Abstract
Chronic lymphocytic leukemia (CLL) is a prototypic neoplasia in which
malignant cells strongly depend on microenvironmental stimulations in
the lymphoid tissues where they accumulate; leukemic cells are exposed
to interaction with bystander and accessory cells, as well as
inflammatory soluble mediators. Cell lines are frequently used to model
the pathobiology of this disease; however, they do not always
recapitulate leukemic cell growth and response to stimulation, and no
data are available on Toll‐like receptors (TLR) signaling in CLL cell
lines. To address this gap, we analyzed HG3, MEC2, and PCL12 cell
lines, before and after CpG stimulation, by RNA‐sequencing followed by
bioinformatic analyses and validation experiments. We identified NFKBIZ
mRNA and the corresponding IkBz protein as robust markers of TLR9
activation in both MEC2 and PCL12, but not in HG3 cells. Next, we
compared our current results with previous results obtained with
primary CLL patient samples and were able to conclude that MEC2 is most
similar to the patients' cells in terms of global responsiveness to TLR
stimulation; in particular, MEC2 better resembles the samples of
patients, as it is characterized by high expression levels of IkBz, but
with a lower number of genes regulated.
Keywords: cell line, chronic lymphocytic leukemia, CpG, NFKBIZ,
Toll‐like receptor 9
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To model the pathobiology of TLR9 response in CLL cell lines, we
analyzed the transcriptome of MEC2, PCL12, and HG3 after CpG
stimulation. MEC2 best recapitulates the characteristics of primary CLL
cells in terms of TLR9 signaling, IkBz expression, and global molecular
fingerprint, pointing to this cell line as the most appropriate
preclinical model to study TLR stimulation in CLL.
graphic file with name FEB4-13-2367-g004.jpg
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Abbreviations
BcR
B‐cell receptor
CLL
chronic lymphocytic leukemia
DEGs
differentially expressed genes
FC
fold change
FDR
false discovery rate
GSEA
gene set enrichment analysis
IGHV
immunoglobulin heavy variable
NES
Normalized Enrichment Score
TLR
Toll‐Like receptor
Monoclonal malignant B‐lymphocytes accumulate in the peripheral blood,
bone marrow, and secondary lymphoid organs of patients with chronic
lymphocytic leukemia (CLL). These cells maintain several features of
normal B‐lymphocytes, including the expression of a clonotypic B‐cell
Receptor (BcR) and of distinct innate immune Toll‐like receptors (TLR)
[[32]1]. On the contrary, CLL cells invariably express on their surface
CD5, a prototypic T‐cell specific protein ‘aberrantly’ expressed by
leukemic cells and representing a diagnostic marker together with CD19,
CD20, and CD23 [[33]2]. CLL accounts for 1% of all new cancer cases,
and it is one of the most common adult leukemia affecting mainly the
elderly with an average age at first diagnosis of 70 years (SEER Cancer
stat facts; [34]https://seer.cancer.gov/statfacts/html/clyl.html).
Despite significant progress in the identification and optimization of
novel treatment strategies, profound responses can be obtained in a
minority of patients, and novel approaches as well as model systems are
urgently needed.
Chronic lymphocytic leukemia is a very heterogeneous disease where
distinct prognostic factors have been identified, including specific
genetic abnormalities [[35]1]; moreover, the somatic hypermutation
status of the immunoglobulin heavy variable (IGHV) genes within the
leukemic cells helps to refine risk stratification of the patients
[[36]3, [37]4]. Notably, CLL is a prototypic microenvironment‐dependent
tumor where leukemic cells co‐evolve with accessory cells into an
inflammatory milieu [[38]5]; among several cytokine receptors, TLRs
have been implicated in cell proliferation and survival in human
primary cells and samples ([39]6, [40]7, [41]8, [42]9, [43]10, [44]11)
but not in a transgenic mouse model of leukemia [[45]12]. Previous
studies demonstrated the correlation between the induction of the
atypical transcription factor IkBz, mediated by TLR9 stimulation, and a
more active cellular response; accordingly, patients' samples were
classified as IkBz‐low or IkBz‐high that show increased metabolic
activity and resistance to chemotherapy [[46]13]. This highlights the
need for careful characterization of this signaling framework in
primary leukemic cells as well as in human cell lines.
