Abstract
Background
Cytokine-induced killer (CIK) cells are an emerging approach of cancer
treatment. Our previous study have shown that CIK cells stimulated with
combination of IL-2 and IL-15 displayed improved proliferation capacity
and tumor cytotoxicity. However, the mechanisms of CIK cell
proliferation and acquisition of cytolytic function against tumor
induced by IL-2 and IL-15 have not been well elucidated yet.
Methods
CIK[IL-2] and CIK[IL-15] were generated from peripheral blood
mononuclear cells primed with IFN-γ, and stimulated with IL-2 and IL-15
in combination with OKT3 respectively. RNA-seq was performed to
identify differentially expressed genes, and gene ontology and pathways
based analysis were used to identify the distinct roles of IL-2 and
IL-15 in CIK preparation.
Results
The results indicated that CIK[IL-15] showed improved cell
proliferation capacity compared to CIK[IL-2]. However, CIK[IL-2] has
exhibited greater tumor cytotoxic effect than CIK[IL-15]. Employing
deep sequencing, we sequenced mRNA transcripts in CIK[IL-2] and
CIK[IL-15]. A total of 374 differentially expressed genes (DEGs) were
identified including 175 up-regulated genes in CIK[IL-15] and 199
up-regulated genes in CIK[IL-2]. Among DEGs in CIK[IL-15], Wnt
signaling and cell adhesion were significant GO terms and pathways
which related with their functions. In CIK[IL-2], type I interferon
signaling and cytokine-cytokine receptor interaction were significant
GO terms and pathways. We found that the up-regulation of Wnt 4 and
PDGFD may contribute to enhanced cell proliferation capacity of
CIK[IL-15], while inhibitory signal from interaction between CTLA4 and
CD80 may be responsible for the weak proliferation capacity of
CIK[IL-2]. Moreover, up-regulated expressions of CD40LG and IRF7 may
make for improved tumor cytolytic function of CIK[IL-2] through type I
interferon signaling.
Conclusions
Through our findings, we have preliminarily elucidated the cells
proliferation and acquisition of tumor cytotoxicity mechanism of
CIK[IL-15] and CIK[IL-2]. Better understanding of these mechanisms will
help to generate novel CIK cells with greater proliferation potential
and improved tumor cytolytic function.
Keywords: CIK cells, Interleukin 2, Interleukin 15, Deep sequencing,
Transcriptome
Background
Cancer is still a leading cause of diseases related death all over the
world. It was estimated that 7.6 million people were dead from various
types of cancer in 2008, and the figure will continue to rise to 13.1
million in 2030 [[51]1]. Fortunately, significant progress has been
made to develop better approaches to prevent, diagnose and treat cancer
in the past several years. These advances have made more people survive
with their cancer today. However, these new approaches are not
completely effective to all of cancers, and side effects were brought
by some of treatments. Among these advances, immunotherapy has shown
its large potential in cancer therapy. Cytokine-induced killer (CIK)
cells, a subset of T lymphocytes with a natural killer T cell
phenotype, have been proven to be effective to most of tumors in vitro
and in vivo [[52]2]. CIK cells exhibit potent cytolytic activities
against tumor cells with minimal adverse effects. CIK cells are
prepared from peripheral blood mononuclear cells (PBMCs) by priming
with IFN-γ, and maintained with monoclonal antibody against CD3 (OKT3)
and interleukin-2 in the following days [[53]3]. During the generation
of CIK cells, monoclonal antibody against CD3 provided mitogenic
signals to T lymphocytes. Priming with IFN-γ is to activate the
monocytes which provide contact-dependent (CD58/LFA-3) and soluble
(IL-12) crucial signals promoting generation of autophagy and antigen
cross-presentation [[54]4]. In following bulk culture, IL-2 promotes T
cell proliferation, survival and acquisition of cytolytic effector
function.
IL-15 is a cytokine which stimulate growth of NK, NKT cells and
activated T lymphocytes in peripheral, and it has similar biological
properties with IL-2 in innate immunity [[55]5]. Studies have suggested
that IL-15 bind to subunits of IL-2 receptor and common gamma chain
[[56]6]. Because IL-15 and IL-2 share common signaling components, they
mediate a series of similar signaling events. These events include
activation of the Janus kinase (Jak) and STAT pathways. The two
cytokines both can facilitate the induction of tumor toxic effector T
cells and proliferation of NK cells. However, IL-15 and IL-2 are
differed in their cDNA/protein sequence and contribute differently to T
cell-mediated immune response [[57]6]. Although IL-2 is a growth and
survival factor, it plays important role in Fas-mediated
activation-induced cell death (AICD) of CD4 T cell. In contrast, IL-15
promotes the survival of T lymphocytes by inhibiting IL-2-mediated
CD4^+ T cell AICD [[58]7].
