Abstract
The methyltransferase Polycomb Repressive Complex 2 (PRC2), composed of
EZH2, SUZ12, and EED subunits, is associated with transcriptional
repression via tri-methylation of histone H3 on lysine 27 residue
(H3K27me3). PRC2 is a valid drug target, as the EZH2 gain-of-function
mutations identified in patient samples drive tumorigenesis. PRC2
inhibitors have been discovered and demonstrated anti-cancer efficacy
in clinic. However, their pharmacological mechanisms are poorly
understood. MAK683 is a potent EED inhibitor in clinical development.
Focusing on MAK683-sensitive tumors with SMARCB1 or ARID1A loss, we
identified a group of PRC2 target genes with high H3K27me3 signal
through epigenomic and transcriptomic analysis. Multiple
senescence-associated secretory phenotype (SASP) genes, such as GATA4,
MMP2/10, ITGA2 and GBP1, are in this group besides previously
identified CDKN2A/p16. Upon PRC2 inhibition, the de-repression of SASP
genes is detected in multiple sensitive models and contributes to
decreased Ki67+, extracellular matrix (ECM) reorganization, senescence
associated inflammation and tumor regression even in CDKN2A/p16
knockout tumor. And the combination of PRC2 inhibitor and CDK4/6
inhibitor leads to better effect. The genes potential regulated by PRC2
in neuroblastoma samples exhibited significant enrichment of ECM and
senescence associated inflammation, supporting the clinical relevance
of our results. Altogether, our results unravel the pharmacological
mechanism of PRC2 inhibitors and propose a combination strategy for
MAK683 and other PRC2 drugs.
Subject terms: Targeted therapies, Senescence
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Introduction
Polycomb Repressive Complex 2 (PRC2) is the sole histone H3 lysine 27
(H3K27) methyltransferase identified from yeast to mammals. Through
binding to promoter and catalyzing the formation of trimethylated H3K27
(H3K27me3), PRC2 represses transcription of target genes and plays
critical roles in embryonic development and adult stem cell maintenance
in multiple lineages [[44]1, [45]2]. The core PRC2 complex is composed
of three subunits: catalytic subunit EZH2 or EZH1, scaffolding subunit
SUZ12 and EED that allosterically activates EZH2 upon binding to
H3K27me3 [[46]3, [47]4]. The aberrant expression or mutation of PRC2
components has been identified in multiple diseases, especially cancers
[[48]5, [49]6]. Gain-of-function (GoF) mutations of EZH2 have been
reported in B-cell lymphoma, melanoma and other cancers [[50]1].
Knock-in of the GoF mutation EZH2-Y641F in mouse led to the occurrence
of spontaneous lymphoma, demonstrating its onco-driver activity
[[51]7]. In addition, PRC2 epigenetically counteracts the SWI/SNF
complex, which mobilizes nucleosomes to facilitate transcription.
Somatic loss of SWI/SNF subunits in cancer, such as SMARCB1 and
SMARCA4, lead to the functional dependence on PRC2 [[52]8]. Knockout of
SMARCB1 in mice causes tumor formation with 100% penetrance, and these
tumors were highly dependent on EZH2 [[53]9, [54]10].
EZH2 and EED inhibitors have been discovered and demonstrated efficacy
in multiple cancer models [[55]11–[56]14]. EZH2 inhibitors target EZH2
directly, while EED inhibitors bind EED and inhibit PRC2
allosterically. We previously reported the discovery of EED inhibitor
EED226 [[57]12], and the optimized inhibitor MAK683 is in clinical
development ([58]NCT02900651) [[59]15]. The EZH2 inhibitor EPZ6438 has
been approved for treatment of follicular lymphoma and epithelioid
sarcoma [[60]16, [61]17]. Mechanistically, EZH2 depletion/inhibition
de-represses cell cycle inhibitor p21^CIP1/WAF1 (p21 for short)
encoding gene CDKN1A and induces apoptosis in lymphoma [[62]18–[63]20].
Similarly, p16^INK4A (p16 for short) encoding gene CDKN2A is a target
of EZH2/PRC2 [[64]21–[65]23] in fibroblast, mesenchymal stem cell
(MSC), pancreatic beta-cell and certain cancers [[66]24–[67]30].
However, it is unclear whether p16 de-repression is essential or
sufficient for the antitumor efficacy of PRC2 inhibitors.
Cellular senescence is a heterogenous stress response, in which cell
cycle is permanently arrested but cell is metabolically alive [[68]31].
Different stresses, such as telomere shortening, oncogene expression,
epigenetic perturbation, or anti-cancer therapies, may trigger
senescence. Although there aren’t senescence-unique markers, senescent
cells exhibit multiple characteristics [[69]32]. These include
irreversible cell cycle arrest by expression of p16 and/or p21,
appearance of senescence-associated beta galactosidase (SA-β-gal)
activity, and the release of chemokines, growth regulators and
extracellular matrix (ECM) components and proteases, termed
senescence-associated secretory phenotype (SASP) [[70]31, [71]33].
Among them, SASP is critical for senescence local spreading, but not
well-characterized as SASP factors often vary depending on cell lineage
and senescence inducers [[72]34]. Simultaneous detection of multiple
features confirms the occurrence of cellular senescence.
Here, we focused on the molecular pharmacological mechanism of PRC2
inhibitors and dissected the critical target genes induced by EED
inhibitor MAK683 in sensitive cancer cells deficient in SMARCB1 or
ARID1A. PRC2 inhibition by MAK683 induces de-repression of not only
CDKN2A/p16, but also GATA4, HLA-B, MMP2/10, ITGA2 and GBP1 with high
H3K27me3 around promoters. As p16 KO does not hamper the de-repression
of SASP genes, they are independently regulated by PRC2. The
de-repression of HLA-B, ITGA2 and other SASP genes by MAK683
potentiates senescence associated inflammation and macrophage
infiltration and contributes to the full efficacy of PRC2 inhibitors.
Results
MAK683 is a highly potent PRC2 inhibitor and blocks cancer cell proliferation
The PRC2 inhibitors MAK683 and EED226 bind EED directly and inhibit
both EZH1/PRC2 and EZH2/PRC2 (Fig. [73]1a) [[74]12, [75]15]. We
acquired these two compounds together with EPZ6438, an FDA-approved
EZH2 inhibitor, and compared them in cellular experiments. First, they
all decreased H3K27me3 dose-dependently in HeLa cell. The IC50 of
MAK683 was 1.014 nM, the lowest among them (Fig. [76]1b, c). The IC50s
of EED226 and EPZ6438 were 209.9 nM and 22.47 nM, respectively. Their
selectivity is high, as only methylation and acetylation of H3K27 were
altered (Fig. [77]1d and Supplementary Fig. [78]1a). MAK683 removed
more H3K27me2/me3 comparing with EPZ6438 at the same concentration,
likely due to its EED-binding mechanism or higher potency. Then, they
were tested in anti-proliferation of lymphoma cell WSU-DLCL2 (WSU) with
GoF mutation EZH2-Y641F [[79]11, [80]35]. These compounds inhibited the
proliferation of WSU with IC50s of 35.86 nM for EED226, 14.86 nM for
EPZ6438 and 1.153 nM for MAK683 (Fig. [81]1e).
