MOLECULAR AND CLINICAL ONCOLOGY 16: 19, 2022

Dose‑dependent expression of extracellular
microRNAs in HCT116 colorectal cancer cells
exposed to high‑dose‑rate ionising radiation
SATORU MONZEN1, TATSUYA UENO2, MITSURU CHIBA3, YUKI MORINO1,
YASUSHI MARIYA4, ANDRZEJ WOJCIK5,6 and LOVISA LUNDHOLM5
1

Department of Radiation Science, Hirosaki University Graduate School of Health Sciences, Hirosaki,
Aomori 036‑8564; 2Department of Radiology, Southern Tohoku General Hospital, Koriyama, Fukushima 963‑8052;
3Department of Bioscience and Laboratory Medicine, Hirosaki University Graduate School of Health Sciences,
Hirosaki, Aomori 036‑8564; 4Department of Radiology, Aomori Rosai Hospital, Hachinohe, Aomori 031‑8551, Japan;
5
Department of Molecular Biosciences, The Wenner‑Gren Institute, Stockholm University, SE‑10691 Stockholm,
Sweden; 6Institute of Biology, Jan Kochanowski University, 25‑369 Kielce, Poland
Received September 25, 2020; Accepted October 27, 2021
DOI: 10.3892/mco.2021.2452
Abstract. Biomarkers of tumour response to radiotherapy
may help optimise cancer treatment. The aim of the present
study was to identify changes in extracellular microRNAs(miRNAs) as a biomarker of radiation‑induced damage tohuman colorectal cancer cells. HCT116 cells were exposed toincreasing doses of X‑rays, and extracellular miRNAs wereanalysed by microarray. The results were correlated with thefrequency of micronuclei. A total of 59 miRNAs with a posi‑tive correlation and 4 with a negative correlation between dose
(up to 6 Gy) and extracellular miRNA expression were identi‑
fied. In addition, for doses between 0 and 10 Gy, 12 miRNAs
among those 59 miRNAs with a positive correlation wereidentified; for these extracellular miRNAs, a significantly
positive correlation was observed between their expression
and the frequency of micronuclei for doses up to 10 Gy. These
results suggest that specific miRNAs may be considered ascell damage markers and may serve as secreted radiotherapy
response biomarkers for colorectal cancer; however, the resultsmust be further validated in serum samples collected frompatients undergoing radiotherapy.
Introduction
Colorectal cancer (CRC) is one of the most common types ofcancer and the fourth leading cause of cancer‑related mortality

Correspondence to: Dr Satoru Monzen, Department of Radiation
Science, Hirosaki University Graduate School of Health Sciences,
66‑1 Hon‑cho, Hirosaki, Aomori 036‑8564, JapanE‑mail: monzens@hirosaki‑u.ac.jp

Key words: extracellular microRNA, radiotherapy, colorectal
cancer, micronuclei

worldwide (1). CRC may be associated with pain and compro‑
mised quality of life (2,3). Although this type of cancer ismainly treated by surgery, radiotherapy is often used in the
neoadjuvant setting to shrink the size of large tumours prior
to surgery (4). When surgery is not an option, radiotherapy
can be used in combination with chemotherapy as a radical
treatment approach (5).
Exter nal beam radiotherapy has been used for>120 years (6) and is currently considered as a high‑precisioncancer treatment type that relies on inverse treatment planningand a magnitude of instrumental solutions that allow highly
conformal dose delivery (7‑10). Despite high dose conformity
and intensity, some tumours exhibit a high degree of intrinsic
radioresistance, leading to poor therapy outcome (11). Factors
responsible for a high intrinsic radioresistance include tumour
hypoxia and poor reoxygenation during treatment, repopula‑tion between radiotherapy fractions, efficient repair of DNA
damage and a high degree of heterochromatin (11‑13).
With respect to CRC, there is considerable interest indevising biomarkers to predict pathological complete response(pCR) of the tumour to a combination of chemoradiotherapy(CRT) and surgery (14). Responsiveness of the tumour topreoperative CRT is crucial, as it may predict clinical outcomeand even help decide whether post‑CRT surgery is advisable.
Han et al (14) analysed several clinical factors to determine
their suitability as pCR biomarkers, and found that tumour
location and post‑CRT levels of the carcinoembryonic antigen(CEA) were promising predictive factors. However, thespecificity and sensitivity of these as biomarkers were fairlylow (area under the receiver operating characteristic curve
comparing sensitivity vs. specificity = 0.638); therefore, addi‑
tional biomarkers are needed.
Cell response to radiation can be estimated by analysing
the release of microRNAs (miRNAs/miRs) to the surrounding
medium. miRNAs are small, single‑stranded non‑coding
RNAs that serve an important role in the regulation of gene
expression. miRNAs bind to the 3'‑untranslated regions of

