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Shigeki Hirabayashi Last modified date:2024.06.27



Graduate School
Undergraduate School
Other Organization


Homepage
https://kyushu-u.elsevierpure.com/en/persons/shigeki-hirabayashi
 Reseacher Profiling Tool Kyushu University Pure
Academic Degree
Doctor (Medicine) (Kyoto University), Bachelor (Medicine) (Niigata University), Bachelor (Pharmacy) (Nagoya City University)
Country of degree conferring institution (Overseas)
No
Field of Specialization
Hematology and Oncology; Systems genomics
Total Priod of education and research career in the foreign country
00years00months
Research
Research Interests
  • Searching for new cancer treatment targets based on large-scale genomics and functional screening
    keyword : CRISPR screening
    2022.04~2022.06.
Academic Activities
Papers
1. Hirabayashi S, Kosugi S, Isobe Y, Nashimoto A, Oda I, Hayashi K, Miyashiro I, Tsujitani S, Kodera Y, Seto Y, Furukawa H, Ono H, Tanabe S, Akazawa K, Development and external validation of a nomogram for overall survival after curative resection in serosa-negative, locally advanced gastric cancer., Annals of oncology : official journal of the European Society for Medical Oncology, 10.1093/annonc/mdu125, 25, 6, 1179-84, 2014.06, BACKGROUND: Few nomograms can predict overall survival (OS) after curative resection of advanced gastric cancer (AGC), and these nomograms were developed using data from only a few large centers over a long time period. The aim of this study was to develop and externally validate an elaborative nomogram that predicts 5-year OS after curative resection for serosa-negative, locally AGC using a large amount of data from multiple centers in Japan over a short time period (2001-2003). PATIENTS AND METHODS: Of 39 859 patients who underwent surgery for gastric cancer between 2001 and 2003 at multiple centers in Japan, we retrospectively analyzed 5196 patients with serosa-negative AGC who underwent Resection A according to the 13th Japanese Classification of Gastric Carcinoma. The data of 3085 patients who underwent surgery from 2001 to 2002 were used as a training set for the construction of a nomogram and Web software. The data of 2111 patients who underwent surgery in 2003 were used as an external validation set. RESULTS: Age at operation, gender, tumor size and location, macroscopic type, histological type, depth of invasion, number of positive and examined lymph nodes, and lymphovascular invasion, but not the extent of lymphadenectomy, were associated with OS. Discrimination of the developed nomogram was superior to that of the TNM classification (concordance indices of 0.68 versus 0.61; P
2. Shigeki Hirabayashi, Shruti Bhagat, Yu Matsuki, Yujiro Takegami, Takuya Uehata, Ai Kanemaru, Masayoshi Itoh, Kotaro Shirakawa, Akifumi Takaori-Kondo, Osamu Takeuchi, Piero Carninci, Shintaro Katayama, Yoshihide Hayashizaki, Juha Kere, Hideya Kawaji, Yasuhiro Murakawa, NET-CAGE characterizes the dynamics and topology of human transcribed cis-regulatory elements, Nature Genetics, 10.1038/s41588-019-0485-9, 51, 9, 1369-1379, 2019.09, Promoters and enhancers are key cis-regulatory elements, but how they operate to generate cell type-specific transcriptomes is not fully understood. We developed a simple and robust method, native elongating transcript-cap analysis of gene expression (NET-CAGE), to sensitively detect 5' ends of nascent RNAs in diverse cells and tissues, including unstable transcripts such as enhancer-derived RNAs. We studied RNA synthesis and degradation at the transcription start site level, characterizing the impact of differential promoter usage on transcript stability. We quantified transcription from cis-regulatory elements without the influence of RNA turnover, and show that enhancer-promoter pairs are generally activated simultaneously on stimulation. By integrating NET-CAGE data with chromatin interaction maps, we show that cis-regulatory elements are topologically connected according to their cell type specificity. We identified new enhancers with high sensitivity, and delineated primary locations of transcription within super-enhancers. Our NET-CAGE dataset derived from human and mouse cells expands the FANTOM5 atlas of transcribed enhancers, with broad applicability to biomedical research..