Fig. 1. MAK683 is a potent PRC2 inhibitor blocking proliferation of multiple
cancer cells.
[82]Fig. 1
[83]Open in a new tab
a Chemical structure of MAK683. b Inhibition of cellular H3K27me3
dose-dependently by MAK683, EED226 and EPZ6438 in HeLa cell after 72 hr
of treatment. c Quantification of data in (b) and two other repetitive
experiments and fit into the dose-responsive curves of H3K27me3
inhibition (n = 3; mean ± s.d.). IC50s were calculated using PRISM. The
IC50s for MAK683, EED226 and EPZ6438 are 1.014 nM, 209.9 nM, and
22.47 nM respectively. d Western blots showing modulation of histone H3
methylations by EPZ6438 and MAK683 using HeLa cell lysates treated with
indicated concentrations of EPZ6438 and MAK683 for 72 h. e
Dose-dependent inhibition of the proliferation of WSU-DLCL2
(EZH2-Y641F) cell after 9 days of treatment with the indicated
compounds at 6-dose points. Viable cells were counted every 3 days in
the presence of the indicated compounds and results were plotted and
IC50s were calculated using PRISM (n = 3; mean ± s.d.). The IC50s for
MAK683, EED226, and EPZ6438 are 1.153 nM, 35.86 nM and 14.86 nM,
respectively. f Proliferation of G401 cells. Viable cells were counted
every 3 days in the presence of MAK683 at the indicated concentrations,
and results were plotted on a logarithmic scale (n = 3; mean ± s.d.). g
Inhibition of the proliferation of multiple cells including G401, G402,
A204, A2780, Hs700T, RD, HeLa, and MCAS after 15 days of MAK683
treatment. Viable cells were counted every 3 days in the presence of
MAK683 at the indicated concentrations, and results were normalized to
the control samples (DMSO as 100%) of respective cells and then plotted
on a logarithmic scale (n = 2 or 3; mean ± s.d.). h Inhibition of the
proliferation of G401, A2780, RD, and HeLa after 15 days of EPZ6438
treatment. Viable cells were counted every 3 days in the presence of
EZP6438 at the indicated concentrations, and results were expressed
similarly as in (g). (n = 2; mean ± s.d.). i Western blots showing
modulation of histone H3K27 methylations and acetylation by EPZ6438 and
MAK683 in G401 and RD cells treated with indicated concentrations of
compounds. All experiments were repeated for more than two times.
We then examined the anti-proliferation of MAK683 in a panel of cancer
cells. G401, G402 and A204 are malignant rhabdoid tumor (MRT) cells
with SMARCB1 deficiency [[84]22]. They were sensitive to MAK683
treatment (Fig. [85]1f, g). Ovarian cancer cell A2780 with
ARID1A-deificiency and pancreatic cancer cell Hs700T with
SMARCA4-deficiency were also moderately sensitive to MAK683. EPZ6438
similarly inhibited the proliferation of A2780, while RD, HeLa and MCAS
cells were not sensitive to PRC2 inhibition by MAK683 or EPZ6438 (Fig.
[86]1g, h) [[87]36]. The growth plot of these sensitive cells presented
a slow inhibition by MAK683, a typical response to epigenetic
inhibitors (Supplementary Fig. [88]1b-d) [[89]11, [90]14, [91]22]. The
proliferation of HeLa and RD was not affected at all, even though the
H3K27me3 level was dramatically decreased by MAK683 or EPZ6438 (Fig.
[92]1b, g, and i). It was hypothesized that the increase of H3K27ac
after H3K27 methylation removal is an important factor affecting
sensitivity to PRC2 inhibitors [[93]4, [94]37]. Here, the increase of
H3K27ac was observed in both sensitive G401 and refractory RD (Fig.
[95]1i). So, adding H3K27ac at the right position may be critical.
Together, EPZ6438 and MAK683 are potent PRC2 inhibitors, and they
inhibit proliferation of tumor cells with EZH2-GoF mutation or
deficiency of SWI/SNF complex. We mainly used MAK683 for PRC2
inhibition in the following studies.
A signature of high H3K27me3 marks genes derepressed by PRC2 inhibition
Next, we seek to understand what happens in sensitive tumor after PRC2
inhibition. We performed RNA-seq on three sensitive cells G401, G402
and A2780, and one refractory cell RD. Hundreds of genes exhibited
upregulation by MAK683 treatment in the sensitive cells, while only 39
genes showed mild increase in RD (Fig. [96]2a and Supplementary Fig.
[97]2a). So, transcriptional activation is a specific event in
sensitive cells. To further dissect the epigenomic changes associated
with PRC2 inhibition, we selected G401 for profiling studies including
Whole Genome Bisulfite Sequencing (WGBS), H3K4me3 and H3K27me3
chromatin immunoprecipitation-sequencing (ChIP-seq) and assays for
transposase-accessible chromatin (ATAC)-seq. Massive genome-wide
depletion of H3K27me3 signal was observed (Fig. [98]2b), while overall
DNA methylation pattern, H3K4me3 signal and chromatin opening around
transcription start site (TSS) were not significantly changed (Fig.
[99]2b and Supplementary Fig. [100]2b, c).
Fig. 2. Multi-omics integrated analysis suggests that H3K27me3-high genes are
direct PRC2 target genes derepressed by PRC2 inhibition.
[101]Fig. 2
[102]Open in a new tab
a Volcano plot showing the differential expression genes (DEGs) of G401
and RD cell after DMSO, MAK683 treated for 3 days. Red shows
up-regulated after MAK683 treatment (log2 fold change ≥ 1 and p adjust
≤ 0.05) and blue indicates down-regulated after MAK683 treatment (log2
fold change ≤ −1 and p adjust ≤ 0.05) unless otherwise noted. b
Composite H3K27me3 profile and H3K4me3 profile around transcripts start
sites (TSS) in G401 cell. c Heat map of log2 mRNA fold change levels,
mRNA expression levels, H3K27me3 modification levels, H3K4me3
modification levels and Chromatin accessibility levels in G401 cell. d
Box plots of log2 mRNA fold change levels, H3K4me3 modification levels,
DNA methylation levels and chromatin openness levels between different
clustering types in G401 cell. The whiskers of the box plot extend to
1.5 times the interquartile range unless otherwise noted. e Box plots
of H3K27me3 modification levels between different clustering types in
G401 cell. f Composite H3K27me3 profile and H3K4me3 profile around TSS
in different clustering types in G401 cell. g Venn diagram showing the
overlap of type 5 genes from clustering (1082 genes) with upregulated
DEGs from RNA-seq analysis (997 genes). The genes lie in both classes
include multiple typical PRC2 target genes in ES cells (indicated by
red line) and senescence-associated secretory factors (indicated by
blue line). h Pathway enrichment analysis of the 624-gene class from
the (g).