2

MONZEN et al: COLORECTAL CANCER RADIOTHERAPY RESPONSE BIOMARKERS

target mRNAs and control protein synthesis by increasing
mRNA degradation or inhibiting translation (15). miRNAs
released extracellularly are contained in extracellular vesicles
and circulate in the body (16). miRNA levels and serum
composition are promising biomarkers of cancer detection andprogression in various types of cancer, including CRC (17‑20).
Selected miRNA levels in the serum of patients who under‑
went radiotherapy for head and neck cancer were found to becorrelated with disease remission (21,22). Promising results
have also been reported for other types of cancer, including
breast or head and neck cancer (23,24).
We became interested in identifying miRNAs that
could be used to predict the response of colorectal tumours
to radiotherapy. Since miRNAs isolated from the serum ofpatients undergoing treatment reflect the response of bothcancer and normal cells to radiation, it was decided to start
the analyses with an in vitro study using a CRC cell line. Thisapproach aims to identify cancer cell‑specific changes in theextracellular miRNA content, which, at a later step, can bevalidated in patient serum. In the present study, the expressionof extracellular miRNAs secreted from irradiated HCT116
CRC cells was quantified by microarray and correlated withthe frequency of cytogenetic damage. Cells were exposed tosingle‑fraction X‑irradiation to assess the basal response of
the cell; however, fractionated irradiation is performed inclinical radiotherapy (e.g., 2 Gy/day x 25 fractions). Deliveringa small fraction of the total radiation dose allows time fornormal cells to repair themselves between treatments, thereby
reducing side effects.
Materials and methods
Cell preparation and culture. The human colorectal cellline HCT116 was purchased from RIKEN BioResource
Center. HCT116 cells were maintained in RPMI‑1640
medium (Thermo Fisher Scientific, Inc.) supplemented with
10% heat‑inactivated foetal bovine serum (Japan Bioserum,Co., Ltd.) and 1% penicillin/streptomycin (Thermo Fisher
Scientific, Inc.) in a humidified atmosphere at 37˚C and 5%
CO2.
Irradiation. X‑ray irradiation (150 kVp, 20 mA with 0.5‑mm
aluminium and 0.3‑mm copper filters) was performed using
an X‑ray generator (MBR‑1520R‑3; Hitachi Medical Co.,
Ltd.), with a distance of 45 cm between the focus and target.
The dose was monitored with a thimble ionisation chamber
placed next to the sample during irradiation. The dose rate was
1 Gy/min.
Apoptosis assay. The apoptotic cells were examined via direct
immunofluorescence flow cytometry (Cell Lab QuantaTM Sc
MPL; Beckman Coulter Immunotech). Cells harvested using
a single pipette were washed twice using Annexin V Binding
Buffer (cat. no. 422201) and immunostained following the
manufacturer's instructions (BioLegend, Inc.). Following
addition of fluorochrome‑labelled protein, Annexin V‑FITC(cat. no. 640906; BioLegend, Inc.), and propidium iodide (PI;MilliporeSigma), fluorescence intensity was quantified using
flow cytometry (Cell Lab QuantaTM Sc MPL) and Kaluza
Analysis Software (ver.2.0; Beckman Coulter, Inc.).

Cytokinesis‑block micronucleus (CBMN) assay. The
CBMN assay was conducted based of the criteria describedby Fenech (25). After exposure of cells to X‑irradiation,
15 µg/ml cytochalasin B (Cyt‑B; FujiFilm Wako Pure
Chemical Corporation) was added to RPMI‑1640 medium,and then the cells were harvested after 3 days, which is whenthe maximum population of binucleated cells (BNCs) could beobserved. Harvesting was performed by fixing the cells with99% methanol at ‑20˚C for 3 min and staining with 1 µg/ml
Hoechst 33342 (MilliporeSigma) for 30 min at room tempera‑
ture. The evaluation was conducted using a fluorescence/bright‑field microscope at x400 magnification (IX71; Olympus
Corporation). The BNC fraction was scored per slide for atleast 103 BNCs. At the same time, the nuclear division index(NDI) was determined from the frequency of >500 viable cells(‘N’ indicates the number of viable cells counted per slide)with 1, 2, 3 or 4 nuclei (M1, M2, M3 or M4, respectively) andcalculated using the formula, NDI = [M1 + (2 x M2) + (3 x M3)+ (4 x M4)]/N by fluorescence microscopic observation (25).
RNA extraction. Total extracellular RNAs released from
irradiated cells (four replicates performed in parallel) wereextracted from the cell culture supernatant using ISOGEN II(Nippon Gene Co., Ltd.), according to the manufacturer's
instructions. The collection of RNAs in the cell culture
supernatant was performed on day 3 after cell irradiation.
This time point was decided as maximum RNA concentra‑tion in the cell culture supernatant and maximum percentage
of apoptotic cells (26). The concentration of extracted RNAs
was examined using Quant‑iT RiboGreen RNA Reagent andKit (Thermo Fisher Scientific, Inc.) and Fluoroskan Ascent(Thermo Fisher Scientific, Inc.). In addition, the peaks ofsmall RNAs were confirmed using Agilent 2100 Bioanalyzer(Agilent Technologies, Inc.). The purity and concentrationof extracellular RNAs were assessed using the NanoDrop
spectrophotometer (NanoDrop Technologies; Thermo Fisher
Scientific, Inc.). The RNA samples had 260/280 nm absor‑
bance ratios of 1.8‑2.0.
Microarray analysis. Cy3‑labelled miRNA was synthesised
from 100 ng total RNA of X‑irradiated and non‑irradiatedcell culture supernatant using miRNA Complete Labelling
Reagent and Hyb kit (Agilent Technologies, Inc.). A SurePrint
G3 human miRNA microarray slide (8x60 K, Ver. 21.0) was
hybridised with the Cy3‑labelled miRNA in a hybridisation
solution prepared with a Gene Expression Hybridisation kit(Agilent Technologies, Inc.), following the manufacturer's
instructions. Cy3 fluorescence signal images on the slide wereobtained by using a microarray scanner (Agilent SureScan
Microarray Scanner G 2600 D; Agilent Technologies, Inc.)and processed using the Feature Extraction version 10.7
software (Agilent Technologies, Inc.) based on the manu‑
facturer's instructions. In the present study, miRNA samples
were collected from cell culture supernatants and the extra‑
cellular miRNA content was examined. The expression data
were processed using GeneSpring GX14.5 software (Agilent
Technologies, Inc.) for normalisation to percentile shift 90%
of all values on the respective microarrays, followed bynormalisation of the median expression level of all samples,
since using an internal control, such as U6, is not appropriate.

