Investigation of the Lack of Angiogenesis in the Formation of Lymph Node Metastases

Abstract

Background: To date, antiangiogenic therapy has failed to improve overall survival in cancer patients when used in the adjuvant setting (local-regional disease with no detectable systemic metastasis). The presence of lymph node metastases worsens prognosis, however their reliance on angiogenesis for growth has not been reported.

Methods: Here, we introduce a novel chronic lymph node window (CLNW) model to facilitate new discoveries in the growth and spread of lymph node metastases. We use the CLNW in multiple models of spontaneous lymphatic metastases in mice to study the vasculature of metastatic lymph nodes (n = 9-12). We further test our results in patient samples (n = 20 colon cancer patients; n = 20 head and neck cancer patients). Finally, we test the ability of antiangiogenic therapy to inhibit metastatic growth in the CLNW. All statistical tests were two-sided.

Results: Using the CLNW, we reveal the surprising lack of sprouting angiogenesis during metastatic growth, despite the presence of hypoxia in some lesions. Treatment with two different antiangiogenic therapies showed no effect on the growth or vascular density of lymph node metastases (day 10: untreated mean = 1.2%, 95% confidence interval [CI] = 0.7% to 1.7%; control mean = 0.7%, 95% CI = 0.1% to 1.3%; DC101 mean = 0.4%, 95% CI = 0.0% to 3.3%; sunitinib mean = 0.5%, 95% CI = 0.0% to 1.0%, analysis of variance P = .34). We confirmed these findings in clinical specimens, including the lack of reduction in blood vessel density in lymph node metastases in patients treated with bevacizumab (no bevacizumab group mean = 257 vessels/mm(2), 95% CI = 149 to 365 vessels/mm(2); bevacizumab group mean = 327 vessels/mm(2), 95% CI = 140 to 514 vessels/mm(2), P = .78).

Conclusion: We provide preclinical and clinical evidence that sprouting angiogenesis does not occur during the growth of lymph node metastases, and thus reveals a new mechanism of treatment resistance to antiangiogenic therapy in adjuvant settings. The targets of clinically approved angiogenesis inhibitors are not active during early cancer progression in the lymph node, suggesting that inhibitors of sprouting angiogenesis as a class will not be effective in treating lymph node metastases.

© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Figures

Figure 1.

Growth of metastatic cancer cells in a lymph node. A) The chronic lymph node window (CLNW) allows stable intravital microscopy of the inguinal lymph node for up to 14 days. This procedure was well tolerated with no detection of a change in animal body weight for 14 days after CLNW implantation. B) TRITC-dextran angiography, imaged with multiphoton microscopy highlights the robust vasculature (red) of the inguinal lymph node. Second harmonic generation was used to highlight fibrillar collagen (blue) in the lymph node capsule. The image is a maximum intensity projection of 25 μm of tissue from inside the lymph node. C) Representative progression of the formation of lymph node metastasis (SCCVII) from the new arrival of isolated cancer cells (green) to the formation of small clusters of cells and finally their growth into tumors, initially near the capsule (blue) and then deeper in the lymph node near the pre-existing vasculature (red). The series of images was taken from multiple lymph nodes. Yellow line marks edge of lymph node. D) Using primary tumors (SCCVII) of multiple colors (red, green, yellow), we imaged the emergent multicolored lymph node metastasis (n = 4). E) Using primary tumors (4T1) of two colors (red, green)(n = 4), we found more than 80% of lung metastases contained just one color, with the rest consisting of two colors. Scale bars as indicated in each panel.

Figure 2.

Intravital imaging of lymph node metastases and the native lymph node vasculature. A) Representative time course of images from a single metastatic lymph node, showing cancer cells (SCCVII, green) and blood vessels (TRITC-dextran, red) at three different depths in tissue. The image was created using multiphoton microscopy, and second harmonic generation was used to highlight fibrillar collagen (blue) in the lymph node capsule. The images are created from maximum intensity projections of 25 μm of tissue from inside the lymph node. In day 40 images, the red signal is background signal from the accumulation of TRITC-dextran as a result of the five intravenous injections over the course of the metastatic growth. Yellow arrows identify individual cancer cells. Yellow circles identify areas in which many cancer cells are found in the subcapsular sinus. White arrows identify blood vessels in the metastatic lesion. Purple, green and light blue arrows identify features in the lymph node vasculature that can be used to identify the same region in the mouse over the multiday experiment. White line marks edge of lymph node. Scale bars = 100 μm. B) A vertical image reconstruction showing the tumor cells (SCCVII, green) initially growing above the blood vessels (red). C) Measurements of the maximum depth of tumor cell invasion (SCCVII) and the minimum depth of blood vessels. Data are presented as mean ± 95% confidence interval.

Figure 3.

Immunohistochemical analysis of lymph node blood vessels and metastases. A) Representative sections of control (from non–tumor bearing mice), contralateral, and tumor-draining lymph nodes with micrometastases (SCCVII, green). Vessels were stained with CD31 (red) and nuclei with DAPI (blue). Scale bars = 300 μm. B) Quantification of CD31+ area per lymph node area in control, contralateral, and micrometastatic lymph nodes. C) In micrometastatic lymph nodes, quantification of CD31+ area per tissue area comparing tumor areas with nontumor areas. D) Costaining for CD105 and Ki67 measured blood vessel proliferation in micrometastatic lymph nodes. E) Using a different tumor model (4T1) that formed macrometastasis in the lymph node (greater than 500 μm in one direction), we measured CD31+ area in micrometastatic or macrometastatic lymph nodes, compared with control or contralateral nodes. F) The vascular area of macrometastatic lesions was measured in tumor areas and nontumor lymph node tissue. G) Costaining for CD31 and Ki67 measured blood vessel proliferation in macrometastatic lymph nodes. Data are presented as mean ± 95% confidence interval. Statistical significance was tested by one-way analysis of variance with Tukey’s Honestly Significant Difference post hoc test (B, D, E, G) or two-tailed paired Student’s t test (C, F).