Cell lines are frequently used to model the pathobiology of tumors,
including leukemia and lymphoma. However, CLL is somewhat an exception
as few cell lines have been stabilized and characterized likely due to
the intrinsic difficulty to immortalize circulating malignant cells.
Among them, MEC1/MEC2, PCL12, and HG3 are the most frequently used;
they express a clonotypic BcR bearing either mutated (MEC1 and MEC2) or
unmutated (PCL12 and HG3) IGHV genes, thus representing the two
different subgroups of CLL cases. CD5 can be expressed by HG3 and
PCL12, but it decreases over prolonged in vitro culture; CD19 and CD20
are expressed in all the three cell lines, while CD23 is expressed at
lower levels in MEC2 as compared to HG3 and PCL12 [[47]14, [48]15,
[49]16, [50]17]. Overall, these data suggest that CLL cell lines are
useful preclinical models even if they are not identical to their
primary counterpart. Accordingly, they have been widely used for drug
response as well as for BcR signaling studies [[51]16, [52]17, [53]18].
However, no data are available on their TLR‐mediated signaling
capabilities as compared to primary leukemic cells. To address this
issue, we analyzed the transcriptomes of these three different cell
lines treated in vitro with CpG, and we compared their gene expression
profiles with that of primary CLL cells previously analyzed [[54]19].
Methods
Cell culture and treatment
The EBV‐positive MEC1, MEC2, PCL12, and HG3 cell lines were purchased
from DMSZ and cultured with RPMI medium (Gibco, Waltham, MA, USA)
supplemented with 10% heat‐inactivated FBS (Gibco) and
Penicillin/Streptomycin (100 U·mL^−1; Invitrogen, Waltham, MA, USA).
ODN‐2006 CpG‐class B oligonucleotide specific for human TLR9
(InvivoGen, San Diego, CA, USA) was added to the cells at a final
concentration of 2.5 μg·mL^−1 as previously described for primary CLL
cells [[55]13].
RNA‐sequencing and analysis
Total RNA was extracted from unstimulated or stimulated MEC2, PCL12,
and HG3 cells (4 h with CpG) using the Qiagen RNA extraction kit
(Hilden, Germany). The library was prepared using a stranded reverse
protocol. Libraries have been checked using Qubit (fluorimeter) and
Bioanalyzer (capillary electrophoresis). Sequencing was performed using
Illumina Novaseq S2 XP, 1 × 100 nt, single read (Illumina, San Diego,
CA, USA). Both library preparation and RNA‐sequencing were performed in
the Genomics Laboratory of the Center for Omics Science (COSR), San
Raffaele Hospital, Milano, Italy. The trimmed sequences obtained were
aligned to the human ‘Hg38’ genome. RNA‐seq raw data have been
deposited in NCBI's Gene Expression Omnibus [[56]20] and are accessible
through [57]GSE233595.
Putative differentially expressed genes (DEGs) between CpG‐stimulated
and unstimulated samples were selected using limma [[58]21]. Genes are
indicated as ‘Differentially Expressed Genes’ (DEGs) if they satisfy
both the following conditions: nominal P value < 0.01 and
|Log[2]FoldChange| ≥ 1 (|Log[2]FC|).
Volcano plots were prepared using the ggplot2 package r
([59]https://CRAN.R‐project.org/package=ggplot2).
Real‐time PCR
Total RNA was extracted from unstimulated or stimulated cells (4 and
24 h with CpG) using the RNeasy Plus Mini kit (Qiagen) and was
quantified with nanodrop, and 1 μg was retro‐transcribed with iScript
Advanced cDNA Synthesis kit (Bio‐Rad, Segrate, Italy).
cDNA was used as template for real‐time PCR using CFX Connect Real‐Time
PCR Detection System (Bio‐Rad) with the Probe protocol and the
following probes:
* Probe NFKBIZ (qHsaCEP0052487; Bio‐Rad).
* Probe IL6 (Hs00985639m1; Thermo Fisher Scientific, Waltham, MA,
USA).
