 miRNAs, miR143-5p, miR145, miR126
and miR29a were associated with favourable prognosis,
whereas the rest of the miRNAs indicated a worse prog-
nosis in stage II CRC patients. Among these, miR143-5p
and miR145 were assessed in multiple studies, and hence,
a subgroup analysis was conducted (Figs. 10, 12; see the
electronic supplementary material). The subgroup analysis
of miR143-5p resulted in a conclusion different from the
cumulative meta-analysis, whereas the miR145 subgroup
analysis resulted in projections similar to that of the total
meta-analysis. Collectively, we could conclude that upregu-
lation of miR143-5p portends a worse prognosis and upregu-
lation of miR145 was associated with a good prognosis in
stage II CRC patients. Likewise, more studies on miR126
and miR29a are required for elucidating the clinical impact
of said miRNAs on the prognosis of stage II CRC patients.
Among the miRNAs studied, miR21 is consistently
reported as being deregulated in CRC as well as in many
other carcinomas [56]. As mentioned earlier, miR21 was
studied by Xia et al. [10] in all stages of CRC patients,
where high expression of miR21 portended a worse progno-
sis. Cheng et al. have previously studied the prognostic sig-
nificance of miR21 from tissue samples and serum samples
separately and performed a meta-analysis of 11 studies [13].
The authors concluded that a higher expression of miR21 was
associated with a poor prognosis in all stages of CRC irre-
spective of the source of the samples. Peng et al. conducted
a meta-analysis of 32 studies, reported that a higher expres-
sion of miR21 was associated with worse prognosis in CRC
patients, and confirmed this by subgroup analysis [57]. The
exhibited HR was 1.223, 95% CI 1.010–1.482, with a p value
of 0.040, which is statistically significant. In agreement with
the results of this study, our results also suggest that miR21
is an essential biomarker in stage II CRC in particular.
A systematic review and meta-analysis of the signifi-
cance of different miRNAs at various stages of CRC was
conducted by Gao et al. [11]. They studied 13 miRNAs from
63 articles with 10,254 patients and conducted a subgroup
analysis of multiple miRNAs identified in repeated studies
based on different survival endpoints (OS, DFS). They con-
cluded that higher expression of blood miR141 and tissue
miR21, miR181a or miR224 or lower expression of tissue
miR126 led to the significantly poorer OS (p 0.05). Unfor-
tunately, the authors did not explore the results based on
cancer stage, as studies have shown that the mortality rate
increases with an increasing stage of CRC [58]. More cohort
studies are needed to verify the effect of cancer stage and
miRNA on prognosis in CRC. The current study focusing
on stage II CRC patients provides a clearer picture of a sub-
set of CRCs where identification of a molecular biomarker
may have real-world significance since it might influence
the decision to deliver adjuvant chemotherapy and/or the
choice of newer agents targeting specific signalling pathways
dysregulated by specific miRNAs.
From our systematic review and meta-analysis, nine
studies evaluated the prognostic effect of miRNAs in CRC
[37,39−43,47,49,50]. 32 miRNAs were included in the main
meta-analysis; amongst these, miR29a and miR126 alone
improved the survival outcome. It is to be noted that some
previous studies have been limited to stage II colon cancer
rather than stage II rectal cancer. Given that the 1-year mor-
tality rate of colon cancer patients was 10.9%, whereas it was
4.8% for rectal cancer patients [59], it may be prudent for
future studies to look at rectal cancer separately.
Surgery and adjuvant chemotherapy are the standard
treatment for stage III CRC (defined by the presence of
lymph node metastases), but not for stage II CRC (where
patients have no lymph-node metastases) [60]. Five-year
survival rates drop from roughly 80% for stage II CRC to
45–50% for stage III CRC [60]. Bockelman et al. [61] con-
ducted a meta-analysis of outcomes of stage II and III colon

14. S. Sabarimurugan et al.
cancer. The results demonstrated a 5-year DFS of 82.7%
for stage II colon cancer without adjuvant chemotherapy,
whereas the 5-year DFS was 63.8% for stage III colon cancer
with adjuvant chemotherapy.
