Abstract
Myeloid-derived suppressor cells (MDSCs) are key players in immune
evasion, tumor progression and metastasis. MDSCs accumulate under
various pathological states and fall into two functionally and
phenotypically distinct subsets that have been identified in humans and
mice: polymorphonuclear (PMN)-MDSCs and monocytic (M)-MDSCs. As dogs
are an excellent model for human tumor development and progression, we
set out to identify PMN-MDSCs and M-MDSCs in clinical canine oncology
patients. Canine hypodense MHC class II^−CD5^−CD21^−CD11b^+ cells can
be subdivided into polymorphonuclear (CADO48A^+CD14^−) and monocytic
(CADO48A^−CD14^+) MDSC subsets. The transcriptomic signatures of
PMN-MDSCs and M-MDSCs are distinct, and moreover reveal a statistically
significant similarity between canine and previously published human
PMN-MDSC gene expression patterns. As in humans, peripheral blood
frequencies of canine PMN-MDSCs and M-MDSCs are significantly higher in
dogs with cancer compared to healthy control dogs (PMN-MDSCs:
p < 0.001; M-MDSCs: p < 0.01). By leveraging the power of evolution, we
also identified additional conserved genes in PMN-MDSCs of multiple
species that may play a role in MDSC function. Our findings therefore
validate the dog as a model for studying MDSCs in the context of
cancer.
Introduction
Myeloid-derived suppressor cells (MDSCs) comprise a functionally
distinct phenotype of innate immune cells that play an important role
in the immune dysregulation characteristic of cancer^[52]1–[53]4.
Recent years have witnessed an increasing recognition of the clinical
relevance of MDSCs. Accumulation of these cells has been reported in
practically all human cancers, and increased frequencies of circulating
MDSCs have been correlated with poor prognosis, offering a biomarker of
clinical outcome in a variety of cancer histotypes^[54]5.
Generated by pathological subversion of polymorphonuclear (PMN) and
monocytic (M) differentiation and activation pathways in the context of
chronic inflammatory conditions and cancer, MDSCs represent a
heterogeneous population of two major subsets, PMN-MDSCs and M-MDSCs,
which are identified by a combination of multiple lineage markers. In
mice, PMN-MDSCs are defined as CD11b^+Ly6G^+Ly6C^lo cells, while
M-MDSCs are defined as CD11b^+Ly6G^−Ly6C^+ cells. In humans, PMN-MDSCs
are characterized as CD11b^+CD14^−CD15^+ or CD11b^+CD14^−CD66b^+ cells,
while M-MDSCs are CD11b^+CD14^+HLA-DR^−/lo CD15^− cells. A third group
comprising immature myeloid progenitors has also been described as
Lin^−(CD3/14/15/19/56)/^−HLA-DR^−/CD33^+ cells^[55]4,[56]6–[57]8.
Although a number of pivotal mechanistic studies on the pathobiology of
cancer have been performed using the mouse as a model for humans, there
is an unmet need for animal models that better recapitulate human
cancer to investigate novel therapeutic targets, including cellular
targets such as MDSCs^[58]9,[59]10. Canine malignancies have already
been recognized as strong comparative models for several human
cancers^[60]11,[61]12. Dogs spontaneously develop a variety of tumors
that share many features with human cancer, including clinical,
pathological, and molecular characteristics^[62]11–[63]13. Furthermore,
dogs have an intact immune system that allows faithful recapitulation
of the tumor microenvironment and circulating regulatory T cells of
human patients^[64]11,[65]14. Of note, a number of drugs utilized in
veterinary medicine were originally developed for human use, further
emphasizing the bilateral benefits of the One Health approach to both
dogs and humans alike^[66]11–[67]13. The contributions of the
comparative oncology field thus far therefore raise the question of
whether dogs with spontaneous tumors may also shed insight into MDSC
biology.
To date, two seminal studies described MDSCs in a variety of cancer
histotypes in dogs^[68]15,[69]16, but many questions remain unanswered.
Although these studies identified the existence of this suppressive
myeloid cell population in the peripheral blood of dogs, this early
work did not characterize the two subsets of MDSCs, an essential
prerequisite to their investigation in canine models of human cancer.
The current study therefore set out to characterize MDSC subsets in
tumor-bearing dogs, hypothesizing that their cellular phenotype and
transcriptomic signatures would reflect those of both human and murine
MDSC subsets. We identified two distinct myeloid cell populations in
the circulating blood of tumor-bearing dogs with similar phenotypic,
functional, and transcriptomic characteristics to human and murine
PMN-MDSCs and M-MDSCs. Capitalizing on the power of a comparative
evolutionary approach, we characterized the cellular and transcriptomic
phenotype of both PMN-MDSCs and M-MDSCs. We identified five transcripts
that are expressed at high levels by canine, human, and murine
PMN-MDSCs, yielding novel insights into fundamentally conserved
PMN-MDSC gene expression patterns spanning multiple evolutionary taxa.
Materials and Methods
Study population and sample collection
Peripheral blood samples were collected from dogs with cancer or
non-neoplastic inflammatory diseases recruited at the Royal Veterinary
College (RVC), North Downs Specialist Referrals (NDSR), and Fitzpatrick
Referrals (Oncology and Soft Tissue; FR) in the United Kingdom, and the
School of Veterinary Medicine at the University of Pennsylvania (Penn
Vet) in the United States of America. Healthy control dogs were also
recruited at the RVC and Penn Vet, defined by an absence of clinically
significant findings following a detailed history and physical
examination performed by a veterinarian or veterinary nurse.
Inflammatory control dogs included those with infectious or
immune-mediated disease, in which neoplasia was ruled out by relevant
diagnostic tests, including imaging of the thorax and/or abdomen.
Forty-one tumor-bearing, 37 inflammatory, and 31 healthy dogs were
recruited at the RVC; 51 tumor-bearing dogs were recruited at NDSR;
five tumor-bearing dogs were recruited at FR; and 21 tumor-bearing,
three inflammatory, and 25 healthy dogs were recruited at Penn Vet.
