Liyushang Chou1,1, Cassandra E Callmann1,1, Donye Dominguez2, Bin Zhang2, Chad A Mirkin1,1,2. 1. Interdisciplinary Biological Sciences Graduate Program, International Institute for Nanotechnology, and Department of Chemistry, Northwestern University, Evanston, Illinois 60208, United States. 2. Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611, United States.
Abstract
Disrupting the interplay between programmed cell death protein 1 (PD-1) and programmed death ligand 1 (PD-L1) is a powerful immunotherapeutic approach to cancer treatment. Herein, spherical nucleic acid (SNA) liposomal nanoparticle conjugates that incorporate a newly designed antisense DNA sequence specifically against PD-L1 (immune checkpoint inhibitor SNAs, or IC-SNAs) are explored as a strategy for blocking PD-1/PD-L1 signaling within the tumor microenvironment (TME). Concentration-dependent PD-L1 silencing with IC-SNAs is observed in MC38 colon cancer cells, where IC-SNAs decrease both surface PD-L1 (sPD-L1) and total PD-L1 expression. Furthermore, peritumoral administration of IC-SNAs in a syngeneic mouse model of MC38 colon cancer leads to reduced sPD-L1 expression in multiple cell populations within the TME, including tumor cells, dendritic cells, and myeloid derived suppressor cells. The treatment effectively increases CD8+ T cells accumulation and functionality in the TME, which ultimately inhibits tumor growth and extends animal survival. Taken together, these data show that IC-SNA nanoconstructs are capable of disrupting the PD-1/PD-L1 interplay via gene regulation, thereby providing a promising avenue for cancer immunotherapy.
Disrupting the interplay between programmed cell death protein 1 (PD-1) and programmed death ligand 1 (PD-L1) is a powerful immunotherapeutic approach to cancer treatment. Herein, spherical nucleic acid (SNA) liposomal nanoparticle conjugates that incorporate a newly designed antisense DNA sequence specifically against PD-L1 (immune checkpoint inhibitor SNAs, or IC-SNAs) are explored as a strategy for blocking PD-1/PD-L1 signaling within the tumor microenvironment (TME). Concentration-dependent PD-L1 silencing with IC-SNAs is observed in MC38 colon cancer cells, where IC-SNAs decrease both surface PD-L1 (sPD-L1) and total PD-L1 expression. Furthermore, peritumoral administration of IC-SNAs in a syngeneic mouse model of MC38 colon cancer leads to reduced sPD-L1 expression in multiple cell populations within the TME, including tumor cells, dendritic cells, and myeloid derived suppressor cells. The treatment effectively increases CD8+ T cells accumulation and functionality in the TME, which ultimately inhibits tumor growth and extends animal survival. Taken together, these data show that IC-SNA nanoconstructs are capable of disrupting the PD-1/PD-L1 interplay via gene regulation, thereby providing a promising avenue for cancer immunotherapy.
Cancer remains a leading cause of death
worldwide, necessitating
the continued study of disease etiology and the development of new
treatment options.[1,2] Owing to an increased understanding
of the hallmarks of many cancers (e.g., uncontrolled cell proliferation
triggered by genetic mutations, rewired cell signaling, dysregulated
metabolism, and increased immune evasion mechanisms),[3,4] cancer treatment has shifted away from surgery and radiotherapy
toward targeted chemo- and immunotherapies. A particularly promising
immunotherapeutic strategy involves disrupting the interplay between
programmed cell death protein 1 (PD-1) and programmed death ligand
1 (PD-L1) within the tumor microenvironment (TME).[5−8] PD-1 is a type I transmembrane
glycoprotein found on the surface of CD8+ T cells,[9] while PD-L1 is overexpressed on the surface of
cancer cells, antigen-presenting cells (APCs), macrophages, and myeloid-derived
suppressive cells (MDSCs) in the TME.[10] The binding of PD-L1 to PD-1 initiates a negative signal cascade
that inhibits T cell activation and decreases T cell cytotoxicity.