In our subgroup analysis coupling stage II and stage III
CRC patients, miRNA deregulation was associated with
a poorer survival outcome, as demonstrated in Fig. 7. Six
articles from our qualitative studies were included in this
subgroup analysis. Of these, 11 miRNAs were studied, for
which overexpression of miR341-5p, miR215, miR106a,
miR17-3p, miR5010-3p, miR-5100, miR-656-3p, miR-
671-3p, miR4772-3p and miR148a was associated with
worse prognosis, whereas upregulation of miR145 was
associated with better prognosis in stage II/III CRC patients.
4.1 The Strength of the Study
This study is the first of its kind to evaluate the prognostic
effect of miRNAs on stage II CRC. By focusing on stage II
CRC patients, we address a clinically relevant question of
which patients are at higher risk of failure and may warrant
adjuvant chemotherapy. Furthermore, identifying miRNAs that
drive poorer outcomes in these patients may also open up the
possibility of selectively targeting the dysregulated molecular
signalling pathways driven by these miRNAs. Therefore, this
emphasis on stage II CRC may help define specific miRNAs as
promising biomarkers of treatment outcomes, determinants of
therapeutic intervention, and possibly the basis for novel inter-
ventions targeting specific molecular vulnerabilities. By ana-
lysing the impact of miRNAs on the prognosis of both stage II
and stage III patients, this meta-analysis ensures that pertinent
data derived from a somewhat similar cohort of patients are not
excluded and inadvertently ignored, particularly since the pat-
terns of failure of both stages is similar albeit the risk of such
failure varies considerably. Lastly, the adaptation of PRISMA
guidelines, the measurement of the quality of enrolled studies,
and the assessment of publication bias are potential strengths
of this systematic review and meta-analysis evaluation.
4.2 Limitations of the Study
There are few limitations that have emerged in this study. (1)
Publication bias was identified in this study, which may be
due to the variation in patients or sources of miRNA detec-
tion. (2) The study period was relatively short (i.e. from
2011 to 2019) due to non-availability of stage II articles
published earlier. (3) Data for various endpoints such as DFS
and OS where not available, limiting our meta-analysis to
just some endpoints. (4) Due to variability in binning of age
groups among all the collected articles, subgroup analysis
on age was somewhat constrained; while this could serve
as hypothesis generating for the future, it is currently not
conclusive. (5) Similarly, dichotomising CRC patients into
colon and rectal cancer patients may be beneficial in an
effort to highlight the role of miRNAs as biomarkers of out-
comes specifically in stage II rectal cancer.
4.3 Future Directions
The focus of this study was on stage II CRC, but as noted
above, there is a need to highlight the role of miRNAs in
defining the prognosis of stage II rectal cancer independ-
ent of colon cancer. Similarly, based on our analysis, addi-
tional emphasis may be placed on benchmarking the role of
miR21 as an important biomarker for further evaluation and
eventual prospective clinical validation. Taken together with
previously published meta-analysis results, our meta-anal-
ysis confirms a prominent role for miRNAs as prognostic
markers in CRC patients and particularly in stage II patients,
where there is an unmet need for stratification into high- and
low-risk patients so as to tailor personalised treatments in
the form of generic adjuvant chemotherapy or molecularly
targeted therapy based on signalling pathways disrupted or
dysregulated by specific miRNAs.
5 Conclusion
In conclusion, this systematic review and meta-analysis
studied the prognostic effect of miRNAs in stage II CRC
patients. Among the studied miRNAs, miR21, miR215,
miR145, miR143-5p and miR106 were assessed in a sub-
group analysis and were associated with a worse prognosis.
These miRNAs may serve as initial targets for prospective
validation studies aimed at identifying significant biomark-
ers of treatment response, especially with an eye towards
the choice of treatment approach in the clinic. As more such
studies are performed, we envision a larger pool of literature
that can improve the accuracy of these results.
