Regulatory T cells crosstalk with tumor cells and endothelium through lymphotoxin signaling

Piao, Wenji; Wu, Long; Xiong, Yanbao; Zapas, Gregory C.; Paluskievicz, Christina M.; Oakes, Robert S.; Pettit, Sarah M.; Sleeth, Margaret L.; Hippen, Keli L.; Schmitz, Jessica; Ivanyi, Philipp; Shetty, Amol C.; Song, Yang; Kong, Dejun; Lee, Young; Li, Lushen; Shirkey, Marina W.; Kensiski, Allison; Alvi, Aamna; Ho, Kevin; Saxena, Vikas; Bräsen, Jan H.; Jewell, Christopher M.; Blazar, Bruce R.; Abdi, Reza; Bromberg, Jonathan S.

doi:10.1038/s41467-024-54874-y

Download PDF

Article
Open access
Published: 02 December 2024

Regulatory T cells crosstalk with tumor cells and endothelium through lymphotoxin signaling

Nature Communications volume 15, Article number: 10468 (2024) Cite this article

8784 Accesses
1 Citations
16 Altmetric
Metrics details

Subjects

Abstract

Regulatory T cells (Tregs) with multifaceted functions suppress anti-tumor immunity by signaling surrounding cells. Here we report Tregs use the surface lymphotoxin (LT)α1β2 to preferentially stimulate LT beta receptor (LTβR) nonclassical NFκB signaling on both tumor cells and lymphatic endothelial cells (LECs) to accelerate tumor growth and metastasis. Selectively targeting LTβR nonclassical NFκB pathway inhibits tumor growth and migration in vitro. Leveraging in vivo Treg LTα1β2 interactions with LTβR on tumor cells and LECs, transfer of wild type but not LTα^-/- Tregs promotes B16F10 melanoma growth and tumor cell-derived chemokines in LTβR^-/- mice; and increases SOX18 and FLRT2 in lymphatic vessels of LTβR^-/- melanoma. Blocking the nonclassical pathway suppresses tumor growth and lymphatic metastasis by reducing chemokine production, restricting Treg recruitment to tumors, and retaining intratumoral IFNγ⁺ CD8 T cells. Our data reveals that Treg LTα1β2 promotes LTβR nonclassical NFκB signaling in tumor cells and LECs providing a rational strategy to prevent Treg promoted tumor growth and metastasis.

Lymphotoxin: from the physiology to the regeneration of the thymic function

Article 22 July 2021

Simultaneous STING and lymphotoxin-β receptor activation induces B cell responses in tertiary lymphoid structures to potentiate antitumor immunity

Article Open access 02 September 2025

Regulatory T cells promote cancer immune-escape through integrin αvβ8-mediated TGF-β activation

Article Open access 28 October 2021

Introduction

Lymphotoxin (LT) beta receptor (LTβR) is a member of the tumor necrosis factor receptor (TNFR) family and mediates unique immune functions critical for the development and maintenance of various lymphoid microenvironments, including stromal cell specialization, positioning of lymphocytes within lymph nodes (LNs), specialization of high endothelial venules, and formation of secondary lymphatic organs and tertiary lymphoid structure organs¹. LTβR has two known ligands: the membrane-bound lymphotoxin heterotrimer (LTα1β2), and LIGHT (TNFSF14)². Unlike TNFRI that exclusively signals through the classical nuclear factor-κB (NFκB) pathway, LTβR signals through a dual cascade that activates both classical and nonclassical NFκB pathways in the lymphatic endothelium². The classical pathway acts rapidly, phosphorylating the inhibitor of the kappa-B kinase (IKK) complex and degrading the inhibitor IκBα, thereby allowing for the release of the RelA/p50 complex and nuclear translocation. The nonclassical pathway has a more sustained response involving the NFκB inducing kinase (NIK) dependent processing of p100 to p52, which dimerizes with RelB for nuclear translocation³.

While the LT system has a defined role in several important aspects of immune regulation and interactions of leukocytes and blood vascular and lymphatic endothelium, there is conflicting evidence for the role LTβR plays in cancer cell biology. Some reports describe links of LTβR to primary tumorigenesis related to mechanisms controlling cell survival, cell-cycle progression, and initiation of angiogenesis⁴. In multiple myeloma, mutations resulting in constitutive activation of the NIK pathway are frequently observed along with associated overexpression of LTβR⁵. LTβR expressing fibrosarcoma cells have been shown to interact with LTα1β2 expressing lymphocytes, resulting in the activation of a proangiogenic pathway required for solid tumor neovascularization⁶. In contrast, other reports demonstrated LTβR activation by LIGHT promoted anti-tumor immunity⁷. Agonist anti-LTβR monoclonal antibody (mAb) treatment inhibited tumor growth in colorectal cancers⁸ and enhanced chemotherapeutic responses¹. Thus, LTβR signaling has a more complex role in the tumor microenvironment (TME) that warrants further investigation.

High frequencies of immunosuppressive regulatory T cells (Tregs) are present in the TME of various primary tumors, and these intratumoral Tregs are key suppressors of anti-tumor immunity^9,10. Selectively targeting Tregs in the TME has emerged as an effective anti-tumor strategy. In our previous studies, we found that among T cell subsets, both human and mouse Tregs express the highest level of membrane-anchored LTα1β2, suggesting that Tregs are the predominant population to interact with LTβR, which is highly expressed on human and mouse lymphatic endothelial cells (LECs)^11,12. LTα deficiency prevents Treg lymphatic migration to draining LNs and impairs their suppressive function in models of allograft protection¹¹. Engagement of LTβR on LECs by LTα1β2⁺ but not LTα^−/− Tregs induces LEC basal protrusions that support Treg afferent transendothelial migration (TEM)¹¹. Blood endothelial cells, including high endothelial venules (HEV) also express high levels of LTβR. However, the LTα1β2-LTβR interaction is not required for Treg cell migration from blood through HEV into the LNs¹¹, although deletion of endothelial LTβR in mice impairs LN homing of conventional T cells and B cells through impaired integrin and selectin expression by HEV¹³. Since tumor cells also express LTβR, Tregs may also have a direct impact on tumor cells through LTα1β2/LTβR pathways.

While LTα1β2-LTβR interaction is integral to many aspects of immune cell migration and endothelial cell responses, there are limited studies that address the roles that LTβR may play in cancer cell migration, interactions with blood or lymphatic endothelium, and initiation of metastasis. Previous studies^1,8,14 assessing the role of LTβR in cancer have used approaches that relied on total receptor blockade or activation with pharmacologic or genetic interventions but did not dissect the contributions of each bifurcated LTβR signaling cascade to specific cell processes, including migration patterns. A more in-depth understanding can be obtained only with selective targeting of the LTβR-mediated classical or nonclassical NFκB signaling pathway. In our previous studies, we constructed and validated cell permeable decoy receptor peptides based on the LTβR cytoplasmic TRAF recruitment domains³. These peptides were capable of selectively and specifically targeting each arm of the LTβR-NFκB signaling pathways.

Since most solid tumors contain both tumor and stroma cells, including LECs which form lymphatic vessels for transporting metastatic and immune cells to draining LNs, we focused on LTβR signaling in tumor cells and LECs. We used these LTβR decoy peptides to selectively target either classical or nonclassical NFκB signaling pathway in melanoma cells and LECs to dissect the molecular underpinnings related to cancer cell migration and metastasis in vitro and in vivo syngeneic mouse melanoma model whose metastasis follow reliable lymphatic routes¹⁵. In this work, we demonstrate that selective inhibition of tumor and LEC LTβR nonclassical NFκB signaling pathway suppresses human and mouse melanoma and other cancer cell growth and TEM in vitro. When applied to an in vivo mouse model of melanoma metastases, the LTβR nonclassical NFκB blocking peptide limits tumor cell and immune cell lymphatic migration into the tumor-draining LNs and induces tumor regression. Mechanistically, constitutively activated tumor LTβR nonclassical NFκB signaling harnesses chemokines and interferon-regulated genes, which promotes immune suppressive cell recruitment, especially Tregs which further enhance LTβR nonclassical NFκB signaling in tumor cells and LECs. These results indicate a general reliance on LTβR signaling in cancer cell migration and the initiation of lymphatic-based metastases that could be utilized for novel therapeutic modalities.

Results

High LTβR expression on tumors denotes a worse patient prognosis

To assess LTβR expression and its association with phenotype and clinical characteristics in human cancer samples, The Cancer Genome Atlas (TCGA) gene expression data and the Human Protein Atlas were queried for LTβR expression levels and patient survival. High LTβR expression on tumors was associated with poor survival in patients with breast cancer, head and neck cancer, lung cancer, renal cancer, and cutaneous melanoma (Fig. 1a). LTβR expression levels were comparable with many oncogenes such as MYC, TP53, and BRCAs in melanoma patients (Fig. 1b), supporting that high LTβR expression on tumors denotes worse patient prognosis. Cancer patient samples were stratified as high and low LTβR expressors using an expression cut-off of one standard deviation above and below the mean of normalized gene expression. The clustering of gene expression of high and low LTβR expression cohorts of melanoma patients was assessed using principal component analysis (PCA). There was distinct clustering of samples, indicating underlying differences between LTβR high and low expressing melanomas (Fig. 1c). To identify other genes that may play an important role alongside LTβR, we analyzed differential gene expression (DGE) between the high and low LTβR expression cohorts. We identified 3285, 2134, and 3285 DEGs for melanoma, breast cancer, and lung cancers, respectively, with an adjusted p value <0.05 and at least a twofold change in gene expression (Fig. 1d–f). Among all three types of cancers, we identified shared DEGs that were upregulated in LTβR high cohorts, including chemotactic chemokines (CCL20, CCL21, CXCL1, CXCL2, and CXCL5)¹⁶; Sox F genes (SOX7, SOX17, and SOX18) which play important roles on angio- and lymphangiogenesis^17,18, and S100A family genes (such as S100A4 and S100A9) with well-established roles in tumor metastases and invasion^19,20. Functional gene ontology (GO) enrichment for skin cutaneous melanoma revealed 272 GO terms with an adjusted p value <0.01. The top ten significantly enriched signaling activities identified in LTβR high cohorts (Fig. 1g) were related to regulation of cellular chemotaxis, immune cell activation and migration, and regulation of inflammatory responses.