When differentially expressed genes (DEG, Log2Fold Change > = 1 and p
adj < 0.05) were laid out by fold change (FC), there was a trend that
the highly upregulated genes have higher H3K27me3 signal in DMSO sample
(Fig. [103]2c). Next, to find out the epigenetic features of these PRC2
inhibition-upregulated genes, we performed unsupervised clustering
using mRNA expression-FC, DNA methylation, H3K4me3 and ATAC-seq data.
This analysis gave 5 different gene types, each represented a different
epigenetic characteristic (Fig. [104]2d). For example, type 2 showed
high DNA methylation, type 4 showed high H3K4me3 level, while type 5
enriched most of the upregulated genes (Fig. [105]2d). Interestingly,
the type 5 genes had significantly higher H3K27me3 signal than other
types at basal state (Fig. [106]2e). By examining the average
distribution of H3K27me3 and H3K4me3 from −3 kb to +3 kb, we found
H3K27me3 of type 5 genes showed a clear peak around TSS (Fig. [107]2f).
As the clustering analysis used G401 data, we examined RNA-seq data of
A2780 and found type 5 genes were also significantly upregulated in
MAK683-treated A2780 (Supplementary Fig. [108]2d). So, the type 5 genes
are likely direct targets of PRC2. Overlapping of type 5 genes with the
upregulated DEGs in G401 gave a list of 624 genes, which included many
well-characterized PRC2 targets such as CDKN2A/p16, HLA-B, TBX3, HOXD1,
GATA3, and GATA4 (Fig. [109]2g). Majority of these genes (578 out of
624) were also H3K4me3 positive (Supplementary Fig. [110]2e, f). In the
enrichment analysis, the top 5 pathways highlighted ECM and
proteoglycan. The enriched genes included COL4A1, COL4A2, COL4A4,
COL4A5, FBN2, and LAMB1, which are typical basement membrane markers
(Fig. [111]2h) [[112]38]. Considering PRC2 represses differentiation in
development [[113]39] and the origin of MRT is neural crest [[114]40],
these enriched pathways and genes suggest PRC2 inhibition in tumor
induces epithelial differentiation and ECM reorganization.
PRC2 inhibition induces multiple features of cellular senescence in sensitive
tumors
As upregulated genes by PRC2 inhibitors are likely the drivers for
tumor sensitivity, we focused on the transcriptome data and performed
Gene Set Enrichment Analysis (GSEA). “Regulation of senescence pathway”
and “SASP” were significantly enriched in MAK683-treated samples (Fig.
[115]3a and Supplementary Fig. [116]3a) [[117]41]. There were 48 genes
commonly upregulated in G401, G402 and A2780 (Supplementary Fig.
[118]3b), and CDKN2A/p16 and HLA-B were at the top of this gene heatmap
(Supplementary Fig. [119]3c). Many genes exhibiting the signature of
high H3K27me3 and positive H3K4me3 decorations on promotor were
clustered in type 5 gene group (Fig. [120]3b). Surprisingly, in
addition to CDKN2A/p16, many of these 48 genes were annotated as
upregulated genes in cellular senescence (red asterisk in Supplementary
Fig. [121]3c, SeneQuest database) [[122]32].
Fig. 3. Senescence induction is a shared phenotype in multiple
MAK683-responsive solid cancer cells in vitro and in vivo.
[123]Fig. 3
[124]Open in a new tab
a GSEA of RNA-seq data from G401 cell with DMSO or MAK683 treatment as
shown in Fig. [125]2a revealing the enrichment of senescence-associated
secretory phenotype (SASP). b H3K27me3 and H3K4me3 ChIP-seq tracks and
ATAC-seq tracks at p16/CDKN2A, MMP2 and BMP6 loci in G401 cells treated
with DMSO or MAK683. Green highlights indicated genomic regions around
TSS. c Representative senescence-associated β-galactosidase staining
(SA-β-gal, blue) of G401, G402, A2780 and RD cells treated with DMSO or
MAK683 at the indicated concentrations for 9 days. RD cell is not
sensitive to MAK683 treatment and is negative for SA-β-gal. Scale bars
represent 50 μm. Representative images of more than two independent
experiments in the indicated cells. d Heat map showing the expression
fold changes of the indicated genes in MAK683 treated G401, G402, A2780
and RD cells assessed by RT-qPCR. These genes were selected based on
Fig. [126]2f and Supplementary Fig. [127]3c (SASP heat map). e Bar
graph presenting the cell cycle changes analyzed by FACS after
treatment with DMSO or 3 μM of MAK683 for 3 days (n = 3; mean ± s.d.).
The P values were determined by Multiple t test (*, p < 0.05; **,
p < 0.01; ****, p < 0.0001; ns, not significant). f Growth curve of
subcutaneous G401 xenograft tumors in mice treated with MAK683 in a
suspension formulation through oral administration (po) once daily (qd)
for 25 days. On day 25, tumor tissues were collected at 4 h post
treatment for molecular analysis. Data are shown as mean ± s.e.m.
(n = 6; **, p < 0.01). g Representative H3K27me3, Ki67 and SA-β-gal
staining of the tumor xenograft collected from the study in (f). Scale
bars, 20 μm. Quantification of the H3K27me3 positive (h), Ki-67
positive (i) and SA-β-gal positive (j) percentage. Mean ± s.d. of
positively stained cell percentage (Ki67 and H3K27me3) or positively
stained area (SA-β-gal) are shown. P values were determined by Multiple
t test (**, p < 0.01; ***, p < 0.001; ****, p < 0.0001). k Quantitative
PCR analysis of gene expression changes in tumor samples after vehicle
or MAK683 dosing. RNA was harvested from the tumor xenograft collected
from the study in (f) (n = 6; mean ± s.d.). (*, p < 0.05; **,
p < 0.01). All experiments were repeated for more than two times.
