Lymph node (LN) stromal cells, particularly fibroblastic reticular cells (FRCs), provide critical structural support and regulate immunity, tolerance and the transport properties of LNs. For many tumors, metastasis to the LNs is predictive of poor prognosis. However, the stromal contribution to the evolving microenvironment of tumor-draining LNs (TDLNs) remains poorly understood. Here we found that FRCs specifically of TDLNs proliferated in response to tumor-derived cues and that the network they formed was remodeled. Comparative transcriptional analysis of FRCs from non-draining LNs and TDLNs demonstrated reprogramming of key pathways, including matrix remodeling, chemokine and/or cytokine signaling, and immunological functions such as the recruitment, migration and activation of leukocytes. In particular, downregulation of the expression of FRC-derived chemokine CCL21 and cytokine IL-7 were accompanied by altered composition and aberrant localization of immune-cell populations. Our data indicate that following exposure to tumor-derived factors, the stroma of TDLNs adapts on multiple levels to exhibit features typically associated with immunosuppression.
Subscribe to Journal
Get full journal access for 1 year
only $18.75 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Gene Expression Omnibus
Bajénoff, M. et al. Stromal cell networks regulate lymphocyte entry, migration, and territoriality in lymph nodes. Immunity 25, 989–1001 (2006).
Link, A. et al. Fibroblastic reticular cells in lymph nodes regulate the homeostasis of naive T cells. Nat. Immunol. 8, 1255–1265 (2007).
Schumann, K. et al. Immobilized chemokine fields and soluble chemokine gradients cooperatively shape migration patterns of dendritic cells. Immunity 32, 703–713 (2010).
Roozendaal, R., Mebius, R.E. & Kraal, G. The conduit system of the lymph node. Int. Immunol. 20, 1483–1487 (2008).
Gretz, J.E., Norbury, C.C., Anderson, A.O., Proudfoot, A.E. & Shaw, S. Lymph-borne chemokines and other low molecular weight molecules reach high endothelial venules via specialized conduits while a functional barrier limits access to the lymphocyte microenvironments in lymph node cortex. J. Exp. Med. 192, 1425–1440 (2000).
Roozendaal, R. et al. Conduits mediate transport of low-molecular-weight antigen to lymph node follicles. Immunity 30, 264–276 (2009).
Sixt, M. et al. The conduit system transports soluble antigens from the afferent lymph to resident dendritic cells in the T cell area of the lymph node. Immunity 22, 19–29 (2005).
Luther, S.A., Tang, H.L., Hyman, P.L., Farr, A.G. & Cyster, J.G. Coexpression of the chemokines ELC and SLC by T zone stromal cells and deletion of the ELC gene in the plt/plt mouse. Proc. Natl. Acad. Sci. USA 97, 12694–12699 (2000).
Förster, R., Davalos-Misslitz, A.C. & Rot, A. CCR7 and its ligands: balancing immunity and tolerance. Nat. Rev. Immunol. 8, 362–371 (2008).
Katakai, T. et al. A novel reticular stromal structure in lymph node cortex: an immuno-platform for interactions among dendritic cells, T cells and B cells. Int. Immunol. 16, 1133–1142 (2004).
Katakai, T., Hara, T., Sugai, M., Gonda, H. & Shimizu, A. Lymph node fibroblastic reticular cells construct the stromal reticulum via contact with lymphocytes. J. Exp. Med. 200, 783–795 (2004).
Gunn, M.D. et al. A chemokine expressed in lymphoid high endothelial venules promotes the adhesion and chemotaxis of naive T lymphocytes. Proc. Natl. Acad. Sci. USA 95, 258–263 (1998).
Fletcher, A.L. et al. Lymph node fibroblastic reticular cells directly present peripheral tissue antigen under steady-state and inflammatory conditions. J. Exp. Med. 207, 689–697 (2010).
Lee, J.W. et al. Peripheral antigen display by lymph node stroma promotes T cell tolerance to intestinal self. Nat. Immunol. 8, 181–190 (2007).