In our previous study, we have shown that CIK cells stimulated with
combination of IL-2 and IL-15 exhibited enhanced cytotoxic capacity
against lung cancer both in vitro and in vivo. Interestingly, we found
that CIK cells activated with IL-2 and IL-15 could up-regulate the
expression levels of IFN-γ and TNF-α in vivo compared to CIK cell
stimulated with IL-2 alone [[59]8]. In order to identify the roles of
IL-2 and IL-15 during induction of tumor toxic function of CIK cells,
we performed comparative transcriptome analysis between CIK cells
prepared with IL-15 and IL-2 respectively by Ion PI mRNA sequencing
(RNA-seq) for the first time. The mRNAs isolated from CIK[IL-15] cells
and CIK[IL-2] cells were transcribed into cDNAs which were applied to
deep sequencing. The results of RNA-seq were analyzed by a series of
bioinformatic methods including mapping, gene differential expression
analysis, gene ontology (GO) and pathway analysis. Our finding will
provide evidence for optimizing the CIK cell propagation strategy which
produces more effective CIK cells against tumor.
Methods
Cell lines and reagents
Human lung adenocarcinoma (SPC-A-1 cells) and gastric tumor cells
(BGC823) were obtained from Chinese Type Culture Collection (Shanghai,
PR China). FITC conjugated anti-CD56 antibody and R-phycoerythrin
conjugated anti-CD3 antibody used in identifying CIK phenotypic markers
were purchased from BD Biosciences. The cell viability assay kit (Cell
Counting Kit-8) was purchased from Dojindo, Molecular Technologies.
Reagents for CIK cells generation including OKT3, IFN-γ, IL-2 and IL-15
were from Miltenyi Biotec. Experiments involving human peripheral blood
were reviewed and approved by Bioethics Committee of Yan’an Affiliated
Hospital of Kunming Medical University. Written informed consents have
been given from all volunteers participated in this study.
Generation of CIK[IL-2] and CIK[IL-15] (Standard protocols)
The Bioethics Committee of Yan’an Affiliated Hospital of Kunming
Medical University has approved the investigation protocols to draw
blood from healthy volunteers after written informed consent for the
purposes of preparation CIK cells against tumor and deep sequencing.
CIK cells were prepared from PBMCs which were isolated by standard
Ficoll separation. PBMCs were cultured in RPMI 1640 growth medium at a
density of 5 × 10^6 cells/mL. The RPMI 1640 growth medium for CIK
contained 10% FBS, 2% L-glutamine and antibiotics. The generation of
CIK cells was primed by adding 1000 U/mL IFN-γ on day 0 and 100 ng/mL
anti-CD3 antibody and 500 U/mL IL-2 or 10 ng/mL IL-15 within the
following 15 days of culture. The CIK cells were propagated every
5 days with RPMI 1640 growth medium supplemented with anti-CD3 antibody
and IL-2 or IL-15 respectively [[60]9]. The CIK cells were expanded for
15 days and analyzed every 5 days.
Cytotoxicity assay based on CCK-8
After co-culture with CIK cells for 48 hours, the cell viabilities of
two tumor cells were determined by CCK-8 based methods. Briefly, 10uL
of CCK-8 solution was added in each well, and the plates were incubated
at 37°C for 2–4 hours. After incubation, the absorbance of each well
was read by a spectrophotometer at 450 nm. Each sample for one
treatment was calculated by values from 5 independent samples.
RNA extraction and quality control
Total RNA was extracted from each sample using TRIzol Reagent (Life
technologies, USA) according to the protocol from manufacturer. The
concentration of each sample was measured by NanoDrop 2000 (Thermo
Scientific, USA). The quality was assessed by the Agilent2200 (Agilent,
USA).
Whole transcriptome libraries preparation and deep sequencing
The sequencing library of each RNA sample was prepared by using Ion
Total RNA-Seq Kit v2 according to the protocol provided by manufacturer
(Life technologies, USA). Briefly, poly(A)-containing mRNA was purified
from 5 ug total RNA with Dynabeads (Life technologies, USA). The mRNA
was fragmented using RNaseIII and purified. The fragmented RNA was
hybrized and ligated with Ion adaptor. The RNA fragments were
reverse-transcribed and amplified to double-stranded cDNA. Then, the
amplified cDNA was purified by magnetic bead based method, and the
molar concentration was determined for each cDNA library. Emulsion PCR
was performed using template of cDNA library. The Template-Positive Ion
PI^TM Ion Sphere^TM Particles were enriched and loaded on the Ion PI^TM
chip for sequencing.
Filtering raw reads and mapping
The raw reads ≥50 bp which passed filtering were used for mapping. We
used the Masplicing as our RNA-seq data mapping analysis tool whose
core program is Bowtie that can identify the exon-exon splicing
immediately and accurately [[61]10].
Identification of differentially expressed genes
We applied the DEseq to filter the differentially expressed genes for
the CIK[IL-15] and CIK[IL-2] groups. After the statistical analysis, we
selected the differentially expressed genes according to the FDR
threshold (FDR < 0.05) [[62]11].
GO analysis
GO analysis was applied to analyze the main function of the
differential expression genes according to the Gene Ontology which is
the key functional classification of NCBI [[63]12,[64]13]. Generally,
Fisher’s exact test and χ^2 test were used to classify the GO category,
and the false discovery rate (FDR) was calculated to correct the
P-value, the smaller the FDR, the small the error in judging the
p-value [[65]14,[66]15]. The FDR was defined as
[MATH: FDR=1−NkT :MATH]
, where N[ k ]refers to the number of Fisher’s test P-values less than
χ^2 test P-values. We computed P-values for the GOs of all the
differential genes. The significant GO terms were defined as P value
<0.05 and FDR <0.05. Concerning on the treatment of GO term redundancy,
we have adopted strategy of filtering out terms by picking only one
from each leaf-to-root path.
