Accession PRJCA009308
Title Parallel single cell and bulk transcriptome analyses reveal key features of the gastric tumor microenvironment
Relevance Medical
Data types Transcriptome or Gene expression
Raw sequence reads
Single cell sequencing
Organisms Homo sapiens
Description We combined bulk and single-cell RNA-sequencing from tumors and matched normal tissue of 24 treatment-naive GC patients to better understand which cell types and transcriptional programs are associated with malignant transformation of the stomach. Clustering 96,623 cell of non-epithelial origin revealed 96 well-defined TME cell types. Activated fibroblasts and endothelial cells were most prominently overrepresented in tumors. Intercellular network reconstruction as well as survival analysis of an independent cohort implied the importance of these cell types together with immunosuppressive myeloid cell subsets and regulatory T cells in establishing an immunosuppressive microenvironment correlating with worsened prognosis and lack of response in anti-PD1 treated patients. In contrast, a subset of IFNg activated T cells and HLA-II expressing macrophages were found to be linked to response and increased overall survival.
Sample scope Single cell
Release date 2022-10-01
Publication
PubMed ID Article title Journal name DOI Year
36550535 Parallel single-cell and bulk transcriptome analyses reveal key features of the gastric tumor microenvironment Genome Biology 10.1186/s13059-022-02828-2 2022
Grants
Agency program Grant ID Grant title
National Natural Science Foundation of China (NSFC) 81988101
National Natural Science Foundation of China (NSFC) 91942307
National Natural Science Foundation of China (NSFC) 31991171
National Natural Science Foundation of China (NSFC) 81402308
National Natural Science Foundation of China (NSFC) 82173151
National Natural Science Foundation of China (NSFC) 81972240
Beijing Municipal Science and Technology Commission Z201100005320014
Science Foundation of Peking University Cancer Hospital 2021-24
Submitter Zemin    Zhang  (zemin@pku.edu.cn)
Organization Peking University
Submission date 2022-04-25

Project Data

Resource name Description
BioSample (48)  show -