**Fig. 1: High LTβR expression in tumors is associated with poor survival in cancer patients.**

Most tumor cells express LTβR which signals by classical and nonclassical pathways

Several murine and human tumor cells of diverse histologic origins were assessed for LTβR expression by flow cytometry. Most tumor cells expressed high levels of LTβR (Supplementary Table 1), including the well-studied B16F10 murine and human A375 melanoma cell lines (Fig. 2a). Indeed, analyzing the major component cells of human melanoma or breast cancer using published single-cell RNA sequencing data, we found LTβR is highly expressed on cancer cells and endothelial cells (Supplementary Fig. 1a–c). while its ligand genes LTα and LTβ are predominantly expressed in T cells and B cells, and Tregs have the highest combined expression levels of LTα and LTβ (Supplementary Fig. 1d, e).

**Fig. 2: Tumor LTβR signals by classical NF_ΚB and nonclassical NF_ΚB pathways.**

To determine LTβR-mediated classical and nonclassical NFκB signaling in tumor cells, we stimulated B16F10 cells with agonist anti-LTβR mAbs along with pretreatment with cell-permeable LTβR blocking decoy peptides, which we previously developed and validated to selectively block LTβR-classical NFκB-IKKβ/p65 (ciLT) or nonclassical NFκB-IKKα/NIK/p52 (nciLT) pathways³. Unstimulated cells in a steady state showed weak IKKα/β and NFκB-p65 phosphorylation, which were not affected by either ciLT or nciLT blocking peptides (Fig. 2b, left panel). LTβR ligation induced phosphorylation of IKKα/β (Fig. 2b, right panel), which was inhibited by both ciLT and nciLT 5 to 20 min post ligation. LTβR ligation further enhanced NFκB-p65 phosphorylation, which was inhibited as early as 5 to 10 min by ciLT but not nciLT (Fig. 2b, right panel). Resting B16F10 cells had constitutively processed p52 and was inhibited by nciLT only (Fig. 2c, left panel). Ligation of LTβR further enhanced p52 processing which was inhibited by nciLT but not ciLT (Fig. 2c, right panel). Immunoprecipitation of LTβR showed a low level of TRAF2 and no TRAF3 bound to the B16F10 LTβR complex in the steady state (Fig. 2d, left panel). Stimulation of LTβR recruited TRAF3, and this binding was blocked by nciLT alone (Fig. 2d, right panel). Notably, stimulation of LTβR also recruited more TRAF2 to the receptor complex, which was blocked by both ciLT and nciLT (Fig. 2d, right panel). These data suggest that B16F10 LTβR nonclassical NFκB signaling involves the recruitment of both TRAF2 and TRAF3 to the LTβR complex, while LTβR-classical NFκB signaling mainly requires TRAF2 recruitment. Similar signaling patterns were observed in human melanoma A375 cells (Fig. 2e, f), Together, these data show that nciLT preferentially blocks B16F10 LTβR nonclassical NFκB signaling. Interestingly, nciLT suppressed IKKα/β but not p65 phosphorylation in mouse melanoma and suppressed p65 but not IKKα/β phosphorylation in human melanoma, indicating cellular context-dependent classical NFκB signaling. It is noteworthy that the same peptide blocks TRAF recruitment to LTβR differently in tumor cells and LECs: nciLT blocks both TRAF2 and TRAF3 binding in B16F10 but blocks only TRAF3 in LECs³, while ciLT blocks only TRAF2 in B16F10 but blocks both TRAF2 and TRAF3 in LECs³, again indicating cellular context-dependent LTβR signaling.

Tumor LTβR nonclassical NFκB signaling preferentially regulates TEM

We previously characterized the role of LTβR in migration and its regulation by Tregs, endothelial cells^3,11,12. Focusing on melanoma and breast cancer, which follow reliable routes of lymphatic metastasis¹⁵, we used the specific blocking peptides to investigate which LTβR signaling pathways regulate tumor lymphatic TEM. We treated mouse and human tumor cell lines with the decoy peptides or with the agonist anti-LTβR mAb and assessed their migration across Boyden chamber transwells coated with the mouse lymphatic endothelial cell line SVEC4–10 or human primary LECs. To enhance migration, we used the chemotactic molecule sphingosine 1-phosphate (S1P), which is spatially compartmentalized in blood, lymph, and tumor, and has widely expressed receptors (S1P1-5)²¹, recapitulating migration from tissue to lymphatic vessels as would occur during metastatic spread²². The nonclassical LTβR-NFκB blocking peptide nciLT (identical sequence in human and mouse) but not classical LTβR-NFκB blocking peptide ciLT (versions specific for mouse and human used) was sufficient to inhibit TEM of murine tumor cells such as sarcoma KPI30, breast cancer 410, ovarian cancer ID8, mammary adenocarcinoma 66.1 (Fig. 3a), human breast cancer MDA-MB-231, and human melanoma A375 (Fig. 3b and Supplementary Table 2). Both nciLT and ciLT inhibited TEM of mouse melanoma B16F10 and human lung cancer A549, although nciLT was far more effective. LTβR stimulation by anti-LTβR mAb enhanced TEM of the mouse or human melanoma and breast cancer (Fig. 3a, b). Notably, tumor cell TEM required the presence of LECs for migration to an S1P gradient (Fig. 3c). This is reminiscent of our previous report that T lymphocyte chemotaxis to S1P also requires the presence of LEC for efficient migration²². This suggests that factors produced by LECs, such as adhesion or junctional molecules or chemokines, are critical for tumor migration.

**Fig. 3: Most tumors use nonclassical NF_ΚB signaling for lymphatic migration.**

Tumor LTβR nonclassical NFκB signaling regulates cell migration and motility

Tumor cells were pretreated for 1 h with LTβR signaling blocking peptides and assessed in a migration response assay. Consistently, blockade of B16F10 or 4T1 LTβR nonclassical NFκB signaling with nciLT abolished the migration response (Fig. 3d, e). ciLT inhibited the migration response with lesser efficiency.

Monitoring peptide-treated B16F10-eGFP migration across LECs by time-lapse microscopy, we observed that nciLT suppressed tumor cell motility assessed by cell displacement while agonist anti-LTβR mAb stimulated B16F10 motility (Fig. 3f). In addition, CRISPR/Cas9 LTβR-depleted B16F10 had impaired TEM across LECs (Fig. 3g). Overall, the data demonstrates that tumor LTβR nonclassical and to a lesser extent classical NFκB signaling plays critical roles in tumor motility and migration.

Tumor LTβR nonclassical signaling regulates tumor growth

Since LTβR expression was associated with worse prognosis and increased expression of detrimental GO terms for tumor patients, we assessed LTβR regulation of tumor growth in vitro. Pretreatment of wild-type (WT) B16F10 for 1 h with nciLT inhibited cell growth, and inhibition was abolished in CRISPR/Cas9 LTβR-depleted B16F10 (Fig. 4a), indicating that inhibition is LTβR signaling specific. Peptide treatment for 1 h with or without LTβR stimulation by agonist mAb did not affect B16F10 cell viability (Fig. 4b). However, 5 to 16 h of nciLT treatment increased B16F10 apoptosis (Fig. 4c), while other peptides with or without LTβR stimulation did not affect viability. Importantly, LTβR stimulation prevented the increased apoptosis by nciLT (Fig. 4c), indicating LTβR stimulation induced classical NFkB signaling, promoted tumor cell survival, and compensated for nciLT-triggered apoptosis. These data indicate that nciLT inhibits tumor cell growth and promotes apoptosis.

**Fig. 4: Tumors use LTβR nonclassical NF_ΚB signaling for tumor growth.**

Tumor LTβR depletion suppresses tumor growth and metastasis

CRISPR/Cas9 LTβR-depleted B16F10 cells were assessed for tumor growth and migration. Subcutaneously inoculated LTβR-depleted B16F10 cells had slower in vivo growth than WT B16F10 (Fig. 4d, e) and reduced lymphatic metastasis into the draining LNs (dLNs) (Fig. 4f). LTβR-depleted B16F10 melanoma had impaired production of tumor cell-derived CXCL1 and CXCL10 (Fig. 4g), and reduced intratumoral Tregs and myeloid-derived suppressor cells (MDSCs) but increased CD4 T cells, B cells, and unaltered CD8 T cells 13 days after melanoma inoculation, compared to WT B16F10 (Fig. 4h). Since these cells were not decreased in tumor dLNs, this suggests that LTβR depletion in tumor cells had no impact on immune cell egress from the tumor. However, the reduced Tregs and MDSCs may result from the reduced CXCL1 and CXCL10, which may recruit these CXCR2 and CXCR3 expressing cells to tumors from the blood circulation (Fig. 4h).

We explored the genes affected by LTβR depletion by whole transcriptome RNA sequencing (RNA-seq) analysis, comparing CRISPR/Cas9 LTβR^−/− to WT B16F10. DEGs were observed between the two cell lines with 323 upregulated and 859 downregulated in LTβR^−/− B16F10 (Fig. 4i). The enhanced expression of tumor suppressor genes such as integral membrane protein 2A (ITM2a) and nuclear receptor 4A3 (NR4a3) in LTβR-depleted B16F10 cells may contribute to cell growth inhibition, while the decreased gap junction protein alpha 1 (GJA1), podoplanin (PDPN), NOTCH3, and basal cell adhesion molecule 1 (BCAM1) which regulate cell adhesion may contribute to reduced Treg tumor recruitment and melanoma metastasis. In addition, GO analysis indicated predominant downregulation of cell surface G-protein-coupled receptor (GPCR) signaling pathways that regulate chemotaxis, localization, and transmembrane transport, in addition to cellular component organization or biogenesis and developmental regulations as key changes induced by LTβR depletion (Supplementary Fig. 2a–c).

