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Blocking IFNRA1 inhibits multiple myeloma-driven Treg expansion and immunosuppression. Yawara Kawano*1, 2, Oksana Zavidij*1, Jihye Park1, Michele Moschetta1, Katsutoshi Kokubun1, Tarek H. Mouhieddine1, Salomon Manier1, Yuji Mishima1, Naoka Murakami3, Mark Bustoros1, Romanos Sklavenitis Pistofidis1, Mairead Reidy1, Yu J. Shen1, Mahshid Rahmat1, Pavlo Lukyanchykov3, Esilida Sula Karreci3, Shokichi Tsukamoto1, Jiantao Shi4, Satoshi Takagi1, Daisy Huynh1, Antonio Sacco1, 5, Yu-Tzu Tai1, Marta Chesi6, P. Leif Bergsagel6, Aldo M. Roccaro1, 5, Jamil Azzi3 and Irene M. Ghobrial1 1Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA 2Department of Hematology, Kumamoto University Hospital, Kumamoto, Japan 3Transplantation Research Center, Renal Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA 4Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA 5Clinical Research Development and Phase I Unit; CREA Laboratory, ASST Spedali Civili di Brescia, Brescia, BS, Italy 6Comprehensive Cancer Center, Mayo Clinic, Scottsdale, AZ, USA. * Equally contributed Corresponding Authors: 1-Irene M. Ghobrial, MD Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School 450 Brookline Ave Boston, MA, 02115 Phone: (617)-632-4198 Fax: (617)-632-4862 Email: irene_ghobrial@dfci.harvard.edu 2- Jamil Azzi MD Transplantation Research Center, Brigham and Women’s Hospital, Harvard Medical School 221 Longwood Ave, Boston, MA, 02115 Phone: (617)-525-7359 Fax: (617)-732-5254 Email: jazzi@rics.bwh.harvard.edu

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ABSTRACT

Despite significant advances in the treatment of multiple myeloma (MM), most patients

succumb to disease progression. One of the major immunosuppressive mechanisms that

is believed to play a role in myeloma progression, is the expansion of regulatory T-cells

(Tregs). In this study, we demonstrate that myeloma cells drive Treg expansion and

activation by secreting type-1 interferon (IFN). Blocking IFNAR1 (interferon alpha and

beta receptor 1) on Tregs significantly decreases both, myeloma-associated Treg

immunosuppressive function and myeloma progression. Using syngeneic transplantable

murine myeloma models and bone marrow (BM) aspirates of multiple myeloma patients,

we found that Tregs were expanded and activated in the BM microenvironment at early

stages of myeloma development. Selective depletion of Tregs led to a complete remission

and prolonged survival in mice injected with myeloma cells. Further analysis of the

interaction between myeloma cells and Tregs using gene sequencing and enrichment

analysis uncovered a feedback loop, wherein myeloma-cell-secreted type-1 IFN induced

proliferation and expansion of Tregs. By using IFNAR1-blocking antibody treatment and

IFNAR1 knockout Tregs, we demonstrated a significant decrease in myeloma-associated

Treg proliferation, which was associated with longer survival of myeloma-injected mice.

Our results thus suggest that blocking type-1 IFN signaling represents a potential strategy

to target immunosuppressive Treg function in MM.

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INTRODUCTION

Immunotherapy has shown promising results in clinical trials against both solid(1) and

hematological malignancies(2), such as Hodgkin lymphoma(3). Even though targeting

the immune microenvironment can lead to significant improvements in response and

patient survival, our understanding of its regulatory mechanisms is incomplete. The role

of immunosurveillance in controlling cancer growth thus remains under active

investigation in many cancer types, including Multiple Myeloma (MM).

Multiple myeloma is characterized by clonal expansion of malignant plasma cells in the

bone marrow (BM). It is preceded by two precursor states, Monoclonal Gammopathy of

Undetermined Significance (MGUS) and Smoldering MM (SMM)(4), which represent

stages of tumor progression with no evidence of end-organ damage. Unfortunately, MM

remains an incurable disease despite significant advances in treatment. Therefore,

immunotherapies may offer a promising strategy that could lead to significant responses,

especially in patients with poor-risk cytogenetics who do not benefit from standard of

care options or in patients at early stages of disease, like Smoldering MM. On the other

hand, MM might not be as immunogenic as other cancers, such as melanoma or lung

cancer(5, 6). Therefore, a better understanding of the immune microenvironment within

the bone marrow niche is critical for the development of novel immune therapies for not

just MM, but other cancers that infiltrate the bone marrow.

Recent success of immune checkpoint inhibitors indicates that anti-tumor T-cell responses

are functionally inhibited by poorly understood immunosuppressive mechanisms(7). One

of the major immunosuppressive mechanisms in tumor progression is the expansion of

regulatory immune cells, particularly regulatory T-cells (Tregs). Tregs are a subset of

CD4+ T lymphocytes characterized by the expression of Factor Forkhead Box P3

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(FOXP3)(8). They play an important role in the maintenance of self-tolerance and the

control of immune homeostasis; however, they can be co-opted by cancer cells to aid in

immune suppression and evasion. Tregs can inhibit tumor-specific CD8+ and CD4+ T-cell

effector functions through cell-cell contact and/or the production of anti-inflammatory

cytokines. Additionally, they can induce effector T-cell exhaustion, which is frequently

seen in the tumor microenvironment(9).

In MM, the role of Tregs in regulating tumor progression remains under active

investigation(10, 11). Despite controversy in previous reports regarding the number and

function of Tregs in the peripheral blood of MM patients(10-13), there is growing

evidence supporting a role for Tregs in MM progression(13, 14). Recent data have shown

a link between Tregs and sustenance of BM plasma cells, indicating that Treg activity

directly affects homeostasis of the plasma cell population(15), while in vitro experiments

have demonstrated that myeloma cells are capable of inducing Treg activation,

predominantly in a contact-dependent manner(16, 17). Moreover, CD38-expressing Tregs

have been suggested as suppressive modulators of anti-tumor immune responses in MM,

while CD38-targeting has been shown to inhibit immunosuppression in ex vivo co-

cultures(17). In this context, understanding Tregs homeostasis and specifically, how to

overcome their suppressive function is critical in developing effective immune therapies

for myeloma and other hematological malignancies infiltrating the bone marrow.

In the present study, we demonstrate that myeloma cells are responsible for Tregs

expansion and activation via secretion of type-1 interferon (IFN). Using the Vk*MYC

transplantable mouse model, we show that Tregs are critical for MM disease progression

and that depletion of Tregs leads to a complete remission. To further validate our findings,

we show that blocking IFNAR1 (interferon alpha and beta receptor 1) signaling

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significantly decreases myeloma-associated Treg proliferation and activation, which is

associated with prolonged survival of myeloma-injected mice. Our results, thus, suggest

that blocking type-1 IFN signaling represents a potential immune-therapeutic strategy in

MM.

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RESULTS

Increased number of Tregs at early stages of disease progression in the BM of a

transgenic MM transplantable mouse model and BM aspirates of MM patients.

To examine the T-cell immune microenvironment in MM during different stages of

disease progression, we injected C57BL/6 mice with transplantable Vk*MYC cells

(Vk12598 cells)(18). The Vk*MYC transgenic mouse uniquely models the natural history

of human MM, with progression of disease from early pre-malignant stages to overt

MM(19). To specifically investigate the changes that occur overtime in the immune

microenvironment within the bone marrow, where the tumor actually grows, vs.

peripheral blood (PB), we used Mass Cytometry, Cytometry by Time of Flight

(CyTOF)(20) to analyze the immune cell profile of Vk*MYC-injected mice, both in the

BM and the PB, at two time points during disease progression compared to control mice

(n=3 per group, per time point, Figure 1A). The gating strategy for Tregs is described in

Supplementary Figures 1A and 1B. CyTOF data were validated by flow cytometry

analyses in independent experimental settings (n=5 per group).

We observed a significant increase in the proportion of Tregs (CD4+FOXP3+) in the PB

and BM of Vk*MYC-injected mice, compared to control mice. Interestingly, the

differences were observed earlier in the BM starting from the early time point (Figures

1B-C and Supplementary Figure 1B-F), but only became detectable in the PB at later time

point (Figure 1D), indicating that Treg regulation occurs early within the tumor

microenvironment, before these changes are reflected in the peripheral blood.

We then analyzed the effector T-cells (Teffs: CD4+CD44++CD62Llow and

CD8+CD44++CD62Llow)(21) (22)/Tregs ratio to assess the suppression of T-cell immunity

in the BM microenvironment. We observed a decrease in the Teffs/Tregs ratio in the BM

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microenvironment and PB at the late time point (Figure 1E, Supplementary Figure 2A),

suggesting the suppression of T-cell immunity at a more advanced stage of disease.

Previous reports have shown an increased frequency of functional FOXP3-expressing T-

cells in the PB and BM of myeloma patients(10, 23). Here, we sought to define whether

the increase in Tregs occurs in the bone marrow already at the precursor stage of multiple

myeloma, in smoldering multiple myeloma (SMM). For this, we analyzed the distribution

of Tregs in BM aspirates of SMM patients (n=17), and compared it to that of healthy BM

donors (n=11). CyTOF analyses of the CD138-negative BM fractions demonstrated a

significant increase of CD3+CD4+ T-cells (data not shown), activated

CD4+CD25+FOXP3+ T-cells as well as CD4+CD25+FOXP3+CD127-/low Tregs within

the CD45+CD3+ compartment in SMM BM compared to healthy controls (Figure 1F,

Supplementary Figure 2B). This data from the human samples is in agreement with the

murine transplantation model.

Immune checkpoint receptors are upregulated in Tregs present within the bone marrow

microenvironment of myeloma-injected mice.

Immune checkpoint receptors, such as PD1 (Programmed cell death 1), LAG3

(Lymphocyte activation gene 3) and TIM3 (T cell immunoglobulin mucin 3), inhibit Teffs

function in the presence of cognate ligands(24). Conversely, when these receptors are

expressed on Tregs, the function and/or proliferation of Tregs are enhanced(7). We

measured number of positive cells, as well as the mean expression of immune checkpoint

receptors (PD1, LAG3 and TIM3) on Tregs in the BM and PB of Vk*MYC-injected and

control mice by CyTOF. BM Tregs of myeloma-bearing mice showed significantly higher

expression of immune checkpoint receptors, compared to control BM Tregs (Figures 2A-

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C). In contrast, PB Tregs of Vk*MYC-injected mice did not show increased expression

of these receptors, compared to control PB Tregs (Figure 2D, Supplementary Figure 3A-

C), suggesting that tumor site affects Treg phenotype and enhances its suppressive

function. SPADE analysis, as depicted in Figure 2B, revealed a significant increase in

LAG3 expression on BM Tregs expressing PD1 and/or TIM3; LAG3 has been shown to

be a marker of Tregs expanding at the tumor site(25). Along with the increase in

proportion of Treg expressing immune checkpoint receptors in BM of myeloma-injected

mice, there is an elevated number of Tregs co-expressing PD1, LAG3 and TIM3 receptors

as compared to healthy mice (Supplementary Figure 3D). Interestingly, we also observed

significantly higher levels of expression of PD1, LAG3 and TIM3 on Vk*MYC-injected

BM CD4+ and CD8+ Teffs (CD44++CD62Llow), which represent markers of T-cell

exhaustion and suppressed effector functions (Figure 2E, Supplementary Figure 3E-G).

