Blockade of TIGIT/CD155 signaling reverses T-cell ... › content › ...Aug 06, 2019 · Blockade of TIGIT/CD155 signaling reverses T-cell exhaustion and enhances antitumor capability

Blockade of TIGIT/CD155 signaling reverses T-cell exhaustion and enhances

antitumor capability in head and neck squamous cell carcinoma

Lei Wu 1

, Liang Mao 1, Jian-Feng Liu

1, Lei Chen

1,Guang-Tao Yu

1, Lei-Lei Yang

1,

Hao Wu 1, Lin-Lin Bu

1, Ashok B. Kulkarni

3, Wen-Feng Zhang

1, 2 , and Zhi-Jun Sun

1,2,3

1 The State Key Laboratory Breeding Base of Basic Science of Stomatology

(Hubei-MOST) & Key Laboratory of Oral Biomedicine, Ministry of Education,

School and Hospital of Stomatology, Wuhan University, Wuhan 430079, China

2 Department of Oral Maxillofacial-Head Neck Oncology, School and Hospital of

Stomatology, Wuhan University, Wuhan 430079, China

3 Functional Genomics Section, Laboratory of Cell and Developmental Biology,

National Institute of Dental and Craniofacial Research, National Institutes of Health,

Bethesda, MD, 20892, USA.

Running title: Blockade of TIGIT/CD155 signaling in HNSCC

This work was supported by the National Natural Science Foundation of China

(NFSC): 81672668, 81472528, 81472529 and the Fundamental Research Funds for

the Central Universities (2042017kf0171)

on June 7, 2021. © 2019 American Association for Cancer Research. cancerimmunolres.aacrjournals.org Downloaded from

Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on August 6, 2019; DOI: 10.1158/2326-6066.CIR-18-0725

http://cancerimmunolres.aacrjournals.org/

L. Wu and L. Mao contributed equally to this article.

Corresponding Author: Prof. Zhi-Jun Sun, School and Hospital of Stomatology,

Wuhan University, Wuhan, 430079, China.

Tel: +86-27-8768-6336

Fax: +86-27-8787-3260

E-mail: [email protected] (Z.J. S.)

No potential conflicts of interest were disclosed.

Abstract

Immunosuppression is common in head and neck squamous cell carcinoma

(HNSCC). In previous studies, the TIGIT/CD155 pathway was identified as an

immune checkpoint signaling pathway that contributes to the “exhaustion” state of

infiltrating T cells. Here, we sought to explore the clinical significance of

TIGIT/CD155 signaling in HNSCC and identify the therapeutic effect of

TIGIT/CD155 pathway in transgenic mouse model. TIGIT was overexpressed on

tumor-infiltrating CD8+ and CD4

+ T cells in both HNSCC patients and mouse models,

and was correlated with immune checkpoint molecules (PD-1, TIM-3, LAG-3).

TIGIT was also expressed on murine regulatory T cells (Tregs) and correlated with

immune suppression. Using a human HNSCC tissue microarray, we found that

CD155 was expressed in tumor and tumor-infiltrating stromal cells, and also indicated

poor overall survival. Multispectral immunohistochemistry indicated that CD155 was




coexpressed with CD11b or CD11c in tumor-infiltrating stromal cells. Anti-TIGIT

treatment significantly delayed tumor growth in transgenic HNSCC mouse models

and enhanced antitumor immune responses by activating CD8+ T-cell effector

function and reducing the population of Tregs. In vitro coculture studies showed that

anti-TIGIT treatment significantly abrogated the immunosuppressive capacity of

MDSCs, by decreasing Arg1 transcripts, and Tregs, by reducing TGFβ1 secretion. In

vivo depletion studies showed that the therapeutic efficacy by anti-TIGIT mainly

relies on CD8+ T cells and Tregs. Blocking PD-1/PD-L1 signaling increased the

expression of TIGIT on Tregs. These results present a translatable method to improve

antitumor immune responses by targeting TIGIT/CD155 signaling in HNSCC.

Introduction

Immune therapies are considered low toxicity, high affinity, and targeted treatment

options that can harness the activity of the host’s immune system to prevent tumor

escape (1,2). When used as a monotherapy or in combination with standard therapies,

immune therapies have been demonstrated to be an effective therapeutic approach in

multiple advanced cancers, including head and neck squamous cell carcinoma

(HNSCC) (3-6). HNSCC accounts for 3 to 5 % of all cancers (7), with the common

features of tumor-mediated immunosuppression and high mutational burden (8).

HNSCC has been shown to develop multiple immune escape mechanisms, attributed

to these characteristics (8). Preclinical studies, clinical trials, and our previous work

have suggested that immunosuppressive cells contribute to the poor survival of

HNSCC patients, whereby immune therapies (such as immune checkpoint blockades,




adoptive cell therapies, and neoantigen-targeting vaccines) can improve clinical

outcomes by reversing the immunosuppressive state (9-13). However, the limited

efficacy of some immune therapies indicates that new applicable immune checkpoints

and therapeutic strategies need to be investigated to overcome the pervasive immune

suppression in HNSCC (14).

T-cell immunoglobulin and ITIM domain (TIGIT), which is also known as Vstm3

and VSIG9, is an immunoglobulin superfamily member (15). TIGIT is expressed

restrictedly on subsets of activated T cells and natural killer (NK) cells, and interacts

with CD155 to induce immunosuppression (16). However, the expression profile and

immunological effect of TIGIT/CD155 signaling in HNSCC are poorly characterized.

Analogous to the B7/CD28/CTLA-4 pathway, which contains both costimulatory and

coinhibitory receptors, TIGIT competes with CD226 (also known as DNAM-1) to

bind CD155 with a high affinity (15). Multiple groups have shown that the genetic

knockout or antibody ablation of TIGIT-enhanced NK cell killing and augmented

CD8+ T-cell activity against tumors (17-20). In addition, TIGIT

+ regulatory T cells

(Tregs) may display a stronger immunosuppressive activity than TIGIT– Tregs (21). It

was reported that CD155 was highly expressed in multiple tumor cells and

tumor-associated myeloid cells (22-24), and that TIGIT/CD155 signaling may

contribute to the potential suppression of conventional NK cells by Myeloid-derived

suppressor cells (MDSCs) (25). Thus, blocking TIGIT/CD155 signaling might

provide a promising complement to current immune checkpoint–based antitumor

immunotherapies for clinical intervention.




In this study, we investigated the expression and function of TIGIT+ T cells and

CD155+ myeloid cells in HNSCC patients and mouse models. We observed an

elevated number of TIGIT+ T cells in HNSCC compared to healthy controls, as well

as an increase in CD155-expressing tumor cells and myeloid cells. We also provide

evidence that blocking TIGIT/CD155 signaling promoted antitumor immunity, aided

in immune homeostasis, and reduced the tumor burden in mouse models by an in vivo

TIGIT mAb administration. Our data demonstrate that TIGIT/CD155 signaling is a

potential immunotherapeutic target for HNSCC.

Materials and Methods

Mice

Six- to 8-week-old male Tgfbr1/Pten 2cKO mice were used in this study. The time

inducible tissue-specific Tgfbr1/Pten double-knockout mice (K14-CreERtam+/–

;

Tgfbr1flox/flox

; Ptenflox/flox

, Tgfbr1/Pten 2cKO) were maintained and genotyped

according to previously published protocols (26). All animal studies were carried out

in accordance with the NIH guidelines for the use of laboratory animals in a

pathogen-free ASBL3 animal center at Wuhan University. All mouse procedures were

approved by the Animal Care and Use Committee of Wuhan University

(2014LUNSHENZI06 and 2016LUNSHENZI62). The tamoxifen treatment was

performed as previously described (27). All the mice had a mixed background of

FVBN/CD1/129/C57BL/6J.