Genes driven by tumor LTβR-NFκB signaling

To determine the molecules regulated by nonclassical LTβR-NFκB signaling in B16F10 melanoma, we employed bulk RNASeq in a two-pronged strategy. First, we performed RNA-Seq on B16F10 cells stimulated by agonist anti-LTβR Ab (3C8) for 6 h to induce LTβR nonclassical NFκB signaling. These stimulated cells were compared to both non-stimulated B16F10 cells and to cells that were stimulated and pretreated with the LTβR-nonclassical blocking peptide nciLT. Second, we generated CRISPR/Cas9 knockout (KO) of nonclassical NFκB/NIK B16F10 and stimulated them for 6 h. Thus, we were able to compare gene expression regulated by the LTβR nonclassical NFκB pathway using both the nciLT inhibitor and NIK deficiency. Melanoma LTβR nonclassical NFκB signaling upregulated angiogenic and immunosuppressive myeloid chemokines CXCL1^20,23, CXCL10²⁴, and CCL5²⁵, which were downregulated by nciLT and diminished in NIK-deficient B16F10 cells (Fig. 5a, b). In addition, protumor interferon-stimulated genes ISG15²⁶ and IFIT3²⁷ (interferon-induced protein with tetratricopeptide repeats 3), and oncoprotein USP18²⁸ (Ubiquitin Specific Peptidase 18), which suppresses IFN responses, were also driven by LTβR-nonclassical signaling, downregulated by nciLT, and diminished in NIK-deficient B16F10 cells (Fig. 5a). The selected genes were further confirmed by real-time PCR (Fig. 5b). CXCL1, CXCL10, and CCL5 expression were abolished in NIK-depleted but not IKKβ-depleted B16F10 (Supplementary Fig. 3a, b), confirming that these genes are regulated by the LTβR-nonclassical NFκB-NIK signaling pathway. CXCL1 and CXCL10 expression were enhanced in Treg-cocultured human melanoma A375 and human LECs and inhibited by nciLT pretreatment (Supplementary Fig. 3c, d). Neither Teff coculture nor ciLT pretreatment affected the chemokine expression. Together, the data showed that CXCL1 and CXCL10 production in tumor cells and LECs are driven by the LTβR-nonclassical NFκB-NIK signaling pathway.

**Fig. 5: Treg LTα1β2 stimulates tumor LTβR nonclassical NF_ΚB pathway to promote tumor growth and TEM.**

A parallel strategy was employed for identifying LTβR-classical NFκB-driven genes, by comparing gene expression in cells stimulated for 1 hour with agonist mAb and pretreated or not with the classical blocking peptide ciLT, and further compared with IKKβ -depleted B16F10 (Fig. 5c). Several pro-cancer genes such as ribosomal proteins 21 and 30 (RPL21 and RPL30)²⁹, migration and invasion enhancer 1 (MIEN1)³⁰, and nuclear receptor NR4a1³¹ were identified to be rapidly induced by LTβR activation and inhibited by blocking LTβR-classical NFκB signaling (Fig. 5c). Selected genes RPL21 and Mien1 were further shown by real-time PCR to be inhibited by the classical NFκB blocking peptide ciLT but not by the nonclassical NFκB blocking peptide nciLT (Fig. 5d), confirming regulation by the LTβR-classical NFκB signaling pathway.

Treg LTα1β2 stimulates tumor LTβR nonclassical NFκB signaling to enhance tumor growth

Our previous study revealed that Tregs express high levels of LTα1β2 which ligate and activate LTβR on LEC¹². Treg LTα1β2 signals primarily to the LTβR nonclassical NFκB pathway and alters LEC morphology and membrane characteristics, thereby causing endothelial morphologic changes and promoting lymphatic TEM of other immune cells¹². To explore the possible role of Tregs directly interacting with tumor cells, we assessed whether Treg LTα1β2 can ligate and activate tumor surface LTβR. LTα1β2 high expressing human Tregs and LTα1β2 low expressing human effector T cells (Teffs) (Supplementary Fig. 4a) cocultured with the melanoma cells equally induced phosphorylation of IKKα/β and p65 classical NFκB signaling in human A375 cells as early as 10 min after incubation (Supplementary Fig. 4b). An identical pattern was observed in mouse B16F10 cultured with mouse Tregs and Teffs (Supplementary Fig. 4c). After 5 h coculture with both human and mouse melanoma cells, only Tregs induced nonclassical NIK signaling for p100 processing to p52 in these tumor cells, while LTαβ-low expressing Teffs (Fig. 5e) or LTα-deficient Tregs (Fig. 5f) did not. Only nonclassical blocking peptide inhibited Treg-induced nonclassical NFκB signaling in human melanoma (Fig. 5g), while both nciLT and ciLT inhibited the Treg-induced nonclassical signaling in B16F10 (Supplementary Fig. 4d). Other immune cells such as B cells, CD8 T cells also express LTα1β2, however, the expression level is significantly lower than that of Tregs (Supplementary Fig. 4e), and B cells failed to induce any NFkB signaling in either tumor or LECs (Supplementary Fig. 4f) and had no impact on tumor cell TEM (Supplementary Fig. 4g). These results indicate that Treg LTαβ exclusively induces nonclassical NFκB signaling on tumor cells through cell-cell interactions. To investigate the biological function of Treg-induced preferential LTβR nonclassical NFκB signaling, we cocultured Tregs with B16F10, which were pretreated with or without blocking peptides to assess tumor cell growth. Treg-cocultured B16F10 demonstrated increased cell growth. Blockade of only the nonclassical NFκB signaling abolished Treg stimulated growth and likewise inhibited basal growth of tumor cell even without Treg pretreatment (Fig. 5h), similar to the observations in Fig. 4a. Thus, these data show that both basal constitutive and Treg-induced LTβR-nonclassical-NFκB signaling in B16F10 promote tumor growth.

Treg LTα1β2 stimulates tumor LTβR nonclassical NFκB signaling to enhance tumor cell TEM

To determine whether Tregs directly affect tumor cell migration, we cocultured Tregs or Teffs with melanoma cells prior to migration assay across LEC-coated transwell. Treg-cocultured B16F10 cells showed enhanced TEM across LECs in a dose-dependent fashion, while Teffs induced no such effect (Fig. 5i). Human Tregs cocultured A375 also had increased TEM (Supplementary Fig. 4h). Importantly, the effect required the presence of LECs. Without LECs, the Treg-pretreated B16F10 had no enhanced TEM (Fig. 5j). Treg enhanced TEM was LTα1β2-LTβR signaling dependent since LTα-deficient Tregs failed to increase tumor TEM (Fig. 5k). Blockade of B16F10 LTβR nonclassical NFκB signaling also abolished Treg promoted tumor TEM (Fig. 5k). Similarly, Tregs but not LTα-deficient Tregs, enhanced 4T1 breast cancer TEM (Fig. 5l). Treg failed to increase TEM of B cell lymphoma M12.4 which has minimal levels of LTβR expression (Fig. 5m and Supplementary Table 1). Together, these data show that Treg LTαβ directly ligates tumor LTβR to activate nonclassical NFκB signaling and enhance tumor cell TEM. To assess in vivo Tregs direct interaction with tumor cells, we intravenously injected WT or LTα-deficient Tregs to LTβR-depleted mice inoculated with WT B16F10. Thus, in this system, Treg LTα1β2 can only ligate and activate tumor surface LTβR. WT Tregs significantly promoted melanoma growth, while LTα-deficient Tregs failed to do so (Fig. 5n). There was also increased LTβR nonclassical signaling driven CXCL1, CXCL10, and CCL5 expression in melanoma cells in the host mice injected with WT Tregs but not with LTα-deficient Tregs (Fig. 5o). These results demonstrate that in vivo Treg LTα1β2 can directly activate tumor cell LTβR nonclassical NFκB signaling.

Treg LTα1β2 stimulates LEC LTβR nonclassical NFκB to promote tumor growth and TEM

We previously demonstrated that Tregs stimulate LTβR nonclassical NFκB signaling in LECs and thereby alter LEC characteristics for leukocyte TEM¹². Since we showed above that Tregs also stimulate tumor LTβR to alter tumor growth and TEM, we next analyzed if this signaling induced additional events between LECs and tumors. LECs were pretreated with Tregs, the Tregs removed, and then B16F10 added to the LECs. This coculture promoted melanoma growth (Fig. 6a). Blockade of LEC LTβR nonclassical NFκB with nciLT prior to coculture with Tregs abolished the activated LEC enhanced tumor cell growth (Fig. 6a, middle row). Blockade of LEC LTβR-classical NFκB with blocking peptide ciLT had no effect on tumor cell growth. LECs pretreated with Teffs did not affect tumor cell growth, and the blocking peptides did not alter the lack of effect of Teffs on LEC for tumor growth (Fig. 6a, lower row). To determine whether the growth effect was from direct tumor-LEC contact or due to the secreted factors from the LECs, 0.4 μm pore transwells were used to separate B16F10 in the upper chamber from LECs in the lower chamber. The B16F10 or the LECs were each independently cocultured with Tregs for 6 h, the Tregs were then removed, and the growth of B16F10 was assessed after another 48 h. WT or LTα-deficient Tregs cocultured with LECs in the lower chamber did not promote B16F10 cell growth in the upper chamber (Supplementary Fig. 5a, b), suggesting soluble cytokines/chemokines produced by activated LECs have no effect on B16F10 cell growth, and that a direct tumor-LEC cell physical contact is required for supporting tumor cell growth. To test the effect of Treg LT-triggered LEC LTβR signaling on tumor migration, we cocultured Tregs with WT or LTβR-deficient LEC prior to assessing tumor cell TEM. WT LECs cocultured with Tregs promoted B16F10 TEM, while LTβR-deficient LECs cocultured with WT Tregs did not enhance B16F10 migration (Fig. 6b). WT LECs cocultured with LTα-deficient Tregs also had no effect on B16F10 or 4T1 TEM (Fig. 6c).

