Abstract
Radiotherapy is a fundamental step in the treatment of breast cancer
patients. The treatment efficiency is however reduced by the possible
onset of radiation resistance. In order to develop the effective
treatment approach, it is important to understand molecular basis of
radiosensitivity in breast cancer. The purpose of the present study was
to investigate different radiation response of breast cancer cell
lines, and find out if this response may be related to change in the
microRNAs expression profile. MDA-MB-231 and T47D cells were subjected
to different doses of radiation, then MTT and clonogenic assays were
performed to assess radiation sensitivity. Cytofluorometric and western
blot analysis were performed to gain insight into cell cycle
distribution and protein expression. MicroRNA sequencing and
bioinformatics prediction methods were used to identify the difference
in microRNAs expression between two breast cancer cells and the related
genes and pathways. T47D cells were more sensitive to radiation respect
to MDA-MB-231 cells as demonstrated by a remarkable G2 cell cycle
arrest followed by a greater reduction in cell viability and colony
forming ability. Accordingly, T47D cells showed higher increase in the
phosphorylation of ATM, TP53 and CDK1 (markers of radiation response)
and faster and more pronounced increase in RAD51 and γH2AX expression
(markers of DNA damage), when compared to MDA-MB-231 cells. The two
cell lines had different microRNAs expression profiles with a confirmed
significant differential expression of miR-16-5p, which targets cell
cycle related genes and predicts longer overall survival of breast
cancer patients, as determined by bioinformatics analysis. These
results suggest a possible role for miR-16-5p as radiation sensitizing
microRNA and as prognostic/predictive biomarker in breast cancer.
Subject terms: Breast cancer, Cancer therapy, miRNAs, Biomarkers
Introduction
Breast cancer (BC) is one of leading cause of mortality among women
worldwide^[36]1. Radiotherapy (RT) is currently used as the standard
treatment for control of breast cancer^[37]2. Although up to 83% of
early- stage diagnosed breast cancer cases can be treated by
postoperative radiotherapy, some patients will suffer from spread
metastasis and recurrence after radiation therapy^[38]3. The failure in
RT application might be due to radiation resistance, which caused by
remaining the cells have greater tolerance to ionizing radiation (IR)
or the intrinsic resistance^[39]4.
Ionizing radiation can cause direct DNA strand break or producing free
radicals, leading to more damages in DNA or other cell components. DNA
lesions activate the DNA damage response (DDR), which essential for
activation of downstream signaling pathways such as DNA repair, cell
cycle arrest or apoptosis^[40]5. Breast cancer cells respond to
radiation in different ways, depending on their different biological
and molecular characteristic^[41]6,[42]7. Understanding the molecular
mechanism behind the differential response to radiation is important
toward a possible personalized use of radiotherapy in patients with
different BC subtype. Furthermore, identification of specific molecular
target can be used to better classify BC patients^[43]8.
Variation in radiation sensitivity could be influenced by gene
expression and post translational modification^[44]9. MicroRNAs
(miRNAs) are the group of short noncoding RNA that mostly have negative
regulatory effect on gene expression^[45]10. They can regulate almost
all cellular processes including DNA repair, cell cycle arrest,
apoptosis, and survival^[46]11. Not surprisingly, miRNAs have been
identified as modulator of radiation responses^[47]12. The relation
between deregulated expression of miRNAs and radiation response has
been also observed in breast cancer cells^[48]13,[49]14. For instance,
miR-668 could mediate radiation resistance by targeting the NF-κB
pathway^[50]15 or miR-21 is well-known miRNA involved in
radioresistance by regulation of G2/M checkpoint^[51]12; on the other
side, miR-200c could enhance radiation sensitivity through inhibiting
expression of DNA repair genes and autophagy^[52]16,[53]17 and miR-620
was upregulated in irradiated breast cancer cells, and its silencing
contributed to reduce cell survival following exposure^[54]18.
Although many clinical studies have identified the specific miRNAs
which associated with radiation sensitivity^[55]19–[56]21, cell-based
studies are needed to better understand the role of specific miRNAs in
the response to radiation and possibly verify if they can be used as
new biomarkers of radioresistance. In the present study, we aimed to
investigate if radiotherapy could commonly alter the expression of
selected miRNAs in two breast cancer cell lines, namely MDA-MB-231 and
T47D, that have different radiosensitivity.