Nichols, L.A. et al. Deletional self-tolerance to a melanocyte/melanoma antigen derived from tyrosinase is mediated by a radio-resistant cell in peripheral and mesenteric lymph nodes. J. Immunol. 179, 993–1003 (2007).
Mueller, S.N. et al. Viral targeting of fibroblastic reticular cells contributes to immunosuppression and persistence during chronic infection. Proc. Natl. Acad. Sci. USA 104, 15430–15435 (2007).
de Boer, M., van Dijck, J.A., Bult, P., Borm, G.F. & Tjan-Heijnen, V.C. Breast cancer prognosis and occult lymph node metastases, isolated tumor cells, and micrometastases. J. Natl. Cancer Inst. 102, 410–425 (2010).
Morton, D.L. et al. MSLT Group. Sentinel-node biopsy or nodal observation in melanoma. N. Engl. J. Med. 355, 1307–1317 (2006).
Karaman, S. & Detmar, M. Mechanisms of lymphatic metastasis. J. Clin. Invest. 124, 922–928 (2014).
Malhotra, D. et al. Transcriptional profiling of stroma from inflamed and resting lymph nodes defines immunological hallmarks. Nat. Immunol. 13, 499–510 (2012).
Cox, T.R. & Erler, J.T. Molecular pathways: connecting fibrosis and solid tumor metastasis. Clin. Cancer Res. 20, 3637–3643 (2014).
Kalluri, R. & Zeisberg, M. Fibroblasts in cancer. Nat. Rev. Cancer 6, 392–401 (2006).
Cremasco, V. et al. B cell homeostasis and follicle confines are governed by fibroblastic reticular cells. Nat. Immunol. 15, 973–981 (2014).
Fletcher, A.L., Acton, S.E. & Knoblich, K. Lymph node fibroblastic reticular cells in health and disease. Nat. Rev. Immunol. 15, 350–361 (2015).
Förster, R., Braun, A. & Worbs, T. Lymph node homing of T cells and dendritic cells via afferent lymphatics. Trends Immunol. 33, 271–280 (2012).
Gunn, M.D. et al. Mice lacking expression of secondary lymphoid organ chemokine have defects in lymphocyte homing and dendritic cell localization. J. Exp. Med. 189, 451–460 (1999).
Mueller, S.N. et al. Regulation of homeostatic chemokine expression and cell trafficking during immune responses. Science 317, 670–674 (2007).
Yang, C.Y. et al. Trapping of naive lymphocytes triggers rapid growth and remodeling of the fibroblast network in reactive murine lymph nodes. Proc. Natl. Acad. Sci. USA 111, E109–E118 (2014).
Harrell, M.I., Iritani, B.M. & Ruddell, A. Tumor-induced sentinel lymph node lymphangiogenesis and increased lymph flow precede melanoma metastasis. Am. J. Pathol. 170, 774–786 (2007).
Hirakawa, S. et al. VEGF-C-induced lymphangiogenesis in sentinel lymph nodes promotes tumor metastasis to distant sites. Blood 109, 1010–1017 (2007).
Hirakawa, S. et al. VEGF-A induces tumor and sentinel lymph node lymphangiogenesis and promotes lymphatic metastasis. J. Exp. Med. 201, 1089–1099 (2005).
Rohner, N.A. et al. Lymph node biophysical remodeling is associated with melanoma lymphatic drainage. FASEB J. 29, 4512–4522 (2015).
Carrière, V. et al. Cancer cells regulate lymphocyte recruitment and leukocyte-endothelium interactions in the tumor-draining lymph node. Cancer Res. 65, 11639–11648 (2005).
Soudja, S.M. et al. Disrupted lymph node and splenic stroma in mice with induced inflammatory melanomas is associated with impaired recruitment of T and dendritic cells. PLoS One 6, e22639 (2011).
MartIn-Fontecha, A. et al. Regulation of dendritic cell migration to the draining lymph node: impact on T lymphocyte traffic and priming. J. Exp. Med. 198, 615–621 (2003).
