Until a few years ago, lymphatic vessels and lymphatic endothelial cells (LEC) were viewed as part of a passive conduit for lymph and immune cells to reach lymph nodes (LN). However, recent work has shown that LEC are active immunological players whose interaction with dendritic cells and T cells is of important immunomodulatory relevance. While the immunological interaction between LEC and other immune cells has taken a center stage, molecular analysis of LEC antigen processing and presentation machinery is still lagging. Herein we review the current knowledge of LEC MHC I and MHC II antigen processing and presentation pathways, Including the role of LEC in antigen phagocytosis, classical, and non-classical MHC II presentation, proteasome processing and MHC I presentation, and cross-presentation. The ultimate goal is to provide an overview of the LEC antigen processing and presentation machinery that constitutes the molecular basis for their role in MHC I and MHC II-restricted immune responses.

Edited by:

Amanda W. Lund, Oregon Health & Science University, United States

#### Reviewed by:

Stephanie Hugues, Université de Genève, Switzerland Ross M. Kedl, University of Colorado Denver, United States

#### \*Correspondence:

Laura Santambrogio<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Immunological Tolerance and Regulation, a section of the journal Frontiers in Immunology

Received: 26 February 2019 Accepted: 23 April 2019 Published: 07 May 2019

#### Citation:

Santambrogio L, Berendam SJ and Engelhard VH (2019) The Antigen Processing and Presentation Machinery in Lymphatic Endothelial Cells. Front. Immunol. 10:1033. doi: 10.3389/fimmu.2019.01033 Keywords: lymphatic endothelial cells, MHC class I, MHC class II, antigen processing and presentation, lymph

## MHC I AND MHC II ANTIGEN PROCESSING MACHINERY

#### MHC I and MHC II Molecules

Under basal physiological conditions both human and murine lymphatic endothelial cells (LEC) express both MHC class I and MHC class II molecules (1). However, as previously reported for blood endothelial cells (BEC) (2) the level of MHC II expression differs according to the anatomical location from which the cells are isolated (1, 3). LEC from LN (LN-LEC) express a high number of MHC II molecules while LEC from diaphragm express a much lower number (1). The MHC II surface expression in LN-LEC is similar to what observed in BEC but less than fibroblastic reticular cells from LN (1). LEC MHC II molecules are both endogenously synthesized or acquired from hematopoietic cells, as determined by chimera experiments in MHC II−/− mice (1, 4, 5). At the transcription level, MHC II expression is regulated by CIITA, which is not a DNA binding factor but instead a transactivator that regulates quantitative aspects of MHC-II expression by binding the MHC-II enhanceosome (6). CIITA expression is under the control of 4 different promoters (I, II, III, IV) and, in non-professional APC, MHC II expression is mostly regulated by CIITA IV (6). This promoter is responsive to IFNγ and other pro-inflammatory cytokines, which induce MHC II expression/up-regulation in fibroblasts and BEC (6). Similarly, in LEC it has been shown that endogenous MHC II expression is controlled by CIITA IV (4, 5). However, it is interesting to notice that, in contrast to other non-professional APC where pro-inflammatory stimuli greatly

**155**

up-regulate surface MHC II molecules, pro-inflammatory stimuli induce less robust MHC II up-regulation in LEC (3, 5, 7). In the future, it would be of interest to analyze why, even though LEC express the type IV INFγ-inducible CIITA, they do not strongly up-regulate MHCII during pro-inflammatory conditions (5).

### The Proteasome and TAP

Every cell expresses the constitutive 26S proteasome (8). This large barrel-shaped protein complex is formed in part by the catalytic 20S core, which consists of two pairs of outer α rings organized in seven α (α1–α7) subunits and two pairs of inner β rings organized in seven β subunits (β1–β7). The outer α subunits function as docking domains that regulate access of substrates to the catalytic chamber. Three of the β subunits (β1, β2, and β5) have proteolytic activities, including caspase-like activity (β1), trypsin-like activity (β2), and chymotrypsin-like activity (β5) (9). In the 26S proteasome, this 20S core is capped at both ends by the 19S regulatory complex (9). Ubiquitinated proteins are recognized by the 19S regulatory elements, which transfer them to the 20S for proteolysis (10). Peptides will then be transported in the ER by the transporter associated with antigen processing (TAP) and trimmed by the ER aminopeptidase I (ERAPI). In the ER the MHC class I heavy chain and β2m will transiently associates with TAP to load the peptides into the binding groove (11).

Following IFNγ or TNFα stimulation, new proteasome subunits are incorporated to generate the immunoproteasome (4, 12). β1 is exchanged with the large multifunctional peptidase 2 (LMP2) (also known as iβ1 or psmb9). β2 is exchanged with the multicatalytic endopeptidase complex-like-1 (MECL-1) (also known as iβ2 or psmb10). β5 is exchanged with the large multifunctional peptidase 7 (LMP7) (also known as iβ5 or psmb8). The 19S regulatory complex is exchanged with the Proteasome Activator α (PA28α) and PA28β, known as 11S regulator (2). The proteolytic functions of the immunoproteasome are greatly enhanced compared to those of the constitutive proteasome, as the immunoproteasome is more efficient in degrading ubiquitinated proteins and viral proteins, and in generating peptides for MHC-I presentation (13).

Until a few years ago, the presence of the proteasome in LEC was only indirectly analyzed by determining that TAP deficient mice were much less efficient in presenting MHC-I restricted OVA-derived peptides (7). However, a recent paper reported proteasome transcripts in LEC and BEC from different anatomical locations [**Table 1** and (14)]. All of these endothelial populations expressed comparable transcript levels for constitutive proteasome subunits and 19S regulatory subunits. However, LEC and BEC from LN expressed 5-8-fold higher levels of transcripts for psmb8, psmb9, and psmb10, and twice as much PA28α and β. This suggests that LN-localized LEC preferentially express immunoproteasomes. Similarly, LNlocalized LEC and BEC express 2–6 fold higher levels of TAP1 and TAP2, and twice as much ERAP1 and tapasin. Although these cells were isolated from resting LN, this suggests that their MHC-I processing and presentation capability is elevated.

Other non-proteasomal proteases have been implicated in MHC-I presentation (15). These additional peptidases can trim the proteasome-generated N-extended precursors or even destroy epitopes, by trimming below the size needed for presentation. Among these, LEC from both LN and lymphatic vessels express significant and comparable transcript levels of tripeptidyl peptidases I and II and nardilysin, but negligible levels of thimet [**Table 1** and (14)]. The functional implications of these additional LEC proteases, in generating the LEC MHC immunopeptidome, are currently unknown.

#### Endosomes and Lysosomes

Late endosomes (LE) and lysosomes (Lyso) are sub-cellular compartments, present in all cell types, specialized for the degradation of endogenous and exogenous materials for maintenance of cellular proteostasis and, in immune cells, for immunosurveillance (16). These organelles characteristically exhibit a low acidic pH, high concentrations of proteases, and expression of lysosome-associated membrane protein (Lamp) protein family members (16). In professional antigen presenting cells, LE and Lyso are also enriched in MHC class II proteins and molecules that regulate peptide loading (Invariant Chain, DM and DO) (17–21) and are referred as MHC class II compartments (MIIC) (22). Ultrastructurally these compartments can appear with different morphologies: multivesicular, multilamellar, or a combination of both (16).

Multivesicular bodies (MVB) are late endosomal compartments with a diameter of between 400 and 500 nm and a limiting membrane that encloses several internal vesicles with diameters of between 40 and 90 nm (16). MVB receive bio-synthetic cargo from the trans-Golgi, cytosolic cargo through autophagy, and exogenous proteins through phagocytosis. MVB are ubiquitously distributed and ultrastructural analysis has shown their presence in LEC (LS, unpublished observation) (23). However, it is currently unknown whether all/or a fraction of these compartments are MHC-II positive and whether there are differences in MHC-II expression in MVBs under steady state and inflammatory conditions. On the other hand the multilamellar bodies (MLB), which are lysosomal-like compartment formed by concentric lamellae and particularly enriched in MHC class II molecules (16) are more specifically expressed in professional APCs, such as DCs, B cells and macrophages, and they have not been found in LEC (LS unpublished observation).

#### Invariant Chain, DM, and DO

The MHC II molecules in association with their chaperone Invariant Chain, traffic from the trans-Golgi network to the plasma membrane before internalization to the endosomal MIIC. Sorting signals on the cytosolic tail of the Invariant chain are recognized by the clathrin-coated vesicle machinery for transport to LE/Lyso, where the Invariant chain will be processed

**Abbreviations:** BEC, blood endothelial cells; LEC, lymphatic endothelial cells; LN, lymph node; LN-BEC, lymph node-associated blood endothelial cells; LN-LEC, lymph node-associated lymphatic endothelial cells; DC, dendritic cells; LE, late endosomes; Lyso, lysosomes; MIIC, MHC class II compartments; MVB, multivesicular bodies; MLB, multilamellar bodies; DM, HLA-DM; Ii, invariant chain; DO, HLA-DO.

TABLE 1 | Comparative transcriptome profiling of antigen processing and presentation pathway genes from mouse lymphatic and blood endothelial cells.

(Continued)

#### TABLE 1 | Continued

(Continued)

#### TABLE 1 | Continued

aData are reported as normalized gene expression levels as Fragments Per Kilobase of transcript per Million mapped reads (FPKM). Data is from Berendam. (14).

by Cathepsins to generate class II-associated invariant chain peptides (CLIP), which occupy the MHC II binding groove and will be exchanged with peptides derived from endosomal processing (24). MHC II/Invariant Chain complexes are present at high levels in LEC and confocal microscopy, performed on primary LEC indicates that MHC II is correctly targeted both at the cell surface and in endosomal compartments (1).

HLA-DM (H-2M in mice) is part of the endosomal antigen processing and presentation machinery and aids peptide loading onto MHC II molecules. HLA-DM (DM) was originally discovered following the analysis of B-cell lines that were inefficient at presenting peptides derived from the processing of phagocytosed proteins but easily presented peptides supplied exogenously (17–19, 25, 26). It was later determined that these cells were defective in the expression of either the HLA-DMA or HLA-DMB genes. Subsequent in vitro and in vivo experiments determined that the role of DM is to catalyze CLIP removal, stabilize empty MHC II molecules for peptide loading and skew the immunopeptidome repertoire toward high affinity peptides (17, 25, 26). Mice lacking H-2M expressed similar I-Ab MHC II cell surface levels as wild type mice. However, the I-Ab MHC II molecules were less compact/SDS-resistant and were predominantly associated with CLIP (27). In contrast, lack of DM led to decreased peptide capture by I-Ad molecules, but enhanced peptide loading by I-Ed MHC II molecules (28). Finally, lack of DM generated a substantial pool of empty or loosely occupied I-Ak MHC II conformers with increase peptide binding activity. Mass spectrometry profiles confirmed the presence of an MHC II-peptidome in absence of DM (28, 29). Additionally DM requirements are different for CLIP binding in different registers (30). These results demonstrate that DM has distinct roles depending on its specific class II partners.

Subsequently, an additional protein, DO, was discovered, whose role is to inhibit DM function (18, 31). Importantly, while DM expression is not greatly increased following proinflammatory stimuli (TLR activation) that induces dendritic cell maturation, DO is down-regulated (32). As such it was hypothesized that high DO expression in immature dendritic cells would inhibit DM activity and skew the MHC II peptidome toward a broader and less stably bound repertoire. Upon DC maturation, reduced DO expression would lead to high DM activity, shaping the peptide repertoire toward long-lived surface class II MHC complexes, thus promoting productive immune responses (18, 33, 34).

Transcript analysis has shown that Invariant chain, I-A alpha, and I-A beta are expressed significantly in LEC and BEC from LN, but not LEC from lymphatic vessels, but DM and DO expression is very low to negligible, albeit DM is up-regulated following inflammatory stimuli (1, 4) [**Table 1** and (14)]. Because removal of CLIP from I-Ab molecules is strongly DM dependent, this could explain the inefficient processing and presentation of I-Ab restricted antigens by LEC (1). However, the haplotype variation data described above indicate that general conclusions about the ability of LEC to present MHC II restricted antigens should await analysis of other mouse haplotypes.

#### Cathepsins

Cathepsins are a large family of serine, cysteine or aspartyl proteases that are present in endo-lysosomal compartments, and may be secreted at steady state or during pathological conditions (35). Cathepsins are most active at acid pH, can still function at neutral pH but are inactive at alkaline pH (36). Although these enzymes are present in most cells, certain cathepsins are enriched in particular antigen presenting cells. For example, Cathepsin S is highly expressed in dendritic cells and B cells, Cathepsin F in macrophages, and Cathepsin L in thymocytes (36–41).

Transcriptome analysis indicated that LEC from vessels express relatively low levels of cathepsins L and F, and negligible levels of Cathepsin S, while the levels of Cathepsin S and L were significantly elevated in LEC from LN [**Table 1** and (14)]. However, measured Cathepsin L activity was variable among LN LEC and not evident in LEC from diaphragm (1). The activity of Cathepsin L indicates that at least some LEC could potentially cleave the Invariant Chain and generate CLIP peptides (1). Additionally, LEC could not efficiently process HA (an influenza membrane protein) and the IE-α protein as determined by either CD4 T cell recognition of the MHC II presented HA epitope or FACS analysis using the Y-Ae Ab that recognize I-Ab molecules loaded with the IE-α epitope, either under basal conditions or upon IFNγ stimulation (1). Furthermore, new evidence indicates that LEC express high levels of Cystatin C, B and 10 [**Table 1** and (14)], which function as natural inhibitors of cathepsins (42). Altogether, the data point to the possibility that CatL and S activity in LEC is diminished, which could affect the generation of LIP10 and CLIP, and might also diminish the processing of other endogenous antigens.