These results were further validated in a second mouse model of MM, C57BL/KalwRij,

that was injected with 5TGM1 murine myeloma cells. Similar to the results of the

Vk*MYC-injected mice, we observed a significant increase in the frequency and

activation of BM Tregs in the bone marrow microenvironment of 5TGM1-injected

C57BL/KalwRij mice, compared to control group (Supplementary Figure 4A-D).

In line with our murine data, we observed a significantly higher proportion of

CD4+CD25+FOXP3+ Tregs expressing immune checkpoint molecules in BM aspirates of

SMM patients (n=17) compared to those in healthy BM (n=11) (Figure 2F). Interestingly,

SMM patients have significantly higher numbers of C-C Chemokine Receptor type 7

(CCR7)-expressing cells in their CD4+CD25+FOXP3+ Treg cell compartment, which

indicates an upregulation of the migratory phenotype of FOXP3-expressing cells (Figure

2F). Examination of immune molecules co-expression on Treg cells revealed that mainly

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proportion of cells expressing PD1, TIM3 and CTLA4 were significantly increased in

SMM group (Supplementary Figure 4E). In addition, analysis of the mean expression fold

change of each immune checkpoint molecule indicates elevated levels of immune

checkpoint receptors on Treg cells in individual SMM patients as compared to healthy

donors (Figure 2G). Further analyses of the CyTOF profiles of immune checkpoint

molecules present on CD4+Teff and CD8+Teff cells in the BM of SMM patients,

compared to healthy BM, revealed individual patients with elevated expression of TIM3,

PD1, CTLA-4 and CCR7 as depicted in the heatmap data in Figure 2H. In 35.3% of the

SMM patients we observed at least a twofold increase in the levels of CD27 and CCR7

on CD4+Teff and TIGIT on CD8+Teff as compared to the expression of these molecules

in the BM of healthy donors. Together, these results indicate an upregulated expression

of immune checkpoint inhibitors on Tregs within the myeloma bone marrow

microenvironment as early as the smoldering myeloma stage.

Tregs contribute to Vk*MYC progression.

A CD38-expressing subset of Tregs from MM patients has been shown to exhibit

immunosuppressive activity in ex vivo co-cultures(17). In order to determine the

significance of Tregs in myeloma progression in vivo, we used a transgenic inducible

knock-out mouse model: “depletion of regulatory T cell” (DEREG) mice, expressing a

diphtheria toxin (DT) receptor-enhanced green fluorescent protein (GFP) fusion protein

under the control of the FOXP3 gene locus, that allows the selective depletion of FOXP3+

Tregs by DT injection(26). Survival of DEREG mice injected with Vk*MYC cells,

followed by 3 injections of DT, was compared to that of Vk*MYC-injected DEREG mice

injected with PBS and that of Vk*MYC-injected wild-type littermates injected with DT

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(Figure 3A). Effective depletion of BM Tregs in Vk*MYC-injected mice was observed

upon DT injection into DEREG mice (Figure 3B). A significant tumor reduction was

observed in the DT-treated DEREG mice, compared to control groups, as shown by the

number of CD138+B220- Vk*MYC cells obtained from their bone marrows

(Supplementary Figure 5A). More importantly, there was a significant difference in

survival, with the control group surviving for a median of 30 days, while the DT-treated

DEREG mice showed no evidence of myeloma progression for up to 60 days of

experimental setup (p<0.0001) (Figure 3C). Flow cytometry analysis of BM cells on day

3 after last DT treatment in Vk*MYC-injected mice demonstrates a significant decrease

in CD138-expressing plasma cells and an increased Teff/Treg ratio compared to control

group (Supplementary Figure 5B). Interestingly, CyTOF analysis of the cellular content

of bone marrow cells showed a significantly increased proportion of CD19-expressing B

cells and F4/80+ macrophages in mice with Treg depletion compared to control mice

(Supplementary Figure 5C).

To further confirm the critical importance of Tregs in regulating tumor progression in

MM, we performed a Treg transfer experiment, in an effort to demonstrate that the

adoptive transfer of Tregs will lead to rapid tumor progression in vivo. We injected sorted

C57BL/6 CD3+CD25- non-Tregs, with or without CD4+CD25+ Tregs, into RAG2 knock

out (ko) immune-deficient mice, which lack a mature T- and B-cell compartment,

followed by Vk*MYC transplantation, and measured their survival (Figure 3D). In the

short time period of about 30 days of survival of these mice, we did not observe weight

loss or signs of colitis in these mice. We did not observe diarrhea or GI symptoms in the

mice. Mice injected with Tregs and CD3+ non-Tregs had significantly shorter survival

compared to mice injected with CD3+ non-Tregs only (Figure 3E), indicating that the

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Treg compartment suppresses anti-myeloma T-cell immunity. Analysis of the BM of

moribund mice showed significant increase of Tregs in the group injected with

CD4+CD25+ Tregs (Figure 3F, Supplementary Figure 5D), confirming that transferred

Tregs proliferated in the recipient’s BM tumor microenvironment.

In parallel, to further validate our results, we specifically depleted Tregs in Vk*MYC-

injected mice using a CD25 antibody (250 Pg of anti-murine CD25 mAbs on day -4 and

day 10 post Vk*MYC cell injection, n=6); isotype antibody treatment was used in the

control group (n=6) as described in previous studies (27). Compared to isotype-treated

mice, the CD25-treated group demonstrated significantly longer survival (Supplementary

Figure 6A, 6B), further confirming the critical role of Tregs in myeloma progression.

Together, our data provide direct in vivo evidence of Tregs supporting multiple myeloma

disease progression.

Human and murine myeloma cells induce and expand Tregs in a contact-dependent

and independent manner

To elucidate mechanisms involved in Treg induction and expansion in MM, we performed

Treg induction and expansion assays by co-culturing Vk*MYC cells with CD4+CD25-

non-Tregs or CD4+CD25+ Tregs respectively, using direct co-culture assays. Both assays

showed significant increase in CD4+CD25+FOXP3+ Tregs when co-cultured with

Vk*MYC cells, compared to B-cells or “No cells” controls (Figure 4A, 4B). Similar

results were obtained when a transwell co-culture assay separating Vk*MYC cells from

T-cells was performed, indicating that it is a soluble factor produced from Vk*MYC cells

that leads to the induction and expansion of Tregs (Figure 4A, B and Supplementary

Figure 7A).

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We further explored a contact-independent Treg induction mechanism in human samples.

For this, we co-cultured human CD4+CD25- PB cells with MM1S and OPM2 myeloma

cell lines without cell-cell interactions. Consistent with our murine data, we observed a

significant induction of CD4+CD25+FOXP3+ cells by co-culture of CD4+CD25- PB cells

with myeloma cells, compared to CD19-expressing B-cells or “No cells” controls (Figure

4C).

Together, these data show that murine and human myeloma cells induce and promote

expansion of Tregs in a cell-cell contact-dependent and independent manner, leading to

the increased presence of Tregs in the tumor microenvironment.

Myeloma cells regulate Tregs in the BM microenvironment by secretion of type 1

interferons.

To further characterize mechanisms that lead to the activation of myeloma-associated

Tregs, we performed RNA sequencing of flow-sorted BM GFP-expressing Tregs from

Vk*MYC-injected DEREG mice and control DEREG mice. We observed a significant

difference in mRNA expression between Tregs derived from the bone marrow

microenvironment of myeloma-injected mice and those derived from control mice, as

depicted in the heat map in Figure 5A. The top genes that were significantly up- or

downregulated in Tregs from Vk*MYC-injected mice, compared to control, are shown in

Supplementary Table 1. Consistent with our CyTOF data at the protein level, expression

of checkpoint-related molecules, including PDCD1 (PD1), LAG3 and HAVCR2 (TIM3),

was significantly upregulated in Vk*MYC-associated Tregs, compared to control Tregs

(Figure 5B). Additionally, other checkpoint-related molecules, such as TNFRSF4

(OX40)(28) and TNFRSF18 (GITR)(29) were also found to be highly expressed in

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Vk*MYC-associated Tregs (Figure 5B).

Tregs use multiple effector molecules, such as IL-10, TGF-b, EBI3, FGL2, GZMB and

PRF1, to suppress the immune effector cells(30) (31) (32). In our study, Vk*MYC-

associated Tregs showed a significantly higher expression of EBI3, FGL2 and GZMB

(Figure 5C), indicating that these molecules may play a role in the suppressive activity of

myeloma-associated Tregs.

Chemokine receptors play a significant role in Treg migration and homing. We analyzed

the expression of CXCR3, CCR6 and CCR7, which are all well-known mediators of Treg

migration to inflammatory sites(33-37). CXCR3 was found to be significantly

overexpressed in Vk*MYC-associated Tregs, compared to control (Figure 5D),

suggesting a significant role for CXCR3 in Treg migration to the myeloma

microenvironment. Interestingly though, CCR7 levels were significantly downregulated

in Vk*MYC-associated Tregs, compared to control, indicating differences in the

regulation of Treg migration in the tumor setting.

To determine pathways that regulate Treg activation and expansion in the MM tumor

microenvironment, we performed Gene set enrichment analysis (GSEA) for the genes

that were found to be significantly upregulated in Vk*MYC-associated Tregs, compared

to control. Interestingly, GSEA analysis showed enrichment of type-1 interferon (IFN) -

related genes in Vk*MYC-associated Tregs, compared to control (Figure 6A). According

to the GSEA analyses, several differentially regulated proteins contributed to the

enrichment score for Interferon alpha beta signaling pathway. These include the type-1

interferon-induced proteins playing a critical role in cellular innate antiviral responses,

such as Interferon-induced 15 kDa protein (ISG-15), interferon-induced Mx1 and Mx2,

IFIT1 and IFIT3, OAS2, OAS3. Additionally, key transcriptional regulators of type I

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interferon (IFN)-dependent immune responses, such as Interferon Regulatory Factors 7

and 9 (IRF7, IRF9) contributed to the enrichment profile. Signal transducer and activator

of transcription STAT1 and STAT2 were enriched in the gene list as well. These results

indicate that type-1 IFN pathway is activated in the BM Tregs of Vk*MYC-injected mice

and may constitute a novel pathway of Treg regulation in the MM immune

microenvironment.