Furthermore, the upregulation of PD-L1 on multiple cell types causes
the inadequate priming of CD8+ T cells and leads to decreased
infiltration of activated T cells into the TME. Cumulatively, this
reduces the cytotoxic effect of T cells on tumors.[11]Because the PD-1/PD-L1 pathway is a dominant regulator
of cancer
immune response, blockade therapies that target this pathway have
been developed and implemented in the clinic.[7,8,10] For example, monoclonal antibodies that
bind with high affinity to PD-1 on the surface of T cells act as competitive
inhibitors of PD-L1. Therapeutic antibodies (commonly referred to
as checkpoint inhibitors) against PD-1 have been shown to cause durable
and persistent tumor regression when administered to patients with
treatment-refractory solid tumors.[12−16] However, 40–60% of patients do not respond
to single-antibody treatment alone.[17−22] Therefore, antibody-based checkpoint inhibitors that bind PD-L1
are often used in conjunction with those that bind PD-1 to block receptor
signal transduction.[23−28] Despite the success of combination checkpoint inhibitor antibody
therapies, many patients acquire resistance to such treatments,[29] experience significant adverse off-target effects,
and/or develop complement-dependent cytotoxicity[30] from long-term systemic use.[31−34] Moreover, antibodies do not have
access to the intracellular compartments.[35] Indeed, PD-L1 exists in multiple forms and in different cellular
compartments (e.g., transmembrane-anchored, cytosolic, nucleic, and
soluble, circulating variants; they also exist as mRNA transcripts
in various cells as a self-defense mechanism for potential autophagy)
and is involved in multiple immunosuppression pathways, both site-specifically
and systemically.[36−39] Thus, additional effective blockade options are needed. In this
regard, gene regulation strategies that decrease the overall expression
of PD-L1 are considered a promising means for blocking immune checkpoints.[21,35−43]Spherical nucleic acids (SNAs) are nanostructures consisting
of
spherical nanoparticle cores with densely packed and highly oriented
oligonucleotides on their surfaces; they have been proven to be extremely
useful in biomedicine.[44−50] Due to their unique architecture, SNAs are more efficiently and
rapidly taken up by cells (over 60 types to date, via scavenger receptor-mediated
endocytosis[51,52]) as compared to linear oligonucleotides
of the same sequence. SNAs also are more resistant to nuclease degradation
and have extended circulation half-lives in vivo relative
to linear nucleic acids,[53,54] due to the dense arrangement
of oligonucleotides on the SNA surface. In addition, the cooperative
binding of nucleic acids on SNAs to complementary mRNA targets increases
the binding affinity by 1–2 orders of magnitude relative to
their linear nucleic acid counterparts under identical conditions.[44,45,55] Although SNAs are initially taken
up via endosomal pathways, a meaningful fraction escape[46−48,56] and have been shown to act as
potent gene regulation[57,58] agents in the cytosol in vivo(50) and in clinical trials.[59] Importantly, the SNAs in such studies exhibited
minimal cytotoxicity and immunogenicity, making them attractive for
use as medicines.Herein, a new anti-PD-L1 antisense DNA sequence
was designed, and
the SNA architecture was leveraged to deliver this sequence into MC38
colon cancer cells and knockdown PD-L1 expression. These SNAs, designated
immune checkpoint inhibitor SNAs (IC-SNAs), were investigated for
their ability to regulate the expression of PD-L1 level in
vitro and in vivo as well as for their ability
to act as potent anticancer therapies.
Results and Discussion
Design of IC-SNAs
In order to target PD-L1 using antisense
DNA, oligonucleotide sequences capable of knocking down the expression
of mouse PD-L1 (mPD-L1) were designed (Scheme ) using the mPD-L1 mRNA data available from
the NCBI GeneBank.[60,61] The full script of the mRNA sequence
transcribed from the mPD-L1 (CD274) gene is comprised of six domains:
5′ UTR (untranslated region), signal sequence, immunoglobulin,
transmembrane, intracellular, and 3′ UTR. Given alternative
splicing mechanisms for mRNA editing before translation, PD-L1 mRNAs
mainly adopt two isoforms in mice. Despite differences in the signal
sequence and the 3′ and 5′ UTR regions, both variants
contain immunoglobulin, transmembrane, and intracellular domains in
their transcripts. Therefore, to target as many PD-L1 protein isoforms
as possible at an mRNA level, the oligonucleotide sequences employed
herein were designed to target the overlapping regions of the mRNA.