MOLECULAR AND CLINICAL ONCOLOGY 16: 19, 2022

3

Figure 1. Analysis of CBMN assay in HCT116 cells exposed to X‑irradiation. (A) Representative flow cytometry images and percentage of apoptotic cells, (B)representative images of nuclear division after irradiation, (C) BNCs with MN, (D) response of NDI and (E) MN frequency. The cell behaviour in HCT116 cells
exposed to 2‑10 Gy X‑irradiation was observed until day 4. Apoptotic analysis and MN frequency in cells exposed to 2‑10 Gy X‑irradiation was estimated using
flow cytometry (Annexin V+/PI- early apoptosis and Annexin V+/PI+ late apoptosis) and the CBMN assay, respectively. The cells were cultured with Cyt‑B,
and MN and NDI were scored at 72 h after exposure to X‑irradiation. The values are the mean ± SE of four separate experiments. CBMN, cytokinesis‑block
micronucleus; MN, micronuclei; NDI, nuclear division index; BNC, binucleated cell; Cyt‑B, cytochalasin B.

The lower raw data signals (lower cut‑off of 50) were removed.
In addition, the coefficient of variation was also set to <50.0%
to remove miRNAs with large variations between experiments
in advance. The average expression of each miRNA from cells
exposed to X‑irradiation at 2‑10 Gy was compared to control
within this normalised dataset (Fig. S1). The results were visu‑
alised with the help of heat maps. The microarray low datain the present study were uploaded onto the Gene Expression
Omnibus database (GSE184174; https://www.ncbi.nlm.nih.
gov/geo/query/acc.cgi?acc=GSE184174).
Statistical analysis. Statistical analysis was performed using
OriginLab software version 9.1 (OriginLab) and Excel 2013
(Microsoft Corporation) with the add‑in software Statcel 3(OMS Publishing, Inc.). The significant differences in miRNA

expression analysis and cell damage analysis were determinedby Pearson's correlation test. P<0.05 was considered to indi‑cate a statistically significant difference.
Results
Analysis of HCT116 cell damage from X‑irradiation. We
previously reported that the clonogenic potential of HCT116
cells exposed to high‑dose‑rate X‑irradiation (1 Gy/min) is
reduced in a dose‑dependent manner, and the number of apop‑
totic cells also increases in a dose‑dependent manner (26).
The percentage of late apoptotic cells (Annexin V+/PI+) andearly apoptotic cells (Annexin V+/PI‑) by exposure to 2‑10 Gy
X‑irradiation was found to be 19‑50% and 5‑17%, respectively,
and it increased in a dose‑dependent manner (Fig. 1A). Based4

MONZEN et al: COLORECTAL CANCER RADIOTHERAPY RESPONSE BIOMARKERS

Figure 2. Dataset of miRNAs in focus. (A) Expression of extracellular miRNAs is displayed using a heat map. (B) miRNAs that were up‑ or downregulated
1.3‑ or 1.5‑fold compared with 0 Gy (left) or the neighbouring lower dose (right) are shown as colour tiles. Upregulation, downregulation and no change areshown as red, blue or grey, respectively. miRNA, microRNA.

