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Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography
Published on: August 16, 2020
The systems of metastatic potential prediction in pheochromocytoma and paraganglioma
Yong Wang1, Minghao Li1, Hao Deng1
1Department of Urology, Xiangya Hospital, Central South University NO. 87 Xiangya Road, Changsha 410008, Hunan, P. R. China.
Abstract:
Pheochromocytoma and paraganglioma (PPGL) are rare neuroendocrine tumors that arising from the adrenal medulla or extra-adrenal autonomic ganglia. Traditionally, PPGL was classified as benign or malignant based on the presence of distant metastasis at the time of initial surgery. However, according to WHO 2017 Classification of Tumors of Endocrine Organs, all PPGL has metastatic potential. The term "metastatic" is used, replacing "malignant" in this group of tumors. The prediction of PPGL's metastatic potential is a clinical concern, although many relevant indicators such as genetics, histology, pathology and molecular biology markers have been proved to be related to the metastasis of PPGL, but none of them is 100% predictive; various types of prediction systems had been created, but previous studies had demonstrated that they still need to be validated in multicenter studies. There is no unified clinical standard to differentiate metastatic from non-metastatic and a highly effective prediction system is of urgent need. In this review, we summarized all reported prediction systems, including the PASS system, the GAPP system, the COPPs system and the ASES system. Additional potential indicators that related to metastatic PPGL were also introduced.

