2019/05/07
Keio University School of Medicine
Kyoto University
National Cancer Center Japan
Japan Agency for Medical Research and Development (AMED)
A group of researchers, including Dr. Hiroyuki Yasuda, Senior Lecturer at the Department of Internal Medicine (Pulmonology), Keio University School of Medicine; Dr. Junko Hamamoto, Project Assistant Professor at the Endowed Chair for Control of Lung Cancer Pathophysiology; Dr. Shinnosuke Ikemura, Assistant Professor at the Cancer Center; Professor Kenzo Soejima of the Clinical and Translational Research Center; Associate Professor Mayumi Kamada, Project Associate Professor Motsugu Araki, and Professor Yasushi Okuno of the Department of Human Health Sciences, Graduate School of Medicine, Kyoto University; Dr. Katsuya Tsuchihara, Head of the Division of Translational Informatics, and Dr. Susumu Kobayashi, Head of the Division of Genome Translational Research, at the Exploratory Oncology Research & Clinical Trial Center, National Cancer Center; Dr. Koichi Goto, Chief of the Department of Thoracic Oncology, and Dr. Shingo Matsumoto, staff physician, at the National Cancer Center Hospital East; and Dr. Takashi Kohno, Head of the Division of Genome Biology at the National Cancer Center Research Institute, has confirmed that the efficacy of drugs for genetic mutations in lung cancer can be predicted with high accuracy using a prediction system on the supercomputer "K" and Japan's largest cancer clinical genome database built by LC-SCRUM-Japan.
With the spread of cancer genomic medicine, various genetic mutations have been identified, and the effects of therapeutic drugs (molecularly targeted drugs) are being predicted. However, predicting the effects of medication for rare genetic mutations has been difficult, posing a major obstacle in selecting drugs.
In this study, the research group focused on the EGFR gene, which has the most frequently observed mutations in lung cancer among Japanese patients, and analyzed the genetic mutations in approximately 2,000 cases of lung cancer. As a result, they were able to predict with high accuracy, using the supercomputer "K," anticancer drugs that are highly effective against lung cancer with rare EGFR genetic mutations. It is expected that by putting this system, which uses an ultra-high-speed, high-performance computer, into practical use, it will become possible to quickly select highly effective therapeutic drugs for more lung cancer patients. Furthermore, by expanding its application to many other genes, it is expected to contribute significantly to the advancement of cancer genomic medicine.
The results of this research were published in the online edition of "Proceedings of the National Academy of Sciences of the United States of America (PNAS)," a journal published by the U.S. National Academy of Sciences, on May 1, 2019 (U.S. Eastern Time).
Please see below for the full press release.