St. John, A.L. & Abraham, S.N. Salmonella disrupts lymph node architecture by TLR4-mediated suppression of homeostatic chemokines. Nat. Med. 15, 1259–1265 (2009).
Acton, S.E. et al. Podoplanin-rich stromal networks induce dendritic cell motility via activation of the C-type lectin receptor CLEC-2. Immunity 37, 276–289 (2012).
Astarita, J.L. et al. The CLEC-2-podoplanin axis controls the contractility of fibroblastic reticular cells and lymph node microarchitecture. Nat. Immunol. 16, 75–84 (2015).
Augsten, M. et al. Cancer-associated fibroblasts expressing CXCL14 rely upon NOS1-derived nitric oxide signaling for their tumor-supporting properties. Cancer Res. 74, 2999–3010 (2014).
Erez, N., Truitt, M., Olson, P., Arron, S.T. & Hanahan, D. Cancer-associated fibroblasts are activated in incipient neoplasia to orchestrate tumor-promoting inflammation in an NF-κνB-dependent manner. Cancer Cell 17, 135–147 (2010).
Harper, J. & Sainson, R.C. Regulation of the anti-tumour immune response by cancer-associated fibroblasts. Semin. Cancer Biol. 25, 69–77 (2014).
Kraman, M. et al. Suppression of antitumor immunity by stromal cells expressing fibroblast activation protein-alpha. Science 330, 827–830 (2010).
Shields, J.D., Kourtis, I.C., Tomei, A.A., Roberts, J.M. & Swartz, M.A. Induction of lymphoidlike stroma and immune escape by tumors that express the chemokine CCL21. Science 328, 749–752 (2010).
Baxter, L.T. & Jain, R.K. Transport of fluid and macromolecules in tumors. I. Role of interstitial pressure and convection. Microvasc. Res. 37, 77–104 (1989).
Dafni, H., Landsman, L., Schechter, B., Kohen, F. & Neeman, M. MRI and fluorescence microscopy of the acute vascular response to VEGF165: vasodilation, hyper-permeability and lymphatic uptake, followed by rapid inactivation of the growth factor. NMR Biomed. 15, 120–131 (2002).
Goldman, J. et al. Cooperative and redundant roles of VEGFR-2 and VEGFR-3 signaling in adult lymphangiogenesis. FASEB J. 21, 1003–1012 (2007).
Hompland, T., Ellingsen, C., Øvrebø, K.M. & Rofstad, E.K. Interstitial fluid pressure and associated lymph node metastasis revealed in tumors by dynamic contrast-enhanced MRI. Cancer Res. 72, 4899–4908 (2012).
Dankort, D. et al. Braf(V600E) cooperates with Pten loss to induce metastatic melanoma. Nat. Genet. 41, 544–552 (2009).
Gentleman, R.C. et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80 (2004).
Du, P., Kibbe, W.A. & Lin, S.M. lumi: a pipeline for processing Illumina microarray. Bioinformatics 24, 1547–1548 (2008).
Saeed, A.I. et al. TM4: a free, open-source system for microarray data management and analysis. Biotechniques 34, 374–378 (2003).
Mootha, V.K. et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat. Genet. 34, 267–273 (2003).
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545–15550 (2005).
Hirosue, S. et al. Steady-state antigen scavenging, cross-presentation, and CD8+ T cell priming: a new role for lymphatic endothelial cells. J. Immunol. 192, 5002–5011 (2014).
Warde-Farley, D. et al. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 38, W214–W220 (2010).
Montojo, J., Zuberi, K., Rodriguez, H., Bader, G.D. & Morris, Q. GeneMANIA: Fast gene network construction and function prediction for Cytoscape. F1000 Res. 3, 153 (2014).
We thank members of the Shields Group for comments and discussions; members of the Ares Facility QU, E23 and T29 staff for animal husbandry and technical assistance; R. Butler for support with image analysis and algorithm development; Cambridge Genomic Services for microarray services and post-analysis advice; and the CIMR flow cytometry core facility for advice and support in flow cytometry and cell-sorting applications. Supported by Medical Research Council core funding (J.S.) and the Royal Society (UF130039 to B.A.H.).
