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Stem cell-like gene expression signature identified in ionizing radiation-treated cancer cells
Stem cell-like gene expression signature identified in ionizing radiationtreated cancer cells Jin-Han Bae, So-Hyun Park, Ju Hwan Yang, Kwangmo Yang, Joo Mi Yi PII: DOI: Reference:
S0378-1119(15)00948-8 doi: 10.1016/j.gene.2015.08.005 GENE 40751
To appear in:
Gene
Received date: Revised date: Accepted date:
1 July 2015 30 July 2015 4 August 2015
Please cite this article as: Bae, Jin-Han, Park, So-Hyun, Yang, Ju Hwan, Yang, Kwangmo, Yi, Joo Mi, Stem cell-like gene expression signature identified in ionizing radiation-treated cancer cells, Gene (2015), doi: 10.1016/j.gene.2015.08.005
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Stem cell-like gene expression signature identified
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in ionizing radiation-treated cancer cells
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Jin-Han Bae1,*, So-Hyun Park2,*, Ju Hwan Yang1, Kwangmo Yang1, §, and Joo Mi Yi1,§
1
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Research Center, Dongnam Institute of Radiological & Medical Sciences (DIRAMS), Busan,
South Korea, 619-953 2
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Department of Biological Science, Pusan National University, Busan, South Korea, 609-735
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*These authors contributed equally to this work
§
Joo Mi Yi, PhD
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Correspondence should be addressed to:
Email: [email protected]
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Research Center
Dongnam Institute of Radiological & Medical Sciences (DIRAMS), Busan, 619-953, South Korea TEL: +82-51-720-5139 FAX: +82-51-720-5929
Kwangmo Yang, M.D. Ph.D. Email: [email protected] Department of Radiation Oncology Dongnam Institute of Radiological & Medical Sciences (DIRAMS) Busan, 619-953, South Korea TEL: +82-51-720-6010 FAX: +82-51-720-5929
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ACCEPTED MANUSCRIPT Abstract
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Recent studies have reported that embryonic stem (ES) cell-associated gene expression
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signatures have been identified in poorly differentiated tumors, revealing a link between ES
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cell identity and cancer cells. Cancer cells originate from cancer stem cells (CSCs). Both types of cells share common properties such as self-renewal and heterogeneity. CSCs are also resistant to conventional chemotherapy and radiotherapy. Here, we show similar gene
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expression patterns between ES cells and ionizing radiation (IR)-treated cancer cells. Using genome-wide transcriptome analysis, we compared the gene expression profiles among ES
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cells, cancer cells, and irradiated cancer cells, and identified a subset of similar gene expression patterns between ES cells and irradiated cancer cells, indicated by hierarchical
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clustering. These gene expression patterns were then confirmed by quantitative real-time
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reverse transcription polymerase chain reaction (qRT-PCR) analyses. Using bioinformatic
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analyses, these candidate genes are also associated with various biological pathways related to stemness in cancer. Taken together, our data suggest that identification of common molecular characteristics between ES cells and irradiated cancer cells is important
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to understand the properties of cancer stem cells and their resistance to radiotherapy.
Abbreviations
ES cell, embryonic stem cell; CSCs, cancer stem cells; IR, ionizing radiation; RT-PCR, reverse transcription polymerase chain reaction; Cy3, cyanine 3; Cy5, cyanine 5; GO, gene ontology; Gy, gray; qRT-PCR, quantitative real-time RT-PCR; SD, standard deviation
Keywords Embryonic stem (ES) cell; Cancer stem cells; Ionizing radiation; Expression microarray
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ACCEPTED MANUSCRIPT 1. Introduction
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Radiation therapy is frequently used as a standard treatment for different types of
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cancer. Ionizing radiation (IR) has been used clinically for cancer treatment, because the
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exposure to high doses of gamma IR causes severe DNA damage that can lead to apoptosis of cancer cells. There is growing evidence that IR causes an increase in the cancer stem cell population, and can affect the stemness characteristics of cancer cells, resulting in
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maintenance of stem-like populations with a higher resistance to radiotherapy. However, molecular mechanisms underlying radiation resistance in cancer cells remain poorly These
mechanisms
characterization.
are
complex
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understood.
and
require
more
comprehensive
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Cancer stem cells (CSCs), a subpopulation of malignant cells in the heterogenous
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cancer cell population, are considered to be responsible for cancer recurrence, metastasis,
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and drug resistance. CSCs have been isolated from a variety of human malignancies, including leukemia (Lapidot et al., 1994 and Bonnet and Dick, 1997), breast cancer (Al-Hajj et al., 2003 and Liu et al., 2005), brain tumors (Singh et al., 2004), and colorectal cancer
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(O'Brien et al., 2007 and Ricci-Vitiani et al., 2007). CSCs have the ability to self-renew and to differentiate into a multitude of cells that comprise the bulk of the tumor mass (Reya et al., 2001). CSCs also express high levels of drug resistant transporter proteins (e.g., ABC proteins) (Gottesman et al., 2002 and Haraguchi et al., 2010), DNA repair enzymes (Martin et al., 2008 and Zhang et al., 2010), and anti-apoptotic proteins (Liu et al., 2006 and Madjd et al., 2009), which make them highly resistant to conventional cancer therapies, including chemotherapy and radiotherapy. In addition, CSCs may be intimately involved in both intrinsic and acquired tumor resistance to anticancer treatments, including radiation therapy. Embryonic stem (ES) cells are of great interest as a model system for studying early developmental processes, and because of their potential therapeutic applications in 3
ACCEPTED MANUSCRIPT regenerative medicine. Stem cells and cancer cells share common properties, including selfrenewal and a block in differentiation. Recently, several groups have reported that
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expression signatures that are specific to ES cells are also found in many human cancers,
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suggesting that these shared features might be the targets of new approaches for cancer
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therapy. Previous reports suggested that a subset of ES cell-associated gene expressions at the transcriptional level can contribute to stem cell-like phenotypes in many tumors (BenPorath et al., 2008). Recently, there is growing evidence that radiation can induce stem-like
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characteristics in cancer cells (Ghisolfi et al., 2012). Based upon these observations, the present study sought to determine if irradiated cancer cells might share the stem-like gene
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expression signatures, which may help identify the mechanisms of regulation of cancer stem cells, and lead to treatments that can regulate the resistance of cancer cells to radiotherapy.
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We used the genome-wide transcriptome approach to identify the gene expression
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signatures shared with ES cells and irradiated cancer cells, and found overlapping gene expression characteristics between these cells. These genes were also associated with
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important cancer or stemness signaling pathways. Together, the results suggest that these gene expression signatures might be important subsets in the maintenance of stem-like
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populations in irradiated cancer cells involved in radiation resistance.
2. Materials and Methods
2.1. Gene expression microarray analysis
Total RNA of human embryonic stem cell (hESC) was purchased from CELPROGEN (Torrance, CA, USA).