* Probe β‐Actin (qHsaCEP0036280; Bio‐Rad).
* Probe TBP (qHsaCIP0036255; Bio‐Rad).
Relative mRNA expression levels of NFKBIZ and IL6 were calculated using
the
[MATH:
2−ΔΔCt :MATH]
and
[MATH: 2−ΔCt :MATH]
methods, respectively, with β‐Actin and TBP as endogenous reference
genes.
Statistical analysis was performed with prism Software (graphpad prism
10 Software, Boston, MA, USA) as indicated in each figure legend.
Western blot
One million cells were lysed in 60 μL of RIPA buffer and centrifuged,
and the supernatant was added to reducing agent and loading buffer;
after boiling, the samples were loaded onto an SDS/PAGE gel (precast
gels 4–12% acrylamide; Invitrogen), run, and immobilized onto a
nitrocellulose membrane (The Trans‐Blot Turbo Transfer System).
Anti‐IkBz antibody #9244 (Cell Signaling Technology),
anti‐phospho‐ERK1/2, p44/42 MAPK #9104 (Cell Signaling Technology,
Danvers, MA, USA), and anti‐ERK1/2, p44/42 MAPK SC‐514302 (Santa Cruz
Biotechnology, Dallas, TX, USA) were added to the membranes; after
addition of the secondary HRP‐conjugated antibody A0545 (Sigma‐Aldrich,
Schnellendorf, Germany) or and anti β‐Actin antibody HRP‐conjugated,
8H10D10 (Cell Signaling Technology), and the ECL detection reagent, the
images were acquired with the ChemiDoc MP Imaging System (Bio‐Rad).
Densitometric analysis was performed utilizing the image lab software
(Bio‐Rad). Statistical analysis was performed with prism Software
(graphpad prism 10 Software) as indicated in each figure legend.
Results and Discussion
Transcriptome analysis of chronic lymphocytic leukemia cell lines
To explore TLR9‐mediated signaling pathways in CLL cell lines, we
performed a transcriptome analysis, including coding and noncoding RNAs
in HG3, MEC2, and PCL12 cells treated in vitro with the
immunostimulatory TLR9 agonist ODN‐2006, a class B unmethylated CpG
oligonucleotide specific for human cells. Four hours after incubation,
the cells were washed and pelleted and the RNA was purified for
sequencing.
Heat map shows the clustered expression values of 50 DEGs between
CpG‐treated and untreated cell lines (Fig. [60]1A); this clustering
suggests that HG3 cell line is quite distant from the other two and
that a limited number of genes are differentially expressed in
stimulated vs unstimulated samples in all the three cell lines.
Fig. 1.
Fig. 1
[61]Open in a new tab
Heat map and Volcano plot of transcriptome analysis of the cell lines.
(A) Heat map showing the clustered expression values of 50 DEGs between
CpG‐treated and untreated cell lines. (B) Volcano plots of HG3, MEC2,
and PCL12 as compared to [62]GSE226904; the X‐axis denotes the values
of Log[2]FC and the Y‐axis the values of Log[10] P value. Significant
genes are defined by |Log[2]FC| ≥ 1 and different P values: P value
between ≤ 0.05 and > 0.01 (green); P value between ≤ 0.01 and > 0.001;
(blue); P value ≤ 0.001 (violet). Unchanged genes are represented in
yellow. (A) Table reporting the number of genes analyzed and
differentially expressed is reported for each cell line as well as
patient's samples as a comparison (Panel C).
All the expressed genes were graphically represented with a Volcano
plot that shows global perturbation of the transcriptomes, including
up‐ and downregulated genes (Fig. [63]1B); as a comparison, we reported
the same graph with previously analyzed data of primary CLL patients'
samples, including IkBz‐high and IkBz‐low cases ([64]GSE226904)
[[65]19]. Volcano plots show an overall increased number of DEGs, as
genes with nominal P value < 0.01 and |Log[2]FC| ≥ 1, in IkBz‐high CpG
samples as compared to both IkBz‐low and CLL cell lines. Specifically,
as reported in Fig. [66]1C, HG3 had a total of 432 genes upregulated
and 347 genes downregulated; MEC2 and PCL12 had a less reactive profile
with 402 and 283 genes upregulated and 197 and 177 genes downregulated,
respectively.