**Fig. 6: Tregs communicate with LEC through LTα1β2/LTβR signaling to activate nonclassical NF_ΚB pathway and promote tumor growth and TEM.**

Genes driven by LTβR nonclassical NFκB signaling in LEC

To investigate which molecules are driven by LEC LTβR signaling to regulate tumor cell growth and migration, we employed DNA microarray analysis of LECs. Primary LECs were treated with control peptide (CP), nciLT, or ciLT prior to agonist anti-LTβR mAb stimulation. Endothelial-specific genes which promote tumor malignancy and metastasis, such as fibronectin leucine-rich transmembrane protein 2 (FLRT2), SRY-box transcription factor 18 (SOX18), and C-type lectin domain containing 14A (Clec14a), were identified to be driven by LTβR nonclassical NFκB signaling and were downregulated by nciLT but not by ciLT (Fig. 6d). The selected genes were further confirmed by RT-PCR (Fig. 6e). Some genes were not transcriptionally regulated while their functions relied on post-translational changes, such as VE-cadherin which is important for endothelial integrity³². Thus, 16 h pretreatment with Tregs could transform intact zipper junctional VE-cadherin expression in lymphatic vessels (LVs) in vivo or LECs in vitro to button-like junction, while LT-deficient Tregs failed to do so (Fig. 6f).

Treg LTα1β2 activates LTβR nonclassical NFkB signaling on tumor-associated LECs in vivo

To study the direct in vivo influence of Treg LTα1β2 on LECs, we intravenously transferred 5 × 10⁵ WT or LTα^−/− Tregs to WT C57BL/6 mice which were subcutaneously inoculated with 0.5 × 10⁶ LTβRKO B16F10. In this system, Tregs can only ligate and activate surface LTβR on stromal cells, including LECs, but not on tumor cells. Since the LTβR-deficient B16F10 had impaired tumor growth compared to WT B16F10 (Fig. 4d), WT Tregs did not significantly promote LTβR-deficient melanoma growth (Fig. 6g), although it promoted WT B16F10 (Fig. 5n). However, WT Treg but not LTα^−/− Treg transfer induced more CXCL1 and CXCL10 in the tumor LECs (Fig. 6h). WT Tregs but not LTα^−/− Tregs accumulated around tumor lymphatic vessels where the nonclassical LTβR-NIK signaling driven endothelial-specific proteins FLRT2, SOX18, and Clec14 were highly upregulated (Fig. 6i and Supplementary Fig. 6a). These data indicated that in vivo Treg LTα1β2 can directly activate LTβR nonclassical NFκB signaling in tumor LECs. To study the combined in vivo influence of Treg LTα1β2 on tumor cells and LECs for tumor growth, we intravenously transferred 0.5 × 10⁶ WT or LTα^−/− Tregs to WT C57BL/6 mice transplanted with 0.5 × 10⁶ B16F10. WT Tregs significantly promoted melanoma growth, while LTα^−/− Tregs failed to do so, suggesting the stronger impact of Treg LTα1β2 on tumor cells than on LECs for LTβR-mediated tumor growth (Supplementary Fig. 6c).

To study whether in vivo LTβR depletion affected tumor growth, we transplanted WT B16F10 into WT or LTβRKO C57BL6 mice, which have lymphatics but lack LNs³³. Transplanted tumors in LTβRKO mice had significantly reduced tumor growth, angiogenesis, and lymphangiogenesis compared to those in WT mice (Fig. 6j, k), and survival was also significantly higher in LTβR-deficient mice (Fig. 6l). Analysis of TILs in LTβRKO mice revealed reduced CD25⁺Foxp3⁺Tregs (Fig. 6m), Ly6G⁺CD11b⁺MDSCs, and F4/80⁺CD11b⁺macrophages, and increased total CD4 T cells, IFNγ⁺CD8 T cells, and B220⁺B cells compared to those of WT mice, although total CD45⁺ immune cells and CD8 T cells remain unchanged (Supplementary Fig. 6b). These data suggest that recipient LTβR regulated recruitment and/or retention of Tregs, MDSCs, and macrophages into the tumor. Since LTβR-deficient mice lack LNs, tumor lymphatic metastasis could not be directly observed³³. Therefore, we then injected B16F10 i.v. to study tumor pulmonary metastasis. LTβR-deficient mice had significantly reduced metastatic colonies in the lung compared to WT mice. Importantly, when LTβR-deficient mice were injected i.v. with B16F10 together with WT LTβR-sufficient primary mouse LECs, there were remarkably increased pulmonary metastases (Fig. 6n), suggesting that LTβR on LECs plays a critical role in tumor metastases.

Selective blockade of LTβR-classical and nonclassical NFκB inhibits tumor growth and lymphatic metastasis

LTβR signaling was assessed for its effects on tumor growth and metastasis by using the blocking peptides in mouse melanoma (Fig. 7a). nciLT dramatically suppressed melanoma growth, while ciLT-treated melanoma had early regression but relapsed later (Fig. 7b). nciLT or ciLT treated melanoma at day 13 after B16F10 intradermal inoculation had increased intratumoral CD4 and CD8 T cell infiltration (Fig. 7c, upper panel). In addition, both nciLT and ciLT treated tumors had increased IFNγ-producing CD8 T cells, but no significant changes in IFNγ⁺ CD4 T cells (Fig. 7c, middle panel). nciLT but not ciLT significantly reduced intratumoral activated CD25⁺ Tregs (Fig. 7c, lower panel). In contrast, ciLT increased the CD25⁻ Treg subset. Both peptides significantly reduced granulocytic Ly6G⁺CD11b⁺ MDSC and B220⁺ B cell infiltration at day 13. Notably, only nciLT suppressed melanoma and endothelium-derived CXCL1 and CXCL10 expression (Fig. 7d). Moreover, both blocking peptides suppressed tumor angiogenesis and lymphangiogenesis by reducing CD31⁺lyve-1^- blood vessels and CD31⁺lyve-1⁺ lymphatic vessels (Fig. 7e–g). Importantly, LTβR-nonclassical NFκB-driven SOX18, a crucial transcriptional regulator of angiogenesis³⁴, and FLRT2 which are highly expressed in LECs and facilitate tumor aggressiveness^35,36, were significantly reduced in lymphatic vessels in nciLT-treated melanoma. ciLT also suppressed their expression but less effectively than nciLT (Fig. 7e–g). SOX18 localized in both blood (CD31⁺Lyve-1^-) and lymphatic vessels (CD31⁺Lyve-1⁺), while FLRT2 mainly localized on lymphatic vessels alone (Figs. 7e, f, h). In dLNs, nciLT reduced both CD4 and CD8 T cells, while ciLT reduced CD4 but not CD8 T cells (Fig. 8a, upper panel), suggesting nciLT inhibited CD4 and CD8 T cell tumor egress, while ciLT inhibited CD4 T cell tumor egress which may contribute to the increased intratumoral CD4 Tregs. The total number of Tregs in dLNs were significantly decreased by both nciLT and ciLT (Fig. 8a, lower panel; 8b). Analysis of dLNs 20 days after melanoma development revealed that both nciLT and ciLT-treated mice had significantly reduced dLN melanoma metastasis and Tregs (Fig. 8b). The increased retention of IFNγ-producing CD8 T cells in tumor-infiltrating lymphocytes (TILs) and reduced CD25⁺Tregs in tumor and dLNs in LTβR blocking peptides treated melanoma may play critical roles for anti-tumor immunity.

**Fig. 7: Blockade of LTβR-nonclassical NF_ΚB inhibits tumor growth, immune suppressive cell recruitment, and tumor angio- and lymphangiogenesis.**

**Fig. 8: Blockade of LTβR-nonclassical NF_ΚB signaling reduces CD4 Tregs in dLNs and suppresses melanoma lymphatic metastases.**

Discussion

Here we report that contact-dependent tumor LTβR-NFκB-NIK signaling triggered by Treg LTα1β2 plays a critical role in tumor growth and metastases. In the TME, a high frequency of Tregs is associated with a poor prognosis in many cancers^37,38. However, effective approaches to selectively targeting intratumoral Tregs are limited. Beyond the known function of immunosuppression, activated Tregs exert other multifaceted functions, such as direct dialog with endothelial cells to regulate TEM of other immune cells^12,39. Our current and previous data^11,12 and published single-cell RNA sequencing data^40,41 have shown that human and mouse CD4 Tregs express the highest level of LTα1β2, while LTβR is predominantly expressed on most tumor cells and endothelial cells^42,43. The TCGA datasets showed high LTβR expressing patients with cancer have a worse prognosis, suggesting anti-LTβR as a potential therapy. However, both blockade and activation of LTβR have shown anti-tumor efficacy^1,6. Activation of LTβR with agonist mAb has been shown to induce both tumor apoptosis and promotion^1,6,44. The seemingly conflicting observations might be due to the bifurcation of LTβR-NFκB signaling. We confirmed that LTβRs on the mouse and human melanoma and breast cancer cells signal through classical NFκB-IKKβ-p65 and nonclassical NFκB-NIK-p52. Dissimilar to primary LEC LTβR, which constitutively binds TRAF3 and recruits TRAF2 upon activation, B16F10 LTβR constitutively binds TRAF2 and recruits TRAF3 for activation. nciLT blocked both TRAF2 and TRAF3 binding to the B16F10 LTβR complex, while blocking only TRAF3 binding to LEC LTβR³. Thus, nciLT not only inhibited melanoma LTβR-nonclassical NFκB-NIK-p52 but also inhibited B16F10 LTβR-classical NFκB-IKKβ-p65 signaling.