Total RNA was extracted from control and irradiated cells using
TRIzol® reagent (Invitrogen, Carlsbad, CA, USA), and the integrity of the isolated total RNA 4
ACCEPTED MANUSCRIPT was measured with an Agilent Bioanalyzer 2100 RNA Nano kit (Agilent Technologies, Palo Alto, CA, USA). Synthesis of target cRNA probes and hybridization were performed using
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Agilent’s Low RNA Input Linear Amplification kit (Agilent Technologies) according to the
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manufacturer’s instructions. Briefly, each 1 μg of total RNA and T7 promoter primer mix were
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combined and incubated at 65ºC for 10 min. The cDNA master mix (5× first strand buffer; 0.1 M DTT, 10 mM dNTP mix, RNase-Out, and MMLV-RT) was prepared and added to RNA and the primer mixture. The samples were incubated at 40ºC for 2 hours for reverse transcription
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and double-stranded cDNA (dsDNA) synthesis, then terminated by incubating at 65ºC for 15 min. The transcription master mix was prepared according to the manufacturer’s protocol (4×
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transcription buffer, 0.1 M DTT, NTP mix, 50% PEG, RNase-Out, inorganic pyrophosphatase, T7-RNA polymerase, and cyanine 3/5-CTP) and added to the dsDNA reaction mixture, and
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incubated at 40ºC for 2 hours for transcription of dsDNA. During transcription-amplification,
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control and test cRNAs were labeled with Cy3-CTP and Cy5-CTP, respectively. Amplified and labeled cRNA were purified and quantified using an ND-1000 spectrophotometer
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(NanoDrop Technologies, Inc., Wilmington, DE, USA) to check labeling efficiency, followed by fragmentation of cRNA by adding 10× blocking agent and 25× fragmentation buffer, then
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incubating at 60ºC for 30 min. The fragmented cRNA was resuspended with 2× hybridization buffer and directly pipetted onto assembled Agilent Technologies human whole genome oligonucleotide microarrays (60K, Agilent Technologies) and placed in a hybridization chamber (Agilent Technologies). By incubating the hybridization chamber at 42ºC for 16 hours with mild agitation, competitive hybridization reactions occurred between labeled targets and probes on the microarray. To eliminate nonspecific binding, hybridized microarrays were washed with Agilent’s Gene Expression Wash Buffer kit (Agilent Technologies). Finally, microarrays were spin-dried and stored in the dark until scanned.
2.2. Microarray data acquisition and analysis
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ACCEPTED MANUSCRIPT Hybridized microarrays were scanned using a DNA microarray scanner and quantified with feature extraction software (Agilent Technologies). All data normalization and statistical
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change analyses were performed using GeneSpring GX 7.3 (Agilent Technologies). Data
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normalization was performed as follows: data transformation, set measurements 0.01 to
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0.01; per chip, normalized to the fiftieth percentile; per gene, normalize to the median. To identify differentially expressed genes, 2-fold change analysis and the statistical t-test (P < 0.05, no multiple testing corrections, no parametric test) were performed. Analyzed genes functionally
annotated
according
to
the
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were
gene
ontology
(GO) consortium
(http://www.geneontology.org). In addition, analyzed genes were functionally classified
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based on DAVID bioinformatics (http://david.abcc.ncifcrf.gov) by uploading target gene lists
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2.3. Cell culture and irradiation
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and using the “Functional Annotation Clustering” menu (Huang da et al., 2009).
Human colorectal carcinoma cell lines (HCT116 and SW480) and the breast cancer cell line MCF7 were obtained from the ATCC (Manassas, VA, USA). HCT116 and SW480 were
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cultured in McCoy’s 5A medium (WelGENE, Daegu-si, Korea), and MCF7 cells were cultured in DMEM medium (WelGENE). All cell culture media were supplemented with 10% fetal bovine serum (Hyclone, Logan, UT, USA) and 1% antibiotic-antimycotic solution (Gibco, Grand Island, NY, USA). All cell lines were incubated at 37ºC, with 20% O2 and 5% CO2. Cells were exposed to a total of 10 Gy gamma radiation through the blood mode after changing to fresh media. All irradiations were performed using a
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Ziegler, Berlin, Germany) at a dose rate of 2.6 Gy/min.
2.4. cDNA synthesis and quantitative real-time RT-PCR (qRT-PCR)
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Cs ray source (Eckert &
ACCEPTED MANUSCRIPT Cultured cells were trypsinized and homogenized using a QIAshredder kit (QIAGEN, GmbH, Hilen, Germany). Total RNA from cells was extracted using an RNeasy mini kit
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(QIAGEN). The amount of RNA was measured using a NanoDrop 2000/2000c instrument
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(Thermo Scientific, Rockford, IL, USA). For cDNA synthesis, 1 μg of total mRNA was reverse
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transcribed into cDNA using the iScriptTM cDNA Synthesis kit (BioRad, Hercules, CA, USA). The reactions were performed at 25ºC for 5 min, 42ºC for 30 min, and terminated by heating to 85ºC for 5 min.
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Transcripts of target genes were analyzed by the SYBR Master Mix (Thermo Scientific) using qRT-PCR with a CFX96TM real-time system (BioRad). For the development of specific
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primers for the candidate genes, all primers were designed using the Primer3 (http://bioinfo.ut.ee/primer3/) and the UCSC genome browser (http://www.genome.ucsc.edu/)
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(Supplementary Table 2). For normalization, human GAPDH was amplified. All relative
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quantifications of expressions were calculated using the ΔΔCt method.
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2.5. Signaling pathway analysis
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of
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Functions and signaling pathways of candidate genes were investigated from the top super-pathway
categories
within
(http://www.genecards.org/cgi-bin),
that
the
GeneCard
database
included
KEGG
(http://www.kegg.jp/kegg/pathway.html). Gene ontology was analyzed using the GOrilla web tool (http://cbl-gorilla.cs.technion.ac.il), and the P-value threshold was limited to 10-3.
2.6. Statistical analysis
Quantified data are expressed as the mean ± standard deviation (SD). Testing of significance performed using the Student's t-test. A P-value of less than 0.05 was considered significant. 7
ACCEPTED MANUSCRIPT 3. Results
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3.1. Gene expression pattern of ES cells, cancer cells, and irradiated cancer cells
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It has been reported that tumors can recur when they are associated with radio resistance, and evidence suggests that radiation resistant breast cancer stem/progenitor cells are enriched after radiation (Debeb et al., 2009). Because increasing evidence supports
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the existence of radiation and chemotherapy resistant cancer stem cells or tumor initiating cells, we hypothesized that ES cells and irradiated cancer cells might share the gene
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expression signature which was responsible for their resistance to radiation. We also reasoned that genome-wide gene expression analyses would be more revealing than single-
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gene analyses (Segal et al., 2005 and Rhodes et al., 2007).
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We first compared the gene expression patterns among ES cells, cancer cells (HCT116,
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SW480, and MCF7), and irradiated cancer cells using a genome-wide expression arraybased approach. A gene expression profile was used to collect gene sets that represented shared gene expression signatures between ES cells and irradiated cancer cells. Global
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normalization was applied for gene expression analyses. To find similar patterns of gene expression between ES cells and irradiated cancer cells, probes were identified that showed a relative 2-fold downregulation (2,619 probes) among ES cells and three irradiated cancer cell datasets. Probes showing 2-fold upregulation (2,894 probes) were used in control cancer cells to find differential gene expression patterns, when compared with ES cells and irradiated cancer cells. Finally, we directly compared with two different datasets and identified 30 probes (24 genes) that overlapped (Supplementary Table1). We found that these 24 genes displayed similar gene expression levels in ES cells and irradiated cancer cells, but not in control cancer cells showing 2-fold up- or downregulation (Fig. 1).
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ACCEPTED MANUSCRIPT 3.2. The relationships between gene expression profiles from ES cells, cancer cells, and
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irradiated cancer cells
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To identify the common gene signature, we wondered how these gene expression
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patterns were related to ES cells, cancer cells, and irradiated cancer cells. Heat maps for 2,619 probes and 2,894 probes indicated a general gene expression signature between ES cells and irradiated cancer cells. As mentioned above, Importantly, thirty probes (24 genes)
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whose gene expression profiles overlapped between these two different datasets showed two significant groups between the ES cells, along with irradiated cancer cells and mock-
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treated cancer cells using hierarchical clustering analyses (MCF7, HCT116, and SW480) (Fig. 2A). This data strongly suggested that the gene expression patterns of these 30 probes
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might be shared between the ES cells and the irradiated cancer cells. Fig. 2B confirms that
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the 30 probes were preferentially over- or underexpressed in control cancer cells, but usually showed similar gene expression patterns in ES cells or irradiated cancer cells (Fig. 2B, left The
30
probes
included
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panel).