### Exogenous Peptides Binding and Antigen Exchange

The MHC I and MHC II presented immunopeptidome not only derives from endosomally processed proteins but also from pre-processed peptides that can be directly acquired from the extracellular milieu. Recent proteomic analyses have indicated that processed peptides are present in every biological fluid, among which lymph and blood, have been best characterized (43–50). The Eisen and Raghavan groups demonstrated binding of extracellular peptides to MHC I molecules and their regulation of CD8 T cell function (51, 52). Our group, among others, characterized extracellular peptide binding to MHC II surface molecules (44, 53–57). We determined that peptides carried in lymph were present in the HLA-DR1 immunopeptidome of immature dendritic cells and some of these peptides were not generated by endosomal processing, pinpointing the physiological relevance of MHC II surface/early endosomes loading (44). As such, the peptides present in the lymph, which derive from the metabolic and catabolic process of different parenchymal organs could contribute to the LEC MHC II immunopeptidome, since it has already been shown that LEC can readily bind and present pre-processed peptides (1).

## PHAGOCYTOSIS AND AUTOPHAGY

Only very recently LEC have been analyzed for their ability to capture exogenous and endogenous antigens through phagocytosis. In vivo experiments using fluorescently labeled OVA indicated that within 90 min the subcutaneously injected protein was identified in LYVE-1+ cells, present in LN subcapsular sinuses (7). Additionally, genes encoding several scavenger receptors, known to be involved in receptor-mediated endocytosis, are upregulated in LEC from lymph node (14). LEC efficiency in processing phagocytosed proteins through the MHC II pathway in steady state condition is low (1); nevertheless LEC can transfer Ags to dendritic cells, which are known to be present in close proximity with LEC in the lymphatic capillary and collectors, to induce CD4 T-cell anergy (1, 58). In addition, LEC efficiently present MHC-I peptides, and it has been reported that phagocytosis in early endosomes can route exogenous antigens (both self and non self) for cross-presentation on MHC class I in a proteasome and TAP-1-dependent manner (1, 3, 7, 58– 61). It is interesting to consider that the acquisition of crosspresented material is mediated by these scavenger receptors. A second mechanism that can transfer endogenous proteins in the endosomes is autophagy. Although autophagy has been extensively characterized in BEC (62), there are no reports on the role of autophagy in antigen processing and presentation in LEC.

## LEC AND PATHOGEN IMMUNITY

A growing body of evidences indicates that LEC are involved in immune response to pathogens. It has been recently reported that in extrapulmonary tuberculosis, the lymphatic system is the most common site of infection and LEC function as a niche for Mycobacterium tuberculosis (59). Indeed M. tuberculosis can replicate in the LEC cytosol and within autophagosomes suggesting that LEC are a previously unrecognized site for infection persistence. Similarly, Hantaviruses have been shown to have a tropism for lymphatic vessels and LEC infection with either Andes virus and Hantaan virus induces LEC hyperpermeabilization and pulmonary edema (63). The edema can be inhibited by αvβ3 integrin as well as VEGFR3 antibodies (63). A LEC role in HIV infection was also reported in promoting infection and latency formation in resting CD4+ T cells (64, 65). Recently an interesting role of LEC in antigen persistence, after resolution of the infection, has been shown (66). After viral challenge and vaccination, the antigen was captured by LEC under proliferative conditions and stored for extended periods of time. This "antigen archiving" mechanism positively influenced the degree of protective immunity provided by circulating memory CD8+ T-cells (66, 67).

### COSTIMULATORY AND CO-INHIBITORY MOLECULES

Effective activation of T-cells requires the display of MHC-I and MHC-II-peptide complexes as well as an antigen-independent signals provided by co-stimulatory molecules, among which CD40, CD80 (B7.1), and CD86 (B7.2) have been extensively analyzed in their requirements for naïve and memory T-cells activation (68, 69). LN LEC were shown to express very low levels of CD40 and negligible levels of CD80 and CD86 (3, 60). More recent transcriptome analysis has validated these observations, and extended them to include additional costimulatory molecules [**Table 1** and (14)]. Importantly these costimulatory molecules did not up-regulate following stimulation with an MHC-I cognate ligand as well as inflammatory signals (TLRs binders or IFNγ) (3, 60).

In contrast, LEC in LN, but not in peripheral tissue lymphatics, express multiple inhibitory receptors that engage counter-receptors on activated T-cells to dampen the immune response (69). These include PD-L1 (CD274) and PD-L2 (CD273), which are present on resting LEC and greatly upregulated by inflammatory stimuli (1, 70). Interestingly, the ligand for LAG-3, another inhibitory receptor on T-cells, is MHC-II, and induction of CD8 T-cell tolerance by LEC depends on engagement of LAG-3 as well as PD-1 (1, 60). Consequently, it has been suggested that in the absence of functional Ag presentation, the expression of MHC-II molecules on LEC is concerned with inducing Lag-3 mediated tolerance. While the low expression of costimulatory molecules would suggest that LEC would be unable to activate T-cells, they stimulate profound proliferation of CD8 T-cells in vivo and in vitro, and after peptide pulsing and CD4 T-cell proliferation in vitro (58, 60). However, the expression of the co-inhibitory molecules leads to deletional tolerance of CD8 T-cells due to a failure to sustain upregulation of the IL-2 receptor. Thus, LEC represent an important mechanism for mediation of systemic peripheral tolerance (58, 60, 61).

#### EXOSOMES AND OTHER VESICLES

Most cells in the human body release vesicles of different sizes and content which can be classified as apoptotic bodies, micro and macrovesicles and exosomes (71). Exosomes are small (30–120 mm) vesicles generated from the multivesicular late endosomes upon fusion with the plasma membrane and release in the extracellular milieu. Exosomes from different sources have been shown to transport a protein cargo as well as mRNAs and microRNAs. Their physiological and pathological relevance has been established in several immune and cancerrelated models (72). Although very little is known about LEC-released exosomes, recently it has been shown that LEC release a vesicular fraction, which includes exosomes, following an inflammatory signal (73). The LEC-derived exosomes are reportedly enriched with a motility-promoting protein signature, which act as a cue for the dendritic cells migratory response (73).

#### REFERENCES

In particular LEC released vesicles accumulate in the perivascular stroma of small lymphatic vessels, mostly in the presence of inflammatory cytokines and promote directional migration of CX3CR1-expressing cells (73).

#### CONCLUDING REMARKS

LEC cells are anatomically placed between parenchymal organs and draining lymph nodes, functioning as a conduit for the lymphatic fluid and are known to control DC and T cell migration in and out of the lymph node (74, 75). During the last few years their functionality in antigen processing and presentation and T cell immune responses has emerged. Under steady-state conditions LEC can present self-antigens to induce T cell tolerance either through expression of peripheral tissue antigens (76) or acquisition of extracellular antigens through phagocytosis or by acquisition of pre-loaded MHC II molecules from DC. Under inflammatory conditions LEC also play an immunosuppressive role by decreasing DC maturation (77) and by up-regulating surface PDL1 (76).

However, the advances in understanding the cross-talk between LEC and T cells has not been paralleled by a detailed mechanistic analysis of their antigen processing and presentation machinery. Characterization of LEC immunoproteasomes, endosomal processing compartments, and antigen acquisition from the lymphatic fluid still needs to be investigated. Nevertheless, the work to date points to an emerging picture of the role played by LEC in maintenance of self-tolerance.

### AUTHOR CONTRIBUTIONS

LS and VE wrote the review. SB contributed the primary data presented in the table.

### FUNDING

Support was provided by United States Public Health Services Research Grant R21 AI109250 (VE) and RO1 AG045223 (LS).

or viral infection. Nat Commun. (2014) 5:3989. doi: 10.1038/ ncomms4989

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Santambrogio, Berendam and Engelhard. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Chronic Liver Disease in Humans Causes Expansion and Differentiation of Liver Lymphatic Endothelial Cells

Beth A. Jiron Tamburini 1,2,3 \* † , Jeffrey M. Finlon1 , Austin E. Gillen3 , Michael S. Kriss 1 , Kent A. Riemondy 3 , Rui Fu3 , Ronald P. Schuyler 2 , Jay R. Hesselberth3,4, Hugo R. Rosen5 and Matthew A. Burchill 1,3 \* †

*1 Division of Gastroenterology and Hepatology, Department of Medicine, School of Medicine, University of Colorado, Aurora, CO, United States, 2 Department of Immunology and Microbiology, School of Medicine, University of Colorado, Aurora, CO, United States, 3 RNA Biosciences Initiative, School of Medicine, University of Colorado, Aurora, CO, United States, 4 Department of Biochemistry and Molecular Genetics, School of Medicine, University of Colorado, Aurora, CO, United States, 5 Keck School of Medicine, University of Southern California, Los Angeles, CA, United States*

#### Edited by:

*Anne Fletcher, Monash University, Australia*

#### Reviewed by:

*Veronika Lukacs-Kornek, Saarland University, Germany Gou Young Koh, Korea Advanced Institute of Science and Technology (KAIST), South Korea*

#### \*Correspondence:

*Beth A. Jiron Tamburini<EMAIL_ADDRESS>Matthew A. Burchill<EMAIL_ADDRESS>
*†These authors have contributed equally to this work*

#### Specialty section:

*This article was submitted to Immunological Tolerance and Regulation, a section of the journal Frontiers in Immunology*

Received: *27 November 2018* Accepted: *23 April 2019* Published: *15 May 2019*

#### Citation:

*Tamburini BAJ, Finlon JM, Gillen AE, Kriss MS, Riemondy KA, Fu R, Schuyler RP, Hesselberth JR, Rosen HR and Burchill MA (2019) Chronic Liver Disease in Humans Causes Expansion and Differentiation of Liver Lymphatic Endothelial Cells. Front. Immunol. 10:1036. doi: 10.3389/fimmu.2019.01036* Liver lymphatic vessels support liver function by draining interstitial fluid, cholesterol, fat, and immune cells for surveillance in the liver draining lymph node. Chronic liver disease is associated with increased inflammation and immune cell infiltrate. However, it is currently unknown if or how lymphatic vessels respond to increased inflammation and immune cell infiltrate in the liver during chronic disease. Here we demonstrate that lymphatic vessel abundance increases in patients with chronic liver disease and is associated with areas of fibrosis and immune cell infiltration. Using single-cell mRNA sequencing and multi-spectral immunofluorescence analysis we identified liver lymphatic endothelial cells and found that chronic liver disease results in lymphatic endothelial cells (LECs) that are in active cell cycle with increased expression of CCL21. Additionally, we found that LECs from patients with NASH adopt a transcriptional program associated with increased IL13 signaling. Moreover, we found that oxidized low density lipoprotein, associated with NASH pathogenesis, induced the transcription and protein production of IL13 in LECs both *in vitro* and in a mouse model. Finally, we show that oxidized low density lipoprotein reduced the transcription of *PROX1* and decreased lymphatic stability. Together these data indicate that LECs are active participants in the liver, expanding in an attempt to maintain tissue homeostasis. However, when inflammatory signals, such as oxidized low density lipoprotein are increased, as in NASH, lymphatic function declines and liver homeostasis is impeded.

Keywords: lymphatic endothelial cells, cirrhosis, fibrosis, non-alcoholic steatohepatitis, hepatitis C virus, alcoholic liver disease, interleukin-13, oxidized low density lipoprotein

## INTRODUCTION

Deaths from chronic liver disease (CLD) have increased by 31% between the years 2000 and 2015 (1). CLD arises due to chronic inflammation in the liver as a result of a number of environmental insults including viral infection (hepatitis C or B virus-HCV/HBV), alcohol consumption (Alcohol associated liver disease-ALD) and diet-induced obesity (Non-alcoholic steatohepatitis-NASH).

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Due to the regenerative capacity of the liver, the liver participates in a dynamic process that can result in several rounds of injury and repair. However, chronic injury eventually leads to severe fibrosis, cirrhosis, and the decline of liver function. While removal of the insult causing injury can be effective at reversing liver fibrosis (2), many patients with advanced disease do not improve or ultimately progress to cirrhosis (3, 4). As a result, these people remain at an elevated risk for development of hepatocellular carcinoma despite the removal of chronic insult (5). Limited therapeutic options exist for these patients causing the rates of morbidity and mortality to continue to climb (6).

The lymphatic system transports interstitial fluid (lymph) from the tissue to the circulatory system for removal from the body (7, 8). In addition, lymphatics participate in the acquisition of fat and the formation of chylomicrons in the gut (9), reverse cholesterol transport (10), and trafficking of dendritic cells (DCs) from the tissue to the lymph node (LN) (11, 12). During CLD, increased lymphatic permeability has been implicated in the formation of ascites, or fluid accumulation, in the peritoneal cavity (13). Furthermore, increased lymphatic vessel permeability has been demonstrated to increase inflammation and immune dysfunction in other tissues (14–17). Obesity and hypercholesterolemia are also associated with lymphatic permeability, hyperplasia, and inflammation at peripheral sites in humans (18, 19) and in animals (20).

Lymphatic vessels are comprised of lymphatic endothelial cells (LECs). LEC interactions with immune cells can guide trafficking of immune cells as well as promote self-tolerance and enhance protective immunity (21–25). Despite the multi-faceted role of LECs in programming immune responses in the lymph node and skin, the role of lymphatics in coordinating the immune response in the liver has not been addressed. Furthermore, with the advent of single cell sequencing, several reports have addressed different cell populations within the liver, including specific interrogation of liver endothelial cell populations (26–28). However, in none of these reports have lymphatic endothelial cells been identified. Thus, the transcriptional profile and function of liver lymphatic endothelial cells in homeostasis or disease is yet unknown. However, previous case reports from almost 20 years ago, using common endothelial markers and histology, did demonstrate that lymphatic vessels increase in diameter and abundance during chronic viral hepatitis (29, 30). Despite these observations, little to nothing is known about lymphatics in non-viral cases of CLD, or the cause and/or consequence of lymphatic expansion in the liver. As diet-induced CLD has surpassed chronic viral infection as the leading cause of liver transplantation (31), understanding the role of lymphatics in the liver in people with diet-induced CLD is an important functional process that needs to be addressed.