Top 10 DEGs both upregulated and downregulated in each cell line are
indicated with their official gene symbol in each plot above the yellow
area; among them, the NFKBIZ gene encoding for IkBz protein emerged in
two out of the three cell lines analyzed (MEC2 and PCL12) with a
stringent P value ≤ 0.001 and |Log[2]FC| ≥ 1. In contrast, NFKBIZ was
not significantly upregulated in HG3 (highlighted below the yellow area
in the relative plot; Fig. [67]1B).
Intersection of the list of DEGs showed no common genes shared by all
the 3 cell lines; however, a limited set of common genes was observed
in selected pairs. In detail, both HG3 and MEC2 upregulate ZNF385C and
OSBPL1A and downregulate CD1D. The HG3 and PCL12 cell lines
co‐upregulate [68]AC106881.1, PLXDC1, and [69]AC090220.1. MEC2 and
PCL12 share the upregulation of ZC3H12A, [70]AL139011.1, and NFKBIZ.
Among all the upregulated noncoding and protein‐coding genes, NFKBIZ
was the only one to be previously described as induced by different
TLRs, including TLR9 [[71]13, [72]22]. To note, ZC3H12A (MCPIP1) is an
endoribonuclease that acts as feedback inhibitor of IL17 signaling by
favoring the degradation of different inflammatory mRNAs, including
NFKBIZ in T‐cells [[73]23]. These data suggest that ZC3H12A may
be involved in a feedback loop of TLR9 signaling; however, in our
cellular models, we could detect the transcripts of both NFKBIZ and its
‘negative regulator’ ZC3H12A at the same time.
Overall, from this gene expression analysis it is difficult to identify
the cell line most similar to the patients' samples in terms of TLR9
stimulation as quite few genes are shared. Even if the HG3 cell line
showed a higher number of DEG, it failed to upregulate NFKBIZ that is
the only bona fide TLR‐response gene of the list [[74]22].
CpG‐induced IkBz expression in the cell lines
In order to validate NFKBIZ expression and regulation in the CLL cell
lines, we performed real‐time PCR analysis at different time points
after CpG stimulation (4 and 24 h). First, we confirmed that low/no
induction of NFKBIZ was detected in HG3 cells. A statistically
significant induction was observed in MEC2 and PCL12 cells treated with
CpG for 4 h (Fig. [75]2A). We added to this analysis also MEC1 cell
line that was isolated from the same patient of the MEC2 and shares
several similar characteristics [[76]17]. MEC1 cells were also
responsive in terms of NFKBIZ mRNA induction similar to the sister
MEC2.
Fig. 2.
Fig. 2
[77]Open in a new tab
NFKBIZ mRNA and IkBz protein expression in cell lines. MEC1, MEC2,
PCL12, and HG3 cell lines were treated with CpG for 4 and 24 h and a
real‐time PCR analysis was performed for NFKBIZ (A) and IL6 (C)
expression. Data are reported as relative mRNA expression calculated
with
[MATH:
2−ΔΔCt :MATH]
and
[MATH: 2−ΔCt :MATH]
methods, respectively, with β‐Actin and TBP as endogenous reference
genes. All the data in Panels A and C are reported as relative
expression levels (mean ± SD). Two‐way ANOVA was performed followed by
Dunnett's multiple comparisons test for each cell line compared with
their respective controls; *P value < 0.05; **P value < 0.01; ****P
value < 0.0001. (B) One representative experiment out of four is
reported where the cell lines were stimulated with CpG at different
time points (4 and 24 h) and IkBz protein expression was assessed by
western blot analysis. β‐actin was used as loading control. Phospho‐ERK
(pERK) and total ERK were analyzed in the same samples as indicated.