LTβR-nonclassical NFκB-NIK signaling has been implicated to upregulate metastatic genes and promote cancer cell lymphatic migration in head and neck cancer which has high levels of NIK and RelB expression⁴⁵, however, selective targeting of the LTβR-nonclassical NFκB-NIK pathway has not been studied. Here we employed specific LTβR receptor decoy permeable peptides to examine tumor TEM. LTβR nonclassical NFκB blocking peptide nciLT but not classical blocking peptide ciLT inhibited TEM of most tumors, including human melanoma and mouse and human breast cancer. B16F10, 4T1, and A549 TEM or migration responses were also inhibited by ciLT but with lesser efficacy, and these cell type-dependent effects may relate to varied TRAF2 and TRAF3 associations with the LTβR receptor in these cells. Conversely, activation of LTβR promoted tumor TEM. Notably, the presence of LECs significantly promoted tumor cell migration, suggesting LEC-derived adhesion or junctional molecules and chemokines are critical. We also observed that blocking LTβR-NIK signaling inhibited tumor cell growth and promoted apoptosis. Classical NFκB signaling is constitutively activated in tumor cells, yet ciLT did not affect tumor growth and produced modest inhibition of B16F10 TEM. LTβR-depleted melanoma cells, in which the entire receptor signaling is ablated, had slower in vivo growth and lymphatic metastasis, although there was no defect in growth in vitro, implicating the importance of environmental cues or intercellular communication in the TME. RNA-seq analysis of LTβR-depleted B16F10 revealed decreased gap junction protein GJA1, PDPN, NOTCH3, and BCAM1, which all regulate cell adhesion and may contribute to the reduced migration and metastasis. Thus, the complexities of LTβR signaling likely account for the diverse effects of receptor blockade or activation. These observations suggest that a more specific approach, as we show here on LTβR signaling pathways, may be more efficacious for tumor therapy.

We found Tregs use LTα1β2 to preferentially stimulate tumor LTβR nonclassical NFκB-NIK signaling to enhance tumor growth and migration. In contrast, neither LTα knockout Tregs nor Teffs enhanced tumor growth or migration. To clarify the role of other related receptor-ligand interactions between Tregs and tumor cells, we analyzed the other ligand of LTβR, LIGHT, however it was not detected on Tregs, while Teffs and B16F10 had negligible LIGHT expression (Supplementary Fig. 7a). Tregs have the highest level of HVEM, the receptor of LIGHT, while B16F10 has minimal HVEM expression, indicating Tregs and Teffs are unlikely to signal B16F10 through LIGHT/HVEM. Tregs but not LTα-deficient Tregs or Teffs induced melanoma LTβR nonclassical NFκB signaling, which was selectively inhibited by nciLT, further evidence that other receptors and ligands of the LTβR family are not involved. Other immune cells, such as B cells and CD8 T cells, also express LTα1β2, but the expression levels are less than that of Tregs in either homeostatic conditions or TME. Similar to Teffs, B cells did not induce LTβR-nonclassical NFkB signaling and had no impact on tumor cell migration. Hence, Tregs are the major source of LTα1β2 to engage LTβR on melanoma or breast cancer cells to promote tumor growth and TEM.

Adoptively transferred WT Tregs but not LTα-deficient Tregs promote tumor growth, and adoptively transferred primary LECs also restore tumor malignancy in LTβR-deficient mice, indicating the critical roles of Treg LTα1β2−LTβR interaction on tumor cells and LECs. Since LTα-deficient Tregs had no defect in immune suppression and viability¹¹, failure to suppress immunity was not the cause of their inability to promote tumor growth. Mechanistically, Treg-driven LTβR nonclassical NFκB signaling stimulates both tumor and LEC responses that sustain tumor survival, growth, and metastases. In the tumor, this signaling drives expression of angiogenic and immunosuppressive myeloid chemokines CXCL1, CXCL10, and CCL5; protumor interferon-stimulated genes ISG15 and IFIT3; and oncoprotein USP18, all of which promote tumor growth and metastases, and are selectively blocked by nciLT but not by ciLT. In LEC, this signaling drives endothelial-specific pro-lymphangiogenic SOX18, tumorigenic FLRT2, proangiogenic tumor endothelial molecules Clec14 and Apelin, and myeloid tropic chemokines to promote tumor growth and TEM. The Treg-activated LEC also directly favored tumor growth via cell-cell contact, and nciLT but not ciLT abolished this effect. Additionally, Treg LTα1β2 directly reduced LV and LEC junctional VE-cadherin expression to transform them from continuous “zipper” to discontinuous “button” junctions, promoting CD4 and CD8 egress from the tumor, thus impairing intratumoral immunity.

Leveraging in vivo Treg interactions with tumor and LECs, nciLT dramatically suppressed melanoma growth and metastasis with increased intratumoral IFNγ⁺CD8 T cells and reduced tumor CD25⁺CD4⁺ Tregs and MDSC infiltration and angiogenesis. Notably, nciLT reduced SOX18 and FLRT2 on tumor LECs, in line with SOX18-deficient mice having suppressed B16F10 lymphangiogenesis and metastases⁴⁶ and pharmaceutical inhibition of SOX18 reduced breast cancer vascularization and metastases⁴⁷. FLRT2 on tumor endothelial cells forms homophilic interendothelial adhesions to safeguard against oxidative stress, and endothelium-specific deletion of FLRT2 suppressed tumor metastases³⁵. Tumor and LEC-derived CXCL1 and CXCL10, recruit CXCR2⁺MDSCs⁴⁸ and CXCR3⁺Tregs⁴⁹ (Supplementary Fig. 7b), respectively. Thus, suppression of these chemokines by nciLT are likely key attributes for the reduced immune suppressive cells in tumor and enhanced anti-tumor immunity. Since CXCL10 recruits both Tregs and CD8 T cells⁵⁰, blockade of the initial prompt recruitment of Tregs to the tumor bed may play a critical role in tumor regression, which unleashes CD8 proliferation in the TME. In addition to their chemotactic properties, CXCL1 is implicated in tumor growth, angiogenesis, and tumorigenesis⁵¹. ciLT also enhanced effector T cells and reduced MDSCs in TME, which may contribute to efficient tumor regression at the early stage. The absence of inhibitory effects of ciLT on the CXCLs chemokines may contribute to later tumor relapse. ciLT also suppressed tumor angiogenesis with less efficiency than nciLT. It is noteworthy that LTβR-classical NFκB-driven RPL21, RPL30, MIEN1, and NR4a1, are selectively inhibited by ciLT. These rapidly induced early response protumor genes are overexpressed in various human cancers and proposed as targets for tumor therapy^51,52,53. Therefore, ciLT and nciLT combined therapy at selected times may optimize therapeutic efficacy. Together, our data revealed that Treg LTαβ promotes LTβR signaling in tumor cells and LECs. Selectively targeting Tregs or Treg-induced classical and nonclassical LTβR-NFκB signaling on tumor cells and LECs may provide a rational strategy to efficiently prevent tumor growth and metastasis.

Methods

Mice

Female C57BL/6J (WT, LTβR^−/−, LTα^−/−) (7–10 weeks), were purchased from The Jackson Laboratory (Bar Harbor, ME). Foxp3GFP mice on a C57BL/6 background were from Dr. A. Rudensky (Memorial Sloan Kettering Cancer Center) (Fontenot et al., 2005). LTα^−/− mice were crossed with Foxp3GFP mice to generate LTα^−/−Foxp3GFP mice. All animal experiments were performed in accordance with the Institutional Animal Care and Use Committee (IACUC) of the University of Maryland at Baltimore approved protocols. Animals of mixed sex and similar age were used within each cohort. The maximum allowable tumor size/burden (with a diameter of less than 2 cm) was not exceeded. Mice were housed at an ambient temperature of 24 ± 2 °C, with circulating air, constant humidity of 50 ± 10%, and a 12-h light/dark cycle.

Cell lines

The mouse melanoma B16F10-eGFP and mouse breast cancer 4T1-eGFP from Imanis Life Sciences (Rochester, MN), B16F10 and Human melanoma A375 from the American Type Culture Collection. were cultured in DMEM with GlutaMAX (4.5 g/L glucose, Invitrogen) containing 10% FCS (Gemini, CA) and 1% Penicillin/Streptomycin (Invitrogen). C57BL/6 mouse (C57-6064L) or human (H-6064L) primary dermal LECs were from Cell Biologics, Inc. (Chicago, IL), and were cultured according to the manufacturer’s instructions in manufacturer-provided mouse endothelial cell medium supplemented with 5% FBS, 2 mM l-glutamine, 100 IU /mL penicillin, vascular endothelial growth factor, endothelial cell growth supplement, heparin, epidermal growth factor, and hydrocortisone.

Peptides

LTβR decoy peptides were synthesized by GenScript. All peptides were >95% purity, dissolved in endotoxin-free ultrapure water. Peptide reconstitution and usage were described previously³. Peptide sequences can be found in Supplementary Table 3.

Mouse T cell and B cell purification and culture

Mouse naïve CD4 T and B cells were isolated using mouse CD4 and B cell negative selection kits (Stemcell Technologies, Cambridge, MA). CD4⁺Foxp3GFP⁺ Tregs or CD4⁺Foxp3 GFP^- naïve CD4 T cells were sorted from total CD4 T cells from LNs and spleens of WT or LTα^−/− Foxp3GFP mice using a FACS Aria II (BD Biosciences, San Jose, CA) with >98% purity. The sorted Tregs were cultured overnight at 37 °C in 5% CO₂, with medium containing IL-2 (20 ng/mL, eBioscience, San Diego, CA), plate-bound anti-CD3ɛ mAb (1 μg/mL, clone 145-2C11, eBioscience), and anti-CD28 mAb (1 μg/mL, clone 37.52, eBioscience), and human TGFβ1 (10 ng/mL, eBioscience). For effector T cells, the sorted naïve CD4 T cells were cultured with the medium but without human TGFβ1 for 3 days. All cells were cultured in complete RPMI 1640 supplemented with 10% FBS, 1 mM sodium pyruvate, 2 mM l-glutamine, 100 IU/mL penicillin, 100 μg /mL streptomycin, non-essential amino acids, and 2 × 10⁻⁵ M 2-ME (Sigma-Aldrich).