Results
Radiation reduced cell viability and colony forming ability of T47D cells
To evaluate radiation sensitivity, three breast cancer cell lines were
exposed to increasing dose of radiation and analyzed for cell viability
using the MTT assay at different time points after irradiation. As it
shown in Fig. [57]1a, using MDA-MB-231 cells, significant reduction in
cells viability was observed only at the doses of 6 and 10 Gy after
72 hours. Conversely, in both SKBR3 and T47D, cell viability gradually
decreased with increasing dose of radiation becoming significant after
48 hours of incubation, when compared to non-irradiated control cells
(Fig. [58]1b,c). These differences were more evident in T47D cells as
demonstrated by the calculation of their LD[50] (i.e. the dose of
radiation which kills the 50 percent of cells) four days after
irradiation. Indeed, the estimated LD[50] values were of 9.26, 5.20,
and 3.94 for MDA-MB-231, SKBR3 and T47D, respectively. Based on these
results, we selected the MDA-MB-231 and T47D, as the two cell lines
with the highest difference in the response to radiation.
Figure 1.
[59]Figure 1
[60]Open in a new tab
T47D cells are the most sensitive to radiation-induced cell death.
(a–c) MTT assay evaluating cell viability of MDA-MB-231 (a), SKBR3 (b)
and T47D (c) exposed to different radiation doses (2, 6, and 10 Gy) and
evaluated 24, 48, or 72 hours after the irradiaition. The LD50 reported
in the Fig (a-c). was caculated for each cell line four days after
irradiation. Data represent the mean ± standard deviation (SD) of three
experiments, each performed in triplcate. Statistical significance was
evaluated using two-way analysis of variance (ANOVA), with Tukey’s
multiple comparison test. (d) Survival curve of MDA-MB-231 and T47D
cell evaluated by their colony forming ability using the indicated
radiation doses. Data represent the mean ± SD of two independent
experiments, each performed in triplicate. Multiple t-test, using the
Holm-Sidak method, was used to statistical comparison. *p < 0.05,
**p < 0.01, ***p < 0.001 and ns (not significant).
The above data were confirmed by the evaluation of colony forming
ability of MDA-MB-231 and T47D irradiated cells showing that the
survival fraction of cells exposed to 2 Gy radiation dose was 72.4% and
53.1% for MDA-MB-231 and T47D cells, respectively and that
statistically significant differences in cell survival were present in
the range of 4 to 10 Gy (Fig. [61]1d). Cell survival curve was fitted
to Linear Quadratic (LQ) model, and α and β parameters were calculated
for each cell line. The α represents cell death at low dose, resulting
from single radiation event. The β term describes the cell killing at
high dose, caused by interaction of damage from two separate radiation
events. The higher α and β indicate more radiation sensitivity. The
higher α value confirmed the higher radiosentivity of T47D cells,
whereas no difference was seen between β values (Table [62]1).
Table 1.
Radiobiological parameters of cell survival curve.
α (Gy^−1) β(Gy^−1) SF[2]
MDA-MB-231 0.069 ± 0.018 0.049 ± 0.016 0.72 ± 0.069
T47D 0.22 ± 0.0051 0.048 ± 0.0053 0.48 ± 0.089
[63]Open in a new tab
The α and β describe cell radiosensitivity, cells with higher α or β
are more sensitive to radiation.
SF[2]: Survival fraction at dose 2 Gy.
Induction of G2/M arrest by ionizing radiation in T47D cells
We next evaluated the cell cycle distribution of irradiated cells
collected 24 and 48 hours after irradiation. As shown in Fig. [64]2a,b,
radiation clearly changed cell cycle distribution in both cell lines,
with differences more prominent in T47D compared to MDA-MB-231 cells as
evaluated by a dose response curve using of cells collected 24 hours
after radiation. In particular, at this time point, T47D cells showed
dose-dependent accumulation of the cells in G2/M and subG1
(apoptotic/dead cells) phases of the cell cycle (Fig. [65]2b).
Conversely, at the 24 hours timepoint, MDA-MB-231 cells started to
accumulate in the G2/M phase of the cell cycle only at doses ≥6 Gy and
failed to accumulate in subG1, again demonstrating a higher resistance
to radiation respect to T47D. Next, the analysis of cell cycle
distribution over the time demonstrated that independently on the dose
used, MDA-MB-231 cells completely recovered from IR within 48 hours
with a minimal accumulation of the subG1 population (likely
necrotic/apoptotic cells), while T47D cells at the 48 hours timepoint
maintained the G2/M block and progressively accumulated in the subG1
phase of the cell cycle (Fig. [66]2c,d).