24
genes,
except
for
uncharacterized
genes
(LOC100505821, LOC100507547, LOC728431, and XLOC013282) and small nucleolar
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RNAs (SNORA11 and SNORD60). We searched past studies of 24 genes, to identify the biological significance of these genes in normal and cancer cells (Table 1). We then hypothesized that these gene sets might be ES expression signatures shared with irradiated cancer cells. The actual gene expression levels of these gene sets from microarrays indicated they were very similar between ES cells and irradiated cancer cells, but were preferentially up- or downregulated in control cancer cells (Fig. 2B, right panel)
3.3. Validation of common gene signature in ES cell, cancer cells, and irradiated cancer cells
To validate the microarray data, we examined whether these 30 probes (24 genes) showed the same actual gene expression levels among ES cells, cancer cells, and irradiated 9
ACCEPTED MANUSCRIPT cancer cells. Using RT-PCR, specific primers were designed for the 24 genes, to check mRNA levels and to analyze whether the gene expression patterns were consistent with the
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microarray data. Sixteen genes were validated among the 24 genes, based on gene
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expression levels from the microarray data. Fig. 3 shows that most of the genes exhibited
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low or lack of gene expression levels in ES cells. Notably, their gene expression levels significantly decreased after IR treatment of cancer cells, as compared to controls. These sixteen genes usually showed low or lack of gene expression in ES cells compare with
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cancer cells, but after IR treatment to cancer cells, these genes tended to have a similar gene expression pattern as ES cells. Taken together, the results are consistent with our
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hypothesis that ES cells and irradiated cancer cells share some gene expression patterns.
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3.4. Implications of the signaling network for ES cell-like gene signatures
Although there was a small subset of ES cell-like gene expressions in irradiated cancer
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cells, we wanted to determine whether these genes were associated with a particular cellular pathway or network. Twenty-four genes were analyzed using well-curated databases (GO,
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GeneMANIA, and KEGG) that included a variety of biological processes, molecular functions, and cellular components (Supplementary Table 3). The possible roles of the candidate genes were hypothesized by inspecting the various signaling pathways predicted by KEGG pathway analysis (Table 1). In addition, several genes (CHRD, ID2, LAMB2, MINA, NF1, and POLR2B) were associated with stem cell regulatory pathways such as TGF-beta signaling, WNT/Hedgehog/Notch signaling for stem cell proliferation and differentiation, and ERK or MAPK signaling for regulation of stem cell proliferation (Fig. 4). These results suggested that expression profiles shared between ES cells and irradiated cancer cells play biological roles in radiation and cellular pathways involved in stemness for cancer.
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ACCEPTED MANUSCRIPT 4. Discussion
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Cancers arise from a cancer stem cell that is capable of self-renewal and tumor
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heterogeneity. The frequency of cancer stem cells is still controversial, depending on the
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technique used to detect the cells and the type of cancer (Visvader and Lindeman, 2008). It has been suggested that ES cells and cancer cells share overlapping molecular characteristics, so many studies have tried to identify the gene expression patterns that
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comprise these similarities. A study reported that the ES cell-like module is activated in various human epithelial cancers (Wong et al., 2008). Recently, a subset of ES cell-
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associated transcription regulators have been identified that are highly expressed in poorly differentiated tumors, revealing a link between genes associated with ES cell identity and the
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histopathology of tumors (Ben-Porath et al., 2008). These studies have reported that cancer
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cells overlap with molecular target signatures of ES cells, such as active core factors (Nanog,
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Oct4, and Sox2), polycomb complex (PRC), and Myc. These studies also provided additional evidence that common pathways could be utilized, both in stem/progenitors and in cancers. CSCs are thought to represent a small subpopulation of cells present in most tumors,
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similar to normal tissue stem cells, but with the ability to self-renew and differentiate into different cancer subtypes (Jordan et al., 2006). These CSC characteristics are responsible for their abilities to initiate and sustain tumors (Reya et al., 2001 and Visvader and Lindeman, 2008). Moreover, CSCs are also believed to play a key role in cancer metastasis, cancer recurrence, and cancer drug resistance (Clarke and Fuller, 2006 and Martin et al., 2008). It has been reported that exposure of cells to IR can result in genome instability and adaptive responses that have the potential to induce gene expression, chromosomal rearrangement, posttranslational modifications, and epigenetic changes that initiate carcinogenesis. The changes induced by IR exposure might lead to resistance to radiation therapy, both in vitro and in vivo. Recently, many studies have reported that CSCs are more resistant to radiation 11
ACCEPTED MANUSCRIPT than other cancer cells (Bao et al., 2006, Phillips et al., 2006, Pajonk et al., 2010 and Kim et al., 2011). In addition, several studies reported that sublethal radiation could promote
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expansion of the cancer stem cell population, resulting in a small population of cells that are
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resistant to conventional cancer therapies, including radiotherapy (Suh and Lee, 2015).
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Although molecular targets or signatures associated with these phenomena and mechanisms are not well understood, emerging evidence has suggested that radiation can contribute to expansion of a cancer stem cell population that is highly tumorigenic.
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Using a genome-wide transcriptome approach, we showed in the present study that cancer cells induced by ionizing radiation share molecular gene expression signatures with
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ES cells. We identified similar gene expression levels between ES cells and irradiated cancer cells, accompanied by increasing or decreasing expression levels in cancer cells.
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Twenty-four genes were clustered in ES cells and IR-exposed cancer cells, suggesting that
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these gene expression signatures were shared between the two types of cells. Importantly, these genes were associated with important signaling pathways involved in cancer and stem
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cell proliferation. MINA, LAMB2, and NF1 genes were especially associated with regulation of stem cell proliferations. Therefore, we searched past studies to identify their biological
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functions.
MINA (MYC-induced nuclear antigen) is a c-MYC target gene that may play a role in cell proliferation or regulation of cell growth (Tsuneoka et al., 2002 and Zhang et al., 2005). Lack of the MINA protein caused a significant decrease in Hela cell numbers and A549 proliferation. Recently, it was reported that c-MYC activates an embryonic stem cell-like response in epithelial cells, leading to epithelial cancer stem cell development (Wong et al., 2008). However, we have checked the Myc target genes in our datasets (Ji et al., 2011), but we could not identify a biological relationship between ES cell and irradiated cancer cell datasets (data not shown). LAMB2 (laminin, beta-2) has been reported to bind directly to calcium channels that are required for neurotransmitter release from motor nerve terminals (Nishimune et al., 2004). However, there is little information regarding the biological function 12
ACCEPTED MANUSCRIPT of the LAMB2 gene in cancer or ES cell development. NF1 (neurofibromin 1) has been reported to be a cytoplasmic protein that is
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predominantly expressed in neurons, Schwann cells, oligodendrocytes, and leukocytes. It
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has also been identified as a tumor suppressor gene, and is able to regulate several proteins
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and/or intracellular processes, including RAS, the cyclic AMP pathway, the ERK and MAP kinase cascades, adenylyl cyclase, and cytoskeletal assembly (Trovo-Marqui and Tajara, 2006). Recent evidence has suggested that enriched cancer stem cells are relatively
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radioresistant. In addition, little is known about the relationships of these genes with the radiation response in cancer cells that contribute to expansion of the cancer stem cell
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population. By comparing gene expression profiles in ES cells, cancer cells, and irradiated cancer cells, our results suggested that these genes are important in understanding the
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molecular imprints of stemness. In the present study, we identified common gene expression
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signatures between ES cells and irradiated cancer cells, which suggest that these genes are associated with molecular characteristics of cancer stem cells that contribute to their
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resistance to radiotherapy.