Here we demonstrate a significant increase in lymphatic vessel density in patients with CLD. We show that in addition to virally induced CLD, that non-virally induced CLD also results in a significant increase in lymphatic vessel density in the liver. To identify specific differences in LECs during disease we performed transcriptional profiling of LECs, using a single-cell platform, from non-diseased and diseased human livers. While other endothelial cell populations have been identified by single cell RNA sequencing in the liver, this is the first demonstration of isolation of LECs and subsequent transcriptional profiling of this rare cell population in the liver. We find that LECs from NASH or HCV infected livers engage a transcriptional program that results in more LECs in active cell cycle and more CCL21 expression. However, when comparing the transcriptional profile of LECs from patients with NASH to patients with HCV we find that NASH specifically induces the activation of the IL13 pathway. Furthermore, we demonstrate that not only is the IL13 pathway increased in patients with NASH, but also that oxidized LDL, commonly associated with inflammation in NASH, can induce the upregulation of IL13 transcript and protein in LECs. Finally, we provide evidence that IL13 expression by LECs occurs specifically in the liver and that oxidized LDL results in the downregulation of the LEC transcription factor, PROX1, and reduced lymphatic stability.

### MATERIALS AND METHODS

#### Patient Samples

For immunohistochemistry archived patient specimens were obtained from the University of Colorado Anschutz Medical Campus biorepository core facility **(Supplementary Table 1)**. For single cell sequencing, patients were selected from a biorepository of patients who had undergone liver transplantation and collected under the IRB protocol of HRR and MSK. Transplanted livers were harvested and nonparenchymal cells (NPCs) were isolated and frozen in a single cell suspension as described (32). Additionally, non-diseased NPCs were purchased from Triangle research laboratories (Lonza, Triangle research park, NC). For Non-diseased patients (n = 6) the age range was 37 to 58 with a mean age of 49 where five patients were male and one was female. For HCV samples (n = 3) the age range was 47–55 with a mean age of 51 and all patients were male. For NASH samples (n = 2) the age range was 49–55 with a mean age of 52 and all patients were females. For Ki67 analysis: the age range was 35–61 for diseased patients and included NASH, ALD, HCV, AIH, PBC, and AIH with NASH. The average age of all diseased patients was 49.4 with 62.5% of the patients being female. The same non-diseased patients from Lonza were used as described above. All patients provided written and informed consent and the study was approved by the institutional review boards at the University of Colorado—Anschutz.

#### Flow Sorting and Flow Cytometric Analysis

To enrich LECs from hepatic NPCs we thawed frozen samples in RPMI containing 10% Human Serum AB (Gemini Bio-products, West Sacramento, CA) and 1% DNASE (MP Biomedicals, Santa Ana, CA). Cells were washed 2x with PBS containing 2% FBS

**Abbreviations:** CLD, chronic liver disease; LEC, lymphatic endothelial cell; PEC, portal endothelial cell; HBV, hepatitis B virus; HCV, hepatitis C virus; PBC, primary biliary cirrhosis; NASH, non-alcoholic steatohepatitis; ALD, alcoholic liver disease; AIH, autoimmune hepatitis; PSC, primary sclerosing cholangitis; PDPN, podoplanin; IL13, Interleukin 13; MELD, model for end-stage liver disease.

(Atlas Biologicals, Fort Collins, CO) and stained with antibodies against CD45 (clone HI30), CD31 (PECAM1, clone WM59), Podoplanin (clone NC-08) and CD146 (clone P1H12) from Biolegend (San Diego, CA), and CD68 (clone KP1) from abcam (San Francisco, CA). Cells from either Non-diseased, NASH or HCV were sorted using an aria Fusion sorter (BD Biosciences, Franklin lakes, NJ) and enriched LECs were sorted into RPMI containing 50% human serum AB. Enriched LECs from each condition were pooled for single cell sequencing as described below. Flow cytometric analysis of human liver LECs: isolated liver NPCs were stained with Fixable viability dye 510 (BD Biosciences) and stained with the above surface antibodies. Following surface staining cells were fixed and permeabilized (Thermo Fischer, Waltham, MA) and stained for Ki67 (clone 11F6) (Biolegend). Flow cytometry was performed using a BD FACSCanto II instrument and was acquired with BD FACSDiva software (BD Biosciences). Analysis ws performed using FlowJo 10 (Treestar, Woodburn, OR).

### Single Cell RNA Sequencing

Approximately 10,000 LEC-enriched hepatic NPCs were loaded onto a 10x genomics (San Francisco, CA) controller per manufacturer instructions to generate barcoded single cell GEMs using the 10x genomics 3′ kit. mRNA was converted to cDNA within each barcoded single cell GEM and libraries were generated as previously described. 10x libraries were sequenced using a NovaSeq 6000 (Illumina, San Diego, CA) to a predicted depth of 100,000 reads/cell. All cell preparation was performed at the University of Colorado Genomics Shared Resource Core. To control for sequencing batch effects, a minimum of three nondiseased samples were included with each diseased capture and sequencing run.

### Quantification of Single Cell RNA Sequencing

scRNA-seq data was processed with the 10x Genomics Cell Ranger Suite for demultiplexing, alignment, assignment of reads to genes, and unique molecular identifier (UMI) deduplication to remove PCR duplicates. Further analysis, including cell clustering, cell type identification, marker gene identification, and differential expression analyses was performed using the R packages Seurat (33) and scran (34). For cell cycle analysis Seurat assigns each cell a score based on its expression of G2/M and S phase markers. These marker sets are anti-correlated in their expression levels, and cells expressing neither are assigned to G1 phase. Cells with fewer than 250 detectable genes or >20% of UMIs derived from mitochondrial genes were excluded from the analysis to eliminate cells with insufficient expression data for clustering and dead cells, respectively **(Supplementary Figure 1)**. Ingenuity pathway analysis (IPA) was performed using IPA software (Qiagen, Venlo, Netherlands). Raw data, count matrices, metadata including cluster assignment are available at the Gene Expression Omnibus under accession GSE129933 (https://www. ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE129933).

### Multispectral Fluorescence Immunohistochemistry and Vectra Analysis

Five micron thick tissue sections were sequentially stained for human PDPN, CD3, CD19, CCL21, and CD68. Slides were dewaxed with xylene, heat treated in pH9 antigen retrieval buffer for 15 min in a pressure cooker, blocked in Antibody (Ab) Diluent (Perkin Elmer, Waltham, MA), incubated for 30 min with the primary Ab, 10 min with horseradish peroxidase (HRP)-conjugated secondary polymer (anti-mouse/anti-rabbit, Perkin Elmer, Waltham, MA), and 10 min with HRP-reactive OPAL fluorescent reagents (Perkin Elmer). Slides were washed between staining steps with PBS 0.01% tween 20 and stripped between each round of staining with heat treatment in antigen retrieval buffer. After the final staining round the slides were stained with spectral DAPI (Perkin Elmer), and coverslipped with Prolong Diamond mounting media (Thermo Fisher, Waltham, MA). Multispectral imaging was preformed using the Vectra 3.0 Automated Quantitative Pathology Imaging System (Perkin Elmer). Whole slide scans were collected using the 10x objective and 10 to 20 regions were selected for multispectral imaging with the 20x objective. The multispectral images were analyzed with inForm software (Perkin Elmer) to unmix adjacent fluorochromes, subtract autofluorescence, segment the tissue into lymphatic vessels and non-lymphatic vessels, segment the cells into nuclear, and membrane compartments, and to phenotype the cells according to morphology and cell marker expression. Lymphatic vessel density was quantified using the Nikon AR software where LVD = vessel area/total area × 100%. Lymphatic vessels with CCL21 staining less 0.036 were classified as CCL21lo or negative while lymphatic vessels with a value >0.036 were classified as CCL21hi or positive using inForm software. For CCL21 analysis three Non-diseased, 5 HCV, and three NASH patient samples were interrogated. For T, B, and macrophage cell analysis three or four non-diseased, 3–5 NASH, and 4 HCV patient samples were quantified. A student's t-test was performed where two asterisks represents a p-value less than 0.001. Patient data is included in **Supplementary Table 1**.

## Branch Forming Assay

Branch forming assay was performed as previously described (35, 36). Briefly, a 4.2 mg/ml matrigel (Corning, Tewksbury, MA) pad with either 100µg/ml oxidized LDL (Alfa Aeser, Ward Hill, MA), 0.25 mM Palmitic Acid (Caymen Chemicals, Ann Arbor, MI, or equivalent amount of DMSO was allowed to solidify for one and a half hours. Fifteen thousand Human Lymphatic Endothelial Cells (PromoCell, Heidelberg, Germany) mixed with 100µg/ml oxidized LDL, 0.25 mM Palmitic Acid, or equivalent amount of DMSO in endothelial cell growth medium (PromoCell) were placed on top of the matrigel pad. Cells were incubated at 37◦C for 21 h, then imaged using a Zeiss microscope, and Axiom camera. For RT-PCR the matrigel was dissolved using ice cold 5 mM EDTA rocking on ice for 1 h. HLECs were pelleted and lysed with RLT buffer, mRNA was extracted using the RNeasy micro kit per manufacturer instructions and cDNA was synthesized using the QuantiTect RT Kit (Qiagen, Venlo, Netherlands) following standard protocols. Quantitative PCR was performed on an Applied Biosystems 7,300 Real-time PCR machine and fold changes in mRNA levels were calculated using the delta-delta CT method. For each gene, all samples were normalized to the average fold change of the vehicle treatment group (DMSO). The following Qiagen QuantiTect primers were used: GUSB (QT00046046), IL13 (QT00000511), PROX1 (QT01006670), and VEGFR3/FLT4 (QT00063637).

#### Animal Studies

Six to eight week old C56BL6/J mice were IV injected with 85 µg of unlabeled or DIL or DIO labeled human highly oxidized LDL (Kalen Biochemicals, Germantown, MD) or 100 µg PolyI:C (InvivoGen, San Diego, CA). Following indicated incubation time mice were administered a second dose of stimulant. For in vivo BFA experiments, 18 h following the second injection mice were administered 250 µg of Brefeldin A as previously described for analysis of in vivo cytokine production by T cells (25, 37). Ninety minutes after Brefeldin A injection mice were euthanized and livers and lymph nodes were processed as described (38) with Brefeldin A in each buffer. For flow cytometric analysis of LEC production of IL13, single cell suspensions of liver and lymph node cells were stained with CD45 (clone 30-F11), CD31 (clone 390), PDPN (clone 8.1.1) from biolegend and CD146 (clone P1H12) and IL13 (clone ebio13A) from ebioscience. Flow cytometry was performed using a BD FACSCanto II instrument and data were acquired with BD FACSDiva software (BD Biosciences) or Cyan ADP and acquired with summit software. Analysis was performed using FlowJo 10 (Treestar). All procedures were approved by the University

anti-CD68 (macrophages-green), and dapi (nuclei-blue) and imaged using the Perkin Elmer Vectra 3.0 imaging system and linear unmixed with inFORM software. (C) Lymphatic vessels density was determined using inFORM software and normalized to area in each disease listed and designated by color of dot. Statistical analysis was performed using a student's *t*-test. \*\**P* < 0.01.

of Colorado School of Medicine Institutional Animal Care and Use Committee.

#### Statistical Analysis

For all graphs with statistical analysis an unpaired student's t-test was used evaluate statistical significance between two points using Prism software (GraphPad, San Diego, CA). One asterisk denotes a p-value of <0.05, two asterisks denotes a p-value <0.01 and three asterisks denotes a p-value <0.001. Statistical analysis for single cell RNA sequencing (differential expression testing) was performed using the Wilcoxon Rank-Sum Test implemented in Seurat.

### RESULTS

### Lymphatic Vessel Density Increases in End Stage Liver Disease

Liver tissue was obtained from 28 patients with end stage liver disease at the time of transplantation (Non-Alcoholic Steatohepatitis (NASH), Alcoholic liver disease (ALD), chronic Hepatitis C viral infection (HCV), Autoimmune hepatitis (AIH), Wilson's disease, Primary sclerosing cholangitis (PSC), and four patients with non-diseased livers **(Supplementary Table 1)**. Lymphatic vessels in the liver were assessed via immunofluorescence staining with the anti-podoplanin antibody (red) to mark lymphatic vessels in addition to anti-CD3 to mark T cells (white), anti-CD68 to mark macrophages (green), and dapi to label nuclei (blue). Shown are representative images from both a non-diseased liver **(Figure 1A)** and an ALD patient explant **(Figure 1B)**. In cirrhotic livers, the density of lymphatic vessels is significantly increased, regardless of disease etiology, when compared to liver sections from non-diseased controls (**Figure 1C)**. Changes in LVD were independent of Model for End Stage Liver Disease (MELD) score at time of transplant, age, body mass index (BMI), race, or disease etiology (**Supplementary Figure 2**). This increased lymphatic vessel density is confined to areas of active inflammation. As such, the lymphatic vessels are in close proximity to regions of inflammation as determined by the frequency of T cells, macrophages, and fibrotic areas. Alternatively, neither lymphatic vessels, nor T cells were found in the regenerative nodules **(Figures 1A,B** and **Supplementary Figure 3)**. This supports lymphatic expansion as a universal marker and potential critical mechanism for chronic liver disease progression.