Usually, multiple features of cellular senescence co-exist upon
senescence induction [[128]32]. Indeed, in addition to SASP
upregulation, MAK683 treatment enhanced SA-β-gal activity in sensitive
tumor cells (Fig. [129]3c and Supplementary Fig. [130]3d, e). GATA4 is
a transcriptional factor linked to senescence and SASP [[131]42], and
it is also a PRC2 target gene in ES cells [[132]43]. Using quantitative
PCR (qPCR), we confirmed the strong upregulation of CDKN2A/p16, HLA-B,
GATA4 and other SASP genes, including BMP6, CCL2, CCL25 and MMP2 in
multiple sensitive cells (Fig. [133]3d). In MAK683-induced senescence,
we also observed significant G0/G1 cell cycle arrest and increase of
p16 protein (Fig. [134]3e and Supplementary Fig. [135]3f). Moreover,
the CDKN2A/p16 promoter exhibited high H3K27me3 signal in ChIP-qPCR of
G401, which strongly diminished upon MAK683 treatment. Meanwhile,
H3K27ac and H3K4me3 at the same regions were increased (region 2 and 3,
Supplementary Fig. [136]3g), confirming PRC2 directly regulates
CDKN2A/p16.
Next, we went on to confirm the cellular observation in G401 xenograft.
MAK683 showed good efficacy in tumor growth inhibition (Fig. [137]3f).
By 25 days treatment, the tumor volume T/C% was 30.55%, and the TGI
reached 67.20%. MAK683 at 100 mg/kg daily was safe, as the animals’
body weight was unaffected (Supplementary Fig. [138]3h). H3K27me3 was
significantly decreased in MAK683-treated tumors, assuring PRC2
inhibition (Fig. [139]3g, h). MAK683-treated tumors exhibited
significantly reduced Ki-67 and increased SA-β-gal activity (Fig.
[140]3g–j), in agreement with the cellular observation. The mRNA level
of CDKN2A/p16 and protein levels of p16 were both significantly
upregulated (Fig. [141]3k and Supplementary Fig. [142]3i). Moreover,
the typical SASPs including GATA4, CCL2, IL6 and IL1B were all
significantly upregulated, and HLA-B, BMP6 and MMP2 showed the trend of
upregulation (Fig. [143]3k). So, multiple features of senescence were
induced by PRC2 inhibition in tumor xenograft.
SASP gene-upregulation by PRC2 inhibition is independent of p16
CDKN2A/p16 was considered a critical PRC2 target for proliferation
blockage upon PRC2 inhibition in many cancers including nasopharyngeal
carcer, breast cancer, leukemia, and ovarian cancer [[144]44–[145]47].
However, the requirement of p16 in these circumstances has not been
studied yet. We observed the upregulation of SASPs and SA-β-gal
activation in addition to CDKN2A/p16 upregulation. To clarify their
individual roles, we constructed CDKN2A/p16 knockout (KO) G401 cells
using Cas9-CRISPR method (Supplementary Fig. [146]4a, b). Two
independent clones with confirmed genomic sequence-change and p16
protein-loss were subjected to proliferation, cell cycle and SA-β-gal
analysis. The p16 deficiency did not alter the level of H3K27me3, while
the p16 KO cells were partially resistant to MAK683-induced cell cycle
arrest and proliferation blockage (Fig. [147]4a, b and Supplementary
Fig. [148]4c). Interestingly, they also lost SA-β-gal activation by
MAK683 (Supplementary Fig. [149]4d). However, the MAK683-induced SASP
factors, such as MMP2, BMP6, IGFBP3 and IGFBP5, were not affected by
p16 KO (Fig. [150]4c). CDKN2A/p16 KO clone in A2780 showed similar
results and SASPs were still significantly upregulated by MAK683 (Fig.
[151]4d and Supplementary Fig. [152]4e–h). So, the causal link between
PRC2 inhibition and SASP upregulation in the sensitive cells is
independent of p16.
Fig. 4. SASP upregulation by PRC2 inhibition is independent of p16.
[153]Fig. 4
[154]Open in a new tab
a Western blotting analysis showing the successful knockout of p16 in
KO#2 and KO#8 cell clones, and the upregulation of p16 protein levels
in MAK683 treated G401 cell are shown as positive control. Inhibition
on H3K27me3 by MAK683 in all three cells is similar. b Proliferation of
G401, p16 KO#2 and p16 KO#8 cells. Viable cells were counted every 3
days in the presence of MAK683 at 1 μM, and results from three repeat
experiments were plotted on a logarithmic scale. Quantitative PCR
analysis of the gene expression changes in G401 or p16 KO#2 cells (c)
and A2780 or p16 KO#23 cells (d) with DMSO or MAK683 at 3 μM for 6 days
(mean ± s.d.). Out of the two p16 KO clones G401, KO#2 cell is used in
the studies of the following panels and labeled as p16 KO. e Antitumor
activity of MAK683 in a suspension formulation in subcutaneous G401 and
p16 KO xenograft tumors after continuous treatment for 46 days (n = 6;
mean ± s.e.m.). The red arrow indicates the time point dosing starts.
On day 46, tumor tissues were collected at 4 h post treatment for
molecular analysis. f Representative Ki67, H3K27me3, and SA-β-gal
staining of the tumor xenograft collected from the study in (e). Scale
bars, 20 μm. Bar graphs showing the quantification of the Ki67 (g),
H3K27me3 (h) and SA-β-gal (i) positivity. Mean ± s.d. of positively
stained cell percentage (Ki67 and H3K27me3) or positively stained area
(SA-β-gal) are shown. P values were determined by Multiple t test. j
Quantitative PCR analysis of gene expression changes in G401 or p16 KO
tumor samples after vehicle or MAK683 dosing. RNA was harvested from
the tumor xenograft collected from the study in (e) (n = 6;
mean ± s.d.). All experiments were repeated for more than two times.
Next, we performed in vivo xenograft study. The p16 KO G401 xenograft
grew more robustly than WT xenograft (Fig. [155]4e, comparing the two
vehicle groups). As MAK683 treatment lasted longer in this study, the
treatment effectively blocked WT tumor growth (T/C% = 7.21%, TGI
reached 91.25% by treatment endpoint). Furthermore, the p16 KO
xenograft also responded to MAK683 treatment (T/C% = 35.81%, TGI
reached 54.18% by treatment endpoint) (Fig. [156]4e). The Ki67
positivity correlated well with tumor size, higher in p16 KO vehicle
than in WT vehicle group and was reduced by MAK683 in both WT and p16
KO tumors (Fig. [157]4f–h). SA-β-gal signal was increased by MAK683
treatment in WT tumors but was unchanged in p16 KO xenografts (Fig.
[158]4f, i), which is consistent with the cellular observation
(Supplementary Fig. [159]4d). The upregulation of classical SASPs
including MMP2, MMP10, BMP6, IGFBP3, IGFBP5 and IL1B was statistically
significant and unaffected by p16 KO, and the same trend for CCL2 was
observed (Fig. [160]4j). Together, these results suggest a class of
SASP genes are directly regulated by PRC2. They are upregulated by PRC2
inhibition independent of p16 and contribute to tumor repression by
PRC2 inhibitors.
