hanna et al., in vivo targeting of skewed myeloid cells in cll...hanna et al., in vivo targeting of...

Hanna et al., In vivo targeting of skewed myeloid cells in CLL

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Supplementary methods:

Cell preparation

Peripheral blood (PB) was drawn via cardiac puncture with EDTA as anti-coagulant. Single cell

suspensions from spleens and LNs were prepared by grinding the tissue through 70 µm cell

strainers (BD Biosciences). Erythrocytes in spleen and PB were lysed using NH4Cl-based lysis

buffer (155 mM NH4Cl, 10 mM KHCO3, 0.1 mM EDTA, pH 7.2). Peritoneal cavity (PC) exudates

were harvested by injection and withdrawal of 5-7 ml of PBS in the peritoneal cavity (PC) and

traces of blood contaminations were removed by brief treatment with NH4Cl-based lysis buffer.

Bone marrow cells were prepared as previously described.(1) Cell counting was performed

using a Vi-CELL XR (Beckman Coulter).

Quantitative reverse transcriptase polymerase chain reaction

PC cells were harvested from 10 months or older WT (n=4) and TCL1 (n=6) mice and were

debulked from B cells using mouse CD19 microbeads (Miltenyi Biotec). Afterwards, PC

macrophages were FACS-sorted as CD45+ CD11b+ F4/80+ cells and RNA was extracted using the

RNeasy Micro Kit (Qiagen) according to the manufacturer’s protocol. cDNA synthesis was done

using QuantiTect Reverse Transcription Kit (Qiagen) containing a oligo-d(T)20/ random hexamer

primer mix as indicated in the manufacturer’s manual. Quantitative reverse transcriptase

polymerase chain reaction (qRT-PCR) was performed using SYBR Green ROX Mix (Abgene,

Epsome, UK) for amplification and quantification in an ABI Prism 7900HT system (life

technologies). Arginase 1 (Arg1) expression was detected using the following forward (5′-

TACAAGACAGGGCTCCTTTCAG-3′) and reverse (5′-TGAGTTCCGAAGCAAGCCAA-3′) primers. After

calculating the efficiency of amplification, expression of Arg1 was quantified relative to the

mean value of two housekeeping genes: Actb (forward; 5′-AGATGTGGATCAGCAAGCAG-3′,

reverse: 5′-GCGCAAGTTAGGTTTTGTCA-3′) and B2m (forward; 5′-TTCTGGTGCTTGTCTCACTGA-3′,

reverse: 5′-CAGTATGTTCGGCTTCCCATTC-3′). Triplicate qRT-PCR reactions were carried out for

each macrophage preparation.

Intracellular phospho-protein stainings

PC cells were harvested, resuspended in PBS+0.5% BSA and stimulated for 10 min at 37°C with

10 ng/ml murine IL-10 or IL-4 (Miltenyi Biotec, Germany). Cells were afterwards fixed with 2%

PFA, permeabilized using BD permeabilization buffer III and finally stained for 30 min using

isotype control, p-STAT3 (pY705) or p-STAT6 (pY641) Alexa Flour 647 antibodies (all from BD

Biosciences).

Cytokine quantification

Serum was harvested by centrifugation of clotted blood at 2,000 g and 4°C for 20 min. IL-10,

CCL2, CCL3, GM-CSF, CXCL10 and TNF-α were measured using MILLIPLEX Mouse


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Cytokine/Chemokine Magnetic Bead Panel (Merck Millipore, Germany) according to the

manufacturer’s protocol on a Bioplex-200 System (Bio-Rad). Flt3L, CXCL9, IL-1ra and CCL4 (R&D

Systems), CXCL16 (RayBiotech) and IL-1β (eBioscience) were measured by ELISA according to

manufacturers’ protocols.

Splenocytes/bone-marrow derived macrophage co-cultures

Bone-marrow derived macrophages (BMDMs) were prepared as previously described (2)

resulting in CD11b+ F4/80+ content of more than 98%. TCL1 splenocytes were cultured at a

density of 2x106 cells/ml either alone or with 1x106 BMDM in 6-well plates in RPMI medium

supplemented with 10% fetal calf serum, 4 mM L-glutamine, 100 U/mL penicillin, 100 μg/mL

streptomycin and 0.1% 2-mercaptoethanol. Cells were cultured at 37°C in a 5% CO2 humidified

incubator and 48 hours later viability of CD5+CD19+ cells was quantified using Annexin-V/7AAD

staining as previously described.(3) CCL2, CCL3 and CCL4 were quantified in the culture

supernatant using ProcartaPlex mouse Luminex beads (eBioscience) on a on a Bioplex-200

System (Bio-Rad).