### Increased CCL21 Expression and Immune Cell Infiltration Occurs in Cirrhotic Livers

As we determined lymphatic vessel density was increased during disease we asked if CCL21, T cell, B cell or macrophage frequency was changed. Others have reported expression of CCL21 by LECs in other tissues and CCL21 is a chemokine that can recruit CCR7+ dendritic cells and T cells (39). We first validated that liver LECs express CCL21 protein using a CCL21 specific antibody. In the imaging of non-diseased and diseased livers we observed that there were populations of LECs that express no or low levels of CCL21 **(Figure 2A)** while others express high levels of CCL21 protein (**Figure 2B**). To stratify lymphatic vessels based on CCL21 expression we calculated negative expression

*Shown is the average log2 gene expression fold change between LEC and PEC in non-diseased livers, the percent of cells in each subset that expresses a given gene, and the raw and adjusted P-values. Data was filtered to include only genes in which the p-value between LEC and PEC was* <*0.0006.*

to be <0.01 counts, based on a no-CCL21 antibody control, CCL21lo expression to be between 0.01 and 0.036 counts and CCL21hi expression to be between 0.036 and 0.252 counts, as assessed by InFORM software **(Supplementary Figure 4)**. Using PDPN to label lymphatic vessels we found that the number of lymphatic vessels that had CCL21hi/+ expression was about 4 vessels per mm2 in non-diseased livers, while the frequency of lymphatic vessels with high expression of CCL21 was between 6 and 10 vessels per mm2 in patients with HCV and NASH **(Figure 2C)**. These vessels were also often associated with infiltrating immune cells and thus we quantified the accumulation of B cells, T cells and macrophages in the liver. Similar to previous results, we found that end stage liver disease resulted in the significant accumulation of T cells and macrophages in the liver of patients with HCV and NASH while B cells were less frequent **(Figure 2D)**. These studies led us to ask if chronic liver disease induces LECs differentiation in the liver that results in modulation of the inflammatory state of the liver microenvironment.

### Isolation and Single Cell Sequencing of Lymphatic Endothelial Cells in the Liver

To understand how LECs were transcriptionally regulated in the liver we isolated LECs and subjected them to single cell mRNA sequencing. While other endothelial cell populations within the liver have been evaluated transcriptionally, the transcriptome of liver lymphatic vessels has yet to be reported. This could be due to the LECs in the liver being a fragile, rare and difficult to identify population. Therefore, we used our expertise in lymphatic endothelial cell flow cytometry to isolate and acquire the transcriptional signature of lymphatic endothelial cells in the liver. Once LECs from explanted human livers were isolated by flow sorting, using our published liver LEC marker set (38) **(Figure 3A)**, we subjected the sorted cells to single cell mRNA sequencing using the 10x genomics 3′ platform. Individual groups of cells were clustered using TSNE clustering based on transcriptional profile **(Figure 3B)**. Interestingly, while we sorted our population of cells based on known phenotypic markers for LECs we still were able to visualize a number of contaminating cells based on their transcriptional profile. However, using this analysis we were also able to discern that in the non-diseased human liver there are two distinct populations of endothelial cells that are transcriptionally distinct from liver sinusoidal endothelial cells (LSECS) (26).

LECs were identified using the expression of prospero homeobox protein 1 (PROX1), lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1), podoplanin (PDPN), vascular endothelial growth factor receptor 3 (FLT4/VEGFR3), and CCL21 **(Figure 3C)**. Based on the expression of these LEC-associated markers we were able to divide these two populations into a fully differentiated LEC population and an endothelial cell population that resembles the recently reported portal endothelial cells (PEC) (27). Specifically, these two populations are distinguished by their expression of several markers such as PROX1, PDPN, CCL21, Neurotensin, and trefoil factor 3 (TFF3) by the LEC cluster; bone marrow stromal antigen two precursor (BST2), interferon alpha inducible protein 27 (IFI27) and ribonuclease 1 (RNASE1) by the other endothelial cluster similar to PECs **(Table 1).** These factors have been previously reported to be associated with either LECs or blood endothelial cells (BECs) in other model systems and in primary endothelial cell cultures confirming that these subsets are of lymphatic or blood origin, respectively (40, 41). As seen in **Figure 2**, liver LECs express CCL21 protein while LECs from diseased livers had more CCL21hi/+ vessels. This was confirmed by our transcriptional analysis and similar to other reports demonstrating expression of the chemokine CCL21 by LECs **(Figure 3D)** (42, 43). We also discovered that TFF3—a gene upregulated in hypoxia that induces expression of VEGF and protects barrier function is upregulated by the LEC population (44, 45). The liver PEClike population has increased expression of genes such as IFI27 which is also expressed by LECs in the lymph node (46–48); and HSPG2 encoding Perlecan which is predominantly expressed by BECs, but whose expression can be increased during the final maturation of lymphatic vessels in the skin (49). These data suggest that the PEC-like population may be a progenitor cell for LECs with transcripts found in both cells from blood and lymphatic lineages. Finally, we confirm that the structures we visualized in the livers of cirrhotic patients **(Figure 1)** are the same LEC population we are evaluating transcriptionally based on the expression of PDPN in this specific endothelial population **(Figure 3C)**. Thus, based on transcriptional profiling we were able to distinguish LECs from other cells in the liver in order to evaluate changes in these cells during chronic liver disease.

#### Liver Disease Results in the Proliferation of Lymphatic Endothelial Cells

As stated above we identified lymphatic endothelial cells in the liver both by flow cytometry and transcriptional profiling.

*Shown is the average log*2 *gene expression fold change differences between LECs isolated from NASH and HCV, the percent of cells in each subset that expresses a given gene, and the raw and adjusted P-values. Data was filtered to include only genes in which the p-value between HCV and NASH were* <*0.0006.*

Being that we saw a substantial increase in the frequency of lymphatic vessels in disease **(Figure 1)** we evaluated if chronic liver disease induced the specific expansion and differentiation of LECs. We first compared liver LECs from non-diseased to diseased livers (both HCV and NASH) and found LECs from diseased livers downregulated pathways involved in apoptosis while upregulating pathways involved in free radical scavenging **(Supplementary Table 2)**. Similarly, upstream pathways activated in LECs from diseased livers included Jun N-terminal kinase (JNK), mitogen-activated protein kinase (MAPK), as well as tumor necrosis factor (TNF) **(Supplementary Table 3)**. We also observed a higher proportion of LECs from diseased patients that are in active cell cycle compared to LECs from non-diseased livers or PECs **(Figure 4A)**. To confirm this transcriptional data we utilized flow cytometry to measure Ki67 expression by LECs from non-diseased and diseased livers. Using this approach, we were able to confirm our transcriptional data demonstrating that a higher frequency of LECs from diseased livers have Ki67 expression compared to LECs from non-diseased livers **(Figure 4B)**. This difference was consistent across patients, suggesting the expansion of LECs is a common event during chronic liver disease **(Figure 4C)**. Finally, when comparing genes between liver LECs from non-diseased, HCV or NASH we found that each group clustered differently **(Figure 4D)**. Many of the same genes were differentially expressed between non-diseased and both NASH and HCV **(Figure 4D)** suggesting different inflammatory stimuli induce some of the same transcriptional programs. However, while there were many similarities in the transcriptional programs of LECs from HCV or NASH explanted livers there were also differences **(Figure 4D**). Taken together, these data demonstrate that LECs and PECs, are differentially regulated during chronic liver disease and that chronic liver disease results in the preferential expansion of LECs. These data also suggest that different inflammatory insults may regulate different gene programs in LECs.

### CLD Alters Signaling Pathways in Liver LECs

To examine differences in gene expression in LECs dependent on disease etiology we compared the gene expression of LECs from NASH patients to HCV patients **(Table 2)**. We also used IPA software to evaluate transcriptional pathways **(Supplementary Table 4)** induced by the different disease etiologies. Intriguingly, the IL13 signaling pathway was upregulated in LECs isolated from patients with NASH **(Supplementary Table 4)**. IL13 has been shown to be involved both in maintaining lymphatic vessel structure and permeability (35, 50) and in the conversion of hepatic stellate cells (HSC) to myofibroblasts (51, 52). While IL13 expression was not detected in any of the cell types we evaluated, suggesting a signal strength issue; CD36, FABP4 and TFF3, genes that are targets of IL13 signaling, were upregulated (53–55), and ATF3, which inhibits IL13 transcription (56), was downregulated in LECs from NASH livers (**Figure 5A**). These data not only gave us potential leads to follow, but also led us to the conclusion that while CLD uniformly induces the expansion of lymphatic vessels in the liver, NASH-associated liver disease elicited a unique transcriptional profile in liver LECs that involves IL13 signaling.

We next asked if these transcriptional differences were a result of direct stimulation of LECs by factors associated with the disease. Therefore, we asked if oxidized LDL (oxLDL) or palmitic acid (PA) affected the lymphatic branching and transcriptional profile of human LECs (hLECs) in vitro (**Figure 5B**). We used oxLDL as it accumulates in response to free radicals generated by inflammation, has been shown to affect other cell types such as macrophages and endothelial cells in atherosclerosis and is elevated in NASH (57–62). Further, oxLDL has a dramatic effect on macrophage activation, while LDL alone does not (63). We used PA as it is an important dietary fatty acid that is largely consumed in foods [reviewed in (64)]. We observed that when LECs were treated with vehicle (DMSO), PA or oxLDL and

24 h with the indicated stimulus. (F) Quantification of (E). \**P* < 0.05. \*\*\**P* < 0.001.

visualized at 4 and 24 h post-treatment that only the vehicle and PA treated LECs were able to maintain their branched structures over the 24-h period (**Figures 5B,C**). OxLDL treated LECs were able to form the branch structures, but by 24 h the structures had collapsed (**Figures 5B,C**). To determine if these dietary constituents were inducing transcriptional changes in the LECs we performed qRT-PCR on the hLECs and evaluated the transcript abundance of IL13 (**Figure 5D**) because the IL13 pathway was upregulated in LECs from people with end stage NASH (**Figure 5A**) and IL13 has been shown to cause defects in lymphatic branching and inhibit PROX1 expression (35). Interestingly, we found that IL13 was upregulated only in LECs that were treated with oxLDL, but not PA (**Figure 5D**). Consistent with LEC structure collapse, oxLDL treatment resulted in the decreased expression of PROX1 and the PROX1 dependent gene, FLT4 (VEGFR3) (**Figure 5D**). This is in contrast to PA which did not affect PROX1 expression. We next asked if IL13 protein levels were increased after oxLDL, PA or interferon alpha. Interferon signaling is significantly increased in HCV while IL13 signaling is not. We found using flow cytometry that there is a significant increase in protein expression of IL13 in hLECs treated with oxLDL, but not PA or IFN **(Figures 5E,F)**.

These data demonstrate that oxLDL can induce transcriptional and functional changes in LECs in vitro that are similar to the signaling pathways we observed in patients with NASH. Thus, IL13 signaling in LECs from patients with NASH could be caused by increased levels of oxLDL in the liver.

### OxLDL Uniquely Induces IL13 Production by Liver LECs in vivo

Above we demonstrated that the IL13 signaling pathway is activated in LECs of people with NASH (**Figure 3**) and increased IL13 gene and protein expression in vitro when LECs were treated with oxLDL (**Figures 5D–F**). We next asked if LECs in the liver and LN of mice treated with oxLDL were able to produce IL13 protein in vivo. To answer this question, we intravenously injected C57BL/6 mice with fluorescently labeled, oxLDL or the interferon inducing toll like receptor agonist, polyI:C (as an inflammatory control that should not induce IL13). To determine if these stimuli resulted in the production of IL13 by liver and/or lymph node (LN) LECs we directly measured production of cytokines in vivo 6 days post-injection **(Figure 6A)**. Using an in vivo Brefeldin A assay (25, 37, 65), we found that acute stimulation with oxLDL, but not polyI:C elicited the production of IL13 by liver LECs **(Figure 6B)**. Interestingly, while the LECs in the skin draining LN were able to take up oxLDL, they did not produce IL13 (**Figure 6**). These findings were confirmed using Balb/c mice that have been engineered to express YFP under the control of the IL13 promoter (IL13-YFP) **(Supplementary Figure 5)**. These findings support our conclusions that liver LECs directly respond to oxLDL by producing IL13 and that liver LECs have a unique functional response to dietary stimulation compared to lymph node LECs.

#### DISCUSSION

The role of lymphatic vessels in normal and disrupted liver homeostasis has largely been ignored. Previous studies have demonstrated an increase in lymphatic vessel-like structures in the liver during chronic viral infection and in the setting of portal hypertension (29, 66). Others have proposed that the ascites associated with chronic liver disease may be a consequence of lymphatic dysfunction or increased lymphatic permeability (13). Furthermore, altered lymphatic function in sites peripheral to the liver has been documented in humans and animal models of obesity, infection, and hypercholesterolemia (18–20, 67). These findings seem to link liver function and lymphatic function, however even recent studies utilizing single cell RNA sequencing to evaluate liver cell populations or even specifically liver endothelial cell populations have failed to identify lymphatic endothelial cells (26, 27). This is likely due to the low frequency of lymphatic endothelial cells in normal human livers and the inability to maintain LEC viability or distinguish these populations for downstream transcriptional profiling. Thus, the precise identification of and transcriptional profile of liver lymphatic vessels in steady state and during chronic liver disease had yet to be achieved. In this study we aimed to understand the lymphatic system in the non-diseased human liver and in the setting of chronic liver disease.

We have previously developed methodology to evaluate liver LECs by flow cytometry (38). In this manuscript we demonstrate a strategy that utilized both flow cytometric sorting and singlecell mRNA sequencing to directly analyze the transcriptional profile of LECs from the liver during steady state and disease. As evident from our data **(Figure 2B)** our flow cytometric sorting strategy does not result in a pure population of LECs but rather an enrichment of these cells. However we do demonstrate that transcriptionally the markers PDPN, PROX1, VEGFR3, CCL21, and LYVE-1, when combined together, adequately label LECs and no other cell type in the liver expresses all of these markers. We were intrigued to find that the expansion of the LEC population in the liver was a result of active cell cycle and cell division suggesting that these cells are actively responding to accommodate the inflammation associated with disease. This expansion of LECs was a direct consequence of the increased expression of pro-proliferative and anti-apoptotic gene expression in LECs in the setting of chronic liver disease. Furthermore, LECs in diseased livers maintained high expression of the chemokine CCL21 suggesting that lymphatic vessels and lymphatic endothelial cells in particular may play an active role in immune cell recruitment, trafficking or programing during chronic liver disease.

