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Primo Vascular System and Its Potential Role in Cancer Metastasis

Conference paper
First Online:
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 789)

Abstract

The primo vascular system (PVS) is a newly found organ, which is distributed throughout the entire body. The system is composed of nodes storing many small cells and thin vessels branching out from the nodes. Inside the vessel there are multiple subvessels. The PVS is found in and on most organs, including the brain, and interestingly inside some lymph and blood vessels. The PVS is normally difficult to visualize due to its semitransparent optical property and its small size, which may be the main reason why it was not discovered until recently. The diameter of primo vessels (PVs) is in the range of 20–50 μm and the size of a primo node (PN), 100–1,000 μm. The outermost layer of the PVS is more porous than that of blood or lymph capillary vessels, and the nuclei of the PVS endothelial cells are rod shaped. Important PVS properties reported are: in the fluid inside the PVS, there are cells presenting stem cell markers CD133, Oct4, and Nanog, which may imply that this system has a role in regeneration. Another very important finding is its potential relevance to cancer. According to results from an animal study using xenografts of various cancer types (lung, ovarian, skin, gastric cancer, and leukemia), as the tumor grows, the PVS is formed in a high density in the vicinity of the tumor. In addition, it was shown that PVs connect the primary and secondary tumors and that cancer cells were transported via the PVs in an active manner. In this report, we illustrated the formation of the PVS in breast cancer, and using the green fluorescent protein-expressing gastric cancer cell lines, we observed the cancer cell movement from the primary to the secondary sites during the cancer progression.

Keywords

Gastric Cancer Cell Line Secondary Tumor Human Gastric Cancer Cell Trypan Blue Solution Melanoma B16BL6 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Chemical EngineeringUniversity of LouisvilleLouisvilleUSA
  2. 2.Department of Physiology and BiophysicsUniversity of LouisvilleLouisvilleUSA
  3. 3.Nano Primo Research Center, Advanced Institute of Convergence TechnologySeoul National UniversitySuwonSouth Korea

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