In vivo EdU staining

Mice were injected i.p. with 0.1 mg/g EdU (5-ethynyl-2´-deoxyuridine, Life Technologies, UK).

After 20 hours, mice were sacrificed and EdU incorporation in spleen cDCs (CD11chi MHC-II+),

CLL cells (CD5+CD19+) and monocytes (Lin- CD11b+ CD11clow-int F4/80int) was analyzed after Click-

iT reaction according to the manufacturer’s instruction.

Gene expression profiling

Six weeks after AT, splenocytes from leukemic mice (n=5) were debulked from CLL cells using

mouse CD19 microbeads (Miltenyi Biotec) and the flow-through was used for FACS-sorting of

total spleen monocytes as Lin- CD11b+ F4/80int CD11clow-int MHC-IIlow cells on a BD FACSAria (BD

Biosciences). Control monocytes from WT mice were sorted accordingly and pooled from 4-5

mice per sample (n=5). The purity of sorted monocytes was ≥95%. RNA was extracted from

sorted cells using the RNeasy Micro Kit (Qiagen) according to the manufacturer’s protocol.

Gene expression was determined using the Illumina Mouse Sentrix-6 BeadChip arrays (Illumina,

Inc.). The quality of total RNA was checked by gel analysis using the total RNA Nano chip assay

on an Agilent 2100 Bioanalyzer (Agilent Technologies GmbH, Berlin, Germany). RNA

concentrations were determined using the NanoDrop spectrophotometer (NanoDrop

Technologies, Wilmington, DE).

The laboratory work was done in the Genomics and Proteomics Core Facility at the German

Cancer Research Center, Heidelberg, Germany (DKFZ). Biotin-labeled cRNA samples for

hybridization on Illumina Mouse Sentrix-6 BeadChip arrays (Illumina, Inc.) were prepared

according to Illumina's recommended sample labeling procedure based on the modified

Eberwine protocol (4). In brief, 100 ng total RNA was used for complementary DNA (cDNA)


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synthesis, followed by an amplification/labeling step (in vitro transcription) to synthesize biotin-

labeled cRNA according to the Illumina® Total Prep™ RNA Amplification Kit (Life Technologies).

Biotin-16-UTP was purchased from Roche Applied Science, Penzberg, Germany. The cRNA was

column purified according to TotalPrep RNA Amplification Kit, and eluted in 60 µl of water.

Quality of cRNA was controlled using the RNA Nano Chip Assay on an Agilent 2100 Bioanalyzer

and spectrophotometrically quantified (NanoDrop).

Hybridization was performed at 58°C, in GEX-HCB buffer (Illumina Inc.) at a concentration of

100 ng cRNA/µl, unsealed in a wet chamber for 20h. Spike-in controls for low, medium and

highly abundant RNAs were added, as well as mismatch control and biotinylation control

oligonucleotides. Microarrays were washed once in High Temp Wash buffer (Illumina Inc.) at

55°C and then twice in E1BC buffer (Illumina Inc.) at room temperature for 5 minutes (in

between washed with ethanol at room temperature). After blocking for 5 min in 4 ml of 1%

(wt/vol) Blocker Casein in phosphate buffered saline Hammarsten grade (Pierce Biotechnology,

Inc., Rockford, IL), array signals were developed by a 10-min incubation in 2 ml of 1 µg/ml Cy3-

streptavidin (Amersham Biosciences, Buckinghamshire, UK) solution and 1% blocking solution.

After a final wash in E1BC, the arrays were dried and scanned. Microarray scanning was done

using an iScan array scanner. Data extraction was done for all beads individually, and outliers

were removed when >2.5 MAD (median absolute deviation). All remaining data points were

used for the calculation of the mean average signal for a given probe, and standard deviation

for each probe was calculated.

