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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

hum0394-v2Release info

This page is a past version (v2). The latest version is v3.
Latest version (v3)

Research title

Multi-institutional joint research of spatial transcriptome analysis for non-small cell lung cancers

Research overview

Aims
We perform spatial transcriptome analysis and other omics analyses, such as genome/epigenome sequencing and multiplexed immunofluorescence, using fresh-frozen and FFPE specimens of non-small cell lung cancers. We try to develop a novel stratification method for lung cancer patients by considering intratumor heterogeneity and conditions of complicated microenvironments of cancer tissues. We aim to characterize omics statuses of cancer cells and their surrounding stromal cells and immune cells, such as cancer-associated fibroblasts and tumor-infiltrating lymphocytes, at a spatial level and evaluate tumor cell-microenvironment relationships at a molecular level.
Methods
Spatial transcriptome sequencing Visium, high-performance in situ gene expression mapping Xenium, Multiplex Fluorescence Immunostaining, Whole Genome Sequencing and Targeted Long-Read Methylation Sequencing (t-nanoEM)
Participants/materials
[Visium] 16 tumor sections from 8 non-small cell lung cancer patients
[Xenium] Five tumor sections from 5 non-small cell lung cancer patients
[WGS] 1 + 1 tumor sections and 1 + 1 non-tumor sections from 1 + 1 non-small cell lung cancer patients
[t-nanoEM] Multiple microdissected tumor regions from 1 + 1 non-small cell lung cancer patients
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
JGAD000742NGS (Visium Spatial Gene Expression), Histological image
Xenium In Situ Gene Expression
Multiplex Fluorescence Immunostaining
  • Xenium 空間トランスクリプトーム
  • Multiplex Fluorescence Immunostaining
  • Visium 空間トランスクリプトーム + 病理画像
Controlled-access (Type I)2024-04-05
JGAD000898NGS (WGS, t-nanoEM)
  • WGS
  • t-nanoEM (Nanopore methylation)
Controlled-access (Type I)2024-11-22

Data provider

Principal investigator
Ayako Suzuki
Affiliation
Laboratory of Medical Omics Data Analysis, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo

Research projects

No research projects.

Grants

NameTitleProject number
KAKENHI Grant-in-Aid for Early-Career Scientists
Development of spatial genome and transcriptome analytical methods in local regions of lung cancer tissues
  • 21K15566
KAKENHI Grant-in-Aid for Transformative Research Areas
Platform for Advanced Genome Science
  • 22H04925
KAKENHI Grant-in-Aid for Scientific Research (B)
Development of a method for targeted long-read methylation analysis and application to breast cancer specimens
  • 23K27160

Related publications

No related publications.

Controlled access users

No use of the controlled access data has been recorded.