When comparing different disease etiologies we found significant differences in the LEC transcriptional profile and pathways between NASH and HCV. Of the pathways that were differentially regulated we identified IL13 signaling as uniquely upregulated in LECs from individuals with end-stage NASH **(Figure 5** and **Supplementary Table 2)**. This pathway was interesting as IL13 has been identified as a pro-fibrogenic factor in the liver (52) as well as a factor involved in regulating lymphatic stability (35, 50). Indeed, our data points to a role for LECs in IL13 signaling through the direct stimulation of LECs with oxLDL. Our findings that IL13 is not produced by LECs either in livers from patients with HCV or in response to IFNα or polyI:C suggests that IL13 is not generally produced during inflammation. Instead, these findings suggest that IL13 production by LECs is a result of increased cholesterol, specifically oxLDL, found in the liver of patients with NASH. From these findings it is difficult to determine if release of IL13 from LECs results in either autocrine or paracrine signaling. However, our in vitro findings suggest that when IL13 is present, either by adding exogenous IL13 (35) or by inducing IL13 production by oxLDL, that LECs receive a signal to reduce PROX1 expression. Loss of PROX1 expression likely results in the decreased ability of LECs to maintain branched structures in vitro. Thus, we predict that while LECs receive signals to divide in order to accommodate the increased inflammation in the liver during disease, that in NASH the vessels become unstable and perhaps more permeable. These findings are intriguing as ascites is associated with chronic liver disease and may be due to increased permeability of the liver lymphatics (13). This is an important consideration when evaluating treatment options for patients with NASH compared to patients with HCV especially as NASH associated CLD is on the rise. Future studies will address whether IL13 production by LECs impacts liver specific cells such as hepatic stellate cells or is important for autocrine signaling within the LECs.

### ETHICS STATEMENT

All patients provided written and informed consent and the study was approved by the institutional review boards at the University of Colorado—Anschutz.

### REFERENCES

### AUTHOR CONTRIBUTIONS

BT and MB designed and executed experiments, analyzed results, and drafted the manuscript. JF performed experiments, analyzed the data, and critically reviewed the manuscript. AG, KR, RF, and JH designed experiments, analyzed single cell mRNA sequencing data and critically reviewed the manuscript. MK provided samples, designed experiments, and critically reviewed the manuscript. RS analyzed immunofluorescence data and critically reviewed the manuscript. HR provided samples and insightful discussion.

## FUNDING

This study was supported by funds from the GALIIP program, a grant from the National Institutes of Health (R01 AI121209) and the University of Colorado Department of Medicine Early Career Scholar/RBI Clinical Scholar Program to BT and a Gilead Sciences North American Liver Disease Research Scholars award to MB.

### ACKNOWLEDGMENTS

The authors thank members of the Consortium for Fibrosis and Translation (CFReT), GI and Liver Innate Immune Program (GALIIP), the Human Immunotherapy Initiative (HI3), and the RNA Bioscience Initiative (RBI) for support and tools used in this manuscript. Further, we would like to thank Kim Jordan and Angela Minic for acquisition and optimization of liver staining on the Vectra microscope and Rachael Dran for processing of explanted human livers at the time of transplant for downstream analysis. Finally, we would like to thank the Andrea Osypuk at the University of Colorado Biorepository Core facility for obtaining pathological samples used in this study.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu. 2019.01036/full#supplementary-material

biomarkers after virological cure in patients with chronic hepatitis. J Hepatol C. (2013) 59:675–83. doi: 10.1016/j.jhep.2013.05.015

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Tamburini, Finlon, Gillen, Kriss, Riemondy, Fu, Schuyler, Hesselberth, Rosen and Burchill. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Lymphatic Migration of Immune Cells

Henry R. Hampton1 and Tatyana Chtanova2,3 \*

*1 Institute for Systems Biology, Seattle, WA, United States, 2 Immunology Division, Garvan Institute of Medical Research, Sydney, NSW, Australia, 3 Faculty of Medicine, St. Vincent's Clinical School, University of New South Wales Sydney, Kensington, NSW, Australia*

Lymphatic vessels collect interstitial fluid that has extravasated from blood vessels and return it to the circulatory system. Another important function of the lymphatic network is to facilitate immune cell migration and antigen transport from the periphery to draining lymph nodes. This migration plays a crucial role in immune surveillance, initiation of immune responses and tolerance. Here we discuss the significance and mechanisms of lymphatic migration of innate and adaptive immune cells in homeostasis, inflammation and cancer.

Keywords: lymphatic, migration, neutrophils, T cells, dendritic cells

#### Edited by:

*Amanda W. Lund, Oregon Health & Science University, United States*

#### Reviewed by:

*Alanna Ruddell, University of Washington, United States Maria M. Steele, Oregon Health & Science University, United States*

#### \*Correspondence:

*Tatyana Chtanova<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Immunological Tolerance and Regulation, a section of the journal Frontiers in Immunology*

Received: *31 January 2019* Accepted: *08 May 2019* Published: *28 May 2019*

#### Citation:

*Hampton HR and Chtanova T (2019) Lymphatic Migration of Immune Cells. Front. Immunol. 10:1168. doi: 10.3389/fimmu.2019.01168*

#### INTRODUCTION

The lymphatic system transports fluids from the periphery back into the circulatory system (1) using a series of open-ended capillaries known as lymphatic vessels (2). This network can be exploited by pathogens to facilitate rapid spread throughout the host (3). To prevent pathogen dissemination and enable a fast targeted immune response, the lymphatic system possesses filterlike structures termed lymph nodes (LNs) (3), where innate immune cells, such as macrophages, neutrophils and dendritic cells (DCs) trap and kill pathogens (3) and activate the adaptive immune response (4).

There are two routes by which immune cells can enter LNs: leukocytes can arrive from the bloodstream by crossing high endothelial venules (HEVs) (5). Alternatively, tissue-resident immune cells can enter afferent lymphatic vessels and migrate to draining LNs (dLNs) (5–8). Cells of the innate immune system including DCs, neutrophils, monocytes as well as adaptive immune leukocytes, such as T and B cells use lymphatic vessels to migrate from tissues into LNs (6– 11). Lymphocytes exit LNs via efferent lymphatic vessels, and eventually return to the circulatory system by the thoracic duct (12), however, in this review we will focus on the mechanisms and consequences of immune cell migration via the afferent lymphatic system.

In vitro and ex vivo models including adhesion and transmigration assays and analysis of immune cell migration in explanted skin provided important mechanistic insight into leukocyte entry and migration within lymphatic vessels (13–17), while in vivo approaches allowed to examine this complex biological process in situ (**Table 1**). Historically, in vivo analysis of immune cell migration in afferent lymphatics involved direct transfer of immune cells into the skin, lymphatic cannulation, as well application of fluorescent sensitizers to the skin to label cells and induce inflammation (18). More recently photoconvertible transgenic mice have been utilized to track immune cell migration from the skin and tumors (6, 9, 19–23), while intravital imaging approaches, such as in vivo two-photon microscopy enabled direct visualization of immune cell migration in lymphatic vessels (6, 16, 24, 25).

TABLE 1 | Methods for investigating immune cell migration *via* afferent lymphatic vessels.

### LYMPHATIC MIGRATION OF INNATE IMMUNE CELLS

#### Dendritic Cells

There are two distinct DC populations: plasmacytoid, which produce high amounts of type 1 interferon, and conventional DCs (cDCs) (26). Upon sensing inflammatory stimuli, cDCs enter lymphatic vessels and migrate to LNs (26, 27). They carry antigens (8) and pathogens including viruses (28, 29), spores (30) and bacteria (31–33) from the site of infection to LNs, while DC-mediated transport of innocuous antigens regulates tolerance (34). In dLNs DCs present antigen to CD4+ T cells, or cross-present to CD8+ T cells, thereby regulating adaptive immune responses (26). DC migration from the periphery has been discussed extensively in several recent reviews (27, 35). Here we provide a brief overview of the mechanisms of DC migration via lymphatic vessels (**Figure 1**).

The most important regulator of DC migration is the chemokine receptor CCR7. Consistent with this, CCR7-deficient DCs show a 90 percent reduction in migration from the periphery in response to inflammatory stimuli (10, 36). An elegant intravital microscopy study demonstrated that CCR7 is required for the LPS-induced directed migration of DCs toward lymphatic vessels and subsequent transmigration (25). DCs also use CCR7 for trafficking to dLNs from the lamina propria (37), lung (34), and skin (23) under homeostatic conditions. Interestingly, CCR7-dependent DC migration decreases lymphatic permeability (38), indicating bidirectional communication between the lymphatic network and immune cells.

Lymphatic vessels express CCR7 ligand, CCL21 (25, 39– 41), which is required for DC trafficking from skin to LNs under homeostatic (41) and inflammatory (42) conditions. Imaging studies have provided important insight into the role of CCL21 in DC migration. Firstly, the size of the CCL21 gradient, and distribution of lymphatic vessels, indicates that most skin DCs are able to sense CCL21 gradients (41). Secondly, DCs enter lymphatic vessels at sites of high CCL21 expression (25), suggesting that CCL21 directly regulates entry into lymphatics. Finally, intravital microscopy has revealed that CCL21 also enhances DC migration within lymphatic vessels (40). Collectively, these observations suggest that CCL21 regulates multiple steps in the lymphatic migration of DCs. In contrast, the other CCR7 ligand, CCL19, appears to be dispensable for DC lymphatic trafficking (42).

Inflammatory mediators regulate DC lymphatic migration (26). The cytokines Interleukin-1β (IL-1β) and Tumor Necrosis Factor-α (TNF-α) promote inflammation-induced DC migration to LNs (43–45). Furthermore, the lipid prostaglandin E2 increased CCR7 expression on DCs, augmenting migration towards CCL19 and CCL21 in vitro (46). Additional regulators of CCR7-mediated migration include the cell surface molecules

CD37, CD38, and CD47 which enhance DC movement toward CCR7 ligands and migration to dLNs (15, 47–50). In contrast, immunosuppressive molecules including IL-10 (51), TGF-β (52, 53) and the anti-inflammatory lipid Resolvin E1 (54) can inhibit DC trafficking.

In addition to CCR7, a number of other chemokine receptor/ligand pairs have been implicated in lymphatic DC migration. CXCR4/CXCL12 and CX3CR1/CX3CL1 enhance DC trafficking from inflamed skin (55, 56). The role of CCR8 is less clear with CCR8-deficient mice displaying reduced lymphatic migration of DCs following an injection of latex beads (57), but enhanced migration of DCs following FITC painting (58), suggesting that CCR8 plays a limited, or stimulus-specific, role in this process.

Intravital imaging and FITC-painting experiments have demonstrated that integrins, and integrin signaling are required for inflammation-induced DC migration to dLNs (14, 59, 60). However, DCs from mice lacking all integrins were able to migrate to LNs when injected into resting skin (61), indicating that integrins are important for DC migration in response to inflammation but dispensable for steady state DC egress. Accordingly, inflammation increases the expression of integrin ligands on lymphatic endothelial cells (LECs) (14). DC-expressed L1 cell adhesion molecule guides transendothelial migration of DCs thereby promoting trafficking to dLNs (17). A recent study demonstrated that interactions between LEC-expressed LYVE-1 and hyaluronan on the DC plasma membrane mediated DC adhesion and transmigration across LECs and subsequent migration to dLNs (13).

Sphingosine-1-phosphate (S1P), a lipid mediator of leukocyte egress from lymphoid organs (62), has been implicated in DC trafficking from the skin and lung (33, 63–65). However, in mice that lack S1P in lymphatic fluid, but not blood, the migration of adoptively transferred DCs to dLNs was comparable to that seen in wild-type mice (66). These results, and the fact that there are five S1P receptors (63), suggest that further experiments are required to uncover the precise role of S1P signaling in DC migration.

In contrast to cDCs, the lymphatic migration of pDCs is poorly understood. While one study reported that adoptively transferred pDCs migrated to dLNs from ovine skin (67), another showed that pDCs were not detected in the lymph of rats (68). However, pDCs transported harmless inhaled antigen from murine lungs to the mediastinal LN where they suppressed T cell activation, suggesting that pDC migration may play a role in preventing inflammation (69).

#### Neutrophils

Neutrophils are the first immune cells recruited to sites of inflammation, where they kill pathogens and release mediators that recruit other leukocytes (70, 71). Until recently neutrophils were thought to die at inflammatory foci. However, several groups, including ours, have shown that neutrophils can enter tissue lymphatic vessels and migrate to dLNs from the site of inflammation (6, 72–74).

Intravital imaging of inflamed mouse skin has enabled direct visualization of neutrophil migration within lymphatic vasculature (**Figure 2A**) (6, 72). However, in comparison to DCs, the significance and extent of neutrophil lymphatic migration are incompletely understood. Cannulation experiments have demonstrated that inflammation leads to a dramatic increase in neutrophils in ovine afferent lymph (8, 75, 76). Furthermore, neutrophils can transport antigens and microorganisms (**Figure 2B**) from the site of infection to LNs (6, 8, 77). Accordingly, inhibiting neutrophil lymphatic migration reduced early lymphocyte proliferation (6). Notably, a recent study did not detect substantial lymphatic migration of neutrophils in response to Staphylococcus aureus (S. aureus) (78). This likely highlights the fact that most neutrophils arrive in dLNs from the circulation via HEVs in response to bacteria already in dLNs, while a smaller population of neutrophils migrates directly from the site of inflammation to dLNs via afferent lymphatics. However, since neutrophils are the first innate immune cell subset to arrive in the LN from inflamed tissues, and often carry microbes, neutrophil lymphatic migration can exert considerable influence on the subsequent adaptive immune response (6, 77, 79).

Lymphatic migration of neutrophils could potentially be exploited by pathogens to enhance dissemination, since some microorganisms including the bacterium S. aureus can survive inside neutrophils (80). Consistent with this, injection of Leishmania major-containing neutrophils was sufficient to establish infection in mice, while depleting neutrophils reduced Leishmania burden when the pathogen was injected into the skin (81). Neutrophils also transported live Mycobacterium bovis bacille Calmette-Guérin from the skin to dLNs (77). In Toxoplasma gondii infection neutrophils removed the macrophages that line the subscapular sinus of the LN (82), however, it is not clear whether this favors pathogen control or spread.