Previous data of primary CLL patients' samples (both IkBz‐high and
IkBz‐low) reported a similar pattern of NFKBIZ mRNA induction at early
time points that decreased after 24 h [[78]13]. However, at protein
levels, only the IkBz‐high samples maintained IkBz induction after 24 h
of TLR9 stimulation. Therefore, we performed western blot analysis to
investigate whether and which cells maintained the capacity to induce
stable IkBz protein. As shown in Fig. [79]2B, IkBz protein is not
detectable in unstimulated cells while it is induced after CpG addition
to the cell culture. In detail, MEC2, and to a lesser extent PCL12,
expressed IkBz already at 4 h, and it was stable up to 24 h
(Fig. [80]2B shows one representative experiment out of four). MEC1
cells produced low levels of IkBz at 4 h, but the protein was almost
undetectable at 24 h. In contrast, HG3 cells did not show any IkBz
protein induction (Fig. [81]2B).
Next, we analyzed ERK activation as it was previously shown to be
constitutively activated in MEC1 and PCL12 cells as well as in a group
of CLL patients' cells rendering these cells anergic toward BcR
stimulation [[82]24]. ERK was constitutively phosphorylated in all the
cell lines analyzed. When MEC2 cells were stimulated with CpG,
induction of phospho‐ERK was detected at early time points in three out
of four independent experiments (Fig. [83]2B and data not shown). MEC1
cells were only partially responsive in terms of ERK phosphorylation.
On the contrary, ERK phosphorylation was reduced in PCL12 and HG3 cells
after 4 h of TLR9 stimulation in all the four replicates returning to
basal levels after 24 h (Fig. [84]2B and data not shown).
Overall, these data suggest that basal levels of ERK phosphorylation do
not impede TLR9 signaling in MEC2 and to a lesser extent MEC1;
surprisingly, in HG3 and PCL12 TLR9 stimulation was effective
but opposite and resulted in decreased levels of ERK phosphorylation.
IkBz is an atypical co‐transcription factor that controls inflammatory
genes that are induced during the so‐called secondary inflammatory
response, including the pro‐inflammatory cytokine interleukin‐6 (IL6).
Indeed, in CLL cells it can be induced by CpG after IkBz upregulation
[[85]25].
Transcriptomic analysis confirmed the significant induction of IL6 mRNA
in MEC2 and PCL12 but not in HG3 cells (Log[2]FC = 2.31 with P
value = 0.02 for MEC2; Log[2]FC = 3.05 with P value = 0.004 for PCL12).
To monitor IL6 mRNA levels over time, we performed real‐time PCR
analysis in MEC1, MEC2, PCL12, and HG3 cells before and after CpG
stimulation. To note, PCL12 and MEC2 expressed higher basal levels of
IL6 mRNA as compared to the others; however, MEC2 only responded to CpG
with highly variable levels of IL6 mRNA induction at 24 h
(Fig. [86]2C).
This biochemical analysis suggested that MEC2 and PCL12 but not HG3 may
resemble primary CLL samples, in particular the IkBz‐high subgroup.
MEC2 cells resemble primary IkBz‐high CLL samples
To understand whether and which cell lines better represent primary
patients' samples at global level, in terms of TLR9 signaling, we
compared the transcriptome profiles of HG3, MEC2, and PCL12 with the
ones of patients' leukemic cells ([87]GSE226904). To overcome the
limitation of the small size of the lists of DEGs to compare, we
exploited GSEA (Gene Set Enrichment Analysis) [[88]26, [89]27] to
extrapolate distinct gene sets from our patients' data and perform a
comparative analysis that could embrace overall concordance of response
to TLR9 stimulation beside the amplitude of each single FC. We
extracted from our patients' gene expression profiles ([90]GSE226904)
four different gene sets listing the upregulated and downregulated
genes in both IkBz‐high and IkBz‐low samples. Next, we compared the
cell line profiles of control and stimulated samples. This examination
resulted in more significant values of similarity for MEC2 as assessed
by high Normalized Enrichment Score (NES) and low false discovery rate
(FDR); when compared to IkBz‐high upregulated genes, MEC2 showed a
NES = 2 and FDR = 0.05 while HG3 was the less represented
(Fig. [91]3A).
Fig. 3.