Human samples

Study cohort 1. A retrospective series of 210 primary HNSCC cases, 35 HNSCC

cases with lymph node metastasis, 68 oral epithelial dysplasia (DYS) cases and 42

normal oral mucosa (MUC) cases was obtained from the Hospital of Stomatology,

Wuhan University. All the included HNSCC patients underwent primary surgery

(without preoperative adjuvant chemotherapy or radiotherapy) between 2011 and

2016. The specimens were used to generate human HNSCC tissue microarrays.

Additionally, 201 primary HNSCC cases were included in the survival analysis due to

9 patients lost to follow-up.

Study cohort 2. A prospective series of the whole blood of 16 primary HNSCC cases

was obtained from the Hospital of Stomatology, Wuhan University. Additionally, 12

matched fresh surgically resected tumor tissues were obtained to isolate

tumor-infiltrating T cells (TILs). All the included HNSCC patients underwent primary

surgery (without preoperative adjuvant chemotherapy or radiotherapy) from October

2017 to March 2019. The whole blood of 10 healthy donors was used as a normal

control.

Informed consent was obtained for all the patients and the study was approved by

the Institutional Medical Ethics Committee of School and Hospital of Stomatology,

Wuhan University (2014LUNSHENZI06，2016LUNSHENZI62) and was conducted

in agreement with the Helsinki Declaration. The pathological diagnosis was made by

two independent pathologists of the Department of Oral Pathology, Wuhan

University.




Immunohistochemistry

IHC was performed as previously (28). Briefly, the sections of HNSCC tissue

microarray were deparaffinized, rehydrated, and subjected to antigen retrieval by

sodium citrate (pH 6.0), followed by blocking endogenous peroxidase. Then the

sections were incubated with CD155 antibody (1:200; Cell Signaling Technology)

overnight. On the second day, the sections were incubated with secondary antibodies

and stained with ABC kits (Vector). The slides were scanned with Aperio ScanScope

CS scanner (Vista, CA, USA) and analyzed by Aperio ScanScope quantification

software (Version 9.1). The detailed quantification procedures were performed as

before (28).

Multispectral IHC, imaging and analysis

Multispectral IHC was performed on formalin-fixed paraffin embedded (FFPE)

HNSCC samples with PerkinElmer Tyramide Plus (Opal) reagents according to Opal

serial immunostaining manual. Briefly, paraffin sections were first deparaffinized and

rehydrated. After antigen retrieval with AR buffer (pH = 6.0; PerkinElmer), the

sections were covered with blocking buffer (PerkinElmer) for 20 minutes at room

temperature, and then were incubated with a primary antibody, followed by the

horseradish peroxidase–conjugated secondary antibody (PerkinElmer). Sections were

washed three times for 2 minutes each in 0.02% Tris-buffered saline–Tween 20

(TBST) followed by signal generation using 100 µl of Opal Fluorophore Working




Solution (PerkinElmer) per slide at a dilution of 1:100 in 1× amplification diluent,

incubated at room temperature for 10 minutes as specified by the manual

(PerkinElmer). Opal 520 Fluorophore, Opal 540 Fluorophore, Opal 620 Fluorophore,

Opal 650 Fluorophore, and Opal 690 Fluorophore (all from PerkinElmer) were

applied to each antibody. Multispectral images were acquired by PerkinElmer Vectra

platform at ×20 magnification. The following primary antibodies were used in this

panel: CD155 (1:200; Cell Signaling Technology), CD11c (1:1000; Cell Signaling

Technology), CD11b (1:400; Cell Signaling Technology), Pan-CK (1:2000; Cell

Signaling Technology), PD-L1(1:1000; Cell Signaling Technology), and DAPI

(PerkinElmer).

In vivo treatments

After 5 consecutive days of tamoxifen administration, all the Tgfbr1/Pten 2cKO

mice were randomized into a treatment group, which was treated with TIGIT mAbs

(10 mg/kg; BE0274; Bio X Cell), and a control group which was treated with IgG1

isotype antibody (10 mg/kg; BE0083; Bio X Cell) by intraperitoneal injection three

times a week from day 12 to day 40. Tumors were measured by micrometer caliper,

and photos were taken every other day. Mice were euthanized on day 40, and tissues

were harvested for flow cytometry and functional analysis.

For the in vivo T cell, Treg, or MDSC depletion, mice received CD4 (200μg;

BE0003-1; Bio X Cell), CD8 (200μg; BE0004-1; Bio X Cell), CD25 (250μg; BE0012;

Bio X Cell), or Gr-1 (500μg; BE0075; Bio X Cell) targeting antibodies on the day




before tamoxifen administration and on day 4 of tamoxifen administration . On day 5,

the blood or lymph nodes were obtained to verify the depletion efficiency by flow

cytometry.

For the in vivo PD-1 antibody treatment, all Tgfbr1/Pten 2cKO mice harboring

tumors were randomized into a group treated with PD-1 mAb (10mg/kg; BE0146; Bio

X Cell), and a control group treated with IgG2a isotype control (10mg/kg; BE0089;

Bio X Cell) by intraperitoneal injection three times a week during day 12 to day 40.

Mice were euthanized on day 40, and tissues were harvested for flow cytometry and

functional analysis.

PBMC separation

Peripheral blood mononuclear cells (PBMCs) were separated from the whole blood

samples of patients and healthy donors with LymphoprepTM

(STEMCELL

Technologies) and used for flow cytometry analysis. Briefly, blood was diluted with

an equal amount of Dulbecco’s Phosphate-Buffered Saline with 2% Fetal Bovine

Serum and was layered on top of Lymphoprep™. Then, the sample was centrifuged at

800 x g for 20 minutes at room temperature and mononuclear cell layer was retained.

Isolation of tumor-infiltrating lymphocytes (TILs)

Tumor tissues were harvested and manually minced into small pieces (smaller than

2 mm), digested in RPMI medium containing collagenase D at 1 mg/ml (Roche),

hyaluronidase at 0.1 mg/ml (Sigma-Aldrich), and DNases at 0.2 mg/ml




(Sigma-Aldrich) for 2 hours at 37℃, and were then filtered with 70 μm cell strainers

(Becton & Dickinson). The filtered cells were collected and separated with

LymphoprepTM

(STEMCELL Technologies). Then the TILs were collected and stored

in liquid nitrogen until flow cytometry analysis.

Flow cytometry

The following human antibodies were used for staining: CD45- APC-eFluor 780

(HI30), CD3-Alexa Fluor 700 (UCHTI), CD4-FITC (OKT4), CD8-PE-Cy7 (SK1),

TIGIT-PE (MPSA43), purchased from eBioscience and PD-1-Alexa Fluor 700

(EH12.2H7), purchased from BioLegend.

For the TILs, splenocytes and lymph node cells of mice were pre-incubated with

purified anti-mouse CD16/CD32 (eBioscience) before membrane staining. The

following mouse antibodies were used for membrane staining: CD3-FITC (17A2),

purchased from BD Biosciences; CD8-PerCP-Cy5.5 (53-6.7), TIGIT-APC (1G9),

TIM3-PE (8B.2C12), LAG3-BV421 (C9B7W), Ly6G-PE (1A8), Ly6C- PE-Cy7

(HK1.4), CD11b-FITC (M1/70), Gr-1-APC (RB6-8C5), purchased from BioLegend;

CD4-PE-Cy7 (GK1.5), PD-1-PE (RMP1-30), CD155-APC (TX56), purchased from

eBioscience.