Figure 2.
[67]Figure 2
[68]Open in a new tab
T47D cells display a prolonged G2/M arrest after irradiation. (a,b)
Graphs reporting the cell cycle distribution of MDA-MB-231 (a) and T47D
(b) treated with 2–10 Gy of radiation and analyzed 24 hours after
irradiation. Data represent the mean of two independent experiments.
(c) Isograms reporting the cell cycle distribution of MDA-MB-231 (c)
and T47D (d) irradiated with 2, 6 and 10 Gy, and analyzed 24 and
48 hours after irradiation. A typical experiment is shown.
Different expression pattern of cell cycle and DNA repair related proteins in
T47D cells
The differences in cell cycle distribution were accompanied by
biochemical differences in key signal transduction pathways, as
evaluated by western blot looking at the expression of selected
phosphorylated proteins. To use a clinical relevant conditions and to
better highlight the differences between RT-sensitive and –resistant
cells, we used the 2 Gy (dose used in fractionated RT) and the 0.5 Gy
doses. Irradiated cells were harvested at different time points (i.e.
1, 8 and 24 hours after radiation) and cell lysates analyzed by western
blot. In MDA-MB-231 cells the expression of both pSer1981-ATM and
pTyr1068- EGFR, two known mechanisms of resistance to radiation,
rapidly increased (onehour timepoint) (Fig. [69]3a, left panels). The
increased expression of pSer1981-ATM remained higher than the one
observed in non-irradiated cells up to 24 hours after irradiation,
while EGFR phosphorylation even increased over the same period of time
(Fig. [70]3a, left panels). In T47D, ATM phosphorylation increased
8 hours after irradiation both at 0.5 and 2 Gy doses while EGFR
phosphorylation was only slightly modified by irradiation at all the
considered time points (Fig. [71]3a Right panels).
Figure 3.
[72]Figure 3
[73]Open in a new tab
Signal transduction pathways are differently activated by radiation in
T47D and MDA-MB-231 cells. (a) Western blot analysis evaluating the
expression of the indicated phospho-proteins in T47D and MDA-MB-231
irradiated with 0.5 and 2 Gy doses and the harvested at the indicated
time points. Vinculin was used as loading control. (b) Western blot
analysis evaluating the expression of γH2AX and RAD51 in cells
irradiated with 2 Gy and then collected at the indicated time points.
Full-length blot is shown in Supplementary Fig. [74]S1. Vinculin and
GAPDH were used as loading control. NIR = Non-Irradiated cells.
The expression of pSer15-TP53 and pTyr15-CDK1, used as markers of cell
cycle arrest and apoptosis and G2/M transition respectively, was
evaluated on the same lysate. Results show that in MDA-MB-231 cells,
irradiation induced a biphasic increase of pSer15-TP53 at one and
24 hours timepoints. These changes were independent on the dose used
(Fig. [75]3a, left panels). The expression of pTyr15-CDK1 (a
phosphorylation event that prevents the fully activation of CDK1 and
thus, when present, it blocks the cell cycle at the G2/M transition),
was only slightly modified by 0.5 Gy dose and started to increase with
the 2 Gy dose at 24 hours after treatment (Fig. [76]3a, left panels).
In T47D cells, both the increase in pSer15-TP53 and pTyr15-CDK1 was
dose dependent. However, while pSer15-TP53 expression increased after
one hour of treatment and remained high over the whole period of
observation, with only a small decrease 24 hours after irradiation,
pTyr15-CDK1 increased at the 8 hours timepoint and remained high up to
24 hours after treatment (Fig. [77]3a, right panels), in line with the
G2/M accumulation observed in FACS analyses (Fig. [78]2).
Finally, we evaluated the expression of two markers of DNA damage,
namely RAD51 and γH2AX (i.e. Ser139 phosphorylated Histone H2X). In
T47D, RAD51 expression increased rapidly and remained high up to
24 hours while γH2AX expression reached a peak 4 hours after
irradiation and then rapidly decreased (Fig. [79]3b, left panels). In
MDA-MB-231 cells, the levels of RAD51 increased only at 24 hours post
irradiation while γH2AX expression was only slightly modified over the
considered period of time (Fig. [80]3b, right panels).