PRC2 inhibition promotes tumor differentiation, senescence and immune
infiltration in vivo
As the p16 KO xenograft still responded to MAK683, we performed RNA-seq
using the samples from Fig. [161]4e to dissect the changes by PRC2
inhibition. Multiple pathways were significantly enriched from GSEA in
MAK683-treated tumors, such as ECM constituents, synaptic membrane
components and basement membrane pathways (Fig. [162]5a, b and
Supplementary Fig. [163]5a, b), consistent with the results of cellular
multi-omics analysis (Fig. [164]2h). The enrichment of pathways “neural
crest cell differentiation” and “cell differentiation in kidney” likely
reflected the neural crest origin of MRT [[165]40]. Differentiation
after EZH2 inhibition has been reported in lymphoma [[166]1, [167]11].
Thus, differentiation induction may be a general theme after PRC2
inhibition.
Fig. 5. PRC2 inhibition promotes tumor cell differentiation,
senescence-associated inflammation and immune infiltration in vivo.
[168]Fig. 5
[169]Open in a new tab
GSEA of RNA-seq data from the G401 (a) or p16 KO (b) tumor xenograft
collected in the study in Fig. [170]4E, showing the enrichment of ECM,
type I IFN and antigen processing and presentation (APP) gene
signatures, and cell differentiation after PRC2 inhibition. c
Quantitative PCR analysis of the expression changes of IFN-I response
genes in G401 or p16 KO tumor samples after vehicle or MAK683 dosing.
RNA was harvested from the tumor xenograft collected from the study in
Fig. [171]4e (n = 6; mean ± s.d.). d Representative ITGA2 and F4/80
staining of G401 or p16 KO tumor xenograft after vehicle or MAK683
dosing collected from the study in Fig. [172]4E. Scale bars represent
20 μm. Bar graphs showing the quantification of the ITGA2 positive
percentage (e), GBP1 positive percentage (f) and F4/80 positive
percentage (g). Mean ± s.d. of positively stained cell percentage or
area are shown. P values were determined by Multiple t test. h
Inhibition of the proliferation of G401 WT or p16 KO cells by
combination of MAK683 and CDK4/6 inhibitor Palbociclib treatment.
Viable cells were counted every 3 days in the presence of 50 nM of
MAK683, 1 nM of Palbociclib, or combo of them, and results were
normalized to DMSO samples (n = 4; mean ± s.d.). P values were
determined by Multiple t test (*, p < 0.05; **, p < 0.01; ***,
p < 0.001). i Box plot of mRNA expression levels (log2 (RPM)) of EZH2
in 498 neuroblastoma samples ([173]GSE62564). The quarter of samples
with the high level of EZH2 expression (125 samples) were designated as
high EZH2 group, and the quarter of samples with the low level of EZH2
expression (126 samples) were designated as low EZH2 group. j Box plots
of log2 mRNA fold change (FC, calculated as shown in Supplementary Fig.
[174]5e) between different clustering types (same gene lists of every
type as in Fig. [175]2d) in neuroblastoma data. P values were
determined by Kruskal nonparametric test. All experiments were repeated
for more than two times.
Nonclassical SASP factors including ECM components have been recognized
as critical players in senescence [[176]31, [177]33]. SASP pathway and
ECM were both significantly upregulated in MAK683-treated tumors (Fig.
[178]5a, b). More importantly, pathways related to innate immunity were
highly enriched in MAK683-treated WT and p16 KO tumors, such as type I
IFN pathway, antigen processing and presentation (APP) of endogenous
antigen (Fig. [179]5a, b and Supplementary Fig. [180]5a, c), confirming
these functional outputs of PRC2 inhibition is independent of p16.
Many ECM, APP, IFN-I and SASP genes were type 5 genes with high
H3K27me3 signal and upregulated by MAK683 treatment, including ITGA2,
COL4A5, DSG2, FBN1, FAS, GBP1 and FRAS1 (Supplementary Fig. [181]5a, c
and d). qPCR analysis confirmed their upregulation in MAK683-treated WT
and p16 KO tumors (Fig. [182]5c and Supplementary Fig. [183]5b).
Senescent MSCs upregulated ECMs included ITGA2, FBN1, COL1 and COL4
[[184]48]. ITGA2 and GBP1 proteins were significantly increased in
MAK683-treated WT and p16 KO tumors (Fig. [185]5d–f). Interestingly,
ITGA2 was a senescence associated inflammatory factor in colorectal
cancer [[186]49, [187]50], while GBP1 was an interferon-responsive gene
in innate immunity [[188]51]. SASPs facilitated macrophage and other
immune cell infiltration to clear senescence cells in cancer therapy
and tissue repairing [[189]52, [190]53]. We detected the mouse
macrophages infiltration in tumor slices and found F4/80 signal was
indeed high in MAK683-treated WT and p16 KO tumors (Fig. [191]5d, g).
As p16 blocks cell cycle through inhibiting CDK4/6, combination of
MAK683 and CDK4/6 inhibitor Palbociclib showed better proliferation
inhibition in p16 KO cell (Fig. [192]5h). Altogether, PRC2 inhibition
in sensitive tumor induced significant upregulation of p16, ECM and
SASP factors, and promoted macrophage infiltration.
Next, we seek validation in human samples with a data set of 498
neuroblastoma cases ([193]GSE62564) [[194]54], as the origin of
neuroblastoma was also neural crest cells [[195]40] and neuroblastoma
is sensitive to PRC2 inhibitor [[196]55]. First, using EZH2 expression
to rank samples, we identified a group of 126 samples with low EZH2 and
a group of 125 samples with high EZH2 (Fig. [197]5i). Then we
calculated gene expression FC for all genes using formula in
Supplementary Fig. [198]5e and got 3006 up-DEGs through low EZH2 group
vs high EZH2 group comparison. Further pathway analysis showed
enrichment of neuronal function (green), cell-cell adhesion (brown) and
interferon response pathways (red, Supplementary Fig. [199]5f) in
up-DEGs class, which were consistent with MAK683-treated cells and
xenografts (Figs. [200]2h, [201]5a, b). Meanwhile, we examined the
log2FC of the 5 types of genes from clustering (Fig. [202]2d).
Similarly, the type 5 genes showed significant higher level in
neuroblastoma with low EZH2 (Fig. [203]5j). This is a relevant piece of
evidence supporting PRC2 may regulate SASPs and IFN pathways in human
neuroblastoma.
