NBDC Research ID: hum0175.v2

 

SUMMARY

Aims: Development of actionable molecular targets and/or biomarkers for prognostication and patient stratification

Methods: Exome analysis and target capture analysis (596 genes) by using Illumina HiSeq 2000

Participants/Materials: primary tumor tissues and non-tumor tissues from 69 endometrial carcinoma patients, endometrial hyperplasia lesions and matched normal tissues/whole blood from 30 endometrial hyperplasia patients

 

Dataset IDType of DataCriteriaRelease Date
JGAS000174 NGS (Exome) Controlled-access (Type I) 2019/10/02
JGAS000642 NGS (Target Capture) Controlled-access (Type I) 2024/03/01

*Release Note

* Data users need to apply an application for Using NBDC Human Data to reach the Controlled-access Data. Learn more

 

MOLECULAR DATA

JGAS000174

Participants/Materials

Endometrial carcinoma (ICD10: C541): 69 cases

(tumor tissues: 118 samples, non-tumor tissues: 69 samples)

Targets Exome
Target Loci for Capture Methods -
Platform Illumina [HiSeq 2000]
Library Source DNAs extracted from tumor or non-tumor tissues
Cell Lines -
Library Construction (kit name) SureSelect Human All Exon V4 or V5
Fragmentation Methods Ultrasonic fragmentation (Covaris)
Spot Type Paired-end
Read Length (without Barcodes, Adaptors, Primers, and Linkers) 101 bp
Japanese Genotype-phenotype Archive Dataset ID JGAD000254
Total Data Volume 5 TB (fastq)
Comments (Policies) NBDC policy

 

JGAS000642

Participants/Materials

Endometrial hyperplasia (ICD10: N850): 30 cases

    92 endometrial hyperplasia lesions (48 non-atypical from 30 cases and 44 atypical from 24 cases)

    matched normal tissues/whole blood: 30 samples

Targets Target Capture
Target Loci for Capture Methods 596 genes
Platform Illumina [HiSeq 2000]
Library Source DNAs extracted from endometrial hyperplasia lesions and normal tissues/whole blood
Cell Lines -
Library Construction (kit name) KAPA Hyper Plus or SureSelect
Fragmentation Methods DNase or Ultrasonic fragmentation (Covaris)
Spot Type Paired-end
Read Length (without Barcodes, Adaptors, Primers, and Linkers) 101 bp
Japanese Genotype-phenotype Archive Dataset ID JGAD000772
Total Data Volume 460 GB (fastq)
Comments (Policies) NBDC policy

 

DATA PROVIDER

Principal Investigator: Nobuhiro Takeshima

Affiliation: The Cancer Institute Hospital of JFCR

Project / Group Name: -

Funds / Grants (Research Project Number):

NameTitleProject Number
The Vehicle Racing Commemorative Foundation Exploration of relevant mutations associated with relapsing or refractory ovarian cancer. 5144, 5274, and 5393
KAKENHI Grant-in-Aid for Scientific Research (C) Genome-wide analyses of endometrial endometrioid carcinoma for early detection and personalized medicine. 26462543
KAKENHI Grant-in-Aid for Scientific Research (C) Molecular analysis of malignant ascites formation by single-cell RNA-sequencing. 15K06861
KAKENHI Grant-in-Aid for Scientific Research (C) Identification of the progestin therapy resistance genes in time-course endometrial cancer samples. 17K11308
KAKENHI Grant-in-Aid for Young Scientists (B) Whole genome sequencing analyses of uterine and ovarian carcinosarcoma. 17K18337
KAKENHI Grant-in-Aid for Scientific Research (C) Immune microenvironment analyses of uterine and ovarian carcinosarcoma. 18K07338
Project for Promotion of Cancer Research and Therapeutic Evolution (P-PROMOTE), Japan Agency for Medical Research and Development (AMED) Understanding of tumorigenic program and identification of novel biomarker for early detection and prevention of endometrial cancer through spatial epigenome analysis JP22ama221513
KAKENHI Grant-in-Aid for Scientific Research (C) Exploration of CTCF downstream targets in endometrial cancer JP20K09634

 

PUBLICATIONS

TitleDOIDataset ID
1 Two Distinct Tumorigenic Processes in Endometrial Endometrioid Adenocarcinoma. doi: 10.1016/j.ajpath.2019.09.022 JGAD000254
2 Genetic and epigenetic alterations in precursor lesions of endometrial endometrioid carcinoma doi: 10.1002/path.6278 JGAD000772

 

USRES (Controlled-access Data)

Principal InvestigatorAffiliationCountry/RegionResearch TitleData in Use (Dataset ID)Period of Data Use
Masaki Mandai Kyoto University Faculty of Medicene, department of Gynecology and Obstetrics Integrated analyses of omics (genomics, transcriptomics, proteomics and metabolomics) associated with clinical variables for developing indivisualizedtreatment in gynecological malignancy JGAD000254 2020/03/13-2025/03/31