Acknowledgements Our cancer research team would like to acknowl-
edge the meta-analysis concepts and applications workshop manual by
Michael Borenstein for detailed instructions and guidelines on report-
ing meta-analysis evaluation, subgroup analysis and publication bias
detection (www.meta-analy​sis-works​hops.com).
Author Contributions RJ and SS conceived this study and provided
supervision and mentorship. SS led the development of the study and
design, wrote the first draft of the article, and coordinated and inte-
grated comments from co-authors. RJ, CK, MRM, AG, SB and SK
revised and edited the final drafts and gave input to the final draft of
the protocol. All the authors read, refined and approved the final ver-
sion of the manuscript.
Compliance with Ethical Standards
Conflict of interest All authors (RJ, SS, CK, MRM, AG, SB and SK)
have declared that there is no conflict of interest.

15. Prognostic Value of MicroRNAs in Stage II Colorectal Cancer
Funding This research received no specific grant from any funding
agency in public, commercial or not-for-profit sectors.
References
1. Naeem BAA. Utilization of microRNAs in colorectal cancer: a
review. Adv Surg Res. 2017;1(1):1–6.
2. Bowel cancer statistics [Internet]. Government of Australia. 2017.
https​://bowel​-cance​r.cance​raust​ralia​.gov.au/stati​stics​. Accessed 4
Jan 2019.
3. Graham JS, Cassidy J. Adjuvant therapy in colon cancer. J Clin
Oncol. 2012;12(1):99–109.
4. To KK, Tong CW, Wu M, et al. MicroRNAs in the prognosis and
therapy of colorectal cancer: from bench to bedside. J Clin Oncol.
2018;24(27):2949.
5. Yang IP, Tsai HL, Hou MF, et al. MicroRNA-93 inhibits
tumor growth and early relapse of human colorectal cancer
by affecting genes involved in the cell cycle. Carcinogenesis.
2012;33(8):1522–30.
6. Weng W, Feng J, Qin H, et al. An update on miRNAs as biological
and clinical determinants in colorectal cancer: a bench-to-bedside
approach. Future Oncol. 2015;11(12):1791–808.
7. Dong Y, Yu J, Ng SS. MicroRNA dysregulation as a prognostic
biomarker in colorectal cancer. Cancer Manag Res. 2014;6:405.
8. Hollis M, Nair K, Vyas A, et al. MicroRNAs potential utility in
colon cancer: early detection, prognosis, and chemosensitivity.
World J Gastroenterol. 2015;21(27):8284.
9. Bastaminejad S, Taherikalani M, Ghanbari R, et al. Investigation
of microRNA-21 expression levels in serum and stool as a poten-
tial non-invasive biomarker for diagnosis of colorectal cancer. Iran
Biomed J 2017;21(2):106.
10. Xia X, Yang B, Zhai X, et al. Prognostic role of microRNA-21 in
colorectal cancer: a meta-analysis. Plos One 2013;8(11):e80426.
11. Gao S, Zhao Z-Y, Wu R, et al. Prognostic value of microR-
NAs in colorectal cancer: a meta-analysis. Cancer Manag Res.
2018;10:907.
12. Gu X, Jin R, Mao X, et al. Prognostic value of miRNA-
181a/b in colorectal cancer: a meta-analysis. Biomark Med
2018;12(3):299–308.
13. Chen Z, Liu H, Jin W, et al. Tissue microRNA-21 expression
predicted recurrence and poor survival in patients with colorectal
cancer—a meta-analysis. OncoTargets Ther 2016;9:2615.
14. Bahnassy AA, El-Sayed M, Ali NM, et al. Aberrant expression
of miRNAs predicts recurrence and survival in stage-II colorectal
cancer patients from Egypt. Appl Cancer Res. 2017;37(1):39.
15. Bertagnolli MM, Redston M, Compton CC, et al. Microsatellite
instability and loss of heterozygosity at chromosomal location
18q: prospective evaluation of biomarkers for stages II and III
colon cancer—a study of CALGB 9581 and 89803. J Clin Oncol
2011;29(23):3153.
16. André T, Boni C, Navarro M, et al. Improved overall survival with
oxaliplatin, fluorouracil, and leucovorin as adjuvant treatment in
stage II or III colon cancer in the MOSAIC trial. J Clin Oncol.
2009;27(19):3109–16.
17. Nielsen BS, Jorgensen S, Fog JU, et al. High levels of micro-
RNA-21 in the stroma of colorectal cancers predict short disease-
free survival in stage II colon cancer patients. Clin Exp Metasta-
sis. 2011;28(1):27–38.
18. Xi Y, Nakajima G, Gavin E, et al. Systematic analysis of micro-
RNA expression of RNA extracted from fresh frozen and for-
malin-fixed paraffin-embedded samples. RNA (New York, NY).
2007;13(10):1668–74.
19. Sabarimurugan S, Kumarasamy C, Madurantakam Royam M,
et al. Validation of miRNA prognostic significance in stage II
colorectal cancer: a protocol for systematic review and meta-
analysis of observational clinical studies. Med (Baltim).
2019;98(12):e14570.
20. Shamseer L, Moher D, Clarke M, et al. Preferred reporting items
for systematic review and meta-analysis protocols (PRISMA-P)
2015: elaboration and explanation. Bmj. 2015;2(350):g7647.
21. National Heart, Lung and Blood Institute. Quality assessment tool
for quality assessment of systematic reviews and meta-analyses.
2019. https​://www.nhlbi​.nih.gov/healt​h-topic​s/study​-quali​ty-asses​
sment​-tools​. Accessed 4 Jan 2019.
22. Sabarimurugan S, Kumarasamy C, Baxi S, et al. Systematic
review and meta-analysis of prognostic microRNA biomarkers
for survival outcome in nasopharyngeal carcinoma. PloS One.
2019;14(2):e0209760.
23. Jayaraj R, Kumarasamy C, Sabarimurugan S, Baxi S. Diag-
nostic and prognostic value of microRNAs for cancers-strat-
egies and approaches to improve the clinical utility. J Cancer.
2019;10(5):1252–3.
24. Jayaraj R, Kumarasamy C, Sabarimurugan S, et al. Commentary:
blood-derived microRNAs for pancreatic cancer diagnosis: a
narrative review and meta-analysis [general commentary]. Front
Physiol. 2019;9:1896.
25. Jayaraj R, Kumarasamy C, Madhav MR, et al. Comment on
“Systematic review and meta-analysis of diagnostic accuracy
of miRNAs in patients with pancreatic cancer”. Dis Mark.
2018;2018:6904569.
26. Jayaraj R, Kumarasamy C, Sabarimurugan S, et al. Meta-anal-
ysis of penile cancer: conceptual interpretations. Lancet Oncol.
2019;20(3):e125.
27. Rosenthal R. The file drawer problem and tolerance for null
results. Psychol Bull. 1979;86(3):638.
28. Egger M, Smith GD, Schneider M, et al. Bias in meta-
analysis detected by a simple, graphical test. BMJ
1997;315(7109):629–634.
29. Begg CB, Mazumdar M. Operating characteristics of a rank corre-
lation test for publication bias. Biometrics. 1994;50(4):1088–101.
30. Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based
method of testing and adjusting for publication bias in meta-anal-
ysis. Biometrics. 2000;56(2):455–63.
31. Jayaraj R, Kumarasamy C, Sabarimurugan S, et al. Letter to the
Editor in response to the article, “The epidemiology of oral human
papillomavirus infection in healthy populations: a systematic
review and meta-analysis”. Oral Oncol. 2018;84:121–2.