Tumor burden was classified as follows: For B cell lymphoma, patients
were grouped based on the World Health Organization staging system,
with stage I/II defined as low burden and stage III-IV defined as high
burden. In patients with solid non-lymphoid tumors, a low burden tumor
was defined as one whose sum of the longest diameters of the lesions
was smaller than 5 cm without evidence of lymph nodal and/or distant
metastasis. A high burden tumor was defined as one whose sum of the
longest diameters of lesions was greater than 5 cm, with or without
evidence of lymph nodal and distant metastasis. This study was approved
by the RVC’s Clinical Research Ethical Review Board (URN 2014 1285),
the University of Pennsylvania’s Institutional Animal Care and Use
Committee, and Penn Vet’s Privately Owned Animal Protocol Committee;
all samples were collected and processed in accordance with the
relevant guidelines and regulations. A peripheral blood sample was
collected aseptically from each dog from the jugular or lateral
saphenous vein into one or more EDTA tubes after informed consent was
granted by the owner of each dog. All blood was processed within
48 hours of collection.
Preparation of PBMCs and PMN cell isolation
MDSCs were isolated from the mononuclear fraction following density
gradient centrifugation as follows. Blood was diluted with an equal
volume of sterile Dulbecco’s Phosphate-Buffered Saline (DPBS; Corning
Cellgro, Tewksbury, MA, USA) containing 2% v/v fetal bovine serum (FBS;
Hyclone, Logan, UT, USA), and gently layered over Histopaque-1077^®
(Sigma-Aldrich, St. Louis, MO, USA). Samples were centrifuged at 400 g
for 30 minutes, with acceleration and deceleration set to zero. The
peripheral blood mononuclear cell (PBMC) layer was washed twice with
Roswell Park Memorial Institute (RPMI)-1640 medium (Life Technologies,
Carlsbad, CA, USA) containing 10 mM HEPES, 2 mM L-glutamine (Life
Technologies), 100 units/mL penicillin-streptomycin (Life
Technologies), 10% FBS, and 50 μM 2-mercaptoethanol (Life Technologies)
(complete medium), before re-suspension in DPBS containing 10% v/v FBS
and staining for analytical flow cytometry or flow-assisted cell
sorting (FACS™). PMNs were isolated from the remaining cell fraction
after removal of the mononuclear cells and treatment with Red Blood
Cell (RBC) Lysis Buffer (Multi-Species; Thermo Fisher Scientific, San
Diego, CA, USA) according to the manufacturer’s instructions. After RBC
lysis, cells were washed and re-suspended in DPBS-10% v/v FBS for
staining.
Flow cytometry and cell sorting
For MDSC analysis, PBMCs were labelled with a cocktail of monoclonal
antibodies (mAb) for 30 minutes at 4 °C according to the respective
manufacturer’s protocol. The cocktail comprised APC-conjugated anti-dog
MHC II (clone YKIX334.2; Thermo Fisher Scientific), PE-conjugated
anti-dog-CD5 (clone YKIX322.3; Bio-Rad, Hercules, CA, USA),
PE-conjugated anti-dog CD21 (clone CA2.1D6; Bio-Rad),
PE-Alexa647-conjugated anti-human CD14 (clone TUK4; Bio-Rad),
PE-Cy7-conjugated anti-dog PMN leukocyte antigen (antigen unknown,
clone CADO48A; University of Washington, Pullman, WA, USA), and Alexa
Fluor 488-conjugated anti-mouse CD11b (clone M1/70; Thermo Fisher
Scientific). PMNs from tumor-bearing or healthy dogs were identified as
CADO48A^+ cells isolated from the RBC-containing pellet.
Antibody-labeled cells were washed twice and re-suspended in DPBS-10%
v/v FBS, then incubated with 4′,6-diamidino-2-phenylindole (DAPI;
BioLegend, San Diego, CA, USA) at room temperature for 10 minutes prior
to analysis.
Flow cytometric data were acquired using a FACSCanto II flow cytometer
(Becton-Dickinson (BD); Franklin Lakes, NJ, USA) and analyzed using
FlowJo^® software, version 10.3 (Tree Star, Ashland, OR, USA). Cell
sorting was performed using a BD FACSAria III or a BD FACSAria Fusion
in the case of dogs recruited at the RVC, and a BD FACSAria II in the
case of dogs recruited at Penn Vet. Monocytes were isolated from the
PBMC layer and identified as CD5^−CD21^−MHCII^+CD11b^+CD14^+ cells (H
MONOs, healthy donor; C MONOs, tumor-bearing donor), while PMNs were
isolated from the hyperdense pellet and identified as
CD5^−CD21^−MHCII^−CD11b^+CADO48A^+ cells (H PMNs, healthy donor; C
PMNs, tumor-bearing donor). MDSCs were isolated from the PBMC layer,
with M-MDSCs identified as CD5^−CD21^−MHCII^−CD11b^+CD14^+CADO48A^−
cells, and PMN-MDSCs identified as CD5^−CD21^−MHCII^−CD11b^+
CD14^−CADO48A^+ cells.
Analysis of MDSC frequencies
Frequencies of MDSCs isolated from peripheral blood were reported as
median [25^th, 75^th percentiles]. A linear mixed effects model was
used to assess differences between PMN-MDSCs and M-MDSCs, and among
tumor-bearing, inflammatory disease and healthy dogs, and specific
contrasts were constructed to compare high and low burden tumors.
Frequencies of MDSCs were log transformed, ln (0.1+ frequency), prior
to the analysis.
Cytocentrifuge spin preparation
A Shandon Cytospin 2 centrifuge (Sandon Southern Products Ltd.,
Astmoor, UK) was used to deposit cells onto Shandon cytoslides (Thermo
Sandon Limited, UK). The slides were dried, stained with Modified
Wright’s (Siemens Hematek Stain Pak, NY, USA) using a Hematek automated
stainer (Siemens, Tarrytown, NY, USA) and examined with a BX50
microscope (Olympus, Tokyo, Japan). Images were captured with a SC50
camera and edited with CellSens^® software (Olympus; Southend-on-Sea,
UK).
Electron microscopy and ER dilation scoring
PMN-MDSCs and PMNs were isolated from two tumor-bearing dogs, while
monocytes were isolated from one tumor-bearing dog. Cells were fixed in
2% w/v paraformaldehyde and 1.5% w/v glutaraldehyde in 0.1 M sodium
cacodylate for 24 hours at 3 °C. After washing in 0.1 M sodium
cacodylate twice, each time for 30 minutes, cells were embedded in 2%
w/v agarose. Specimens were then dehydrated in a graded ethanol-water
series, before being immersed in agar resin. The specimens were left in
fresh agar resin for eight hours, before being hardened for 48 hours at
60 °C. Representative areas were selected and ultra-thin sections cut
at 70–80 nm using a diamond knife in an Ultracut S microtome (Reichert
Technologies; Munich, Germany). Sections were collected on 200 mesh
copper, stained with lead citrate, and viewed with a 1010 transition
electron microscope (Jeol; Peabody, MA, USA). Images were recorded
using an Orius CCD camera (Gatan; Pleasanton, CA, USA). Our approach
was adopted from a published protocol^[70]17, reviewing at least 100
cells per sample. The proportion of visible cytoplasmic area per cell
containing dilated ER was estimated, scores 1, 2, and 3 representing
areas of up to one third, more than one third but less than two thirds,
and more than two thirds respectively.
