Dataset Information

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy.

ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished 'classical' from 'basal-like' tumors with more aggressive clinical behavior. We derive PDAC organoids from 18 primary tumors and two matched liver metastases, and show that 'classical' and 'basal-like' cells coexist in individual organoids. By single-cell transcriptome analysis of PDAC organoids and primary PDAC, we identify distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. Cell states are connected by a differentiation hierarchy, with 'classical' cells concentrated at the endpoint. In an imaging-based drug screen, expression of 'classical' subtype genes correlates with better drug response. Our results thus uncover a functional hierarchy of PDAC cell states linked to transcriptional tumor subtypes, and support the use of PDAC organoids as a clinically relevant model for in vitro studies of tumor heterogeneity.

SUBMITTER: Krieger TG

PROVIDER: S-EPMC8492851 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy.

Krieger Teresa G TG Le Blanc Solange S Jabs Julia J Ten Foo Wei FW Ishaque Naveed N Jechow Katharina K Debnath Olivia O Leonhardt Carl-Stephan CS Giri Anamika A Eils Roland R Strobel Oliver O Conrad Christian C

Nature communications 20211005 1

Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished 'classical' from 'basal-like' tumors with more aggressive clinical behavior. We derive PDAC organoids from 18 primary tumors and two matched liver metastases, and show that 'classical' and 'basal-like' cells coexist in individual organoids. By single-cell transcriptome analysis of PDAC organoids and primary PDAC, we identify distinct tum ...[more]

PMID: 34611171

Similar Datasets

Project description:BackgroundFragmentomics, the investigation of fragmentation patterns of cell-free DNA (cfDNA), has emerged as a promising strategy for the early detection of multiple cancers in the field of liquid biopsy. However, the clinical application of this approach has been hindered by a limited understanding of cfDNA biology. Furthermore, the prevalence of hematopoietic cell-derived cfDNA in plasma complicates the in vivo investigation of tissue-specific cfDNA other than that of hematopoietic origin. While conventional two-dimensional cell lines have contributed to research on cfDNA biology, their limited representation of in vivo tissue contexts underscores the need for more robust models. In this study, we propose three-dimensional organoids as a novel in vitro model for studying cfDNA biology, focusing on multifaceted fragmentomic analyses.ResultsWe established nine patient-derived organoid lines from normal lung airway, normal gastric, and gastric cancer tissues. We then extracted cfDNA from the culture medium of these organoids in both proliferative and apoptotic states. Using whole-genome sequencing data from cfDNA, we analyzed various fragmentomic features, including fragment size, footprints, end motifs, and repeat types at the end. The distribution of cfDNA fragment sizes in organoids, especially in apoptosis samples, was similar to that found in plasma, implying occupancy by mononucleosomes. The footprints determined by sequencing depth exhibited distinct patterns depending on fragment sizes, reflecting occupancy by a variety of DNA-binding proteins. Notably, we discovered that short fragments (< 118 bp) were exclusively enriched in the proliferative state and exhibited distinct fragmentomic profiles, characterized by 3 bp palindromic end motifs and specific repeats.ConclusionsIn conclusion, our results highlight the utility of in vitro organoid models as a valuable tool for studying cfDNA biology and its associated fragmentation patterns. This, in turn, will pave the way for further enhancements in noninvasive cancer detection methodologies based on fragmentomics.

Dataset Information

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy.

Publications

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets