supplementary materials for - science · 2020. 2. 14. · fig. s3. sample labels and marker genes...
TRANSCRIPT
immunology.sciencemag.org/cgi/content/full/5/44/eaay6017/DC1
Supplementary Materials for
Defining the emergence of myeloid-derived suppressor cells in breast cancer using
single-cell transcriptomics
Hamad Alshetaiwi, Nicholas Pervolarakis, Laura Lynn McIntyre, Dennis Ma, Quy Nguyen, Jan Akara Rath, Kevin Nee, Grace Hernandez, Katrina Evans, Leona Torosian, Anushka Silva, Craig Walsh, Kai Kessenbrock*
*Corresponding author. Email: [email protected]
Published 21 February 2020, Sci. Immunol. 5, eaay6017 (2020)
DOI: 10.1126/sciimmunol.aay6017
The PDF file includes:
Fig. S1. Expansion of CD11b+Gr1+ cells during tumor progression in PyMT mice. Fig. S2. MDSCs emerge predominantly in spleen of tumor-bearing mice. Fig. S3. Sample labels and marker genes from scRNAseq analysis. Fig. S4. CD84 is a generalizable MDSC marker in different breast cancer models. Fig. S5. CD84 and JAML are up-regulated by in vitro–generated mouse and human MDSCs. Fig. S6. Characterization and validation of myeloid cell subsets for CD84 and JAML expression. Fig. S7. Reconstruction of MDSC differentiation trajectory in neutrophils and monocytes. Legends for tables S1 to S10
Other Supplementary Material for this manuscript includes the following: (available at immunology.sciencemag.org/cgi/content/full/5/44/eaay6017/DC1)
Table S1 (Microsoft Excel format). Marker genes from combined Seurat analysis. Table S2 (Microsoft Excel format). Marker genes from Seurat analysis of monocytes only. Table S3 (Microsoft Excel format). Gene signature from G-MDSCs-versus-neutrophils comparison. Table S4 (Microsoft Excel format). Gene signature from M-MDSCs-versus-monocytes comparison. Table S5 (Microsoft Excel format). Combined MDSC signature gene list. Table S6 (Microsoft Excel format). GO terms (Biological Process 2018) MDSC gene signature. Table S7 (Microsoft Excel format). qPCR primer sequences. Table S8 (Microsoft Excel format). Marker genes from Seurat analysis of neutrophils only. Table S9 (Microsoft Excel format). Neutrophil-specific Monocle state marker genes. Table S10 (Microsoft Excel format). Monocyte-specific Monocle state marker genes.
CD11b+Gr157.6
0-103
103
104
105
0
-103
103
104
105
Gr1
CD11b+Gr166.7
0-103
103
104
105
CD11b
0
-103
103
104
105
Gr1
Specimen_001_2PYMT_BM_026.fcsCD45+87725
CD11b+Gr137.8
0-103
103
104
105
0
-103
103
104
105
Specimen_001_2PYMT_blood_022.fcsCD45+92253
CD11b+Gr13.60
0-103
103
104
105
0
-103
103
104
105
CD11b+Gr127.7
0-103
103
104
105
0
-103
103
104
105
Specimen_001_2PYMT_sple en_024.fcsCD45+92521
CD11b+Gr10.14
0-103
103
104
105
0
-103
103
104
105
CD11b+Gr143.3
0-103
103
104
105
0
-103
103
104
105
Specimen_001_1PYMT_lung_018.fcsCD45+64897
CD11b+Gr114.5
0-103
103
104
105
0
-103
103
104
105
CD11b+Gr18.70
0-103
103
104
105
0
-103
103
104
105
Specimen_001_1PYMT_tumor_020.fcsCD45+20327
CD11b+Gr10.18
0-103
103
104
105
0
-103
103
104
105
CD11b+Gr118.5
0-103
103
104
105
0
-103
103
104
105
Specimen_001_ALL_PYMT_brain-1_015.fcsCD45+11097
CD11b+Gr12.34
0-103
103
104
105
0
-103
103
104
105
WT
PyMT
0
20
40
60
80
100
% o
f C
D11b+
Gr1
*
WT
PyM
T0
20
40
60
% o
f C
D11b+
Gr1
*
WT
PyM
T0
20
40
60
% o
f C
D11b+
Gr1
*
WT
PyM
T0
20
40
60
% o
f C
D11b+
Gr1
*
WT
PyM
T0
5
10
15
20
% o
f C
D11
b+
Gr1
*
WT
PyM
T0
20
40
60
% o
f C
D11b+
Gr1
*
CD11b
Gr1
Bone Marrow Blood Spleen Lung MFP vs Tumor Brain
WT
Py
MT
WTPy
MT
0.0
0.1
0.2
0.3
0.4
0.5
Sp
leen
We
igh
t (g
)
*
PyMTWT
1cm
fig S1
A
B
C
D E
Fig. S1. Expansion of CD11b+Gr1
+ cells during tumor progression in PyMT mice.