Scheme 1
Targeting Sequence Design Rationale
The mouse PD-L1
gene (CD274)
is located on chromosome 19, which is composed of 7 exons with introns
in between. The gene transcript mRNA for CD274 encodes a full script
at a length of 3639 base pairs (bp) with six domains in total: 5′
UTR, signal sequence, immunoglobulin (immunoglobulin V-like and C-like),
transmembrane, intracellular, and 3′ UTR. The mRNA full scripts
adopt mainly two variant isoforms, which can be subsequently translated
into PD-L1 antigen and precursor. Both isoforms have full immunoglobulin,
transmembrane, and intracellular domains. Therefore, the interactions
of these PD-L1 isoforms with their receptors inhibit T cell activation
and cytokine production. To target the entire PD-L1 population, test
sequences (15 bps in length) were designed to be complementary to
mouse PD-L1 (mPD-L1) mRNA in locations such as the mRNA base pair
positions 148 (A), 178 (B), 344 (C), and 766 (D).
Targeting Sequence Design Rationale
The mouse PD-L1
gene (CD274)
is located on chromosome 19, which is composed of 7 exons with introns
in between. The gene transcript mRNA for CD274 encodes a full script
at a length of 3639 base pairs (bp) with six domains in total: 5′
UTR, signal sequence, immunoglobulin (immunoglobulin V-like and C-like),
transmembrane, intracellular, and 3′ UTR. The mRNA full scripts
adopt mainly two variant isoforms, which can be subsequently translated
into PD-L1 antigen and precursor. Both isoforms have full immunoglobulin,
transmembrane, and intracellular domains. Therefore, the interactions
of these PD-L1 isoforms with their receptors inhibit T cell activation
and cytokine production. To target the entire PD-L1 population, test
sequences (15 bps in length) were designed to be complementary to
mouse PD-L1 (mPD-L1) mRNA in locations such as the mRNA base pair
positions 148 (A), 178 (B), 344 (C), and 766 (D).To reduce nonspecific targeting, a BLAST analysis (NCBI Basic Local
Alignment Search Tool) was run and screened for sequence homogeneity.
Subsequently, to identify a specific binding region, the sequences
were designed with the goal of either: (1) recruiting RNase H for
targeted degradation or (2) sterically hindering ribosome movement
down the translating strand. In the case of the RNase recruitment
model, the designed sequence must be able to bind the RNase H cleavage
pocket, which is ∼18 base pairs (bp) in length[62−65] (Scheme S1A). In the latter case, the
sequence must be designed to halt ribosome translation via steric
hindrance by hybridizing tightly to an accessible region on the target
mRNA. Hence, sequence binding should not occur in regions where protein
machineries, such as poly-A-binding protein, translation initiation
factors, and ribosomes, bind during translation (Scheme S1B). Moreover, the sequence must hybridize tightly
to the mRNA to halt translation; thus, the accessibility of the single-strand
base pair position and the melting temperature of the hybrid are other
factors that were taken into consideration. With these constraints
in mind, the sequences were designed by initially simulating a folding
process for mPD-L1 mRNA with the Mfold Web Server[66,67] to generate an accessibility mapping profile using the RNA folding
tool. With input of mPD-L1 mRNA, Mus musculus CD274
antigen (Cd274), and mRNA NM_021893.3 from NCBI GenBank, the regions
with the highest accessibility for hybridization were identified (Scheme , Figure S1).
PD-L1 Knockdown by Designed Sequences with Transfection Agents
Based on these design rules, four antisense oligonucleotide sequence
candidates were identified and synthesized (sequence A: 5′-AGT
CCT TTG GAG CCG-3′, sequence B: 5′-TGA CGT TGC TGC CAT-3′,
sequence C: 5′-AGC TGG TCC TTT GGC-3′, and sequence
D: 5′-GAT GTG TTG CAG GCA-3′, sequence positions are
labeled in Scheme ), and subsequently their knockdown efficacy in cells was investigated.
In MC38 colon cancer cells cultured in RPMI-1640 media, PD-L1 expression
was induced via incubation with interferon-gamma (IFN-γ) (20
ng/mL) overnight (Figure A). Compared to the other candidate sequences, sequence B
achieved the greatest knockdown of total PD-L1 expression when Lipofectamine
2000 was used as the transfection agent (Figure B); knockdown was achieved in a concentration-dependent
manner (Figure C).