T cell suppression assay
Proliferation assays were performed in duplicate, when cell numbers
allowed, in 96-well, flat bottom culture plates pre-coated with
anti-dog CD3 mAb (clone CA17.2A12; Bio-Rad), applied as a 5 µg/ml
solution for two hours at 37 °C before washing. An aliquot of 100,000
healthy PBMCs was deposited into each well, alone or with either PMNs
from tumor-bearing or healthy dogs, or PMN-MDSCs, at a 1:1 ratio.
Anti-CD28 mAb (clone 1C6; ThermoFisher Scientific) was added to each
well at a final concentration of 2.5 µg/ml. Plates were incubated at
37 °C for 72 hours in an atmosphere of 5% carbon dioxide, before
staining of the cells for analytical flow cytometry on a BD FACSCanto
II. Responder PBMCs and co-cultured cells, if applicable, were
harvested and stained with eBioscience fixable viability dye
(eFluor780, Thermo Fisher Scientific) for 20 minutes at room
temperature, followed by a 30 minute incubation at 4 °C with a cocktail
comprising of anti-dog CD5 (as above) and AlexaFluor647-conjugated
anti-dog CD8 mAb (YCATE55.9; Bio-Rad). The cells were then fixed and
permeabilized (Foxp3/Transcription Factor Staining Buffer Set; Thermo
Fisher Scientific) prior to staining with pacific blue-conjugated
anti-mouse/rat Ki-67 (SolA15; Thermo Fisher Scientific) for 30 minutes
at 4 °C. A linear mixed effects model was used to analyze suppression
assay results. Normality of the residuals were inspected using
histograms and Shapiro-Wilk normality test. The analyses were carried
out in R using lme4 (Version 1.1.17), lmerTest (Version 3.0.1) and
multcomp (Version 1.4.8) packages.
RNA extraction
FACS™ was used to isolate MDSC subsets from dogs with cancer, alongside
PMNs and monocytes from both tumor-bearing and healthy dogs. Cells were
centrifuged at 600 g for five minutes at 4 °C, re-suspended in RNA-Bee
(Amsbio; Abingdon, UK), and stored at −80 °C until extraction. RNA
extraction was performed using the Direct-zol RNA MicroPrep Kit (Zymo
Research; Irvine, CA, USA) according to the manufacturer’s protocol.
RNA was stored at −80 °C.
Library preparation and sequencing
RNA sequencing (RNA-Seq) libraries were prepared and sequenced by the
Oxford Genomics Centre at the Wellcome Centre for Human Genetics, using
the protocol for low-input RNA library preparation with
Smart-seq2^[71]18. Briefly, full-length cDNA was generated from
0.6–1.0 ng of total RNA. Illumina libraries were prepared from cDNA
samples using the Nextera XT DNA Library Prep Kit (Illumina, San Diego,
CA, USA) and PCR-amplified with in-house indexing primers^[72]19. All
samples were sequenced on the Illumina HiSeq4000 platform, with 75 bp
paired-end sequencing.
Read processing and expression quantification
Reads were trimmed for Nextera, Smart-seq2 and Illumina adapter
sequences using skewer-v0.1.125^[73]20. Trimmed read pairs were aligned
to a modified reference genome comprising the canine genome Canis
familiaris CanFam3.1 and External RNA Controls Consortium (ERCC)
spike-in mix sequences (ThermoFisher), using HISAT2 version
2.0.4^[74]21 with default parameters. Duplicate reads were marked using
MarkDuplicates.jar implemented in Picard tools v1.92
([75]http://broadinstitute.github.io/picard/, February 2018). Binary
Alignment Map (BAM) alignments were name-sorted with Samtools version
1.1^[76]22. Reads mapping uniquely to exons of genes annotated in
Ensembl release 81^[77]23 were counted using featureCounts^[78]24
implemented in subread-v1.5^[79]25.
Data quality control and differential expression analysis
Alignment metrics were calculated using CollectRnaSeqMetrics from
Picard tools for both full BAM files, and BAM files with potential PCR
duplicates were marked. Additional metrics were calculated and
downstream analysis performed with custom R scripts using R core
tools^[80]26, v3.1.0 and v3.4.2 respectively. Differentially expressed
genes were identified for each comparison using edgeR
v3.20.4^[81]27,[82]28. Genes with significant differential expression
and a false discovery rate (FDR) ≤0.05 in each comparison were used for
gene-ontology enrichment analysis using GOseq v1.22.0^[83]29.
Gene enrichment comparisons were plotted on Venny 2.1.0
([84]http://bioinfogp.cnb.csic.es/tools/venny/). Ingenuity Pathway
Analysis (IPA) (Qiagen, Hilden, DE) was used for interpretation of the
RNA-Seq data, using differentially expressed genes whose fold change
(FC) ≥2 and FDR ≤ 0.05. In pathway enrichment analysis, p-values were
calculated by right-tailed Fisher’s exact tests, which indicate the
probability of association of molecules from the dataset with the
canonical pathway by random chance alone. The Z-score was used to
quantitatively compare the dataset with the canonical pathway patterns,
taking into account the activation state of one or more key molecules
when the pathway was activated, as well as the molecules’ causal
relationships with each other. Pathways with p ≤ 0.05 in the enrichment
analysis were considered enriched, while the activation states of
pathways were determined when |Z-score| ≥ 2. Heatmaps illustrating the
RNA-Seq dataset were created in Morpheus
([85]https://software.broadinstitute.org/morpheus/, Broad Institute),
using only those genes expressed in every patient and cell type with
transcripts per million (TPM) values of over 10. Clustering of the rows
and columns in the heatmap comparing transcriptomic signatures of
different cell types was performed using the 1-Spearman rank
correlation metric as the measure of dissimilarity. Box-and-whisker
plots were drawn and all transcriptomic analyses were undertaken in R
v3.4.2 (The R Foundation, Vienna, AT), using R packages lattice
v0.20.35 and ggplot2 v2.2.1. R was also used to create principal
component analysis (PCA) and volcano plots.