For regulatory T-cell staining, Mouse Regulatory T-cell Staining Kit #3

(eBioscience) was used. Cells were first stained with CD4-FITC (RM4-5) and

CD25-PE (PC61.5) surface marker antibodies, fixed with fixation/permeabilization




buffer, and stained with anti-Foxp3-PerCP-Cy5.5 (FJK-16s) in 1X permeabilization

buffer.

For mouse intracellular cytokine staining, the TILs were first stimulated with Cell

Activation Cocktail with Brefeldin A (BioLegend) in vitro for 6 hours. The cells were

collected for CD8-PerCP-Cy5.5 (53-6.7), and CD4-PE-Cy7 (GK1.5) staining, fixed

with fixation buffer (BioLegend), and permeabilized with 1X intracellular staining

permeabilization wash buffer (BioLegend). Fixed cells were stained with IFNγ-PE

(XMG1.2), IL2-PE (JES6-5H4), and TNFα-APC (MP6-XT22), which were purchased

from BioLegend.

All samples were analyzed on a CytoFLEX flow cytometer (BECKMAN

COULTER), and data were analyzed using CytoExpert software (BECKMAN

COULTER). Dead cells were excluded based on Fixable Viability Dye-eFluor 506

(eBioscience).

Cell isolation

For mouse MDSC isolation, a mouse Myeloid-Derived Suppressor Cell Isolation

Kit (Miltenyi Biotec) was used to enrich Gr-1high

Ly6G+ cells and Gr-1

dimLy6G

- cells

from the TILs or splenocytes of the anti-TIGIT treatment and control groups. Then,

the CD11b+Ly6G

+Ly6C

lo PMN-MDSCs were sorted from Gr-1

highLy6G

+ cells, and

CD11b+Ly6G

-Ly6C

hi M-MDSCs were sorted from Gr-1

dimLy6G

- cells by flow

cytometry. Flow cytometry cell sorting was performed on a Moflo XDP (BECKMAN

COULTER).




For mouse Treg isolation, the CD4+CD25

hi Tregs were sorted from lymph node

cells or TILs of mice with an EasySep™ Mouse CD4+CD25+ Regulatory T-cell

Isolation Kit (STEMCELL Technologies). Foxp3 staining was performed to analyze

the purity. Cells of over 90% purity could be used for the next step.

For mouse CD8+ T-cell isolation, CD8

+ T cells were sorted from the lymph node

cells of wildtype mouse with a CD8α+ T-cell isolation Kit (Miltenyi Biotec). The

purity was analyzed by flow cytometry.

Coculture assays

The sorted CD8+ T cells were labeled with CFSE and stimulated with 5 μg/ml

anti-CD3, 2.5 μg/ml anti-CD28, and 20 ng/ml rIL2 (BD PharmingenTM

). Then, the

activated T cells (1 x 105/well) were cocultured with sorted PMN-MDSCs, M-MDSCs,

and Tregs, respectively, at different concentration gradients in 96-well round-bottom

plates. After 72 hours, the cells were collected for CFSE dilution analysis by flow

cytometry. Dead cells were excluded based on Fixable Viability Dye-eFluor 506

staining.

Apoptosis assays

The sorted PMN-MDSCs, M-MDSCs, and Tregs (1 x 105/well) from the control

group were cultured in RPMI with 10% FBS, 5 mM glutamine, 25 mM HEPES, and 1%

antibiotics (Invitrogen). Recombinant GM-CSF (Invitrogen) was added to the media

of PMN-MDSCs and M-MDSCs at 10 ng/ml. Then, the TIGIT mAb (10 μg/ml) or




isotype control antibody (10 μg/ml) was administered. After 20 hours, the cells were

assessed and analyzed by flow cytometry. Annexin V-FITC/PI staining was

performed in staining buffer (BD Biosciences) according to the manufacturer’s

protocol.

Enzyme-linked immunosorbent assay (ELISA)

The sorted Tregs (2 x 105/well) from the control group were cultured in RPMI with

10% FBS, 5 mM glutamine, 25 mM HEPES, and 1% antibiotics (Invitrogen). Then,

the TIGIT mAb (10 or 20 μg/ml) or isotype control antibody (10 μg/ml) was

administered respectively. After 48 hours, the supernatants were harvested, and the

concentrations of TGFβ1 were detected with an ELISA Kit (Neobioscience)

according to the manufacturer’s protocol. Briefly, appropriately diluted samples were

added to each well with precoated capture antibody. Then, diluted detection antibody

and conjugated secondary antibody were added to each well successively. After that,

the substrate solution was dispensed to per well. Finally, the absorbance was recorded

at 450 nm on a plate reader.

Real Time-PCR

Total RNA of MDSCs were extracted by the RNeasy Mini Kit (Qiagen). The

cDNA was synthesized by PrimeScriptTM

RT reagent Kit (TaKaRa). The target genes

of samples were analyzed by CFX Connect™ Real-Time PCR Detection System. The

following primers were used: β-actin-F: 5’-GTGACGTTGACATCCGTAAAGA-3’,




β-actin-R: 5’-GCCGGACTCATCGTACTCC-3’; ARG1-F:

5’-TTGGGTGGATG-CTCACACTG-3’, ARG1-R:

5’-GTACACGATGTCTTTGGCAGA-3’. The expression of arginase-I (ARG1) was

calculated by the 2-∆∆ct method and β-actin was used as a normalized control.

Statistical analysis

GraphPad Prism 7.0 for windows (GraphPad Software, Inc., La Jolla, CA) was

used to conduct statistical analyses. Data analyses were conducted by the unpaired (or

paired where specified) Student t test for two-group comparisons or by one-way

analysis of variance (ANOVA) for multiple group comparisons. All values are

presented as the mean ± SD. P < 0.05 considered statistical significance. The Kaplan–

Meier method followed by long-rank test was used to analyze the overall survival of

patients with HNSCC and the significance of observed differences was assessed by

log-rank test.

Results

High expression of TIGIT on tumor-infiltrating T cells

TIGIT expression has been shown to be increased on T cells in multiple types of

malignant tumors (17,18). To confirm that TIGIT was expressed in HNSCC, we

performed flow cytometry to assess the surface expression of TIGIT within human

PBMCs and HNSCC tissues. We found that TIGIT expression on HNSCC patient

PBMCs was higher than that on CD4+

and CD8+ T cells from healthy donor PBMCs




(Fig. 1A and B). Furthermore, TIGIT was expressed by a large percentage of

HNSCC-infiltrating CD4+

and CD8+ T cells, and the expression was significantly

higher than those on the matched PBMC (Fig. 1A and B). The coexpression of

immune checkpoint molecules may drive T lymphocyte exhaustion (29,30). Therefore,

we examined the expression of TIGIT with coinhibitory receptor PD-1 in human

PBMCs and HNSCC tissues. We observed that TIGIT was coexpressed with PD-1 on

CD4+

and CD8+

T cells from human PBMC and TILs. We found that the coexpression

of TIGIT and PD-1 on TILs was higher than that on PBMCs (Fig. 1C). Considering

these data from human HNSCC, we investigated TIGIT expression in a Tgfbr1/Pten

2cKO HNSCC mouse model. Analogously, TIGIT was expressed on 23.96% of CD4+

TILs and 50.15% of CD8+ TILs, which was significantly higher than that in the spleen

in WT and in tumor-bearing mice (Fig. 2A and B). Moreover, we found that the

coexpression of TIGIT/PD-1, TIGIT/TIM-3, and TIGIT/LAG-3 was upregulated on

CD4+ and CD8

+ TILs in the mouse model compared to that in the spleen (Fig. 2C and

D; Supplementary Fig. S1). These data indicated that TIGIT was highly expressed by

HNSCC TILs and correlated with expression of other immune checkpoint molecules,

especially PD-1.