Therefore, sequence B was used in all experiments involving SNA formulations.
Figure 1
PD-L1
knockdown by antisense DNA sequences. (A) PD-L1 expression
level in the MC38 cell line following IFN-γ stimulation. (B)
Evaluation of the ability of the designed sequences (A–D) to
inhibit PD-L1 expression (sequences A–D, ϕ = untreated)
using standard transfection protocols. Cell lysates were harvested
after 48 h incubation, and PD-L1 protein level was measured using
a Western blot analysis (n = 4, representative example
shown in panel). (C) Concentration-dependent knockdown of PD-L1 expression
in MC38 cells by sequence B (n = 4, representative
example shown in panel). Actin was used as a standard control to ensure
that an equal amount of protein lysates were loaded to each lane.
(D) Statistical analysis of reduction in PD-L1 by sequences shown
in Figure B (n = 4). (E) Statistical analysis of concentration-dependent
knockdown as shown in Figure C (n = 4). Statistical analysis was performed
using a one-way ANOVA, where “**” p < 0.01; “***” p < 0.001; and
“****” p < 0.0001.
PD-L1
knockdown by antisense DNA sequences. (A) PD-L1 expression
level in the MC38 cell line following IFN-γ stimulation. (B)
Evaluation of the ability of the designed sequences (A–D) to
inhibit PD-L1 expression (sequences A–D, ϕ = untreated)
using standard transfection protocols. Cell lysates were harvested
after 48 h incubation, and PD-L1 protein level was measured using
a Western blot analysis (n = 4, representative example
shown in panel). (C) Concentration-dependent knockdown of PD-L1 expression
in MC38 cells by sequence B (n = 4, representative
example shown in panel). Actin was used as a standard control to ensure
that an equal amount of protein lysates were loaded to each lane.
(D) Statistical analysis of reduction in PD-L1 by sequences shown
in Figure B (n = 4). (E) Statistical analysis of concentration-dependent
knockdown as shown in Figure C (n = 4). Statistical analysis was performed
using a one-way ANOVA, where “**” p < 0.01; “***” p < 0.001; and
“****” p < 0.0001.
PD-L1 Reduction with IC-SNA Treatments In Vitro
To prepare IC-SNAs, sequence B was anchored onto ∼50
nm liposomal cores (Figure S2A), and the
resulting structures were characterized via dynamic light scattering
(DLS) and ζ potential. Upon DNA loading (∼50 strands
per particle, Figure S2B), the average
increase in diameter was 6.4 nm, and the decrease in ζ potential
was 16 mV (Figure S2C). With these materials
in hand, the effect of IC-SNAs on PD-L1 expression was explored in
the same cell line as a single-entity agents (transfection agents
are not needed in this case); SNAs comprised of a scrambled version
of sequence B (SCR-SNAs) was used as a control. Increasing the concentration
of IC-SNAs (from 0 nM to 0.6 μM in terms of DNA concentration)
resulted in an increase in overall PD-L1 knockdown from 0 to ∼83%.
Conversely, the SCR-SNA control did not influence PD-L1 expression
(Figure A), indicating
that the knockdown observed is sequence specific.
Figure 2
In vitro PD-L1 knockdown by IC-SNA treatment in
MC38 colon cancer cells. (A) Dose-dependent knockdown of PD-L1 expression
in MC38 cells by IC-SNAs. Actin was used as a standard control to
ensure that an equal amount of protein lysates were loaded to each
lane. (B) Surface PD-L1 (sPD-L1) expression levels following incubation
with IC-SNAs as a function of DNA concentration and incubation time.
The results are presented as the mean ± SD (n = 4). Statistical analysis was performed using one-way ANOVA. “**” p < 0.01; “***” p <
0.001; and “****” p < 0.0001.
In vitro PD-L1 knockdown by IC-SNA treatment in
MC38 colon cancer cells. (A) Dose-dependent knockdown of PD-L1 expression
in MC38 cells by IC-SNAs. Actin was used as a standard control to
ensure that an equal amount of protein lysates were loaded to each
lane. (B) Surface PD-L1 (sPD-L1) expression levels following incubation
with IC-SNAs as a function of DNA concentration and incubation time.