Pathway analysis
Similarly, pathway analysis was used to find out the significant
pathway of the differential genes according to KEGG, Biocarta and
Reactome [[67]10,[68]16,[69]17]. Still, we turn to the Fisher’s exact
test and χ^2 test to select the significant pathway, and the threshold
of significance was defined by P-value and FDR. The significant pathway
was identified by P value <0.05 and FDR < 0.05. The enrichment was
calculated like the equation above [[70]18-[71]20].
Gene-act-network
Use the KEGG database to build the network of genes according to the
relationship among the genes, proteins and compounds in the database
[[72]21-[73]25].
Path-act-network
KEGG database has included metabolism, membrane transport, signal
transduction, cell cycle pathways and information about interactions
among them. The genes we have selected may involved in two or more
signaling pathways. Because of the same genes in different pathways,
overlappings between pathways were obvious. We picked the genes in
enriched biological pathway and used Cytoscape for graphical
representations of pathways [[74]26].
Co-expression network analysis
For each pair of genes, we calculate the Pearson Correlation and choose
the significant correlation pairs (FDR < 0.01) to construct the network
[[75]27]. Within the network analysis, degree centrality is the most
simplest and important measures of the centrality of a gene within a
network that determine the relative importance. Degree centrality is
defined as the link numbers one node has to the other [[76]28].
Moreover, to study some properties of the networks, k-cores in graph
theory were introduced as a method of simplifying graph topology
analysis [[77]29].
Quantitative reverse-transcription PCR
All the qRT-PCR involved in this study was performed on the CFX96
Touch™ (BIORAD, USA). The first strand of cDNA was synthesized with
adjusted concentration of RNA, and corresponding genes were amplified
by employing EVA Green Supermix. All the primers used for qRT-PCR were
obtained from GeneCopoeia (USA).
Results
Enhanced cell proliferation capacity of CIK[IL-15] and superior tumor toxic
effect of CIK [IL-2]
CIK cells were generated from peripheral blood mononuclear cells of
three healthy volunteers. The CIK[IL-15] and CIK[IL-2] cells were
confirmed by flow cytometry with the phenotypes of CD3^+CD56^+. The
results have demonstrated that the percentages of CD3^+CD56^+ cells
were 98.80 ± 0.503% and 97.60 ± 0.603% respectively in CIK[IL-2] and
CIK[IL-15] (Figure [78]1A). We determined the proliferation capacities
of CIK[IL-15] and CIK[IL-2] by automatic cell counting. The result
showed that CIK[IL-15] displayed significantly higher proliferation
capacity than CIK[IL-2] (Figure [79]1B). To evaluate the tumor toxic
effects of CIK[IL-15] and CIK[IL-2], we have chosen two types of tumor
cell lines including human gastric tumor (BGC823) and human lung
adenocarcinoma (SPC-A-1) as the targets in anti-tumor assay. After
co-culture with CIK[IL-15] and CIK[IL-2] for 48 hours, the cell
viabilities were measured for each type of tumor based on CCK-8 method.
The results indicated that CIK[IL-2] cells have shown greater cytotoxic
potential against tumor than CIK[IL-15] (Figure [80]1C). In order to
investigate the distinct roles of IL-2 and IL-15 in CIK cell
generation, we performed transcriptome-wide analysis of CIK[IL-2]
(n = 3) and CIK[IL-15] (n = 3) by deep sequencing.
Figure 1.
Figure 1
[81]Open in a new tab
A overview of phenotypes, functions and RNA-seq quality control of
CIK[IL-15 ]and CIK[IL-2]. (A) Flow cytometric and statistical analysis
of the proportion of CD3^+CD56^+ CIK cells. Numbers indicate the
percentage of each subset. (B) Cell proliferation capacity assay of
CIK[IL-15] and CIK[IL-2] based on automatic cell counting; (C)
Detection of tumor cytotoxic effect of CIK[IL-15] and CIK[IL-2] against
SPC-A-1 and BGC823; (D) Distribution of reads on chromosomes; (E)
Percentage of mapped reads onto the regions of exons, introns, 5’-UTR,
3’-UTR, transcription start site (TSS), transcription end site (TES)
and intergenic region.
Overview of sequencing data of RNA-seq analysis
Total raw reads among the six samples ranged from 19 to 34 million. The
average of the GC content is approximately 49% for each sample. By a
stringent quality check, more than 95% of the reads we obtained have a
quality score of ≧Q20. The sequencing quality was analyzed by using
RSeQC [[82]30]. The raw sequence data have yielded about 2.2 gigabases
(GB) of data per sample. About 1.58 ± 0.48 × 10^7 reads (73.5% of the
total raw reads) were mapped to human genome sequence in the six
independent samples (Table [83]1) and 1.49 ± 0.48 × 10^7 reads (69.5%
of the total raw reads) were uniquely aligned to human genome. The
mapping of the reads was performed by using MapSplice. Mapped reads in
six independent samples were distributed consistently on the
chromosomes (Figure [84]1D). We found that chromosome 1 has been
matched the most reads and the least reads were found in chromosome Y.