Reverse transcriptase-quantitative PCR
RNA was converted into cDNA using the High-Capacity RNA-to-cDNA Kit
(ThermoFisher Scientific), following the manufacturer’s protocol.
RT-qPCR reactions were prepared according to the manufacturer’s
protocol, using TaqMan Fast Advanced Master Mix (ThermoFisher
Scientific). Primers, all purchased from ThermoFisher Scientific,
recognized hypoxanthine phosphoribosyltransferase 1 (HPRT1;
Cf02690456_g1), ribosomal protein L13a (RPL13A; Cf04947268_gH),
lactoferrin (LTF; Cf02649397_m1), lipocalin 2 (LCN2; Cf02667820_m1),
cathelicidin (CAMP; Cf02626391_m1), erythrocyte band protein EPB41L3
(Cf02682517_m1), and the matrix metalloprotease MMP8 (Cf03649138_u1).
The reactions were run on a Quant Studio 6 Flex Real-Time PCR System
(ThermoFisher Scientific), using recommended cycle conditions for
TaqMan Fast Advanced Master Mix: hold at 50 °C for 2 minutes, hold at
95 °C for 20 seconds, and 40 cycles of denaturing for 1 second at
95 °C, followed by annealing and extending for 20 seconds at 60 °C.
No-template and no-reverse transcriptase reactions were used as
controls, verifying the specificity of the assay. PCR efficiency was
determined by testing the primers across a 4 or 5-fold logarithmic
dilution of cDNA template. The plot of Cq versus template concentration
was used to calculate the slope, and amplification efficiency (E) of
individual primers was determined by the equation
[MATH: E=10−1/slope :MATH]
. The most stable reference genes, HPRT1 and RPL13A, were selected from
a set of tested candidate reference genes as determined by the
qbase + (Biogazelle) implementation of geNorm. Relative expression of
genes was determined by Pfaffl’s model,
[MATH: RelativeExpression=
(Etarget)ΔCqtarget(control−sample)(Eref)ΔCqref(control−sample) :MATH]
where E[target] is the efficiency of the target gene primer, E[ref] is
the efficiency of the reference gene primer, ΔCq[target] is the
difference in Cq of C PMNs and PMN-MDSCs for the target gene
transcript, and ΔCq[ref] is the difference in Cq of C PMNs and
PMN-MDSCs for the reference gene transcript.
Cross-species comparisons
Data used for the cross-species analysis of PMN-MDSCs were obtained
from the authors^[86]30 and NCBI (GEO accession number
[87]GSE43254)^[88]31. Differential gene expression for murine data was
evaluated in GEO2R (NCBI), using the Benjamin-Hochberg multiple
comparisons correction and auto-detecting log transformation. Gene
lists used to create Venn diagrams excluded genes with absolute FC < 2
and FDR > 0.05. Only those genes expressed in all three species were
included in similarity score calculation. Gene lists for each species
were ranked in the following order: FDR ≤ 0.05 and FC ≥ 2, FDR ≤ 0.05
and FC ≤ −2, FDR ≥ 0.05 and FC ≥ 2 and FDR ≥ 0.05 and FC ≤ −2, so that
most significantly upregulated genes were at the top and the most
significantly downregulated genes were at the bottom of the list,
followed by non-statistically significant genes. Each
cell-type-specific signature from dog was compared with respective
human and murine signatures using the R package OrderedList
v1.48.0^[89]32. This tool determines the number of shared elements in
the first n elements of two lists and calculates a final similarity
score, genes receiving more weight the closer they are to the top or
bottom of the list. Similarity scores for n = 500 are reported. To
assess the statistical significance of the similarity scores, the
observed values were compared with a null distribution obtained by
reshuffling the genes.
Pathway enrichment analysis was performed in IPA for the 44 commonly
upregulated genes in human and canine PMN-MDSCs. Those pathways
containing two or more genes (from the list of 44 shared genes) showing
the strongest statistical significance were reported.
Results
Hypodense myeloid cell subsets accumulate in the peripheral blood of
tumor-bearing dogs
To test the hypothesis that phenotypically distinct hypodense myeloid
cell subsets resembling PMN-MDSCs and M-MDSCs exist in canine blood,
PBMCs were stained with a mAb panel reflective of the phenotypic
markers used to identify human MDSC subsets^[90]4,[91]6,[92]33. Using a
cascaded gating strategy as shown in Fig. [93]1a, hypodense myeloid
cells resembling MDSCs, i.e. CD5^−CD21^−MHCII^−CD11b^+ cells, were
stratified into two distinct subsets – one expressing CADO48A^+, a
canine specific neutrophil marker (putative PMN-MDSCs), and the other
expressing CD14^+ (putative M-MDSCs). Morphologic examination of
cytocentrifuged preparations of these two myeloid populations supported
their putative identity as MDSC subsets: the CADO48A^+ cells resembled
PMNs with segmented nuclei, while the CD14^+ cells resembled monocytes
with a large nucleus and vacuolar cytoplasm, reflecting MDSC images
previously published in the human and murine literature^[94]34–[95]37
(Fig. [96]1b). Parental gating analyses were also consistent with our
view that these cells were MDSCs (Supplementary Fig. [97]S1A).
Figure 1.
[98]Figure 1
[99]Open in a new tab
Two phenotypically distinct subsets of hypodense myeloid cells can be
isolated from canine peripheral blood. (a) Gating strategy used to
identify putative PMN-MDSC (CADO48A^+CD14^−) and M-MDSC
(CADO48A^−CD14^+) subsets in the peripheral blood of dogs. Shown are
representative examples from dogs that have PMN-MDSC frequencies
(relative to total PBMCs) similar to the median values of all dogs in
that group (cancer, top, median: 2.58%; inflammatory, middle, median:
1.33%; healthy, bottom, median: 0.78%). (b) Cytocentrifuge preparations
of flow-sorted MDSCs with PMN (top) and MONO (bottom) morphology. Scale
bars: 10 μm. (Images collected by B.S.). (c) Images obtained through
electron microscopy analysis of cell morphology, with arrows denoting
prominent ER. Scale bars: 500 nm, magnification 9700x, featured square
magnification 3600x. (Images collected by M.T.). (d) C PMNs, PMN-MDSCs,
C MONOs, and M-MDSCs were scored for the presence of dilated ER; the
bar chart depicts the proportion of cells with each ER dilation score.