It was reported that TIGIT predominantly regulates the function of regulatory T

cells (31). Thus, we then characterized TIGIT expression on Tregs in our HNSCC

mouse model. We found that CD4+CD25

+Foxp3

+ Tregs from tumor-bearing mice

expressed more TIGIT than that in WT mice (Fig. 3A and B). We observed that the

CD25hi or med

Foxp3+ subset expressed the majority of TIGIT among the CD4

+ T cells,




compared with the CD25–Foxp3

– subset and CD25

medFoxp3

– subset (Fig. 3A and B).

Suppression assays indicated that Tregs sorted from tumor-bearing mice showed an

increased ability to suppress the proliferation of CD8+ T cells that were activated by

CD3/CD28 antibodies compared with that from WT mice (Fig. 3C and D;

Supplementary Fig. S2). These results suggested that TIGIT might act as a negative

immune checkpoint to generate an exhausted phenotype in HNSCC.

High expression of CD155 in patients and in a mouse model

TIGIT might transduce negative signals to effector T cells by binding to their

inhibitory receptors, such as CD155 (16). Thus, we assessed the expression and

functional consequences of CD155 in HNSCC. First, using the TCGA database via

GEPIA (32), we found that the CD155(PVR) mRNA expression in HNSCC tissues

was significantly higher than that in normal tissues (Supplementary Fig. S3A).

Survival analysis indicated that HNSCC patients with high CD155 expression

demonstrated a worse overall survival than that of patients without CD155 expression

(Supplementary Fig. S3B). We detected constitutive expression of CD155 on the

epithelial and interstitial cells of human HNSCC tissue (Fig. 4A - C). High CD155

expression on the malignant cells or stromal cells of HNSCC patients was associated

with poor survival (Fig. 4B and C). Furthermore, higher expression of CD155 in

epithelial cells was correlated with the pathologic grade (Fig. 4D; Supplementary Fig.

S4A) and lymph node metastasis (Fig. 4E). However, there was no significant

difference in CD155 expression between tumors of different sizes (Supplementary Fig.




S4B), and no significance difference in CD155 expression was observed between

patient HNSCC tissue and the matched metastatic lymph nodes (Supplementary Fig.

S4C). To investigate further, multiplexed IHC analysis showed that CD155 (green)

was highly expressed in Pan-CK+ (red) HNSCC (Fig. 4F). We also found that CD155

was coexpressed with myeloid cell markers, such as CD11b (yellow) and CD11c

(pink), at the invasive front (Fig. 4F). We observed that CD155 and PD-L1

coexpressed on CD11b+ myeloid cells (Supplementary Fig. S5). Based on the CD155

expression profiles in patient tissues, we observed that CD155 was similarly

overexpressed on CD11b+Ly6G

+Ly6C

lo PMN-MDSCs and CD11b

+Ly6G

-Ly6C

hi

M-MDSCs in the tumor-bearing Tgfbr1/Pten 2cKO HNSCC mouse model compared

with that in the bone marrow and MDSCs of WT mice (Fig. 4G and H;

Supplementary Fig. S6A). In our previous work, we verified that these two subsets of

MDSCs in tumor-bearing mice had immunosuppressive activity (28). To further

confirm this observation, we sorted these cells to detect their capacity to produce

arginase-1(Arg-1). Higher expression of arginase-1 was found in the PMN-MDSCs

and M-MDSCs in the tumor-bearing mice, whereas this gene was lowly expressed in

the MDSCs of WT mice (Fig. 4I; Supplementary Fig. S6B). These data confirmed the

high prevalence of CD155 in human and mouse HNSCC and suggested that CD155

may correlate with an immunosuppressive function in HNSCC. Thus, we

hypothesized that blocking TIGIT/CD155 signaling may activate antitumor immunity

in HNSCC.




Blocking TIGIT/CD155 signaling inhibits tumor progression

To test our hypothesis, tumor-bearing HNSCC mice were subjected to in vivo

TIGIT/CD155 blockade by treatment with a TIGIT mAb. Tgfbr1/Pten 2cKO mice

were administered five consecutive days of tamoxifen. When the papilloma had

formed, the mice were intraperitoneally injected with a TIGIT mAb (Fig. 5A). The

results indicate that blocking TIGIT led to a significant delay in tumor progression

compared to that of the control (Fig. 5B ). We did not observe significant differences

between the anti-TIGIT treatment group and control group in liver and kidney using

H&E staining (Supplementary Fig. S7A), indicating that there was no detectable

cytotoxicity in our mouse model upon anti-TIGIT treatment, which was consistent

with previous study (33). We also observed a lower frequency of Tregs infiltrating in

the peripheral immune organs, local circulation, and the tumor microenvironment

(TME) after treatment compared to those in the controls (Fig. 5C). A higher

frequency of tumor-infiltrating CD8+ T cells expressing IL2/TNFα/IFNγ and CD4

+ T

cells expressing IL2 were also observed after TIGIT mAb treatment relative to those

in the control mice (Fig. 5D). However, treatment with a TIGIT mAb did not reduce

tumor-infiltrating MDSCs frequencies (Supplementary Fig. S7B). These data

suggested that blocking TIGIT/CD155 signaling alleviated CTL exhaustion and

delayed tumor growth in HNSCC mouse models.

Blocking TIGIT/CD155 signaling decreases suppression by Tregs and MDSCs



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To determine the potential mechanism of the TIGIT/CD155 signaling blockade, we

selectively sorted MDSCs and Tregs from Tgfbr1/Pten 2cKO mice for in vitro

investigations. Coculture assays indicated that the immunosuppressive activity of

MDSCs was abrogated by in vivo TIGIT mAb treatment (Fig. 6A). In addition, Arg-1

transcripts were also decreased by anti-TIGIT treatment compared to those in the

controls (Fig. 6B). Consistent with the in vivo data, anti-TIGIT treatment in vitro did

not induce apoptosis in MDSCs (Fig. 6C). These data suggested that blocking

TIGIT/CD155 may partially regulate the immunosuppression of MDSCs by reducing

Arg-1 production.

Then, CD4+CD25

+Foxp3

+ Tregs that were isolated from the spleens of TIGIT or

isotype antibody–treated mice were cocultured with CD8+ effector T cells. The results

indicated that the anti-TIGIT treatment decreased the suppressive function of Tregs

compared to that in the controls (Fig. 6D). The in vitro analysis revealed that the

anti-TIGIT treatment did not induce the apoptosis of Tregs (Fig. 6E), but the

treatment reduced the secretion of TGFβ1 in cell supernatants from Tregs compared

to that in the controls (Fig. 6F). Overall, these data suggested that blocking

TIGIT/CD155 signaling may partially regulate the immunosuppression of Tregs by

downregulating TGFβ1 secretion.

Anti-TIGIT therapeutic efficacy is mainly dependent on CD8+ T cells and Tregs

As the anti-TIGIT treatment may partially influence the function of CD4+ T cells,

CD8+ T cells, MDSCs, and Tregs, we determined whether the effect of anti-TIGIT




was mainly dependent on one of these cell populations. Next, tumor-bearing HNSCC

mice were subjected to in vivo depletion of CD4+ T cells, CD8

+ T cells, MDSCs, or

Tregs by depleting antibodies before the blockade of TIGIT antibody. Using depleting

antibodies, we found that antitumor effects in tumor-bearing HNSCC mice were

abrogated when CD8+ T cells, but not CD4

+ T cells, were depleted (Fig. 7A).

Moreover, we found that when depleting CD25+ Tregs, there were no differences in

the antitumor effects between the anti-CD25 alone and the combination of anti-CD25

and anti-TIGIT. However, the tumor growth was slower with the combination of

anti-Gr1 and anti-TIGIT than that with anti-Gr1 alone (Fig. 7B). These results

indicated that the therapeutic efficacy by anti-TIGIT mainly relies on CD8+ T cells

and Tregs.