In the uniquely mapped reads, more than 50% of the reads were aligned
at the transcript exon, 17% at the intron regions, 13% at the UTR
regions and the remaining at TES (transcription end site), TSS
(transcription start site) and intergenic regions (Figure [85]1E).
Subsequently, we analyzed the aligned reads for transcript assembly,
abundance evaluation and normalization. After annotation, there were
3,6267 transcripts annotated with known function Additional file [86]1.
In order to quantify the expression levels of the transcripts, the
RNA-seq data was normalized to RPKM values.
Table 1.
Statistics of raw and mapped reads from RNA-seq analysis of CIK cells
stimulated by IL-15 and IL-2 respectively
CIK[ IL-15 ]-1 CIK[ IL-15 ]-2 CIK[ IL-15 ]-3 CIK[ IL-2 ]-1 CIK[ IL-2
]-2 CIK[ IL-2 ]-3
Raw reads
__________________________________________________________________
19810412
__________________________________________________________________
19235209
__________________________________________________________________
21693091
__________________________________________________________________
22108193
__________________________________________________________________
24539599
__________________________________________________________________
21801487
__________________________________________________________________
Unmapped reads
__________________________________________________________________
5198537
__________________________________________________________________
4707536
__________________________________________________________________
5509521
__________________________________________________________________
6426050
__________________________________________________________________
6846138
__________________________________________________________________
5934418
__________________________________________________________________
Mapped reads (Rate)
__________________________________________________________________
14611875 (0.74)
__________________________________________________________________
14527675 (0.76)
__________________________________________________________________
16183570 (0.75)
__________________________________________________________________
15682144 (0.71)
__________________________________________________________________
17693461 (0.72)
__________________________________________________________________
15867070 (0.73)
__________________________________________________________________
Unique mapping (Rate)
__________________________________________________________________
13874295 (0.70)
__________________________________________________________________
13786260 (0.72)
__________________________________________________________________
15299443 (0.71)
__________________________________________________________________
14820672 (0.67)
__________________________________________________________________
16748163 (0.68)
__________________________________________________________________
15024084 (0.69)
__________________________________________________________________
Repeat mapping 737580 741413 884127 861471 945298 842985
[87]Open in a new tab
Differential gene expression profiles of CIK[IL-15] and CIK[IL-2] and GO
analysis
To characterize the functional consequences of gene expression changes
induced by IL-15 and IL-2, we screened the differentially expressed
genes (DEGs) between CIK[IL-15] cells and CIK[IL-2] cells by the
following criteria: Log[2]FC > 1 or Log[2]FC < −1, FDR < 0.05 and P
value < 0.05. We found 374 DEGs between CIK[IL-15] and CIK[IL-2]
Additional file [88]2. Of these DEGs, 175 and 199 genes were
up-regulated in CIK cells activated by IL-15 and IL-2 respectively. We
used hierarchical cluster analysis to compare the DEGs between these
two types of CIK cells and similarity of expression patterns of three
biological replicates (Figure [89]2). To identify the functions of
these DEGs, we performed gene ontological analysis based on GO database
Additional file [90]3. Among these DEGs which were up-regulated in
CIK[IL-15], there were 11 genes involved in cell adhesion and 5 genes
involved in Wnt signaling pathway (Figure [91]2). By analyzing the
significant GO terms, we found that T cell receptor V(D)J
recombination, cell adhesion and alpha-beta T cell differentiation were
involved (Figure [92]3A). In order to target the DEGs which may cause
functional changes, we screened DEGs whose GO terms were closely
related with the functions of CIK cells. Based on the functional assay,
CIK[IL-15] cells have shown greater proliferation capacity than
CIK[IL-2] cells in vitro. Interestingly, we found that Wnt 4 was
significantly up-regulated in CIK[IL-15] compared to CIK[IL-2]
(Table [93]2). By gene ontological analysis, Wnt 4 is involved in
multiple biological processes including Wnt signaling pathway, immature
T cell proliferation and negative regulation of apoptosis
(Table [94]2). Platelet-derived growth factor D (PDGFD) is a growth
factor that plays an essential role in cell proliferation and survival.
The expression of PDGFD is up-regulated after stimulation of IL-15.
Therefore, we speculated that the enhanced proliferation capacity of
CIK[IL-15] may be brought by up-regulation of Wnt4 and PDGFD.
Interleukin 21 receptor, which has played important role in natural
killer cell activation and cytokine signaling pathway was found highly
expressed in CIK[IL-15.] Moreover, E3 ubiquitin protein ligase (DTX4)
and intercellular adhesion molecule (ICAM4) were also up-regulated in
CIK[IL-15]. These proteins may be involved in type I interferon
production and cell adhesion. Among the DEGs in CIK[IL-2], there were
17 genes participated in innate immune response, 16 genes involved in
cytokine-mediated signaling pathway and 12 genes involved in type I
interferon signaling pathway (Figure [95]2). By analyzing the
significant go terms, we found that type I interferon signaling
pathway, cytokine-mediated signaling pathway and immune response are
significant GO terms in response to stimulation of IL-2
(Figure [96]3B). Compared to CIK[IL-15], CIK[IL-2] has shown enhanced
cytotoxic capacity against tumor. Consistently, we have found 3 tumor
suppressive genes which were significantly up-regulated in CIK[IL-2]
including tumor necrosis factor ligand superfamily member 10 (TNFSF10),
CD40 ligand (CD40LG) and interferon regulatory factor 7 (IRF7)
(Table [97]3). These genes were widely involved in positive regulation
of apoptotic signaling pathway, potent anti-tumor effect and promote
type I interferon production. Surprisingly, we found that CD80 and its
inhibitory ligand CTLA4 were co-upregulated in CIK cells after
activation of IL-2. The function of CD80 is mainly involved in the
costimulatory signal for T lymphocyte activation. CTLA4 functions as a
negative regulator of T cell activation, which may inhibit the T cell
proliferation.
