Blood vessels and tumor angiogenesis are generally associated with tumor growth and poor clinical outcome of cancer patients. However, we recently discovered that some blood vessels present within the tumor microenvironment can be associated with favorable prognosis. These vessels, designated tumor high endothelial venules (HEVs), appear to facilitate tumor destruction by allowing high levels of lymphocyte infiltration into tumors. In this study, we investigated the mechanisms regulating HEV blood vessels in human breast cancer. We found that lymphotoxin β was overexpressed in tumors containing high densities of HEVs (HEVhigh) and correlated to DC-LAMP, a marker of mature DCs. DCs were the main producers of lymphotoxin β in freshly resected HEVhigh breast tumor samples, and the density of DC-LAMP+ DCs clusters was strongly correlated with the density of tumor HEVs, T and B cell infiltration, and favorable clinical outcome in a retrospective cohort of 146 primary invasive breast cancer patients. Densities of tumor HEVs and DC-LAMP+ DCs were strongly reduced during breast cancer progression from in situ carcinoma to invasive carcinoma, suggesting that loss of tumor HEVs is a critical step during breast cancer progression. Finally, an increase in the infiltration of regulatory T cells was observed in HEVhigh breast tumors, indicating that tumor HEVs can develop in the presence of regulatory T cells. Together, our results support a key role for DCs and DC-derived lymphotoxin in the formation of tumor HEVs. These findings are important because novel therapeutic strategies based on the modulation of tumor HEVs could have a major impact on clinical outcome of cancer patients.

This article is featured in In This Issue, p.1507

Blood vessels and tumor angiogenesis are generally associated with tumor growth and poor clinical outcome of cancer patients (1, 2). However, we recently found that some blood vessels present within the tumor microenvironment can be associated with favorable prognosis (3). These specialized blood vessels, designated tumor high endothelial venules (HEVs), are normally found in lymph nodes where they mediate the extravasation of large numbers of lymphocytes from the blood (46). In human breast tumors (3) and primary melanomas (7), the density of tumor HEVs was highly correlated with the density of tumor-infiltrating CD3+ T cells, CD8+ cytotoxic T cells, and CD20+ B cells, indicating that, like in lymph nodes, HEVs may function as major gateways for lymphocyte infiltration into solid tumors (3, 79). In contrast, we found no correlation between tumor HEVs and density of blood vessels (HEVhigh and HEVlow tumors had the same numbers of CD34+ tumor blood vessels), indicating that differences in the density of tumor HEVs are not related to differences in tumor angiogenesis (3).

By allowing infiltration of naive, memory, cytotoxic, and activated T cells (3, 8, 9), tumor HEVs may facilitate destruction of tumor cells and generation of memory T cells that limit metastasis of tumor cells at distant sites. Indeed, in breast cancer, we found that high densities of tumor HEVs were associated with longer disease-free and metastasis-free survival of the patients (3). Tumor HEVs were also associated with good clinical characteristics in primary melanomas, including thin Breslow thickness and low Clark level of invasion and tumor regression (7). Therefore, although blood vessels are generally believed to promote tumor growth, our studies showed that the phenotype of blood vessels is important and that some types of blood vessels present in the tumor microenvironment (i.e., tumor HEVs) can contribute to tumor suppression rather than tumor growth. Tumor HEVs have been observed in many different types of human solid tumors, including primary and metastatic melanomas, breast, lung, ovarian, and colon carcinomas (3, 7, 10, 11). A better understanding of tumor HEVs could thus have broad applications for human cancer.

Interestingly, tumor HEVs have been detected in murine B16 melanoma tumors after targeting of lymphotoxin α (LTα) within the tumor (12, 13), and more recently in methylcholanthrene-induced fibrosarcomas upon depletion of regulatory T cells (Tregs) in FoxP3-DTR transgenic mice (14). In both cases, the presence of HEVs in the tumors was associated with T cell infiltration and tumor regression (1214). It is currently unknown whether Tregs regulate HEV differentiation directly. In contrast, CD11c+ dendritic cells (DCs) were recently shown to play a critical role in this process (15). In vivo depletion of DCs in adult mice resulted in a profound downregulation of the HEV phenotype in mouse lymph nodes. Coculture experiments revealed that lymphotoxin β receptor (LTβR) signaling is involved in the dialog between DCs and HEV endothelial cells (15). DCs expressed lymphotoxin ligands for LTβR, and DC-derived lymphotoxin was found to be important for HEV-mediated extravasation of lymphocytes in lymph nodes (15). DCs and LTβR signaling have also been implicated in the regulation of HEVs in murine inflamed lymph nodes and chronically inflamed nonlymphoid tissues (1623). Despite these important advances in mouse models, little is known yet about the mechanisms governing the development of HEVs in human solid tumors.

In this study, we investigated the mechanisms regulating HEV blood vessels in human breast cancer. We show that high densities of tumor HEVs in breast tumors were associated with high expression levels of lymphotoxin β (LTβ) and high densities of DC-LAMP+ DC clusters. LTβ expression was strongly correlated with expression of DC-LAMP, and CD11c+ DCs were found to be the major producers of membrane-bound LTβ (LTα1β2) in the breast tumor microenvironment. Tumor HEVs were often surrounded by Fascin+ and DC-LAMP+ DCs within breast tumor stroma, and the density of DC-LAMP+ DC clusters was strongly correlated with the density of tumor HEVs, T and B cell infiltration, and favorable clinical outcome of breast cancer patients. Strikingly, a progressive loss of tumor HEVs and DC-LAMP+ DCs was observed during breast cancer progression from in situ to invasive carcinoma. Finally, densities of Tregs and tumor HEVs were correlated in human breast tumors. However, the Tregs/CD3+ T cells ratio was significantly reduced in HEVhigh breast tumors.

Fresh, frozen, and paraffin-embedded breast tumor samples were all obtained from breast cancer patients undergoing surgery at the Institut Claudius Regaud (ICR Biological Resource Center, Toulouse, France). Approval of the study was obtained from the Scientific Review Board of the ICR. A written informed consent was obtained from the patients before inclusion in the study. The retrospective study was conducted with a cohort of 146 unselected primary invasive breast cancer patients operated at ICR between 1997 and 1998 (3). Patient characteristics have been previously described (3) and are summarized in Supplemental Table I. Experiments also involved tissue samples from 110 patients operated at ICR between 2004 and 2012, including invasive ductal carcinomas (IDCs; n = 66), ductal carcinomas in situ (DCISs; n = 29), and nonmalignant breast tissues (n = 15).