(e) Box-and-whisker plots depicting frequency of PMN-MDSCs in
peripheral blood of healthy and inflammatory controls as well as
tumor-bearing dogs, grouped by cancer subtype (HM: hematopoietic
mesenchymal/mesodermal, NHM: non-hematopoietic mesenchymal/mesodermal,
EPI: epithelial) and burden (low vs high). Frequencies are expressed as
a percentage of total PBMCs. A capital letter denotes that the two
groups are significantly different with p < 0.001; a lowercase letter
denotes a significant difference with p < 0.01. In the case of all
box-and-whisker plots, the box shows the respective 25th and 75th
percentiles, the line indicates the median value, and the whiskers
stretch from the lowest to the highest data points still within 1.5
times the interquartile range of the respective lower and upper
quartiles. Red values indicate patient frequencies that are off-scale.
Each dot represents a single dog.
We next interrogated the ultrastructure of these myeloid subsets, in
particular to ask whether they exhibited features of ER stress,
manifested through dilation, as has been described in human MDSC
subsets^[100]17. Putative PMN-MDSCs, putative M-MDSCs, PMNs and MONOs
were isolated from tumor-bearing dogs and scored for the presence of
dilated ER. Although a small proportion of cancer PMNs and MONOs had
mild ER dilation (see arrows), with a score of 1, only the putative
PMN-MDSCs and putative M-MDSCs exhibited moderate to marked ER dilation
(see arrows), with scores of 2 or 3 (Fig. [101]1c,d), further
supporting their identity as MDSCs.
Since increased frequencies of MDSC subsets have been described in
human cancer patients and tumor-bearing mice compared to individuals
with non-neoplastic inflammatory diseases and healthy controls, we set
out to determine whether this pattern could be observed in dogs. First,
a global comparison of CADO48A^+ and CD14^+ CD5^−CD21^−MHCII^−CD11b^+
myeloid cell frequencies (relative to total PBMCs) in the peripheral
blood of tumor-bearing versus control dogs revealed an increased
frequency of the CADO48A^+ myeloid population (putative PMN-MDSCs;
2.53% [0.93, 4.94]) in comparison to healthy dogs (0.78% [0.13, 1.95];
p = 1.8 × 10^−12) and those with non-neoplastic inflammatory diseases
(1.33% [0.31, 2.75]; p = 0.0024) (Supplementary Fig. [102]S1B). The
CD14^+ myeloid population (putative M-MDSCs) was also increased in
tumor-bearing dogs (0.20% [0.06, 0.57]) when compared to healthy
control dogs (0.14% [0.05, 0.24]; p = 0.018) but not those with
inflammatory disease (0.28% [0.12, 0.64]; p = 0.72) (Supplementary
Fig. [103]S1C).
Tumor-bearing dogs were then grouped according to broad tumor histotype
(hematopoietic mesenchymal/mesodermal, HM; non-hematopoietic
mesenchymal/mesodermal, NHM; and epithelial, EPI) and based on tumor
burden (low versus high burden) (Fig. [104]1e). In the case of the
putative PMN-MDSCs, dogs with high burden HM tumors had higher median
frequency than those with low burden HM tumors (3.20% [1.46, 6.32]
versus 1.20% [0.69, 1.91]; p = 0.0086); statistically significant
differences in frequency with burden were not present for NHM tumors
(1.69% [1.48, 4.79] versus 0.89% [0.72, 1.47]; p = 0.17) or EPI tumors
(2.81% [1.37, 5.30] versus 1.50% [0.40, 6.31]; p = 0.28). Furthermore,
dogs with a high tumor burden, regardless of histotype, had higher
frequencies of these cells than healthy control dogs (HM: 3.20% [1.46,
6.32] versus 0.78% [0.13, 1.95], p = 1.5 × 10^−13; NMH: 1.69% [1.48,
4.79] versus 0.78% [0.13, 1.95], p = 0.0034; EPI: 2.81% [1.37, 5.30]
versus 0.78% [0.13, 1.95], p = 5 × 10^−6). Dogs with high burden HM or
EPI tumors also had higher frequencies of the putative PMN-MDSCs than
those of non-neoplastic inflammatory control dogs (HM: 3.20% [1.46,
6.32] versus 1.33% [0.31, 2.75], p = 0.00015; EPI: 2.81% [1.37, 5.30]
versus 1.33% [0.31, 2.75], p = 0.0091, respectively). Of dogs with low
burden tumors, only those bearing EPI tumors had higher frequencies of
these cells than healthy control dogs (1.50% [0.40, 6.31] versus 0.78%
[0.13, 1.95], p = 0.00098), but not inflammatory control dogs (1.50%
[0.40, 6.31] versus 1.33% [0.31, 2.75], p = 0.16). Similar differences
were not apparent for putative M-MDSCs (Supplementary Fig. [105]S1D).
However, dogs with high burden as well as low burden EPI tumors had
higher frequencies of putative M-MDSCs than healthy control dogs (high
burden: 0.31% [0.09, 0.87] versus 0.14% [0.05, 0.24], p = 0.037; low
burden: 0.21% [0.15, 0.86] versus 0.14% [0.05, 0.24], p = 0.01).
In toto, these findings added further credibility to our hypothesis
that the myeloid subsets we identified were indeed canine MDSC
populations. However, legitimately labeling the cells as MDSCs would
require evidence of their suppressive activity, prompting functional
studies in vitro. For this purpose, we focused on the most numerous of
the two myeloid populations, i.e. the CADO48A^+ cells that were
putatively PMN-MDSCs, to ensure that we would have sufficient cells
available to allow reliable suppression assays to be performed.
Hypodense CADO48A^+ myeloid cells suppress CD8^+ T cell proliferation in
vitro
The CADO48A^+ cells suppressed polyclonal CD8^+ T cell proliferation as
indicated by reduced Ki-67 expression (Fig. [106]2a), confirming their
functional credentials as regulatory cells. PMNs isolated from
tumor-bearing dogs showed no statistically significant suppressive
activity (Fig. [107]2b). Our findings therefore confirmed the
suppressive function of the CADO48A^+ cells. Given both the phenotypic
resemblance of these cells to PMN-MDSCs and their regulatory
credentials, we were able to confirm their identity as PMN-MDSCs. We
hypothesized that the CD14^+ myeloid cells would also be suppressive,
and thus tentatively labeled them as M-MDSCs; however, in the absence
of evidence of suppressive function, this designation remained
speculative. Further interrogation of the molecular phenotype of the
myeloid cells followed, drawing comparisons with both human and murine
MDSCs.
Figure 2.