We then sought to examine whether myeloma cells secrete type-1 IFNs, potentially

leading to Treg activation. We observed a significant increase of IFN-beta in the

supernatants of Vk*MYC cells in culture, compared to the supernatant of control B-cells

obtained from C57BL/6 mice (Figure 6B), while IFN-alpha was below detection level in

both cell types (data not shown). Collectively, these results suggest that myeloma-cell-

secreted type-1 INF could be a mediator of Treg activation in MM.

INFA1 expression is associated with poor outcome in MM patients

We then investigated whether CD138-expressing plasma cells from MM patients showed

significant changes in pathways or the expression levels of genes related to type-1 IFN

signaling. GSEA analysis of two gene expression datasets generated from CD138-

enriched plasma cells, one from 73 newly diagnosed MM patients and one from 147 cases

of MGUS, SMM, MM and relapsed myeloma (GSE6477), showed significant enrichment

for type-1 IFN signaling compared to 15 healthy donors (Figure 6C). Notably,

upregulated expression of IFNA2, one of the INF�alpha homologous genes(38), and IFN

regulatory transcription factor 3 (IRF3)(39) contributed to core enrichment score in this

dataset. Further analysis showed significantly increased levels of IRF3 and other

members of the IFN regulatory factors, including IRF4, IRF5 and IRF9 (Figure 6D).

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Similarly, there was an increase in the expression of IFNA1 and IFNA2 isoforms, and

another key component of the IFN induction pathway, MAVS protein(40, 41), in MM

samples, compared to healthy controls. Interestingly, lower expression of TLR2 and

TLR8 receptors was also observed in MM patients, pointing to concurrent deregulation

of Toll-like receptor signaling in malignant plasma cells (Figure 6D).

We next sought to determine the prognostic role of genes regulating type-1 IFN in MM,

and therefore analyzed the survival probability of these genes in a large dataset of newly

diagnosed MM patients (n=542, GSE2658). Median modus was used for cutoff

determination, P values were corrected for multiple testing and R2 visualization platform

(http://r2.amc.nl) was used for calculation. We found a significant decrease in the overall

survival of patients with high levels of IFNA1 (Figure 6E), supporting the results of our

murine experiments and indicating that type-1 interferon is indeed an essential player in

MM progression. Interestingly, lower levels of endosomal Toll-like receptor TLR8(42),

were also associated with poor outcome in MM patients (Figure 6F), further suggesting a

high impact for deregulated type-1 IFN pathways on MM progression.

Blocking interferon alpha and beta receptor 1 (IFNAR1) suppresses inhibitory

function of Tregs and inhibits myeloma progression

In order to validate the effect of myeloma-cell-secreted type-1 IFN on Treg function, we

co-cultured Vk*MYC cells with sorted Tregs and treated them with either IFNAR1

(interferon alpha and beta receptor 1) antibody, which blocks ligand-induced intracellular

signaling and induction of type I IFN-induced biologic responses(43), or isotype control.

Treg proliferation, analyzed by Ki-67 expression, was significantly decreased in the

IFNAR1-treated group, compared to control. This led to a decrease in Treg expansion in

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IFNAR1-treated cells, compared to control (Figure 7A-D). This study was also performed

with 5TGM1 MM cells, which were capable of inducing expansion of C57BL/KaLwRij

Tregs in a transwell co-culture assay (Supplementary Figure 7B). Once more, IFNAR1-

blocking antibody treatment led to decreased Treg proliferation and expansion, compared

to treatment with isotype control (Supplementary Figure 7C). Collectively, our data

demonstrate that myeloma-cell-secreted Type-1 IFN induces proliferation and expansion

of Tregs when present in the myeloma microenvironment.

Finally, we sought to validate in vivo the significance of IFNAR1 as a critical regulator

of Treg function and expansion in MM. For this, we performed a T-cell transfer

experiment using IFNAR1 ko Tregs; we injected sorted wild-type (C57BL/6) CD3+CD25-

non-Tregs, wild-type Tregs or IFNAR1 ko Tregs into RAG2 ko mice, followed by

Vk*MYC transplantation, and then analyzed tumor growth and survival (Figure 7E).

Mice injected with IFNAR1 ko Tregs lacked the effect of wild-type Tregs in enhancing

progression of MM, with survival rates similar to those of mice that had been injected

with non-Tregs (CD3+ only) (Figure 7F). Namely, Tregs lacking IFNAR1 failed to

suppress MM-directed T-cell immunity, and that failure was further reflected in their

reduced proliferation and expansion in vivo. While an increase in the number of Tregs

was observed in mice that received wild-type Tregs, in accordance to the results of our

previous experiments, the expansion was abrogated in the IFNAR1 ko mice, confirming

that MM cells induce Treg expansion through type-1 IFN signaling (Figure 7G). As

expected, the BM Tregs of mice transferred with IFNAR1 ko Tregs had lower expression

of IFNAR1, compared to mice transferred with wild-type Tregs (Figure 7H). Moreover,

when comparing BM Tregs between mice injected with wild-type Tregs and those

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injected with IFNAR1 ko Tregs, we observed a significant decrease in the expression of

LAG3 in the latter group (Figure 7I), indicating that type-1 IFN signaling is also partly

responsible for checkpoint molecule expression on Tregs in the tumor microenvironment.

Thus, our data demonstrate that blocking IFNAR1 reduces myeloma-mediated Treg

immunosuppression, leading to better survival rates of myeloma-injected animals.

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DISCUSSION

Increased presence of Tregs in the tumor microenvironment of cancer patients has been

associated with both improved(44, 45) and poor prognosis(46, 47). A few studies

described an increase in the number of Tregs in the peripheral blood of patients with

myeloma, compared to healthy donors(10, 12, 13, 48), indicating a potential role for Tregs

in multiple myeloma in particular. However, the mechanisms of Treg expansion in

myeloma, as well as the role of Tregs in myeloma progression, have not been fully

elucidated(49). Understanding those mechanisms is critical, as it could be key in

developing new immune therapies in MM. In the present study, we identified a feedback

loop between myeloma cells and Tregs, wherein type-1 IFN secreted from myeloma cells

induces immunosuppression caused by Tregs, thus promoting myeloma progression.

Interrupting this loop by blocking IFNAR1 signaling relieves immunosuppression and

prevents/delays tumor progression.

First, we confirmed that Tregs increase in number and expand in the BM with disease

progression, a phenomenon that was detectable in the BM at an earlier time point,

compared to the PB, indicating that myeloma-promoting Treg deregulation first occurs in

the context of the tumor microenvironment. In addition, we showed that myeloma-

associated BM Tregs highly express immune checkpoint receptor molecules, like PD1,

LAG3 and TIM3. Again, in contrast to Teffs, where these molecules are markers of

exhaustion, in Tregs, they signify enhanced immunosuppressive function(7). Thus, our

data indicate that Tregs in the myeloma microenvironment are activated not only in terms

of quantity, but also quality.

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Next, we sought to determine the importance of Tregs in myeloma progression. Our in

vivo Treg depletion and Treg transfer experiments demonstrated a strong impact of Tregs

on the progression of multiple myeloma, as continuous Treg depletion in vivo led to tumor

remission and prolonged survival of Vk*MYC-injected mice. These results are consistent

with other tumor models where enhancement of anti-tumor immune responses occurs

with depletion of Tregs by targeting highly expressed surface receptors(17, 50-52).

Interestingly, we found that the cellular content of the bone marrow after Treg depletion

reflects an environment hostile for tumor growth with a significant increase in Teff/Treg

ratio as well as B cells and macrophages, indicating that these cells could be critical for

the reconstitution of the immune microenvironment and the prevention of tumor

progression in MM.

To further explore mechanisms by which myeloma-associated Tregs are activated, we

then conducted RNA sequencing, comparing BM Tregs of Vk*MYC-injected mice to BM

Tregs of control mice. In addition to checkpoint-related genes and Treg effector genes

being significantly upregulated, type-1 IFN pathway was found to be highly enriched in

the gene signature of myeloma-associated Tregs. Validating these results, expression data

from MM patients also demonstrated upregulation of well-known genes regulating type-

1 IFN induction pathways, such as IRF3, IRF4, IRF5, IRF9 and MAVS protein in

malignant plasma cells; these genes were associated with worse prognosis in the survival

of MM patients underscoring the impact of IFNA1 on survival outcome.

Type-I IFNs are known players in a variety of diseases, such as viral infection,

inflammatory bowel disease, systemic lupus erythematosus and type-I diabetes(53), but

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their role in myeloma remains poorly characterized. Recently, it was shown that type-1

IFN signaling is essential for maintenance of FOXP3 expression, as well as Treg

suppressive function under inflammatory conditions(54), while IFN-alpha/beta receptor

signaling was shown to promote Treg development and function under stress

conditions(55). In the cancer setting, IFNAR-mediated signaling was found to be

necessary for tumor-infiltrating Treg activation and production of IL10, as well as

suppression of T-helper 17 cells, in the tumor microenvironment of colon

adenocarcinoma(56). In our system, we demonstrated that type I IFN is critical for Tregs

function using in vitro and in vivo models.

Based on this, we thus hypothesized that suppression of the type-1 IFN pathway could

inhibit myeloma-mediated Treg expansion and hinder tumor progression. Indeed,

IFNAR1 antibody led to the suppression of the proliferation of myeloma-associated Tregs

in an in vitro co-culture assay, as well as extending the survival of myeloma-injected mice

in a T-cell transfer experiment with IFNAR1 ko Tregs.

In conclusion, we have unprecedented findings demonstrating that Treg function and

homeostasis is regulated by type-1 IFN secreted from myeloma cells in the BM

microenvironment, effectively evoking a feedback loop between Tregs and myeloma cells

that promotes disease progression and leads to inferior outcome. Prolonged survival in

MM mouse models was achieved by Tregs depletion and by blocking IFNAR1 signaling

and suppressing myeloma-mediated Treg induction and proliferation, indicating that

type-1 IFN signaling is a novel therapeutic target for regulating Treg-mediated

immunosuppression in multiple myeloma.

21

METHODS

Cells

The 5TGM1 cell line was a kind gift of Dr. David G. Roodman (Indiana University,

Indianapolis, Indiana, USA). The Vk*MYC derived transplantable Vk12598 cell line(18)

was kindly provided by Dr Marta Chesi and Dr P. Leif Bergsagel (Mayo Clinic, Scottsdale,

AZ) and was maintained and expanded by in vivo re-transplantation in Rag2 ko mice

similar to previous reports(5, 57). For in vitro experiments, these cell lines were cultured

in RPMI-1640 containing 10% fetal bovine serum/FBS (Sigma Chemical, St Louis, MO),

2mM L-glutamine, 100 U/mL penicillin, and 100μg/mL streptomycin (GIBCO, Grand

Island, NY). Human MM1S cells were purchased from ATCC. Human OPM2 myeloma

cell line was purchased from DMSZ.