32. Jayaraj R, Kumarasamy C, Sabarimurugan S, et al. Prognostic
significance of Lymph Node Ratio (LNR): clinical insights and
strategies for routine clinical practice. Oral Oncol. 2019;19:125–7.
https​://doi.org/10.1016/j.oralo​ncolo​gy.2019.02.012
33. Sabarimurugan S, Royam MM, Das A, et al. Systematic review
and meta-analysis of the prognostic significance of miRNAs in
melanoma patients. Mol Diagn Therapy 2018;2018:1–17.
34. Sabarimurugan S, Madurantakam Royam M, Kumarasamy
C, et al. Prognostic miRNA classifiers in t cell acute lympho-
blastic leukemia: study protocol for a systematic review and
meta-analysis of observational clinical studies. Med (Baltim).
2019;98(9):e14569.
35. Madhav MR, Nayagam SG, Biyani K, et al. Epidemiologic analy-
sis of breast cancer incidence, prevalence, and mortality in India:
protocol for a systematic review and meta-analyses. Medicine.
2018;97(52):e13680.
36. Bullock MD, Pickard K, Mitter R, et al. Stratifying risk of recur-
rence in stage II colorectal cancer using deregulated stromal and
epithelial microRNAs. Oncotarget. 2015;6(9):7262–79.
37. Caritg O, Navarro A, Moreno I, et al. Identifying high-risk
stage II colon cancer patients: a three-microRNA-based

16. S. Sabarimurugan et al.
Affiliations
Shanthi Sabarimurugan1
· Madurantakam Royam Madhav2
· Chellan Kumarasamy3
· Ajay Gupta4
· Siddharta Baxi5
·
Sunil Krishnan6
· Rama Jayaraj7
Shanthi Sabarimurugan
Shanthi.Sabarimurugan@genesiscare.com
Madurantakam Royam Madhav
madhav.sridaran@gmail.com
Chellan Kumarasamy
chellank54@gmail.com
Ajay Gupta
oncol@rediffmail.com
1
Theranostics, GenesisCare, Perth, WA, Australia
2
School of Biosciences and Technology, Vellore Institute
of Technology, Vellore, Tamil Nadu, India
3
University of Adelaide, North Terrace Campus, Adelaide,
SA 5005, Australia
4
American Oncology Institute, Nagpur, India
5
Genesis Cancer Care Centre, Bunbury, WA, Australia
6
Department of Radiation Oncology, The University of Texas,
Houston, TX, USA
7
College of Health and Human Sciences, Charles Darwin
University, Ellengowan Drive, Darwin, NT 0810, Australia
score as a prognostic biomarker. Clin Colorectal Cancer.
2016;15(4):e175–82.
38. Gao J, Li N, Dong Y, et al. miR-34a-5p suppresses colorectal
cancer metastasis and predicts recurrence in patients with stage
II/III colorectal cancer. Oncogene. 2015;34(31):4142–52.
39. Hansen TF, Kjær-Frifeldt S, Christensen RD, et al. Redefining
high-risk patients with stage II colon cancer by risk index and
microRNA-21: results from a population-based cohort. Br J Can-
cer. 2014;111(7):1285–92.
40. Hansen TF, Kjaer-Frifeldt S, Morgenthaler S, et al. The prognostic
value of microRNA-126 and microvessel density in patients with
stage II colon cancer: results from a population cohort. J Transl
Med. 2014;10(12):254.
41. Jacob H, Stanisavljevic L, Storli KE, et al. Identification of a
sixteen-microRNA signature as prognostic biomarker for stage II
and III colon cancer. Oncotarget. 2017;8(50):87837–47.
42. Jacob H, Stanisavljevic L, Storli KE, et al. A four-microRNA clas-
sifier as a novel prognostic marker for tumor recurrence in stage
II colon cancer. Sci Rep. 2018;8(1):6157.
43. Kjaer-Frifeldt S, Hansen TF, Nielsen BS, et al. The prognostic
importance of miR-21 in stage II colon cancer: a population-based
study. Br J Cancer. 2012;107(7):1169–74.