Figure 2.
Figure 2
[98]Open in a new tab
Clustering of differentially expressed genes in CIK[IL-15 ]and CIK[IL2
]and multiple DEGs involved GO terms. The genes included for further
analysis were labeled with red line by the sides of their gene symbols.
Figure 3.
Figure 3
[99]Open in a new tab
Significant gene ontology analysis of DEGs in CIK[IL-15 ]and CIK[IL-2].
(A) Significant GO terms of CIK[IL-15]; (B) Significant GO terms of
CIK[IL-2]. P value < 0.01 for all significant GO terms.
Table 2.
Up-regulated genes related with functions and phenotypes of CIK[ IL-15
]
Gene symbol Description Log[ 2 ]FC P value FDR Go Term
Wnt 4
__________________________________________________________________
Protein Wnt-4
__________________________________________________________________
1.10
__________________________________________________________________
3.61 × 10^−4
__________________________________________________________________
7.28 × 10^−3
__________________________________________________________________
Regulation of cell-cell adhesion; Wnt signaling pathway; immature T
cell proliferation in thymus; positive regulation of focal adhesion
assembly; T cell differentiation in thymus; cell differentiation;
cell-cell signaling; negative regulation of apoptotic process; positive
regulation of transcription, DNA-templated
__________________________________________________________________
IL21R
__________________________________________________________________
Interleukin 21 receptor
__________________________________________________________________
1.17
__________________________________________________________________
2.53 × 10^−4
__________________________________________________________________
5.53 × 10^−3
__________________________________________________________________
Interleukin-21-mediated signaling pathway; natural killer cell
activation; cytokine-mediated signaling pathway
__________________________________________________________________
DTX4
__________________________________________________________________
E3 ubiquitin-protein ligase
__________________________________________________________________
2.65
__________________________________________________________________
2.02 × 10^−3
__________________________________________________________________
2.82 × 10^−2
__________________________________________________________________
Regulation of type I interferon production; positive regulation of type
I interferon production; Notch signaling pathway; innate immune
response; protein ubiquitination
__________________________________________________________________
ICAM4
__________________________________________________________________
Intercellular adhesion molecule 4
__________________________________________________________________
1.90
__________________________________________________________________
1.46 × 10^−4
__________________________________________________________________
3.51 × 10^−3
__________________________________________________________________
Cell adhesion; cell-cell adhesion; regulation of immune response
__________________________________________________________________
PDGFD Platelet-derived growth factor D 1.65 2.38 × 10^−5 8.11 × 10^−4
Platelet-derived growth factor receptor signaling pathway; cellular
response to amino acid stimulus; multicellular organismal development;
regulation of peptidyl-tyrosine phosphorylation; positive regulation of
cell division
[100]Open in a new tab
Table 3.
Up-regulated genes related with functions and phenotypes of CIK[ IL-2 ]
Gene symbol Description Log[ 2 ]FC P value FDR Go terms
CTLA4
__________________________________________________________________
Cytotoxic T-lymphocyte-associated protein 4
__________________________________________________________________
1.01
__________________________________________________________________
1.64 × 10^−3
__________________________________________________________________
2.38 × 10^−2
__________________________________________________________________
Immune response; negative regulation of regulatory T cell
differentiation; negative regulation of B cell proliferation; T cell
costimulation; B cell receptor signaling pathway; cellular response to
DNA damage stimulus; positive regulation of apoptotic process
__________________________________________________________________
CD80
__________________________________________________________________
CD80 antigen
__________________________________________________________________
1.03
__________________________________________________________________
1.11 × 10^−3
__________________________________________________________________
1.75 × 10^−2
__________________________________________________________________
Innate immune response; positive regulation of GMCSF biosynthetic
process; positive regulation of T-helper 1 cell differentiation; T cell
activation; regulation of interleukin-2 biosynthetic process; T cell
costimulation
__________________________________________________________________
TNFSF10
__________________________________________________________________
Tumor necrosis factor ligand superfamily member 10
__________________________________________________________________
1.24
__________________________________________________________________
7.02 × 10^−18
__________________________________________________________________
4.45 × 10^−15
__________________________________________________________________
Immune response; activation of cysteine-type endopeptidase activity
involved in apoptotic process regulation of extrinsic apoptotic;
