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.

Highlights

  • Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors with a 5-year survival rate of 8% according to annual cancer statistical reports [1, 2]

  • This single-cell study will contribute novel insight into Copy-number alterations in PDACs cellular landscape for deciphering intra-tumoral heterogeneity To distinguish malignant cells, we calculated and identified largeand understanding the molecular mechanism in tumor metas- scale chromosomal copy number variation (CNV) by inferCNV for tasis, with valuable significance for therapeutic management each sample based on transcriptomes [20]

  • Since Epithelial-Mesenchymal Transformation (EMT)+ cancer cell subpopulations were correlated with poorer patient prognosis and more aggressive disease [23], our findings suggested pivotal roles of type 5 ductal cells for distant metastasis in PDAC

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Summary

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors with a 5-year survival rate of 8% according to annual cancer statistical reports [1, 2]. Singe cell RNA-sequencing analysis was employed to present a comprehensive landscape of the transcriptomic profiles of 6236 qualified single cells from 5 liver metastatic PDAC lesions, further dissecting intra-tumoral heterogeneity and identify crucial factors during PDAC metastatic progression. Metastasis-related genes expression and signaling pathways were further confirmed in bulk RNA Sequencing data. This single-cell study will contribute novel insight into Copy-number alterations in PDACs cellular landscape for deciphering intra-tumoral heterogeneity To distinguish malignant cells, we calculated and identified largeand understanding the molecular mechanism in tumor metas- scale chromosomal copy number variation (CNV) by inferCNV for tasis, with valuable significance for therapeutic management each sample based on transcriptomes [20].

RESULTS
CONCLUSIONS
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MATERIALS AND METHODS
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