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Acknowledgements
This study was supported by a National Research Foundation of Korea (DIRAMS) grant funded by the Korea government (MSIP) (50591-2015). We would like to thank Khadijah Mitchell at National Cancer Institute (NCI) for critical reading of the manuscript and providing language help.
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(10.1038/nature05372). Pajonk, F., Vlashi, E. and McBride, W.H., 2010. Radiation resistance of cancer stem cells: the 4 R's of radiobiology revisited. Stem Cells 28 (4), 639 648 (10.1002/stem.318). Phillips, T.M., McBride, W.H. and Pajonk, F., 2006. The response of CD24(-/low)/CD44+ breast cancer-initiating cells to radiation. J Natl Cancer Inst 98 (24), 1777-85. (10.1093/jnci/djj495). Reya, T., Morrison, S.J., Clarke, M.F. and Weissman, I.L., 2001. Stem cells, cancer, and cancer stem cells. Nature 414 (6859), 105 111 (10.1038/35102167). Rhodes, D.R., Kalyana-Sundaram, S., Tomlins, S.A., Mahavisno, V., Kasper, N., Varambally, R., Barrette, T.R., Ghosh, D., Varambally, S. and Chinnaiyan, A.M., 2007. Molecular concepts analysis links tumors, pathways, mechanisms, and drugs. Neoplasia 9 (5), 443 454. Ricci-Vitiani, L., Lombardi, D.G., Pilozzi, E., Biffoni, M., Todaro, M., Peschle, C. and De Maria, R., 2007. Identification and expansion of human colon-cancer-initiating cells. Nature 445 (7123), 111 115 (10.1038/nature05384). Segal, E., Friedman, N., Kaminski, N., Regev, A. and Koller, D., 2005. From signatures to models: understanding cancer using microarrays. Nat. Genet. 37 Suppl, S38-45 (10.1038/ng1561). Singh, S.K., Hawkins, C., Clarke, I.D., Squire, J.A., Bayani, J., Hide, T., Henkelman, R.M., Cusimano, M.D. and Dirks, P.B., 2004. Identification of human brain tumour initiating cells. Nature 432 (7015), 396 401 (10.1038/nature03128). Suh, Y. and Lee, S.J., 2015. Radiation treatment and cancer stem cells. Arch. Pharm. Res. 38 (3), 408 413 (10.1007/s12272-015-0563-1). Trovo-Marqui, A.B. and Tajara, E.H., 2006. Neurofibromin: a general outlook. Clin. Genet. 70 (1), 113 (10.1111/j.1399-0004.2006.00639.x). Tsuneoka, M., Koda, Y., Soejima, M., Teye, K. and Kimura, H., 2002. A novel myc target gene, mina53, that is involved in cell proliferation. J. Biol. Chem. 277 (38), 35450 35459 (10.1074/jbc.M204458200). Visvader, J.E. and Lindeman, G.J., 2008. Cancer stem cells in solid tumours: accumulating evidence and unresolved questions. Nat. Rev. Cancer 8 (10), 755 768 (10.1038/nrc2499). Wong, D.J., Liu, H., Ridky, T.W., Cassarino, D., Segal, E. and Chang, H.Y., 2008. Module map of stem cell genes guides creation of epithelial cancer stem cells. Cell Stem Cell 2 (4), 333 344 (10.1016/j.stem.2008.02.009). Zhang, M., Atkinson, R.L. and Rosen, J.M., 2010. Selective targeting of radiation-resistant tumorinitiating cells. Proc. Natl. Acad. Sci. USA 107 (8), 3522 35227 (10.1073/pnas.0910179107). Zhang, Y., Lu, Y., Yuan, B.Z., Castranova, V., Shi, X., Stauffer, J.L., Demers, L.M. and Chen, F., 2005. The Human mineral dust-induced gene, mdig, is a cell growth regulating gene associated with lung cancer. Oncogene 24 (31), 4873 4882 (10.1038/sj.onc.1208668).
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ACCEPTED MANUSCRIPT Figure legends
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Fig. 1. Schematic overview of the screening approach using the Gene Expression
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microarray platform.
Fig. 2. Identification of stem cell-like gene expression signatures in irradiated cancer cells. (A) The upper Venn diagram shows 2,589 (2-fold upregulated) and 2,618 (2-fold
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downregulated) probes from the microarray data set. Hierarchical clustering analyses of gene expression data from microarray profiles in embryonic stem (ES) cells, control cancer
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cells, and irradiated cancer cell are shown. Green indicates reduced expression. Cluster analyses placed a group of these probes in the upper category. Thirty probes (24 genes)
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overlapped between the two different gene expression profile sets. The heat map shows 24
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gene expression values along with clustering analyses. Red and green in cells denote
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relative high or low expression levels, respectively, which are defined in the “Color Key” scale bar. (B) Gene expression pattern of 30 probes from the microarray data. Box plots display differential gene expression levels in ES cells, cancer cells, and irradiated cancer
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cells.
Fig. 3. qRT-PCR analysis of gene expression levels in ES cells, cancer cells, and irradiated cancer cells. Correlations between microarray data and qRT-PCR analyses results for gene expression levels in ES cells, cancer cells, and irradiated cancer cells. Representative genes show validation using qRT-PCR analyses from the microarray data. Bar graphs show gene expression levels and IR indicates the 10 Gy used to treat the cancer cells. * indicates significant decrease in ES and IR (*P<0.05).
Fig. 4. Biological implications of stem cell related genes. Some of our candidate genes 16
ACCEPTED MANUSCRIPT are related to stem-like signaling pathways in cancer. CHRD and NF1 regulate cancer stem cell proliferation. ID2 induces cell growth reduction by inhibition of DNA binding. c-Myc is a
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stemness factor, and ID2 and MINA regulate transcriptional activations in stem cells. The
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roles of LAMB2 and POLR2B have not been identified in stem cells. However, abnormal
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functioning of the ERK pathway, DNA repair, and mRNA splicing can affect stem-like
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Table 1. Information and signaling pathway of target genes. Accession No.