signaling pathway in absence of ligand; apoptotic process; positive
regulation of extrinsic apoptotic signaling pathway; positive
regulation of release of cytochrome c from mitochondria; apoptotic
signaling pathway; positive regulation of cysteine-type endopeptidase
activity involved in apoptotic process; positive regulation of
apoptotic process
__________________________________________________________________
CD40L
__________________________________________________________________
CD40 ligand
__________________________________________________________________
2.08
__________________________________________________________________
2.32 × 10^−6
__________________________________________________________________
1.18 × 10^−4
__________________________________________________________________
Immune response; inflammatory response; immunoglobulin secretion;
positive regulation of endothelial cell apoptotic process; B cell
proliferation; positive regulation of interleukin-12 production;
leukocyte cell-cell adhesion
__________________________________________________________________
IRF7 Interferon regulatory factor 7 1.08 3.12 × 10^−5 1.02 × 10^−3
Innate immune response; inflammatory response; positive regulation of
type I interferon-mediated signaling pathway; positive regulation of
type I interferon production; toll-like receptor signaling pathway
[101]Open in a new tab
Pathways analysis of CIK[IL-15] and CIK[IL-2]
To further identify the influence of DEGs on the functions of these two
types of CIK cells, we performed pathway analysis of DEGs based on KEGG
database using Fisher exact test Additional file [102]4. Among DEGs of
CIK[IL-15], there 5 genes participated in focal adhesion including
collagen type VI alpha 3 (COL6A3), collagen alpha-2(VI) chain (COL6A2),
collagen alpha-1(VI) chain (COL6A1), Platelet-derived growth factor D
(PDGFD) and Myosin light chain kinase family member 4 (MYLK4)
(Figure [103]4A). Surprisingly, 3 genes coding collagens were involved
in this pathway which may be related with enhanced cell proliferation
capacity of CIK[IL-15]. In CIK[IL-2], the results indicated that 13
genes participated in cytokine-cytokine receptor interaction
(Figure [104]4B). Of these genes, IL-4 and CXCL10 were newly identified
DEGs that may contributed to tumor suppression. Subsequently, we have
built the pathways interaction network to perform deep analysis.
Through analyzing the interactions among the significant pathways, it
was obvious Wnt signaling pathway, focal adhesion and cytokine-cytokine
receptor interaction were the most important pathways involved in the
function of CIK[IL-15] and CIK[IL-2] (Figure [105]4C). Because these
three pathways located at the centers of each clusters and showed the
most interactions with their surrounding pathways (the most arrows
toward them). The results suggested that Wnt 4 signaling pathway and
focal adhesion be the key biological events of CIK[IL-15] cell
proliferation, and cytokine-cytokine receptor interaction be the
dominant element in CIK[IL-2] cells in acquisition of tumor cytotoxic
capacity. This evidence indicated that DEGs involved in these three
pathways may play important roles in the distinct functions of
CIK[IL-15] and CIK[IL-2].
Figure 4.
Figure 4
[106]Open in a new tab
Pathway enrichment analysis of DEGs based on KEGG. (A) Enriched
pathways in CIK[IL-15]; (B) Enriched pathways in CIK[IL-2]; (C)
Pathways interaction network of CIK[IL-15] and CIK[IL-2], Red circles
represent enriched pathways in CIK[IL-15]; Green circle represent
enriched pathways in CIK[IL-2].
Differentially expressed genes act network
After functional analysis, it is important to explore the relationships
among these DEGs. According to KEGG database, we built the act network
of genes based on the relationships between them including
activation\binding, expression, inhibition and compound. In this gene
interaction network, CXCL10, CXCL9, CCL22, GLI2, WNT4, CD80 and CTLA4
were in involved in pathways which previously mentioned including Wnt
signaling pathway, Cytokine-cytokine receptor interaction and T cell
signaling (Figure [107]5). In Figure [108]5, we showed that GLI2 (Zinc
finger protein) functioned as transcription factor which involved in
the expression of protein Wnt 4 in CIK[IL-15]. Again, the interaction
between CD80 and CTLA-4 has been highlighted in CIK[IL-2]. After
stimulation of IL-2, CD80 were up-regulated and interacted with CD28
providing costimulation signal for T cell activation and proliferation.
However, negative feedback has been turned on through up-regulating the
expression of CTLA4 which bound to CD80 providing inhibitory signal
instead of CD28. Moreover, we also have noticed that CXCL10, CCL22 and
CXCL9 were associated with CCR1. The association among these genes may
be related with anti-tumor activity and CIK cell recruitment.
Figure 5.
Figure 5
[109]Open in a new tab
Gene Act network analysis. Red circles represent up-regulated genes in
CIK[IL-15]; Green circles represent up-regulated genes in CIK[IL-2].
Gene co-expression network
Alternatively, we performed the gene co-expression network analysis
between DEGs in CIK[IL-15] and CIK[IL-2] to highlight groups of DEGs in
synergy which may participate in biological processes resulted in
phenotypic changes [[110]31,[111]32]. Among DEGs of CIK[IL-15], we
showed that the expression levels of IL21R (Interleukin 21 receptor),
ENPP3 (Ectonucleotide pyrophosphatase/phosphodiesterase 3) and TXNIP
(Thioredoxin interacting protein) were positively correlated (Pearson’s
r = 0.99), and mainly involved in immune response (Figure [112]6A).
