Alan Greig , Rui Henrique , Boyu Xie , Christopher Thrasivoulou , Michael Millar , Aamir Ahmed
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引用次数: 0
Abstract
Super-resolution microscopy holds great promise for detailed structural analysis of proteins, yet its application in the investigations of protein structures in situ remains sparse. Clathrin-coated pit-mediated endocytosis (CME) plays a key role in human cancer. This study aimed to discover whether there are structural changes in clathrin pits in cancer. Immunofluorescence combined with super-resolution structured illumination microscopy (SR-SIM) on normal and cancerous prostate tissue was used to reveal novel details of clathrin structure and biology. Clathrin (heavy-chain) plaques and pits, expression of adaptor protein 2 (a clathrin adaptor protein), and epidermal growth factor receptor (a receptor target for CME) at nanometer scale in human tissue were observed in situ with immunofluorescence-SR-SIM. The size of the clathrin pits in high-grade cancer was greater compared with that in low-grade or normal prostate tissue. These results demonstrate that SR-SIM can be used to identify protein structures at high resolution in clinical tissue sections and there is an increased cargo capacity due to the increase in the size of clathrin pits as a mechanism that facilitates aggressiveness of cancer. These results shed new light on the pathology of cancer and the role CME via clathrin may play in carcinogenesis.
期刊介绍:
The American Journal of Pathology, official journal of the American Society for Investigative Pathology, published by Elsevier, Inc., seeks high-quality original research reports, reviews, and commentaries related to the molecular and cellular basis of disease. The editors will consider basic, translational, and clinical investigations that directly address mechanisms of pathogenesis or provide a foundation for future mechanistic inquiries. Examples of such foundational investigations include data mining, identification of biomarkers, molecular pathology, and discovery research. Foundational studies that incorporate deep learning and artificial intelligence are also welcome. High priority is given to studies of human disease and relevant experimental models using molecular, cellular, and organismal approaches.