Remodeling of the Lymph Node High Endothelial Venules Reflects Tumor Invasiveness in Breast Cancer and is Associated with Dysregulation of Perivascular Stromal Cells

The tumor-draining lymph nodes (TDLNs) are primary sites for induction of tumor immunity. They are also common sites of metastasis, suggesting that tumor-induced mechanisms can subvert anti-tumor immune responses and promote metastatic seeding. The high endothelial venules (HEVs) together with CCL21-expressing fibroblastic reticular cells (FRCs) are essential for lymphocyte recruitment into the LNs. We established multicolor antibody panels for evaluation of HEVs and FRCs in TDLNs from breast cancer (BC) patients. Our data show that patients with invasive BC display extensive structural and molecular remodeling of the HEVs, including vessel dilation, thinning of the endothelium and discontinuous expression of the HEV-marker PNAd. Remodeling of the HEVs was associated with dysregulation of CCL21 in perivascular FRCs and with accumulation of CCL21-saturated lymphocytes, which we link to loss of CCL21-binding heparan sulfate in FRCs. These changes were rare or absent in LNs from patients with non-invasive BC and cancer-free organ donors and were observed independent of nodal metastasis. Thus, pre-metastatic dysregulation of core stromal and vascular functions within TDLNs reflect the primary tumor invasiveness in BC. This adds to the understanding of cancer-induced perturbation of the immune response and opens for prospects of vascular and stromal changes in TDLNs as potential biomarkers. Simple Summary Tumor draining lymph nodes (TDLNs) are the most common metastatic sites in human cancer but are also essential sites for induction of tumor immunity. How different types of primary tumors affect the anti-tumor immune response in the LNs is not fully understood. By analyzing biobank tissue from breast cancer patients, we demonstrate that invasive breast cancer induce dramatic pre-metastatic LN changes affecting the structure and function of the specialized LN vasculature and associated stromal cells, required for recruitment of T-lymphocytes into the LNs. These changes could not be seen in patients with non-invasive breast cancer and provide new insights of how invasive tumors can disrupt essential functions within the immune system. The data also shows promise of LN stromal and vascular changes as possible future biomarkers for prediction of disease progression in human cancer

Magnetic-Guided Axillary UltraSound (MagUS) Sentinel Lymph Node Biopsy and Mapping in Patients with Early Breast Cancer. A Phase 2, Single-Arm Prospective Clinical Trial

Simple Summary Superparamagnetic iron oxide nanoparticles (SPIO) have been shown to identify sentinel lymph nodes (SLNs) in patients with breast cancer. This study investigated whether a minimally invasive approach with MRI-LG after SPIO injection in the breast followed by a magnetic guided axillary ultrasound and core biopsy of the SLN (MagUS) could accurately stage the axilla. The study included not only patients planned for primary surgery but also patients with recurrent cancer after previous surgery, but also patients scheduled for neoadjuvant treatment (NAT). The latter underwent minimally invasive SLNB prior to treatment and had their SLN clipped; surgery in the axilla was performed after NAT. In 79 included patients, MagUS detected all patients with macrometastasis and performed comparably with surgical sentinel lymph node dissection (SLND). It also allowed for marking of the SLN in patients planned for PST and enabled tailored decision making in breast cancer recurrence. Lymph Node Dissection (SLND) is standard of care for diagnosing sentinel lymph node (SLN) status in patients with early breast cancer. Study aim was to determine whether the combination of Superparamagnetic iron oxide nanoparticles (SPIO) MRI-lymphography (MRI-LG) and a Magnetic-guided Axillary UltraSound (MagUS) with biopsy can allow for minimally invasive, axillary evaluation to de-escalate surgery. Patients were injected with 2 mL of SPIO and underwent MRI-LG for SN mapping. Thereafter MagUS and core needle biopsy (CNB) were performed. Patients planned for neoadjuvant treatment, the SLN was clipped and SLND was performed after neoadjuvant with the addition of isotope. During surgery, SLNs were controlled for signs of previous biopsy or clip. The primary endpoint was MagUS SLN detection rate, defined as successful SLN detection of at least one SLN of those retrieved in SLND. In 79 patients, 48 underwent upfront surgery, 12 received neoadjuvant and 19 had recurrent cancer. MagUS traced the SLN in all upfront and neoadjuvant cases, detecting all patients with macrometastases (n = 10). MagUS missed only one micrometastasis, outperforming baseline axillary ultrasound AUS (AUC: 0.950 vs. 0.508, p < 0.001) and showing no discordance to SLND (p = 1.000). MagUS provides the niche for minimally invasive axillary mapping that can reduce diagnostic surgery

Automated detection of vascular remodeling in human tumor draining lymph nodes by the deep learning tool HEV-finder

Vascular remodeling is common in human cancer and has potential as future biomarkers for prediction of disease progression and tumor immunity status. It can also affect metastatic sites, including the tumor-draining lymph nodes (TDLNs). Dilation of the high endothelial venules (HEVs) within TDLNs has been observed in several types of cancer. We recently demonstrated that it is a premetastatic effect that can be linked to tumor invasiveness in breast cancer. Manual visual assessment of changes in vascular morphology is a tedious and difficult task, limiting high-throughput analysis. Here we present a fully automated approach for detection and classification of HEV dilation. By using 12,524 manually classified HEVs, we trained a deep-learning model and created a graphical user interface for visualization of the results. The tool, named the HEV-finder, selectively analyses HEV dilation in specific regions of the lymph nodes. We evaluated the HEV-finder's ability to detect and classify HEV dilation in different types of breast cancer compared to manual annotations. Our results constitute a successful example of large-scale, fully automated, and user-independent, image-based quantitative assessment of vascular remodeling in human pathology and lay the ground for future exploration of HEV dilation in TDLNs as a biomarker