on these responses, a CBMN assay was performed using fluo‑
rescence microscopy to elucidate whether these cells exhibit
dose‑dependent nuclear damage by ionising radiation (Fig. 1B
and C). The NDI, which is a marker of cell proliferation in
cultures and is considered as a measure of general cytotoxicity(Fig. 1B), was significantly decreased in HCT116 cells between
days 1 and 4 after exposure to 6 and 10 Gy compared with
non‑irradiated controls (Fig. 1D). As regards the frequency of
micronuclei (MN), an increase (76.0±6.81 MN/103 BNCs) was
observed for doses up to 6 Gy; however, a decreased frequency
was observed at doses >6 Gy (Fig. 1E).
Extracellular miRNA expression following exposure to
X‑irradiation. To determine the miRNAs released from
HCT116 cells X‑irradiated with 2‑10 Gy, the cell culture super‑
natants were collected, and miRNAs were isolated at day 3
when the maximum ratio of apoptotic cells and MN frequency
were reached (26,27). These samples were applied to 8x60 K
format miRNA microarrays, and 132 human miRbase‑anno‑tated miRNAs were detected (Table SI, Fig. 2A). To identify
miRNAs responding in a radiation dose‑dependent manner,
the miRNAs up‑ and downregulated by 1.3‑ or 1.5‑fold wereconsidered, as the number of detectable miRNAs was too

small (1 or 0) at an up‑/downregulation threshold of 2‑fold.
Following exposure to 2‑10 Gy, 44 and 15 miRNAs wereupregulated by 1.3‑ and 1.5‑fold, respectively, vs. the 0 Gy
control group. In addition, 9 and 6 miRNAs were down‑
regulated vs. the 0 Gy control group. On the other hand, no
miRNAs were stepwise up‑ or downregulated by 1.3‑ and1.5‑fold, respectively, compared with the adjacent lower dosein any of the combinations (2 vs. 0, 6 vs. 2 or 10 vs. 6 Gy).
There were still some miRNAs responding in accordance withthe 6‑Gy peak seen for the MN frequency. When comparing
to the adjacent lower dose, patterns of up‑up‑down/up‑up‑nochange and down‑down‑up/down‑down‑no change were foundfor 1 (miR‑3195: 1.3‑ and 1.5‑fold upregulation), 6 (miR‑17,
miR‑29a, miR‑98, miR‑320d, miR‑320e and miR‑4286:
1.3‑fold downregulation) and 2 (miR‑29a and miR‑98: 1.5‑folddownregulation) miRNAs, respectively. The absolute level ofmiRNAs may also be a relevant factor allowing for detectionin the serum, and miR‑572, miR‑939 and miR‑3610 were themost highly expressed miRNAs on average (Table SI).
To elucidate the statistical correlation between radiation
doses and miRNA expression, the 132 miRNA dataset was used,which was created based on the criteria described in Materials
and methods. Using samples between 0 and 6 Gy, 59 miRNAs

MOLECULAR AND CLINICAL ONCOLOGY 16: 19, 2022

5

Figure 3. Schematic illustration of miRNA analysis. From the miRNA microarray data, initial filtering is displayed. Pearson's correlation analysis was
performed between radiation dose and miRNA expression on the 132 filtered miRNAs of focus for this study. The 12 miRNAs exhibiting a significant positive/
negative correlation between MN frequency and miRNA expression were analysed for both the 0‑6 Gy and 0‑10 Gy ranges. IR, ionizing radiation; miRNA/
miR, microRNA; MN, micronuclei.

Figure 4. Relationship between radiation dose and miRNA expression. The 16 experimental samples exposed to X‑irradiation were analysed, and bar charts of
12 miRNAs in each dose (0, 2, 6 and 10 Gy) are shown. *P<0.05 by Tukey's test. miRNA/miR, microRNA.

exhibiting a positive correlation and 4 miRNAs exhibiting anegative correlation were identified (Fig. 3, Table SII). In addi‑tion, for samples between 0 and 10 Gy, 13 miRNAs exhibiting
a positive correlation were identified. Of these, 12 miRNAs
exhibited significantly upregulated expression at doses between
6 and 10 Gy compared with 0 Gy (Fig. 4). It is known that the
maximum limiting dose of MN frequency in blood cells is
3‑4 Gy (25). In the present study on HCT 116 cells, the maximum

limiting dose was up to 6 Gy (Fig. 1E). To predict the cellular
damage and induction of apoptosis by the expression of extra‑
cellular miRNAs, we focused on the relationship between the
12 dose‑dependently upregulated miRNAs and MN frequency(Fig. 5A), and the percentage of Annexin V+/PI+ cells (Fig. 5B).
A significantly positive correlation of all miRNAs (miR‑422a,
R= 0.77; miR‑197, R= 0.50; miR‑1183, R= 0.63; miR‑1288, R= 0.73;
miR‑1229, R= 0.84; miR‑3198, R= 0.74; miR‑423‑5p, R= 0.78;

6

MONZEN et al: COLORECTAL CANCER RADIOTHERAPY RESPONSE BIOMARKERS

Figure 5. Relationship between (A) MN frequency and miRNA expression and between (B) percentage of Annexin V+/PI+ cells and miRNA expression. The
16 experimental samples exposed to 0‑6 Gy X‑irradiation were analysed, and cellular MN frequency was correlated with extracellular miRNA expression.
The correlation line (black line), 95% upper confidence limit and lower confidence limit (dotted lines) are shown. R, Pearson's correlation coefficient. MN,
micronuclei.

