You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["AnatomicalEntity"].

Please return the output as a JSON object of the format: {"AnatomicalEntity": ["tumor cells", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

VEGF-targeted therapy: therapeutic potential and recent advances.
After over 30 years of theorizing, the use of angiogenesis inhibitors as anticancer therapy has finally moved from the realm of research to reality. Normal adult vasculature is generally quiescent in nature, with endothelial cells dividing approximately every 10 years. In contrast, the growth of tumors requires constant vascular growth and remodeling in order for solid tumors to grow beyond 1-2 mm(3) in size. Vascular endothelial growth factor (VEGF) and its receptors are key regulators of the process of angiogenesis, which makes them attractive therapeutic targets. A multitude of VEGF-targeted inhibitory agents are currently being investigated for the treatment of cancer. This review article focuses on recent developments in the use of angiogenesis inhibitors for the treatment of breast, lung, and colorectal cancers.
{"AnatomicalEntity": ["breast", "tumors", "cancer", "colorectal cancers", "endothelial cells", "vascular", "lung", "vasculature", "solid tumors"]}