Immunohistochemistry was performed on 5-μm consecutive sections from RCL2, formalin- or Duboscq-fixed, paraffin-embedded tumor blocks using a Techmate Horizon slide processor (Dako, Trappes, France) as previously described (3). Details of the Abs, fixatives, and Ag retrieval methods used are provided in Supplemental Table II. For immunofluorescence detection, tumor slides were incubated with fluorochrome- or biotin-coupled secondary Abs diluted in PBS, BSA 1% for 30 min at room temperature and counterstained with DAPI. When necessary, AF350-, AF488-, or AF546-coupled streptavidin (Invitrogen) was added for 20 min. Images were acquired using a Nikon Eclipse 90i microscope (Nikon, Champigny-sur-Marne, France) operated with Nikon NIS Elements BR software.

Tumor slides stained with MECA-79, anti-CD3, anti-CD20, anti-DC-LAMP, or anti-Foxp3 Abs were scanned with a high-resolution scanner (NDP slide scanner, Hamamatsu and Panoramic 250 Flash; 3Dhistech). The density of tumor HEVs (HEV/mm2) was calculated and patients with a high and a low density of tumor HEVs were separated with the following cutoff (0.19 HEV/mm2) as previously described (3). CD3+, CD20+, and FOXP3+ cells densities were evaluated by automatic cell count with ImageJ software (National Institutes of Health, Bethesda, MD) as described previously (3). We evaluated the density of DC-LAMP+ infiltrating cells by optical quantification of the number of DC-LAMP+ DC clusters within tumor stroma (Supplemental Fig. 1A). An optical grading (grade 0, 1, 2, and 3 for none, low, intermediate, and high number of tumor-infiltrating DC-LAMP+ cells) of DC-LAMP marker was also performed to verify the results obtained with DC-LAMP quantification. We obtained similar results with the two different methods; therefore, only the results obtained with the quantitative method are presented in this article. We used the following cutoff (highest tercile versus two lowest terciles) to discriminate tumors with a high and low density of DC-LAMP+ cells. Quantification of blood vessels and scoring were performed by three independent observers (L.M., I.G., S.L.G.) who were blinded to the clinical outcome.

Freshly resected breast tumor samples were reduced in small fragments and incubated 30 min at 37°C in sterile RPMI 1640 containing collagenase IV (1 mg/ml; Sigma-Aldrich). The samples were classified “HEVhigh” when high densities of tumor HEVs were detected on adjacent sections by immunostaining for MECA-79. Total cells were then extracted by mechanical dispersion and incubated for 30 min at 4°C with fluorochrome-conjugated mAbs directed against different immune cell markers or their isotype-matched controls (Supplemental Table II). LTβ expression was determined by incubating PBMCs or total cells isolated from HEVhigh breast tumor samples (n = 9) with primary Ab directed against human LTβ (MAB1684; R&D, Minneapolis, MN) for 30 min at 4°C, followed by incubation with FITC-conjugated goat anti-mouse IgG secondary Abs (Jackson Immunoresearch, Suffolk, U.K.) for 30 min at 4°C. Fluorochrome-conjugated mAbs directed against CD3, CD20, CD56, CD11c, and CD45 were then added for 30 min at 4°C. Analyses were performed on a six-color fluorescence-activated cell sorter (LSRII; Becton Dickinson) with Diva (Becton Dickinson) and FlowJo softwares (Tree Star, Ashland, OR).

For cell sorting, total cells from freshly resected HEVhigh breast tumor samples (n = 7), extracted as described earlier, were pooled together and incubated for 30 min at 4°C with fluorochrome-conjugated mAbs directed against different immune and tumor cell markers. Tumor cells (EpCAM+ CD45), T lymphocytes (CD45+CD3+), B lymphocytes (CD45+CD20+), NK cells (CD3CD56+), and DCs (CD45+, lin, HLA-DR+, CD11c+, CD1A+) were isolated by flow cytometry using a FACSAria II cell sorter.

An RNeasy isolation kit was used to isolate total RNA (Qiagen, Valencia, CA) from 22 cryopreserved breast tumor samples (12 HEVlow versus 10 HEVhigh, identified by immunohistochemistry with MECA-79) and cells isolated by cell sorting as described earlier. The integrity and the quantity of the RNA were evaluated using a bioanalyzer-2100 (Agilent Technologies, Palo Alto, CA). cDNA was prepared by reverse transcription using superscript VILO cDNA Synthesis Kit (Invitrogen, Paisley, U.K.). Quantitative RT-PCR (qRT-PCR) experiments were performed using Power SYBR Green mix with an ABI PRISM 7300HT (Applied Biosystems, Warrington, U.K.) according to manufacturer’s instructions. All reactions were done in triplicate and normalized to the expression of GAPDH. Heat map representation of gene expression in tumor tissues containing a high (HEVhigh) or a low density of HEVs (HEVlow) was performed with the use of Genesis software (Institute for Genomics and Bioinformatics, Graz, Austria) (24, 25). The expression of each gene was obtained by the Δ cycling threshold (CT) method as 2(−ΔCTsample), and the relative change in expression between HEVhigh and HEVlow tumor samples was calculated as 2−(ΔCTsample − average ΔCT from HEVlow tumors).

Categorical variables were reported by frequencies and percentages; continuous variables were presented by median and range. Comparisons between groups were performed using the Mann–Whitney rank sum test for continuous variables and χ2 or Fisher exact test for categorical variables. Correlations between continuous variables were evaluated using Spearman rank correlation test.

We analyzed two main end points: disease-free survival (DFS), which was defined as time from surgery to any recurrence (local or regional or distant metastasis) or death, and overall survival (OS), which was defined as time from surgery to death from any cause. The Kaplan–Meier product-limit estimator was used to display time-to-event curves for the two end points. Comparisons between groups were performed using log rank test. Cox regression model was applied to determine whether a factor was an independent predictor of survival in multivariate analysis (with backward variable elimination). All p values were two sided, and statistical significance was defined as p < 0.05. Statistical analyses were performed using the STATA 11.0 (STATA Corp, College Station, TX) software.