The authors declare no competing financial interests.
Integrated supplementary information
(a) Confocal images of B16.F10 brachial NDLNs (left), day 4 TDLNs (middle) and day 11 TDLNs (right) stained for ER-TR7 (green), CD31 (red) and LYVE1 (blue). (b) qRT-PCR quantification Tyrp1 and Dct in LN suspensions (106 cells) spiked with indicated numbers of B16.F10; or whole NDLNs, day 4 TDLNs and day 11 TDLNs. (c) Flow cytometry measurement of total LN cells, BECs, LECs, and FRCs in axillary LN (B16.F10). (d) Confocal image of NDLN (left) and TDLN (right) from TyrCreERBrafCAPtenlox stained for CD31 (green), podoplanin (red) and LYVE-1 (blue). (e) Flow cytometry quantification of EdU-labeled stromal cells. Scale bars (a) 150 µm, (d) 200 µm. Data points indicate the mean ± s.e.m. *P <0.05 (two-tailed unpaired t-test (e)). Data represent one experiment performed with n=4 for LNs (b); two independent experiments n=4 NDLNs, n=6 TDLNs in C57BL/6 female mice (c), n=6 day 2, n=6 day 4 and n=10 day 11 for both NDLNs and TDLNs in C57BL/6 female mice (e).
(a) Flow cytometry measurement of FRC number in TDLN. Red line denotes baseline FRC percentage/LN. (b) Confocal images of FRC networks in NDLNs (top) and day 11 TDLNs (bottom) LNs stained for podoplanin (red) and collagen I (blue). (c) Confocal Airyscans of conduit side and end views from NDLNs (top) and day 11 TDLNs (bottom) stained for podoplanin (green) ER-TR7 (blue) and CCL21 (red). (d) Confocal Airyscans of conduit side and end views from NDLNs (top) and day 11 TDLNs (bottom) stained for podoplanin (green) ER-TR7 (red) and collagen I (blue). (e) Quantification of network branch length. (f-h) Scatterplots showing the log2 fold expression change for all genes in the array (x axis), ranked according to increasing expression value (y axis); NDLNs vs. day 4 TDLNs (f), NDLNs vs. day 11 TDLNs (g), day 4 TDLNs vs. day 11 TDLNs (h). (i) Primary eigenvectors for Principal Component Analysis. The vast majority of change in the data (93.4%) are contained within the first 2 eigenvalues. Scale bars (b) 50 µm, (c) 0.487 µm (NDLN end), 0.291 µm (NDLN side), 0.588 µm (TDLN end), 0.873 µm (TDLN side), (d) 0.437 µm, 0.441 µm, 0.256 µm, 0.328 µm (NDLN end) and 0.454 µm (NDLN side); 0.363 µm, 0.481 µm, 0.47 µm, 0.363 µm (TDLN end) and 0.55 µm (TDLN side). Each symbol represents an individual FOV (e). Small horizontal lines indicate mean ± s.e.m. *P <0.05 (two-tailed unpaired t-test (a)). Data represent two independent experiments n=4 NDLNs, n= 6 TDLNs (mean ± s.e.m. (a)); or three independent experiments in female C57BL/6 mice, n=6 NDLNs and n=4 TDLNs.
(a) Heatmap displaying all gene probes with a cutoff of change in expression of 1.5-fold for day and day 11 TDLNs. (b) Heatmap displaying normalized enrichment scores (NES) above 1.5 and with a P<0.05 for deregulated Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using GSEA. (c) Heatmap of z-scores (indicating activation or inhibition) of canonical pathways Ingenuity Pathway Analysis (IPA) above 0.5 and P<0.05 (left) and top canonical pathways (IPA) ordered according to their P values (right). (d) Heatmap displaying z-scores (indicating activation or inhibition) of disease and biofunctions (IPA) above 2 and P<0.05 (left), and biofunctions (IPA) ordered according to their P values (right). Grey boxes represent pathways/functions with no significant deregulation.