MicroRNA expression profiling identified upregulation of miR-23b-3p,
miR-16-5p in radiosensitive breast cancer cells
Data collected so far indicated that T47D and MDA-MB-231 had different
sensitivity to irradiation with differences in cell cycle distribution
and signaling pathways activation. We thus investigated if these
differences were also accompanied by differences in miRNAs expression
using microRNAs sequencing. The miRNAs expression level in MDA-MB-231
and T47D irradiated cells collected 24 hours after the treatment was
compared with their non-expression in not-exposed control. In
MDA-MB-231, we found 88 differentially expressed miRNAs of which 44
were upregulated and 44 were downregulated in irradiated cells. A
larger proportion of miRNAs was modified in T47D cells where we found
183 were upregulated and 59 were downregulated by 2 Gy irradiation
(Table [81]2). The most upregulated and downregulated miRNAs in
radiation treated T47D and MDA-MB-231 cells are reported in
Fig. [82]4a,b. When we look closer to the expression of the miRNAs
mostly modified in the two cell lines, we observed that the miR-23b-3p
and miR-16-5p were commonly modified by irradiation being upregulated
in T47D and downregulated in MDA-MB-231 (Fig. [83]4c).
Table 2.
The deregulated miRNAs in the cell exposed to 2 Gy dose at 24 hours.
DE group Total DEG Upregulated Downregulated
MDA-MB-231 (2 Gy) vs. MDA-MB-231 (Control) 88 44 44
T47D (2 Gy) vs. T47D (Control) 242 183 59
[84]Open in a new tab
DEG: Differential Expression Group.
Figure 4.
[85]Figure 4
[86]Open in a new tab
Evaluation of miRNAs expression modified by irradiation in breast
cancer cells. (a,b) Heat maps of the most differentially expressed
miRNAs in T47D (a) and MDA-MB-231 (b) cells irradiated with 2 Gy dose
and analyzed 24 hours after irradiation and compared to the miRNAs
expression levels of the respective non-irradiated cells. (c) Venn
diagram of the 5/6 most differentially expressed miRNAs in the two cell
lines. In red are reported miRNAs overexpressed and in green those
downregulated in irradiated cells. FC = Fold change.
The miR-16-5p showed different expression in radioresistant compared to
radiosensitive cells
To validate the miRNA-Seq results and evaluation of the difference in
miR-16-5p expression after irradiation, we used quantitative real-time
polymerase chain reaction (qRT-PCR) on RNA extracted from both cell
lines 24 hours after irradiation with 2 Gy. In line with the miRNA
sequencing results, we found a two-fold increase in miR-16-5p
expression in irradiated T47D respect to non-irradiated cells, while no
significant differences were observed between irradiated and
non-irradiated MDA-MB-231 cells (Fig. [87]5).
Figure 5.
Figure 5
[88]Open in a new tab
Validation of miR-16-5p expression modification. Graph reporting the
normalized expression of miR-16-5p in T47D and MDA-MD-231 cells exposed
to 2 Gy and collected after 24 hours evaluated by the qRT-PCR analysis.
The U6 (RNU6-1) snRNA was used as reference gene. Data represent the
mean ± standard deviation (SD) of two experiments, performed in
duplicate. Statistical significance was evaluated using two-way
analysis of variance (ANOVA), with Tukey’s multiple comparison test.
**p < 0.01, ***p < 0.001.
The miR-16-5p targets prediction and pathway enrichment analysis
The potential target genes of miR-16-5p were retrieved by
online TargetScan database, after setting threshold ranging from −1 to
−0.4 for total score and then visual mapped in Cytoscape (Fig. [89]6a).
The repression of the target gens are defined by the complementary
features between miRNA and mRNAs, as negative score represent better
repression^[90]22. To explore the probable biological function and
related pathway, Gene Ontology and KEGG enrichment analysis were
predicted through Enrichr online database. The results showed the
correlation between target genes and negative regulation of mitotic
cell cycle (GO: 0045930), G2 DNA damage checkpoint (GO: 0031572),
regulation of response to DNA damage stimulus (GO: 2001020), activation
of MAPKKK activity (GO: 0000185), cellular response to UV (GO:
0034644), DNA damage response, signal transduction by p53 class
mediator resulting in cell cycle arrest (GO: 0006977), cytoplasmic
sequestering of NF-kappaB (GO: 0007253) and DNA damage induced protein
phosphorylation (GO: 0006975). KEGGG pathway analysis also indicated
that cell cycle is the downstream pathway principally related to
miR-16-5p (Fig. [91]6b,c).
Figure 6.
