Promising New Biomarker for Ovarian Cancer: Development of a Novel Exosome Capture Method Using Polyketone Chain-Modified Nanowires

July 10, 2023

Nagoya University, Tokai National Higher Education and Research System

Tokyo Institute of Technology

Hokkaido University

National Cancer Center Japan

Keio University

Tokyo Medical University

Japan Science and Technology Agency

A research group—led by Dr. Akira Yokoi, Hospital Lecturer at the Department of Obstetrics and Gynecology, Nagoya University Hospital (also serving at the Institute for Advanced Research, Nagoya University); Dr. Mayu Ukai, a physician in the Department of Obstetrics and Gynecology, Nagoya University Graduate School of Medicine [currently Head of the Department of Obstetrics and Gynecology at Toyota Memorial Hospital]; Professor Hiroaki Kajiyama of the same department; Professor Takao Yasui of the School of Life Science and Technology, Tokyo Institute of Technology; Professor Yasuhide Inokuma of the Faculty of Engineering (and the Institute for Chemical Reaction Design and Discovery (WPI-ICReDD)), Hokkaido University; Dr. Yusuke Yamamoto, Head of the Division of Molecular and Cellular Medicine, National Cancer Center Research Institute; Associate Professor Juntaro Matsuzaki of the Division of Pharmacotherapeutics, Faculty of Pharmacy, Keio University; and Project Professor Takahiro Ochiya of the Institute of Medical Science, Tokyo Medical University—has newly identified specific membrane proteins in ovarian cancer exosomes through comprehensive proteomics and has also developed polyketone chain-modified nanowires as a method for exosome separation. These results are promising as new biomarkers for the diagnosis and prediction of treatment outcomes for ovarian cancer.

Extracellular vesicles (EVs), including exosomes, are present in all human body fluids and are gaining attention as essential tools for intercellular communication. Furthermore, because the molecules they carry change depending on the disease, they are expected to be promising disease biomarkers. Within EVs, membrane proteins on their surface are extremely important for detecting specific EVs and for use as biomarkers themselves. However, the specific EV membrane proteins in ovarian cancer were unknown, posing a major challenge. Ovarian cancer is a female reproductive malignancy with a poor prognosis and is one of the leading causes of cancer-related deaths among women worldwide. Ovarian cancer is one of the most difficult cancers to detect early, and the development of highly accurate and sensitive biomarkers has been an urgent task. In this study, by conducting detailed quantitative protein analysis of EVs in ovarian cancer, we identified the ovarian cancer EV-associated membrane proteins FRα, Claudin-3, and TACSTD2. Additionally, by applying nanowires, one of the methods for capturing EVs, and modifying them with polyketone chains, we enhanced their EV-binding affinity, enabling the capture of higher-purity EVs. By using a method that combines these findings, we have developed a new detection method using EVs in ovarian cancer patients. These research findings are promising as new biomarkers for ovarian cancer.

This research was mainly supported by the Japan Science and Technology Agency (JST) Forest for Restructuring Research and Development Programs: Research Project "Fundamental technological development for clinical application of cancer extracellular vesicles" (JPMJFR204J) and "Creation of giant functional molecules based on 'medium-sized molecular strings'" (JPMJFR211H); the JST PRESTO program "Elucidation of miRNA secretion pathway by comprehensive capture and mechanical analysis of extracellular vesicles" (JPMJPR19H9); and the Japan Agency for Medical Research and Development (AMED) Project for Cancer Research and Therapeutic Evolution (P-CREATE): Research Project "Novel liquid biopsy strategy using extracellular vesicles carrying ovarian cancer genomes." The results of this research were published in the online edition of the academic journal "Science Advances" on July 7, 2023.

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