Previous studies in mouse have demonstrated that maintenance of HEVs depend on LTβR signaling initiated by its cell-associated ligand LTα1β2, an heterotrimer formed by the membrane-associated subunit LTβ, and LTα, which is critical for cell-surface expression of the complex (15, 16, 18). We thus analyzed the mRNA levels of LTBR and its ligands LTA (encoding LTα), LTB (encoding LTβ), and LIGHT (an alternative LTBR ligand) by qRT-PCR in HEVhigh and HEVlow breast tumor samples. Levels of LTBR and LIGHT mRNA were not significantly different between HEVhigh and HEVlow tumors. A small but significant increase in LTA was detected in HEVhigh tumors (Fig. 1A), whereas LTB was specifically and strongly overexpressed (>10-fold) in HEVhigh breast tumors (Fig. 1A). Interestingly, LTB relative expression within breast tumor samples was highly correlated to expression of chemokines associated with HEV-mediated lymphocyte extravasation (4, 10, 14, 26, 27), including CCL21 (Spearman r = 0.78, p < 0.001), CCL19 (Spearman r = 0.91, p < 0.001), and CXCL13 (Spearman r = 0.78, p < 0.001) (Fig. 1B). In contrast, LTB mRNA levels were not correlated (p > 0.05) to mRNA levels of chemokines implicated in myeloid cell, neutrophil, and lymphocyte migration independently of HEVs (CCL2, CXCL8, CXCL12; Fig. 1B).

FIGURE 1.

Expression of LTβ is increased in HEVhigh breast tumors and highly correlated with expression of HEV-associated chemokines. (A) Graphs showing the relative mRNA levels of LTβR signaling pathway genes in HEVhigh (n = 10, black bars) and HEVlow (n = 11, white bars) breast tumor samples. (B) Graphs showing the correlation between the relative mRNA levels of LTB (coding for LTβ) and HEV-associated chemokines (CCL19, CCL21, or CXCL13) in breast tumor samples, and the absence of correlation between expression of LTB and expression of chemokines CCL2, CXCL8, or CXCL12. *p < 0.05, **p < 0.01, Mann–Whitney U test.

FIGURE 1.

Expression of LTβ is increased in HEVhigh breast tumors and highly correlated with expression of HEV-associated chemokines. (A) Graphs showing the relative mRNA levels of LTβR signaling pathway genes in HEVhigh (n = 10, black bars) and HEVlow (n = 11, white bars) breast tumor samples. (B) Graphs showing the correlation between the relative mRNA levels of LTB (coding for LTβ) and HEV-associated chemokines (CCL19, CCL21, or CXCL13) in breast tumor samples, and the absence of correlation between expression of LTB and expression of chemokines CCL2, CXCL8, or CXCL12. *p < 0.05, **p < 0.01, Mann–Whitney U test.

Close modal

To identify the cells that produce membrane-associated LTβ (LTα1β2) within breast tumors, we used flow cytometry to analyze cell-surface expression of LTβ on cells isolated from freshly resected breast tumor samples containing high densities of tumor HEVs and large numbers of tumor-infiltrating lymphocytes (HEVhigh breast tumors). Control experiments were performed on blood mononuclear cells from healthy donors stimulated or not with anti-CD3/anti-CD28–coated beads to induce LTβ expression (Supplemental Fig. 2). In HEVhigh breast tumors, ∼30% of CD11c+ DCs expressed membrane-bound LTβ (Fig. 2A, 2B). In contrast, very few CD45 tumor cells, CD3CD56+ NK cells, CD3+ T cells, and CD20+ B cells had detectable LTβ expression. To confirm these results, we used qRT-PCR to analyze LTβ mRNA expression in tumor cells, NK cells, T cells, B cells, and DCs isolated from HEVhigh breast tumor samples by cell sorting (Supplemental Fig. 2). We found that LTB mRNA levels were significantly higher in DCs than in other immune cell populations (Fig. 2C) and were strongly correlated to the levels of mature DC marker DC-LAMP in breast tumor samples (Fig. 2D). Similarly to LTB, DC-LAMP expression in breast tumor samples was correlated (p < 0.001) to expression of HEV-associated chemokines CCL19, CCL21, and CXCL13, but not (p > 0.05) to that of chemokines CCL2, CXCL8, and CXCL12 (Fig. 2E). Together, these results indicated that CD11c+ DCs represent the main source of membrane-associated LTβ within human breast tumors.

FIGURE 2.

LTβ is produced by DCs within the breast tumor microenvironment. (A) Representative histograms showing the staining with anti-LTβ Ab (filled histogram) or isotype control (open histogram) at the cell surface of CD45 tumor cells, CD3+ T cells, CD20+ B cells, CD3CD56+ NK cells, and CD11c+ DCs from HEVhigh breast tumor samples. (B) Mean (+SD) percentage of CD3+ T cells, CD20+ B cells, CD3CD56+ NK cells, and CD11c+ DCs among LTβ-expressing cells in HEVhigh breast tumor samples (n = 9). (C) Graph showing the mean (+SD) relative LTB mRNA expression in Epcam+ tumor cells, CD3+ T cells, CD20+ B cells, CD11c+CD1A+HLADR+ DCs, and CD3CD56+ NK cells, isolated from HEVhigh breast tumor samples by cell sorting (n = 7). Relative expression to B cells is shown. (D) Graph showing the correlation between the relative mRNA expression levels of DC-LAMP and LTB in breast tumor samples (n = 21). (E) Graphs showing the correlation between the relative mRNA expression levels of DC-LAMP and CCL19, CCL21, or CXCL13 in breast tumor samples (n = 21), and the absence of correlation between expression of DC-LAMP and expression of chemokines CCL2, CXCL8, or CXCL12. **p < 0.01, ***p < 0.001, Mann–Whitney U test.

FIGURE 2.

LTβ is produced by DCs within the breast tumor microenvironment. (A) Representative histograms showing the staining with anti-LTβ Ab (filled histogram) or isotype control (open histogram) at the cell surface of CD45 tumor cells, CD3+ T cells, CD20+ B cells, CD3CD56+ NK cells, and CD11c+ DCs from HEVhigh breast tumor samples. (B) Mean (+SD) percentage of CD3+ T cells, CD20+ B cells, CD3CD56+ NK cells, and CD11c+ DCs among LTβ-expressing cells in HEVhigh breast tumor samples (n = 9). (C) Graph showing the mean (+SD) relative LTB mRNA expression in Epcam+ tumor cells, CD3+ T cells, CD20+ B cells, CD11c+CD1A+HLADR+ DCs, and CD3CD56+ NK cells, isolated from HEVhigh breast tumor samples by cell sorting (n = 7). Relative expression to B cells is shown. (D) Graph showing the correlation between the relative mRNA expression levels of DC-LAMP and LTB in breast tumor samples (n = 21). (E) Graphs showing the correlation between the relative mRNA expression levels of DC-LAMP and CCL19, CCL21, or CXCL13 in breast tumor samples (n = 21), and the absence of correlation between expression of DC-LAMP and expression of chemokines CCL2, CXCL8, or CXCL12. **p < 0.01, ***p < 0.001, Mann–Whitney U test.