(A-B), Tissues from tumor-bearing PyMT and WT mice were collected and analyzed by FACS.
Cells from WT (A) and PyMT (B) mice were gated on CD45+ and analyzed using CD11b/Gr1
to identify neutrophils/monocytes, which expanded significantly during tumor progression in
bone marrow, blood, spleen, lung, brain and tumor compared to WT. (C) Combined
quantification of FACS results including statistical analysis is shown in bar graphs unpaired t-
test (Mean ± SEM of n =3) *P< 0.05. (D-E) Spleen from tumor-bearing PyMT (14 weeks) was
enlarged compared to WT.
Fig. S2. MDSCs emerge predominantly in spleen of tumor-bearing mice.
(A) Experimental overview. Bone marrow, spleen and lung were processed into single cell
suspensions and (sytox blue-negative) CD45+CD11b
+Gr1
+ cells were sorted and subjected to
functional T cell suppression and ROS formation assays. (B-C) Splenic CD11b+Gr1
+ cells from
tumor-bearing mice suppress T cell proliferation. Histogram overlay (B) and quantitative bar
charts (C) showing CD4/CD8 T cell proliferation measured by FACS. (D-E), Bone marrow-
derived CD11b+Gr1
+ cells from tumor-bearing mice show non-significant suppression of T cell
activation. (F-G) CD11b+Gr1
+ cells were sorted from tumor-bearing mouse lungs and co-
cultured with activated T cells showed no effect in T cell proliferation. (H-I), ROS formation in
CD11b+Gr1
+ cells from tumor-bearing and control mice. PMA-treated cells were used as
positive control. ROS was measured by FACS using H2DCFDA in CD11b+Gr1
+ cells from
bone marrow, spleen, and lung from control and tumor-bearing mice. (C-I) Statistical analysis
unpaired t-test (Mean ± SEM of n = 3) *P< 0.05. ns = not significant. Color labels (B-G) in
control samples, T cells (red) activated by CD3/CD28 (blue), activated T cells plus
CD11b+Gr1
+ cells from control spleens or bone marrow (orange) and activated T cells plus
CD11b+Gr1
+ cells from spleen, bone marrow or lung of tumor-bearing mice (green).
Fig. S3. Sample labels and marker genes from scRNAseq analysis.
(A) Seurat analysis of combined CD11b+Gr1
+ cells from WT and tumor-bearing PyMT mouse
spleens shown in tSNE projection labeled by tissue source. (B) Seurat analysis subsetted on
monocytes only from WT and tumor-bearing PyMT mouse spleens shown in tSNE projection
labeled by tissue source. (WT = blue; PyMT = red). (C-D) Heatmaps of Top 10 upregulated
genes of all clusters in of combined Seurat analysis including G-MDSC cluster C2 (C) and
subset monocyte analysis (D) in all monocyte clusters including M-MDSC cluster M2. (E-F)
Membership pie charts demonstrated clusters belong to WT or PyMT.