Moreover, we also found a group of genes that related with immune
response including IFI44 (Interferon-induced protein 44), FOXP3
(Forkhead box P3), IF44L (Interferon-induced protein 44-like), LY9
(T-lymphocyte surface antigen Ly-9) and IFI27 (Interferon,
alpha-inducible protein 27) in CIK[IL-15] (Figure [113]6A). It was
obvious that a cluster genes related with cell proliferation and
apoptosis including PDGFD (Platelet-derived growth factor D), PHLDA1
(PHLDA1 protein), DSCC1 (Sister chromatid cohesion protein), S100A8
(Protein S100-A8), DST (Bullous pemphigoid antigen 1) and EIF2AK2
(EIF2AK2 protein) were correlated in CIK[IL-15] (Figure [114]6A). In
CIK[IL-2], three pairs of genes with similar expression profiles were
found to be involved in type I interferon signaling pathway (MX1/USP18;
MX2/OAS1; IFT1/IFT3) (Figure [115]6B). Interestingly, the expression
pattern of T cell activation negative regulator Foxp3 was correlation
with the expression of IL-17 receptor B in CIK[IL-2] (Figure [116]6B).
Figure 6.
Figure 6
[117]Open in a new tab
Gene co-expression network analysis. (A) CIK[IL-15]; (B) CIK[IL-2];
Degree in different color is defined as the link numbers one node has
with the other. The Pearson Correlation of each pair of genes were
calculated from these three independent samples.
Validation of representative genes by qRT-PCR
We have examined the expression profiles of DEGs which were referred in
Table [118]2 and Table [119]3. The results of qRT-PCR have indicated
that the expression profiles of DEGs in CIK[IL-15] and CIK[IL-2] were
consistent with RNA-seq except for TNFSF10 (Figure [120]7). Notably,
the expression level of Wnt 4 in CIK[IL-15] was over 3 fold of those in
CIK[IL-2]. However, TNFSF10 in CIK[IL-2] were slightly higher than
CIK[IL-15] (p>0.05). Therefore, TNFSF10 may not be a contributor of
enhanced tumor toxic function of CIK[IL-2].
Figure 7.
Figure 7
[121]Open in a new tab
qRT-PCR validation of relative expression levels of representative
DEGs. (A) DEGs in CIK[IL-15]; (B) DEGs in CIK[IL-2]; the expression
levels of corresponding genes were normalized by β-actin. The results
were means and SEMs, representative of nine independent samples.
(P < 0.05 in all DEGs except TNSF10).
Discussion
Although clinical trials of CIK cells in cancer therapy were widely
performed in China, fewer studies on molecular mechanism of their
anti-tumor function were observed [[122]33,[123]34]. The pioneering
work of CIK cells was performed by Schmidt-Wolf from Stanford. The
authors indicated that CIK cells were a subset of non-MHC-restricted T
cells expressing both CD3 and CD56, and CIK cells showed potent
cytotoxicity against a variety of tumor cells [[124]2]. The efficiency
of CIK cells preparation is dependent on T cell proliferation and
cytolytic activity against tumor. To generate CIK cells with high
quality, cytokines such as IL-1, IL-7, IL-15 and IL-12 have been
employed instead of IL-2 or in combination with IL-2 [[125]4]. Of these
cytokines, IL-15 is widely tested in CIK cells preparation against
several tumor cells. In this study, the results have indicated that
CIK[IL-15] exhibit enhanced proliferation capacity than CIK[IL-2],
whereas, CIK[IL-2] showed more efficient cytotoxic effect against tumor
cells than CIK[IL-15]. Consistently, the results from transcriptome
analysis have shown corelationship with their functional
characteristics.
IL-15 is a pleiotropic cytokine which promote T cells and NK cells
proliferation and survival [[126]35,[127]36]. To better elucidate the
mechanism of increased proliferation capacity induced by IL-15, we have
found that Wnt 4 and PDGFD which were correlated with cell
proliferation were up-regulated in CIK[IL-15]. Wnt signaling pathway is
widely involved in cell proliferation and differentiation [[128]37]. It
has been reported that Wnt agonist promoted mouse muscle cell
proliferation, and specific silencing RNA knockdown of Wnt 4
significantly reduced muscle cell proliferation [[129]38]. Moreover,
study showed that the expression of Wnt 4 was required for
proliferation of cells in mouse coelomic epithelium [[130]39]. By
pathway interaction analysis, we have found that Wnt signaling pathway
is located at the center of the network, which got the most
interactions with other pathways. Therefore, we suggested that Wnt
signaling be one of the most important pathways which contributed to
the improved proliferation capacity of CIK[IL-15]. Except for Wnt 4,
PDGFD is also a proliferation promoting factor which regulates several
cellular processes including cell proliferation, apoptosis and
transformation [[131]40]. Over-expression of PDGFD in mouse or human
breast cancer cell significantly increased cell proliferation while
silencing PDGFD expression decreased proliferation and increased
apoptosis [[132]41]. Studies have indicated that PDGFD promoted cell
proliferation by increasing DNA binding capacity of NF-κB and
down-regulation of PDGFD inhibit tumor invasion through inactivation of
Notch-1 and NF-κB signaling [[133]42]. Therefore, the up-regulation of
Wnt 4 and PDGFD may be responsible for enhanced cell proliferation of
CIK[IL-15].
Additionally, we also have found important evidence which may inhibit
the proliferation of CIK[IL-2]. By differentiated expressed genes and
gene act network analysis, we found that CTLA4 and CD80 were
up-regulated in CIK[IL-2]. These two proteins can interact with each
other to provide inhibitory signal during T cell activation [[134]43].