Figure 4.

Hypoxia in lymph node metastases. A) Representative images of pimonidazole staining for hypoxia (green) and perfused lectin staining for functional blood vessels (red) in lymph node metastases from 4T1 mammary carcinoma (cytokeratin, blue). The top panels show a lesion in the subcapsular sinus that is hypoxic and has no perfused blood vessels in the lesion. The bottom panels show a lesion in the parenchyma of the lymph node with perfused blood vessels and no hypoxia. Dashed line shows edge of the lymph node. Scale bars = 100 μm. B) Higher magnification of pimonidazole staining in metastatic lymph node showing colocalization of cytokeratin and pimonidazole. Contralateral lymph node is non–tumor bearing. Dashed line shows edge of the lymph node. Scale bars = 50 μm. C) Quantification of pimonidazole and perfused vessel staining in metastatic lesions in the subcapsular sinus and lymph node parenchyma. Data are presented as mean ± 95% confidence interval. Statistical significance was tested by two-tailed unpaired Student’s t test. D and E) Staining for CAIX, a marker of the cellular response to hypoxia, and CD31-positive blood vessels shows similar results to pimonidazole staining. Dashed line shows the outline of the metastatic lesions. Scale bars = 636 μm.

Figure 5.

Molecular signature of quiescent lymph node vasculature. A-C) Levels of vascular endothelial growth factor (VEGF) protein were measured in metastatic lymph nodes containing 4T1 (A), SCCVII (B), or E0771 (C) and compared with control and contralateral lymph nodes. D) Quantitative polymerase chain reaction (qPCR) transcriptional array for angiogenesis-related genes compared the transcriptional profile of a diaeresis lymph node to a tumor-bearing lymph node. Differentially transcribed genes were defined as having more than a four-fold change and a P value under .01 when comparing metastatic lymph nodes to diaeresis lymph nodes. E) Confirmation of the qPCR transcriptional array for the Vegf and Thbs1 genes. *P < .05. F) Dual immunofluorescence staining for CD31 (red) and TSP-1 (green) showed distinctive TSP-1 staining surrounding the blood vessels in diaeresis, contralateral, and metastatic lymph nodes. Scale bars = 100μm. Data are presented as mean ± 95% confidence interval. Statistical significance was tested by one-way analysis of variance with Tukey’s Honestly Significant Difference post hoc test (A, B, and C) and two-tailed unpaired Student’s t test (E).

Figure 6.

Vascular density in metastatic lymph nodes from colon cancer patients. A) Representative images of nonmetastatic (n = 19) and metastatic (n = 39) lymph nodes as well as lymph node tumors in which no normal lymph node tissue remained (n = 9). The sections were stained with CD31 (brown) to identify blood vessels. Scale bars = 200 μm. Images of whole lymph node sections can be found in Supplementary Figure 7 (available online). B) The number of vessels per area as determined by CD31 staining was measured in metastatic lymph nodes and in lymph node tumors in which no normal lymph node tissue remained and compared with nonmetastatic lymph nodes. C) The fraction of lymph node area composed of CD31-positive vessels was similarly measured in metastatic lymph nodes and in lymph node tumors in which no normal lymph node tissue remained and compared with nonmetastatic lymph nodes. *P value was determined by Tukey’s Honestly Significant Difference post hoc test of analysis of variance model. D and E) Within a metastatic lymph node, vascular density (D) and vessel area fraction (E) were measured in the tumor and the nontumor area. * P value was determined by paired Student’s t test. F) Vessel density was not dependent on the lesion size. Data are presented as mean ± 95% confidence interval throughout figure.

Figure 7.

Antiangiogenic therapy in the early growth of lymph node metastases. A) Representative intravital multiphoton microscopy images of spontaneous lymph node metastases treated with vehicle control, sunitinib, or the blocking monoclonal anti–VEGFR-2 antibody DC101. Tumor cells are shown in green and blood vessels in red. Scale bars = 200 μm. B) Primary tumors were of equal size at the time treatment began, when the lymph node micrometastases were 5–10×10–3 mm3. C) The growth rate of the metastatic tumor in the lymph node was measured during antiangiogenesis therapy. D) The vessel density in metastatic lesions in the lymph node was measured during antiangiogenesis therapy. Biological replicates: untreated n = 15 (C), 12 (D), control (IgG = 2, PBS = 4) n = 6, sunitinib = 6, DC101 = 5. Data are presented as mean ± 95% confidence interval. Statistical significance was tested by one-way analysis of variance with Tukey’s Honestly Significant Difference post hoc test (B and C) and two-tailed unpaired Student’s t test (D and E).

Figure 8.

Vascular density in lymph node metastases in rectal cancer patients treated with bevacizumab. The number of CD31+ vessels per area (A) and the fraction of lymph node area composed of CD31+ vessels (B) were measured in nonmetastatic and metastatic lymph nodes in colorectal cancer (CRC) patients that received neoadjuvant chemoradiation (No Bev.) or neoadjuvant chemoradiation with bevacizumab (Bev.). P value was determined by two-tailed unpaired Student’s t test. C and D) Within the tumor area of metastatic lymph nodes, we measured vascular density (C) and vessel area fraction (D) in rectal cancer patients that received neoadjuvant chemoradiation (No Bev.) or neoadjuvant chemoradiation with bevacizumab (Bev.). P value was determined by two-tailed unpaired Student’s t test. Data are presented as mean ± 95% confidence interval.