CCR7 appears to be less important for neutrophil lymphatic migration than for that of DCs. Although it was required for neutrophil entry into lymphatic vessels in response to TNF-α and Complete Freund's Adjuvant (CFA) (72), and for CFA-driven migration from skin to LNs (83), neutrophil migration from the skin to dLNs in response to S. aureus was CCR7-independent (6). This suggests that the requirements for neutrophil trafficking vary depending on the stimulus and additional molecules may play key roles in guiding this migration.

The chemokine receptor CXCR4 regulates neutrophil migration from the bone marrow into the circulation (84) and may also play a role in their lymphatic migration. Inhibiting CXCR4 decreased neutrophil trafficking in response to immune complexes and S. aureus (6, 73). However, CXCR4 was not required for neutrophil entry into lymphatic vessels in response to CFA, as revealed by confocal imaging (72), again highlighting differences in neutrophil trafficking in response to distinct stimuli.

The cell surface receptor CD11b, which is involved in neutrophil recruitment from the vasculature into tissues (85), is emerging as a major regulator of neutrophil migration via lymphatics since neutrophil migration from inflammatory foci to LNs is substantially reduced when CD11b is inhibited (6, 73, 74). Intravital imaging demonstrated that blocking CD11b or its ligand ICAM-1 impaired neutrophil intraluminal crawling within lymphatic vasculature following CFA injection by reducing neutrophil speed and directionality (72). Likewise, inhibiting CD11b and ICAM-1 reduced neutrophil entry into lymphatic vessels and diminished egress from the skin in response to Mycobacterium bovis (74). Lymphocyte Functionassociated Antigen (LFA-1), which binds to ICAMs and is involved in neutrophil entry into tissues from the circulation, was required for neutrophil migration via afferent lymphatics in response to immune complexes (73) but not S. aureus (6).

Inflammatory cytokines may enhance neutrophil entry into lymphatics. TNF-α promoted neutrophil entry and crawling within lymphatic vessels in mouse cremaster muscle (72). However, since inflammatory cytokines also control neutrophil recruitment to sites of inflammation and lifespan, identifying a distinct role for these molecules in neutrophil lymphatic migration requires further investigation.

#### Monocytes and Macrophages

Monocytes are circulating leukocytes that phagocytose and kill bacteria and fungi and regulate the activity of other immune cells via cytokine release (86–88). They can also differentiate into DC and macrophage subsets (89). Several studies have demonstrated that monocytes egress tissues via afferent lymphatic vessels and transport antigen to dLNs (7, 8, 90–92). Once there, monocytes may present and cross-present antigens since a subcutaneous injection of antigen-pulsed monocytes induced the proliferation of antigen-specific CD4+ and CD8+ T cells (91). The molecular mechanisms controlling monocyte migration via lymphatic vessels are yet to be identified. However, CCR7 may be important, since CCR7-deficient LPS-primed monocytes failed to migrate from the footpad to the popliteal LN (91). Accumulating evidence suggests that macrophages can also migrate from inflammatory lesions to dLNs (93–95) and that α1β1 integrin may limit macrophage egress via afferent lymphatics (93).

### LYMPHATIC MIGRATION OF ADAPTIVE IMMUNE CELLS

#### T Cells

T cells possess a rearranged T cell receptor which includes either αβ or γδ polypeptides (96). While αβ T cells are more abundant, γδ T cells are enriched in epithelial and mucosal tissues where they act as the first line of defense against pathogens. One of the main functions of CD8+ T cells is to kill infected cells (97), while CD4+ helper T cells secrete cytokines and regulate the function of other immune subsets (98). Photoconversion experiments (22), along with lymphatic cannulation (99), have demonstrated that effector, rather than naïve, T cells comprise the majority of lymph migrating T cells under homeostatic (22, 99) and inflammatory conditions (22, 100). This migration plays an important role in immune surveillance and in resolution of inflammation (18, 101–103).

Like DCs, T cells use CCR7 to migrate to LNs under homeostatic and inflammatory conditions. Following antigen challenge, T cells overexpressing CCR7 were preferentially lost from the lung and accumulated in the mediastinal LNs (104), while CCR7-deficient T cells failed to migrate from the footpad to the popliteal LN (11). However, the need for CCR7 in T cell migration might be context dependent, as T cells used CCR7 for trafficking from acute, but not chronically, inflamed skin (100). Tumor-infiltrating T cells could also emigrate to dLNs independently of CCR7 (9).

The lipid S1P, which promotes αβ T cell exit from LNs (62), can also mediate their migration via afferent lymphatics. Consequently, antagonizing S1P receptors led to T cell accumulation near skin lymphatic vessels and reduced migration to dLNs (100, 105). LEC-expressed macrophage mannose receptor (MR) and the cell surface molecule CD44, which interacts with MR, promoted T cell lymphatic migration by increasing T cell adhesion to lymphatic vessels (106, 107). Another LEC-expressed protein, CLEVER-1, was also demonstrated to be important for T cell migration via afferent lymphatics (108). Additionally, intravital imaging has shown that LFA-1 and its ligand ICAM-1, increased T cell velocity within afferent lymphatic vessels thereby promoting T cell migration to dLNs (16).

T cell egress from tissues to dLNs can either promote inflammatory responses or suppress them. For example, lymphatic migration of Regulatory T (Treg) cells may suppress allograft rejection (103). Likewise, CCR7-deficient Treg cells failed to migrate to the draining LN and accumulated in the skin, reducing skin inflammation during a delayed-type hypersensitivity reaction (101). Conversely, overexpression of CCR7 on antigen-specific Th1-cells enhanced their egress to dLNs and led to faster resolution of the inflammatory response in the skin (102).

Like αβ T cells, γδ T cells can migrate from the skin (23, 95, 109) and tumors (9) via lymphatic vessels to dLNs and comprise a large proportion of the cells in bovine lymph (110). Photoconversion experiments have demonstrated that murine γδ T cells can migrate from the skin to dLNs in the absence of CCR7 (23). Similarly, bovine γδ T cells can egress tissues independently of this receptor (111). The consequences of γδ T cell lymphatic migration are poorly understood, though it may enhance CD8+ T cell proliferation (23).

## B CELLS

Cannulation experiments in sheep (112) and photoconversion experiments in mice (95), suggest that B cells use afferent lymphatic vessels to migrate from tissues to dLNs. The mechanisms of this migration are not yet known, however, at least in chronic inflammation, B cell egress may be independent of S1P and requires CCR7 (100). Similarly to T cells, blocking CLEVER-1 reduced B cell migration to dLNs (108).

### LYMPHATIC MIGRATION OF IMMUNE CELLS IN DISEASE

The importance of immune cell migration via lymphatics in host defense is illustrated by the observations that mice lacking CCR7 are susceptible to microbial and viral infections (113– 115). On the other hand, lymphatic migration of immune cells may also augment autoimmunity since preventing immune cell trafficking from the meninges to the cervical LNs reduced the severity of EAE (116). Furthermore, higher densities of lymphatic vessels in transplanted corneas (117) and kidneys (118) were associated with rejection, while preventing DC migration to the dLN by blocking Vascular Endothelial Growth Factor C (VEGF-C) improved corneal transplantation outcomes (119). Interestingly, in mice, obesity was associated with decreased lymphatic function and reduced immune cell migration to dLNs (120), suggesting that obesity may be linked to decreased immunity. CCR7 as well as its two ligands, CCL19 and CCL21, have been identified in mouse and human atherosclerotic lesions (121), consistent with accumulating evidence of a role for immune cell lymphatic migration in heart disease (122–125).

Lymphatic vasculature also plays a crucial role in tumor immunity by enabling transport of antigens from tumors to dLNs and egress of immune cells (9, 126). Lymphatic vessels can also serve as conduits for tumor cell spread (1). Their dual role in cancer is highlighted by the findings that many tumors overexpress VEGF-C, which promotes the growth and survival of LECs (127, 128) leading to increased LN metastasis (128–130). Furthermore, a recent study demonstrated that IFNγinduced PD-L1 expression by LECs may dampen anti-tumor immunity by limiting cytotoxic CD8+ T cell accumulation in melanoma (131). On the other hand, overexpression of VEGF-C in a mouse melanoma model increased DC migration to dLNs (132). Consistent with an increase in lymphatic migration in cancer, enhanced trafficking of adoptively transferred B and T lymphocytes from footpads to dLNs was observed in melanomabearing mice (133).

Similarly to DC migration from the periphery, the DCdependent transfer of antigen from B16F10 melanoma to the dLN required CCR7. This correlated with an increase in CD8+ T cell priming and a reduction in tumor growth (126). Overexpression of TGF-β1 in a model of squamous cell carcinoma reduced DC trafficking to dLNs, which led to

#### REFERENCES

an increase in LN metastasis (53). However, since CCR7 and the TGF-β1 receptor are not restricted to DCs (134), other immune cells may also contribute to these effects on tumor growth and metastasis. In contrast to DCs, photoconversion experiments demonstrated that tumor-infiltrating T cells do not require CCR7 to migrate to dLNs via afferent lymphatics (9).

#### CONCLUDING REMARKS

Lymphatic migration of immune cells presents opportunities for control of immune responses in infection and homeostasis. However, with the exception of DCs and T cells, the mechanisms controlling lymphatic migration of immune cells remain poorly understood. New tools, such as photoconversion and intravital imaging are poised to provide novel insight into the migration of previously overlooked immune subsets. A better understanding of the distinct mechanisms guiding lymphatic migration of specific immune subsets may suggest new approaches for treatment of cancer, autoimmunity and excessive inflammation.

#### AUTHOR CONTRIBUTIONS

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

#### FUNDING

This work was funded by the National Health and Medical Research Council (NHMRC) project grant GNT1106043 (TC) and a Postdoctoral Fellowship from the Global Lyme Alliance (HH).

Salmonella enterica serovar typhimurium and limit systemic disease in mice. Infect Immun. (2009) 77:3170–80. doi: 10.1128/IAI.00272-09

CD14+ CD16+ monocytes, promote Th17 responses to Candida albicans. Eur J Immunol. (2011) 41:2915–24. doi: 10.1002/eji.201141418

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Hampton and Chtanova. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# PD-1 Blockade During Post-partum Involution Reactivates the Anti-tumor Response and Reduces Lymphatic Vessel Density

Beth A. Jirón Tamburini 1,2 \*, Alan M. Elder 3,4, Jeffrey M. Finlon1 , Andrew B. Winter 1 , Veronica M. Wessells 3,4, Virginia F. Borges 3,4 and Traci R. Lyons 3,4 \*

1 Division of Gastroenterology and Hepatology, Department of Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, United States, 2 Department of Immunology and Microbiology, Department of Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, United States, 3 Division of Medical Oncology, Department of Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, United States, 4 Young Women's' Breast Cancer Translational Program and University of Colorado Cancer Center, Aurora, CO, United States

#### Edited by:

Ursula Grohmann, University of Perugia, Italy

#### Reviewed by:

Lianjun Zhang, Suzhou Institute of Systems Medicine (ISM), China Cornelia Halin, University of Zurich, Switzerland

#### \*Correspondence:

Beth A. Jirón Tamburini<EMAIL_ADDRESS>Traci R. Lyons<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Immunological Tolerance and Regulation, a section of the journal Frontiers in Immunology

Received: 07 December 2018 Accepted: 23 May 2019 Published: 11 June 2019

#### Citation:

Tamburini BAJ, Elder AM, Finlon JM, Winter AB, Wessells VM, Borges VF and Lyons TR (2019) PD-1 Blockade During Post-partum Involution Reactivates the Anti-tumor Response and Reduces Lymphatic Vessel Density. Front.  Additionally, post-partum patients have increased tumor-associated lymphatic vessels and LN involvement, including when controlled for size of the primary tumor. In pre-clinical, immune-competent, mouse mammary tumor models of post-partum breast cancer (PPBC), tumor growth and lymphogenous tumor cell spread occur more rapidly in post-partum hosts. Here we report on PD-L1 expression by lymphatic endothelial cells and CD11b+ cells in the microenvironment of post-partum tumors, which is accompanied by an increase in PD-1 expression by T cells. Additionally, we observed increases in PD-L1 and PD-1 in whole mammary tissues during post-partum mammary gland involution; a known driver of post-partum tumor growth, invasion, and metastasis in pre-clinical models. Importantly, implantation of murine mammary tumor cells during post-partum mammary gland involution elicits a CD8+ T cell population that expresses both the co-inhibitory receptors PD-1 and Lag-3. However, upon anti-PD-1 treatment, during post-partum mammary gland involution, the involution-initiated promotional effects on tumor growth are reversed and the PD-1, Lag-3 double positive population disappears. Consequently, we observed an expansion of poly-functional CD8+ T cells that produced both IFNγ and TNFα. Finally, lymphatic vessel frequency decreased significantly following anti-PD-1 suggesting that anti-PD-1/PD-L1 targeted therapies may have efficacy in reducing tumor growth and dissemination in post-partum breast cancer patients.

 Additionally, post-partum patients have increased LN involvement and peritumor lymphatic vessel density (LVD) (2–4). In 2010, Asztalos et al. identified alterations to gene expression patterns in normal mammary tissues from post-pregnant women that persist up to 10 years post-partum in comparison to nulliparous women (5). Specifically, they observed changes to genes involved in inflammation, angiogenesis, extracellular matrix (ECM), and breast cancer; suggesting that the mammary microenvironment after pregnancy may be conducive to malignancy. Consistent with this hypothesis, recent pregnancy can increase a woman's risk for developing breast cancer for more than 20 years following childbirth (6–8). Normal mammary gland development associated with pregnancy consists of a period of expansion of the mammary epithelium, to prepare the gland for lactation, followed by full differentiation of the mammary epithelium into milk secreting cells. Following lactation, or pregnancy in the absence of lactation, post-partum mammary gland involution occurs to return the mammary epithelium to the pre-pregnant state. Previous studies of normal post-partum mammary gland involution in rodents and women have revealed that attributes of this normal developmental process are similar to those observed in breast tumors (9–12). These attributes include establishment of a tissue microenvironment that is characterized by ECM remodeling, increased LVD, immune infiltration and evidence of immune suppression (3, 13–15). Additionally, non-metastatic tumor cells implanted into this tissue microenvironment in pre-clinical models grow and invade more rapidly, seed micro-metastases, and are durably altered to a more invasive and metastatic state; suggesting that post-partum involution can drive intrinsic, prometastatic changes, in tumor cells (3, 16). These findings predict that the process of normal involution may drive post-partum breast cancer (PPBC) metastasis.