Blocking PD-1/PD-L1 signaling increases the expression of TIGIT on Tregs.

Our data showed that PD-1 was coexpressed with TIGIT on human and mouse

TILs. We therefore examined the expression of TIGIT on CD4+

T cells, CD8+ T cells,

and Tregs after blocking PD-1/PD-L1 signaling to investigate whether there is a

possible rationale to combine the TIGIT and PD-1 treatment in HNSCC. The results

showed that blockade of PD-1 increased the expression of TIGIT on Tregs compared

with the isotype (Fig. 7C). However, there were no differences on the expression of

TIGIT on CD8+ T cells between anti–PD-1 treatment group and the control group

(Supplementary Fig. S8D). Collectively, these data indicated that blocking PD-1 and

TIGIT corporately may elicit better antitumor effects.




Discussion

Cancer immunotherapy with immune checkpoint blockade has been one of the

most successful strategies for cancer therapy (34). Although blocking PD-1, PD-L1,

and CTLA-4 have shown to generate antitumor immunity and durable responses, drug

resistance still occurs in some patients (14,35), emphasizing the need for

supplementary strategies. TIGIT is an inhibitory checkpoint receptor that has been

demonstrated to have immunosuppressive effects on antitumor immunity in several

solid tumors and in leukemia (15,17,20). The coexpression of TIGIT and other

immune checkpoints can lead to an exhausted phenotype in cytotoxic lymphocytes

(29). TIGIT+ Tregs are believed to be a distinct Treg subset capable of strong

suppression (21). However, direct evidence suggesting a clinical role for TIGIT in

HNSCC patients has not been presented. In this study, we found that TIGIT was

highly expressed by both human and mouse tumor-infiltrating CD4+ and CD8

+ T cells,

and was related to several key T-cell checkpoints. In addition, we also demonstrated

that TIGIT was more highly expressed on Foxp3+ Tregs than that on Foxp3

– CD4

+ T

cells in our HNSCC mouse model, which could be associated with the high amount of

suppression on CD8+ T-cell proliferation. CD155 is a ligand of TIGIT that interacts

with TIGIT with high affinity. The loss of both host- and tumor-derived CD155 leads

to decreased tumor growth and metastasis and increased response to immunotherapy

(22). Here, we showed that CD155 was widely expressed in the TME of HNSCC

patients, and the overexpression of CD155 in both cancer cells or in tumor-infiltrating




stromal cells could predict poor overall survival. The overexpression of CD155 was

also associated with pathological grade and lymph node metastasis, which indicated

that the assessment of CD155 expression could be used as an approach to predict the

prognostic outcomes of HNSCC patients. These results were consistent with several

previous studies in other types of malignant tumors (20,36,37). In addition, high

CD155 expression on tumor-infiltrating myeloid cells was observed in human and

murine HNSCC. In these studies, the blockade of TIGIT/CD155 signaling enhanced

the antitumor CTL responses and downregulated the immunosuppressive function of

Tregs and MDSCs by decreasing the production of suppressive cytokines. To our

knowledge, this is the first evidence regarding the role of TIGIT/CD155 signaling in

HNSCC pathogenesis and immunotherapy.

Current studies have shown that the depletion of CD8+ CTLs or the absence of NK

cells might abrogate the therapeutic effects of anti-TIGIT blockade (17,19). However,

the contribution of tumor-infiltrating immunosuppressive cells was not been studied

in these investigations. Two previous studies indicated that the expression of PD-L1

on host DCs and macrophages may predict the clinical therapeutic efficacy of

PD-L1/PD-1 blockade (38,39). These data provide evidence that the interaction

between CTLs and tumor-associated stromal cells may play an essential role in

immune checkpoint inhibition. In line with our previous work, CD4+CD25

+Foxp3

+

Tregs, CD11b+Ly6G

+Ly6C

lo PMN-MDSCs, and CD11b

+Ly6G

–Ly6C

hi M-MDSCs

are the major immune suppressive cells in the Tgfbr1/Pten 2cKO mouse model

(28,40). In this work, a decrease in the suppressive function of Tregs and MDSCs was




observed in an HNSCC mouse model by blocking TIGIT, which indicates that CD8+

CTL exhaustion was reversed as a result of the reduction of the immunosuppression

of the TME. In pathologic conditions, MDSCs highly express multiple

anti-inflammatory cytokines and immunosuppressive factors, inhibiting adaptive

immunity and supporting tumor progression (41). In a mouse model, rapid tumor

growth and inflammatory infiltrates can result in expansion of the MDCS populations

(42). Although the blockade of TIGIT did not induce apoptosis or decrease the

MDSCs in this study, the downregulation of ARG1 transcripts were observed in the

mouse model. These data indicated that TIGIT mAbs may not directly affect the

expansion of MDSCs in the HNSCC TME, but may reduce immunosuppression by

inhibiting ARG1 production. The complete mechanism needs to be further

investigated. In addition, Tregs are recruited into the TME early and play a prominent

role in the regulation of the immune response to tumors via cytokine production or

surface molecule interactions (43,44). Previous studies also revealed that apoptotic

Tregs could mediate enhanced immunosuppression via the adenosine pathways (45).

In this study, we found that TIGIT mAbs did not directly affect the apoptosis of Tregs

in vitro but could downregulate the secretion of typical suppressive cytokine TGFβ1.

Paradoxically, we also observed that the blockade of TIGIT/CD155 signaling in vivo

could significantly decrease the Treg population in our mouse model. These results

may be explained by previous studies, which showed that TIGIT-deficient T cells

generate less TGFβ-mediated Treg differentiation (21), but the exact mechanism

needs to be further studied.




In summary, TIGIT/CD155 signaling was enhanced in HNSCC patients and in

mouse models and was correlated with immunosuppression. Targeting TIGIT/CD155

signaling may be a potential therapeutic strategy for HNSCC treatment.

Disclosure of Potential Conflicts of Interest

No potential conflicts of interest were disclosed.

Authors' Contributions

Conception and design: L. Wu, L. Mao, Z. Sun

Development of methodology: L. Wu, L. Mao, Z. Sun

Acquisition of data (provided animals, acquired and managed patients, provided

facilities, etc.): L. Wu, L. Mao, J. Liu, L. Chen, G. Yu, L. Yang, H. Wu, Z. Sun

Analysis and interpretation of data (e.g., statistical analysis, biostatistics,

computational analysis): L. Wu, L. Mao, J. Liu, L. Chen, G. Yu, L. Yang, H. Wu, L.

Bu, Z. Sun

Writing, review, and/or revision of the manuscript: L. Wu, L. Mao, AB. Kulkarni,

Z. Sun

Administrative, technical, or material support (i.e., reporting or organizing data,

constructing databases): AB. Kulkarni, W. Zhang, Z. Sun

Study supervision: W. Zhang, Z. Sun

Acknowledgments




This work was supported by the National Natural Science Foundation of China

(NFSC): 81672668, 81472528, 81472529 and the Fundamental Research Funds for

the Central Universities (2042017kf0171).

We are grateful to Prof. Ashok B. Kulkarni for kindly proof editing. And we also

want to thank Shu-Yan Liang and Yin Liu from Wuhan Institute of Biotechnology

and Ya-Zhen Zhu from Tongji Hospital for their excellent technical assistance on

flow cytometry and cells isolation.

1. Ribas A, Wolchok JD. Cancer immunotherapy using checkpoint blockade. Science

2018;359(6382):1350-5 doi 10.1126/science.aar4060.