miR‑629‑3p, R= 0.65; miR‑3610, R= 0.79; miR‑939, R= 0.67;
miR‑3125, R= 0.62; and miR‑572, R= 0.79) was observed
between the expression level and MN frequency (Fig. 5A). In
addition, a significantly positive correlation of all miRNAs(miR‑422a, R= 0.60; miR‑197, R= 0.54; miR‑1183, R= 0.60;
miR‑1288, R= 0.66; miR‑1229, R= 0.76; miR‑3198, R= 0.76;
miR‑423‑5p, R= 0.64; miR‑629‑3p, R= 0.63; miR‑3610, R= 0.65;
miR‑939, R= 0.63; miR‑3125, R= 0.63; and miR‑572, R= 0.60)
was also observed with the percentage of Annexin V+/PI+ cells(Fig. 5B).
Discussion
The aim of the present study was to quantify the expressionof extracellular miRNAs released from HCT116 CRC cells
exposed to high‑dose single‑fraction ionising radiation to

identify predictive extracellular markers of radiotherapeutic
CRC cell damage.
The dose‑dependent radiation response at the level of cell
nuclear damage, MN (Fig. 1), was in line with the previously
reported reduced clonogenic potency for doses up to 6 Gy (26).
This increased MN frequency indicates increased number of
apoptotic cells. At doses >6 Gy, increased cell death or cell
division arrest most likely contributed to the lower frequency
of MN, since a larger proportion of cells with severe damage
may have undergone apoptosis at the 72‑h time point following
exposure to X‑irradiation.
In radiation biology, the CBMN assay is a radiation
biodosimetry tool that uses peripheral blood lymphocytes andhas an excellent dose dependency (28), contributing to dose
estimation within the range of 2‑6 Gy in cases of accidental
radiation exposure (29). Clinically, 50 Gy/25 fractions orMOLECULAR AND CLINICAL ONCOLOGY 16: 19, 2022

25 Gy/5 fractions (30), which corresponds to 2‑5 Gy/fraction,
are delivered to the target region for CRC. Therefore, the expo‑
sure conditions of the present study are in the clinical range fora single fraction.
It is extremely difficult to analyse the target tissue cells
located in deep regions using the CBMN assay in patients
undergoing radiotherapy. However, it is possible to use
body fluids to detect radiation response markers. A total of
60 specific miRNAs that were released extracellularly andtheir increased or decreased expression after exposure to
X‑radiation correlated with dose were identified (Fig. 4). The
12 selected miRNAs included those positively correlated todose when analysing both 0‑6 and 0‑10 Gy, which shows that
there was a lower expression and MN frequency at 10 Gycompared with those at 6 Gy. According to the American
Society for Radiation Oncology and the Japanese Society for
Radiation Oncology (31,32), the clinical fractionation scheme
for CRC tissue is delivering ~50 Gy as a total dose in 25 frac‑
tions (2 Gy/day). Therefore, miRNA expression in body fluids,
such as the serum, has a potential as a monitoring tool within
this dose range, whether or not cancer cells are damaged.
In research on biomarkers from body fluids, the peripheral
blood, including the metabolites from cancer tissue, has been
evaluated for diagnosis and prognosis prediction. In CRC,
CEA and carbohydrate antigen 19‑9 antigens are considered as
representative markers in cancer screening tests (33). Cancer
researchers have recently become interested in detailed
screening of proteins, DNA and RNA in body fluids for clinicalapplications to further improve the accuracy of cancer detec‑tion (34‑37). In recent years, miRNAs have been reported to behighly promising as cancer biomarkers (38). miRNAs regulate
various biological processes in cells, and their expression fluc‑tuates with the DNA damage response to radiation (39). Thus,
extracellular miRNAs in patients receiving radiotherapy may
reflect a radiation‑specific response and may be useful for thedetermination of radiation dose.
Within the data presented herein, it was observed that 8of 12 miRNAs (miR‑422a, miR‑197, miR‑1183, miR‑1288,
miR‑1229, miR‑423‑5p, miR‑939 and miR‑572) have a function
in CRC. Intracellular expression of miR‑422a, miR‑572 andmiR‑939 serve a role in tumour suppression; miR‑422a targets
AKT1 and MAPK1; miR‑572 targets the MOP‑1 pathway
activated by STAT3 and miR‑939 targets NF‑κ B (40‑44).
Of those, miR‑572 and miR‑939 were also among the threemost highly expressed miRNAs, with the highest chance ofdetection in the blood. miR‑197, miR‑1183 and miR‑1288 areassociated with CRC response (upregulation) to chemotherapy
and/or radiotherapy (45‑47). miR‑423‑5p and miR‑1229 werereported as diagnostic circulating biomarkers of CRC (48,49).
However, the remaining miRNAs (miR‑3198, miR‑629‑3p,
miR‑3610 and miR‑3125) have no previous reports in thefield of CRC. Therefore, the phenomenon seen in this study isthat the dose‑dependent intracellular response to the ionising
reaction affected the mRNA release system, including extra‑
cellular vesicles. Therefore, these 12 miRNAs may serve as
potential biomarkers of radiation response in CRC cells.
Radiotherapy causes activation of several processes inthe tumour microenvironment, such as inflammation, cycling
hypoxia, immunomodulation, revascularisation, and extracel‑lular matrix remodelling coordinated by cancer‑associated7