[92]Figure 6
[93]Open in a new tab
Bioinformatics evaluation of miR-16-5p target genes. (a) The predicted
genes target of miR-16-5p obtained setting the cut of ≤–0.4 using the
target prediction TargetScan V7.2. (b) GO biological process and (c)
KEGG pathway enrichment analysis evaluating the process/pathways most
significantly represented among the possible miR-16-5p target genes (as
evaluated in a). (d) Kaplan-Meier survival curves evaluating the
Overall Survival (OS) of stage breast cancer patient included in the
METABRIC (n = 1262, left) and TCGA (n = 1061, right) datasets, based on
the expression of miR-16 using the KM Plotter online tool. HR = Hazard
Ratio and CI = Confidence Interval. p-values were calculated using the
log-rank test.
Finally, using in silico analyses we tried to verify if miR-16
expression, being correlated with a higher sensitivity to radiation,
could have a prognostic value in breast cancer patients. To this aim we
used the Kaplan- Meier plotter online tool, which allows verifying the
prognostic potential of miRNAs in up to four different databases. Our
analyses showed that both in the Metabric dataset (n = 1262 patients
with a median follow up of 94 months) and in the TCGA dataset (n = 1061
patients with a median follow up of 25 months) high miR-16 expression
predicts longer overall survival for the patients (Hazard Ratio 0.73
and 0.75 for Metabric and TCGA, respectively) (Fig. [94]6d).
Discussion
Radiation resistance represents a relevant clinical unmet need in the
treatment of breast cancer patients. Identification of molecular
markers involved in radiation response could help to identify new drugs
as a radiosensitizer and could be used as predictive biomarker of
radiation response^[95]23. Several studies have reported many potential
targets for enhancement of radiation sensitivity in breast cancer
cells^[96]24–[97]27.
Here we report the identification of miR-16 as a possible prognostic
biomarker in breast cancer starting from the analysis of miRNAs
modified by radiation in breast cancer cells.
To reach this goal we have characterized an in vitro model of radiation
response using two estrogen receptors positive and one triple negative
breast cancer cell lines. Among the three tested breast cancer cell
lines, we selected MDA-MB-231 and T47D cells that showed the highest
differences in radiation sensitivity. Using clonogenic assay to
extrapolate radiobiological parameters, we found that T47D had a 3.1
folds higher α value accompanied by a 1.5 folds higher SF2 when
compared to MDA-MB-231 suggesting that they had an intrinsic radiation
sensitivity^[98]28. Similar results were recently reported by Speers et
al. that showed a higher survival fraction for MDA-MB-231 compared to
T47D cells at 2 Gy dose^[99]29.
Induction of cell cycle arrest in both G1 and G2 cell cycle phases
provide time for DNA damages repair following irradiation^[100]23.
Interestingly, we found a stronger increase of G2/M cell population in
T47D compared to MDA-MB-231 cells in each dose of radiation. This
result is in agreement with the previous findings reporting that
radiation-induced G2 arrest is more pronounced in radiosensitive
respect to radioresistant cells^[101]30. These differences are in line
with the notion that in response to radiation cancer cells usually
activate G2 checkpoint to complete DNA repair.
Following irradiation G2 cell cycle arrest is regulated by activation
of ATM-CHK2 pathway that eventually induce the phosphorylation of
cyclin- dependent kinase like CDK1 (CDC2) on Tyr-15 by WEE1 kinase,
preventing CDK1 full activation and inhibiting G2/M transition^[102]31.
Accordingly, we found in T47D a higher radiation-dependent CDK1
phosphorylation that might explain the higher percentage of G2 arrested
cells in T47D respect to MDA-MB-231.
The tumor suppressor gene TP53 is a validated target of ATM that
phosphorylates p53 protein on Ser15^[103]32. This is an activating
phosphorylation that increases p53 transcriptional activity that
eventually participates in the establishment of the G2 checkpoint
following irradiation^[104]33. Accordingly, we found that in both T47D
and MDA-MB-231, p53-Ser15 is phosphorylated although with different
kinetics, which might reflect the different G2/M arrest observed in the
two cell lines. Of note, both T47D and MDA-MB-231 carried a mutated
TP53 that however could also sustain the radiation-induced G2
arrest^[105]34.
EGFR expression and phosphorylation has been associated with decreased
efficacy of radiotherapy not only in Head and Neck Squamous Carcinoma
but also in TNBC cells^[106]35,[107]36. In our study, the high
expression of phosphosho-EGFR was observed in MDA-MB-231, but not in
T47D cells supporting the possibility that the higher radiation
resistance of MDA-MB-231 could be at least partially due to EGFR
phosphorylation.
