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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)
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

hum0200-v5Release info

This page is a past version (v5). The latest version is v7.
Latest version (v7)

Research title

Analysis of somatic mutations and gene expression abnormalities involved in mammary tumor phenotype

Research overview

Aims
Search for risk stratification factors based on the molecular biological background of non-invasive ductal carcinoma and analysis of the metastatic process of invasive ductal carcinoma of the breast
Methods
Selected the patients with Ductal Carcinoma In Situ (DCIS) or Invasive Ductal Carcinoma (IDC) based on clinical risk factors and examined the association with risk factors by comprehensive gene analyses.
- IDC: target capture sequencing (TC), methylation, spatial gene expression, single-cell RNA sequencing (scRNA-seq), semibulk RNA-seq, whole genome sequencing (WGS), Enzymatic Methyl-seq (EM-seq), targeted long-read methylation sequencing (t-nanoEM) analyses
- DCIS: target capture sequencing (TC), methylation, spatial gene expression, single-cell RNA sequencing (scRNA-seq), semibulk RNA-seq, whole exome sequencing (Exome), single-cell copy number variant (scCNV), and whole genome sequencing (WGS) analyses
Participants/materials
Human Ductal Carcinoma In Situ (DCIS), Invasive Ductal Carcinoma (IDC)
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
JGAD000287NGS (Exome)
single-cell CNV analysis
  • WES
  • Single-cell CNV
Controlled-access (Type I)2021-04-02
JGAD000368NGS (WGS)
Methylation analysis
  • WGS
  • メチル化解析
Controlled-access (Type I)2021-04-26
JGAD000307NGS (Target Capture)
NGS (Visium Spatial Gene Expression), Histological image
  • Targeted DNA sequencing
Controlled-access (Type I)2021-04-02
JGAD000308NGS (Target Capture)
NGS (Visium Spatial Gene Expression), Histological image
  • Visium 空間トランスクリプトーム + 病理画像
Controlled-access (Type I)2021-04-02
JGAD000396NGS (Visium Spatial Gene Expression), Histological image
  • Visium 空間トランスクリプトーム + 病理画像
Controlled-access (Type I)2022-03-10
JGAD000502NGS (semibulk RNA-seq)
NGS (scRNA-seq)
  • semibulk RNA-seq
  • scRNA-seq
Controlled-access (Type I)2022-08-23

Data provider

Principal investigator
Satoi Nagasawa
Affiliation
Division of Breast and Endocrine Surgery, Department of Surgery St. Marianna University School of Medicine

Research projects

No research projects.

Grants

NameTitleProject number
KAKENHI Grant-in-Aid for Scientific Research on Priority Areas (Research in a proposed research area)
Platform for Advanced Genome Science
  • 16H06279
JSPS Fujita Memorial Fund for Medical Research
Investigation of novel risk factors for recurrence to optimize the treatment of ductal carcinoma in situ (DCIS) of the breast
N/A

Related publications

TitleDOIDataset ID
Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation
https://doi.org/10.1038/s41598-022-07685-4 (opens in a new tab)
Semibulk RNA-seq analysis as a convenient method for measuring gene expression statuses in a local cellular environment
https://doi.org/10.1038/s41598-022-19391-2 (opens in a new tab)

Controlled access users

No use of the controlled access data has been recorded.