Single-cell RNA transcriptome reveals the intra-tumoral heterogeneity and regulators underlying tumor progression in metastatic pancreatic ductal adenocarcinoma

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is the most frequent and aggressive pancreatic tumor characterized by high metastatic risk and special tumor microenvironment. To comprehensively delineate the complex intra-tumoral heterogeneity and the underlying mechanism during metastatic lesions malignant progression, single-cell RNA sequencing (scRNA-seq) was employed. PCA and TSNE were used for dimensionality reduction analysis and cell clustering. Find All Markers function was used to calculate differential genes in each cluster, and Do Heatmap function was used to plot the distribution of differential genes in each cluster. GSVA was employed to assign pathway activity estimates to individual cells. Lineage trajectory progression was inferred by monocle. CNV status was inferred to compare the heterogeneity among patients and subtypes by infercnv. Ligand-receptor interactions were identified by CellPhoneDB, and regulons network of cells was analyzed by SCENIC. Through RNA-sequencing of 6236 individual cells from 5 liver metastatic PDAC lesions, 10 major cell clusters are identified by using unbiased clustering analysis of expression profiling and well-known cell markers. Cells with high CNV level were considered as malignant cells and pathway analyses were carried out to highlight intratumor heterogeneity in PDAC. Pseudotime trajectory analysis revealed that components of multiple tumor-related pathways and transcription factors (TFs) were differentially expressed along PDAC progression. The complex cellular communication suggested potential immunotherapeutic targets in PDAC. Regulon network identified multiple candidates for promising cell-specific transcriptional factors. Finally, metastatic-related genes expression levels and signaling pathways were validated in bulk RNA Sequencing data. This study contributed a comprehensive single-cell transcriptome atlas and contributed into novel insight of intratumor heterogeneity and molecular mechanism in metastatic PDAC.

Gene Coexpression Network Characterizing Microenvironmental Heterogeneity and Intercellular Communication in Pancreatic Ductal Adenocarcinoma: Implications of Prognostic Significance and Therapeutic Target

“…These molecules form a ligand–receptor web, guiding the crosstalk between cancer cells and nontumoral cells ( Figures 5D, E ). Unlike other single-cell studies in pancreatic cancer that analyze general ligand–receptor–directed cell interactions ( 19 , 48 , 49 ), we focused on intercellular crosstalk directed by the hub genes within coexpression networks. Under this prerequisite, the main participators in the network were fibroblasts and endothelial cells, which are frequently connected to tumor cells.…”

Single Cell RNA Sequencing: A New Frontier in Pancreatic Ductal Adenocarcinoma

“…Xu et al have shown the utility of scRNA-seq in characterizing tumor heterogeneity in liver metastases from PDAC [ 45 ]. Their analysis identified multiple lineages of cancer cells within metastatic lesions, including five different types of ductal cells, and temporal trajectory mapping for cell lineage evolution was performed to elucidate the origins of cells within the metastatic lesions under investigation, highlighting the role that scRNA-seq has in predicting the composition of metastatic lesions or primary PDAC when tissue is only available from one source, as well as investigating the driver mutations behind neoplastic progression and dissemination.…”

LAMC2 marks a tumor-initiating cell population with an aggressive signature in pancreatic cancer

“…Graphs were designed with the Seurat package in R as previously described. The ductal signature was clustered according to a 9-genes score identified in Xu et al, [ 28 ]. To analyze Moffitt subtypes, cells from each patient were clustered using the FindClusters function in Seurat with a resolution of 0.5.…”