Description ATP-Binding Cassette, Sub-Family D (ALD), Member 3
Signaling pathway ABC-family proteins mediated transport; Transport of glucose and other sugars, bile salts and organic acids, metal ions and amine compounds; Peroxisome; Nuclear receptors in lipid metabolism and toxicity Synthesis and Degradation of Ketone Bodies; superpathway of cholesterol biosynthesis; Metabolism; Acetyl-CoA Acetyltransferase 1 Valirne, leucine and isoleucine degradation; Fatty acid, triacylglycerol, and ketone body metabolism Superpathway of cholesterol biosynthesis; Valine, leucine and isoleucine degradation; tryptophan utilization Acetyl-CoA Acetyltransferase 2 II; Fatty acid metabolism; Butanoate metabolism Cyclin J -Chordin Signaling by BMP; TGF-beta signaling pathway Deleted In Primary Ciliary Dyskinesia Homolog -Energy Homeostasis Associated -Immune response Fc epsilon RI pathway; PI-3K cascade; Signaling by GPCR; Development Slit-Robo Fer (Fps/Fes Related) Tyrosine Kinase signaling; Sertoli-Sertoli Cell Junction Dynamics Global Genomic NER (GG-NER); Assembly of RNA Polymerase-II Initiation Complex; Viral GTF2H2 Family Member C, Copy 2 carcinogenesis Inhibitor of DNA Binding 2, Dominant Negative Wnt / Hedgehog / Notch; Validated targets of C-MYC transcriptional repression; Validated targets of CHelix-Loop-Helix Protein MYC transcriptional activation; Transcriptional misregulation in cancer; TGF-beta signaling pathway Integral Membrane Protein 2B RNA Polymerase I Promoter Opening; Disease Focal adhesion; Integrin Pathway; ERK Signaling; Phospholipase-C Pathway; Non-integrin membrane-ECM Laminin, Beta 2 (Laminin S) interactions Leucine-Rich Repeats And IQ Motif Containing 3 -MYC Induced Nuclear Antigen Validated targets of C-MYC transcriptional activation MAPK signaling pathway; G-protein signaling M-RAS regulation pathway; Development VEGF signaling Neurofibromin 1 via VEGFR2 - generic cascades; ERK Signaling; Ras signaling pathway Pyridoxal (Pyridoxine, Vitamin B6) Phosphatase Metabolism; Vitamin B6 metabolism; Phosphatases; Cytoskeletal Signaling Circadian rhythm; Circadian Clock; Circadian entrainment; Influenza A; Metabolic States and Circadian Period Circadian Clock 1 Oscillators Polymerase (RNA) II (DNA Directed) Polypeptide B, Formation of RNA Pol II elongation complex; Purine metabolism; DNA Repair; mRNA Splicing - Major 140kDa Pathway; Assembly of RNA Polymerase-II Initiation Complex Ring Finger Protein 126 -Ribosomal Protein L22-Like 1 CFTR translational fidelity (class I mutations) Arginine/Serine-Rich Protein 1 -Trichohyalin --
ABCD3
NM_001122674
ACAT1
NM_000019
ACAT2
NM_005891
CCNJ CHRD DPCD ENHO
NM_019084 NM_003741 NM_015448 NM_198573
FER
NM_005246
GTF2H2D
NM_001042490
ID2
NM_002166
ITM2B
NM_021999
LAMB2
NM_002292
LRRIQ3 MINA
NM_001105659 NM_032778
NF1
NM_000267
PDXP
NM_020315
PER1
NM_002616
POLR2B
NM_000938
RNF126 RPL22L1 RSRP1 TCHH
NM_194460 NM_001099645 NM_020317 NM_007113
TCOF1
NM_001008657
Treacher Collins-Franceschetti Syndrome 1
Ribosome biogenesis in eukaryotes
TTC3
NM_003316
Tetratricopeptide Repeat Domain 3
--
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CR
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Highlights Comparision between gene expression profile between ES cells and irradiated cancer cells We identified stem cell like gene expression signature in irradiated cancer cells. Irradiated cancer cells might have stem-like characteristics for cancer stem cells at the molecular level.
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S0378-1119(15)00948-8 doi: 10.1016/j.gene.2015.08.005 GENE 40751
To appear in:
Gene
Received date: Revised date: Accepted date:
1 July 2015 30 July 2015 4 August 2015
Please cite this article as: Bae, Jin-Han, Park, So-Hyun, Yang, Ju Hwan, Yang, Kwangmo, Yi, Joo Mi, Stem cell-like gene expression signature identified in ionizing radiation-treated cancer cells, Gene (2015), doi: 10.1016/j.gene.2015.08.005
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Stem cell-like gene expression signature identified
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in ionizing radiation-treated cancer cells
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Jin-Han Bae1,*, So-Hyun Park2,*, Ju Hwan Yang1, Kwangmo Yang1, §, and Joo Mi Yi1,§
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Research Center, Dongnam Institute of Radiological & Medical Sciences (DIRAMS), Busan,
South Korea, 619-953 2
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Department of Biological Science, Pusan National University, Busan, South Korea, 609-735
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*These authors contributed equally to this work
§
Joo Mi Yi, PhD
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Correspondence should be addressed to:
Email: [email protected]
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Research Center
Dongnam Institute of Radiological & Medical Sciences (DIRAMS), Busan, 619-953, South Korea TEL: +82-51-720-5139 FAX: +82-51-720-5929
Kwangmo Yang, M.D. Ph.D. Email: [email protected] Department of Radiation Oncology Dongnam Institute of Radiological & Medical Sciences (DIRAMS) Busan, 619-953, South Korea TEL: +82-51-720-6010 FAX: +82-51-720-5929
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ACCEPTED MANUSCRIPT Abstract
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Recent studies have reported that embryonic stem (ES) cell-associated gene expression
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signatures have been identified in poorly differentiated tumors, revealing a link between ES
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cell identity and cancer cells. Cancer cells originate from cancer stem cells (CSCs). Both types of cells share common properties such as self-renewal and heterogeneity. CSCs are also resistant to conventional chemotherapy and radiotherapy. Here, we show similar gene
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expression patterns between ES cells and ionizing radiation (IR)-treated cancer cells. Using genome-wide transcriptome analysis, we compared the gene expression profiles among ES
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cells, cancer cells, and irradiated cancer cells, and identified a subset of similar gene expression patterns between ES cells and irradiated cancer cells, indicated by hierarchical
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clustering. These gene expression patterns were then confirmed by quantitative real-time
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reverse transcription polymerase chain reaction (qRT-PCR) analyses. Using bioinformatic
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analyses, these candidate genes are also associated with various biological pathways related to stemness in cancer. Taken together, our data suggest that identification of common molecular characteristics between ES cells and irradiated cancer cells is important
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to understand the properties of cancer stem cells and their resistance to radiotherapy.
Abbreviations
ES cell, embryonic stem cell; CSCs, cancer stem cells; IR, ionizing radiation; RT-PCR, reverse transcription polymerase chain reaction; Cy3, cyanine 3; Cy5, cyanine 5; GO, gene ontology; Gy, gray; qRT-PCR, quantitative real-time RT-PCR; SD, standard deviation
Keywords Embryonic stem (ES) cell; Cancer stem cells; Ionizing radiation; Expression microarray
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ACCEPTED MANUSCRIPT 1. Introduction
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Radiation therapy is frequently used as a standard treatment for different types of
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cancer. Ionizing radiation (IR) has been used clinically for cancer treatment, because the
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exposure to high doses of gamma IR causes severe DNA damage that can lead to apoptosis of cancer cells. There is growing evidence that IR causes an increase in the cancer stem cell population, and can affect the stemness characteristics of cancer cells, resulting in
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maintenance of stem-like populations with a higher resistance to radiotherapy. However, molecular mechanisms underlying radiation resistance in cancer cells remain poorly These
mechanisms
characterization.
are
complex
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understood.
and
require
more
comprehensive
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Cancer stem cells (CSCs), a subpopulation of malignant cells in the heterogenous
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cancer cell population, are considered to be responsible for cancer recurrence, metastasis,
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and drug resistance. CSCs have been isolated from a variety of human malignancies, including leukemia (Lapidot et al., 1994 and Bonnet and Dick, 1997), breast cancer (Al-Hajj et al., 2003 and Liu et al., 2005), brain tumors (Singh et al., 2004), and colorectal cancer
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(O'Brien et al., 2007 and Ricci-Vitiani et al., 2007). CSCs have the ability to self-renew and to differentiate into a multitude of cells that comprise the bulk of the tumor mass (Reya et al., 2001). CSCs also express high levels of drug resistant transporter proteins (e.g., ABC proteins) (Gottesman et al., 2002 and Haraguchi et al., 2010), DNA repair enzymes (Martin et al., 2008 and Zhang et al., 2010), and anti-apoptotic proteins (Liu et al., 2006 and Madjd et al., 2009), which make them highly resistant to conventional cancer therapies, including chemotherapy and radiotherapy. In addition, CSCs may be intimately involved in both intrinsic and acquired tumor resistance to anticancer treatments, including radiation therapy. Embryonic stem (ES) cells are of great interest as a model system for studying early developmental processes, and because of their potential therapeutic applications in 3
ACCEPTED MANUSCRIPT regenerative medicine. Stem cells and cancer cells share common properties, including selfrenewal and a block in differentiation. Recently, several groups have reported that
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expression signatures that are specific to ES cells are also found in many human cancers,
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suggesting that these shared features might be the targets of new approaches for cancer
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therapy. Previous reports suggested that a subset of ES cell-associated gene expressions at the transcriptional level can contribute to stem cell-like phenotypes in many tumors (BenPorath et al., 2008). Recently, there is growing evidence that radiation can induce stem-like
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characteristics in cancer cells (Ghisolfi et al., 2012). Based upon these observations, the present study sought to determine if irradiated cancer cells might share the stem-like gene
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expression signatures, which may help identify the mechanisms of regulation of cancer stem cells, and lead to treatments that can regulate the resistance of cancer cells to radiotherapy.
