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: ["Chemical"].

Please return the output as a JSON object of the format: {"Chemical": ["Arsenic", ...]}. 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:

The molecular fingerprint of high grade serous ovarian cancer reflects its fallopian tube origin. High grade serous ovarian cancer (HGSC), the most lethal and frequent type of epithelial ovarian cancer (EOC), has poor long term prognosis due to a combination of factors: late detection, great metastatic potential and the capacity to develop resistance to available therapeutic drugs. Furthermore, there has been considerable controversy concerning the etiology of this malignancy. New studies, both clinical and molecular, strongly suggest that HGSC originates not from the surface of the ovary, but from the epithelial layer of the neighboring fallopian tube fimbriae. In this paper we summarize data supporting the central role of fallopian tube epithelium in the development of HGSC. Specifically, we address cellular pathways and regulatory mechanisms which are modulated in the process of transformation, but also genetic changes which accumulate during disease progression. Similarities between fallopian tube mucosa and the malignant tissue of HGSC warrant a closer analysis of homeostatic mechanisms in healthy epithelium in order to elucidate key steps in disease development. Finally, we highlight the importance of the cancer stem cell (CSC) identification and understanding of its niche regulation for improvement of therapeutic strategies.
{"Chemical": []}