Discussion
Deciphering the molecular pharmacological mechanisms of a target
therapy is crucial for its appropriate clinical application and
maximizing the benefit it may bring to patients. In this study, we
addressed a fundamental question for PRC2 inhibitors, how do they work
in responsive tumors. Using MAK683 as an example, our results indicate
there are at least three independent molecular responses upon PRC2
inhibition and H3K27me3 loss. Firstly, CDKN2A/p16 is transcriptionally
derepressed in treated tumors. This is likely responsible for acute
cell cycle arrest. Secondly, there is a differentiation program induced
by PRC2 inhibition. As the origin-of-tumor for MRT is neural crest, a
prominent induction of genes related to axon guidance and neuronal
functions are derepressed. This effect may also be related to the
bivalent genes in embryonic development. Finally, PRC2 inhibition
enables the de-repression of SASP factors and ECM genes, including
GATA4, HLA-B, MMP2/10, BMP6, FAS, GBP1 and ITGA2. These gene products
may enhance the antigen presentation and immune infiltration to
potentiate efficacy of MAK683. In total, these responses all contribute
to the antitumor efficacy of PRC2 inhibitors.
H3K27 methylation covers more than 50% of genomic region and exhibits
broad distribution in cancer cells [[204]1, [205]39]. However, only
hundreds of genes showed transcriptional de-repression after PRC2
inhibition and H3K27me3 removal [[206]11, [207]13, [208]56]. This
contradictory observation suggest that H3K27me3 removal may only be
permissive for PRC2 target activation. Indeed, studies in embryonic
stem cells revealed the bivalency model, in which H3K4me3 and H3K27me3
often co-reside on the promoters of the developmental genes to
transiently repress their expression [[209]57]. When H3K27me3 is
removed, H3K4me3 would quickly drive the upregulation of these genes,
and therefore push forward the developmental process. Many of the type
5 genes exhibit moderate H3K4me3 signal, such as GATA4, HLA-B,
CDKN2A/p16, HOXD13, TBX3, FOXO1 and WNT6 (Fig. [210]3b and
Supplementary Fig. [211]2e, [212]2f). They may be the remanence of
bivalent genes.
p16 is a classical senescence marker. It has been used as a label for
senescent cells, and depletion of p16-positive cells in aged mice
extended their healthy lifespan [[213]58]. It is also a typical
bivalent gene (Fig. [214]3b) [[215]30, [216]57, [217]59], which
explains why it is generally regulated by PRC2. Interestingly, we found
that p16 protein correlated with SA-β-gal activity, but not SASP. The
p16 KO cells did not turn on SA-β-gal with MAK683 treatment (Fig.
[218]4f, [219]i and Supplementary Fig. [220]4c). Consistently,
overexpression of p16 or p21 in normal human fibroblasts induced
senescent morphology and expression of SA-β-gal without SASP [[221]60].
There are multiple possible reasons. For example, lysosomal
amplification may occur in G1 of cell cycle, and senescent cells are
long-arrested in G0/G1 and therefore accumulate lysosomes.
Alternatively, p16 or CDK4/6 inhibition may be actively required for
SA-β-gal gene GLB1 expression with an unknown mechanism. Further
investigation on the linkage between p16 and SA-β-gal would be
warranted. Meanwhile, p21 was not upregulated in the RNA-seq data of
MAK683 treated cells ([222]GSE183600), and the involvement of p53/p21
axis merited further investigation.
Other than p16 and p21, there are a few PRC2 target genes reported
previously in literature. For example, the MHC class I molecules are
bivalent genes under the control of PRC2. PRC2 depletion or inhibition
would significantly upregulate their expression in multiple cell types
[[223]61]. T helper 1-type chemokines CXCL9 and CXCL10 are silenced by
PRC2 in ovarian and colon cancer [[224]62, [225]63]. IGFBP3 and IGFBP5
have also been shown under the regulation of PRC2 [[226]64, [227]65].
Interestingly, HLA-B, CXCL9, CXCL10, IGFBP3 and IGFBP5 are all
senescence-upregulated genes in SeneQuest database [[228]32]. It is
conceivable that these genes may be SASP factors repressed by PRC2,
consistent with our results. Tissue- and lineage-dependency is an
intrinsic feature of SASP, which is also a characteristic for
epigenetic marks. It is well-noted that epigenome changes dramatically
during senescence and multiple epigenetic modulators are involved, such
as BRD4 and MLL1 [[229]66, [230]67]. Our work provides strong evidence
that PRC2 belongs to this list. Furthermore, many of these genes are
tumor suppressors, such as GATA4 and IGFBP3/5, and may contribute to
the therapeutic effect of PRC2 inhibition in tumor (Fig. [231]4e).
In summary, our results suggest that PRC2 inhibitors in cancer
treatment induce differentiation and multiple features of senescence,
including p16, ECM, and SASPs to render their anti-cancer efficacy.
Senescence-induced inflammation further attracts immune infiltration
for senescent cell clearance [[232]33] (Fig. [233]5d, g). Along the
line, combining PRC2 inhibitor with senolytic agents, such as
navitoclax (BCL2 inhibitor), may provide a way to enhance tumor
shrinkage and patient survival. Recently, Morel et al. reported that
EZH2 depletion/inhibition upregulated IFN pathways and potentiated
response to PD-1 therapy in prostate cancer [[234]68], which may be
similar for MRT and ovarian cancers. Meanwhile, the application of
CDK4/6 inhibitor together with MAK683 achieved better efficacy,
especially in p16 inactivated tumors (Fig. [235]5h). We used SMARCB1 or
ARID1a deficient models regardless of location. These pieces of
evidence support that PRC2 inhibitors could induce therapeutic response
in cancer from different body location, and the combination of PRC2
inhibitor with PD-1 therapy and/or CDK4/6 inhibitors could be a valid
clinic strategy.
Materials and methods
Cell culture
Cells were maintained in a humidified incubator at 37 °C with 5%
(vol/vol) CO[2]. G401, G402, A204 were cultured in DMEM (Invitrogen,
12100046) with 10% (vol/vol) FBS (Lonsera, S711-001S), 0.055 mM
2-mercaptoethanol (Sigma, M3148) and 1% penicillin/streptomycin. MCAS,
HEK293T, A2780, Hs700T, U2OS, RD, HeLa were cultured in DMEM
(Invitrogen, 12100046) with 10% (vol/vol) FBS and 1%
penicillin/streptomycin. WSU-DLCL2 was cultured in RPMI1640
(Invitrogen, 31800022) with 15% (vol/vol) FBS and 1%
penicillin/streptomycin. All cells are authenticated by STR profiling
and tested for confirmation of mycoplasma-free. EED226, EPZ6438 and
MAK683 were purchased from MCE and Selleck.
Cell proliferation and cell cycle analysis
Cells were seeded in 6-well plates at a density of 2 × 10^5 cells with
the indicated concentrations of EPZ6438 or MAK683. Viable cell numbers
were counted every 3 days up to 15 days by Vi-CELL (Beckman Coulter).
For cell cycle analysis, MAK683 treated cells were fixed with
pre-chilled 70% ethanol and kept at -20 degree overnight. On the second
day, the cells were washed with cold PBS twice and collected by spin at
1000 rpm, digested with RNase A, then stained with 10 μg /mL Propidium
Iodide in PBS solution for 30 min at room temperature. The stained cell
samples were filtered through 70 μm cell strainer, and the staining
signals were detected using flow cytometer (BD Fortessa). The acquired
data were further analyzed by Modfit LT.