(a) T cell area (left) and B cell follicle size (right) as percentage/LN measured based on CD3εe+ or CD45R+ staining. (b) Flow cytometry of CD8α+ T cells (CD45+CD3ε+CD8α +) in NDLNs and day 11 TDLNs. (c) Confocal image of NDLN (top) and day 11 TDLN (bottom) stained for FoxP3 (green) CD3ε (red) and collagen I (blue). (d) Confocal image of NDLN (left), day 4 TDLN (middle) and day 11 TDLN (right) stained for CD3ε (green), CD45R (red) and collagen I (blue). (e) Confocal image of NDLN (top) and day 11 TDLN (bottom) of paracortical area (left) or B cell follicles (right) stained for EdU (green), CD45R (red), LYVE1 (blue), and CD3ε (magenta). (f) Flow cytometry quantification of CD45+EdU+ cells in NDLNs and day 11 TDLNs. Scale bars (c) 150 µm (d and e) 50 µm. Each symbol represents an individual LN (a,b,f). Small horizontal lines indicate mean ± s.e.m. *P <0.05, **P <0.01 (two-tailed unpaired t-test (a,f)). Data represent 3 independent experiments, n=6 NDLNs and n=5 TDLNs (a), n=6 NDLNs and n=6 TDLNs (b), n=8 NDLNs and n=12 TDLNs.
(a) Confocal images of NDLNs (left) and day 11 TDLNs (right) stained for Macrophages (red) and collagen I (blue). (b) Flow cytometry quantification of CD11b+ cells (CD45+CD3ε-CD45R-CD11c-CD11b+) in NDLNs and TDLNs. (c) Flow cytometry quantification of CD11c+ cells (CD45+CD3ε-CD45R-CD11c+) in NDLNs and TDLNs. (d) qRT-PCR validation of Cd248 in an independent FRC sample set from B16.F10 NDLNs, day 4 TDLNs and day 11 TDLNs. (e) Collagen gel contraction (related to Fig. 5g). (f) qRT-PCR validation of Aqp1 in an independent FRC sample set from B16.F10 NDLNs, day 4 TDLNs and day 11 TDLNs. Scales bars 150 µm (a). Each symbol represents an individual LN (b-d,f). Small horizontal lines indicate mean ± s.e.m. *P <0.05, **P <0.01, ***P <0.001 and ****P <0.0001 (two-tailed unpaired t-test (b,c), one-way ANOVA with Tukey post hoc (d,f)). Data represent 2 independent experiments n=6 NDLNs and n=8 TDLNs (day 11) or one experiment n=4 day 4, 7 and 14 TDLNs (b,c); one experiment in technical duplicates, n=3 per condition. All in C57BL/6 female mice.
Supplementary Figure 6 Gene-interaction networks for significantly deregulated gene probes from day-11 TDLNs.
The MANIA algorithm includes 3 edge types between nodes: Predicted Edges, which implies functional relationships due to orthology with other organisms (gold), Co-localization Edges, where linked gene products are expressed in the same cellular location (blue), and Co-expression edges, where the expression levels of gene products are similar across conditions in a previously published gene expression study (pink). Node color also indicates whether a gene is predicted to be involved in the network (grey), or is one of the input genes (blue). Genes are linked through calculated edges, and networks of linked genes generated. The four most relevant probe groups are shown; all are involved in cell structure or shape. Models predict a large degree of relatedness and significance between Extracellular Matrix Proteins, Microtubule Cytoskeletal Elements, and Microtubule Regulation. Less dense networks (Structural Proteins) indicate less specific functional annotation.
About this article
Cite this article
Riedel, A., Shorthouse, D., Haas, L. et al. Tumor-induced stromal reprogramming drives lymph node transformation. Nat Immunol 17, 1118–1127 (2016) doi:10.1038/ni.3492
Journal of Oral Pathology & Medicine (2019)
CAF hierarchy driven by pancreatic cancer cell p53-status creates a pro-metastatic and chemoresistant environment via perlecan
Nature Communications (2019)
Cell Reports (2019)
ACS Pharmacology & Translational Science (2019)