[108]Figure 2
[109]Open in a new tab
Canine CADO48A^+ myeloid cells exhibit T cell suppression. (a) Exemplar
of Ki-67 incorporation in CD5^+CD8^+ cells after PBMCs were co-cultured
alone or 1:1 with H PMNs, C PMNs, and PMN-MDSCs for 72 hours. Exemplar
depicts results using PBMCs from one healthy control dog. (b) Summary
of proliferation assay results using cells isolated from five
tumor-bearing dogs (normalized to PBMCs alone, average of co-culture
results with two different healthy PBMCs). Top: Mean proportion of T
cells that are Ki67+ [+ as superscript], with each line identifying C
PMNs and PMN-MDSCs from the same tumor-bearing dog, as well the H PMNs
used in that experiment. Bottom: Box-and-whisker plots depicting
arithmetic mean values (dots) for all experiments. In each case, the
box shows the respective 25th and 75th percentiles, the line indicates
the median value, and the whiskers stretch from the lowest to the
highest data points still within 1.5 times the interquartile range of
the respective lower and upper quartiles. A letter indicates a
significant difference for that comparison (p < 0.01).
Canine MDSC subsets show distinctive transcriptomic signatures
We undertook RNA-Seq of PMN-MDSCs (n = 8), M-MDSCs (n = 5), PMNs
(n = 9), and MONOs (n = 8) isolated from tumor-bearing dogs, and PMNs
(n = 5) and MONOs (n = 3) isolated from healthy dogs. Principal
component analysis of the samples from all dogs suggest the distinctive
transcriptomes of the MDSC subsets, which were more closely related to
their respective conventional populations than to each other
(Fig. [110]3a). Similar conclusions were derived from a heatmap
analysis comparing PMN-MDSCs, M-MDSCs, PMNs isolated from healthy (H
PMN) and tumor-bearing patients (C PMN), and MONOs isolated from
healthy (H MONO) and tumor-bearing patients (C MONO), supporting the
finding that putative M-MDSCs, C MONOs, and H MONOs were more closely
related to each other than to PMN-MDSCs, C PMNs, and H PMNs, which
occupied a separate cluster (Fig. [111]3b). Within each cluster the
respective MDSC subset was distinct, confirming its molecular
credentials as a separate population from the adjacent conventional
cells.
Figure 3.
[112]Figure 3
[113]Open in a new tab
Canine MDSC subsets are characterized by distinct transcriptomic
signatures. (a) Principal component analysis depicting transcriptional
similarities of the different cell populations (demarcated by colors)
and whether the sample came from a healthy (circle) or tumor-bearing
(triangle) dog. Each symbol indicates one dog. The ellipse summarizes
each cell subtype grouping using the multivariate t-distribution. PC1
accounted for 63.8% of all variance, while PC2 accounted for 8.22% of
all variance. (b) Heatmap comparing transcriptional signatures across
the 6 different cell populations, using the 1-Spearman rank correlation
metric. Red indicates positive enrichment, and blue indicates negative
enrichment. Increased vertical length of the dendrogram is inversely
proportional to similarity between the cell types. (c,d) Volcano plot
depicting differentially expressed genes in PMN-MDSCs relative to C
PMNs (c) and putative M-MDSCs relative to C MONO MONOs (d). The red
line indicates a significant FDR. Each dot represents one gene, and
genes previously associated with MDSC function or novel but strongly
upregulated genes are labeled in red.
On deeper scrutiny of the different patterns of gene expression between
cell populations, we observed that canine PMN-MDSCs differentially
expressed a number of transcripts associated with MDSC function
compared to C PMNs, including those encoding the matrix
metalloproteases MMP8 and MMP9, nitric oxide synthase 2 (NOS2), NADPH
oxidase 2 (NOX2), myeloperoxidase (MPO), cyclooxygenase 1 (COX1), the
chemokine CXCL17, prostaglandin E synthase (PTGS1) and prostaglandin E
receptor 2 (PTGER2) (Fig. [114]3c). A number of transcripts previously
not attributed to PMN-MDSC function were also expressed at higher
levels, including those encoding succinate receptor 1 (SUCNR1),
cathelicidin antimicrobial peptide (CAMP), and cathepsin G (CTSG).
Similar observations were made in putative canine M-MDSCs, which
expressed transcripts encoding the calcium-binding proteins S100A8 and
S100A12 at high levels compared to C MONOs, in addition to tetraspanin
2 (TSPAN2), IL1 receptor 2 (IL1R2), and IL4 receptor (IL4R)
(Fig. [115]3d). Of interest, the respective PMN and MONO populations
showed a number of differentially expressed genes when comparing
tumor-bearing and healthy dogs (Supplementary Figs [116]S2A–[117]S2D).
Ingenuity Pathway Analysis was performed on all differentially
expressed genes in PMN-MDSCs compared to C PMNs with an absolute FC ≥ 2
and FDR ≤ 0.05. Two pathways were found to be positively enriched in
PMN-MDSCs, eukaryotic initiation factor 2 (EIF2) signaling and
peroxisome proliferator-activated receptor (PPAR) signaling, while
numerous pro-inflammatory pathways were negatively represented
(Fig. [118]4).
Figure 4.
Figure 4
[119]Open in a new tab
Canine PMN-MDSC transcriptomic signatures show enrichment of
immune-related pathways. Ingenuity Pathway Analysis (IPA) of
differentially expressed genes in PMN-MDSCs relative to C PMNs. Only
those genes with a |FC| ≥ 2 and FDR ≤ 0.05 were imported into IPA.
Greater color intensity correlates with stronger enrichment of Z-score,
positive (orange) or negative (blue). Ratio refers to the proportion of
genes represented in our data set relative to all known genes in IPA’s
database for a given pathway.
Taken together, these findings substantiated our view that these
hypodense myeloid populations were indeed MDSC subsets that were
distinct from the comparative conventional cells.
Cross-species analysis of PMN-MDSCs identifies a conserved gene signature
Focusing on the more numerous PMN-MDSC population, for which we had
functional data, we next formally assessed the degree of similarity of
the respective canine, human, and murine cells of this phenotype. We
did not perform parallel analyses for our putative M-MDSC population
since we have not yet validated their identity by T cell suppression
assays.
