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Due to system maintenance, the application system, application review by the Data Access Committee will be unavailable during the following period.
Schedule: October 5th (Mon), 2026, 9:00 - October 7th (Wed), 2026, 15:00 (JST)
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Following a change to our organizational structure effective April 1, 2026, this division has been renamed from the "Database Center for Life Science, Joint Support-Center for Data Science Research" to the "Database Division for Life Science (DBCLS), BioData Science Initiative (BSI), National Institute of Genetics (NIG)". Where the former name still appears in the guidelines, please read it as the new name.

Research ID

hum0470-v1Release info

Latest

Research title

Prognostic Investigation and Genomic Profiling of Urothelial Carcinoma Treated with Immunotherapy

Research overview

Aims
The aim of this study is to investigate the prognosis of patients with urothelial carcinoma who have undergone immunotherapy and to assess the presence/absence of genomic instability using tumor tissue obtained after pathological diagnosis. By clarifying whether genomic instability accurately reflects the efficacy of immunotherapy in urothelial carcinoma, we will evaluate its potential as useful biomarkers for determining whether to continue or modify treatment. Furthermore, we will explore its potential utility as clinical information that could contribute to the development of novel therapeutic agents.
Methods
Whole exome sequencing, RNA sequencing, Whole genome sequencing, single-cell RNA sequencing, spatial transcriptomics (Visium)
Participants/materials
One patient diagnosed with urothelial carcinoma who received immunotherapy. Tumor tissues were obtained from either 8 organs (primary lesion, peritumoral region, retroperitoneal lymph nodes, two distinct para-aortic lymph nodes, cervical lymph nodes, right lung metastasis, and left lung metastasis) or 5 organs (central region of the primary tumor, retroperitoneal lymph nodes, para-aortic lymph nodes, cervical lymph nodes, and left lung metastasis).
URL
N/A

Datasets

CartDataset IDType of dataAnalysis methodAccess criteriaDate published
JGAD000858NGS (Exome)
NGS (RNA-seq)
NGS (WGS)
NGS (scRNA-seq)
NGS (Visium Spatial Gene Expression), Histological image
  • WES
  • RNA-seq
  • WGS
Controlled-access (Type I)2025-07-09

Data provider

Principal investigator
Nobuyuki Tanaka
Affiliation
Department of Urology, Keio University School of Medicine

Research projects

NameURL
Department of Urology, Keio University School of Medicine / Tsunoda Laboratory, Department of Biological Sciences, Graduate School of Science, The University of Tokyo / M&D Data Science Center, Institute of Integrated Research, Institute of Science Tokyo
N/A

Grants

NameTitleProject number
KAKENHI Grant-in-Aid for Early-Career Scientists
Prognostic modeling of myxoid liposarcoma by gene expression and histopathology with focus on tumor immunity
  • 20K16408
KAKENHI Grant-in-Aid for Early-Career Scientists
Identification of Treatment-Related Factors Using Multi-Region Analysis Before and After Cancer Immunotherapy
  • 22K15576
KAKENHI Grant-in-Aid for Scientific Research (C)
Elucidation of the role of long non-coding RNA in bladder cancer
  • 23K08724
KAKENHI Grant-in-Aid for Challenging Research (Exploratory)
Establishment of a research platform for visualization of tumor heterogeneity and clinical application
  • 21K19414
KAKENHI Grant-in-Aid for Scientific Research (B)
In situ analysis of diverse urothelial carcinoma immunogenomics and liquid biopsy study
  • 22H03217
  • 23K24476
KAKENHI Grant-in-Aid for Challenging Research (Pioneering)
Spatial Analysis of Stromal Trajectory Map and Establishment of New Stromal Reprogramming Method under Cancer Immunotherapy
  • 24K21301
KAKENHI Grant-in-Aid for Scientific Research (A)
Clonal Evolution of Urologic Cancer and Spatial Analysis of Tumor Stroma to Elucidate Immunotherapy Resistance Mechanisms
  • 24H00649
KAKENHI Grant-in-Aid for Scientific Research (B)
Integrated Multi-Omics Analysis Methodology with Image Transformation and Deep Learning for Pathophysiology and Drug Response Mechanisms
  • 20H03240
KAKENHI Grant-in-Aid for Scientific Research (B)
Embed omics data to quantum computation and construct predictive models with quantum-classical hybrid machine learning
  • 25K02261
Moonshot R&D Program, Japan Science and Technology Agency (JST)
Realization of a society watched over by remote control of intracellular cybernetic avatars
  • JPMJMS2217
Core Research and Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST)
Development of AI-driven single molecule nanopore measurement methods from biological environments
  • JPMJCR2231

Related publications

No related publications.

Controlled access users

Principal investigatorAffiliationCountry/RegionResearch titlePeriod of data useDataset ID
Michiaki HamadaHamada Laboratory, Faculty of Science and Engineering, Waseda UniversityJapanConstruction of RNA-targeted Drug Discovery Database2023-01-05 – 2027-10-31