Primary peripheral blood (PB) cells or bone marrow samples from patient/healthy donor

aspirates were collected from the Dana-Farber Cancer Institute. CD 138-negative bone

marrow cell fraction was isolated using MACS technology (Miltenyi Biotec).

Mice

C57BL/6, DEREG, Rag2 ko and IFNAR1 ko mice, all under C57BL/6 background, were

purchased from Jackson Laboratories (Bar Harbor, Maine). C57BL/KalwRij mice were

purchased from Harlan Laboratories (Horst, Netherlands).

2×106 Vk12598 cells were injected intravenously (IV) into each mouse for T-cell analysis

or survival studies. 3×106 5TGM1 cells were injected IV into C57BL/KalwRij mice for

T-cell analysis. BM cells and peripheral blood from mice were harvested for CyTOF

analysis by BM aspiration from the femur and by sub-mandibular bleeding, respectively.

For other experiments, BM cells were obtained through flushing of femurs with 1XPBS,

22

as previously described(58).

Treg depletion study

Treg depletion was performed during Vk*MYC progression on DEREG mice by injecting

intraperitoneally 10 ng/g/mouse of DT on day 5, 12 and 19 post Vk*MYC injection. For

control groups, same amount of DT or PBS were injected into C57BL/6 or DEREG mice,

respectively. Depletion of Tregs using CD25 antibody was performed as described in

previous reports (250 Pg of anti-murine CD25 mAbs)(27). Isotype antibody and anti-

CD25 antibody treatment was performed on day -4 and day 10 post tumor injection.

T-cell transfer study

Tregs were obtained from spleens of C57BL/6 or IFNAR1 ko mice by flow-sorting CD4+

CD25+ cells by FACSAria II flow cytometry system (BD Biosciences, San Jose, CA).

Similarly, CD3+ non-Tregs were obtained from C57BL/6 splenocytes by sorting CD3+

CD25– cells. 1×106 Tregs and 3×106 non-Tregs were injected IV into Rag2 ko mice,

followed by Vk12598 cell injection 5 days afterwards.

Analysis of cells by CyTOF

Sample staining and data analysis were performed as reported previously(57). Briefly,

cells were first stained with MaxPar Intercalator-Rh (Fluidgm Sciences Inc., Sunnyvale,

CA) for determination of viable cells. After blocking with mouse Fc Receptor Blocking

Reagent (Miltenyi Biotec Inc., San Diego, CA), cell surface marker antibodies were

added and stained. Following staining, cells were washed with MaxPar Cell staining

23

buffer (Fluidgm Sciences Inc.) and fixed/permeabilized with Fix/Perm buffer (PBS with

1.6% Paraformaldehyde and 0.3% Saponin). Cells were then washed with Cell staining

buffer containing 0.3% saponin, following Intra-cellular antibody staining. For mass

cytometry analysis, cells were stained with MaxPar Ir DNA intercalator (Fluidgm

Sciences Inc.) overnight at 4°C. Cells were then washed with Cell staining buffer and

then finally with MaxPar water (Fluidgm Sciences Inc.) alone. Cells were acquired on the

CyTOF2 mass cytometer (Fluidgm Sciences Inc.). The acquired data were analyzed in

Cytobank (Cytobank, Inc., Menlo Park, CA). The gating strategy of Tregs is described in

Supplementary Figure 1A.

The CD138-negative populations of SMM patients or healthy donors' bone marrow cells

were thawed, washed and barcoded using the Cell-ID™ 20-Plex Pd Barcoding Kit

(Fluidgm Sciences Inc.). After barcoding, cells were incubated with human surface

marker antibodies as a single multiplexed sample (TIGIT-143Nd, CD152 (CTLA4)-

152Sm, PD1-175Lu, TIM3-153Eu (Maxpar) and Maxpar® Human T-Cell Phenotyping

Panel Kit, 16 Marker). The cells were fixed with 4% Paraformaldehyde, permeabilized

with ice-cold Methanol and incubated with antibodies against intracellular proteins

(FOXP3 -clone PCH101, custom conjugation with 165Ho by Harvard Medical Area

CyTOF Antibody Resource and Core, Boston, USA). Then the cells were washed,

resuspended at the concentration of 1x106 cells/mL and acquired on a CyTOF Helios mass

cytometer (Fluidgm Sciences Inc.). Downstream analysis of the individual component

samples was performed after running the debarcoding application. Human T-cell

populations were gated according to the Maxpar Human T Cell Phenotyping Panel Kit.

24

Flow cytometric analysis

Anti-mouse antibodies against CD3, CD4, CD8, PD1 (Biolegend, San Diego, CA), CD25,

LAG3, TIM3, B220, FOXP3, Ki-67 (eBioscience, San Diego, CA), CD138 (BD

Biosciences, San Jose, CA) and anti-human antibodies against CD4, CD25, FOXP3

(eBioscience, San Diego, CA) were used for the FACS analyses. Cells were surface

stained, fixed/permeabilized and stained intracellularly using the FOXP3/Transcription

Factor Staining Buffer Set (eBioscience, San Diego, CA) according to the manufacturer’s

protocol. The data of the stained samples were acquired using FACS Canto II flow

cytometer (BD Biosciences). The acquired data were analyzed in Cytobank (Cytobank,

Inc.)

RNA Sequencing Analysis

Total RNA was isolated from flow-sorted CD4+FOXP3-GFP+ cells acquired from the BM

of Vk*MYC-injected and control mice using RNeasy Micro kit (QIAGEN, Venlo,

Netherlands). Whole RNA was subject to library preparation using NEBNext Ultra RNA

Library prep for Illumina kit (New England Biolabs, Ipswich, MA). Quality control of

the libraries was evaluated by Bioanalyzer analysis with High Sensitivity chips (Agilent

Technologies, Santa Clara, CA). Sequencing was performed on a HiSeq 2000 (Illumina,

San Diego, CA) by 2X50bp paired-end reads at the Biopolymers Facility of Harvard

Medical School. We used Picard and STAR to process and align the RNA-seq reads with

mouse reference genome (mm10) and to compute a series of quality control metrics.

RNA-seq transcript abundances were estimated using RSEM (Li B and Dewey CN, 2011).

Genes with low expression (RSEM expected counts) were filtered out and differential

gene expression between different samples was determined using DESeq2 (Love MI et

25

al., 2014). Differential expression was selected based on fold changes > 2.0 and a p-value

threshold of 0.05 (Sequencing data are submitted to GEO; reference number will be

provided). Gene set enrichment analysis (GSEA) was used to identify significantly

enriched pathways(59), with false discovery rate (FDR) <0.25 and p-value < 0.05. Gene

sets were downloaded from the Broad Institute’s MSigDB

(http://www.broadinstitute.org/gsea/index.jsp). The accession numbers for the human

data reported in this manuscript are GEO: GSE6477 and GSE2658.

ELISA

Murine myeloma cell lines' (C57BL/6 or C57BL/KalwRij mice) B-cells were seeded into

12-well plates at a concentration of 2x105 /mL and cultured for 24hrs. Murine IFN-alpha

and IFN-beta levels of cell culture supernatants were detected using VeriKine-HS Mouse

IFN ELISA Kits (PBL Assay Science, Piscataway, NJ) according to the manufacturer’s

protocol.

Treg induction and expansion assay

CD4+CD25- non-Tregs (induction assay) at 2×105 or CD4+CD25+ Tregs (expansion

assay), isolated from C57BL/6 or C57BL/KalwRij splenocytes were co-cultured with

1×105 myeloma cell lines in the presence of recombinant murine IL-2 (1000 IU/ml; R&D

Systems, Minneapolis, MN), anti–CD3-Ab (5 ug/ml; eBioscience) and anti–CD28-Ab (5

ug/ml; eBioscience) for 72 hrs. TGF-beta (10 ng/mL; R&D Systems) was added for the

induction assay. IFNAR1-Ab (Biolegend) or isotype control-Ab were added to the

appropriate wells at the concentration of 100 ug/mL.

26

Human CD4+CD25- non-Tregs or CD19-expressing B-cells were obtained from fresh PB

cells using CD4+CD25+ Regulatory T Cell Isolation Kit or CD19 Microbeads (Miltenyi

Biotech). Briefly, red blood cells were lysed (RBC lysis buffer, Biolegend), washed and

isolated according to manufacturer’s instructions. The CD4+CD25- non-Tregs at 2×105

were co-cultured with 1×105 myeloma cell lines in the presence of recombinant human

IL-2 (1000 IU/ml; R&D Systems, Minneapolis, MN) and the Treg Suppression Inspector

beads (Miltenyi Biotech) in 1:1 beads to cells ratio. Transwell permeable inserts with a

pore size 0.4 Pm were used to prevent cell-cell interactions (Corning).

Statistical analysis

One-way ANOVA was used when three or more independent groups were compared. The

unpaired Student t test was used to compare two independent groups with Bonferroni

correction for multiple comparisons. For survival data, Kaplan–Meier curves were plotted

and compared using a log-rank test. All tests were two-tailed. A p-value < 0.05 was

considered statistically significant. Analysis was performed with GraphPad Prism

Software (GraphPad Software Inc., La Jolla, CA).

Study approval

All mice were treated, monitored, and sacrificed in accordance with an approved protocol

of the Dana-Farber Cancer Institute Animal Care and Use Committee (Boston, USA).

Human studies were approved by the Dana-Farber Cancer Institute Institutional Review

Board (Boston, USA). Informed consent was obtained from all patients and healthy

volunteers in accordance with the Declaration of Helsinki protocol.

27

AUTHORS’CONTRIBUTIONS

Conception and design: Y. K., O. Z., J. A. and I. M. G.

Acquisition of data: Y. K., O. Z., M. M., K. K., T. M., N. M., M. R., Y. J. S., M. R., M.

B., P. L., E. S. K., S. T., S. M., J. S., S. T., M. R. R., D. H., A. S.

Analysis and interpretation of data: Y. K., O. Z., M.M., J. P., S. M., J. S., Y. T., M. C.,

P. L. B., A. M. R., J. A., I. M. G.

Writing, review, and/or revision of the manuscript: Y. K., O. Z., J. P., R. S. P., A. M.

R., J. A., I. M. G.

CONFLICT OF INTERESTS

The Authors declare no relevant conflict of interests.

Funding support: NIH R01 CA181683-01A1 and Leukemia and Lymphoma Society.