A cluster analysis using Euclidean distances and average linkage was performed to search for

unwanted grouping effects. Intensity values were normexp-by-control background corrected

and quantile normalized with control probes (5). Probes that failed to reach a detection P-value

of 0.05 on at least two arrays were filtered as not expressed. Linear regression models

approach of Smyth (6) was used to derive moderated statistics to compare WT with TCL1

monocytes. To correct for multiple testing P-values were adjusted using the method of

Benjamini and Hochberg (7) to control the false discovery rate (FDR). The analysis was done

using R, version 3.0.2, together with R/Bioconductor packages limma, version 3.18.13, and

beadarray, version 2.12.0. Dataset is available on Gene Expression Omnibus (GEO) under the

accession number GSE66858

(http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=yzetomgervqpzyd&acc=GSE66858).

http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=yzetomgervqpzyd&acc=GSE66858


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Supplementary Table 1: Flow cytometry antibodies and respective clones

Antibody Clone Vendor

anti-mouse CD19 eBio1D3 eBioscience

anti-mouse CD3 145-2C11 eBioscience

anti-mouse CD11b M1/70 eBioscience

anti-mouse CD11c N418 eBioscience

anti-mouse F4/80 BM8 eBioscience

anti-mouse MHC-II I-A/I-E M5/114.15.2 eBioscience

anti-mouse CD31 390 eBioscience

anti-mouse CD54 YN1/1.7.4 eBioscience

anti-mouse PDL1 MIH5 eBioscience

anti-mouse PDL2 TY25 eBioscience

anti-mouse CD86 GL-1 eBioscience

anti-mouse CD4 RM4-5 eBioscience

anti-mouse CD8a 53-6.7 eBioscience

anti-mouse CD62L MEL-14 eBioscience

anti-mouse CD44 IM7 eBioscience

anti-mouse CD124 MIL4R-M1 BD Biosciences

anti-mouse CD5 53-7.3 BD Biosciences

anti-mouse Ly6G 1A8 BD Biosciences

anti-mouse Ly6C AL-21 BD Biosciences

anti-mouse CD43 S7 BD Biosciences

anti-mouse CD117 2B8 BD Biosciences

anti-mouse TER-119 TER-119 Biolegend

anti-mouse NK1.1 PK136 Biolegend

anti-mouse CD45 30F-11 Biolegend

anti-mouse CXCR3 CXCR3-173 Biolegend

anti-mouse CD206 Polyclonal Goat IgG R&D

anti-mouse Trem-1 174031 R&D

anti-mouse F4/80 Cl:A3-1 AbD Serotec


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Supplementary Table 2: Top 10 most differential pathways between TCL1 AT and WT splenic