Human natural Treg and naive CD4 T cell purification and activation

Human Tregs were enriched from peripheral blood mononuclear cells (purchased from Memorial Blood Center (St. Paul, MN), complying with all relevant ethical regulations, donor consents, and Institutional Review Board (IRB) of Memorial Blood Center approval or exemption (https://www.mbc.org/products-and-services/research/)) with anti-CD25 microbeads (Miltenyi Biotec, Bergisch Gladbach, Germany). The CD4⁺CD25^highCD127⁻CD45RA⁺ natural Treg (nTreg) and CD4⁺CD25^-CD127⁺CD45RA⁺ naïve CD4 T cells were sorted by flow cytometry and were expanded as previously described⁵⁴. Briefly, purified nTreg were stimulated with irradiated KT64/86 cells cultured in XVivo-15 (BioWhittaker, Walkersville, MD) media containing 10% human AB serum (Valley Biomedical, Winchester, VA), Pen/Strep (Invitrogen, Carlsbad, CA), N-acetyl cysteine (USP), and recombinant IL-2 (300 IU/mL; Chiron, Emeryville, CA) for 14 days and frozen. The frozen nTreg and naïve CD4 were thawed and re-stimulated with anti-CD3/CD28 mAb-Dynabeads (Life Technologies, Carlsbad, CA) at 1:3 (cell to bead) plus recombinant IL-2 (300 U/mL) for 10 days before assay.

MTT viability assay and cell apoptosis analysis

Cells were plated into 24-well tissue culture plates. After treatment, the cells were washed and followed by 3-h incubation with 0.5 mg/mL MTT (3-(4, 5-Dimethylthiazol-2-yl)−2,5 diphenyl tetrazolium bromide) (Sigma-Aldrich). Cell apoptosis was measured with Annexin V Apoptosis Detection Kit I (BD Pharmingen) following manufactory instructions.

Flow cytometry

Cells were washed and incubated with anti-CD16/32 (clone 93, eBioscience), followed by incubation with fluorescently labeled antibodies (See Supplementary Table 3) for 30 min at 4 °C. Cells were then washed and fixed with 4% paraformaldehyde. Data acquisition was performed using an LSR Fortessa flow cytometer (BD Biosciences) and analyzed with FlowJo 10. 8.1 (Tree Star, Inc).

Immunoblotting

Cells were lysed in buffer containing 20 mM Hepes (pH 7.4), 150 mM NaCl, 10 mM NaF, 2 mM Na₃VO₄, 1 mM EDTA, 1 mM EGTA, 0.5% Triton X-100, 0.1 mM DTT, 1 mM PMSF, and protease inhibitor cocktail (Roche). Protein in the cell extract was quantified using a protein quantification kit (Bio-Rad, Philadelphia, PA), and 10 μg total protein was run on Novex™ WedgeWell™ 4–20% Tris-Glycine Mini Gels (Invitrogen) and transferred to an Immobilon-P membrane (Bio-Rad). Membranes were probed with indicated antibodies (See Supplementary Table 3). Quantification of blots was performed with ImageJ from the National Institutes for Health. The relative intensity of blots was normalized to housekeeping gene GAPDH and presented as fold induction to non-stimulation.

Quantitative reverse transcription PCR and cDNA microarray analysis

About 1 μg of total RNA extracted using Trizol reagent (Invitrogen) was reverse transcribed into cDNA with GoScript™ Reverse Transcription System (Promega, Fitchburg, WI). mRNA expression levels were quantified by real-time PCR using SYBR Green Master Mix with an ABI Prism 7900HT (Applied Biosystems, Foster City, CA). Values for specific gene expression were normalized to housekeeping HPRT gene expression and were calculated as: 2^(Ct of HPRT−Ct specific gene). For microarray analysis, samples were further cleaned using an RNeasy Mini Kit (QIAGEN), labeled with Cyanine 3-CTP using a Low Input Quick Amp Labeling Kit (Agilent), and hybridized to a SurePrint G3 Mouse GE Microarray (Agilent). Fluorescence was scanned using a DNA Microarray Scanner (Agilent) and quantified with Feature Extraction ver 10.7.1.1 (Agilent). Expression values for each probe set were calculated using the RMA method with GeneSpring Gx 12.0 software (Agilent). Primers can be found in Supplementary Table 3.

Bulk RNA sequencing

Total RNA was isolated using the NucleoSpin RNA Plus kit per the manufacturer’s instructions. Messenger RNA was purified and sequenced by Novogene. Reference genome and gene model annotation files were downloaded from Ensembl directly. Index of the reference genome was built using Hisat2 v2.0.5 and paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5. featureCounts v1.5.0-p3 was used to count the reads numbers mapped to each gene. FPKM (fragments per kilobase of transcript sequence per millions) of each gene was calculated based on the length of the gene and the read count mapped to this gene. Differential expression analysis of two conditions was performed using the edgeR R package (version 3.22.5). Differential expression analysis of two conditions/groups (two biological replicates per condition) was performed using the DESeq2 R package (1.20.0). The resulting P-values were adjusted using Benjamini and Hochberg’s approach for controlling the false discovery rate. Genes with an adjusted P value ≤0.05 found by DESeq2 were assigned as differentially expressed. Gene ontology (GO) enrichment analysis of differentially expressed genes was implemented by the clusterProfiler R package.

Time-lapse microscopy

WT or LTβR^-/-B16F10-GFP (5 × 10⁴ cells per transwell) migrating across endothelial monolayers to CCL19 (50 ng/mL) were visualized by EVOS FL Auto Cell Imaging System (Thermo Fisher Scientific) with a ×20 objective. One image was captured every 5 min for 3 h. Cell tracks were analyzed with Volocity version 6.3 software (Perkin Elmer).

Tumor cell lymphatic transendothelial migration

Transmigrations across endothelial cells were described previously (ref. ¹¹; ref. ²²). Briefly, the inverted transwell insert (24-well, Corning International) with 8 μm pore size was coated with 0.2% (w/v) gelatin (Bio-Rad) for 1 h at 37 °C before loading with 1.0 × 10⁵ primary skin LEC in 100 μL LEC medium. After 2 days, the LEC cell layers were treated with various conditions as noted in the text and figure legends prior to adding 1 × 10⁵ tumor cells in 100 μL to the upper chamber of the transwell plate while the lower chamber contained S1P (Avanti Polar Lipids, Inc., Alabaster, AL). All cells or reagents were prepared in IMDM containing transferrin and 0.5% (w/v) fatty acid-free BSA (Gemini, West Sacramento, CA). T cells that migrated to the lower chamber after 3 h at 37 °C were counted.

Cell migration assay

The cells were seeded in a 12-well plate and cultured to 90% confluence. The plates were scratched with a sterile 200 μL pipette tip on the cell monolayer. The cells pretreated with peptides were then cultured for 48 h. The images were acquired using an ordinary optics microscope (Olympus, Japan) at 0 and 48 h. The migration percentage was calculated according to this formula: (the size of the cell defect at 0 h − the size of the defect at 48 h)/the size of the defect at 0 h.

Immunohistochemistry

Cell monolayers or tissues were fixed for 20 min at 4 °C with 4% (w/v) paraformaldehyde (Affymetrix, Santa Clara, CA), then permeabilized with PBS 0.2% (v/v) Triton X-100 (Sigma-Aldrich) and treated with 4% donkey serum for 30 min then incubated with primary antibodies (see Supplementary Table 3) for overnight at 4 °C. The bound antibodies were detected with Alexa Fluor 448, 647 (Cy5), or 546 (Cy3)-conjugated secondary antibodies (Jackson ImmunoResearch, West Grove, PA) for 1 h at 4 °C. The mounted slides were visualized by fluorescent microscopy (Zeiss LSM 510 Meta and LSM5 Duo). Images were analyzed with Volocity version 6.3 software. Quantification of the junctional VE-cadherin in 60x magnified images of LVs of whole-mounted LVs or adherent LECs was performed with ImageJ. Length of zipper junctions and button junctions were measured. The percentage of zipper junction was calculated as the length of zipper junction × 100/(length of zipper junction + length of button junction)⁵⁵.

CRISPR/Cas9 knockout of LTβR, NIK, and IKKβ in B16F10 and LECs

gRNA designed to target the common exons for all murine LTβR, NIK, and IKKβ isoforms were synthesized as oligo: 5′-AGCCGAGTGCCGCTGTCAGC-3′, 5′-GCTGGCCGCCATCAAGGTTA−3′, and 5′-CGCCATCAAGCAATGCCGAC-3′, respectively and cloned to lentiCRISPRv2 (include Cas9 and puromycin-resistant gene) vector by GenScript. Lentiviruses were produced by co-transfecting HEK293T cells with the packaging plasmids psPAX2 and pMD2.G (Addgene plasmid # 12260 and 12259) and the transfer plasmid LentiCRISPRv2-gRNAs, using Lipofectamine 2000 (Thermo Fisher Scientific). The media was changed to antibiotic-free complete DMEM with 10% FBS after 16 h. The lentivirus supernatants were collected 24 and 48 h after transfection and filtered through 0.45 mm PES syringe filter (SARSTEDT, Newton, NC). mLEC, B16F10, or B16F10-fluc/eGFP were transduced with the lentiviruses for 3 days, followed by a selection medium containing 2 mg/mL puromycin (Sigma-Aldrich) for 3 days. LTβR-lentiCRISPRv2 transduced B16F10-fluc/eGFP cells which have Neomycin and Puromycin resistance, were flow sorted for GFP⁺LTβR^- cells. Surviving or sorted cells were expanded and checked with immunoblotting of NIK and IKKβ expression or flow cytometry analysis of LTβR surface expression.