44. Li J, Liu Y, Wang C, et al. Serum miRNA expression profile as a
prognostic biomarker of stage II/III colorectal adenocarcinoma.
Sci Rep. 2015;5:12921–12921.
45. Liu C, Eng C, Shen J, et al. Serum exosomal miR-4772-3p is a
predictor of tumor recurrence in stage II and III colon cancer.
Oncotarget. 2016;7(46):76250–60.
46. Tsai HL, Yang IP, Huang CW, et al. Clinical significance of
microRNA-148a in patients with early relapse of stage II stage
and III colorectal cancer after curative resection. Transl Res.
2013;162(4):258–68.
47. Weissmann-Brenner A, Kushnir M, Lithwick Yanai G, et al.
Tumor microRNA-29a expression and the risk of recurrence in
stage II colon cancer. Int J Oncol. 2012;40(6):2097–103.
48. Yamazaki N, Koga Y, Taniguchi H, et al. High expression of miR-
181c as a predictive marker of recurrence in stage II colorectal
cancer. Oncotarget. 2017;8(4):6970–83.
49. Zhang JX, Song W, Chen ZH, et al. Prognostic and predictive
value of a microRNA signature in stage II colon cancer: a micro-
RNA expression analysis. Lancet Oncol. 2013;14(13):1295–306.
50. Karaayvaz M, Pal T, Song B, et al. Prognostic significance of miR-
215 in colon cancer. Clin Colorectal Cancer. 2011;10(4):340–7.
51. Kandimalla R, Gao F, Matsuyama T, et al. Genome-wide Discov-
ery and Identification of a Novel miRNA Signature for Recurrence
Prediction in Stage II and III Colorectal Cancer. Clin Cancer Res.
2018;24(16):3867–3877
52. Gungormez C, Gumushan Aktas H, Dilsiz N, et al. Novel miR-
NAs as potential biomarkers in stage II colon cancer: microarray
analysis. Mol Biol Rep. 2019;46(4):4175–83.
53. Anvarnia A, Mohaddes-Gharamaleki F, Asadi M, et al. Dys-
regulated microRNAs in colorectal carcinogenesis: new
insight to cell survival and apoptosis regulation. J Cell Physiol.
2019;234(12):21683–93.
54. Chen B, Xia Z, Deng Y-N, et al. Emerging microRNA biomarkers
for colorectal cancer diagnosis and prognosis. R Soc Open Biol.
2019;9(1):180212.
55. Hernandez R, Sánchez-Jiménez E, Melguizo C, et al. Downregu-
lated microRNAs in the colorectal cancer: diagnostic and thera-
peutic perspectives. BMB Rep. 2018;51(11):563.
56. Li T, Leong MH, Harms B, et al. MicroRNA-21 as a poten-
tial colon and rectal cancer biomarker. World J Gastroenterol.
2013;19(34):5615–21.
57. Peng Q, Zhang X, Min M, et al. The clinical role of microRNA-21
as a promising biomarker in the diagnosis and prognosis of colo-
rectal cancer: a systematic review and meta-analysis. Oncotarget.
2017;8(27):44893–909.
58. Marcella S, Miller JE. Racial differences in colorectal cancer mor-
tality: the importance of stage and socioeconomic status. J Clin
Epidemiol. 2001;54(4):359–366.
59. Gooiker GA, Dekker JW, Bastiaannet E, et al. Risk factors for
excess mortality in the first year after curative surgery for colo-
rectal cancer. Ann Surg Oncol. 2012;19(8):2428–34.
60. Liefers G-J, Cleton-Jansen A-M, van de Velde CJH, et al. Micro-
metastases and survival in stage II colorectal cancer. N Engl J
Med. 1998;339(4):223–8.
61. Bockelman C, Engelmann BE, Kaprio T, et al. Risk of recurrence
in patients with colon cancer stage II and III: a systematic review
and meta-analysis of recent literature. Acta Oncol (Stockholm,
Swed). 2015;54(1):5–16.