fig S4
FMO-CD84
SS
C-A
CD84 expression
0-103
103
104
105
0
20
40
60
80
100
No
rmaliz
ed
To M
odal
0-103
103
104
105
0
20
40
60
80
100
CD84
Isotype CD84-PyMTCD84-WT
Spleen MFP vs TM
A
Spleen MFP vs TM
48629 587928482
0-103
103
104
105
Comp-PE-A :: JAML
0
20
40
60
80
100
No
rma
lize
d T
o M
od
e
Sample NameSubset Name CountCD11b+Gr1 372 CD11b+Gr1 5879 CD11b+Gr1 4105
0-103
103
104
105
Comp-PE-A :: JAML
0
20
40
60
80
100
No
rma
lize
d T
o M
od
e
Jaml+1.36
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_33_PYMT_SPLN_iso_033.fcsCD11b+Gr14105
0-103
103
104
105
Comp-PE-A :: JAML
0
20
40
60
80
100
No
rmaliz
ed T
o M
od
e
Sample Name Subset Name Count
Specimen_001_21_WT_SPLN_021.fcs CD11b+Gr1 372
Specimen_001_24_PYMT_SPLN_024.fcs CD11b+Gr1 5879
Specimen_001_33_PYMT_SPLN_iso_033.fcs CD11b+Gr1 4105
Jaml+
1.36
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_33_PYMT_SPLN_iso_033.fc s
CD11b+Gr1
4105
Norm
aliz
ed T
o M
od
al
JAMLFMO-JAML
SS
C-A
Isotype JAML-PyMTJAML-WT
B
CD84+0
0-103
103
104
105
0
50K
100K
150K
200K
250K JAML+0
0-103
103
104
105
0
50K
100K
150K
200K
250K
JAML expression
BM Lung
SS
C-A
WT
4T
1
Spleen MFP vs TM
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_20_WT_SPLN_020.fcsCD11b+Gr1+1460
CD84+27.4
0-103
103
104
105
0
50K
100K
150K
200K
250K
SS
C-A
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_26_WT_MFP_026.fcsCD11b+Gr1+271
CD84+11.4
0-103
103
104
105
0
50K
100K
150K
200K
250K
SS
C-A
CD84+2.80E-3
0-103
103
104
105
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_8_WT_BM_008.fcsCD11b+Gr1+35723
CD84+1.70E-3
0-103
103
104
105
0
50K
100K
150K
200K
250K
SS
C-A
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_14_WT_LUNG_014.fcsCD11b+Gr1+6614
CD84+0.017
0-103
103
104
105
0
50K
100K
150K
200K
250K
SS
C-A
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_20_WT_SPLN_020.fcsCD11b+Gr1+1460
CD84+27.4
0-103
103
104
105
0
50K
100K
150K
200K
250K
SS
C-A
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_26_WT_MFP_026.fcsCD11b+Gr1+271
CD84+11.4
0-103
103
104
105
0
50K
100K
150K
200K
250K
SS
C-A
CD84+2.80E-3
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_8_WT_BM_008.fcsCD11b+Gr1+35723
CD84+1.70E-3
0-103
103
104
105
0
50K
100K
150K
200K
250K
SS
C-A
CD84+0
0-103
103
104
105
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_14_WT_LUNG_014.fcsCD11b+Gr1+6614
CD84+0.017
0-103
103
104
105
0
50K
100K
150K
200K
250K
SS
C-A
CD84+0
0-103
103
104
105
0
50K
100K
150K
200K
250KCD84+0
0-103
103
104
105
0
50K
100K
150K
200K
250K
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_20_WT_SPLN_020.fcsCD11b+Gr1+1460
CD84+27.4
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_21_4T1_SPLN_021.fcsCD11b+Gr1+32625
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_26_WT_MFP_026.fcsCD11b+Gr1+271
CD84+11.4
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_27_4T1_Tumor_027.fcsCD11b+Gr1+33723
CD84+2.80E-3
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_8_WT_BM_008.fcsCD11b+Gr1+35723
CD84+1.70E-3
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_9_4T1_BM_009.fcsCD11b+Gr1+58753
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_14_WT_LUNG_014.fcsCD11b+Gr1+6614
CD84+0.017
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_15_4T1_LUNG_015.fcsCD11b+Gr1+53062
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_20_WT_SPLN_020.fcsCD11b+Gr1+1460
CD84+27.4
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_21_4T1_SPLN_021.fcsCD11b+Gr1+32625