2. Postow MA, Callahan MK, Wolchok JD. Immune Checkpoint Blockade in Cancer Therapy. J Clin

Oncol 2015;33(17):1974-82 doi 10.1200/JCO.2014.59.4358.

3. Larkin J, Chiarion-Sileni V, Gonzalez R, Grob JJ, Cowey CL, Lao CD, et al. Combined Nivolumab

and Ipilimumab or Monotherapy in Untreated Melanoma. N Engl J Med 2015;373(1):23-34

doi 10.1056/NEJMoa1504030.

4. Jie HB, Srivastava RM, Argiris A, Bauman JE, Kane LP, Ferris RL. Increased PD-1(+) and TIM-3(+)

TILs during Cetuximab Therapy Inversely Correlate with Response in Head and Neck Cancer

Patients. Cancer Immunol Res 2017;5(5):408-16 doi 10.1158/2326-6066.CIR-16-0333.

5. Kalos M, June CH. Adoptive T cell transfer for cancer immunotherapy in the era of synthetic

biology. Immunity 2013;39(1):49-60 doi 10.1016/j.immuni.2013.07.002.

6. Schoenfeld JD. Immunity in head and neck cancer. Cancer Immunol Res 2015;3(1):12-7 doi

10.1158/2326-6066.CIR-14-0205.

7. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin 2018;68(1):7-30 doi

10.3322/caac.21442.

8. Whiteside TL. Head and Neck Carcinoma Immunotherapy: Facts and Hopes. Clin Cancer Res

2018;24(1):6-13 doi 10.1158/1078-0432.CCR-17-1261.

9. Shayan G, Kansy BA, Gibson SP, Srivastava RM, Bryan JK, Bauman JE, et al. Phase Ib Study of

Immune Biomarker Modulation with Neoadjuvant Cetuximab and TLR8 Stimulation in Head

and Neck Cancer to Overcome Suppressive Myeloid Signals. Clin Cancer Res 2018;24(1):62-72

doi 10.1158/1078-0432.CCR-17-0357.

10. Chow LQM, Haddad R, Gupta S, Mahipal A, Mehra R, Tahara M, et al. Antitumor Activity of

Pembrolizumab in Biomarker-Unselected Patients With Recurrent and/or Metastatic Head

and Neck Squamous Cell Carcinoma: Results From the Phase Ib KEYNOTE-012 Expansion

Cohort. J Clin Oncol 2016;34(32):3838-45 doi 10.1200/JCO.2016.68.1478.

11. Yu GT, Bu LL, Zhao YY, Mao L, Deng WW, Wu TF, et al. CTLA4 blockade reduces immature

myeloid cells in head and neck squamous cell carcinoma. Oncoimmunology




2016;5(6):e1151594 doi 10.1080/2162402X.2016.1151594.

12. Yu GT, Bu LL, Huang CF, Zhang WF, Chen WJ, Gutkind JS, et al. PD-1 blockade attenuates

immunosuppressive myeloid cells due to inhibition of CD47/SIRPalpha axis in HPV negative

head and neck squamous cell carcinoma. Oncotarget 2015;6(39):42067-80 doi

10.18632/oncotarget.5955.

13. Tran L, Allen CT, Xiao R, Moore E, Davis R, Park SJ, et al. Cisplatin Alters Antitumor Immunity

and Synergizes with PD-1/PD-L1 Inhibition in Head and Neck Squamous Cell Carcinoma.

Cancer Immunol Res 2017;5(12):1141-51 doi 10.1158/2326-6066.CIR-17-0235.

14. Restifo NP, Smyth MJ, Snyder A. Acquired resistance to immunotherapy and future challenges.

Nat Rev Cancer 2016;16(2):121-6 doi 10.1038/nrc.2016.2.

15. Yu X, Harden K, Gonzalez LC, Francesco M, Chiang E, Irving B, et al. The surface protein TIGIT

suppresses T cell activation by promoting the generation of mature immunoregulatory

dendritic cells. Nat Immunol 2009;10(1):48-57 doi 10.1038/ni.1674.

16. Manieri NA, Chiang EY, Grogan JL. TIGIT: A Key Inhibitor of the Cancer Immunity Cycle. Trends

Immunol 2017;38(1):20-8 doi 10.1016/j.it.2016.10.002.

17. Johnston RJ, Comps-Agrar L, Hackney J, Yu X, Huseni M, Yang Y, et al. The immunoreceptor

TIGIT regulates antitumor and antiviral CD8(+) T cell effector function. Cancer Cell

2014;26(6):923-37 doi 10.1016/j.ccell.2014.10.018.

18. Chauvin JM, Pagliano O, Fourcade J, Sun Z, Wang H, Sander C, et al. TIGIT and PD-1 impair

tumor antigen-specific CD8(+) T cells in melanoma patients. J Clin Invest 2015;125(5):2046-58

doi 10.1172/JCI80445.

19. Zhang Q, Bi J, Zheng X, Chen Y, Wang H, Wu W, et al. Blockade of the checkpoint receptor

TIGIT prevents NK cell exhaustion and elicits potent anti-tumor immunity. Nat Immunol 2018

doi 10.1038/s41590-018-0132-0.

20. Kong Y, Zhu L, Schell TD, Zhang J, Claxton DF, Ehmann WC, et al. T-Cell Immunoglobulin and

ITIM Domain (TIGIT) Associates with CD8+ T-Cell Exhaustion and Poor Clinical Outcome in

AML Patients. Clin Cancer Res 2016;22(12):3057-66 doi 10.1158/1078-0432.CCR-15-2626.

21. Joller N, Lozano E, Burkett PR, Patel B, Xiao S, Zhu C, et al. Treg cells expressing the

coinhibitory molecule TIGIT selectively inhibit proinflammatory Th1 and Th17 cell responses.

Immunity 2014;40(4):569-81 doi 10.1016/j.immuni.2014.02.012.

22. Li XY, Das I, Lepletier A, Addala V, Bald T, Stannard K, et al. CD155 loss enhances tumor

suppression via combined host and tumor-intrinsic mechanisms. J Clin Invest

2018;128(6):2613-25 doi 10.1172/JCI98769.

23. Stamm H, Klingler F, Grossjohann EM, Muschhammer J, Vettorazzi E, Heuser M, et al. Immune

checkpoints PVR and PVRL2 are prognostic markers in AML and their blockade represents a

new therapeutic option. Oncogene 2018 doi 10.1038/s41388-018-0288-y.

24. Inozume T, Yaguchi T, Furuta J, Harada K, Kawakami Y, Shimada S. Melanoma Cells Control

Antimelanoma CTL Responses via Interaction between TIGIT and CD155 in the Effector Phase.

J Invest Dermatol 2016;136(1):255-63 doi 10.1038/JID.2015.404.

25. Sarhan D, Cichocki F, Zhang B, Yingst A, Spellman SR, Cooley S, et al. Adaptive NK Cells with

Low TIGIT Expression Are Inherently Resistant to Myeloid-Derived Suppressor Cells. Cancer

Res 2016;76(19):5696-706 doi 10.1158/0008-5472.CAN-16-0839.

26. Sun ZJ, Zhang L, Hall B, Bian Y, Gutkind JS, Kulkarni AB. Chemopreventive and

chemotherapeutic actions of mTOR inhibitor in genetically defined head and neck squamous




cell carcinoma mouse model. Clin Cancer Res 2012;18(19):5304-13 doi

10.1158/1078-0432.CCR-12-1371.

27. Bian Y, Hall B, Sun ZJ, Molinolo A, Chen W, Gutkind JS, et al. Loss of TGF-beta signaling and

PTEN promotes head and neck squamous cell carcinoma through cellular senescence evasion

and cancer-related inflammation. Oncogene 2012;31(28):3322-32 doi 10.1038/onc.2011.494.