The different activation of signal transduction pathways was also
followed by a different expression of γH2AX and RAD51, whose persistent
expression has been linked to un-rejoined DSB and increased
radiosensitivity^[108]37.
Interestingly, the different biological and biochemical response of
MDA-MB-231 and T47D cells allowed us to identify miR-16 as a possible
important mediator of response to radiation.
Of course it is possible that other differentially expressed miRNA
(e.g. miR-23b-3p) could participate to the response to radiation. In
the available literature the role of miR-23b-3p in the response to
irradiation is still controversial and not investigated in breast
cancer^[109]38,[110]39, therefore it could be relevant to explore its
role in breast cancer response to RT in future studies.
The miR-16, which belongs to miR-15/miR-16 cluster, is the example of
highly conserved miRNAs able to regulate several important signaling
pathway like cell proliferation, apoptosis and cell cycle^[111]40. In
the context of breast cancer miR-16 has been reported to be down
regulated respect to normal breast tissues with the lowest expression
observed in highly metastatic breast cancer^[112]41,[113]42.
Yet, only few other reports have investigated the role of miR-16 in the
response to radiation, showing that it could promote the sensitivity to
radiation of non-small cell lung and breast cancer^[114]43,[115]44.
Moreover, miR-16 was also identified as the regulator of immune
response tumor microenvironment after radiation therapy^[116]45. In
this context it is plausible that miR-16 might mediate
radiation-induced G2 arrest by the targeting of cell cycle regulators
like WEE1 and/or CHEK1 that control the G2/M transition and are
validated miR-16 target genes. Intriguingly, by bioinformatics we also
observed that high miR-16 predicts good prognosis in breast cancer
patients.
This study has some limitations. First, although our bioinformatics
analyses indicated that miR-16-5p may also be involved directly in the
regulation of genes, those involved in radiation sensitivity include
CHEK1, CDC27, SMAD3, GADD45G we did not prove in wet lab experiments
that these genes are bona fide miR-16 targets in control and/or
irradiated cells. Similarly, we did not prove that miR-16-5p act as
radiosensitizer by modifying its expression in radioresistant and in
radiosensitive cells and therefore it is possible that the increased
expression of miR-16 in T47D cells after irradiation is only an
epiphenomenon and it does not have a causal role of the increased
radiosensitivity of these cells. We hope we will be able to better
investigate and clarify these points in future studies.
Despite these limitations, our work starting from the analyses of the
biological response of different breast cancer cell lines to radiation
leaded to the identification of miR-16-5p as radiation modified miRNA
and as biomarker of breast cancer patient’s prognosis, and possible
radiosensitivity. Future works on larger cohorts of breast cancer
patients are necessary to confirm this possibility.
Methods
Cell culture and radiation exposure
The breast cancer cell lines MDA-MB-231, T47D, and SKBR3 were grown in
Dulbecco’s Modified Eagle’s Medium (DMEM) (Gibco) and RPMI1640 (Roswell
Park Memorial Institute medium) (Gibco) containing 100 units/mL of
penicillin and 100 mg/mL of streptomycin, supplemented with 10% Fetal
Bovine Serum (FBS) (Gibco), and maintained in humidified 37 °C
incubator with 5% CO2. Cells were seeded at different density, and
incubated for 24 hours to reach 60–70% confluence for all experiments.
Then, cells were exposed to different doses of radiation 2, 4, 6, 8,
and 10 Gy, using Elekta Compact Linear Accelerator, with 6 MeV and dose
rate 2 Gy/ min. The medium was changed immediately after irradiation.
Cell viability assay
The MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide)
cell cytotoxicity assay was performed as previously described^[117]46.
Briefly, cells (8 × 10^3 cells/well) were cultured in 96-well plate,
24 hours before treatment. Cells were irradiated by different doses of
radiation (2 to 10 Gy). After incubation for 24, 48, 72 and 96 hours,
10 µl MTT (5 μg/ml) was added to each well followed by incubation for
3 hours. Next 100 µl DMSO was added to dissolve precipitation, and kept
at room temperature for 10 minutes with gentle shaking. Non-irradiated
cells were treated as same procedure. The absorbance was quantified by
microplate reader (BioTek Instruments, Inc., Winooski, VT, USA) at
540 nm. The viability was normalized to non- irradiated group.