We compared our canine RNA-Seq data with those previously published on
human and murine PMN-MDSCs. For all three species, genes differentially
expressed by PMN-MDSCs compared to C PMNs were ordered according to the
FDR of their expression, using only those genes that were detected in
all three species. The resulting lists for each species were then
analyzed for similarity. The signatures of the top 500 differentially
expressed genes were statistically similar between canine and human
PMN-MDSCs (Fig. [120]5a), but no such pattern was observed when this
same list of genes were compared between canine and murine PMN-MDSCs
(Supplementary Fig. [121]S3A,B). To further understand the similarity
between canine and human PMN-MDSCs, we identified those genes
differentially expressed by PMN-MDSCs in comparison to C PMNs of both
species with a FC ≥ 2. A comparison of these two lists identified 44
genes, including MPO, ELANE, as well as numerous ribosomal proteins
(Fig. [122]5b and Supplementary Fig. [123]S3C). Pathway analysis of
these 44 genes highlighted six enriched pathways in PMN-MDSCs,
including EIF2 signaling and TREM1 signaling (Supplementary
Fig. [124]S3D).
Figure 5.
[125]Figure 5
[126]Open in a new tab
Cross-species comparisons of PMN-MDSCs highlight common transcriptomic
signatures across three mammalian taxa. (a) Similarity score (square)
and p-value (circle) are graphed using the top 100–500 canine and human
PMN-MDSC differentially expressed genes input into the ‘OrderedList’ R
program. Dashed line indicates p = 0.05, and up to the top 500 genes
are statistically similar in both species. (b,c) Venn diagram comparing
upregulated genes in canine and human (b) and canine, human, and murine
(c) PMN-MDSCs relative to C PMNs. Only those genes with a FC ≥ 2 and
FDR ≤ 0.05 were included in this analysis. (d) Bar chart comparing the
fold change of the five conserved genes across the three species.
A comparison of those genes differentially expressed by PMN-MDSCs
compared to C PMNs of dogs, humans and mice revealed five genes shared
by all three species (Fig. [127]5c) – MMP8, LTF, LCN2, EPB41L3, and
CAMP – four of which had not previously been implicated in PMN-MDSC
function. A comparison of the FC expression in each species for these
five genes, both in the respective transcriptomic datasets – including
our own RNA-Seq dataset – and confirmatory RT-qPCR assays, revealed
broad concordance (Fig. [128]5d and Supplementary Fig. [129]S3E).
Discussion
Pet dogs with spontaneous tumors have contributed to the development of
a variety of therapies used in human medicine^[130]11. Their outbred
nature, larger size, presence of an intact immune system, and exposure
to environmental factors shared with humans makes them an attractive
model to better understand cancer development, progression, and
treatment^[131]11,[132]13. Although previous studies in dogs with
spontaneous tumors have identified MDSCs, these studies did not
differentiate between the two established subsets of
MDSCs^[133]15,[134]16. Our study therefore set out to characterize the
cellular and molecular phenotype of PMN-MDSCs and M-MDSCs in dogs, with
the ultimate aim of better understanding these two cell populations and
their role in cancer.
We identified myeloid populations in canine peripheral blood resembling
both murine and human MDSCs, using a gating schema similar to that used
to identify these cells in humans^[135]4,[136]6,[137]33. The lack of
availability of canine-specific or validated cross-reactive mAb against
CD15, CD66b and/or LOX-1 in dogs at the time of the current study
precluded the use of these markers in our panel for PMN-MDSCs.
Nevertheless, we were able to capitalize on the availability of a
validated mAb used to identify PMNs in dogs^[138]38, which we
substituted as a sentinel for CD15. This mAb was also used in one of
the two original reports describing MDSCs in dogs^[139]16. The
hypodense myeloid cells isolated using this mAb clearly resembled
PMN-MDSCs by light and electron microscopy, thus lending support to
their identity as PMN-MDSCs. In the case of M-MDSCs, the availability
of a validated cross-reactive mAb against canine CD14^[140]39
facilitated the identification of this subset in a directly comparable
manner to that of human M-MDSCs. Given that CD14 may also be expressed
by non-myeloid cells^[141]40, we considered it important to adopt a
cascaded gating approach focusing only on CD5^−CD21^−CD11b^+ cells in
our analyses. Electron microscopic images added additional weight to
the putative identity of the MDSC subsets, demonstrating greater ER
dilation than the respective conventional cells^[142]17. Further
confirmation of the identify of these subsets came from our downstream
transcriptomic studies.
Significantly higher frequencies of these MDSC subsets were documented
in the peripheral blood of tumor-bearing dogs than healthy controls,
showing parallels to findings in human patients^[143]41,[144]42.
Furthermore, bulkier tumors of a variety of histotypes were associated
with higher frequencies of PMN-MDSCs – the more prevalent of the two
populations in peripheral blood – concordant with the prevailing
viewpoint that inflammatory signals generated in the tumor, which would
broadly correlate with tumor size, drive the differentiation of
MDSCs^[145]43,[146]44. This phenomenon is also consistent with studies
showing that tumor resection reduces^[147]45,[148]46, and tumor
recurrence increases^[149]47, MDSC frequency. Ultimate proof that the
myeloid cells identified in our study were indeed PMN-MDSCs came with
demonstration of their suppressive function, using a standard,
polyclonal T cell suppression assay^[150]48. Variability of the
suppression data reflected the clinical nature of samples, derived from
individual dogs with various cancer histotypes. Moreover, PMN-MDSCs
typically demonstrate only modest suppressive function that diminishes
with age of sample in the context of polyclonal assays in
vitro^[151]4,[152]6, prompting our wish to streamline assays and
minimize post-sorting delays before cells were put into culture. We
therefore employed an assay whose readout was Ki-67 expression, which
correlates with proliferation in multiple different contexts and shows
greater sensitivity and ease of use than cell tracer
dyes^[153]49,[154]50. Furthermore, preliminary studies confirmed the
close correlation between Ki-67 expression and dye dilution as metrics
of T cell proliferation in our hands (data not shown).