28

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0

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FIGURE 1

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C on tro l

V k *M YC

Bone marrow

Figure 1. Tregs are increased in the BM of Vk*MYC transplantable mouse model.(A) BM and PB were harvested from control (n=3) and Vk*MYC-injected mice (n=3) at early (day 14)and late (day 28) time points for CyTOF analysis. (B) Significant increase of Tregs frequency withinCD4+ T-cells in the BM of Vk*MYC-injected mice compared to control mice from early time points.Data validated by FACS (n=5). (C) Spanning-tree progression analysis of density-normalized events(SPADE) was conducted on late BM CD4+ T-cells of control and Vk*MYC injected mice. The size of thenodes indicates the frequency of each population, while the color indicates the expression of FOXP3.Increase of FOXP3+ cells within CD4+ T-cells was observed in Vk*MYC-injected BM. (D) Significantincrease of Tregs frequency within CD4+ T-cells in the PB of Vk*MYC-injected mice compared tocontrol mice at late time points. (E) Significant decrease of Teffs (CD4+CD44++CD62Llow andCD8+CD44++CD62Llow)/Tregs ratio was observed in BM of Vk*MYC injected mice at the late time pointas compared to BM of control mice. (F) Significant increase of CD4+CD25+FOXP3-expressing cells andCD4+CD25+FOXP3+CD127-/low Tregs in BM aspirates of SMM patients (n=17) compared to healthydonors (n=11). Data combined from 3 independent experiments. Cell numbers were normalized to thecell proportion in healthy BM. (t-test 2-tailed, error bars indicate SD)

E

Vk*MYC

D

Tre

gs(%

)

ControlVk*MYC

ControlVk*MYC

Tre

gs(%

)

Early Late

Early Late

Early Late

ControlVk*MYC

Tef

fs/T

regs

NBMSMMp=0.016

Cel

l rat

io (%

)

p=0.007

Human bone marrow

FIGURE 2A B

C

E

P D 1 L AG 3 T im 30

1 0

2 0

3 0

4 0

5 0

Ex

pre

ssio

n in

Tre

gs

(%

) C on tro l

V k *M YC

p=0.0001

p<0.0001

p=0.002

D

Control

Vk*MYC

Early Late

PD1

LAG

3

TIM

3

PD1

LAG

3

TIM

3

Fold change

Figure 2. Upregulation of immune checkpoint molecules in Tregs in the BM of Vk*MYC-injected mice andSMM patients. (A) BM Tregs of Vk*MYC-injected mice have significantly higher frequency of immune checkpointreceptor (PD1, LAG3 and TIM3) expressing Tregs compared to control BM Tregs at the late time point (n=3 pergroup, validated by FACS with n=5 per group). (B) SPADE tree was conducted on BM Tregs of control andVk*MYC-injected mice at the late time point. The nodes of the tree represent clusters of cells that are similar in markerexpression. The color indicates the expression of LAG3. Increase of LAG3+ cells within Tregs was observed inVk*MYC injected BM. Heatmap of immune checkpoint receptor (PD1, LAG3 and TIM3) expression of BM (C) andPB (D) Tregs at early and late time points. The color indicates the mean expression fold change of each molecule. BMTregs of Vk*MYC injected mice had higher expression of immune checkpoint receptors compared to control BMTregs, while PB Tregs of Vk*MYC injected mice did not show increased expression compared to control PB Tregsthroughout disease progression. (E) Increased number of Tregs expressing immune checkpoint receptors in BM ofSMM patients (n=17) as compared to healthy donors (n=11). Data combined from 3 independent experiments. (G)Heatmap of immune checkpoint molecules and CCR7-chemokine receptor expression of Tregs in BM of MM patientscompared to healthy donors. The color indicates the ratio of mean expression of each molecule. Tregs of MM patientsshow elevated expression levels of immune checkpoint molecules (H) CD4+ and CD8+ T effector cells in BM of MMpatients have higher expression of immune checkpoint molecules compared to healthy donors. The color indicates theratio of mean expression of each molecule. (t-test 2-tailed, error bars indicate SD)

Control Vk*MYCPD1+

LAG3+

Tim3+

LAG3 intensity

G

Early Late

PD1

LAG

3

TIM

3

PD1

LAG

3

TIM

3

Control

Vk*MYC

Fold change

CD4 Teffs

PD1

LAG

3

TIM

3

PD1

LAG

3TI

M3

CD8 Teffs

Control

Vk*MYC

Fold change

CD

27C

TLA

-4

CC

R7

TIM

3

PD1

TIG

IT

Tregs

NBM

SMM

Ratio of means

NBM

SMM

Ratio of means

CD

27C

TLA

-4

CC

R7

TIM

3

PD1

TIG

IT

CD4 Teffs

CD

27C

TLA

-4

CC

R7

TIM

3

PD1

TIG

IT

CD8 Teffs

ControlVk*MYC

PD1+TIM3+Control Vk*MYC

LAG3+

TIM3

LAG3 intensity

LAG3PD1

Exp

ress

ion

in T

regs

(%)

F

0

5

10Chart Title

NBM SMM

NBMSMM

Cel

l rat

io (%

)

p=0.032

p=0.018

p=0.022p=0.013

p=0.003

p=0.306

H

FIGURE 3

A B C

Figure 3. Treg depletion in DEREG mice leads to extended survival of Vk*MYC-injectedmice, while adoptive transfer of Tregs promotes tumor progression in vivo.(A) Diphteria toxin or PBS were injected 3 times (day 5, day 12 and day 19) post Vk*MYC-injection into DEREG mice or wild type mice (n=7/group). (B) Proportion of Vk*MYC cells(CD138+B220- cells) in the BM of each group at day 20 post Vk*MYC injection. 3 mice from eachgroup were sacrificed at day 20 for analysis of BM Vk*MYC frequency. Significant tumorreduction occurred in the DEREG mice treated with DT compared to control mice. (t-test 2-tailedwith Bonferroni correction) (C) Kaplan-Meier curve showing significant increase in survival ofDEREG mice treated with DT (DEREG + DT) compared to control groups (DEREG + PBS, Wildtype + DT) (n=7/group) (p<0.0001: Log-rank). (D) For Treg transfer experiments, 3×106 non Tregswere injected with or without 1×106 Tregs i.v into Rag2 ko mice followed by Vk*MYC cellinjection 5 days afterwards. (E) Kaplan-Meier curve showing mice injected with Tregs and CD3+

non Tregs (Tregs + CD3+ non Tregs: Median survival 21 days) had significantly shorter survivalcompared to mice injected only with CD3+ non Tregs (CD3+ non Tregs: Median survival 25.5 days)(n=6/group) (p<0.01: Log-rank). (F) FACS analysis of mice BM showing significant increase ofBM Tregs in the “Tregs + CD3+ non Tregs” group compared to “CD3+ non Tregs” group(n=3/group). T-test 2-tailed. (error bars indicate SD)

D E R E G -D T D E R E G -P B S W ild typ e -D T0

5

1 0

1 5

Vk

*MY

C c

ell

s i

n t

he

BM

(%) p<0.001

p<0.001

Vk*

MY

C c

ells

in th

e B

M (%

)

WT+DTDEREG DEREG+PBS

D E F

DEREG + DT

DEREG + PBS

DT

Wild type + DT

DT DT

DT DT DT

PBS PBS PBS

DEREG +DT

DEREG +PBS

Wild type +DT

DT DT DT

PBS PBS PBS

DT DT DT

p<0.001 (Log-rank)

DEREG+DT

Wildtype+PBSDEREG+PBS

Perc

ent s

urvi

val

Days post tumor injection

GDEREG+DTDEREG+PBSWild type+DT

p<0.001(Log-rank)

CD

3+ N

o n Tre

g s

T reg s +

CD

3+ N

o n Tre

g s0

1 0

2 0

3 0

Tre

gs

(%

)

p=0.001

Treg

s(%

)CD3+

non T

regs

Treg

s+CD3+

nonT

regs

p=0.001

0

20

40

60

80

100

15 20 25 30Days post tumor injection

Perc

ent s

urvi

val

p<0.01 (Log-rank)

Tregs+CD3+NonTregsCD3+nonTregs

Perc

ent s

urvi

val

Days post tumor injection

Tregs + CD3+ non TregsCD3+ non Tregs

p<0.01(Log-rank)

Tregs+

CD3+ non Tregs

CD3+ non Tregs

Tregs+

CD3+ non Tregs

CD3+

non Tregs

FIGURE 4

A B

C

B cells

OPM2 cells

No cells

MM1S cells

0

5

10

15

20

25

No cells B cells MM1S OPM2

Human Treg induction assay

Treg

s(%

)

No cells B cells MM1S OPM2

T r a n s -w e ll D ir e c t0

2 0

4 0

6 0

8 0

1 0 0

Tre

gs

(%

)

N o ce lls

B c e lls

V k *M Y C c e lls

p<0.001

p<0.001p<0.001

p<0.001

Treg expansion assay

No cellsB cellsVk*MYC cells

Trans-well Direct

Treg

s(%

)

T r a n s -w e ll D ir e c t0

1 0

2 0

3 0

4 0

5 0

Tre

gs

(%

)

N o ce lls

B c e lls

V k *M Y C c e lls

p<0.001

p<0.001p<0.001p<0.001

Treg induction assay

No cellsB cellsVk*MYC cells

Trans-well Direct

Treg

s(%

)

Figure 4. Myeloma cells induce and expand Tregs in vitro.(A) Treg induction assay. CD4+CD25- non-Tregs were co-cultured with C57BL/6 B cells or Vk*MYCcells for 72 hrs using trans-well or direct co-culture. Significant Treg induction was observed in theVk*MYC co-culture group either under trans-well or direct co-culture compared to “No cells” or “Bcells” groups. Average of experiments performed in triplicate is shown. The experiment was repeated 3times. (B) Treg expansion assay. CD4+CD25+ Tregs were co-cultured with C57BL/6 B cells orVk*MYC cells for 72 hrs using trans-well or direct co-culture. FOXP3+ cells within the CD4+ cells areshown. Significant Treg expansion was observed in the Vk*MYC co-culture group either under trans-well or direct co-culture compared to “No cells” or “B cells” groups. Average of experiments performedin triplicate is shown. The experiment was repeated 3 times. (C) Significant Treg induction wasobserved in co-culture of MM1S and OPM2 myeloma cells with human PB cells. Human CD4+CD25-

cells were co-cultured with MM1S or OPM2 myeloma cells for 72 hrs using trans-well co-culture.MM1S and OPM2 co-culture groups were compared to “No cells” or CD19-expressing “B cells”groups. Treg cells were assessed as CD4+CD25+FOXP3-expressing cells. Data from independentexperiments performed in triplicate of three different PB donors is shown. (t-test 2-tailed withBonferroni correction; *p<0.05, **p<0.01, error bars indicate SD)

