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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

hum0030-v2Release info

This page is a past version (v2). The latest version is v6.
Latest version (v6)

Research title

The Molecular Biological Analysis about Occurrence and Malignant Transformation in gynecological carcinogenesis

Research overview

Aims
To clarify the biological difference between clear cell carcinoma and other histological subtypes in ovarian carcinomas by comparing copy number variants, and to identify molecular subtypes and carcinogenesis in clear cell ovarian carcinomas by whole-exome sequencing and RNA-sequencing. Then, characterize high-grade serous carcinomas by NGS-based, integrative genomic analyses, with focus on homologous recombination deficiency, molecular subtypes, and prognostic factors.
Methods
Copy Number Variation Analysis: Gene Chip Human Mapping 250K Nsp Arrays were used for detecting the signal intensity of about 260 thousands SNPs and intensities of ovarian clear cell carcinoma were compared to the ones of non-carcinoma.
Whole Exome sequencing and RNA-seq
Participants/materials
Ovarian cancer: 57 cases (12 endometrioid carcinoma) + 111 cases
URL
N/A

Datasets

The list is the one this version published; each dataset's content is shown as it is now.

CartDataset IDType of dataAnalysis methodAccess criteriaDate published
JGAD000022Copy Number Variations in cancer genome
  • Genotyping by array (CNV)
Controlled-access (Type I)2020-09-28
JGAD000682NGS (Exome, RNA-seq)
  • WES
  • RNA-seq
  • Methylation array
  • Expression array
Controlled-access (Type I)2024-05-13

Data provider

Principal investigator
Katsutoshi Oda
Affiliation
Department of Obstetrics and Gynecology, Faculty of Medicine, The University of Tokyo

Research projects

No research projects.

Grants

NameTitleProject number
KAKENHI Grant-in-Aid for Scientific Research (S)
An Integrated Genomic Analysis on Evolution of Cancer Cell Population
  • 24221011
KAKENHI Grant-in-Aid for Scientific Research (C)
Search for the New Molecular Targeted Therapies and Biomarkers Inducing Apoptosis in Endometrial Carcinoma and Ovarian Carcinoma
  • 26462515
KAKENHI Grant-in-Aid for Young Scientists (B)
Search for the New Molecular Targeted Therapies Based on Genetic Profiles of Ovarian Clear Cell Carcinoma
  • 25861473
Project for Development of Innovative Research on Cancer Therapeutics (P-DIRECT)
Development of the Intractable Cancer Therapies through the New Target Identification by the Molecular Profiling (The Identification of the Gene Variation to Regulate the Treatment Sensitivity of the Progressive Ovarian Cancer)
  • 11114014

Related publications

TitleDOIDataset ID
Integrated Copy Number and Expression Analysis Identifies Profiles of Whole-Arm Chromosomal Alterations and Subgroups with Favorable Outcome in Ovarian Clear Cell Carcinomas
https://doi.org/10.1371/journal.pone.0128066 (opens in a new tab)
The frequency of neoantigens per somatic mutation rather than overall mutational load or number of predicted neoantigens per se is a prognostic factor in ovarian clear cell carcinoma
https://doi.org/10.1080/2162402x.2017.1338996 (opens in a new tab)
Neoantigen load and HLA-class I expression identify a subgroup of tumors with a T-cell-inflamed phenotype and favorable prognosis in homologous recombination-proficient high-grade serous ovarian carcinoma
https://doi.org/10.1136/jitc-2019-000375 (opens in a new tab)

Controlled access users

Principal investigatorAffiliationCountry/RegionResearch titlePeriod of data useDataset ID
Ikuo KonishiDepartment of Gynecology and Obstetrics, Kyoto UniversityJapanIntegrated analyses of omics (genomics, transcriptomics, proteomics and metabolomics) associated with clinical variables for developing indivisualized treatment in gynecologycal malignancy2015-07-03 – 2017-09-04
Masaki Mandaidepartment of Gynecology and Obstetrics, Kyoto University Faculty of MediceneJapanIntegrated analyses of omics (genomics, transcriptomics, proteomics and metabolomics) associated with clinical variables for developing indivisualizedtreatment in gynecological malignancy2018-10-04 – 2025-04-14
Noriomi MatsumuraObstetrics and Gynecology, Kindai UniversityJapanIntegrated multi-omics analysis for ovarian clear cell adenocarcinoma: JGOG3017-TR12024-10-15 – 2027-12-31
Ken YamaguchiGynecology and Obstetrics, Kyoto UniversityJapanIntegrated multi-omics analysis for ovarian clear cell adenocarcinoma: JGOG3017-TR12024-10-22 – 2027-12-31