Fig. 3
[92]Open in a new tab
Gene Set Enrichment Analysis (GSEA) and Metascape analysis of DEGs. (A)
We created specific gene sets from lists of DEGs in IkBz‐high samples
([93]GSE226904), and we used them to perform enrichment analysis of the
cell line transcriptomes. Enrichment plots for each cell line against
upregulated (UP) or downregulated (DOWN) gene sets are reported as
indicated. In each panel, the green curve represents the running
enrichment score and the black bars indicate the positions of the gene
set hits on the rank‐ordered list in GSEA. The highest signal‐to‐noise
values are indicated with red color, while blue indicates the lowest
ones. Significant gene sets are defined by |NES| ≥ 1.5 and FDR ≤ 0.25
shown inside the plot. For paired contrast ‘CpG‐stimulated vs ctrl’, we
calculated the DEGs as genes with |Log[2]FC| ≥ 1 and nominal P
value ≤ 0.05, and with those lists, we performed enrichment analysis
with Metascape. (B) Circos plot showing the DEGs overlapping among the
lists of upregulated genes. (C) Heat map showing the top 20 enriched
pathways among the lists of DEGs identified in the meta‐analysis. The
heat map box is colored by their P values, and gray box indicates the
lack of enrichment for that term in the corresponding gene list against
KEGG, REACTOME, and canonical pathways. (D) Enrichment analysis against
transcriptional regulatory network collection of gene set TRRUST was
performed, and the heat map shows the enriched terms among the lists of
DEGs identified in the meta‐analysis for each cell line and the
[94]GSE226904 patients' samples as indicated.
To further enlarge the spectrum of analysis and to capture subtle
similarities, we selected genes with a |Log[2]FC| ≥ 1 and a P
value < 0.05 and we performed a comparative analysis of both cell lines
and patients' samples. The three cell lines shared only a limited
number of genes represented by the purple lines in the Circos plot
(Fig. [95]3B). Next, to explore the global perturbations in terms of
TLR9‐mediated signaling activation, we performed pathway enrichment
analysis with Metascape [[96]28]. Metascape allows to perform
enrichment analysis of multiple gene lists at the same time with the
advantage of performing a concomitant comparative analysis of all the
results. In particular, the investigation of the pathways involved
showed that MEC2 cells are the only ones sharing some similarity with
both categories of patients' samples, including different
inflammatory/cytokine pathways (Fig. [97]3C). As expected, the two
groups of primary leukemic cells share an inflammatory response, but
IkBz‐positive samples only show stress‐related and RNA metabolism
signatures [[98]19].
In parallel, the enrichment analysis was performed against TRRUST
(Transcriptional Regulatory Relationships Unraveled by Sentence‐based
Text mining) curated gene sets, including gene lists regulated by
specific transcription factors; this examination resulted in MEC2 as
the only profile shared with CLL primary samples. Genes regulated by
NFKB1 and RELA prototypic inflammatory factors are enriched in MEC2 and
CLL (both subgroups) while SP3 emerged in MEC2 and IkBz‐low samples
(Fig. [99]3D).
In conclusion, MEC2 and PCL12 cell lines showed a dampened response to
TLR9 stimulation as compared to primary patients' samples. On the
contrary, HG3 showed a higher number of DEGs; however, from pathway
analysis they appeared very distant from primary leukemic cells.
Overall, among the cell lines analyzed, MEC2 cell line best
recapitulates the characteristics of primary CLL patient cells in terms
of TLR9 signaling and IkBz expression; however, we cannot propose them
as a ‘representative cell line’ for all the patient cells.
Notwithstanding the lower response of MEC2 in terms of DEGs, advanced
enrichment analysis called attention to a similar molecular fingerprint
that pointed to this cell line as the most appropriate preclinical
model to study TLR stimulation in CLL.
Conflict of interest
The authors declare no conflict of interest.
Peer review
The peer review history for this article is available at
[100]https://www.webofscience.com/api/gateway/wos/peer‐review/10.1002/2
211‐5463.13726.
Author contributions
MiM and IS designed the research, performed the experiments and
bioinformatic and statistical analysis, and wrote the manuscript; MEM
participated in experimental planning and performed experiments and
data analysis; MR analyzed the RNA‐sequencing data and supervised the
bioinformatic analyses; MaM designed and supervised the research and
wrote the manuscript.
Acknowledgements