Close modal

When we compared the expression of genes related to immune subpopulations and angiogenesis, by qRT-PCR in cryopreserved breast tumor samples containing either low (HEVlow) or high (HEVhigh) densities of tumor HEVs (12 HEVlow versus 10 HEVhigh), we observed that the “DCs” cluster was significantly upregulated in HEVhigh breast tumors (Fig. 3A). In contrast, the “angiogenesis” cluster was not significantly different between tumors with a low or a high density of tumor HEVs (Fig. 3A). To further define the association between tumor HEVs and DCs within the breast tumor microenvironment, tissue sections were double stained with the HEV-specific mAb MECA-79 and Abs against two markers of mature DCs, Fascin and DC-LAMP. These immunofluorescence analyses revealed that tumor HEVs were often surrounded by mature Fascin+ DCs (Fig. 3B) and DC-LAMP+ DCs (Fig. 3C). We then analyzed DC-LAMP and MECA-79 markers by immunohistochemistry in a retrospective cohort of 146 primary invasive breast cancer patients, previously used to study the impact of tumor HEVs on clinical outcome (3). The density of DC-LAMP+ cells was variable within breast tumor microenvironment, allowing us to define tumors containing either low (DC-LAMPlow) or high (DC-LAMPhigh) densities of DC-LAMP+ cells (Fig. 3D). Tumor HEVs were mainly found in DC-LAMP+ cell–rich areas within tumor stroma (Fig. 3E), and significantly higher densities of tumor HEVs (Fig. 3F) were observed in DC-LAMPhigh breast tumors. We concluded that tumor HEVs were associated with DC-LAMP+ DCs clusters within breast tumor stroma.

FIGURE 3.

Tumor HEVs are associated with DC-LAMP+ DCs clusters in human breast tumors. (A) DC-associated genes are upregulated in HEVhigh breast tumors. Expression levels of the indicated genes were determined by quantitative PCR and compared between 22 human breast tumor samples (10 HEVhigh versus 12 HEVlow). Heat map representations of the DC and “angiogenesis” gene clusters are shown. Genes are plotted from the minimal level of expression (green) to the maximal level (red). The Mann–Whitney U test was used to compare the expression levels of each gene between tumor groups. n.s., p > 0.05. (B and C) Immunofluorescence staining of breast tumor sections with Abs against HEV (MECA-79) and mature DC markers Fascin (B) and DC-LAMP (C). DNA was stained with DAPI (B) and T cells with an anti-CD3 Ab (C). Original magnifications ×100. (D) Immunohistochemical detection of DC-LAMP in breast tumors containing either low (DC-LAMPlow) or high (DC-LAMPhigh) densities of DC-LAMP+ cells. (E and F) Serial breast tumor sections (n = 146) were stained with Abs directed against DC-LAMP or HEV (MECA-79), and the density of the two cell types was calculated as described in 2Materials and Methods. Representative pictures of the spatial association between HEVs and DC-LAMP+ DCs clusters are shown (E). The density of tumor HEVs is significantly higher in breast tumors with a high density of DC-LAMP+ DC clusters (F). Original magnification (D) ×20; (E) ×10. ***p < 0.001, Mann–Whitney U test.

FIGURE 3.

Tumor HEVs are associated with DC-LAMP+ DCs clusters in human breast tumors. (A) DC-associated genes are upregulated in HEVhigh breast tumors. Expression levels of the indicated genes were determined by quantitative PCR and compared between 22 human breast tumor samples (10 HEVhigh versus 12 HEVlow). Heat map representations of the DC and “angiogenesis” gene clusters are shown. Genes are plotted from the minimal level of expression (green) to the maximal level (red). The Mann–Whitney U test was used to compare the expression levels of each gene between tumor groups. n.s., p > 0.05. (B and C) Immunofluorescence staining of breast tumor sections with Abs against HEV (MECA-79) and mature DC markers Fascin (B) and DC-LAMP (C). DNA was stained with DAPI (B) and T cells with an anti-CD3 Ab (C). Original magnifications ×100. (D) Immunohistochemical detection of DC-LAMP in breast tumors containing either low (DC-LAMPlow) or high (DC-LAMPhigh) densities of DC-LAMP+ cells. (E and F) Serial breast tumor sections (n = 146) were stained with Abs directed against DC-LAMP or HEV (MECA-79), and the density of the two cell types was calculated as described in 2Materials and Methods. Representative pictures of the spatial association between HEVs and DC-LAMP+ DCs clusters are shown (E). The density of tumor HEVs is significantly higher in breast tumors with a high density of DC-LAMP+ DC clusters (F). Original magnification (D) ×20; (E) ×10. ***p < 0.001, Mann–Whitney U test.

Close modal

Significantly higher densities of CD3+ T cells and CD20+ B cells were found in breast tumors containing high densities of DC-LAMP+ DC clusters (Fig. 4A, Supplemental Fig. 1B). Indeed, the density of DC-LAMP+ DC clusters was strongly correlated with the density of tumor HEVs (Spearman r = 0.63, p < 0.001), CD3+ T cells (Spearman r = 0.72, p < 0.001), and CD20+ B cells (Spearman r = 0.58, p < 0.001; Fig. 4B), consistent with the link between tumor HEVs and tumor-infiltrating lymphocytes (3).

FIGURE 4.

Density of DC-LAMP+ DCs correlates with HEV density, lymphocyte infiltration, and favorable clinical outcome of breast cancer patients. (A) Representative images from immunohistochemistry with DC-LAMP, MECA-79, CD3, and CD20 Abs showing the spatial association between DCs, HEVs, T cells, and B cells within breast tumor stroma. Original magnification ×10. (B) The density of DC-LAMP+ DC clusters is correlated with the density of HEVs, CD3+ T cells, and CD20+ B cells in breast tumor samples. Serial breast tumor sections (n = 146) were stained with Abs directed against DC-LAMP, HEV (MECA-79), CD3, and CD20, and the density of the different cell types was calculated as described in the 2Materials and Methods. (C) Kaplan–Meier curves for DFS and OS rates of 146 patients with primary breast cancer, according to the density of DC-LAMP+ DCs. The rapid decrease in the DC-LAMPhigh DFS curve after 144 mo is due to the small number of patients at risk at this time.

FIGURE 4.