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_26_WT_MFP_026.fcsCD11b+Gr1+271
CD84+11.4
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_27_4T1_Tumor_027.fcsCD11b+Gr1+33723
CD84+2.80E-3
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_8_WT_BM_008.fcsCD11b+Gr1+35723
CD84+1.70E-3
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_9_4T1_BM_009.fcsCD11b+Gr1+58753
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_14_WT_LUNG_014.fcsCD11b+Gr1+6614
CD84+0.017
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_15_4T1_LUNG_015.fcsCD11b+Gr1+53062
CD84+0.013
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_BRCA_BLOOD_CD8 4_010.fcsCD11b+Gr-163324
CD84+4.25E-3
0-103
103
104
105
Comp-PE-A :: CD8 4
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_BRCA_LUNG_CD84_012.fcsCD11b+Gr-147078
CD84+40.7
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_BRCA_SPLN_sort MDSCs_019.fcsCD11b+Gr-113390
CD84+0.18
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_BRCA_tumor_CD84_018.fcsCD11b+Gr-19831
CD84+5.87E-3
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_WT_BLOOD_CD84_009.fcsCD11b+Gr-117033
CD84+0.017
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_WT_LUNG_CD84_011.fcsCD11b+Gr-111713
CD84+0.080
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_WT_SPLN_CD84_013.fcsCD11b+Gr-11257
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_WT_MFP_CD84_017.fcsCD11b+Gr-1867
CD84
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
CD11b+Gr1+1460
CD84+27.4
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_21_4T1_SPLN_021.fcsCD11b+Gr1+
SS
C-A
CD84+11.4
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_27_4T1_Tumor_027.fcsCD11b+Gr1+
CD84+2.80E-3
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_8_WT_BM_008.fcsCD11b+Gr1+35723
CD84+1.70E-3
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_9_4T1_BM_009.fcsCD11b+Gr1+
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_14_WT_LUNG_014.fcsCD11b+Gr1+6614
SS
C-A
CD84+27.4
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_21_4T1_SPLN_021.fcs
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_26_WT_MFP_026.fcsCD11b+Gr1+271
CD84+11.4
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_27_4T1_Tumor_027.fcs
CD84+2.80E-3
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_8_WT_BM_008.fcsCD11b+Gr1+35723
CD84+1.70E-3
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
Specimen_001_9_4T1_BM_009.fcs
CD84+0
0-103
103
104
105
Comp-PE-A :: CD84
0
50K
100K
150K
200K
250K
SS
C-A
CD11b+Gr1+6614
WT
4T1
0
10
20
30
*
Spleen
WT
4T1
0
10
20*
30
MFP vs TM
D
4T1
% o
f
CD
84 E
xpre
ssio
n
% o
f
CD
84
Expre
ssio
n
C
Fig. S4. CD84 is a generalizable MDSC marker in different breast cancer models.
(A-B) FMO and isotype controls were used to determine CD84 and JAML expression. (C-D)
Tissues from 4T1 breast cancer models and WT mice were collected and processed to single cell
suspensions. Cells were stained with antibodies for CD45+CD11b
+Gr1
+ and were gated based on
live and FMO controls then analyzed by flow cytometry. (C) FACS profiles showing CD84-
expression on the x-axis of cell samples from various organs from both control and 4T1 tumor-
bearing mice (D) CD11b+Gr1
+CD84
+ cells were profiled in different tissues from WT and 4T1
and showed significantly increased expansion in tumor bearing host in spleen, and tumor
compared to WT. Statistical analysis unpaired t-test (Mean ± SD of n =3) *P< 0.05 t-test.
