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)
We apologize for any inconvenience this may cause and appreciate your understanding.

We are currently receiving a large number of applications for data submission, and the review process is taking longer than usual.We sincerely apologize for the delay and kindly ask for your understanding. When submitting an application, we would greatly appreciate it if you could allow sufficient time for the processing.

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

hum0067-v1Release info

Latest

Research title

Project for Development of Innovative Research on Cancer Therapeutics; identifiying the predictive factors for response to chemoherapy in ovarian cancer

Research overview

Aims: To identify novel predictive biomarkers of response to chemotherapy for clear cell carcinoma of the ovary
Methods: whole exome sequencing by using of Illumina HiSeq 2000
Participants/materials: 110 samples (non-tumor and tumor tissues) from 55 ovarian clear cell carcinoma patients
URL: N/A

Datasets

Cart	Dataset ID	Type of data	Analysis method	Access criteria	Date published
	JGAD000076	NGS (Exome)	WES	Controlled-access (Type I)	2020-09-28

Data provider

Principal investigator: Toru Sugiyama
Affiliation: Department of Obstetrics and Gynecology, Iwate Medical University School of Medicine

Research projects

No research projects.

Grants

Name	Title	Project number
Project for Development of Innovative Research on Cancer Therapeutics	Identifiying the predictive factors for response to chemoherapy in ovarian cancer	N/A

Related publications

No related publications.

Controlled access users

Principal investigator	Affiliation	Country/Region	Research title	Period of data use	Dataset ID
Masaki Mandai	department of Gynecology and Obstetrics, Kyoto University Faculty of Medicene	Japan	Integrated analyses of omics (genomics, transcriptomics, proteomics and metabolomics) associated with clinical variables for developing indivisualizedtreatment in gynecological malignancy	2018-10-04 – 2025-04-14	JGAD000076
Kouya Shiraishi	Division of Genome Biology, National Cancer Research Institute	Japan	Elucidation of immune-system networks between host and tumor based on genomic analysis	2019-08-05 – 2029-03-31	JGAD000076
Tatsuhiko Tsunoda	Tsunoda Laboratory (Medical Science Mathematics), Department of Biological Sciences, Graduate School of Science, The University of Tokyo	Japan	Research on sequence, image data analysis for precision medicine (9)	2021-07-09 – 2025-07-07	JGAD000076
Noriomi Matsumura	Obstetrics and Gynecology, Kindai University	Japan	Integrated multi-omics analysis for ovarian clear cell adenocarcinoma: JGOG3017-TR1	2024-10-15 – 2027-12-31	JGAD000076
Ken Yamaguchi	Gynecology and Obstetrics, Kyoto University	Japan	Integrated multi-omics analysis for ovarian clear cell adenocarcinoma: JGOG3017-TR1	2024-10-22 – 2027-12-31	JGAD000076