Deeper analysis of the phenotype of the canine MDSC subsets by RNA-Seq
yielded a number of interesting observations. Whether or not MDSCs are
indeed a separate subset of cells has been a controversial topic in the
field for a number of years^[155]2,[156]4. Our transcriptomic findings
suggested that they possess distinct molecular signatures, as shown by
PCA and heatmaps of the respective populations. The canine MDSCs showed
increased expression of a number of canonical genes implicated in MDSC
function. For example, PMN-MDSCs produce reactive oxygen and nitrogen
species^[157]51,[158]52: in line with these characteristics, the canine
PMN-MDSCs showed greater abundance of transcripts encoding NOS2, NOX2,
and MPO than PMNs from the same patient^[159]3,[160]51,[161]53. COX1,
which mediates the synthesis of prostaglandins and has been implicated
in MDSC development^[162]54,[163]55, was also differentially
represented in canine PMN-MDSCs, as were PTGS1 and PTGER2. Furthermore,
transcripts encoding the matrix metalloproteases MMP8 and MMP9 were
differentially expressed by canine PMN-MDSCs. Functioning in degrading
the extracellular matrix, these enzymes mediate the release of vascular
endothelial growth factor (VEGF) to promote new vessel development and
metastasis^[164]56,[165]57. Interestingly, the transcript encoding
CD177, a PMN marker^[166]58,[167]59 expressed on the surface of MDSCs
as well as MDSC exosomes^[168]60, was also differentially expressed by
canine PMN-MDSCs. This observation prompted consideration of CD177 as a
marker to distinguish canine PMN-MDSCs from PMNs. Increased expression
of CXCL17 by PMN-MDSCs was also of interest, as previous studies have
implicated CXCL17 in the recruitment of MDSCs and poor prognosis in
human cancer patients^[169]61,[170]62. Another differentially expressed
transcript, SUCNR1, has been implicated in prostaglandin synthesis and
promotion of an anti-inflammatory phenotype in a model of multiple
sclerosis^[171]63; a similar mechanism may be at play in PMN-MDSCs. On
the other hand, putative M-MDSCs showed greater abundance of
transcripts encoding both the IL4R, consistent with previous
data^[172]8,[173]64, and S100A8, serum concentrations of which have
been associated with poor cancer survival^[174]36,[175]65–[176]67.
IL1R2 was also of interest, as it has previously been implicated in the
transcription of IL-6 and VEGF, promoting angiogenesis^[177]68.
Putative canine M-MDSCs differentially expressed transcripts encoding
thrombospondin 1 (THBS1), another protein implicated in MDSC
migration^[178]60, and TPSAN1, which has been implicated in cell
invasion and motility in tumor cells^[179]69. Whether high expression
of TPSAN1 by M-MDSCs could promote tumor progression was an intriguing
question. IPA revealed additional interesting insights. One of the two
sole pathways enriched in canine PMN-MDSCs – EIF2 signaling – has been
previously reported to be enriched in human MDSCs^[180]30 and is
induced by ER stress^[181]30,[182]70, concordant with our
ultrastructural analyses of these cells. PPAR signaling, meanwhile, has
been implicated in the recruitment and expansion of MDSCs by a variety
of extrinsic mechanisms^[183]71, but intrinsic roles for this signaling
axis in MDSCs have hitherto not been recognized. Nevertheless, this
pathway has anti-inflammatory properties in myeloid cells in
general^[184]72–[185]74, speaking to a possible role in maintaining the
suppressive status of MDSCs. In contrast to EIF2 and PPAR signaling, a
number of pro-inflammatory pathways were less active in canine
PMN-MDSCs than C PMNs, consistent with the prevailing view of MDSCs as
immunosuppressive cells. Taken together, the canine transcriptomic data
therefore reconciled with previously published findings on these MDSC
subsets in other species, while also revealing some novel avenues for
future research.
Harnessing previously published transcriptomic data for humans and
mice, we were surprised to discover that only the human and canine
PMN-MDSCs had a significantly similar pattern of differentially
expressed genes, adding support to the notion that the dog provides an
attractive model for human cancer^[186]11,[187]13,[188]75,[189]76.
However, owing to the relative lack of available transcriptomic data in
other species, these comparisons were made using only one human and one
murine publication, both of which were based on gene microarray
experiments. This difference in technical platform from our analysis
had the potential to introduce bias into the comparisons, adding a note
of caution to these preliminary findings. Nevertheless, using this
published dataset to compare canine to human PMN-MDSCs identified 44
commonly upregulated genes. Importantly, pathway enrichment analysis
using the 44 shared genes highlighted six pathways that are enriched in
PMN-MDSCs. Interestingly, the two pathways with the most significant
activation states in our canine PMN-MDSCs (EIF2 signaling and TREM1
signaling) were also highly enriched in the 44 genes shared between the
two species, emphasizing the importance of these pathways to MDSC
function^[190]30,[191]77. HIF1α has been implicated in the
differentiation of MDSCs to suppressive tumor-associated
macrophages^[192]78,[193]79, while Gαi signaling is required for the
activation of STAT3^[194]80,[195]81, an important transcription factor
in PMN-MDSC development and function^[196]82,[197]83. Representation of
the colorectal cancer metastasis signaling pathway presumably reflects
the importance of these cells to the dissemination of colorectal
cancer^[198]84, but this notion remains speculative in the absence of
more direct evidence. Enrichment of the phagosome maturation pathway
was also interesting, because to the best of our knowledge it has not
previously been associated with MDSC function. Phagocytosis is a
well-established phenomenon in PMNs^[199]85, raising the important
question of whether PMN-MDSCs also show phagocytic function, perhaps as
an anti-microbial defense mechanism.
To further drill down on potential evolutionarily conserved mechanisms,
we asked whether there were genes commonly upregulated in the PMN-MDSCs
of all three species; five such genes were identified. Four of the five
genes have not previously been implicated in PMN-MDSC function, and
three of them – LTF, LCN2, and CAMP – play an important antimicrobial
role^[200]86,[201]87. LCN2 and LTF are both iron-binding proteins,
raising the question of whether iron is important for MDSC suppressive
function. Interestingly, LCN2 expands regulatory T cells^[202]88 and
deactivates macrophages^[203]89, and LCN2 and LTF have been shown to
play a protective role against oxidative stress^[204]90,[205]91.
Furthermore, LTF has been shown to inhibit neutrophil and eosinophil
migration^[206]92,[207]93. These novel observations, made by leveraging
the power of evolution, therefore raise the intriguing possibility that
PMN-MDSCs serve a hitherto unrecognized role in anti-microbial
defenses, and/or have co-opted conserved antimicrobial peptides to
serve immunoregulatory functions to promote tumor growth. In synopsis,
both individual genes and evolutionarily conserved pathways shape the
view that canine PMN-MDSCs show striking similarities to those of other
mammalian species, but also raise important new questions about the
functional breadth and versatility of these intriguing cells.
Supplementary information
[208]Supplementary Figures with Captions^ (855.6KB, pdf)
[209]41598_2019_40285_MOESM2_ESM.pdf^ (826KB, pdf)
Supplementary Figures with Captions, Changes Tracked
Acknowledgements