The results are presented as the mean ± SD (n = 4). Statistical analysis was performed using one-way ANOVA. “**” p < 0.01; “***” p <
0.001; and “****” p < 0.0001.To confirm that IC-SNAs induce PD-L1 knockdown
in cells other than
MC38, PD-L1 knockdown was also evaluated in B16.F10 melanoma cells.
Consistent with previous results,[12,16,18,19,68−72] PD-L1 knockdown by IC-SNAs in B16.F10 cells was also dose dependent,
albeit to a lesser extent compared to in the MC38 cells (Figure S3).Because the knockdown of protein
expression by antisense DNA is
a dynamic process and PD-L1 mainly functions by binding to its receptor
PD-1, it is critical to evaluate both the onset and the duration for
reducing functional PD-L1 (i.e., surface PD-L1 in this context). Toward
this end, MC38 cells were stimulated with IFN-γ and then incubated
with a set of concentrations of IC-SNAs, and the sPD-L1 protein expression
levels were evaluated at 4, 24, and 48 h postincubation (Figure B). At both 4 and
24 h, a statistically significant reduction in sPD-L1 expression was
observed (Figure B, Figure S5, Table S2). Specifically, at 4 and 24 h, treatment with the 1 μM sample
(in terms of DNA) resulted in an average of 45.1% and 40.6% reduction
in sPD-L1 expression, respectively, as compared to the untreated IFN-γ
positive control (Figure S6, Table S2). Conversely, at 48 h, no difference
in sPD-L1 expression was observed between the IC-SNA-treated group
and the control groups, presumably due to the decrease in IFN-γ
stimulation across all groups over time (Figures S6, Table S2).
Immunotherapeutic Potency and In Vivo Antitumor
Efficacy of IC-SNAs in MC38 Colon Cancer Cells
To determine
the ability of IC-SNAs to silence PD-L1 expression and act as antitumor
immunotherapeutics in vivo, C57BL/6 mice bearing
MC38 colon cancer tumors (n = 4 per group) were subcutaneously
administered IC-SNAs peritumorally every 2 days (20 nmole per injection
in DNA amount) starting on day 7 until days 21–25 post-tumor
inoculation. The results attained with these animals were compared
to those attained with animals that were untreated or those that were
treated with SCR-SNAs (negative controls).At day 22, a subset
of animals in each group were sacrificed and the tumor-infiltrating
cells were stained and measured for sPD-L1 expression (Figure ). IC-SNA treatment led to
a decrease in overall PD-L1 expression within all live cells from
tumor tissues, as compared to treatment with the SCR-SNAs and the
untreated controls (Figure A, Figure S8A). Within individual
cell populations, IC-SNAs reduced sPD-L1 expression in tumor cells
(Figure B, Figure S8B), DCs (Figure C, Figure S8C),
and MDSCs (Figure D, Figure S8D). Moreover, IC-SNAs enhanced
antitumor T cell activity within the TME, as evidenced by increased:
(1) accumulation of intratumoral CD8+ T cells (Figure E), (2) production
of cytotoxic cytokines (IFN-γ and TNF-α) (Figure F), and (3) accumulation of
an effector memory T cell (CD44+ and CD62L–) subset (Figure G). Importantly, IC-SNA treatment significantly reduced tumor growth
(Figure A, Figures S10 and S11) and extended the survival
of mice as compared to those animals that were treated with the scrambled
SNAs and the untreated animals (Figure B), suggesting that the silencing PD-L1 by IC-SNAs
contributes significantly to tumor clearance in vivo.
Figure 3
Influence of IC-SNA treatments on the TME. The expression levels
of PD-L1 were measured by flow cytometry in different cell populations
within MC38 tumors with treatment as indicated. A reduction in sPD-L1
expression was observed in the (A) total live cells of the TME, (B)
tumor cells, (C) tumor-infiltrating DCs, and (D) tumor-infiltrating
MDSCs. The results are presented as the mean ± SD (n = 3/4). (E) Percentage of tumor infiltrating CD8+ T cells.