***

****

FIGURE 5

A B

Figure 5. Differences in gene expression between myeloma-associated and control Tregs in the BMmicroenvironment.(A) mRNA expression profiling by RNA sequencing on total RNA isolated from Control (n=3) andVk*MYC-injected (n=3) BM Tregs. A heatmap was generated after supervised hierarchical clusteranalysis. Differential mRNA expression is shown in red (upregulation) versus blue (downregulation)intensity (Control versus Vk*MYC, 2-fold change, p<0.05). (B) Differences in checkpoint related geneexpression levels of Tregs isolated from Vk*MYC-injected and control mice. A number of checkpointrelated molecules were significantly up-regulated in Tregs from Vk*MYC-injected mice compared tocontrol Tregs. The gene expression fold change in Tregs from Vk*MYC-injected mice compared tothose from control Tregs is shown. (C) Differences in Treg effector gene expression levels betweenVk*MYC and control Tregs. The gene expression fold change of Tregs from Vk*MYC-injected micecompared to control Tregs is shown. (D) Differences in chemokine receptor gene expression levelsbetween Tregs from Vk*MYC-injected mice and control Tregs. (* p≤0.05, ** p<0.01, t-test 2-tailed,error bars indicate SD)

Control Vk*MYC

PD1OX40

CTLA-4

TIGIT

ICOS

GITR

LAG3TIM

30

1

2

3

4

Series1

Series2

ControlVk*MYC

Fold

cha

nge

*

***

** **

C

D

Fold

cha

nge

IL10

FGL2

GZMBPRF1

TGFB1EBI3

0

1

2

3

4

5

6

7

8

Series1

Series2

****

** ControlVk*MYCVk*MYCControl

CXCR3CCR6

CCR70

1

2

3

Series1

Series2

**

Fold

cha

nge

ControlVk*MYC

**

Vk*MYCControl

FIGURE 6

Bp=0.024

FDR 0.0p<0.01

FDR 0.0p<0.01

A

FDR 0.023p<0.01

FDR 0.02p<0.01

p=0.038

IFNA1

p=0.043

TLR8FE

C D

0

1

2

3

4

5

6

IRF3 IRF4 IRF5 IRF9 IFNA1 IFNA2 MAVS TLR8

Series1 Series2

HealthyPatients

Fold

cha

nge

** ** ***

**

** **

IRF3 IRF4 IRF5 IRF9 IFNA1 IFNA2 MAVS TLR8

Vk*MYCB cells

IFN

-bet

a (p

g/m

L)

Figure 6. Type-1 IFN signaling associated with Treg activation and overall patient survival.(A) Vk*MYC BM Tregs show an enrichment for Type-1 IFN-related mRNA signature compared to Control BMTregs, as presented by GSEA. The green curves show the enrichment score and reflect the degree to which eachgene (black vertical lines) is represented at the top or bottom of the ranked gene list. The heatmap indicates therelative abundance (red to blue) of the genes specifically enriched in the Vk*MYC Tregs as compared to controlTregs. FDR indicates false discovery rate and p indicates p values and are shown per each geneset analyzed. (B)IFN-beta secretion from Vk*MYC cells. IFN-beta secretion, detected by ELISA, in Vk*MYC cell culturesupernatants was significantly higher compared to the supernatants of control B cells obtained from C57BL/6 mice.Average of experiments performed in triplicate is shown. The experiment was repeated 3 times. (C) Myeloma cellsfrom MM patients show enrichment in type-1 IFN signaling pathway compared to cells from healthy donors. (D)Differential gene expression levels for genes involved in type-1 IFN production. (E) IFNA1 overexpression isassociated with worse overall survival in MM patients. (F) Expression of TLR8 receptor significantly correlates withworse outcome in MM patients. (t-test 2-talied, error bars indicate SD, * p<0.05, ** p<0.01)

E F

HG I

FIGURE 7

A

C D

p=0.0005

IFNAR1 AbIsotyp Ab

Ki-6

7+ T

regs

(%)

IFNAR1 Abki-67

FOXP

3

Isotype Ab IFNAR1 Ab

51.41 % 19.61 %

IFNAR1 AbIsotype Ab

Ki-67

FOX

P3

CD4

FOXP

3

Isotype Ab IFNAR1 Ab

70.37 % 55.63 %

IFNAR1 AbIsotype Ab

CD4

FOX

P3

p=0.0024p=0.0024

IFNAR1 AbIsotyp Ab

Ki-6

7+ T

regs

(%)

IFNAR1 Ab

WT Tregs+

CD3+ non Tregs

IFNAR1 ko Tregs+

CD3+ non Tregs

CD3+ non Tregs

WT Tregs+

CD3+ non Tregs

IFNAR1 ko Tregs+

CD3+ non Tregs

CD3+ non Tregs0

5 0

1 0 0

1 5 2 0 2 5 3 0

D a y s p o s t tu m o r in je c t io n

Per

cent

sur

viva

l p<0.01 (Log-rank)

WTTregs+CD3+NonTregsIFNAR1koTregs+CD3+NonTregsCD3+NonTregs

Perc

ent s

urvi

val

Days post tumor injection

p<0.01 (Log-rank)

WT Tregs + CD3+ non TregsIFNAR1 ko Tregs + CD3+ non TregsCD3+ non Tregs

P D 1 L AG 3 T im 30

2 0

4 0

6 0

Ex

pre

ssio

n in

Tre

gs

(%

) W ild ty p e

IF N A R 1 ko

p=0.018n.sn.s

P D 1 L AG 3 T im 30

2 0

4 0

6 0

Ex

pre

ssio

n in

Tre

gs

(%

) W ild ty p e

IF N A R 1 ko

p=0.018n.sn.s

Expr

essi

on in

Tre

gs(%

)

PD1 LAG3 TIM3

p=0.018

n.s n.s

Wild typeIFNAR1 ko

IFNAR1

60.22 % 9.52 %

Wild type IFNAR1 ko

IFNAR1

IFNAR1 ko

W ild typ e IF N AR 1 k o 0

5

1 0

1 5

2 0

2 5

Tre

gs

(%

)

p=0.0032

Treg

s(%

)

Wild type IFNAR1 ko

p=0.0032

B

Figure 7. Blocking IFNAR1 suppress Treg expansion and myeloma progression.(A) Representative FACS analysis of Ki-67 expression of Tregs expanded under co-culture with Vk*MYCcells and IFNAR1 antibody (IFNAR1 Ab) or isotype control (Isotype Ab). (B) Significant decrease of Ki-67expression in Tregs co-cultured with Vk*MYC and IFNAR1 Ab compared to those with Isotype Ab. Averageof experiments performed in triplicate is shown. The experiment was repeated 3 times. (C) RepresentativeFACS analysis of Treg expansion assay with IFNAR1 Ab or isotype Ab co-culture. Proportion of FOXP3+

cells in the CD4+ cells is shown. (D) Significant decrease of Treg proliferation by cells co-cultured withVk*MYC and IFNAR1 Ab compared to Isotype control. Average of experiments performed in triplicate isshown. The experiment was repeated 3 times. (E) 3×106 non Tregs were injected with or without 1×106

C57BL/6 Tregs or IFNAR1 ko Tregs i.v into Rag2 ko mice followed by Vk*MYC cell injection 5 daysafterwards. (F) Kaplan-Meier curve showing survival of mice injected with C57BL/6 Tregs and CD3+ nonTregs (WT Tregs + CD3+ non Tregs) compared to mice injected with IFNAR1 ko Tregs and CD3+ non Tregs(IFNAR1 ko Tregs + CD3+ non Tregs) and only with CD3+ non Tregs (CD3+ non Tregs) (n=6/group). (G)Significant decrease of BM Tregs in the “IFNAR1 ko” group (IFNAR1 ko Tregs + CD3+ non Tregs)compared to “Wild type” group (n=3/group) by FACS. (H) Representative FACS analysis of BM Tregs ofmice transferred with IFNAR1 ko Tregs compared to mice transferred with wild type Tregs. (I) FACSanalysis of checkpoint related molecules on BM Tregs obtained from mice injected with IFNAR1 ko Tregsand wild type Tregs. Significant decrease of LAG3 was observed in BM Tregs obtained from mice injectedwith IFNAR1 ko mice (n=3/group). (t-test 2 tailed, error bars indicate SD)

Wild type

Supplementary Figure 1

A

B

Supplementary Figure 1. Gating strategy for Treg analysis by CyTOF.(A) Gating strategy of CD4+ T cells by CyTOF. BM and PB CD4+ T cells were determined byfirst excluding non-viable cells. After initial gating on CD45+ cells, CD11b- CD11c- non myeloidcell population was gated, followed by selecting CD3+ B220- T cell population and finally gatedon CD4+ CD8- population. (B) Representative Treg plots by CyTOF. FOXP3+ cells weredetermined within CD4+ T cells. Control and Vk*MYC injected BM Tregs of late time points areshown. (C) Absolute numbers of Treg cells in BM of Vk*Myc-injected mice at late time point.(D) Number of Treg per 1 ml PB in Vk*Myc-injected mice at late time point. SPADE tree wasconducted on viable BM cells of control (E) and Vk*MYC-injected (F) mice at the early timepoint. The nodes of the tree represent clusters of cells that are similar in marker expression. Thecolor indicates level of marker expression. Size of the nodes represents number of cells.Increased numbers of CD3-expressing cells were observed in the BM of Vk*MYC-injected micecompared to control BM cells.