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We used the genome-wide transcriptome approach to identify the gene expression
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signatures shared with ES cells and irradiated cancer cells, and found overlapping gene expression characteristics between these cells. These genes were also associated with
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important cancer or stemness signaling pathways. Together, the results suggest that these gene expression signatures might be important subsets in the maintenance of stem-like
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populations in irradiated cancer cells involved in radiation resistance.
2. Materials and Methods
2.1. Gene expression microarray analysis
Total RNA of human embryonic stem cell (hESC) was purchased from CELPROGEN (Torrance, CA, USA).
Total RNA was extracted from control and irradiated cells using
TRIzol® reagent (Invitrogen, Carlsbad, CA, USA), and the integrity of the isolated total RNA 4
ACCEPTED MANUSCRIPT was measured with an Agilent Bioanalyzer 2100 RNA Nano kit (Agilent Technologies, Palo Alto, CA, USA). Synthesis of target cRNA probes and hybridization were performed using
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Agilent’s Low RNA Input Linear Amplification kit (Agilent Technologies) according to the
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manufacturer’s instructions. Briefly, each 1 μg of total RNA and T7 promoter primer mix were
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combined and incubated at 65ºC for 10 min. The cDNA master mix (5× first strand buffer; 0.1 M DTT, 10 mM dNTP mix, RNase-Out, and MMLV-RT) was prepared and added to RNA and the primer mixture. The samples were incubated at 40ºC for 2 hours for reverse transcription
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and double-stranded cDNA (dsDNA) synthesis, then terminated by incubating at 65ºC for 15 min. The transcription master mix was prepared according to the manufacturer’s protocol (4×
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transcription buffer, 0.1 M DTT, NTP mix, 50% PEG, RNase-Out, inorganic pyrophosphatase, T7-RNA polymerase, and cyanine 3/5-CTP) and added to the dsDNA reaction mixture, and
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incubated at 40ºC for 2 hours for transcription of dsDNA. During transcription-amplification,
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control and test cRNAs were labeled with Cy3-CTP and Cy5-CTP, respectively. Amplified and labeled cRNA were purified and quantified using an ND-1000 spectrophotometer
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(NanoDrop Technologies, Inc., Wilmington, DE, USA) to check labeling efficiency, followed by fragmentation of cRNA by adding 10× blocking agent and 25× fragmentation buffer, then
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incubating at 60ºC for 30 min. The fragmented cRNA was resuspended with 2× hybridization buffer and directly pipetted onto assembled Agilent Technologies human whole genome oligonucleotide microarrays (60K, Agilent Technologies) and placed in a hybridization chamber (Agilent Technologies). By incubating the hybridization chamber at 42ºC for 16 hours with mild agitation, competitive hybridization reactions occurred between labeled targets and probes on the microarray. To eliminate nonspecific binding, hybridized microarrays were washed with Agilent’s Gene Expression Wash Buffer kit (Agilent Technologies). Finally, microarrays were spin-dried and stored in the dark until scanned.
2.2. Microarray data acquisition and analysis
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ACCEPTED MANUSCRIPT Hybridized microarrays were scanned using a DNA microarray scanner and quantified with feature extraction software (Agilent Technologies). All data normalization and statistical
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change analyses were performed using GeneSpring GX 7.3 (Agilent Technologies). Data
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normalization was performed as follows: data transformation, set measurements 0.01 to
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0.01; per chip, normalized to the fiftieth percentile; per gene, normalize to the median. To identify differentially expressed genes, 2-fold change analysis and the statistical t-test (P < 0.05, no multiple testing corrections, no parametric test) were performed. Analyzed genes functionally
annotated
according
to
the
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were
gene
ontology
(GO) consortium
(http://www.geneontology.org). In addition, analyzed genes were functionally classified
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based on DAVID bioinformatics (http://david.abcc.ncifcrf.gov) by uploading target gene lists
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2.3. Cell culture and irradiation
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and using the “Functional Annotation Clustering” menu (Huang da et al., 2009).
Human colorectal carcinoma cell lines (HCT116 and SW480) and the breast cancer cell line MCF7 were obtained from the ATCC (Manassas, VA, USA). HCT116 and SW480 were
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cultured in McCoy’s 5A medium (WelGENE, Daegu-si, Korea), and MCF7 cells were cultured in DMEM medium (WelGENE). All cell culture media were supplemented with 10% fetal bovine serum (Hyclone, Logan, UT, USA) and 1% antibiotic-antimycotic solution (Gibco, Grand Island, NY, USA). All cell lines were incubated at 37ºC, with 20% O2 and 5% CO2. Cells were exposed to a total of 10 Gy gamma radiation through the blood mode after changing to fresh media. All irradiations were performed using a
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Ziegler, Berlin, Germany) at a dose rate of 2.6 Gy/min.
2.4. cDNA synthesis and quantitative real-time RT-PCR (qRT-PCR)
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Cs ray source (Eckert &
ACCEPTED MANUSCRIPT Cultured cells were trypsinized and homogenized using a QIAshredder kit (QIAGEN, GmbH, Hilen, Germany). Total RNA from cells was extracted using an RNeasy mini kit
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(QIAGEN). The amount of RNA was measured using a NanoDrop 2000/2000c instrument
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(Thermo Scientific, Rockford, IL, USA). For cDNA synthesis, 1 μg of total mRNA was reverse
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transcribed into cDNA using the iScriptTM cDNA Synthesis kit (BioRad, Hercules, CA, USA). The reactions were performed at 25ºC for 5 min, 42ºC for 30 min, and terminated by heating to 85ºC for 5 min.
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Transcripts of target genes were analyzed by the SYBR Master Mix (Thermo Scientific) using qRT-PCR with a CFX96TM real-time system (BioRad). For the development of specific
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primers for the candidate genes, all primers were designed using the Primer3 (http://bioinfo.ut.ee/primer3/) and the UCSC genome browser (http://www.genome.ucsc.edu/)
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(Supplementary Table 2). For normalization, human GAPDH was amplified. All relative
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2.5. Signaling pathway analysis
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of
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Functions and signaling pathways of candidate genes were investigated from the top super-pathway
categories
within
(http://www.genecards.org/cgi-bin),
that
the
GeneCard
database
included
KEGG
(http://www.kegg.jp/kegg/pathway.html). Gene ontology was analyzed using the GOrilla web tool (http://cbl-gorilla.cs.technion.ac.il), and the P-value threshold was limited to 10-3.
2.6. Statistical analysis
Quantified data are expressed as the mean ± standard deviation (SD). Testing of significance performed using the Student's t-test. A P-value of less than 0.05 was considered significant. 7
ACCEPTED MANUSCRIPT 3. Results
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3.1. Gene expression pattern of ES cells, cancer cells, and irradiated cancer cells
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It has been reported that tumors can recur when they are associated with radio resistance, and evidence suggests that radiation resistant breast cancer stem/progenitor cells are enriched after radiation (Debeb et al., 2009). Because increasing evidence supports
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the existence of radiation and chemotherapy resistant cancer stem cells or tumor initiating cells, we hypothesized that ES cells and irradiated cancer cells might share the gene
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expression signature which was responsible for their resistance to radiation. We also reasoned that genome-wide gene expression analyses would be more revealing than single-
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gene analyses (Segal et al., 2005 and Rhodes et al., 2007).