(F) Percentage of IFN-γ+ TNF-α+ cells
among tumor-infiltrating CD8+ T cells. (G) Percentage of
CD44+CD62L– effector memory subset among
tumor-infiltrating CD8+ T cells. Statistical analysis was
performed using one-way ANOVA. “**” p < 0.01; “***” p < 0.001; and
“****” p < 0.0001.
Figure 4
Antitumor efficacy of IC-SNAs in a MC38 mouse syngeneic
tumor model.
(A) Tumor growth (n = 4/group) and (B) survival analysis
of MC38 tumor-bearing mice treated with IC-SNAs or SCR-SNAs, or untreated
mice (n = 10/group). The results are presented as
the mean ± SD. Statistical analysis was performed using one-way
ANOVA (A) and a log-rank test for overall survival (B). “**” p < 0.01, and “***” p <
0.001.
Influence of IC-SNA treatments on the TME. The expression levels
of PD-L1 were measured by flow cytometry in different cell populations
within MC38 tumors with treatment as indicated. A reduction in sPD-L1
expression was observed in the (A) total live cells of the TME, (B)
tumor cells, (C) tumor-infiltrating DCs, and (D) tumor-infiltrating
MDSCs. The results are presented as the mean ± SD (n = 3/4). (E) Percentage of tumor infiltrating CD8+ T cells.
(F) Percentage of IFN-γ+ TNF-α+ cells
among tumor-infiltrating CD8+ T cells. (G) Percentage of
CD44+CD62L– effector memory subset among
tumor-infiltrating CD8+ T cells. Statistical analysis was
performed using one-way ANOVA. “**” p < 0.01; “***” p < 0.001; and
“****” p < 0.0001.Antitumor efficacy of IC-SNAs in a MC38 mouse syngeneic
tumor model.
(A) Tumor growth (n = 4/group) and (B) survival analysis
of MC38 tumor-bearing mice treated with IC-SNAs or SCR-SNAs, or untreated
mice (n = 10/group). The results are presented as
the mean ± SD. Statistical analysis was performed using one-way
ANOVA (A) and a log-rank test for overall survival (B). “**” p < 0.01, and “***” p <
0.001.Finally, to preliminarily assess the efficacy of
IC-SNAs relative
to conventional antibody-based checkpoint inhibition, we completed
a small pilot study (n = 4 per group) on the antitumor
efficacy of IC-SNAs as compared to anti-PD-L1 antibodies. Significantly,
IC-SNAs performed as well as antibody checkpoint inhibitors at suppressing
tumor growth (Figure S12) relative to untreated
controls. Because these agents act on the same target, but by completely
different mechanisms of action, it is difficult to benchmark IC-SNAs
against conventional antibody treatments. Nevertheless, this early
pilot study provides direct evidence that IC-SNAs potentially can
be used as an alternative to antibodies in cancer immunotherapy.
Conclusion
This work shows that arranging antisense
DNA on the nanoscale in
the form of an SNA is a viable strategy for generating chemical constructs
that act as potent immunotherapeutic agents. Furthermore, these data
provide evidence that SNAs and gene knockdown pathways can be used
as an alternative to traditional checkpoint inhibitors in cancer immunotherapy.
This is an attractive approach to immunotherapy since sPD-L1 is not
always a viable target because of the dynamic nature of protein expression
and the ever-changing TME. Significantly, subcutaneous administration
of IC-SNAs to mice bearing MC38 colon cancer tumors resulted in decreased
PD-L1 expression in all cell types within the TME, increased T cell
cytotoxicity, reduced tumor growth, and extended animal survival.
Moreover, the data presented herein shows that SNAs can provide additional
opportunities for regulating PD-L1, potentially with reduced side
effects by virtue of peritumoral administration. In addition, since
the SNA platform is scalable and modular, it establishes the potential
for combining multiple antisense DNA and/or siRNA sequences directed
toward different molecular targets (including multiple immune checkpoints)
in the same cell on the same particle; thus, multiple immunosuppressive
pathways can be silenced simultaneously. Taken together, this work
highlights the promise of using nanostructured chemical constructs
to regulate the action of PD-L1 on a genetic level and that this can
be leveraged to yield powerful gene regulation agents for cancer immunotherapy.
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