Lentiviral infections
HEK293T cells were co-transfected with plasmid DNAs of a lentiviral
vector, packaging plasmid psA2X and envelope plasmid pMD2G using
Lipofectamine 2000 (Invitrogen) with the ratio of 4:3:1. The
supernatant was collected 48 and 72 hr after transfection and filtered
by 0.45 μM filter. The fresh filtered lentiviruses were used to infect
the target cells G401 and A2780 in the presence of 8 μg /mL polybrene
(Sigma). After 72 hr, GFP positive cells were sorted by flow cytometer
(BD Melody). For cells infected with shRNA vectors, puromycin resistant
cells were cultured under the selection of 0.7 μg/mL puromycin for 4
days before further experiments.
CRISPR/Cas9 gene editing
Two pairs of guide RNAs (Supplementary Table [236]1) targeting the
exon2 of human CDKN2A ([237]NM_000077) were designed using ChopChop
website. gRNA oligos were synthesized, annealed and subcloned into the
pSpCas9(BB)-2A-GFP (PX458). G401 and A2780 cell lines were transfected
with the resultant plasmids, cultured for 48 h, and then applied to the
single cell sorting for selecting GFP-positive cell by flow cytometer.
Single cell clones were first cultured each well of 96-well plate, and
then gradually expanded in larger cultures for further experiments. We
amplified the genomic DNA fragment through PCR using primers
p16-cas9-primer-F and -R (Supplementary Table [238]1) for sequencing,
and the positive clones were further validated using western blot of
p16 in the presence of MAK683 treatment for 3–6 days.
Western blotting
Cells were washed once with cold PBS and lysed by RIPA lysis buffer and
incubated with 4 × SDS loading buffer at 95 °C for 10 min. Whole cell
proteins were used for electrophoresis and then transferred to a
nitrocellulose membrane. The membrane was blocked with Tris buffered
saline containing 0.075% Tween-20 and 5% non-fat milk. Then the
membranes were incubated with primary antibodies overnight at 4 °C. The
next day, membranes were incubated with secondary antibodies for 1 h at
room temperature.
Antibodies used in this study included H3 (Cell Signaling Technology,
9715; dilution 1:1000), H3K27me3 (Cell Signaling Technology, 9733;
dilution 1:1000), H3K27me2 (Cell Signaling Technology, 9728; dilution
1:1000), H3K27me1 (Merck Millipore, 07-448; dilution 1:1000), H3K27ac
(Cell Signaling Technology, 8173; dilution 1:1000), H3K4me3 (Merck
Millipore, 04-745; dilution 1:1000), H3K36me3 (Cell Signaling
Technology, 4909; dilution 1:1000), H3K9me3 (Active Motif, 39161;
dilution 1:1000), H3K79me2 (Abcam, ab3594; dilution 1:1000), p16 (Santa
Cruz, sc-377412; dilution 1:200), β-actin (Cell Signaling Technology,
3700, dilution 1:1000) (Supplementary Table [239]1).
Chromatin immunoprecipitation (ChIP)
We used the ChIP kit from Millipore for ChIP-seq sample preparation
(with spike-in step) and ChIP-qPCR analysis. Briefly, G401 cells
(1 × 10^6) were seeded in 10-cm dishes and treated with DMSO or 3 μM of
MAK683 for 3 days. Cells were fixed with 0.7% formaldehyde in culture
medium for 7 min at room temperature and the reaction was quenched with
0.125 M glycine sharply. Then remove media and wash the cell twice with
cold PBS including protease inhibitor mix. Cells were scraped off the
plate and the pellets were collected, lysed at the volume of 4 × 10^6
per 300 μL using SDS lysis buffer for 10 min on ice, and then proceed
to sonication. Each sample was sonicated for 14 min, 15 s on and 45 s
off with 70% output (Qsonica 4905 Chiller). Sonicated samples were
diluted with ChIP dilution buffer, additionally add 40 ng Drosophila
chromatin for spike in normalization, and applied to 1 h pre-clear with
30 μL protein A+G agarose beads. After that, input samples were
collected, and every 300 uL of cell lysate samples were applied into
ChIP with 2 μg H2Av antibody plus 8 μg of H3K4me3 antibody, 8 μg of
H3K27me3 antibody, or negative control lgG respectively.
Antibody-chromatin complex were incubated overnight at 4 °C, then
captured by 60 μL protein A+G agarose beads for 1 h at 4 °C. The beads
were washed in low salt buffer once, high salt buffer once, LiCl buffer
once, and TE buffer twice. DNA-protein complex was eluted twice with
elution buffer (1% SDS, 0.1 M NaHCO[3]), eluted chromatin was
de-crosslink at 65 °C for 4 h with 5 M NaCl and Proteinase K. Reserved
chromatin DNA were purified with Phenol-chloroform method.
RNA-seq data analysis
Total pair-end sequences obtained on Illumina PE150 (150-bp reads)
instruments were aligned to the human genome (hg19). We used
Trim-galore (version 0.4.4_dev) (Krueger F. Trim galore. 2012.
Available from:
[240]http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) to
remove low quality sequences as well as sequencing connectors. mRNA
levels of genes in triplicate samples were calculated as FPKM using
RSEM (version v1.3.0) [[241]69] and featureCounts (version v1.5.3)
[[242]70]. We determined differential gene expression using R package
DESeq2 (version v1.20.0) [[243]71] with an FDR threshold of 0.05 and an
Log2 Fold Change threshold of ±1.
ChIP-seq and ATAC-seq data analysis
Total pair-end sequences obtained on Illumina PE150 (150-bp reads)
instruments were aligned to the human genome (hg19). We used
Trim-galore (version 0.4.4_dev) to remove low quality sequences as well
as sequencing connectors. Sequences were aligned with Bowtie2 (version
7.3.0) [[244]72]. ChIP-seq sample depleted repeat sequences by Picard
(version 2.23.6) (“Picard Toolkit” 2019. Broad Institute, GitHub
Repository. [245]http://broadinstitute.github.io/picard/; Broad
Institute) and normalized by drosophila histone modification
(Spike-in). These reads were used to generate binding site with MACS2
(version 2.2.7.1) [[246]73] and featureCounts (version v2.0.0).
Spike-in normalization
All samples were sequenced with corresponding Drosophila histone
modification sequences and aligned to the Drosophila genome (dm6).
Firstly, counted the number of read segments specifically matched to
the Drosophila genome after remove duplication. Secondly, calculated
standardization factor (SF) with the minimum number of reads matched to
the Drosophila genome divided by the number of reads matched to the
Drosophila genome of the corresponding samples.