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We first compared the gene expression patterns among ES cells, cancer cells (HCT116,
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SW480, and MCF7), and irradiated cancer cells using a genome-wide expression arraybased approach. A gene expression profile was used to collect gene sets that represented shared gene expression signatures between ES cells and irradiated cancer cells. Global
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normalization was applied for gene expression analyses. To find similar patterns of gene expression between ES cells and irradiated cancer cells, probes were identified that showed a relative 2-fold downregulation (2,619 probes) among ES cells and three irradiated cancer cell datasets. Probes showing 2-fold upregulation (2,894 probes) were used in control cancer cells to find differential gene expression patterns, when compared with ES cells and irradiated cancer cells. Finally, we directly compared with two different datasets and identified 30 probes (24 genes) that overlapped (Supplementary Table1). We found that these 24 genes displayed similar gene expression levels in ES cells and irradiated cancer cells, but not in control cancer cells showing 2-fold up- or downregulation (Fig. 1).
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ACCEPTED MANUSCRIPT 3.2. The relationships between gene expression profiles from ES cells, cancer cells, and
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irradiated cancer cells
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To identify the common gene signature, we wondered how these gene expression
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patterns were related to ES cells, cancer cells, and irradiated cancer cells. Heat maps for 2,619 probes and 2,894 probes indicated a general gene expression signature between ES cells and irradiated cancer cells. As mentioned above, Importantly, thirty probes (24 genes)
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whose gene expression profiles overlapped between these two different datasets showed two significant groups between the ES cells, along with irradiated cancer cells and mock-
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treated cancer cells using hierarchical clustering analyses (MCF7, HCT116, and SW480) (Fig. 2A). This data strongly suggested that the gene expression patterns of these 30 probes
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might be shared between the ES cells and the irradiated cancer cells. Fig. 2B confirms that
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the 30 probes were preferentially over- or underexpressed in control cancer cells, but usually showed similar gene expression patterns in ES cells or irradiated cancer cells (Fig. 2B, left The
30
probes
included
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panel).
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genes,
except
for
uncharacterized
genes
(LOC100505821, LOC100507547, LOC728431, and XLOC013282) and small nucleolar
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RNAs (SNORA11 and SNORD60). We searched past studies of 24 genes, to identify the biological significance of these genes in normal and cancer cells (Table 1). We then hypothesized that these gene sets might be ES expression signatures shared with irradiated cancer cells. The actual gene expression levels of these gene sets from microarrays indicated they were very similar between ES cells and irradiated cancer cells, but were preferentially up- or downregulated in control cancer cells (Fig. 2B, right panel)
3.3. Validation of common gene signature in ES cell, cancer cells, and irradiated cancer cells
To validate the microarray data, we examined whether these 30 probes (24 genes) showed the same actual gene expression levels among ES cells, cancer cells, and irradiated 9
ACCEPTED MANUSCRIPT cancer cells. Using RT-PCR, specific primers were designed for the 24 genes, to check mRNA levels and to analyze whether the gene expression patterns were consistent with the
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microarray data. Sixteen genes were validated among the 24 genes, based on gene
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expression levels from the microarray data. Fig. 3 shows that most of the genes exhibited
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low or lack of gene expression levels in ES cells. Notably, their gene expression levels significantly decreased after IR treatment of cancer cells, as compared to controls. These sixteen genes usually showed low or lack of gene expression in ES cells compare with
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cancer cells, but after IR treatment to cancer cells, these genes tended to have a similar gene expression pattern as ES cells. Taken together, the results are consistent with our
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3.4. Implications of the signaling network for ES cell-like gene signatures
Although there was a small subset of ES cell-like gene expressions in irradiated cancer
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cells, we wanted to determine whether these genes were associated with a particular cellular pathway or network. Twenty-four genes were analyzed using well-curated databases (GO,
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GeneMANIA, and KEGG) that included a variety of biological processes, molecular functions, and cellular components (Supplementary Table 3). The possible roles of the candidate genes were hypothesized by inspecting the various signaling pathways predicted by KEGG pathway analysis (Table 1). In addition, several genes (CHRD, ID2, LAMB2, MINA, NF1, and POLR2B) were associated with stem cell regulatory pathways such as TGF-beta signaling, WNT/Hedgehog/Notch signaling for stem cell proliferation and differentiation, and ERK or MAPK signaling for regulation of stem cell proliferation (Fig. 4). These results suggested that expression profiles shared between ES cells and irradiated cancer cells play biological roles in radiation and cellular pathways involved in stemness for cancer.
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ACCEPTED MANUSCRIPT 4. Discussion
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Cancers arise from a cancer stem cell that is capable of self-renewal and tumor
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heterogeneity. The frequency of cancer stem cells is still controversial, depending on the
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technique used to detect the cells and the type of cancer (Visvader and Lindeman, 2008). It has been suggested that ES cells and cancer cells share overlapping molecular characteristics, so many studies have tried to identify the gene expression patterns that
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comprise these similarities. A study reported that the ES cell-like module is activated in various human epithelial cancers (Wong et al., 2008). Recently, a subset of ES cell-
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associated transcription regulators have been identified that are highly expressed in poorly differentiated tumors, revealing a link between genes associated with ES cell identity and the
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histopathology of tumors (Ben-Porath et al., 2008). These studies have reported that cancer
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cells overlap with molecular target signatures of ES cells, such as active core factors (Nanog,
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Oct4, and Sox2), polycomb complex (PRC), and Myc. These studies also provided additional evidence that common pathways could be utilized, both in stem/progenitors and in cancers. CSCs are thought to represent a small subpopulation of cells present in most tumors,
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similar to normal tissue stem cells, but with the ability to self-renew and differentiate into different cancer subtypes (Jordan et al., 2006). These CSC characteristics are responsible for their abilities to initiate and sustain tumors (Reya et al., 2001 and Visvader and Lindeman, 2008). Moreover, CSCs are also believed to play a key role in cancer metastasis, cancer recurrence, and cancer drug resistance (Clarke and Fuller, 2006 and Martin et al., 2008). It has been reported that exposure of cells to IR can result in genome instability and adaptive responses that have the potential to induce gene expression, chromosomal rearrangement, posttranslational modifications, and epigenetic changes that initiate carcinogenesis. The changes induced by IR exposure might lead to resistance to radiation therapy, both in vitro and in vivo. Recently, many studies have reported that CSCs are more resistant to radiation 11
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expansion of the cancer stem cell population, resulting in a small population of cells that are
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resistant to conventional cancer therapies, including radiotherapy (Suh and Lee, 2015).
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Although molecular targets or signatures associated with these phenomena and mechanisms are not well understood, emerging evidence has suggested that radiation can contribute to expansion of a cancer stem cell population that is highly tumorigenic.
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Using a genome-wide transcriptome approach, we showed in the present study that cancer cells induced by ionizing radiation share molecular gene expression signatures with
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ES cells. We identified similar gene expression levels between ES cells and irradiated cancer cells, accompanied by increasing or decreasing expression levels in cancer cells.
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Twenty-four genes were clustered in ES cells and IR-exposed cancer cells, suggesting that
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these gene expression signatures were shared between the two types of cells. Importantly, these genes were associated with important signaling pathways involved in cancer and stem
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cell proliferation. MINA, LAMB2, and NF1 genes were especially associated with regulation of stem cell proliferations. Therefore, we searched past studies to identify their biological
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functions.
