Tumor-induced stromal reprogramming drives lymph node transformation

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Abstract

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.

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Figure 1: LN expansion and FRC remodeling.
Figure 2: Statistical analysis of microarray results.
Figure 3: Identification of specific genes and pathways deregulated in TDLN FRCs.
Figure 4: Perturbation in chemokine and cytokine signaling alters the composition and localization of immune cells.
Figure 5: FRCs in TDLNs are activated.
Figure 6: Modified transporter repertoires within TDLN FRCs translate into altered solute transport throughout the conduit system.

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Acknowledgements

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.).

Author information

A.R. planned and performed most experiments and associated analyses; D.S. performed in silico analysis; L.H. performed in vitro experiments; B.A.H. contributed to in silico analysis and data interpretation; J.S. conceived of the project, planned and performed experiments and contributed to data interpretation; A.R., D.S. and J.S. wrote the paper; and all authors contributed to editing of manuscript and critical review.

Correspondence to Benjamin A Hall or Jacqueline Shields.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 LN expansion in response to tumor-cell injection.

(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).

Supplementary Figure 2 Stromal expansion in TDLNs.

(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.

Supplementary Figure 3 Overall significantly deregulated probes and pathways.

(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.

Supplementary Figure 4 Immune-cell composition and localization in TDLNs.

(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.

Supplementary Figure 5 Macrophage and dendritic cell populations in TDLNs and verification.

(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.

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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

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