Tumor treatments

WT or LTβR^−/− C57/BL6J mice (7–8 weeks old, female) were subcutaneously injected with 0.5 × 10⁶ WT B16F10 or B16F10-fluc/eGFP tumor cells. 5, 7, 9, and 11 days after tumor inoculation, tumor-bearing mice were peritumoral injected with 20 nmol of CP, nciLT, or ciLT. The tumor volume was recorded for each mouse every 2 days and calculated according to (longest width) × (longest length)²/2. 2 or 9 days after the last peptide treatment, six mice from each group were euthanized, and the tumors and dLNs were harvested and analyzed by flow cytometry or immunohistochemistry. Parallel groups of mice were monitored daily for tumor growth. There were 6 to 10 mice in each group. For the Treg adoptive transfer assay, induced Tregs differentiated from naïve CD4 T cells from WT or LTα KO Foxp3GFP transgenic mice were FACS sorted before intravenous transfer of 0.5 × 10⁶ cells per mouse. For the LEC adoptive transfer assay, 1 × 10⁵ primary mouse LECs were intravenously transferred to WT or LTβRKO C57BL/6 mice inoculated with WT B16F10. For the pulmonary metastases study, mice were injected via the tail vein with 0.3 × 10⁶ WT B16F10 or B16F10-fluc/eGFP. Lungs were harvested on day 21 after injection.

Quantification and statistical analysis

Numerical data are presented as mean ± SEM. Asterisks mark data statistically different from the controls, with p values noted in the figure legends. The p values were calculated by one-way or two-way ANOVA and Student’s t-tests (paired or unpaired) using GraphPad Prism version 10.1.0 (La Jolla, CA). The number of replicates is noted in the figure legends.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The RNA sequencing data and cDNA microarray processed data generated in this study has been deposited and have been made publicly available at NCBI’s Gene Expression Omnibus (GEO) repository with accession numbers GSE271338 and GSE270960, respectively. The TCGA data of human skin cutaneous melanoma, breast cancer, lung cancer patients were accessible using the NIH-NCI GDC Data Portal (https://portal.gdc.cancer.gov/)⁵⁶ using the following accessions: skin cutaneous (phs000178), melanoma, breast cancer (phs000178), and lung cancer (phs000178) [https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000178]. The remaining data were available within the Article, Supplementary Information or Source Data file. Source data are provided with this paper.

References

Lukashev, M. et al. Targeting the lymphotoxin-beta receptor with agonist antibodies as a potential cancer therapy. Cancer Res. 66, 9617–9624 (2006).
Article CAS PubMed Google Scholar
Gommerman, J. L. & Browning, J. L. Lymphotoxin/light, lymphoid microenvironments and autoimmune disease. Nat. Rev. Immunol. 3, 642–655 (2003).
Article CAS PubMed Google Scholar
Piao, W. et al. Regulation of T cell afferent lymphatic migration by targeting LTbetaR-mediated non-classical NFkappaB signaling. Nat. Commun. 9, 3020 (2018).
Article ADS PubMed PubMed Central Google Scholar
Wolf, M. J., Seleznik, G. M., Zeller, N. & Heikenwalder, M. The unexpected role of lymphotoxin beta receptor signaling in carcinogenesis: from lymphoid tissue formation to liver and prostate cancer development. Oncogene 29, 5006–5018 (2010).
Article CAS PubMed Google Scholar
Keats, J. J. et al. Promiscuous mutations activate the noncanonical NF-kappaB pathway in multiple myeloma. Cancer Cell 12, 131–144 (2007).
Article CAS PubMed PubMed Central Google Scholar
Hehlgans, T. et al. Lymphotoxin-beta receptor immune interaction promotes tumor growth by inducing angiogenesis. Cancer Res. 62, 4034–4040 (2002).
CAS PubMed Google Scholar
Tang, H. et al. Facilitating T cell infiltration in tumor microenvironment overcomes resistance to PD-L1 blockade. Cancer Cell 30, 500 (2016).
Article CAS PubMed Google Scholar
Hu, X. et al. Lymphotoxin beta receptor mediates caspase-dependent tumor cell apoptosis in vitro and tumor suppression in vivo despite induction of NF-kappaB activation. Carcinogenesis 34, 1105–1114 (2013).
Article CAS PubMed PubMed Central Google Scholar
Kos, K. et al. Tumor-educated T(regs) drive organ-specific metastasis in breast cancer by impairing NK cells in the lymph node niche. Cell Rep. 38, 110447 (2022).
Article CAS PubMed Google Scholar
Kos, K. & de Visser, K. E. The multifaceted role of regulatory T cells in breast cancer. Annu. Rev. Cancer Biol. 5, 291–310 (2021).
Article PubMed Google Scholar
Brinkman, C. C. et al. Treg engage lymphotoxin beta receptor for afferent lymphatic transendothelial migration. Nat. Commun. 7, 12021 (2016).
Article ADS PubMed PubMed Central Google Scholar
Piao, W. et al. Regulatory T cells condition lymphatic endothelia for enhanced transendothelial migration. Cell Rep. 30, 1052–1062 e1055 (2020).
Article CAS PubMed PubMed Central Google Scholar
Onder, L. et al. Endothelial cell-specific lymphotoxin-beta receptor signaling is critical for lymph node and high endothelial venule formation. J. Exp. Med. 210, 465–473 (2013).
Article CAS PubMed PubMed Central Google Scholar
Zhai, Y. et al. LIGHT, a novel ligand for lymphotoxin beta receptor and TR2/HVEM induces apoptosis and suppresses in vivo tumor formation via gene transfer. J. Clin. Invest. 102, 1142–1151 (1998).
Article CAS PubMed PubMed Central Google Scholar
Leong, S. P., Naxerova, K., Keller, L., Pantel, K. & Witte, M. Molecular mechanisms of cancer metastasis via the lymphatic versus the blood vessels. Clin. Exp. Metastasis 39, 159–179 (2022).
Article CAS PubMed Google Scholar
Kohli, K., Pillarisetty, V. G. & Kim, T. S. Key chemokines direct migration of immune cells in solid tumors. Cancer Gene Ther. 29, 10–21 (2022).
Article CAS PubMed Google Scholar
Yang, H. et al. Sox17 promotes tumor angiogenesis and destabilizes tumor vessels in mice. J. Clin. Invest. 123, 418–431 (2013).
Article CAS PubMed Google Scholar
Grimm, D. et al. The role of SOX family members in solid tumours and metastasis. Semin Cancer Biol. 67, 122–153 (2020).
Article CAS PubMed Google Scholar
Chen, H., Xu, C., Jin, Q. & Liu, Z. S100 protein family in human cancer. Am. J. Cancer Res. 4, 89–115 (2014).
PubMed PubMed Central Google Scholar
Acharyya, S. et al. A CXCL1 paracrine network links cancer chemoresistance and metastasis. Cell 150, 165–178 (2012).
Article CAS PubMed PubMed Central Google Scholar
Cartier, A. & Hla, T. Sphingosine 1-phosphate: lipid signaling in pathology and therapy. Science https://doi.org/10.1126/science.aar5551 (2019).
Xiong, Y. et al. A robust in vitro model for trans-lymphatic endothelial migration. Sci. Rep. 7, 1633 (2017).
Article ADS PubMed PubMed Central Google Scholar
Wang, N. et al. CXCL1 derived from tumor-associated macrophages promotes breast cancer metastasis via activating NF-kappaB/SOX4 signaling. Cell Death Dis. 9, 880 (2018).
Article PubMed PubMed Central Google Scholar
Kim, M., Choi, H. Y., Woo, J. W., Chung, Y. R. & Park, S. Y. Role of CXCL10 in the progression of in situ to invasive carcinoma of the breast. Sci. Rep. 11, 18007 (2021).
Article ADS CAS PubMed PubMed Central Google Scholar
Aldinucci, D. & Colombatti, A. The inflammatory chemokine CCL5 and cancer progression. Mediators Inflamm. 2014, 292376 (2014).
Article PubMed PubMed Central Google Scholar
Bolado-Carrancio, A. et al. ISGylation drives basal breast tumour progression by promoting EGFR recycling and Akt signalling. Oncogene 40, 6235–6247 (2021).
Article CAS PubMed PubMed Central Google Scholar
Pidugu, V. K., Pidugu, H. B., Wu, M. M., Liu, C. J. & Lee, T. C. Emerging functions of human IFIT proteins in cancer. Front. Mol. Biosci. 6, 148 (2019).
Article CAS PubMed PubMed Central Google Scholar
Hong, B. et al. USP18 is crucial for IFN-gamma-mediated inhibition of B16 melanoma tumorigenesis and antitumor immunity. Mol. Cancer 13, 132 (2014).
Article PubMed PubMed Central Google Scholar
Kang, J. et al. Ribosomal proteins and human diseases: molecular mechanisms and targeted therapy. Signal Transduct. Target Ther. 6, 323 (2021).
Article ADS CAS PubMed PubMed Central Google Scholar
Kpetemey, M. et al. MIEN1, a novel interactor of Annexin A2, promotes tumor cell migration by enhancing AnxA2 cell surface expression. Mol. Cancer 14, 156 (2015).
Article PubMed PubMed Central Google Scholar
Hibino, S. et al. Inhibition of Nr4a receptors enhances antitumor immunity by breaking Treg-mediated immune tolerance. Cancer Res. 78, 3027–3040 (2018).
Article CAS PubMed Google Scholar
Sidibe, A. & Imhof, B. A. VE-cadherin phosphorylation decides: vascular permeability or diapedesis. Nat. Immunol. 15, 215–217 (2014).
Article CAS PubMed Google Scholar
Futterer, A., Mink, K., Luz, A., Kosco-Vilbois, M. H. & Pfeffer, K. The lymphotoxin beta receptor controls organogenesis and affinity maturation in peripheral lymphoid tissues. Immunity 9, 59–70 (1998).
Article CAS PubMed Google Scholar
Young, N. et al. Effect of disrupted SOX18 transcription factor function on tumor growth, vascularization, and endothelial development. J. Natl Cancer Inst. 98, 1060–1067 (2006).
Article CAS PubMed Google Scholar
Ando, T. et al. Tumor-specific interendothelial adhesion mediated by FLRT2 facilitates cancer aggressiveness. J. Clin. Invest. https://doi.org/10.1172/JCI153626 (2022).
Olbromski, M., Podhorska-Okolow, M. & Dziegiel, P. Role of the SOX18 protein in neoplastic processes. Oncol. Lett. 16, 1383–1389 (2018).
PubMed PubMed Central Google Scholar
Petersen, R. P. et al. Tumor infiltrating Foxp3+ regulatory T-cells are associated with recurrence in pathologic stage I NSCLC patients. Cancer 107, 2866–2872 (2006).
Article PubMed Google Scholar
Saleh, R. & Elkord, E. Acquired resistance to cancer immunotherapy: role of tumor-mediated immunosuppression. Semin Cancer Biol. 65, 13–27 (2020).
Article CAS PubMed Google Scholar
Ring, S. et al. Regulatory T cells prevent neutrophilic infiltration of skin during contact hypersensitivity reactions by strengthening the endothelial barrier. J. Invest. Dermatol. 141, 2006–2017 (2021).
Article CAS PubMed Google Scholar
He, M. X. et al. Transcriptional mediators of treatment resistance in lethal prostate cancer. Nat. Med. 27, 426–433 (2021).
Article CAS PubMed PubMed Central Google Scholar
Wu, S. Z. et al. A single-cell and spatially resolved atlas of human breast cancers. Nat. Genet. 53, 1334–1347 (2021).
Article CAS PubMed PubMed Central Google Scholar
Wu, S. Z. et al. Cryopreservation of human cancers conserves tumour heterogeneity for single-cell multi-omics analysis. Genome Med. 13, 81 (2021).
Article CAS PubMed PubMed Central Google Scholar
Zilionis, R. et al. Single-cell transcriptomics of human and mouse lung cancers reveals conserved myeloid populations across individuals and species. Immunity 50, 1317–1334 e1310 (2019).
Article CAS PubMed PubMed Central Google Scholar
Daller, B. et al. Lymphotoxin-beta receptor activation by lymphotoxin-alpha(1)beta(2) and LIGHT promotes tumor growth in an NFkappaB-dependent manner. Int. J. Cancer 128, 1363–1370 (2011).
Article CAS PubMed Google Scholar
Das, R. et al. Lymphotoxin-beta receptor-NIK signaling induces alternative RELB/NF-kappaB2 activation to promote metastatic gene expression and cell migration in head and neck cancer. Mol. Carcinog. 58, 411–425 (2019).
Article CAS PubMed Google Scholar
Duong, T. et al. Genetic ablation of SOX18 function suppresses tumor lymphangiogenesis and metastasis of melanoma in mice. Cancer Res. 72, 3105–3114 (2012).
Article CAS PubMed Google Scholar
Overman, J. et al. Pharmacological targeting of the transcription factor SOX18 delays breast cancer in mice. Elife https://doi.org/10.7554/eLife.21221 (2017).
Highfill, S. L. et al. Disruption of CXCR2-mediated MDSC tumor trafficking enhances anti-PD1 efficacy. Sci. Transl. Med. 6, 237ra267 (2014).
Article Google Scholar
Moreno Ayala, M. A. et al. CXCR3 expression in regulatory T cells drives interactions with type I dendritic cells in tumors to restrict CD8(+) T cell antitumor immunity. Immunity 56, 1613–1630 e1615 (2023).
Article CAS PubMed Google Scholar
Ozga, A. J., Chow, M. T. & Luster, A. D. Chemokines and the immune response to cancer. Immunity 54, 859–874 (2021).
Article CAS PubMed PubMed Central Google Scholar
Kushwaha, P. P., Gupta, S., Singh, A. K. & Kumar, S. Emerging role of migration and invasion enhancer 1 (MIEN1) in cancer progression and metastasis. Front. Oncol. 9, 868 (2019).
Article PubMed PubMed Central Google Scholar
Guo, H. et al. NR4A1 regulates expression of immediate early genes, suppressing replication stress in cancer. Mol. Cell 81, 4041–4058 e4015 (2021).
Article CAS PubMed PubMed Central Google Scholar
Li, C. et al. RPL21 siRNA blocks proliferation in pancreatic cancer cells by inhibiting DNA replication and inducing G1 arrest and apoptosis. Front. Oncol. 10, 1730 (2020).
Article PubMed PubMed Central Google Scholar
Hippen, K. L. et al. Generation and large-scale expansion of human inducible regulatory T cells that suppress graft-versus-host disease. Am. J. Transpl. 11, 1148–1157 (2011).
Article CAS Google Scholar
Zhang, F. et al. Lacteal junction zippering protects against diet-induced obesity. Science 361, 599–603 (2018).
Article ADS CAS PubMed PubMed Central Google Scholar
Grossman, R. L. et al. Toward a shared vision for cancer genomic data. N. Engl. J. Med. 375, 1109–1112 (2016).
Article PubMed PubMed Central Google Scholar