Post-partum mammary gland involution, induced by weaning, has been extensively studied in rodents where it is characterized by two phases of tissue remodeling. The first, known as the reversible phase, is triggered by milk stasis and results in death of the secretory mammary epithelium (17, 18). The second phase, known as the irreversible phase, consists of stromal remodeling and repopulation of the gland with adipocytes. Insight into molecular programs that govern this developmental process in mice has been gained through gene expression profiling studies on whole mammary tissues where roles for death receptors and immune mediators were revealed (10, 11, 19). Additionally, influx of immunosuppressive Foxp3+ regulatory T cells and IL-10+ macrophages occurs during involution resulting in effector T cell suppression (13). Furthermore, M2-like or tissue repair type macrophages and macrophages with pro-lymphatic phenotypes are evident (3, 20, 21). As epithelial cell apoptosis during involution likely results in the increased presentation of self-antigens (22) it is not surprising that numerous cell types initiate an immune-tolerant microenvironment and, consequently, an environment that could be primed for post-partum tumor growth. Importantly, LVD also increases during mammary gland involution, presumably to promote the clearance of increased fluid—generated by milk stasis, apoptotic cell debris, and immune cell infiltrates. However, we have recently shown that the mammary lymphatics that arise during post-partum involution are also capable of transporting tumor cells to distant lymph nodes during the active phase of tissue remodeling and that post-partum patients are enriched for lymph node involvement (2, 21). These studies suggest that metastatic seeding via lymphatics may be an early event in post-partum patients, which may account for the increased metastasis observed (21).

Tumor-associated lymphatic vessels not only promote dissemination (23–27), but have recently been shown to reduce anti-tumor immune responses in tumor models (28, 29). Lymphatic endothelial cells (LECs) normally promote peripheral immune tolerance in the lymph node during homeostasis. Specifically, lymph node LECs express PD-L1 to inhibit autoreactive T cells via engagement of the inhibitory receptor Programmed Death-1 (PD-1) (30–34). In addition, inhibitory receptor expression of PD-1 is also an important marker of T cell effector function. However, upregulation of multiple inhibitory receptors, such as PD-1, Lag-3, and TIGIT can occur as a result of chronic antigen stimulation and lead to non-responsive T cells that fail to successfully clear the pathogen (35–40). In the cancer setting, a similar phenomenon occurs as tumor-infiltrating T cells upregulate multiple co-inhibitory receptors and are limited in their ability to produce multiple effector cytokines (such as IFNγ and TNFα) (41), making them less polyfunctional and unable to clear the tumor (42). Recently, several studies have pointed to a role for tumorassociated lymphatic and/or macrophage expression of PD-L1 in contributing to T cell inhibition (28, 29, 43, 44). In addition, we and others have published that PD-L1 expression by LECs promotes their survival during an immune response and a role for PD-L1 expression in promoting tumor cell survival has been demonstrated (45–48). Thus, PD-L1 clearly plays a role in promoting cell survival and immunosuppression in multiple cell types present in the tumor microenvironment (TME).

Since T-cell infiltration, immune suppression, macrophage infiltration, and lymphangiogenesis have all been described during post-partum involution (3, 13, 21), we sought to determine whether T cell expression of co-inhibitory receptors allows for immune evasion by tumor cells during post-partum involution and whether this mechanism could be reversed with anti-PD-1 treatment. In this manuscript, we investigate the immune regulatory state of the mammary tissue during postpartum involution and in tumors implanted during involution (post-partum tumors). We demonstrate that PD-L1 and PD-1

**Abbreviations:** LEC, Lymphatic endothelial cell; PDPN, Podoplanin; PD-1, Programmed Death-1; PD-L1, Programmed Death-Ligand 1; Lag-3, Lymphocyteactivation gene-3; LN, Lymph node; LVD, Lymphatic Vessel Density; TME, Tumor Micro Environment.

are a part of the involution program and show increased expression of PD-L1 on lymphatic endothelial cells, and cells of myeloid lineage, as well as PD-1 on T cells during mammary gland involution and in post-partum tumors. Importantly, we demonstrate that this mechanism is an integral part of the tumor promotional program effects of involution. Administration of an anti-PD-1 antibody to mice during involution, when the tumors are established, reduced growth of the post-partum tumors to levels observed in nulliparous hosts. Upon evaluation of the tumor infiltrating CD8+ T cells we discovered co-expression of two inhibitory receptors, PD-1 and Lag-3, that were specific to tumors established during involution. Following treatment with anti-PD-1, the PD-1+Lag-3+ inhibitory CD8+ T cell population disappeared and the frequency of total CD8+ T cells and polyfunctional CD8+ T cells increased significantly suggesting a reversal of at least some of the immunosuppressive effects of involution. Surprisingly, anti-PD-1 treatment also reduced tumor/involution associated LVD suggesting this treatment may have implications for stopping lymphatic-mediated metastasis. Our results lay the ground work for additional studies aimed at uncovering the potential role of the mammary LECs during involution, and in the tumor microenvironment, in promoting immunosuppression and suggest a potential treatment option for PPBC patients.

### MATERIALS AND METHODS

#### Animal Studies

All animal procedures were approved by the University of Colorado Anschutz Medical Campus Institutional Animal Care and Use Committee. BALB/c and C57Bl/6 (age 6–8 weeks) were obtained from Charles River Laboratories. Mice were crossbred for involution studies; C57Bl/6 female mice were bred in triad with BALB/c males and BALB/c females were bred with C57Bl/6 males. Age-matched nulliparous females were used as controls. At 10–14 days post-parturition, post-partum mammary gland involution was instigated in the bred females by force-weaning the pups. For normal involution studies, mammary glands, and draining lymph nodes (inguinal lymph nodes) were harvested from nulliparous and involution day 6 mice. Tumor studies for the 66cl4 and E0771 mouse mammary carcinoma models were performed as previously described (21) with the tumors, mammary glands, and lymph nodes being taken for flow cytometry, immunohistochemistry, and downstream biochemical analyses. For the E0771 PD-1 intervention studies, 250,000 tumor cells were injected into the number 4 mammary glands of either nulliparous or involution day 1 C57Bl/6 dams. Tumor sites were palpated daily (E0771) or twice weekly (66cl4) for tumors. Calipers were used to take measurements and the tumor volumes were calculated using length x width x width × 0.5. Additionally, 66cl4 tumor cells were luciferase and GFP tagged allowing for tumors to be detected using the Xenogen 200. Once tumors became measurable, mice were randomized into control or treatment groups and injected with 250 µg of either isotype control (anti-IgG2a [clone 2A3; Bio X Cell cat. #BP0089]) or anti-PD-1 (clone RMP1-14; Bio X Cell cat. #BP0146) antibody, respectively. Injections were administered intra-peritoneally every third day. Tumor studies were ended based on primary tumor cell growth or ulceration at 3–4 weeks post injection (66cl4) or 1–2 weeks post injection (E0771). In vivo studies were performed in triplicate with pooled or representative data shown.

### Mammary Gland Processing and Staining (IHC)

Mammary glands were harvested and placed into 10% neutral buffered formalin for 48 h. After 48 h, tissues were moved to 70% EtOH, processed, and stained for LYVE-1 as previously described (3, 14, 16, 21, 49).

### Lymphatic Vessel Density Quantification

Lymphatic vessel density (LVD) was performed as previously described (3, 21). Briefly, slides stained for PDPN (D2-40) or LYVE-1 were scanned into the Aperio ImageScope software. Lymphatic vessels were counted in the tumor-adjacent tissue (peri-tumor region) and LVD was quantified as the number of lymphatic vessels per area of tissue.

#### Human Tissue Acquisition

Research using de-identified human breast tissue (**Supplemental Table 1**) was conducted under a protocol deemed exempt from subject consent as approved by the Colorado Multiple Institution Review Board (COMIRB) and tissues were acquired by Virginia Borges as previously reported (1). Dr. Borges obtained written informed consent from the patients, the studies were conducted in accordance with recognized ethical guidelines (e.g., Declaration of Helsinki, CIOMS, Belmont Report, U.S. Common Rule), and the studies were approved by an institutional review board.

#### Staining of Human Tissue Using Vectra

Four-micron thick sections were taken from Formalin Fixed Paraffin Embedded tissue, dewaxed in xylenes and rehydrated. Slides were placed in 10% NBF for 20 min for extra fixation, rinsed with DI water, then submerged in Target Retrieval Solution pH6 (Dako cat# S1699) and placed in a pressure cooker for 20 min. Slides were rinsed with Dako wash buffer (Dako cat# K8000), blocked for 10 min with Perkin Elmer Diluent/Block (Perkin Elmer cat# ARD1001EA), then sequentially stained for the following markers: PD-L1 (clone E1L3N), PD-1 (clone NAT105;), PDPN (clone D2-40), and CD68 (clone KP1). Incubation time for all primary antibodies was 1 h at room temperature. Slides were rinsed and stripped in Target Retrieval Solution in between every primary. Slides were then incubated in Perkin Elmer Opal Polymer HRP Mouse+Rabbit secondary (cat# ARH1001EA) for 30 min at room temperature, followed by a 10 min incubation in Opal Fluorophore reagents (Perkin Elmer). After the final stain, Spectral DAPI (Perkin Elmer cat# FP1490) was applied to slides for 5 min, then slides were rinsed and coverslipped with ProLong Diamond Antifade Mountant (Thermo cat# P36970). Multispectral imaging was then performed using the Vectra 3 Automated Quantitative Pathology Imaging System (Perkin Elmer). Whole slide scans were collected using the

10x objective and 5–10 regions were selected for multispectral imaging with the 20x objective. The multispectral images were analyzed with inForm software (Perkin Elmer) to unmix adjacent fluorochromes, subtract autofluorescence, segment the tissue into lymphatic vessels and non lymphatic vessels, segment the cells into nuclear, and membrane compartments, and to phenotype the cells according to morphology and cell marker expression. Cells with a PD-L1 threshold <0.95 were classified as PD-L1 negative while cells with a value >0.95 threshold were classified as PD-L1 positive using inForm software. To quantitate PD-L1 in lymphatics a blinded observer imaged 5–10 representative fields from the peritumor region that were positive for PDPN vessels by only the PDPN channel. For PDPN we also counted PD-L1+ lymphatic vessels by adding the PD-L1 channel and counted PDPN+PD-L1+ vessels as well as PDPN+PD-L1 vessels and calculated the percent positive per case, which was then normalized to area. PD-1+ cells were also counted in the same manner as PDPN+ vessels.

#### Flow Cytometry

Tumors were separated from the mammary gland. Both tumors and mammary glands were placed in six-well plates with 2 mL of Click's media without mercaptoethanol or L-glutamine (Irvine Scientific, Santa Ana, CA), where they were minced with scalpels, digested with 500 units/ml collagenase type II and IV and 20µg/ml DNase (Worthington Biochemical Corporation, Lakewood, NJ) and incubated for 1 h at 37◦C. The tissue suspension was then filtered through a 100µm strainer and washed with Click's. The filtered cells were centrifuged at 1,400 RPM for 5 min, the supernatant was removed, and the pellet was resuspended in 1 mL FACS buffer (500 mL 1x HBSS pH 7.4, 0.1% BSA, 0.02% sodium azide, up to 1L ddH2O). The tumor cells were stained with BD viability 510 dye prior to staining with CD45 (clone30-F11), CD8a APC/Cy7 (clone 53-6.7) (1:400), CD4 APC or PerCp-Cy5.5 (clone RM4-5) (1:300), PD-1 FITC or BV421 (clone 29F.1A12) (1:100), Lag-3 PerCP/Cy5.5 (clone C9B7W) (1:100), and/or CD11a FITC (clone M17/4) (1:200). The mammary glands were stained with BD viability dye 510 followed by CD45 APC-Cy7 or Pacific Blue (clone 30-F11) (1:300), CD31 Pacific Blue or PerCp-Cy5.5 (clone 390) (1:200), PDPN APC or PE-Cy7 (clone 8.1.1) (1:200), CD11b Pacific Blue or PerCp or FITC (clone M1/70)(1:400), F4/80 APC, APC-Cy7, PerCP-Cy5.5 or FITC (clone BM8) (1:100), PD-L1 PE, FITC, or BV421 (clone RMP1-30 or 29F.1A12) (1:200), and EpCAM PE-Cy7 or APC-Cy7 (clone G8.8) (1:100). Flow cytometry antibodies were purchased from Biolegend (San Diego, CA). CD8 T cells were identified from live, CD3+/CD8+, where they were further characterized by their expression of PD-1 and Lag-3. Lymphatic endothelial cells were identified from live, CD45-/EpCAM-, and CD31+PDPN+. Cells were run on the DakoCytomation CyAn ADP flow cytometer (Fort Collins, CO) or FACs Canto II, acquired using Summit software or Diva Software, and analyzed with FlowJo software (Tree Star, Ashland, OR). Geometric mean fluorescence intensity (gMFI) was calculated with FlowJo software.

### Intracellular Cytokine Staining

Cells were isolated from the tissue and treated with or without (unstimulated controls) phorbol 12-myristate 13-acetate (PMA) (20 ng/ml) (Sigma, St. Louis, MO) plus ionomycin (1 ug/ml) (Sigma, St. Louis, MO) for 4–6 h at 37 degrees in the presence of 2 ug/ml of brefeldin A (Adipogen, San Diego, CO) in RPMI+2.5% FBS. Cells were then stained with CD8, CD45, CD4, CD44, PD-1, and Lag-3 (as above) and incubated at 37◦C for 30 min. Following surface marker staining cells were fixed with 1% paraformaldehyde and 4% sucrose for 10 min in the dark at room temperature. Following fixation, cells were permeabilized with BD Perm Wash (BD Biosciences, San Jose CA) and stained for cytokines IFNγ (1:200) (APC; Biolegend clone XMG1.2) and TNFα (1:200) (FITC; Biolegend clone MP6-XT22). After washing cells were resuspended in FACs buffer (0.5% Bovine Serum Albumin and 0.1% Sodium Azide in PBS) and were run on an ADP Cyan. Gating was determined based on unstimulated controls. All antibodies were purchased from Biolegend (San Diego, CA).