Density of DC-LAMP+ DCs correlates with HEV density, lymphocyte infiltration, and favorable clinical outcome of breast cancer patients. (A) Representative images from immunohistochemistry with DC-LAMP, MECA-79, CD3, and CD20 Abs showing the spatial association between DCs, HEVs, T cells, and B cells within breast tumor stroma. Original magnification ×10. (B) The density of DC-LAMP+ DC clusters is correlated with the density of HEVs, CD3+ T cells, and CD20+ B cells in breast tumor samples. Serial breast tumor sections (n = 146) were stained with Abs directed against DC-LAMP, HEV (MECA-79), CD3, and CD20, and the density of the different cell types was calculated as described in the 2Materials and Methods. (C) Kaplan–Meier curves for DFS and OS rates of 146 patients with primary breast cancer, according to the density of DC-LAMP+ DCs. The rapid decrease in the DC-LAMPhigh DFS curve after 144 mo is due to the small number of patients at risk at this time.

Close modal

We then analyzed the prognostic value of DC-LAMP marker in the retrospective cohort. In univariate analysis, we observed that a high density of DC-LAMP+ cells was significantly associated with a longer DFS (p < 0.02) and OS (p < 0.02) as compared with tumors with a low density of DC-LAMP+ cells (Fig. 4C, Supplemental Table I). DC-LAMP density also showed a significant correlation with DFS and OS in multivariate analysis after adjusting on prognostic factors previously identified (tumor size, grade, estrogen receptor status, HER2 expression). The adjusted hazard ratios of DFS and OS rates for patients with DC-LAMPlow tumors versus DC-LAMPhigh tumors were 3.56 (95% CI, 1.42–8.94, p = 0.007) and 4.14 (95% CI, 1.28–13.32, p = 0.017), respectively (Table I). We concluded that a high density of DC-LAMP+ DCs correlates with the presence of HEV blood vessels within breast tumors and constitutes an independent factor of good clinical outcome for breast cancer patients.

Table I.
Multivariate analysis using Cox proportional hazard model
DFS
OS
HR95% CIp (Wald)HR95% CIp (Wald)
DC-Lamp       
 Low 3.56 1.42–8.94 0.007 4.14 1.28–13.32 0.017 
 High     
Tumor size, cm       
 <2     
 ≥2 3.32 1.82–6.06 <0.001 3.18 1.58–6.38 0.001 
Nodal status (N)       
 N     
 N+ 2.15 1.22–3.79 0.005 2.38 1.23–4.61 0.010 
DFS
OS
HR95% CIp (Wald)HR95% CIp (Wald)
DC-Lamp       
 Low 3.56 1.42–8.94 0.007 4.14 1.28–13.32 0.017 
 High     
Tumor size, cm       
 <2     
 ≥2 3.32 1.82–6.06 <0.001 3.18 1.58–6.38 0.001 
Nodal status (N)       
 N     
 N+ 2.15 1.22–3.79 0.005 2.38 1.23–4.61 0.010 

HR, Hazard ratio.

The tumorigenesis and progression of breast cancer constitute a multistep process that is influenced by many factors including genetic composition, age, hormonal status, and immune environment. IDC is thought to derive from a series of intermediate hyperplasic and neoplastic stages including DCIS. To better understand the role of tumor HEVs during breast tumor development, we performed MECA-79 immunohistochemistry on 15 nonmalignant breast tissues, 29 pure DCISs, and 173 IDCs (Fig. 5A). HEVs were present in breast tumor tissues, but not in normal breast tissue samples (Fig. 5A), and their density was significantly higher in DCIS (7.467 ± 1.324) than in IDC (0.6363 ± 0.1132; Fig. 5B). To evaluate the role of tumor HEVs in the progression of DCIS to invasive carcinomas, we compared the density of MECA-79+ HEVs in matched IDC and DCIS components of 31 cases of invasive carcinomas with a DCIS component (Fig. 5C). We found a preferential localization of HEVs around in situ tumor components (Fig. 5C). A strong reduction in the density of tumor HEVs between DCIS components and IDC components was observed for all tumor samples analyzed (Fig. 5D). Given the clear association between DCs and HEVs in peripheral lymph nodes (15) and breast tumor tissues (this study), we then analyzed the density of DC-LAMP+ DCs in invasive carcinomas containing matched invasive and DCIS components (Fig. 5E). Similar to the density of tumor HEVs, we found that the density of DC-LAMP+ DCs was significantly reduced between DCIS and IDC components (Fig. 5F). Finally, we analyzed the density of CD3+ T cells in matched DCIS and IDC tumor areas (Fig. 5G), and we found that it was significantly reduced in IDC compared with DCIS areas (Fig. 5H). Together, these results indicate that breast cancer invasiveness is associated with a progressive loss of HEV blood vessels, DC-LAMP+ DCs, and CD3+ T cells around DCIS structures.

FIGURE 5.

Loss of tumor HEV and DC-LAMP+ DC clusters during breast cancer progression from in situ to IDC. (A) Representative images from digitized breast tissue slides stained with MECA-79 Ab showing that tumor HEVs are more frequently observed around DCISs than IDCs, and are absent from normal breast tissues. (B) Graph showing the density of MECA-79+ HEVs in normal breast tissue (n = 15), DCIS (n = 29), and IDC (n = 173). (CH) Serial breast tumor sections containing both in situ and invasive components were stained with Abs directed against HEV (MECA-79), DC-LAMP, and T cells (CD3), and the density of the different cell types was calculated in matched in situ and invasive components. Representative images of the preferential location of MECA-79+ HEV blood vessels (C, box), DC-LAMP+ DCs clusters (E), and CD3+ T cells (G) in DCIS areas and their relative absence in IDC areas are shown (C, E, G). The density of tumor HEVs (D, n = 31), DC-LAMP+ DCs clusters (F, n = 31), and CD3+ T cells (H, n = 16) was decreased between in situ (DCIS) and invasive (IDC) matched samples. Original magnification (A) ×5, (C) ×2.5, (E) ×5, (G) ×2.5. **p < 0.01, ***p < 0.001, Mann–Whitney U test.

FIGURE 5.