[MATH:
SFi=MinUMD<
mn>1,UMD<
/mi>2,UM
D3,⋯,UMD
iUMDi :MATH]
UMD represents the number of read segments specifically matched to
Drosophila, i represents the i^th sample. Thirdly, multiplied the
number of read segments matched to the human genome by the
corresponding standardized factor.
[MATH:
NHi=SFi*OH
i :MATH]
NH represents the number of read segments specifically matched to the
human genome after standardization, OH represents the number of read
segments specifically matched to the human genome before
standardization, i represents the i^th sample.
Bisulfite-seq data analysis
Total pair-end sequences obtained on Illumina NoveSeq 6000 PE150
(150-bp reads) instruments were aligned to the human genome (hg19). We
used Trim-galore (version 0.4.4_dev) to remove low quality sequences as
well as sequencing connectors. Sequences were aligned with Bismark
(version v0.19.0) [[247]74], which based on Bowtie2 (version 2.2.8) and
can transformed reference genome by three-letter alignment.
K-means cluster
Preprocessing
Due to different scales among different sequence features, z-score
normalization was performed for all features.
Parameter selection
The optimal number of clusters was chosen using the elbow method.
Through several iterations and calculating the contour coefficient of
each cluster, the turning point of decreasing contour coefficient is
determined as the number of clusters.
Implementation
All calculations are performed in Python (version 3.7.0) and its
modules, mainly through the Cluster and Preprocessing methods of the
Sklearn module (version 0.21.2) [[248]75].
Enrichment analysis
Fisher-exact test
Through Python (version 3.7.0) and its Scipy (version 1.2.1) module
[[249]76], the enrichment level of each gene set was calculated
according to Fisher’s exact test method.
Gene set enrichment analysis (GSEA)
GSEA is based on GSEA Desktop Application (version 4.0.3, download from
[250]http://www.gsea-msigdb.org/gsea/downloads.jsp).
Database
All gene sets download from Molecular Signatures Database (MSigDB,
[251]http://www.gsea-msigdb.org/gsea/msigdb/index.jsp, version
v7.1/v7.2), including C2.cp/C5.go gene sets.
Visualization
Data visualization was performed using Python’s Matplotlib (version
3.1.0) [[252]77] and Seaborn (version 0.9.0) [[253]78] module, R’s Gviz
(version 1.30.3) package [[254]79] and DeepTools software (version
3.4.3) [[255]80].
Quantitative PCR
Total RNA samples were prepared using Trizol reagent (Sigma) following
the protocol provided with the reagent. 2 μg of total RNA were
reserve-transcribed to cDNA using M-MLV Reverse Transcriptase
(Promega). Following cDNA synthesis, real-time quantitative PCR was
performed using SYBR Green gene expression assay on CFX Real-time
System (Bio-Rad). GAPDH was used as the normalization control, and the
data were further calculated by the 2^−ΔΔCt method. All reactions were
performed in triplicates. The sequence information for the primers are
listed in Supplementary Table [256]2.
Mouse xenograft studies
The animal study design and performance were evaluated and approved by
Institutional Animal Care and Use Committee of ShanghaiTech University
under the document number of 20201225001 and following the
internationally recognized guidelines on animal welfare. To establish
G401 xenograft models, WT G401 or p16 knock out cells were washed and
resuspended in cold PBS and mixed with Matrigel at 1:1 (v/v) to reach
the final ratio of 5 × 10^6 cells per 200 μL. Then the tumor cell mix
were injected subcutaneously into the right flank of female Balb/c nude
mice (5–6 weeks of age).
When tumor volume reached around 60-350 mm^3, the mice were numbered
and randomized into vehicle or 100 mg/kg MAK683 treatment groups. The
random numbers were generated using Excel (Software). The mice with
tumor size out of the range were not included in the study.
Empirically, at least 6 mice were included for each group. For compound
dosing, MAK683 was resolved and suspended in water with 0.5% HPMC and
0.5% Tween at the concentration of 10 mg/mL. Dosing without blinding
took place very day in the morning around 8 am. Mice weight and tumor
volumes are measured and recorded every 3 days. Tumor volumes were
calculated based on perpendicular length and width caliper measurements
using the following formula: tumor volume (mm^3) = 0.5 × (length ×
width^2).
Immunohistochemistry
Tumor tissues were fixed in freshly-prepared 4% PFA for 24 hours,
dehydrated through 30%, 50%, 70%, 85%, and 90% ethanol five-minute
each, and 100% ethanol triple, permeabilized through xylene five-minute
twice and then embedded in paraffin, and finally cut into 5 μm-thick
sections. The sections were de-paraffinized with xylene for 10 min
triple, rehydrated with ethanol from high to low concentration five
minutes each and dH[2]O twice. For antigen retrieval, sections were
boiled in a microwave for 15 min in 10 mM citrate buffer (pH 6.0) for
Ki-67 (Abcam, ab16667; dilution 1:100), H3K27me3 (Cell Signaling
Technology, 9733; dilution 1:200), and F4/80 (Thermo Fisher,
14-4801-82; dilution 1:50); or in 10 mM Tris-EDTA buffer (pH 9.0) for
ITGA2 (Abcam, ab181548; dilution 1:50) (Supplementary Table [257]1).
After cool down to room temperature, endogenous peroxidase was
inactivated with 3% H[2]O[2] in methanol. Then the sections were washed
with dH[2]O twice, blocked with 5% normal goat serum in PBS with 0.25%
Triton X-100 for 1 hour at room temperature followed by primary
antibodies incubation overnight at 4 °C. After HRP-conjugated secondary
antibodies were incubated for 1 hours at room temperature, the sections
were visualized with DAB. For quantification of Ki-67, H3K27me3 or
ITGA2 positivity, the ratios of DAB positive cells to total cells in
five representative fields were counted. For quantification of F4/80
positivity, the ratios of DAB positive area to total cells were
counted. Five 40 × objective magnification fields per selection were
counted and averaged.
β-gal staining
Cell senescence study was used by Beyotime in Situ β-galactosidase
Staining Kit. Adherent cells were fix by fix-buffer for 15 min at room
temperature and wash with PBS twice, then stain by stain-buffer mixture
at 37 °C overnight. Frozen tissue sections were counterstained with
eosin.
Statistical analysis
Statistical analysis for qPCR and tumor tissue section staining were
carried out using GraphPad Prism 8 (Supplementary Table [258]1). Data
are shown as mean ± s.d. The variance within each group is similar.
Statistical significance was determined using the two-tailed Student’s
test (t test). P < 0.05 was considered significant.
Supplementary information
[259]Supplementary Figures^ (9.6MB, docx)
[260]Supplementary table 1^ (19KB, docx)
[261]Supplementary table 2^ (13.5KB, xlsx)
[262]Reproducibility checklist^ (952.4KB, pdf)
Acknowledgements