28. Mao L, Zhao ZL, Yu GT, Wu L, Deng WW, Li YC, et al. gamma-Secretase inhibitor reduces

immunosuppressive cells and enhances tumour immunity in head and neck squamous cell

carcinoma. Int J Cancer 2018;142(5):999-1009 doi 10.1002/ijc.31115.

29. Davoodzadeh Gholami M, Kardar GA, Saeedi Y, Heydari S, Garssen J, Falak R. Exhaustion of T

lymphocytes in the tumor microenvironment: Significance and effective mechanisms. Cell

Immunol 2017;322:1-14 doi 10.1016/j.cellimm.2017.10.002.

30. Pauken KE, Wherry EJ. SnapShot: T Cell Exhaustion. Cell 2015;163(4):1038- e1 doi

10.1016/j.cell.2015.10.054.

31. Kurtulus S, Sakuishi K, Ngiow SF, Joller N, Tan DJ, Teng MW, et al. TIGIT predominantly

regulates the immune response via regulatory T cells. J Clin Invest 2015;125(11):4053-62 doi

10.1172/JCI81187.

32. Tang Z, Li C, Kang B, Gao G, Li C, Zhang Z. GEPIA: a web server for cancer and normal gene

expression profiling and interactive analyses. Nucleic Acids Res 2017;45(W1):W98-W102 doi

10.1093/nar/gkx247.

33. Harjunpaa H, Blake SJ, Ahern E, Allen S, Liu J, Yan J, et al. Deficiency of host CD96 and PD-1 or

TIGIT enhances tumor immunity without significantly compromising immune homeostasis.

Oncoimmunology 2018;7(7):e1445949 doi 10.1080/2162402X.2018.1445949.

34. Lonberg N, Korman AJ. Masterful Antibodies: Checkpoint Blockade. Cancer Immunol Res

2017;5(4):275-81 doi 10.1158/2326-6066.CIR-17-0057.

35. Zaretsky JM, Garcia-Diaz A, Shin DS, Escuin-Ordinas H, Hugo W, Hu-Lieskovan S, et al.

Mutations Associated with Acquired Resistance to PD-1 Blockade in Melanoma. N Engl J Med

2016;375(9):819-29 doi 10.1056/NEJMoa1604958.

36. Huang DW, Huang M, Lin XS, Huang Q. CD155 expression and its correlation with

clinicopathologic characteristics, angiogenesis, and prognosis in human cholangiocarcinoma.

Onco Targets Ther 2017;10:3817-25 doi 10.2147/OTT.S141476.

37. Nishiwada S, Sho M, Yasuda S, Shimada K, Yamato I, Akahori T, et al. Clinical significance of

CD155 expression in human pancreatic cancer. Anticancer Res 2015;35(4):2287-97.

38. Lin H, Wei S, Hurt EM, Green MD, Zhao L, Vatan L, et al. Host expression of PD-L1 determines

efficacy of PD-L1 pathway blockade-mediated tumor regression. J Clin Invest

2018;128(2):805-15 doi 10.1172/JCI96113.

39. Tang H, Liang Y, Anders RA, Taube JM, Qiu X, Mulgaonkar A, et al. PD-L1 on host cells is

essential for PD-L1 blockade-mediated tumor regression. J Clin Invest 2018;128(2):580-8 doi

10.1172/JCI96061.

40. Wu L, Yu GT, Deng WW, Mao L, Yang LL, Ma SR, et al. Anti-CD47 treatment enhances

anti-tumor T-cell immunity and improves immunosuppressive environment in head and neck

squamous cell carcinoma. Oncoimmunology 2018;7(4):e1397248 doi

10.1080/2162402X.2017.1397248.

41. Veglia F, Perego M, Gabrilovich D. Myeloid-derived suppressor cells coming of age. Nat

Immunol 2018;19(2):108-19 doi 10.1038/s41590-017-0022-x.




42. Eruslanov EB, Singhal S, Albelda SM. Mouse versus Human Neutrophils in Cancer: A Major

Knowledge Gap. Trends Cancer 2017;3(2):149-60 doi 10.1016/j.trecan.2016.12.006.

43. Darrasse-Jeze G, Bergot AS, Durgeau A, Billiard F, Salomon BL, Cohen JL, et al. Tumor

emergence is sensed by self-specific CD44hi memory Tregs that create a dominant

tolerogenic environment for tumors in mice. J Clin Invest 2009;119(9):2648-62 doi

10.1172/JCI36628.

44. Chen W, Jin W, Hardegen N, Lei KJ, Li L, Marinos N, et al. Conversion of peripheral CD4+CD25-

naive T cells to CD4+CD25+ regulatory T cells by TGF-beta induction of transcription factor

Foxp3. J Exp Med 2003;198(12):1875-86 doi 10.1084/jem.20030152.

45. Maj T, Wang W, Crespo J, Zhang H, Wang W, Wei S, et al. Oxidative stress controls regulatory T

cell apoptosis and suppressor activity and PD-L1-blockade resistance in tumor. Nat Immunol

2017;18(12):1332-41 doi 10.1038/ni.3868.

Figure legends

Figure 1.

TIGIT is expressed on human TILs. A, Representative flow cytometry contour plots

of TIGIT expression on CD4+ T cells from healthy donor peripheral blood (HD, n =

10), human HNSCC peripheral blood (n = 16), and matched human HNSCC TILs (n

= 12) (left). Quantitation of TIGIT expression percentage in total CD4+ T cells is

shown at right. B, Representative flow cytometry plots of TIGIT expression on CD8+

T cells from healthy donor peripheral blood (HD, n = 10), human HNSCC peripheral

blood (n = 16), and matched human HNSCC TILs (n = 12) (left). Quantitation of

TIGIT expression as percentage of total CD8+ T cells is shown at right. C,

Representative flow cytometry plots of TIGIT and PD-1 coexpression on CD8+ T

cells from human HNSCC peripheral blood and TILs (n = 6) (left). Quantitation of

TIGIT and PD-1 coexpression as the percentage of total CD8+ or CD4

+ T cells is

shown at right. Data represent mean ± SD.




Figure 2.

TIGIT is expressed on murine TILs and coordinately with immune checkpoints. A,

Representative flow cytometry contour plots of TIGIT expression on CD4+ T cells by

wild-type mice spleen (WT, n = 6), tumor-bearing mice spleen (TB, n = 6), and

tumor-bearing mice TILs (n = 6) (left). Quantitation of TIGIT expression as a

percentage of total CD4+ T cells is shown at right. B, Representative flow cytometry

contour plots of TIGIT expression on CD8+ T cells by wild-type mice spleen (WT, n

= 6), tumor-bearing mice spleen (TB, n = 6), and tumor-bearing mice TILs (n = 6)

(left). Quantitation of TIGIT expression as a percentage of total CD8+ T cells is

shown at right. C, Representative flow cytometry plots of TIGIT and PD-1

coexpression on CD4+ or CD8

+ T cells by wild-type mice spleen (WT, n = 6),

tumor-bearing mice spleen (TB, n = 6), and tumor-bearing mice TILs (n = 6) (left).

Quantitation of TIGIT and PD-1 coexpression as a percentage of total CD4+ or CD8

+

T cells is shown at right. D, Quantitation of TIGIT/LAG3 or TIGIT/TIM3

coexpression percentage in total CD4+ T cells or CD8

+ T cells is shown. Data

represent mean ± SD with two independent biological duplications.

Figure 3

TIGIT is expressed on murine Tregs and correlated with highly immune suppression.