Loss of tumor HEV and DC-LAMP+ DC clusters during breast cancer progression from in situ to IDC. (A) Representative images from digitized breast tissue slides stained with MECA-79 Ab showing that tumor HEVs are more frequently observed around DCISs than IDCs, and are absent from normal breast tissues. (B) Graph showing the density of MECA-79+ HEVs in normal breast tissue (n = 15), DCIS (n = 29), and IDC (n = 173). (CH) Serial breast tumor sections containing both in situ and invasive components were stained with Abs directed against HEV (MECA-79), DC-LAMP, and T cells (CD3), and the density of the different cell types was calculated in matched in situ and invasive components. Representative images of the preferential location of MECA-79+ HEV blood vessels (C, box), DC-LAMP+ DCs clusters (E), and CD3+ T cells (G) in DCIS areas and their relative absence in IDC areas are shown (C, E, G). The density of tumor HEVs (D, n = 31), DC-LAMP+ DCs clusters (F, n = 31), and CD3+ T cells (H, n = 16) was decreased between in situ (DCIS) and invasive (IDC) matched samples. Original magnification (A) ×5, (C) ×2.5, (E) ×5, (G) ×2.5. **p < 0.01, ***p < 0.001, Mann–Whitney U test.

Close modal

Tumor HEVs have recently been found to be induced in mouse tumor models upon depletion of Tregs (14). To better define the link between Tregs and HEV blood vessels within breast tumor stroma, we analyzed MECA-79, FOXP3, and CD3 markers by immunohistochemistry for 40 invasive breast cancer patients (Fig. 6A). We found a significant increase in the density of tumor-infiltrating FOXP3+ Tregs (Fig. 6B) and CD3+ T cells (Fig. 6C) in tumors containing a high density of HEV blood vessels (p < 0.01), and a significant correlation between the density of FOXP3+ Tregs and tumor HEVs (Spearman r = 0.54, p < 0.003). However, we also observed a significant reduction in the FOXP3+ Tregs/CD3+ T cell ratio in tumors with a high density of tumor HEVs (p < 0.01; Fig. 6D). These findings demonstrate that HEV blood vessels can fully develop in the presence of Tregs within breast tumor stroma, but that their density is influenced by the Tregs/T cells ratio.

FIGURE 6.

Tumor HEVs develop in the presence of FOXP3+ Tregs. (AD) Serial breast tumor sections (n = 40) were stained with Abs directed against HEV (MECA-79), CD3, and FOXP3, and the density of the different cell types was calculated. Representative pictures of MECA-79+ HEVs and CD3+ and FOXP3+ T cells in HEVlow and HEVhigh breast tumors are shown Original magnification ×5. (A). The density of FOXP3+ T cells (B) and CD3+ T cells (C) is increased in tumors containing a high density of tumor HEVs. The FOXP3+/CD3+ T cells ratio is decreased in HEVhigh breast tumors (D). **p < 0.01, ***p < 0.001, Mann–Whitney U test.

FIGURE 6.

Tumor HEVs develop in the presence of FOXP3+ Tregs. (AD) Serial breast tumor sections (n = 40) were stained with Abs directed against HEV (MECA-79), CD3, and FOXP3, and the density of the different cell types was calculated. Representative pictures of MECA-79+ HEVs and CD3+ and FOXP3+ T cells in HEVlow and HEVhigh breast tumors are shown Original magnification ×5. (A). The density of FOXP3+ T cells (B) and CD3+ T cells (C) is increased in tumors containing a high density of tumor HEVs. The FOXP3+/CD3+ T cells ratio is decreased in HEVhigh breast tumors (D). **p < 0.01, ***p < 0.001, Mann–Whitney U test.

Close modal

The current dogma in the field of tumor angiogenesis is that blood vessels contribute to tumor growth, and they are thus generally associated with poor prognosis. Recently, we proposed the novel concept that “tumor blood vessels are not all the same and that some types of blood vessels found in the tumor microenvironment (i.e., tumor HEVs) can be associated with favorable clinical outcome” (3). Tumor HEVs were frequently observed in the stroma of human solid tumors and appeared to contribute to tumor suppression by allowing high levels of lymphocyte infiltration (including CD8+ cytotoxic T cells infiltration) into tumors (3, 7). A better understanding of tumor HEVs and their regulation is important because it could allow, in the future, the manipulation of tumor blood vessel phenotype to transform regular tumor blood vessels into tumor HEVs.

The lymphotoxin pathway has been shown to regulate HEV blood vessels in both lymphoid organs and chronically inflamed tissues (16, 1820, 22, 23). We demonstrated previously that DCs and DC-derived lymphotoxin are critical for maintenance of HEV blood vessel phenotype in mouse lymph nodes (4, 15). In this study, we asked whether similar mechanisms regulate tumor HEVs in human breast tumors. We found that LTα and LTβ were both overexpressed in HEVhigh tumors, and DCs were the major producers of membrane-associated LTβ (LTα1β2) within breast tumors. Whereas most T and B cells expressed LTβ after polyclonal activation of PBMCs, we observed only a few T and B lymphocytes expressing LTβ in breast tumors. In contrast, a considerable fraction (∼30%) of CD11c+ DCs from HEVhigh breast tumors expressed membrane-bound LTβ. In addition, DC-LAMP expression was strongly correlated to LTβ expression in breast tumor samples. These results suggested that DCs may contribute to the formation of HEVs in human breast tumors through LTβ production. In support of this possibility, tumor HEVs were often surrounded by clusters of mature Fascin+ and DC-LAMP+ DCs, and high densities of DC-LAMP+ DCs clusters were observed in HEVhigh breast tumors. The density of DC-LAMP+ DCs clusters was strongly correlated with the density of tumor HEVs, T and B cell infiltration, and favorable clinical outcome (longer DFS and OS) in a retrospective cohort of 146 primary invasive breast cancer patients. Together, these results indicated that, similar to mouse lymph nodes (15), DCs and lymphotoxin pathway may be critical regulators of HEV blood vessels in human breast tumors.

We observed that densities of DC-LAMP+ DCs and tumor HEVs were significantly higher in DCIS than in IDC. Interestingly, in a series of 31 invasive breast carcinomas containing matched DCIS and IDC components, the density of tumor HEVs and DC-LAMP+ DCs was strongly reduced between DCIS and IDC components. These observations suggest that loss of tumor HEVs and DC-LAMP+ DCs during breast cancer progression may represent a critical step in the transition from in situ carcinoma to invasive carcinoma.

Although our results strongly suggest that DCs foster HEV development and/or maintenance within human breast tumors, we cannot exclude the alternative possibilities that DCs arriving via tissue lymphatics may preferentially be attracted to pre-existing HEVs or that DCs may enter the stroma via tumor HEVs. Functional analyses in mouse tumor models will be required to demonstrate the direct role of DCs in the induction and/or maintenance of tumor HEVs.