Fig. S5. CD84 and JAML are up-regulated by in vitro–generated mouse and human
MDSCs.
(A-B) MDSCs were generated in vitro by treating bone marrow cells with GM-CSF, and probed
for CD84 and JAML expression by FACS compared to untreated normal bone marrow cells.
Statistical analysis unpaired t-test (Mean ± SEM of n =3) *P< 0.05. (D-E) Gating strategies and
isotype controls were used (CD45+CD11b
+CD14
+ or CD15
+) to determine CD84, HLA-DR, and
LOX-1 expression in human G- and M-MDSCs. (E) Bar charts show quantitative analysis of
FACS results of HLA-DR and LOX-1 unpaired t-test (Mean ± SEM of n =3). *P< 0.05. (F)
CD11b+Gr1
+JAML
hi cells from tumor-bearing mice show increased ROS formation compared to
CD11b+Gr1
+JAML
-/lo. ROS formation was measured by FACS using H2DCFDA. Statistical
analysis of ROS formation assay unpaired t-test (Mean ± SEM of n = 3) *P< 0.05.
Fig. S6. Characterization and validation of myeloid cell subsets for CD84 and JAML
expression.
(A) CD11b+Gr1
+CD84
hi cells and CD11b
+Gr1
+CD84
-/lo cells were sorted by FACS and subjected
to qPCR. Numerous of genes were confirmed to be significantly upregulated or downregulated in
CD11b+Gr1
+CD84
hi compared to CD11b
+Gr1
+CD84
-/lo. Statistical analysis unpaired t-test (Mean
± SEM of n =3) *P< 0.05. (B) Gating strategies for Ly6C/Ly6G myeloid subsets. CD84
expression was measured in Ly6C+ and Ly6G+ cells from spleen of control and tumor-bearing
mice (C) and in primary tumor compared to mammary fat pads from control mice (D). JAML
expression Ly6C+ and Ly6G+ cells from spleen of control and tumor-bearing mice (E) and in
primary tumor compared to mammary fat pads from control mice (F). (G-H) Histogram overlay
and quantitative bar charts of in vitro generation MDSCs subsets; CD11b+Ly6C
+CD84
hi cells
and CD11b+Ly6G
+CD84
hi suppressed T cell proliferation.
Fig. S7. Reconstruction of MDSC differentiation trajectory in neutrophils and monocytes.
(A) Seurat-based clustering of neutrophil subset is shown, which was used define a set of marker
genes for subsequent Monocle analysis. (B) Pseudotemporal analysis using Monocle labeled by
cell source (WT=blue; PyMT=red) and cell cycle score overlay in monocle plot. Membership
pie charts per monocle detected state (WT=blue; PyMT=red). (C) MDSC score for Top.200
genes is overlayed in dark (low) to light blue (high). (D-F) Monocyte-specific pseudotemporal
analysis using Monocle. (D) Cells were labeled by monocyte cluster (see Figure 1E) and
pseudotime score overlay from dark blue (early) to light blue (late) is included. (E) Cells were
labeled by cell source (WT=blue; PyMT=red). (F) MDSC score for Top.200 genes is overlayed
in monocyte-specific trajectory shown in dark (low) to light blue (high).
SUPPLEMENTARY TABLES
Table S1. Marker genes from combined Seurat analysis.
Table S2. Marker genes from Seurat analysis of monocytes only.
Table S3. Gene signature from G-MDSCs-versus-neutrophils comparison.
Table S4. Gene signature from M-MDSCs-versus-monocytes comparison.
Table S5. Combined MDSC signature gene list.
Table S6. GO terms (Biological Process 2018) MDSC gene signature.
Table S7. qPCR primer sequences.
Table S8. Marker genes from Seurat analysis of neutrophils only.
Table S9. Neutrophil-specific Monocle state marker genes.
Table S10. Monocyte-specific Monocle state marker genes.