monocytes as obtained by Ingenuity pathway analysis

Ingenuity

Canonical

Pathways

-log

(p-value) Molecules

1

Type I

Diabetes

Mellitus

Signaling

1,32E01

IRF1,TRAF2,SOCS3,HLA-DQA1,TNFRSF1A,SOCS4,HSPD1,

NFKBIE,NFKBIA,STAT1,TNF,CD3D,HLA-DRB5,NFKBIB,

MAPK11,CD3E,NFKB1,HLA-DOA,HLA-DQB1,CD3G,PRF1,

HLA-G,HLA-DOB,NFKB2,HLA-A,MAPK13,H2-Eb2,FAS,BID,

IKBKE

2

OX40

Signaling

Pathway

1,15E01

JUN,TRAF2,H2-T24,TNFRSF4,HLA-DQA1,NFKBIE,NFKBIA,H2-

Q8,H2-K2/H2-Q9,CD3D,HLA-DRB5,NFKBIB,H2-T10,H2-

T22,CD3E,NFKB1,HLA-DOA,HLA-DQB1,CD3G,HLA-G,HLA-

DOB,TRAF5,NFKB2,HLA-A,H2-Eb2

3 CD40 Signaling 1,01E01

JUN,TANK,TRAF2,NFKB1,PIK3R6,JAK3,NFKBIE,CD40,NFKBIA,

TRAF5,NFKB2,FOS,STAT3,PIK3CA,TNFAIP3,MAPK13,NFKBIB,

MAPK11,ICAM1,IKBKE

4

Role of NFAT

in Regulation

of the Immune

Response

9,62E00

JUN,PIK3R6,HLA-DQA1,GNG10,RCAN3,NFKBIE,NFKBIA,

FOS,GNAQ,PIK3CA,LCK,CD3D,HLA-DRB5,NFKBIB,NFAT5,

CD3E,NFKB1,HLA-DOA,GNB2L1,HLA-DQB1,RCAN1,CD3G,

RAF1,CD79B,HLA-DOB,FCGR2A,NFKB2,Calm1 (includes

others),FCGR2B,H2-Eb2,GNG2,GNA15,IKBKE

5 Dendritic Cell

Maturation 9,49E00

PIK3R6,HLA-DQA1,TNFRSF1A,NFKBIE,CD40,NFKBIA,

TREM2,IRF8,IL1RN,PIK3CA,CD1D,STAT1,RELB,TNF,HLA-

DRB5,NFKBIB,MAPK11,TLR2,LTB,NFKB1,HLA-DOA,HLA-

DQB1,STAT2,HLA-DOB,FCGR2A,NFKB2,HLA-A,FCGR2B,

MAPK13,IL10,H2-Eb2,ICAM1,IKBKE

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Activation of

IRF by

Cytosolic

Pattern

Recognition

Receptors

9,34E00

JUN,TANK,DHX58,NFKB1,STAT2,DDX58,IFIT2,NFKBIE,CD40,

NFKBIA,NFKB2,IRF7,STAT1,TNF,ISG15,NFKBIB,IL10,ZBP1,

IKBKE

7 IL-10 Signaling 9,23E00

JUN,NFKB1,SOCS3,LBP,NFKBIE,NFKBIA,FCGR2A,IL10RA,

NFKB2,FOS,CCR5,STAT3,FCGR2B,IL1RN,TNF,MAPK13,

NFKBIB,IL10,MAPK11,IKBKE


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8 TNFR2

Signaling 9,12E00

JUN,BIRC2,TANK,TRAF2,NFKB1,NFKBIE,NFKBIA,NFKB2,FOS,

TNFAIP3,TNF,NFKBIB,IKBKE

9 iNOS Signaling 8,95E00

IRF1,JUN,NFKB1,JAK3,LBP,NFKBIE,NFKBIA,IRAK3,NFKB2,

FOS,Calm1 (includes others),STAT1,MAPK13,NFKBIB,

MAPK11,IKBKE

10

Acute Phase

Response

Signaling

8,16E00

JUN,TRAF2,CFB,TF,SOCS3,TNFRSF1A,SOCS4,IL6R,LBP,

NFKBIE,NFKBIA,FOS,C4A/C4B,STAT3,FN1,HP,IL1RN,PIK3CA,

TNF,NFKBIB,MAPK11,VWF,Saa3,NFKB1,RAF1,NFKB2,SOD2,

CEBPB,MAPK13,IKBKE


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Supplementary figure 1

Supplementary figure 1: A) Representative dot plots showing infiltration of CD11bint Ly6Chi monocytes in PC of TCL1 mice. B) Representative dot plots for the expression of CD11c, Ly6G and F4/80 on CD11bint Ly6Chi cells in TCL1 PC (n=6). C) Total PC CD11b+ F4/80+ macrophages were analyzed for expression of CD206, CD124, CD86 and PD-L2. Representative histograms are shown. D) Normalized MFI of CD206, CD124, CD86 and PD-L2 on PC macrophages in TCL1 AT mice and matched WT controls in at least 5 mice per group. E) PC cells from TCL1 and WT mice were stimulated for 10 min with 10ng/ml IL-10 or IL-4 at 37°C. Levels of p-STAT3 and p-STAT6 in CD11b+ F4/80+ cells upon IL-10 or IL-4 stimulation, respectively, were assessed. One representative example is shown.


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Supplementary figure 2: Single cell suspensions of spleens were analyzed by flow cytometry.

Total DAPI-negative cells were used for the analysis. A) Gating strategy to define splenic

monocytes (Lin- (CD19- CD3- Ly6G- NK1.1-) CD11b+ F4/80int CD11clow-int MHC-IIlow SSCint), cDCs

(Lin- CD11chi MHC-II+) and macrophages (Lin- F4/80hi CD11blow). B) Representative histograms

showing CD62L and CD11c expression on TCL1 and WT spleen monocytes as determined by

flow cytometry. C) Representative histograms showing PECAM1 and ICAM1 expression on TCL1

and WT spleen monocytes as determined by flow cytometry.