In the generation of CIK[IL-2], OKT3 and IL-2 were sustainedly
presented in the culture system. However, IL-2 mediated
activation-induced cell death (AICD) occurred during the following
culture [[135]7]. Consistently, our previous phenotypic study of
CIK[IL-2] have showed that the cells subset of CD3^+CD28^+ was
increasing in the first several days while significantly decreased
since the 7^th day of culture (Data not shown). These results
demonstrated that the interaction between CTLA4 and CD80 may lead to
inactivation of CD3^+CD28^+ T cell and inhibit proliferation of
CIK[IL-2]. The inhibitory signal from ligation of CTLA4 to CD80 is the
negative feedback to IL-2 stimulation of CIK cells. Comprehensively,
not only up-regulated Wnt 4 and PDGFD but also activation inhibitory
signal from CTLA4 and CD80 in CIK[IL-2] has resulted in the enhanced
proliferation capacity of CIK[IL-15]. We suggest that supplement with
cytokines or mAb which down-regulates the inhibitory signal from CTLA4
and CD80 facilitate proliferation of CIK[IL-2] production.
The most important of characteristic of CIK cell is cytolytic activity
against tumor. In vitro, CIK[IL-2] cells have shown more efficient
tumor cytotoxicity than CIK[IL-15]. The expression of CD40LG and IFR7
were up-regulated in CIK[IL-2]. CD40LG, which is the ligand of CD40,
has shown great potentials in cancer therapy [[136]44]. It has been
reported that CD40 is expressed in nearly all B cell malignancy and
many solid tumors [[137]45]. The ligation of CD40 on the surface of
tumor cells inhibits the growth of tumor and induces apoptosis
[[138]46]. Besides CD40LG, IFN-β has also been found to play critical
role in anti-tumoral immune response [[139]47]. Interestingly,
Moschonas has indicated that stimulation of CD40 by its ligand has
promoted the expression of IFN-β through the binding IRF7 to its
promoter. IRF7 is a transcriptional factor which regulates the
expression of type I interferon [[140]48]. Silencing of IRF7 pathways
in breast cancer accelerated bone metastasis through immune escape
[[141]49]. Thus CD40LG and IFR7 may work synergically to improve the
tumor cytotoxic effect of CIK[IL-2].
On the other hand, the expression of DTX4 was up-regulated in
CIK[IL-15]which positively regulated the production of type I
interferon through NLRP4 [[142]50]. Moreover, the expression of IL-21R
whose ligand is involved in natural killer cell was also increased in
CIK[IL-15]. Paradoxically, the up-regulation of PDGFD in CIK[IL-15] not
only could promote the proliferation of CIK[IL-15] cells but also
promote tumor cells survival through cell and cell interaction in tumor
cytotoxic assay. PDGFs are composed of four different polypeptide
chains (PDGF A-D). It has been reported that PDGFD was deregulated in
most of human malignancies with up-regulated expression in solid tumors
[[143]51]. The factor interacts with PDGFR-β and activates downstream
signaling phosphatidylinositol 3-kinase (PI3K)/AKT, resulted in tumor
progression. Moreover, Li et al. reported that PDGFD is a potent
transformation growth factor for NIH/3 T3 which increased the cell
proliferation rate [[144]52]. We suggested that up-regulated PDGFD is a
double-edged sword in CIK[IL-15]. Because it favored the proliferation
of CIK[IL-15] cells during preparation, while it may also promoted the
survival and proliferation of tumor cells when CIK cells were in
contact with tumor cells.
Conclusions
In this study, deep sequencing was performed to analyze the different
gene expression profiles of CIK[IL-2] and CIK[IL-15] for the first
time. By advanced bioinformatic analysis of DEGs, we found that cell
proliferation promoting function was dominant in CIK[IL-15] involving
Wnt signaling pathway and focal cell adhesion. In CIK[IL-2], type I
interferon signaling pathway and cytokine-cytokine receptor
interactions were dominant. Through our findings, we have preliminarily
elucidated the cells proliferation and acquisition of tumor
cytotoxicity mechanism of CIK[IL-15] and CIK[IL-2]. Better
understanding of these mechanisms will help to generate novel CIK cells
with greater proliferation potential and improved tumor cytolytic
function.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
ZLH and RHL conceived and designed the study. WJW, MYM and YYZ
performed the experiments. WJW, DC and JZ analyzed the data. CHW and
WWT contributed reagents/material. CYW, YHX and LHJ interpreted the
data and wrote the paper. FY and XFJ revised the manuscript. All
authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
[145]http://www.biomedcentral.com/1755-8794/7/49/prepub
Supplementary Material
Additional file 1: Table S1
RNA-seq of data of all count for CIK[IL-15] and CIK[IL-2].
[146]Click here for file^ (3.8MB, xls)
Additional file 2: Table S2
The list of differentially expressed genes between CIK[IL-15] and
CIK[IL-2].
[147]Click here for file^ (118.5KB, xls)
Additional file 3: Table S3
GO analysis differentially expressed genes in CIK[IL-15] and CIK[IL-2].
[148]Click here for file^ (285.5KB, xls)
Additional file 4: Table S4
Pathway analysis differentially expressed genes in CIK[IL-15] and
CIK[IL-2].
[149]Click here for file^ (58KB, xls)
Contributor Information
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Acknowledgements