MINA (MYC-induced nuclear antigen) is a c-MYC target gene that may play a role in cell proliferation or regulation of cell growth (Tsuneoka et al., 2002 and Zhang et al., 2005). Lack of the MINA protein caused a significant decrease in Hela cell numbers and A549 proliferation. Recently, it was reported that c-MYC activates an embryonic stem cell-like response in epithelial cells, leading to epithelial cancer stem cell development (Wong et al., 2008). However, we have checked the Myc target genes in our datasets (Ji et al., 2011), but we could not identify a biological relationship between ES cell and irradiated cancer cell datasets (data not shown). LAMB2 (laminin, beta-2) has been reported to bind directly to calcium channels that are required for neurotransmitter release from motor nerve terminals (Nishimune et al., 2004). However, there is little information regarding the biological function 12
ACCEPTED MANUSCRIPT of the LAMB2 gene in cancer or ES cell development. NF1 (neurofibromin 1) has been reported to be a cytoplasmic protein that is
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predominantly expressed in neurons, Schwann cells, oligodendrocytes, and leukocytes. It
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has also been identified as a tumor suppressor gene, and is able to regulate several proteins
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and/or intracellular processes, including RAS, the cyclic AMP pathway, the ERK and MAP kinase cascades, adenylyl cyclase, and cytoskeletal assembly (Trovo-Marqui and Tajara, 2006). Recent evidence has suggested that enriched cancer stem cells are relatively
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radioresistant. In addition, little is known about the relationships of these genes with the radiation response in cancer cells that contribute to expansion of the cancer stem cell
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population. By comparing gene expression profiles in ES cells, cancer cells, and irradiated cancer cells, our results suggested that these genes are important in understanding the
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molecular imprints of stemness. In the present study, we identified common gene expression
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signatures between ES cells and irradiated cancer cells, which suggest that these genes are associated with molecular characteristics of cancer stem cells that contribute to their
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Acknowledgements
This study was supported by a National Research Foundation of Korea (DIRAMS) grant funded by the Korea government (MSIP) (50591-2015). We would like to thank Khadijah Mitchell at National Cancer Institute (NCI) for critical reading of the manuscript and providing language help.
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ACCEPTED MANUSCRIPT Figure legends
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Fig. 1. Schematic overview of the screening approach using the Gene Expression
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microarray platform.
Fig. 2. Identification of stem cell-like gene expression signatures in irradiated cancer cells. (A) The upper Venn diagram shows 2,589 (2-fold upregulated) and 2,618 (2-fold
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downregulated) probes from the microarray data set. Hierarchical clustering analyses of gene expression data from microarray profiles in embryonic stem (ES) cells, control cancer
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cells, and irradiated cancer cell are shown. Green indicates reduced expression. Cluster analyses placed a group of these probes in the upper category. Thirty probes (24 genes)
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overlapped between the two different gene expression profile sets. The heat map shows 24
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gene expression values along with clustering analyses. Red and green in cells denote
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relative high or low expression levels, respectively, which are defined in the “Color Key” scale bar. (B) Gene expression pattern of 30 probes from the microarray data. Box plots display differential gene expression levels in ES cells, cancer cells, and irradiated cancer
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cells.
Fig. 3. qRT-PCR analysis of gene expression levels in ES cells, cancer cells, and irradiated cancer cells. Correlations between microarray data and qRT-PCR analyses results for gene expression levels in ES cells, cancer cells, and irradiated cancer cells. Representative genes show validation using qRT-PCR analyses from the microarray data. Bar graphs show gene expression levels and IR indicates the 10 Gy used to treat the cancer cells. * indicates significant decrease in ES and IR (*P<0.05).
Fig. 4. Biological implications of stem cell related genes. Some of our candidate genes 16
ACCEPTED MANUSCRIPT are related to stem-like signaling pathways in cancer. CHRD and NF1 regulate cancer stem cell proliferation. ID2 induces cell growth reduction by inhibition of DNA binding. c-Myc is a
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stemness factor, and ID2 and MINA regulate transcriptional activations in stem cells. The
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roles of LAMB2 and POLR2B have not been identified in stem cells. However, abnormal
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functioning of the ERK pathway, DNA repair, and mRNA splicing can affect stem-like
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Table 1. Information and signaling pathway of target genes. Accession No.
Description ATP-Binding Cassette, Sub-Family D (ALD), Member 3
Signaling pathway ABC-family proteins mediated transport; Transport of glucose and other sugars, bile salts and organic acids, metal ions and amine compounds; Peroxisome; Nuclear receptors in lipid metabolism and toxicity Synthesis and Degradation of Ketone Bodies; superpathway of cholesterol biosynthesis; Metabolism; Acetyl-CoA Acetyltransferase 1 Valirne, leucine and isoleucine degradation; Fatty acid, triacylglycerol, and ketone body metabolism Superpathway of cholesterol biosynthesis; Valine, leucine and isoleucine degradation; tryptophan utilization Acetyl-CoA Acetyltransferase 2 II; Fatty acid metabolism; Butanoate metabolism Cyclin J -Chordin Signaling by BMP; TGF-beta signaling pathway Deleted In Primary Ciliary Dyskinesia Homolog -Energy Homeostasis Associated -Immune response Fc epsilon RI pathway; PI-3K cascade; Signaling by GPCR; Development Slit-Robo Fer (Fps/Fes Related) Tyrosine Kinase signaling; Sertoli-Sertoli Cell Junction Dynamics Global Genomic NER (GG-NER); Assembly of RNA Polymerase-II Initiation Complex; Viral GTF2H2 Family Member C, Copy 2 carcinogenesis Inhibitor of DNA Binding 2, Dominant Negative Wnt / Hedgehog / Notch; Validated targets of C-MYC transcriptional repression; Validated targets of CHelix-Loop-Helix Protein MYC transcriptional activation; Transcriptional misregulation in cancer; TGF-beta signaling pathway Integral Membrane Protein 2B RNA Polymerase I Promoter Opening; Disease Focal adhesion; Integrin Pathway; ERK Signaling; Phospholipase-C Pathway; Non-integrin membrane-ECM Laminin, Beta 2 (Laminin S) interactions Leucine-Rich Repeats And IQ Motif Containing 3 -MYC Induced Nuclear Antigen Validated targets of C-MYC transcriptional activation MAPK signaling pathway; G-protein signaling M-RAS regulation pathway; Development VEGF signaling Neurofibromin 1 via VEGFR2 - generic cascades; ERK Signaling; Ras signaling pathway Pyridoxal (Pyridoxine, Vitamin B6) Phosphatase Metabolism; Vitamin B6 metabolism; Phosphatases; Cytoskeletal Signaling Circadian rhythm; Circadian Clock; Circadian entrainment; Influenza A; Metabolic States and Circadian Period Circadian Clock 1 Oscillators Polymerase (RNA) II (DNA Directed) Polypeptide B, Formation of RNA Pol II elongation complex; Purine metabolism; DNA Repair; mRNA Splicing - Major 140kDa Pathway; Assembly of RNA Polymerase-II Initiation Complex Ring Finger Protein 126 -Ribosomal Protein L22-Like 1 CFTR translational fidelity (class I mutations) Arginine/Serine-Rich Protein 1 -Trichohyalin --
ABCD3
NM_001122674
ACAT1
NM_000019
ACAT2
NM_005891
CCNJ CHRD DPCD ENHO
NM_019084 NM_003741 NM_015448 NM_198573
FER
NM_005246
GTF2H2D
NM_001042490
ID2
NM_002166
ITM2B
NM_021999
LAMB2
NM_002292
LRRIQ3 MINA
NM_001105659 NM_032778
NF1
NM_000267
PDXP
NM_020315
PER1
NM_002616
POLR2B
NM_000938
RNF126 RPL22L1 RSRP1 TCHH
NM_194460 NM_001099645 NM_020317 NM_007113
TCOF1
NM_001008657
Treacher Collins-Franceschetti Syndrome 1
Ribosome biogenesis in eukaryotes
TTC3
NM_003316
Tetratricopeptide Repeat Domain 3
--
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CR
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Highlights Comparision between gene expression profile between ES cells and irradiated cancer cells We identified stem cell like gene expression signature in irradiated cancer cells. Irradiated cancer cells might have stem-like characteristics for cancer stem cells at the molecular level.
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