Surprisingly, increased densities of Tregs were observed in breast tumors containing high densities of tumor HEVs. In contrast, it was previously reported that in mouse methylcholanthrene-induced fibrosarcomas, formation of tumor HEVs only occurs after depletion of Tregs (14). Our results indicate that the absence of Tregs is not an essential prerequisite for development of HEVs in human breast tumors. However, the relative proportion of Tregs compared with other T cell populations appears to be important because HEVhigh breast tumors were associated with low FOXP3+ Tregs/CD3+ T cell ratios. Therefore, Tregs may limit HEV neogenesis in human breast tumors, similar to mouse tumor models (14). LTα and LTβ were upregulated in mouse fibrosarcomas upon depletion of Tregs (14), suggesting that Tregs may inhibit HEV development through reduction of LTα1β2 levels.

Interestingly, targeting of LTα to mouse melanomas tumors has been shown to result in formation of tumor HEVs, T cell infiltration, and eradication of the tumors (12, 13). Overexpression of LIGHT, the second ligand for LTβR, in mouse tumors has also been shown to induce antitumor immunity and eradication of the tumors (28, 29). However, it remains unclear whether tumor HEVs were generated upon overexpression of LIGHT. Although DCs in lymph nodes express both LTα/LTβ and LIGHT (15), it is unknown yet whether LIGHT plays a role in the regulation of HEVs. In this study, we observed that LIGHT was not overexpressed in HEVhigh breast tumors, indicating that LTα1β2, rather than LIGHT, is likely to be the major LTβR ligand involved in the generation of human breast tumor HEVs.

Further characterization of the cellular and molecular mechanisms regulating the formation of tumor HEVs (including the roles of DCs and lymphotoxin) will be important because it could lead to the development of improved therapeutic strategies for human solid tumors. For instance, it could provide means to induce the HEV endothelial cell differentiation program in tumor blood vessels. This would increase the density of tumor HEVs without increasing tumor angiogenesis (total number of tumor blood vessels) and would suppress tumor growth through enhanced recruitment of cytotoxic lymphocytes. Novel therapeutic strategies based on the modulation of tumor HEVs could thus have a major impact on tumor growth and clinical outcome of cancer patients.

We are grateful to Jean-Jacques Fournié and members of the Girard team and ICR Anatomopathology Service for help. We thank the Biological Resource Center of the ICR for providing breast tumor samples. We thank Renaud Poincloux for designing the lymphocyte count macro and the IBiSA TRI facility for flow cytometry and imaging.

This work was supported by the Institut National du Cancer (Grant 2012-039), Fondation Réseau Innovations Thérapeutiques en Cancérologie, Région Midi-Pyrénées, Fondation ARC pour la Recherche sur le Cancer (Programme ARC number SL220110603471; Equipment ARC number ECL2010R00650), Ligue Nationale contre le Cancer (postdoctoral fellowship to L.M.), and the Association “Le Cancer du Sein, Parlons-en!”

The online version of this article contains supplemental material.

Abbreviations used in this article:

     
  • CT

    cycling threshold

  •  
  • DC

    dendritic cell

  •  
  • DCIS

    ductal carcinoma in situ

  •  
  • DFS

    disease-free survival

  •  
  • HEV

    high endothelial venule

  •  
  • ICR

    Institut Claudius Regaud

  •  
  • IDC

    invasive ductal carcinoma

  •  
  • LTα

    lymphotoxin α

  •  
  • LTβ

    lymphotoxin β

  •  
  • LTβR

    lymphotoxin β receptor

  •  
  • OS

    overall survival

  •  
  • qRT-PCR

    quantitative RT-PCR

  •  
  • Treg

    regulatory T cell.