Clonogenic assay
The breast cancer cells were seeded in 6-well plates and let to adhere
to the plates. Cells were exposed to different doses of radiation (2 to
10 Gy). Then cells were plated in triplicate in 6-well plate and
maintained at 37 °C and 5% CO[2] for 7–14 days. The cells were fixed
with 4% (v/v) paraformaldeide, and stained with 5% (w/v) crystal
violet. Colonies with more than approximately 50 cells were counted
manually, and clonogenic survival fraction (SF) was expressed as the
relative plating efficiencies of the irradiated cells to the control
cells. The linear-quadratic model (LQ model) was used to describe cell
survival fraction as the function of radiation dose. The survival
fraction was fitted into inverse exponential equation:
[MATH: SF=exp(−αD−βD2) :MATH]
In this equation, SF is surviving fraction of cells at dose D, and α
and β are two constants of linear and quadratic components of cell
killing^[118]28.
Cell cycle analysis
Cell cycle distribution was examined by Propidium Iodide (PI) staining
according to previous protocol^[119]47. Briefly, 2 × 10^5 cells were
seeded per well in 6-wells plates, and allowed to attach for 24 hours.
Plates were then exposed to different doses of radiation and the medium
was replaced immediately after irradiation. Irradiated cells were
collected 4 and 24 hours after irradiation by tryspinization. Cell
suspension was washed with ice-cold PBS twice, and fixed by adding 70%
(v/v) cold ethanol and under gentle agitation. The cells were then
maintained in 4 °C in the dark until used. Prior to staining, fixed
cell were washed twice in PBS, resuspended in PBS supplemented with
100 μg/mL RNase A, 50 μg/mL propidium iodide and 0.1% (v/v) Triton
X-100 and then incubated at 37 °C for 30 minutes, protected from light.
DNA content was quantified by measuring PI florescence signal versus
count, using FACSCalibur Flow Cytometer (BD, San Jose, CA, USA). The
percentage of cell in each phase of the cell cycle was analyzed using
the FACSDiva 7.0 software (BD Biosciences).
RNA extraction and sequencing
For RNA extraction, cells in exponential growth phase were subjected to
irradiation with a 2 Gy dose, replacing medium and incubated for
additional 24 hours. The total RNA was extracted using TRIzol total RNA
isolation reagent (Invitrogen)and Total RNA isolation kit (Norgen
Biotek Corporation, Canada) according to manufacturer’s instruction.
The concentration of RNA was more than 500 ng/µl for all samples with
an OD260/OD280 ratio equal to 2 and more, as quantified by NanoDrop
spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). The RNA
integrity was also checked by agarose gel electrophoresis. For small
RNA sequencing, total RNA was subjected to ligation 3′ and 5′ small RNA
adapters. Then, single strand cDNA was synthesized and amplified using
specific primers followed by purification and quantification. The small
RNA libraries were loaded on flow cell and then sequenced on Illumina
HiSeq2000 genome analyzer, using SBS (sequencing by synthesis) method
according to manufacturer’s instructions^[120]48–[121]50.
miRNA-Seq analysis pipeline
FASTQ files were groomed and subsequently FASTQC algorithm was applied
to check the presence and the type of adaptor contaminations within
FASTQ files. Trimming of FASTQ files were then carried out using Trim
Galore algorithm^[122]51 followed by running FASTQC^[123]52 to ensure
removing of adaptor contaminations. The transcriptome reference
sequence was downloaded from miRBase database, (Version 22). Mapping of
short reads on the reference transcriptome reference sequence were
performed applying HISAT2 algorithm^[124]53. Read counts for each
feature were calculated using Salmon algorithm^[125]54. Finally, DESeq2
were employed on the resulted read counts to get the list of
deregulated miRNAs. Applying the adjusted p-value ≤0.05 the most
significant up and down-regulated genes were selected for downstream
studies.
Western blot
To evaluate protein expression, western blot analysis was performed on
protein extract of cells, were exposed to 0.5 and 2 Gy radiation doses
at different time points. For cell lysate preparation, cells were
washed with cold PBS twice, collected in 100 µl cold RIPA lysis buffer
(50 mM Tris HCl pH 8, 1% Igepal, 0.5% sodium deoxycholate, 0.1% SDS),
containing protease inhibitor cocktail (Complete TM, Roche), 1 mM
Na3VO4 (Sigma), 100 mM NaF (Sigma) and 1 mM DTT (Sigma). Total protein
concentration was quantified by standard Bradford assay (Bio-Rad; CA,
USA). 25 to 40 μg of proteins were mixed with 5 µl of Laemmli sample
buffer and boiled at 95 °C for 5 minutes. The protein samples were then
loaded and separated using 4–20% SDS polyacrylamide precast gels
(Criterion Precast Gel, Bio-Rad). Proteins were transferred to
nitrocellulose membranes (GE Healthcare), and membrane blocked with 5%
Non-Fat Dried Milk (NFDM) in Tris Buffered Saline-Tween (TBS)
containing 0·1% Tween-20 (TBST) for 1 hour at room temperature (RT).