fibroblasts and fibrosis (50). The release of miRNAs fromtumour cells may contribute to these effects, and it is possiblethat metabolite control differs among patients with cancer.
Of note, there is still a need for improved estimates of which
patients are responding well or less well to treatment; there‑
fore, these miRNAs may serve as markers with the purposeof optimising target exposure to the radiation dose during
radiotherapy. Further detailed in vitro and in vivo studies areneeded to validate these data and to analyse if the expres‑sion pattern of these specific miRNAs also contributes tothe radiosensitivity of CRC. A limitation of the present study
was the lack of investigation of miRNA expression in clinicalsamples (e.g., colon cancer vs. normal adjacent non‑cancerous
samples). To verify the evidence on the 12 released extracel‑lular miRNAs, the reproducibility in animal models and/or
clinical specimens, and the response of CRC cell exposed to
fractionated irradiation, should be further investigated in the
future. In addition, we plan to test the role of these 12 miRNAs
in endocytosis by CRC cells exposed to high‑dose rate ionisingradiation.
In conclusion, the findings of the present study suggest thatspecific extracellular miRNAs have the potential to serve as
cell injury markers induced by single high doses of ionisingradiation in CRC cells.
Acknowledgements
Not applicable.
Funding
The present study was supported by KAKENHI, Grants‑in‑Aid
for Scientific Research, Fund for the Promotion of Joint
International Research (Fostering Joint International Research)(project no. 17KK0181) and Grant‑in‑Aid for challenging
Exploratory Research (project no. 19K22731). The funders had
no role in study design, data collection and analysis, decision
to publish or preparation of the manuscript.
Availability of data and materials
The datasets used and/or analyzed during the current study areavailable from the corresponding author on reasonable request.
Authors' contributions
SM, TU, YMa and LL designed the study, prepared themanuscript draft and substantively participated in revising themanuscript. SM, TU, YMo and MC contributed by analysing
the biological data. TU and AW contributed by normalizing by
the microarray data. All authors read and approved the final
manuscript.
Ethics approval and consent to participate
Not applicable.
Patient consent for publication
Not applicable.

8

MONZEN et al: COLORECTAL CANCER RADIOTHERAPY RESPONSE BIOMARKERS

Competing interests
The authors declare that they have no competing interests.
References
1. Araghi M, Soerjomataram I, Jenkins M, Brierley J, Morris E,
Bray F and Arnold M: Global trends in colorectal cancer
mortality: Projections to the year 2035. Int J Cancer 144:
2992‑3000, 2019.
2. Siegel RL, Miller KD and Jemal A: Cancer statistics, 2019. CA
Cancer J Clin 69: 7‑34, 2019.
3. Arnold M, Sierra MS, Laversanne M, Soerjomataram I, Jemal A
and Bray F: Global patterns and trends in colorectal cancer
incidence and mortality. Gut 66: 683‑691, 2017.
4. van Gijn W, Marijnen CA, Nagtegaal ID, Kranenbarg EM,
Putter H, Wiggers T, Rutten HJ, Påhlman L, Glimelius B andvan de Velde CJ; Dutch Colorectal Cancer Group: Preoperative
radiotherapy combined with total mesorectal excision forresectable rectal cancer: 12‑year follow‑up of the multicentre,
randomised controlled TME trial. Lancet Oncol 12: 575‑582,
2011.
5. Kye BH and Cho HM: Overview of radiation therapy for treating
rectal cancer. Ann Coloproctol 30: 165‑174, 2014.
6. No authors listed: News of Science. Science 125: 18‑22, 1957.
7. Brock KK, McShan DL, Ten Haken RK, Hollister SJ, Dawson LA
and Balter JM: Inclusion of organ deformation in dose calcu‑
lations. Med Phys 30: 290‑295, 2003.
8. De Ruysscher D, Belderbos J, Reymen B, van Elmpt W,
van Baardwijk A, Wanders R, Hoebers F, Vooijs M, Ollers M
and Lambin P: State of the art radiation therapy for lung cancer
2012: A glimpse of the future. Clin Lung Cancer 14: 89‑95,
2013.
9. Emami B, Lyman J, Brown A, Coia L, Goitein M, Munzenrider JE,
Shank B, Solin LJ and Wesson M: Tolerance of normal tissue totherapeutic irradiation. Int J Radiat Oncol Biol Phys 21: 109‑122,
1991.
10. Marks LB, Yorke ED, Jackson A, Ten Haken RK, Constine LS,
Eisbruch A, Bentzen SM, Nam J and Deasy JO: Use of normal
tissue complication probability models in the clinic. Int J Radiat
Oncol Biol Phys 76 (Suppl): S10‑S19, 2010.
11. Baumann M, Krause M, Overgaard J, Debus J, Bentzen SM,
Daartz J, Richter C, Zips D and Bortfeld T: Radiation oncology
in the era of precision medicine. Nat Rev Cancer 16: 234‑249,
2016.
12. Tang L, Wei F, Wu Y, He Y, Shi L, Xiong F, Gong Z, Guo C, Li X,
Deng H, et al: Role of metabolism in cancer cell radioresistanceand radiosensitization methods. J Exp Clin Cancer Res 37: 87,
2018.
13. Chen T, Zhang Y, Guo WH, Meng MB, Mo XM and Lu Y:
Effects of heterochromatin in colorectal cancer stem cells on
radiosensitivity. Chin J Cancer 29: 270‑276, 2010.
14. Han YD, Kim WR, Park SW, Cho MS, Hur H, Min BS, Baik SH,
Lee KY and Kim NK: Predictors of pathologic complete response
in rectal cancer patients undergoing total mesorectal excision
after preoperative chemoradiation. Medicine (Baltimore) 94:
e1971, 2015.
15. Valadi H, Ekström K, Bossios A, Sjöstrand M, Lee JJ and
Lötvall JO: Exosome‑mediated transfer of mRNAs andmicroRNAs is a novel mechanism of genetic exchange between
cells. Nat Cell Biol 9: 654‑659, 2007.
16. Czochor JR and Glazer PM: microRNAs in cancer cell response
to ionizing radiation. Antioxid Redox Signal 21: 293‑312, 2014.
17. Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK,
Pogosova‑Agadjanyan EL, Peterson A, Noteboom J, O'Briant KC,
Allen A, et al: Circulating microRNAs as stable blood‑based
markers for cancer detection. Proc Natl Acad Sci USA 105:
10513‑10518, 2008.
18. Bhat SA, Majid S and Hassan T: MicroRNAs and its emerging
role as breast cancer diagnostic marker ‑ A review. Adv Biomarker
Sci Technol 1: 1‑8, 2019.
19. Yu H, Guan Z, Cuk K, Zhang Y and Brenner H: Circulating
microRNA biomarkers for lung cancer detection in East Asian
populations. Cancers (Basel) 11: 415, 2019.
20. Masuda T, Hayashi N, Kuroda Y, Ito S, Eguchi H and Mimori K:
MicroRNAs as biomarkers in colorectal cancer. Cancers (Basel)
9: 124, 2017.