1
Carmeliet
P.
2005
.
Angiogenesis in life, disease and medicine.
Nature
438
:
932
936
.
2
Carmeliet
P.
,
Jain
R. K.
.
2000
.
Angiogenesis in cancer and other diseases.
Nature
407
:
249
257
.
3
Martinet
L.
,
Garrido
I.
,
Filleron
T.
,
Le Guellec
S.
,
Bellard
E.
,
Fournie
J. J.
,
Rochaix
P.
,
Girard
J. P.
.
2011
.
Human solid tumors contain high endothelial venules: association with T- and B-lymphocyte infiltration and favorable prognosis in breast cancer.
Cancer Res.
71
:
5678
5687
.
4
Girard
J. P.
,
Moussion
C.
,
Förster
R.
.
2012
.
HEVs, lymphatics and homeostatic immune cell trafficking in lymph nodes.
Nat. Rev. Immunol.
12
:
762
773
.
5
von Andrian
U. H.
,
Mempel
T. R.
.
2003
.
Homing and cellular traffic in lymph nodes.
Nat. Rev. Immunol.
3
:
867
878
.
6
Miyasaka
M.
,
Tanaka
T.
.
2004
.
Lymphocyte trafficking across high endothelial venules: dogmas and enigmas.
Nat. Rev. Immunol.
4
:
360
370
.
7
Martinet
L.
,
Le Guellec
S.
,
Filleron
T.
,
Lamant
L.
,
Meyer
N.
,
Rochaix
P.
,
Garrido
I.
,
Girard
J. P.
.
2012
.
High endothelial venules (HEVs) in human melanoma lesions: Major gateways for tumor-infiltrating lymphocytes.
OncoImmunology
1
:
829
839
.
8
Martinet
L.
,
Garrido
I.
,
Girard
J. P.
.
2012
.
Tumor high endothelial venules (HEVs) predict lymphocyte infiltration and favorable prognosis in breast cancer.
OncoImmunology
1
:
789
790
.
9
Fridman
W. H.
,
Galon
J.
,
Pagès
F.
,
Tartour
E.
,
Sautès-Fridman
C.
,
Kroemer
G.
.
2011
.
Prognostic and predictive impact of intra- and peritumoral immune infiltrates.
Cancer Res.
71
:
5601
5605
.
10
de Chaisemartin
L.
,
Goc
J.
,
Damotte
D.
,
Validire
P.
,
Magdeleinat
P.
,
Alifano
M.
,
Cremer
I.
,
Fridman
W. H.
,
Sautès-Fridman
C.
,
Dieu-Nosjean
M. C.
.
2011
.
Characterization of chemokines and adhesion molecules associated with T cell presence in tertiary lymphoid structures in human lung cancer.
Cancer Res.
71
:
6391
6399
.
11
Cipponi
A.
,
Mercier
M.
,
Seremet
T.
,
Baurain
J. F.
,
Théate
I.
,
van den Oord
J.
,
Stas
M.
,
Boon
T.
,
Coulie
P. G.
,
van Baren
N.
.
2012
.
Neogenesis of lymphoid structures and antibody responses occur in human melanoma metastases.
Cancer Res.
72
:
3997
4007
.
12
Schrama
D.
,
thor Straten
P.
,
Fischer
W. H.
,
McLellan
A. D.
,
Bröcker
E. B.
,
Reisfeld
R. A.
,
Becker
J. C.
.
2001
.
Targeting of lymphotoxin-alpha to the tumor elicits an efficient immune response associated with induction of peripheral lymphoid-like tissue.
Immunity
14
:
111
121
.
13
Schrama
D.
,
Voigt
H.
,
Eggert
A. O.
,
Xiang
R.
,
Zhou
H.
,
Schumacher
T. N.
,
Andersen
M. H.
,
thor Straten
P.
,
Reisfeld
R. A.
,
Becker
J. C.
.
2008
.
Immunological tumor destruction in a murine melanoma model by targeted LTalpha independent of secondary lymphoid tissue.
Cancer Immunol. Immunother.
57
:
85
95
.
14
Hindley
J. P.
,
Jones
E.
,
Smart
K.
,
Bridgeman
H.
,
Lauder
S. N.
,
Ondondo
B.
,
Cutting
S.
,
Ladell
K.
,
Wynn
K. K.
,
Withers
D.
, et al
.
2012
.
T-cell trafficking facilitated by high endothelial venules is required for tumor control after regulatory T-cell depletion.
Cancer Res.
72
:
5473
5482
.
15
Moussion
C.
,
Girard
J. P.
.
2011
.
Dendritic cells control lymphocyte entry to lymph nodes through high endothelial venules.
Nature
479
:
542
546
.
16
Browning
J. L.
,
Allaire
N.
,
Ngam-Ek
A.
,
Notidis
E.
,
Hunt
J.
,
Perrin
S.
,
Fava
R. A.
.
2005
.
Lymphotoxin-beta receptor signaling is required for the homeostatic control of HEV differentiation and function.
Immunity
23
:
539
550
.
17
Liao
S.
,
Ruddle
N. H.
.
2006
.
Synchrony of high endothelial venules and lymphatic vessels revealed by immunization.
J. Immunol.
177
:
3369
3379
.
18
Drayton
D. L.
,
Ying
X.
,
Lee
J.
,
Lesslauer
W.
,
Ruddle
N. H.
.
2003
.
Ectopic LT alpha beta directs lymphoid organ neogenesis with concomitant expression of peripheral node addressin and a HEV-restricted sulfotransferase.
J. Exp. Med.
197
:
1153
1163
.
19
Drayton
D. L.
,
Liao
S.
,
Mounzer
R. H.
,
Ruddle
N. H.
.
2006
.
Lymphoid organ development: from ontogeny to neogenesis.
Nat. Immunol.
7
:
344
353
.
20
Marinkovic
T.
,
Garin
A.
,
Yokota
Y.
,
Fu
Y. X.
,
Ruddle
N. H.
,
Furtado
G. C.
,
Lira
S. A.
.
2006
.
Interaction of mature CD3+CD4+ T cells with dendritic cells triggers the development of tertiary lymphoid structures in the thyroid.
J. Clin. Invest.
116
:
2622
2632
.
21
Webster
B.
,
Ekland
E. H.
,
Agle
L. M.
,
Chyou
S.
,
Ruggieri
R.
,
Lu
T. T.
.
2006
.
Regulation of lymph node vascular growth by dendritic cells.
J. Exp. Med.
203
:
1903
1913
.
22
Gräbner
R.
,
Lötzer
K.
,
Döpping
S.
,
Hildner
M.
,
Radke
D.
,
Beer
M.
,
Spanbroek
R.
,
Lippert
B.
,
Reardon
C. A.
,
Getz
G. S.
, et al
.
2009
.
Lymphotoxin beta receptor signaling promotes tertiary lymphoid organogenesis in the aorta adventitia of aged ApoE-/- mice.
J. Exp. Med.
206
:
233
248
.
23
Motallebzadeh
R.
,
Rehakova
S.
,
Conlon
T. M.
,
Win
T. S.
,
Callaghan
C. J.
,
Goddard
M.
,
Bolton
E. M.
,
Ruddle
N. H.
,
Bradley
J. A.
,
Pettigrew
G. J.
.
2012
.
Blocking lymphotoxin signaling abrogates the development of ectopic lymphoid tissue within cardiac allografts and inhibits effector antibody responses.
FASEB J.
26
:
51
62
.
24
Galon
J.
,
Costes
A.
,
Sanchez-Cabo
F.
,
Kirilovsky
A.
,
Mlecnik
B.
,
Lagorce-Pagès
C.
,
Tosolini
M.
,
Camus
M.
,
Berger
A.
,
Wind
P.
, et al
.
2006
.
Type, density, and location of immune cells within human colorectal tumors predict clinical outcome.
Science
313
:
1960
1964
.
25
Pagès
F.
,
Kirilovsky
A.
,
Mlecnik
B.
,
Asslaber
M.
,
Tosolini
M.
,
Bindea
G.
,
Lagorce
C.
,
Wind
P.
,
Marliot
F.
,
Bruneval
P.
, et al
.
2009
.
In situ cytotoxic and memory T cells predict outcome in patients with early-stage colorectal cancer.
J. Clin. Oncol.
27
:
5944
5951
.
26
Cyster
J. G.
2005
.
Chemokines, sphingosine-1-phosphate, and cell migration in secondary lymphoid organs.
Annu. Rev. Immunol.
23
:
127
159
.
27
Förster
R.
,
Davalos-Misslitz
A. C.
,
Rot
A.
.
2008
.
CCR7 and its ligands: balancing immunity and tolerance.
Nat. Rev. Immunol.
8
:
362
371
.
28
Yu
P.
,
Lee
Y.
,
Liu
W.
,
Chin
R. K.
,
Wang
J.
,
Wang
Y.
,
Schietinger
A.
,
Philip
M.
,
Schreiber
H.
,
Fu
Y. X.
.
2004
.
Priming of naive T cells inside tumors leads to eradication of established tumors.
Nat. Immunol.
5
:
141
149
.
29
Yu
P.
,
Lee
Y.
,
Wang
Y.
,
Liu
X.
,
Auh
S.
,
Gajewski
T. F.
,
Schreiber
H.
,
You
Z.
,
Kaynor
C.
,
Wang
X.
,
Fu
Y. X.
.
2007
.
Targeting the primary tumor to generate CTL for the effective eradication of spontaneous metastases.
J. Immunol.
179
:
1960
1968
.

The authors have no financial conflicts of interest.