#### TCGA RNASeq Analysis

Analysis was performed on cbioportal.org TCGA Breast provisional dataset using the co-expression tool and the RNA-Seq data.

#### Statistics

One-way ANOVA, unpaired t-test, and linear regression were run in the GraphPad Prism software, assuming normal distributions among independent samples. For **Figure 6**, Pearson and Spearman analysis was performed on cbioportal.org. P-values of <0.05 were deemed significant.

## RESULTS

### PD-L1 Expression and PD-1 T Cells Are Observed in Patients With PPBC and in Pre-clinical Models

To determine if the increased lymphatics (PDPN) that we observe in our patients with PPBC exhibit upregulation of PD-L1 and/or whether PD-1+ T cell infiltration occurs in the tumor microenvironment (TME) of PPBCs, we utilized multispectral imaging of the peri-tumor region in tissues from three different patients with PPBC, who were within 1-year (PPBC1), 3 years (PPBC2), and 4 years post-partum (PPBC3) (**Supplemental Table 1**). In comparison to three non-PPBC patients, who were all nulliparous, we observed increased PDPN+ LVD in the peri-tumor region from our PPBCs. We also observed frequent lymphatic vessel expression of PD-L1 (arrow) and that lymphatic vessels were frequently infiltrated with PD-L1 expressing tumor cells (asterisk), identified by their altered nuclear morphology. Furthermore, we also observed the presence of CD68+ macrophages that appear to express PD-L1 (+ symbol) as well as cells expressing PD-1 (arrowhead) in the surrounding areas (**Figure 1A** and **Supplemental Figure 1**). We quantitated PD-L1+ cells in the peritumor region and observed that total numbers of PD-L1+ cells per area did not differ between groups (**Figure 1B**), but that total PDPN+ vessel

FIGURE 1 | from A. (C) Number of PDPN+ vessels in the peritumoral region of the patients from A. (D) Number of PDPN+ vessels that are also PD-L1+ in the peritumoral region of the patients from A. (E) Number of PD-1+ cells in the peritumoral region of the patients from A. (F) Histogram of PD-L1 expression by LECs (CD45-EpCAM-CD31+PDPN+PD-L1+) from 66CL4 tumors implanted during mammary gland involution. Gray dotted line indicates a PD-L1 negative population (CD45+CD11b-F4/80-) that does not change. (G) gMFI of PD-L1 of LECs in tumor. (H) Histogram of PD-L1 expression by CD45+ CD11b+ cells from tumors implanted during mammary gland involution. Gray dotted line indicates a PD-L1 negative population (CD45+CD11b-F4/80-) that does not change. (I) gMFI calculated for PD-L1 from D. Data shown from animal experiments are from 1 representative experiment of 2 replicates with at least 4 tumors per group. Unpaired t-test: \*p < 0.05; \*\*p < 0.01. Scale bars are 100 microns in length.

density, as well as PDPN+PD-L1+ vessel density, were increased in our patients with PPBC compared to nulliparous controls (**Figures 1C,D**) suggesting that PD-L1 lymphatics are a part of the TME in patients with PPBC. Finally, we observe a significant increase in PD-1+ cells in the TME of our PPBC patients (**Figure 1E**).

Since we observed PD-L1 expression in cells of the TME from patients with PPBC, we next asked if PD-L1 expression was a characteristic of the TME of post-partum tumors in our murine model of PPBC. Using the 66cl4 isograft model where we have shown increased lymph vessel density (LVD) and lymph node metastasis in post-partum hosts (3), we examined post-partum tumor-associated LEC expression of PD-L1 in Balb/c mice. As previously observed, tumor cells implanted on day 1 of involution (involution group tumors) exhibited decreased latency and increased growth compared to nulliparous (**Supplemental Figure 2A**) (3, 13, 16). At study endpoint, 4 weeks post-injection, tumors were harvested, and populations were analyzed by flow cytometry (**Supplemental Figures 2B,C**). We observed an increase in the fluorescence intensity of PD-L1 on CD45-Epcam-CD31+PDPN + tumor associated LECs (**Figures 1F,G**), which we also observed with implantation of E0771 tumors into BL6 mice (**Supplemental Figure 3A**). We found that while there were similar frequencies of the monocyte (CD11b+) populations in both tumor models (**Supplemental Figure 3B** and not shown), CD11b+ cells in both 66cl4 and E0771 tumors implanted during mammary gland involution had higher average levels of PD-L1 (**Figures 1H,I** and **Supplemental Figure 3C**). The number of PD-L1+ cells was also increased in the involution group, but this increase was lost when normalized to tumor size (**Supplemental Table 2**). We also analyzed additional cell populations for PD-L1 including monocytes, fibroblasts, blood endothelial cells (BECs), and EpCAM+ tumor cells based on described markers. We did not see significant staining differences or staining above background in the fibroblasts, BECs or EpCAM+ cells (**Supplemental Figure 3D**). These results complement our recently published data showing that CD11b+ monocytes in the TME of involution group tumors contribute to lymphangiogenesis and extend our observations to describe their expression of PD-L1 (21).

As PD-L1 is the inhibitory ligand, we next examined expression of the inhibitory receptor, PD-1, by CD4+ and CD8+ tumor-associated T cells (gating-**Supplemental Figure 2D**) all of which are also positive for CD11a, a molecule that has been shown to render them unable to control tumor growth (50). We found an increase in the expression of PD-1 on CD4+ T cells (**Figure 2A**) and after quantification we found that an average of 30% of CD4+ T cells in the involution group tumors expressed PD-1 compared to 10% in the nulliparous controls (**Figure 2B**). As cytotoxic CD8 T cells are typically thought to be important in controlling tumors we next asked about expression of PD-1 on CD8+ T cells. We observed a striking difference in the expression profile of CD8+ T cells in tumors implanted during mammary gland involution compared to tumors implanted in nulliparous hosts (**Figure 2C**). When we quantified this difference, we found a >4-fold increase in expression of PD-1 by CD8+ T-cells from involution group tumors (**Figure 2D**). Additionally, we observed similar phenotypes in the mammary draining lymph nodes of tumor bearing animals (**Figure 2E**) suggesting this mechanism of tumor-associated immune suppression may extend beyond the local tumor microenvironment to drive the increased LN metastasis that we observe in post-partum patients. Finally, we observed similar phenotypes in the E0771 tumors, but not lymph nodes (**Supplemental Figures 4A,B**).

#### PD-L1 and PD-1 Expression Are Observed in Mouse Mammary Tissues During Normal Post-Partum Mammary Gland Involution

We next asked if the LECs of C57/BL6 (B6) or Balb/c female mice exhibit expression of PD-L1 during normal post-partum mammary gland involution, similar to what is observed in LN LECs to induce peripheral tolerance during tissue homeostasis (31). We evaluated mouse mammary LECs at involution day 6, the peak of the remodeling phase of involution, for expression of PD-L1. PD-L1+ LECs were evaluated based on the markers described above and validated by staining with isotype and fluorescence minus one (FMO) controls (**Supplemental Figure 2B**). We observed that expression of PD-L1 was increased in mammary LECs isolated from involution group mice compared to nulliparous (**Figure 3A**). We also found that the percentage and number of LECs expressing PD-L1, as well as the geometric mean fluorescence intensity (gMFI) of PD-L1, was increased on LECs during involution (**Figures 3B–D**), which is similar to that observed in our pre-clinical model of PPBC (**Figures 1F,G**). We found these increases in both the B6 mice as well as the Balb/C mice (**Supplemental Figures 5A–C**). Since we observed increased PD-L1 expression in the CD11b+ population in our model of PPBC, we first confirmed that the CD11b+ population increased (gating-**Supplemental Figure 2C**) during involution in both B6 (**Figure 3E**) and Balb/C (**Supplemental Figure 5D**) mouse mammary glands. Then, we also observed an increase in expression of PD-L1 by this

FIGURE 2 | Tumor-associated PD-1+ T cells are increased in tumors implanted during involution. (A) Representative flow plots for cells from nulliparous or involution group tumors of CD11a and PD-1 expression by CD4+ T cells. (B) Quantification of CD4+ T cells that express PD-1 from A. (C) Representative flow plots of CD8+ T cell expression of PD-1 and CD11a from nulliparous and involution tumors and (D) quantification of PD-1+ CD8+ T cells. (E) Representative flow plots of CD11a and PD-1+ CD4+ T cells or CD8+ T cells in the tumor draining lymph nodes and quantification of PD-1+ frequency of each cell type. Data shown are from 1 representative experiment of 2 replicates with at least 4 tumors per group. Unpaired t-test: \*p < 0.05; \*\*\*p < 0.001.

FIGURE 3 | PD-L1+ lymphatic endothelial cells and PD-L1+ myeloid cells increase in the mammary gland during post-partum involution. (A) Representative histogram of PD-L1 by lymphatic endothelial cells (CD45−EpCAM−CD31+PDPN+PD-L1+) acquired by flow cytometry from B6 mammary glands of nulliparous (n = 6) or recently weaned, involution day 6 (n = 6), mice. Gray dotted line indicates a PD-L1 negative population (CD45+CD11b-F4/80-) that does not change. (B) Quantification of the frequency of PD-L1+ LECs of total LECs per mammary gland. (C) Number of PD-L1+ LECs per mammary gland. (D) Quantification of gMFI of PD-L1 expression by LECs from A. (E) Frequency of CD11b+ cells of the CD45+ cells found in the mammary gland in nulliparous or involution group mice. (F) Histogram of PD-L1 expression by CD11b+ cells in mammary gland of nulliparous or involution group mice. Gray dotted line indicates a PD-L1 negative population (CD45+CD11b−F4/80−) that does not change. (G) Quantification of PD-L1 expression by gMFI on CD11b+ cells as shown in F. (H) Percent of CD4+ T cells that are PD-1+ from the mammary glands of B6 mice and (I) as in H except from Balb/c mice. (J) Percent of PD-1+ CD4+ T cells in the axillary lymph nodes from nulliparous and involution group tissues. Data shown are from 1 representative experiment of 2 replicates with at least 6 mammary glands per group. Unpaired t-test: \*\*p < 0.01; \*\*\*p < 0.001; \*\*\*\*p < 0.0001.

#### population (**Figure 3F**) that was significant (**Figure 3G**) in both models (**Supplemental Figure 5E**).

To better understand if PD-1 expression on T cells is similarly increased during post-partum mammary gland involution, we evaluated the T-cell compartment at involution day 6 by assessing the frequency of PD-1 expression by CD4+ and CD8+ T-cells in B6 and Balb/c mice compared to isotype controls (gating-**Supplemental Figure 2D**). Similar to previous results in Balb/c mice (51), we observed a significant increase in the percent of PD-1+ CD4+ T cells in mammary glands from B6 (**Figure 3H**) and confirmed this in our Balb/c mice (**Figure 3I**). This increase in PD-1+ CD4+ T cells also extended to the LN (**Figure 3J**). Further, we found an increase in CD8+ T cells expressing PD-1 in the B6 mice (**Supplemental Figure 5F**), which was not significant in the Balb/c mice (**Supplementary Figures 5G,H**). These results suggest that a mechanism of LEC and/or monocyte/macrophage mediated T cell inhibition could be driving the decreased latency and increased growth rate that we observe in our preclinical models when tumor cells are implanted during involution (16, 21, 52).

### PD-1 Targeted Therapy Reduces Tumor Growth in Post-partum Hosts by Reactivating T-Cells

A prediction of our results is that inhibition of PD-L1/PD-1 signaling during involution would dampen the increased tumor growth observed when tumors are implanted during involution by reversing this involution-driven mechanism of immune suppression. To test our hypothesis, we utilized the E0771 mouse mammary tumor model since tumors implanted in this model become palpable during active involution; when the immune suppressive mechanism is most activated. Thus, we orthotopically implanted E0771 tumor cells into the intact mammary glands of C57BL/6 mice at involution day 1 or into nulliparous hosts. Then, we blocked PD-L1-mediated inhibition of T cells by administering an anti-PD-1 monoclonal antibody every third day after tumors were palpable and size-matched in both nulliparous and involution groups. Following two and three treatments, in involution and nulliparous mice, respectively, mice were euthanized and flow cytometry performed on tumors (**Figure 4A**). Similar to previous results, involution group tumors exhibited decreased latency and increased growth compared to tumors in nulliparous hosts (**Figure 4B**) (3, 13, 16). Importantly, the anti-PD-1 treatment significantly reduced the growth rate in involution group tumors, to levels more similar to those observed in the nulliparous hosts, and did not significantly affect tumor growth in the nulliparous group (**Figure 4B**). We then evaluated whether the anti-PD-1 treatment affected immune cell infiltration into the tumors in the involution group. Immunohistochemistry (IHC) on a single tumor from each involution group revealed increased intratumoral staining for CD45, which was validated by our flow cytometry where we observed a >2-fold increase in the number of CD45+ cells in the tumor (**Figures 4C,D**). We also observed a significant increase in the number of intra-tumoral CD8+ T cells following treatment with anti-PD-1 when the tumors were implanted into involution hosts (**Figure 4E**). Additionally, we found a significant decrease in LEC frequency in the adjacent mammary tissues of involution group mice treated with anti-PD-1 by both flow cytometry (**Figure 4F**) and by tissue staining with PDPN to assess LVD (**Figure 4G**). Conversely, we found no significant difference in PD-L1 expression by LECs after anti-PD-1 treatment (**Supplemental Figure 6A**). These findings suggest that blockade of PD-1 could have potential for blocking both tumor growth and lymphogenous tumor cell spread during involution.