21. Chen L, Wen Y, Zhang J, Sun W, Lui VWY, Wei Y, Chen F and
Wen W: Prediction of radiotherapy response with a 5‑microRNAsignature‑based nomogram in head and neck squamous cell
carcinoma. Cancer Med 7: 726‑735, 2018.
22. Pasi F, Corbella F, Baio A, Capelli E, De Silvestri A, Tinelli C
and Nano R: Radiation‑induced circulating miRNA expressionin blood of head and neck cancer patients. Radiat Environ
Biophys 59: 237‑244, 2020.
23. Halimi M, Parsian H, Mohsen Asghari S, Sariri R, Moslemi D
and Yeganeh F: MicroRNAs: Are they indicators for prediction of
response to radiotherapy in breast cancer? Irn J Med Hypotheses
Ideas 7: 59‑64, 2013.
24. Moertl S, Mutschelknaus L, Heider T and Atkinson MJ:
MicroRNAs as novel elements in personalized radiotherapy.
Transl Cancer Res 5: S1262‑S1269, 2016.
25. Fenech M: Cytokinesis‑block micronucleus cytome assay. Nat
Protoc 2: 1084‑1104, 2007.
26. Ueno T, Monzen S, Chiba M, Morino Y and Hosokawa Y:
Screening for biological marker of dose‑optimization in cancer
radiotherapy. Nippon Hoshasen Gijutsu Gakkai Zasshi 74:
459‑464, 2018 (In Japanese).
27. Ueno T, Monzen S, Chiba M and Hosokawa Y: Basic investi‑
gation to optimize radiation dose using biological evaluation inradiotherapy. Cytometry Res 28: 7‑11, 2018.
28. International Atomic Energy Agency: Cytogenetic Dosimetry:
Applications in Preparedness for and Response to Radiation
Emergencies. EPR‑Biodosimetry 2011. Vienna, 2011.
29. Liu Q, Cao J, Wang ZQ, Bai YS, Lü YM, Huang QL, Zhao WZ, Li
J, Jiang LP, Tang WS, et al: Dose estimation by chromosome aber‑ration analysis and micronucleus assays in victims accidentally
exposed to (60)Co radiation. Br J Radiol 82: 1027‑1032, 2009.
30. Rodrigues G, Velker V and Best L: Radiation Oncology Primer
and Review, Essential Concepts and Protocols. 1st edition.
Demos MEDICAL, pp1‑376, 2013.
31. Japanese Society for Radiation Oncology: JASTRO Guidelines
2020 for Radiotherapy Treatment Planning. Fifth edition.
Kanehara & Co. Ltd., 2020. (In Japanese)
32. Wo JY, Anker CJ, Ashman JB, Bhadkamkar NA, Bradfield L,
Chang DT, Dorth J, Garcia‑Aguilar J, Goff D, Jacqmin D, et al:
Radiation therapy for rectal cancer: Executive summary of an
ASTRO clinical practice guideline. Pract Radiat Oncol 11: 13‑25,2021.
33. Lech G, Słotwiński R, Słodkowski M and Krasnodębski IW:
Colorectal cancer tumour markers and biomarkers: Recent thera‑
peutic advances. World J Gastroenterol 22: 1745‑1755, 2016.
34. Babel I, Barderas R, Díaz‑Uriarte R, Martínez‑Torrecuadrada JL,
Sánchez‑Carbayo M and Casal JI: Identification of tumor‑associatedautoantigens for the diagnosis of colorectal cancer in serum using highdensity protein microarrays. Mol Cell Proteomics 8: 2382‑2395, 2009.
35. Oh T, Kim N, Moon Y, Kim MS, Hoehn BD, Park CH, Kim TS,
Kim NK, Chung HC and An S: Genome‑wide identificationand validation of a novel methylation biomarker, SDC2, forblood‑based detection of colorectal cancer. J Mol Diagn 15:
498‑507, 2013.
36. Han M, Liew CT, Zhang HW, Chao S, Zheng R, Yip KT, Song ZY,
Li HM, Geng XP, Zhu LX, et al: Novel blood‑based, five‑genebiomarker set for the detection of colorectal cancer. Clin Cancer
Res 14: 455‑460, 2008.
37. Wang S, Xiang J, Li Z, Lu S, Hu J, Gao X, Yu L, Wang L, Wang J,
Wu Y, et al: A plasma microRNA panel for early detection ofcolorectal cancer. Int J Cancer 136: 152‑161, 2015.
38. Chen X, Ba Y, Ma L, Cai X, Yin Y, Wang K, Guo J, Zhang Y,
Chen J, Guo X, et al: Characterization of microRNAs in serum:
A novel class of biomarkers for diagnosis of cancer and otherdiseases. Cell Res 18: 997‑1006, 2008.
39. Bartel DP: MicroRNAs: Genomics, biogenesis, mechanism, andfunction. Cell 116: 281‑297, 2004.
40. Faltejskova P, Svoboda M, Srutova K, Mlcochova J, Besse A,
Nekvindova J, Radova L, Fabian P, Slaba K, Kiss I, et al:
Identification and functional screening of microRNAs highly
deregulated in colorectal cancer. J Cell Mol Med 16: 2655‑2666,
2012.
41. Wei WT, Nian XX, Wang SY, Jiao HL, Wang YX, Xiao ZY,
Yang RW, Ding YQ, Ye YP and Liao WT: miR‑422a inhibits
cell proliferation in colorectal cancer by targeting AKT1 and
MAPK1. Cancer Cell Int 17: 91, 2017.
42. Cui C, Yu J, Huang S, Zhu H and Huang Z: Transcriptional regu‑
lation of gene expression by microRNAs as endogenous decoysof transcription factors. Cell Physiol Biochem 33: 1698‑1714,
2014.