A, Representative flow cytometry contour plots of TIGIT expression on CD25–

Foxp3–, CD25

medFoxp3

–, and CD25

hi or medFoxp3

+ of wild-type (WT) or tumor-bearing

(TB) mice spleen CD4+ T cells (n = 6, respectively). B, Quantitation of TIGIT




expression in Tregs. C, Representative suppression assay of wild-type (WT) or

tumor-bearing (TB) mice Tregs cocultured with CFSE-labeled CD8+ effector T cells

for 72 hours. D, Quantitation of suppression percentage in CD8+ effector T cells. Data


Figure 4

CD155 is highly expressed on malignant cells and tumor-infiltrating myeloid cells in

human and murine HNSCC, and correlated with poor overall survival. A,

Representative IHC images of CD155 expression on human primary HNSCC and oral

mucosa samples in the HNSCC tissue microarrays (Scale bar, 50 μm). B, Quantitation

of CD155 expression score in epithelial cells according to oral mucosa (MUC),

dysplasia (DYS), and HNSCC (left). Kaplan-Meier survival curves for overall

survival for 201 HNSCC patients according to the presence of a low or high

expression of CD155 by median cut-off approach, P = 0.0337 (right). C, Quantitation

of CD155 expression score in interstitial cells according to oral mucosa (MUC),

dysplasia (DYS), and HNSCC (left). Kaplan-Meier survival curves for overall

survival for 201 HNSCC patients according to the presence of a low or high

expression of CD155 by median cut-off approach, P = 0.0149 (right). D, Quantitation

of CD155 expression score in epithelial cells according to pathological grade (I, n =

53; II + III, n = 157). E, Quantitation of CD155 expression score in epithelial cells

according to lymph node status (N0, n = 136; N1 + N2, n = 72). F, Representative

multiplexed IHC image of human primary HNSCC samples. CD155 (green) was




distributed broadly within the carcinoma element of human HNSCC, identified by

Pan-CK positivity (red). Tumor-infiltrating myeloid cells were revealed by CD11b

(yellow) or CD11c (pink) positivity. The merged image shows colocalization of

CD155 and CD11c (bottom left) or CD11b (bottom right). Scale bars: 50 μm (above).

Nuclei were stained with DAPI (blue). G, Flow cytometry histogram representative of

CD155 expression by CD11b+Ly6G

+Ly6C

lo PMN-MDSCs and CD11b

+Ly6G

-Ly6C

hi

M-MDSCs of wild-type (WT) or tumor-bearing (TB) mice spleens (n = 6,

respectively). H, Quantitation of CD155 mean fluorescent intensity (MFI) on MDSCs.

I, Relative quantification of arginase-1 (Arg1) transcripts in CD11b+Ly6G

+Ly6C

lo

PMN-MDSCs and CD11b+Ly6G

–Ly6C

hi M-MDSCs subsets sorted from wild-type

(WT) or tumor-bearing (TB) mice. The relative mRNA expression was counted as the

ratio of TB to WT. Data represent mean ±SD with two (G-I) independent biological

duplications.

Figure 5

TIGIT blockades elicit tumor rejection and reverses T cells exhaustion. A,

Experimental protocol. Beginning on day 0, Tgfbr1/Pten 2cKO mice were

administered tamoxifen each day for 5 consecutive days. On day 12, TIGIT mAb or

isotype antibody was administered i.p. three times per week. On day 40, the mice

were euthanized (n = 6, respectively). B, Quantitation of tumor size of isotype and

anti-TIGIT treatment groups. C, Representative flow cytometry plots of

CD25+Foxp3

+ Treg cells in CD4

+ T cells of TILs from isotype and anti-TIGIT




treatment groups (left). Quantitation of CD25+Foxp3

+ Treg cells as a percentage of

CD4+ T cells from spleens, lymph nodes, peripheral blood, and TILs from isotype and

anti-TIGIT treatment groups is shown at right. D, Representative flow cytometry plots

of IL2, IFNγ, and TNFα expression on CD4+ and CD8

+ T cells of TILs from isotype

and anti-TIGIT treatment groups (left). Quantitation of IL2-producing, and

IFNγ/TNFα dual–producing, CD4+ and CD8

+ T cells as percentages of total CD4

+ and

CD8+ TILs is shown at right. Data represent mean ± SD with two independent

biological duplications.

Figure 6

Blocking TIGIT/CD155 signaling increased T-cell resistance to MDSC– and Treg–

mediated suppression. A, Representative of suppression assay of PMN-MDSCs

isolated from isotype and anti-TIGIT treatment groups cocultured with CFSE-labeled

effector T cells for 72 hours (left). Quantitation of suppression assay of PMN-MDSCs

and M-MDSCs subsets isolated from isotype and anti-TIGIT treatment groups is

shown at right. B, Relative quantification of arginase-1 (Arg1) transcripts in

PMN-MDSCs and M-MDSCs subsets sorted from isotype and anti-TIGIT treatment

groups. The relative mRNA expression was counted as the ratio of anti-TIGIT

treatment groups to isotype groups. C, Representative contour plots of annexin V+PI

+

apoptotic PMN-MDSCs. Isolated MDSCs were cultured with TIGIT mAb or isotype

antibody in vitro for 20 hours and stained annexin V and PI to assess apoptotic

percentage by flow cytometry (left). Quantitation of annexin V+PI

+ apoptotic




PMN-MDSCs and M-MDSCs from TIGIT mAb or isotype antibody treatment in vitro

is shown at right. Data represent mean ± SD with two independent biological

duplications. D, Representative of suppression assay of Tregs isolated from isotype

and anti-TIGIT treatment groups cocultured with CFSE-labeled CD8+ effector T cells

for 72 hours (left). Quantitation of suppression assay of Tregs isolated from isotype

and anti-TIGIT treatment groups is shown at right. E, Representative contour plots of

annexin V+PI

+ apoptotic Tregs. Isolated Tregs were cultured with TIGIT mAb or

isotype antibody in vitro for 20 hours, and stained annexin V, and PI to assess

apoptotic percentage by flow cytometry (left). Quantitation of annexin V+PI

+

apoptotic Tregs from TIGIT mAb or isotype antibody treatment in vitro is shown at

right. F, Quantitation of TGFβ1 concentrations in the supernatants from TIGIT mAb

(10 or 20 μg/ml) or isotype antibody (10 μg/ml) in vitro treated Tregs by ELISA. Data


Figure 7

The therapeutic efficacy by anti-TIGIT is mainly dependent on CD8 T cells and Tregs.

(A and B), Beginning on day 0, Tgfbr1/Pten 2cKO mice were administered tamoxifen

each day for 5 consecutive days. On the day before tamoxifen administration and on

day 4, mice were treated with anti-CD4, anti-CD8, anti-CD25, anti-Gr-1, or isotype

control. On day 5, the efficacy of depletion was detected by flow cytometry

(Supplementary Fig. S8A-C). On day 12, mice were treated with TIGIT mAb or

isotype antibody i.p. three times per week for three weeks as described in Figure 5.




Quantitation of tumor volume in Tgfbr1/Pten 2cKO mice over time (n = 4,

respectively). C, Representative flow cytometry contour plots of TIGIT expression on

CD4+CD25

hiFoxp3

+ Tregs cells of TILs from isotype and anti-PD-1 treatment groups

(left). Quantitation of TIGIT expression on Tregs of spleens, lymph nodes, and TILs

from isotype and anti-PD-1 treatment groups is shown at right (n = 5, respectively).

Data represent mean ± SD.




Published OnlineFirst August 6, 2019.Cancer Immunol Res Lei Wu, Liang Mao, Jian-Feng Liu, et al. squamous cell carcinomaand enhances antitumor capability in head and neck Blockade of TIGIT/CD155 signaling reverses T-cell exhaustion

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