Accession PRJCA001063
Title Single-Cell RNA-seq Highlights Intra-tumoral Heterogeneity and Malignant Progression in Pancreatic Ductal Adenocarcinoma
Relevance Medical
Data types Transcriptome or Gene expression
Organisms Homo sapiens
Description Herein, we implemented the single-cell RNA-seq to determine the transcriptomes of over 50,000 individual pancreatic cells from 24 primary PDAC tumors and 11 normal pancreas. We detected two ductal subtypes representing nonmalignant and malignant ductal cells in PDAC. The malignant cells show high CNV and heterogeneity within and between tumors, in which specific proliferation and metastatic sub-malignant cells present in PDAC patients. Computational cell trajectory analysis revealed that multiple pathways and TFs dynamic expressed during the malignant, proliferation and metastasis progress. By integrating single-cell transcriptomes with bulk expression prfiles for PDAC, we established the association of malignant ductal cells and T cell signals with clinical pathological features.
Sample scope Single cell
Release date 2019-07-09
Publication
PubMed ID Article title Journal name DOI Year
31273297 Single-cell RNA-seq highlights intra-tumoral heterogeneity and malignant progression in pancreatic ductal adenocarcinoma. Cell Research 10.1038/s41422-019-0195-y 2019
33819739 Single-cell RNA-seq reveals dynamic change in tumor microenvironment during pancreatic ductal adenocarcinoma malignant progression EBioMedicine 10.1016/j.ebiom.2021.103315 2021
35319989 Radiotherapy orchestrates natural killer cell dependent antitumor immune responses through CXCL8 Science Advances 10.1126/sciadv.abh4050 2022
33544846 SPOTlight: seeded NMF regression to deconvolute spatial transcriptomics spots with single-cell transcriptomes Nucleic Acids Research 10.1093/nar/gkab043 2021
36864399 Integrated transcriptional analysis reveals macrophage heterogeneity and macrophage-tumor cell interactions in the progression of pancreatic ductal adenocarcinoma BMC Cancer 10.1186/s12885-023-10675-y 2023
Grants
Agency program Grant ID Grant title
National Natural Science Foundation of China (NSFC) 31625016
National Natural Science Foundation of China (NSFC) 81672443
National Natural Science Foundation of China (NSFC) 81773292
Chinese Academy of Medical Sciences (CAMS) Initiative for Innovative Medicine 2017I2M1001
Ministry of Science and Technology of the People's Republic of China (MOST) National Key R&D Program of China 2018YFA0109700
Chinese Academy of Sciences (CAS) Strategic Priority Research Program of Chinese Academy of Sciences (CAS) XDA16010501
Submitter sun    baofa  (sunbf@big.ac.cn)
Organization Beijing Institute of Genomics, Chinese Academy of Sciences
Submission date 2018-10-12

Project Data

Resource name Description
BioSample (35)  show -
GSA (1) -
CRA001160 GSA-PDAC