Download references

Acknowledgements

This work was supported by NIH grant R37 AI062765 to J.S.B., Emerald grant 2022 to J.S.B. and W.P., R01 AI126596 and R01 HL141815 to R.A., R37 AI34495, R01 HL11879, R01 HL15514, and P01 CA 065493 to B.R.B. and K.L.H. Dr. Xiaoxuan Fan from UMB-Flow Core Facility for his excellent help for flow cell sorting and data analysis.

Author information

These authors contributed equally: Wenji Piao, Long Wu, Yanbao Xiong, Gregory C. Zapas.

Authors and Affiliations

Department of Surgery, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
Wenji Piao, Long Wu, Yanbao Xiong, Christina M. Paluskievicz, Young Lee, Lushen Li & Jonathan S. Bromberg
Center for Vascular and Inflammatory Diseases, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
Wenji Piao, Long Wu, Yanbao Xiong, Gregory C. Zapas, Sarah M. Pettit, Dejun Kong, Young Lee, Lushen Li, Marina W. Shirkey, Allison Kensiski, Aamna Alvi, Kevin Ho, Vikas Saxena & Jonathan S. Bromberg
Fischell Department of Bioengineering, University of Maryland, 8278 Paint Branch Drive, College Park, MD, 20742, USA
Robert S. Oakes, Christopher M. Jewell & Jonathan S. Bromberg
Department of Pediatrics, Division of Blood & Marrow Transplantation & Cellular Therapy, University of Minnesota, Minneapolis, MN, 55455, USA
Margaret L. Sleeth, Keli L. Hippen & Bruce R. Blazar
Institute for Pathology, Hannover Medical School, 30625, Hannover, Germany
Jessica Schmitz & Jan H. Bräsen
Department of Hematology and Oncology, Hannover Medical School, 30625, Hannover, Germany
Philipp Ivanyi
Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
Amol C. Shetty & Yang Song
Transplantation Research Center, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02115, USA
Reza Abdi
Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
Jonathan S. Bromberg

Authors

Wenji Piao
View author publications
Search author on:PubMed Google Scholar
Long Wu
View author publications
Search author on:PubMed Google Scholar
Yanbao Xiong
View author publications
Search author on:PubMed Google Scholar
Gregory C. Zapas
View author publications
Search author on:PubMed Google Scholar
Christina M. Paluskievicz
View author publications
Search author on:PubMed Google Scholar
Robert S. Oakes
View author publications
Search author on:PubMed Google Scholar
Sarah M. Pettit
View author publications
Search author on:PubMed Google Scholar
Margaret L. Sleeth
View author publications
Search author on:PubMed Google Scholar
Keli L. Hippen
View author publications
Search author on:PubMed Google Scholar
Jessica Schmitz
View author publications
Search author on:PubMed Google Scholar
Philipp Ivanyi
View author publications
Search author on:PubMed Google Scholar
Amol C. Shetty
View author publications
Search author on:PubMed Google Scholar
Yang Song
View author publications
Search author on:PubMed Google Scholar
Dejun Kong
View author publications
Search author on:PubMed Google Scholar
Young Lee
View author publications
Search author on:PubMed Google Scholar
Lushen Li
View author publications
Search author on:PubMed Google Scholar
Marina W. Shirkey
View author publications
Search author on:PubMed Google Scholar
Allison Kensiski
View author publications
Search author on:PubMed Google Scholar
Aamna Alvi
View author publications
Search author on:PubMed Google Scholar
Kevin Ho
View author publications
Search author on:PubMed Google Scholar
Vikas Saxena
View author publications
Search author on:PubMed Google Scholar
Jan H. Bräsen
View author publications
Search author on:PubMed Google Scholar
Christopher M. Jewell
View author publications
Search author on:PubMed Google Scholar
Bruce R. Blazar
View author publications
Search author on:PubMed Google Scholar
Reza Abdi
View author publications
Search author on:PubMed Google Scholar
Jonathan S. Bromberg
View author publications
Search author on:PubMed Google Scholar

Contributions

W.P. and J.S.B. designed the research. W.P., L.W., Y.X., G.C.Z., S.M.P., M.L.S., R.S.O., J.S., K.H., C.M.P., D.K., Y.L., A.K., L.L., A.A., V.S., and M.W.S. performed the experiments. A.C.S. and Y.S. performed bioinformatic data analysis of the TCGA datasets. W.P., J.S.B., B.R.B., K.L.H., R.A., P.I., J.H.B., and C.M.J. analyzed and discussed the results. W.P. and J.S.B. wrote the manuscript.

Corresponding authors

Correspondence to Wenji Piao or Jonathan S. Bromberg.

Ethics declarations

Competing interests

J.S.B., W.P., and X.Y. are inventors on a patent related to LTβR antagonists entitled “Inhibitors of LTβR-NFκB signaling pathways for treating inflammation and cancer” (Patent number: 11590202). The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Reporting Summary

Peer Review file

Source data

Source Data

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Cite this article

Piao, W., Wu, L., Xiong, Y. et al. Regulatory T cells crosstalk with tumor cells and endothelium through lymphotoxin signaling. Nat Commun 15, 10468 (2024). https://doi.org/10.1038/s41467-024-54874-y

Download citation

Received: 05 March 2024
Accepted: 25 November 2024
Published: 02 December 2024
DOI: https://doi.org/10.1038/s41467-024-54874-y