C D

B22

0

CD3

CD

8

CD4

CD

11c

CD11b

CD45+ CD11b- CD11c- CD3+ B220-

CD4

FOX

P3

Control Vk*MYC

30.56 %17.73 % p=0.014p=0.2

BM Tregs absolute numbers (/Femur)

PB Tregs absolute numbers (/mL)

ControlVk*MYC

Treg

coun

t (/F

emur

)

Control Vk*MYC

Treg

coun

t (/m

L)

Control BM (early) Vk*MYC–injected BM (early)E F

NBM

145N

d_C

D4

156Gd_CD25_IL2R 165Ho_FOXP3 176Yb_127_IL-7R

145N

d_C

D4

156Gd_CD25_IL2R 165Ho_FOXP3 176Yb_127_IL-7R

156Gd_CD25_IL2R 165Ho_FOXP3 176Yb_127_IL-7R

145N

d_C

D4

156Gd_CD25_IL2R 165Ho_FOXP3 176Yb_127_IL-7R

145N

d_C

D4

145N

d_C

D4

165Ho_FOXP3

1.61% 0.21% 0.06%

0.89% 0.15% 0.04%

0.94% 0.2% 0.08%

0.66% 0.09% 0.03%

0.61% 0.1% 0.04%

156Gd_CD25_IL2R 176Yb_127_IL-7R

SMM

Supplementary Figure 2

Peripheral bloodp=0.0068

Teff

s/Tre

gs

Early Late

A

B

Supplementary Figure 2. Decrease of Teff/ Tregs ratio in PB of Vk*MYC-injected miceand increased number of Tregs in BM of SMM patients.(A) Significant decrease of Teffs (CD4+ CD44++ CD62Llow and CD8+ CD44++ CD62Llow)/Tregsratio was observed in PB of Vk*MYC injected mice at the late time point as compared to BMof control mice. (B) Representative CyTOF profiles showing proportion of CD4+CD25+,CD4CD25FOXP3+ and CD4CD25FOXP3CD127-/low cells in CD45-expressing bone marrowfraction of 3 SMM patients compared to healthy donors. (t-test 2-tailed, error bars indicate SD)

p=0.002

p=0.097 p=0.002

p=0.006

Expr

essio

n in

Tre

gs(%

)

Supplementary Figure 3Ex

pres

sion

in T

regs

(%)

PD1 LAG3 Tim3

ControlVk*MYC

Peripheral blood (early)

p=0.036

PD1 LAG3 Tim3

Expr

essio

n in

Tre

gs(%

)

A

ControlVk*MYC

BPeripheral blood (late)

Expr

essio

n in

Tre

gs(%

)

ControlVk*MYC

PD1 LAG3 TIM3

Bone marrow (early)

Control

D

Vk*MYC

CD4+ Teffs

PD1

LAG

3

TIM

3

PD1

LAG

3

TIM

3

CD8+ Teffs

Fold change

Control

Vk*MYC

PD1

LAG

3

TIM

3

PD1

LAG

3

TIM

3

Fold change

Control

Vk*MYC

PD1

LAG

3

TIM

3

PD1

LAG

3

TIM

3

Fold change

Peripheral blood (early) Peripheral blood (late)

Bone marrow (early)

E F

G

CD4+ Teffs CD8+ Teffs CD4+ Teffs CD8+ Teffs

C

ControlVk*MYC

Bone marrow (late)

Supplementary Figure 3. Decrease of Teff/ Tregs ratio in PB of Vk*MYC-injected mice and expressionof immune checkpoint molecules in Tregs in the BM and PB at different time points post injection.Expression of immune checkpoint receptor (PD1, LAG3 and TIM3) on Tregs in PB of Vk*MYC-injectedmice (n=3) compared to control Tregs (n=3) at early (A), late (B) time point. (C) Expression of immunecheckpoint receptor (PD1, LAG3 and TIM3) on Tregs in BM of Vk*MYC-injected mice compared tocontrol Tregs at early time point. (D) Co-expression of checkpoint receptor (PD1, LAG3 and TIM3) onTregs in BM of Vk*MYC-injected mice compared to healthy controls at late time point. Heatmap ofimmune checkpoint receptor (PD1, LAG3 and TIM3) expression on PB CD4+ and CD8+ Teffs (CD44++

CD62Llow) at early (E) and late (F) time points. The color indicates the mean expression fold change of eachmolecule. (G) Heatmap of PD1, LAG3 and TIM3 expression on BM CD4+ and CD8+ Teffs (CD44++

CD62Llow) at early time point. (t-test 2-tailed, error bars indicate SD)

0

20

40

60

80

100

120

Supplementary Figure 4A B

C o n tr o l 5 T G M 10

2

4

6

8

1 0

Te

ffs

/ Tre

gs

C o n tr o l 5 T G M 10

1 0

2 0

3 0

4 0

Tre

gs

(%

)p=0.017 p=0.0257

C

Control

5TGM1

PD1

LAG

3

TIM

3

Fold change

D

Control

5TGM1

CD4+ Teffs

PD1

LAG

3

TIM

3

PD1

LAG

3

TIM

3

CD8+ Teffs

Fold change

Tregs

Supplementary Figure 4. Treg increased and activated in BM of 5TGM1-injected C57BL/KalwRij mice and co-expression of immune checkpoint molecules in BM of SMM patients.(A) Significant increase of Tregs frequency within CD4+ T cells in the BM of 5TGM1 injected mice(n=3) compared to control mice (n=3) at late time point (day 28). (B) Significant decrease of Teffs /Tregs ratio was observed at the late time point of 5TGM1 injected mice compared to control mice. (C)Heatmap of immune checkpoint receptor (PD1, LAG3 and TIM3) expression of BM Tregs at late timepoint. The color indicates the mean expression fold change of each molecule. BM Tregs of 5TGM1injected mice had higher expression of immune checkpoint receptors compared to control BM Tregs.(D) Heatmap of PD1, LAG3 and TIM3 expression of BM CD4+ and CD8+ Teffs at late time point.Higher expression of PD1, LAG3 and TIM3 on 5TGM1 injected BM Teffs. (E) Increased proportion ofTregs co-expressing PD1, TIM3 and CTLA4 in BM aspirates of SMM patients (n=17) compared tohealthy donors (n=11). Data combined from 3 independent experiments. (t-test 2-tailed, error barsindicate SD)

Control 5TGM1 Control 5TGM1

Treg

s, %

Teffs

/Tre

gs

NBMSMM

p=0.018

p=0.027 p=0.036

Expr

essio

n in

Tre

gs(%

)

Human bone marrowE

0

1

2

3

4

5

6

7

8

Co DT

Supplementary Figure 5

CD4

FOXP

3

DTPBS

27.12% 0.8%

A

D

Supplementary Figure 5. Proportion of Tregs after depletion by DT or adoptive transfer.(A) Effective depletion of BM Tregs in Vk*MYC-injected DEREG mice by DT injection comparedto PBS injection at day 20 post Vk*MYC injection. (B) Flow cytometry data of BM cells at day 3after last DT treatment in Vk*MYC-injected mice demonstrate a significantly increased Teff/Tregratio compared to PBS treated mice (4 weeks post Vk*MYC injection). (C) Phenotypic distributionof bone marrow cells in Vk*MYC-injected mice 4 weeks post Vk*Myc injection and DT treatmentcompared to Vk*MYC-injected, non-treated DEREG mice (n=5 per group). (D) RepresentativeFACS analysis of BM Tregs of mice injected with Tregs and CD3+ non Tregs (Tregs + CD3+ nonTregs) and mice injected only with CD3+ non Tregs (CD3+ non Tregs). (t-test 2-tailed, error barsindicate SD)

B

Non-treated CoDT-treated

Prop

ortio

n of

cel

ls in

BM

, %

p<0.05

p<0.05

C

CD4

FOX

P3

PBS DT

0

2

4

6

8

DEREG+PBS DEREG+DT

Teff

/Tre

gra

tio

p<0.001

CD4

FOXP

3 1.59 % 20.69 %

CD3+ non Tregs

Tregs+

CD3+ non Tregs

CD4

FOX

P3

CD3+ non Tregs

Tregs+

CD3+ non Tregs

20.69 %2.75 %

Supplementary Figure 6

Supplementary Figure 6. Blocking of CD25 receptor using CD25 antibody prolongs survival ofVk*MYC injected animals.(A) Treatment with anti-CD25 antibody leads to better survival of injected mice. Mice were treated withanti-CD25 antibody on day -4 and day 10 post Vk*MYC cell injection (n=6). Isotype antibody treatmentwas used in the control group (n=6). (B) Significantly lower numbers of Tregs were detected in PB of anti-CD25 antibody treated mice as compared to isotype controls. PB analysis was done on day 11 postVk*MYC injection. (t-test 2-tailed, error bars indicate SD)

A B

p=0.025 (Log-rank)

Days post tumor injection

Perc

ent s

urvi

val,

%

IsotypeCD25 Ab

p=0.026

Treg

s, %

Isotype CD25 Ab

Supplementary Figure 7

N o c e lls B c e lls 5 T G M 10

2 0

4 0

6 0

8 0

Tre

gs

(%

)

A

p<0.001

p<0.001

p<0.05

Is o typ e Ab IF N AR 1 Ab0

3 0

6 0

9 0

ki-

67+

Tre

gs

(%

)

BP=0.0062

Is o typ e Ab IF N AR 1 Ab0

2 0

4 0

6 0

8 0

Tre

gs

(%

)

CP=0.0007

Isotype AB IFNAR1 Ab Isotype AB IFNAR1 Ab

Ki-6

7+Tr

egs,

%K

i-67+

Treg

s, %

Treg

s, %

Treg

s, %

No cells B -cells 5TGM1

Supplementary Figure 7. Type-1 IFN pathway plays a role in Treg expansion by 5TGM1cells.(A) 5TGM1 cells are capable of expanding Tregs in vitro. CD4+ CD25+ Tregs were co-cultured with C57BL/KalwRij B cells or 5TGM1 cells for 72 hrs using trans-well. FOXP3+

cells within the CD4+ cells are shown. Significant Treg expansion was observed in the5TGM1 co-culture group under trans-well compared to “No cells” or “B cells” groups.Average of experiments performed in triplicate is shown. The experiment was repeated 3times. (B) Significant decrease of ki-67 expression of 5TGM1 expanded Tregs co-culturedwith IFNAR1 Ab was observed compared to Isotype Ab. Average of experiments performedin triplicate is shown. The experiment was repeated 3 times. (C) Significant decrease of Tregexpansion by 5TGM1 cells co-cultured with IFNAR1 Ab compared to Isotype Ab. Average ofexperiments performed in triplicate is shown. The experiment was repeated 3 times. (t-test 2-tailed, error bars indicate SD)

1

SUPPLEMENTARY TABLE 1

gene_name log2FoldChange pvalue CR2 -1.754105105 1.14E-07 GM38257 -1.663325205 5.07E-07 GM11175 -1.625350548 1.78E-08 H2-DMB2 -1.580643499 9.61E-07 NTRK3 -1.538300689 3.19E-06 RGS2 -1.535722917 2.48E-07 PPP1R15A -1.493961489 3.26E-06 DNAJB9 -1.489792391 2.98E-13 BAMBI -1.453324869 3.85E-06 TNFAIP3 -1.413637676 6.27E-06 SLC30A4 -1.363309794 5.53E-06 GM10698 -1.360612906 6.90E-07 FOS -1.312912328 5.00E-05 ALAS2 -1.311925596 2.46E-10 HBA-A1 -1.308836618 2.61E-16 CD22 -1.304986205 6.08E-06 SCD1 -1.299237228 6.01E-05 PTPRF -1.293199031 5.00E-05 ZFP354C -1.278876062 0.000119035 PAX5 -1.269783046 9.99E-05 RP23-4F16.12 -1.246683443 5.08E-06 BLK -1.232624802 0.000211979 JUN -1.229247208 0.000153806 ATP1B1 -1.198212543 1.09E-08 ZSCAN10 -1.196748707 0.000137553 CACNA2D2 -1.181106971 0.000334108 E430014B02RIK -1.180031188 0.000216646 VANGL2 -1.173394111 0.000122724 RASL11B -1.169355359 9.85E-05 MAFF -1.16763885 0.000336557 RYR2 -1.16547011 0.000458805 PIM3 -1.155030723 3.51E-08 C1QL3 -1.153808501 0.000493352 NR4A2 -1.147471441 5.88E-05 C230085N15RIK -1.145522682 0.000538342