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Supplementary figure 3:

A) Percentage of CD5+CD19+ cells and B) spleen weight following adoptive transfer of 1x107

splenocytes from leukemic TCL1 mice into young syngenic WTs (TCL1 AT). 3-4 mice were

sacrificed at the indicated time points.

4x107 splenocytes from leukemic TCL1 mice were adoptively transferred to young syngeneic

WTs (TCL1 AT) via tail vein injection and mice were sacrificed 6 weeks later. C) Splenic

monocytes were identified by flow cytometry as described in Suppl. Fig. 2 and their

percentages out of B220- cells in TCL1 AT (n=9) and matched WT (n=6) spleens are shown. Bar

plots represent percentage of inflammatory and patrolling subsets of total monocytes (D) and

total absolute counts of monocytes (E) in spleens of TCL1 AT (n=9) and matched WT (n=6) mice.

F) Proliferation of spleen cDCs in TCL1 AT mice as measured by the percentage of EdU+ cells in

3-4 mice per time point. G) Serum levels of GM-CSF and Flt3L in WT and TCL1 AT mice as

measured by multiplex bead arrays or ELISA in at least 5 mice per group. All bar plots show

means ± SEM. Statistical analysis was performed using unpaired t-test. **p<0.01, ***p<0.001.



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Supplementary figure 4: Splenocytes from TCL1 mice (n=4) were either cultured alone or co-

cultured with bone marrow-derived macrophages (BMDM), and cell-free cell culture

supernatant was collected 48 hours later. Levels of A) CCL2, B) CCL3 and C) CCL4 were

quantified using ProcartaPlex multiplex beads.

Three months old age- and sex-matched WT (n=8) and CCR2-/- (n=6) mice were intraperitoneally

transplanted with 2x107 CLL cells. Graphs show spleen weight (D) and absolute counts of

CD5+CD19+ cells in spleen (E) after 6 weeks of transplantation. Results are derived from two

independent transplantation experiments.


Supplementary figure 5: A) EdU incorporation in splenic monocytes (Lin- CD11b+ CD11clow-int

F4/80int) in PBS Lip. (n=8) and Clod. Lip. (n=9) treated mice. B) Relative subset composition of

spleen monocytes in PBS Lip. (n=9) and Clod. Lip. (n=14) mice at day 30 based on Ly6C and

CD43 expression. C) Normalized MFI of TREM-1 expression on total splenic monocytes of PBS

Lip. (n=9) and Clod. Lip. (n=10) mice. D) Percentage of CXCR3+ cells in CD4 and CD8 T cells in


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spleens of PBS Lip. (n=9) and Clod. Lip. (n=10) mice. All bar plots show means ± SEM. Statistical

analysis was performed using unpaired t-test. ns = not significant, *p<0.05, **p<0.01,

***p<0.001.

References:

1. McClanahan F, Hanna B, Miller S, Clear AJ, Lichter P, Gribben JG, et al. PD-L1 Checkpoint Blockade Prevents Immune Dysfunction and Leukemia Development in a Mouse Model of Chronic Lymphocytic Leukemia. Blood. 2015. 2. Ying W, Cheruku PS, Bazer FW, Safe SH, Zhou B. Investigation of macrophage polarization using bone marrow derived macrophages. Journal of visualized experiments : JoVE. 2013(76). 3. Schulz A, Toedt G, Zenz T, Stilgenbauer S, Lichter P, Seiffert M. Inflammatory cytokines and signaling pathways are associated with survival of primary chronic lymphocytic leukemia cells in vitro: a dominant role of CCL2. Haematologica. 2011;96(3):408-16. 4. Eberwine J, Yeh H, Miyashiro K, Cao Y, Nair S, Finnell R, et al. Analysis of gene expression in single live neurons. Proceedings of the National Academy of Sciences of the United States of America. 1992;89(7):3010-4. 5. Shi W, Oshlack A, Smyth GK. Optimizing the noise versus bias trade-off for Illumina whole genome expression BeadChips. Nucleic acids research. 2010;38(22):e204. 6. Smyth GK. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Statistical applications in genetics and molecular biology. 2004;3:Article3.

7. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach

to multiple testing. Journal of the Royal Statistical Society Series B, 1995; 57: 289-300.

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