MOLECULAR AND CLINICAL ONCOLOGY 16: 19, 2022

43. Cui C, Zhai D, Cai L, Duan Q, Xie L and Yu J: Long noncoding
RNA HEIH promotes colorectal cancer tumorigenesis via
counteracting miR‑939-mediated transcriptional repression of
Bcl‑xL. Cancer Res Treat 50: 992‑1008, 2018.
44. Wang N, He X, Zhou R, Jia G and Qiao Q: STAT3
induces colorectal carcinoma progression through a novel
miR‑572‑MOAP‑1 pathway. OncoTargets Ther 11: 3475‑3484,
2018.
45. Wang M, Hu H, Wang Y, Huang Q, Huang R, Chen Y, Ma T,
Qiao T, Zhang Q, Wu H, et al: Long non‑coding RNA TUG1
mediates 5‑fluorouracil resistance by acting as a ceRNA of
miR‑197‑3p in colorectal cancer. J Cancer 10: 4603‑4613, 2019.
46. Della Vittoria Scarpati G, Falcetta F, Carlomagno C, Ubezio P,
Marchini S, De Stefano A, Singh VK, D'Incalci M, De Placido S
and Pepe S: A specific miRNA signature correlates with complete
pathological response to neoadjuvant chemoradiotherapy inlocally advanced rectal cancer. Int J Radiat Oncol Biol Phys 83:1113‑1119, 2012.

9

47. Gopalan V, Pillai S, Ebrahimi F, Salajegheh A, Lam TC, Le TK,
Langsford N, Ho YH, Smith RA and Lam AK: Regulation of
microRNA‑1288 in colorectal cancer: Altered expression andits clinicopathological significance. Mol Carcinog 53 (Suppl 1):
E36‑E44, 2014.
48. Lu X and Lu J: The significance of detection of serum miR‑423‑5p
and miR‑484 for diagnosis of colorectal cancer. Clin Lab 61:
187‑190, 2015.
49. Ogata‑Kawata H, Izumiya M, Kurioka D, Honma Y, Yamada Y,
Furuta K, Gunji T, Ohta H, Okamoto H, Sonoda H, et al:
Circulating exosomal microRNAs as biomarkers of colon cancer.
PLOS ONE 9: e92921, 2014.
50. Barker HE, Paget JT, Khan AA and Harrington KJ: The tumour
microenvironment after radiotherapy: mechanisms of resistanceand recurrence. Nat Rev Cancer 15: 409‑425, 2015.