Blocked membranes were incubated overnight at 4 °C using the following
primary antibodies: phospho-ATM (Ser1981) (1:1000, #13050),
phospho-EGFR (Tyr1068) (1:1000, #3777), phospho- p53(Ser15) (1:500,
#9284), phospho- cdc2(Tyr 15)(1:1000, #9111), Rad51 (D4B10)(1:1000
#8875) were from Cell Signaling Technology, γH2AX(Ser139)(1:1000) and
GAPDH (6C5 CB1001, 1:1000) were from Millipore, and goat polyclonal
antibody against vinculin (1:5000, sc-7649 clone N-19) was from Santa
Cruz Biotechnology.
After incubation with the primary antibodies membranes were washed in
TBST (x3), and incubated with secondary antibodies at RT for 1 hour.
The Horseradish peroxidase-conjugated goat anti-mouse and goat
anti-rabbit antibodies (Rockland) were prepared in 5% NFDM in TBST at
the concentration of 1:2000. The fluorophores-conjugated antibody
(AlexaFluor 680, Invitrogen or IRDye 800, Rockland) was diluted 1:1500
in Odyssey Blocking Buffer (LI-COR, Biosciences). Finally, proteins
expression were detected by Enhanced Chemi -Luminescence (ECL) system
or Odyssey Imaging scanner (LI-COR), as appropriate. To evaluate the
quantity and quality of loaded proteins, we used Vinculin and GAPDH as
loading controls. The membranes were stripped using the Re-blot Plus
Strong Solution 10×(Millipore) diluted 1:10 in ionized water for
10 minutes at room temperature. After washing three times in TBST, the
membranes were reblot as described above.
Quantitative real-time PCR (qRT-PCR)
Total RNA from 2 Gy irradiated breast cancer cells was extracted using
TRIzol (Invitrogen) 24 hours after irradiation, then quantified and
diluted to reach the concentration of 50 nanogram per each µliter. The
concentration of RNA was measured by NanoDrop 3300 spectrometer (Thermo
Scientific, Waltham, MA, US). The cDNA was produced by TaqMan MicroRNA
Reverse Transcription Kit (Applied Biosystem) as previously
described^[126]55. Following cDNA dilution, qRT–PCR was carried out
using TaqMan microRNA assay kit (Applied Biosystems) using the CFX96
Thermocycler (Bio-Rad, USA). U6 (RNU6-1) snRNA was used to normalize
miRNAs expression.
miRNAs target prediction and pathway enrichment analysis
The target prediction of differentially expressed miRNA was performed
using TargetScan 7.2 bioinformatics software tool
([127]http://www.targetscan.org/vert_72/)^[128]56. The predicted genes
were selected by setting the threshold based on the total context
score ≤ −0.4. Then the genes information were uploaded to Enrichr
online database ([129]https://amp.pharm.mssm.edu/Enrichr/) to predict
target related pathways throughout Gene Ontology (GO) analysis tool and
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway^[130]57,[131]58.
We specifically focused on targets involved in DNA repair, cell cycle
and apoptosis regulation.
Statistical analysis
Statistical analyses were performed using GraphPad PRISM, Version 8
(GraphPad Software Inc. CA) and the difference with p-value below 0.05
was considered significant. The radiobiological parameters of cell
survival curve were also measured by GraphPad prism.
The LD50 values were estimated using the equation of first order
polynomial non-linear regression. Western blot images were analyzed
using ImageLab analysis software, Version 6 (Bio-Rad, Hercules, CA).
Kaplan-Meier survival curves were generated using the KM Plotter online
tool ([132]http://kmplot.com)^[133]59, using the most appropriate cut
off choice. KM Plotter is an online algorithm exploitable to
interrogate the expression of up to 1052 miRNAs on up to 1,262
(METABRIC dataset) or 1061 breast cancer patients (TCGA dataset) with a
mean follow-up of 94 (METABRIC dataset) or 25 months (TCGA dataset), as
described previously^[134]60,[135]61.
Supplementary information
[136]Supplementary information.^ (1.1MB, docx)
Acknowledgements