2

TRP53INP2 -1.141599881 0.000274122 BTG2 -1.137583817 2.61E-15 LY6D -1.132680814 0.000252716 SPTY2D1 -1.116065657 2.57E-08 DAPK1 -1.103332552 4.56E-05 SIK1 -1.087969101 0.000940377 GFOD2 -1.07715986 0.000948759 TRIB1 -1.073847646 2.72E-09 CD55 -1.070912389 1.32E-13 GEM -1.068014009 0.000236276 CECR2 -1.067194084 0.001331875 GM37811 -1.065655387 0.00122256 ZFP36 -1.065106335 1.05E-12 DUSP1 -1.05100995 6.25E-11 GM30292 -1.047008312 0.001008288 IRS2 -1.043354899 3.16E-07 HBA-A2 -1.042529375 8.39E-05 SLC25A23 -1.041967417 7.54E-06 HBB-BS -1.036951957 0.000248255 TET1 -1.035944757 0.000285789 HBB-BT -1.026969464 9.51E-05 PRRT2 -1.011071105 0.000669147 CERS6 -1.009686382 3.13E-05 TOB1 -1.008933656 4.46E-07 IGHD -1.004497214 9.82E-05 GM20518 -1.002087894 0.002512408 SCAND1 1.001369748 0.002539504 EAF2 1.003642029 0.002477922 SH3BP2 1.008766975 5.94E-06 GM20559 1.013158536 4.92E-17 RGS12 1.018507433 0.000596453 MPP4 1.018949259 0.001831878 ICA1 1.024838143 0.001353931 HIP1 1.029539163 6.89E-07 BCL2A1A 1.034434774 0.000710139 GM3164 1.035517446 0.001872974 GM6637 1.038669623 0.000156508 ADGRE1 1.039700291 0.001723903 CP 1.041958608 0.001698374

3

TMEM158 1.04279845 8.42E-05 CHIL3 1.044581948 0.000156244 BC147527 1.047536484 2.42E-05 SOCS1 1.048840236 0.000789071 CASP4 1.049297949 6.17E-06 BASP1 1.05746133 0.001501014 NES 1.05757639 0.000452303 FCNA 1.068582796 0.001082541 EBI3 1.073064945 5.91E-07 SLC52A3 1.074613694 1.65E-06 GM6548 1.079941637 3.09E-07 CYP51 1.082781175 5.66E-08 IGKC 1.083198381 0.000733206 SH3PXD2B 1.087953986 0.001080636 MT-ND3 1.088637219 0.000786208 TCTEX1D2 1.08926198 0.000927467 BSPRY 1.091614041 8.79E-06 HMGN3 1.093532681 2.51E-05 STAT1 1.094043084 1.70E-20 LPCAT2 1.095535467 0.000645603 CD200R4 1.096444242 1.37E-05 5430427O19RIK 1.098073883 0.000707204 GM4841 1.098776209 0.000827399 FKBP11 1.10287262 0.000760344 H2-T24 1.105629551 1.11E-09 4930512H18RIK 1.108047937 0.000724009 BCL2A1B 1.110126289 5.95E-08 GM5970 1.110754461 0.000788536 GM5431 1.110866239 0.000777824 TOR3A 1.113582731 1.13E-13 GNGT2 1.113997466 0.000119205 GM18752 1.114592703 0.000795976 MPO 1.114824206 9.52E-05 RASA4 1.121610185 0.000575146 PHF11C 1.12277566 8.08E-12 CAMP 1.123186311 7.88E-05 GPR55 1.125583986 2.16E-08 RBMS3 1.128988564 0.00025565 TREX1 1.129992747 3.52E-10

4

ABCB1A 1.131277826 1.36E-16 CD63 1.133631118 0.000665654 CASP1 1.135809142 2.54E-07 TRIM30A 1.136887548 3.24E-20 CCR3 1.137533447 2.79E-06 PTAFR 1.139419711 5.59E-05 TMEM67 1.152764987 1.50E-05 PHF11D 1.152877254 4.99E-05 KLRG1 1.156370238 3.05E-13 GRN 1.156994471 0.000241286 GM15135 1.157079313 0.000211861 LDLR 1.159771627 1.07E-07 MAFB 1.167243015 0.000458463 APOBR 1.168616595 4.42E-05 IL1R2 1.173275516 0.00014506 TMCC3 1.174761286 9.20E-05 PON3 1.176099496 2.43E-05 CCRL2 1.187297139 1.95E-08 GM10175 1.187953348 2.99E-09 F830016B08RIK 1.190081222 0.000105571 MS4A7 1.195775093 0.000289061 GM3468 1.196550035 1.03E-05 CLIC4 1.197818519 1.91E-11 HERC6 1.199291097 4.61E-16 ERDR1 1.199785325 0.00030423 GZMA 1.199934318 0.00022304 SEMA7A 1.209890061 0.000208051 PYDC3 1.212671092 2.88E-14 MS4A4C 1.216484615 0.000223092 IGKV1-117 1.221325905 0.00021762 NR4A3 1.227888915 4.29E-10 IGTP 1.234096576 1.14E-31 CXCL11 1.248418621 4.89E-05 HOXB4 1.252410074 3.69E-06 NAMPT 1.252749973 1.59E-22 CD300A 1.26064519 0.000153922 CCL6 1.261792632 9.56E-05 GM26917 1.26385414 0.000108552 AW112010 1.266039911 3.26E-14

5

GM4955 1.271731042 3.13E-20 STAB1 1.281071179 2.40E-06 IFI47 1.282309228 1.86E-29 GM14005 1.286809507 4.65E-05 HAVCR2 1.287290048 6.65E-06 CITED4 1.295169111 8.08E-05 AW011738 1.306109907 5.61E-07 PPA1 1.320178061 2.15E-12 OAS1G 1.328872033 6.64E-05 GM43197 1.336949545 4.50E-11 SLC15A3 1.339568654 2.08E-06 GM12250 1.344169383 6.05E-14 OAS1B 1.347048356 2.30E-14 GBP6 1.353023467 3.13E-37 STAT2 1.354924947 1.24E-20 DLL1 1.378800133 2.31E-05 GM12185 1.38074827 7.18E-09 JCHAIN 1.380878605 1.39E-05 HOXB3 1.383021836 3.24E-05 PYDC4 1.385414901 2.56E-24 TGTP2 1.394913467 3.60E-35 PHF11B 1.40665229 2.04E-28 TRAFD1 1.410275673 1.17E-20 CLEC7A 1.413461174 2.18E-05 GM7609 1.420988286 5.86E-07 IFITM3 1.421733729 1.97E-05 CYBB 1.43884076 1.79E-15 TRIM30D 1.443810351 9.50E-27 A230005M16RIK 1.444853517 1.44E-05 GJB2 1.450925577 5.91E-06 PGAM2 1.459750164 1.03E-05 IGKV1-110 1.460227786 3.78E-06 TNFRSF8 1.464298932 2.29E-07 2310031A07RIK 1.478324191 1.81E-06 PARP9 1.483784389 2.75E-25 CTLA2B 1.4875031 6.37E-06 GM16464 1.489977611 8.97E-07 FGL2 1.491789641 2.09E-38 TDRD7 1.493025722 4.06E-12

6

GM43126 1.494357031 3.34E-06 IRGM1 1.496371348 3.41E-29 GBP6 1.511196014 1.70E-06 CAPN11 1.519456885 2.36E-06 DAXX 1.52137526 2.01E-21 PHF11A 1.532932568 1.68E-21 ASB2 1.536593957 2.46E-06 IFIH1 1.543091248 1.59E-22 TGTP1 1.547998408 9.61E-32 NBEA 1.555243044 3.01E-06 AI607873 1.569320377 2.31E-06 CLEC4A3 1.572916155 2.26E-06 ALOX15 1.598276628 1.10E-06 TRIM30C 1.60348943 1.48E-06 CCR5 1.610138097 1.91E-11 MLKL 1.629821429 1.30E-08 XAF1 1.645732679 7.43E-36 TBX21 1.648506268 2.38E-11 DDX60 1.654399355 1.55E-29 IFIT1BL1 1.669001668 9.40E-33 BC094916 1.684393885 5.76E-26 PLAC8 1.684564995 2.22E-11 LGALS3BP 1.694255968 3.50E-26 RNF213 1.711070519 2.19E-31 GM12338 1.722961279 1.23E-07 H2AFJ 1.730319213 2.54E-16 SERPINA3F 1.738391129 5.76E-10 NKG7 1.740084454 2.05E-11 DHX58 1.756183428 2.45E-28 CD86 1.778766006 3.41E-21 ZBP1 1.783705644 5.92E-37 FCGR4 1.88251529 1.60E-08 GBP10 1.905632856 2.57E-45 ISG20 1.935859627 1.97E-41 SDC3 1.949803332 8.09E-16 APOL9B 1.953308856 9.34E-11 USP18 2.008189107 2.41E-30 CCL5 2.01812883 1.89E-30 LY6A 2.023697966 3.07E-52

7

PARP12 2.030801403 2.54E-32 IIGP1 2.039347672 1.67E-38 CCL4 2.049569457 5.49E-10 IFI27L2A 2.050202143 1.16E-76 OAS1A 2.160719625 1.66E-33 CMPK2 2.19332456 5.27E-33 RTP4 2.193588902 4.17E-40 GM4951 2.212083177 1.50E-16 RSAD2 2.230319355 3.12E-36 BST2 2.274620521 3.44E-69 IRF7 2.33301622 7.37E-45 CXCL10 2.369495039 1.16E-13 OAS3 2.4292666 3.95E-39 OASL1 2.586914015 2.26E-29 IFIT1 2.645642235 4.44E-46 OASL2 2.68690895 4.73E-20 IFIT3 2.693997567 3.02E-20 IFIT3B 2.697812916 5.60E-19 GZMB 2.710077584 9.17E-71 MX2 2.735753401 1.50E-31 MX1 2.7380499 3.01E-22 MNDA 2.884359591 1.81E-25 IFI204 3.051636274 2.89E-27 OAS2 3.275260084 2.34E-53 ISG15 3.282058987 1.43E-83 IFI44 3.437057621 1.78E-43

Supplementary Table 1. Genes up-regulated and down-regulated in Vk*MYC

injected BM Tregs compared to control BM Tregs.

A list of the genes significantly up-regulated and down-regulated in BM Tregs obtained

from Vk*MYC injected mice (n=3) compared to BM Tregs from control mice (n=3).