Single-cell RNA-seq reveals invasive trajectory and determines cancer stem cell-related prognostic genes in pancreatic cancer

ABSTRACT

Pancreatic duct adenocarcinoma (PDAC) is an aggressive and lethal malignancy. Pancreatic cancer stem cells (PCSCs) are assumed to contribute to the initiation and invasion of PDAC. In this study, we performed single-cell RNA sequencing (scRNA-seq) analysis of PDAC tumor samples from patients and control pancreas tissues to reveal the transformation process of cancer stem cell (CSC)-like ductal cells into ductal cells with invasive potential and we screened out CSC-related genes (CRGs). Subsequently, we applied LASSO and Cox regression models to identify five CRGs with potential prognostic values and constructed a risk prognostic model using the Cancer Genome Atlas datasets. The risk models were verified using Gene Expression Omnibus datasets. Patients in the high-risk group had a significantly poor overall survival (Pvalue<0.0001), as illustrated by the Kaplan-Meier survival curve, and the area under the curve confirmed the accuracy of predictions by our risk model. Tumor mutation burden variations were used to further explore the differences between the two risk cohorts. In addition, the Human Protein Atlas was used to investigate the protein expression of five hub CRGs. In brief, we utilized scRNA-seq to reveal the invasive trajectory of ductal cells and identified crucial CRGs in PDAC, which may help predict patient survival and provide potential clinical therapeutic targets against CSCs.

Graphical abstract

KEYWORDS:

• Pancreatic cancer
• scRNA-seq
• cancer stem cell
• survival prognosis

Acknowledgements

In this study, we thank the Cancer Genome Atlas (TCGA) Database, Gene Expression Omnibus (GEO), Biological Project Libraryfor providing data support.

Disclosure statement

All authors declared no conflict of interest..

Data availability statement

The datasets analyzed was acquired from The Cancer Genome Atlas (TCGA) database(https://portal.gdc.cancer.gov/), Gene Expression Omnibus (GEO) database(https://www.ncbi.nlm.nih.gov/geo/) and Biological Project Library(https://bigd.big.ac.cn/bioproject/browse/PRJCA001063).

Highlights

(1) ScRNA-seq reveals heterogeneity and invasion trajectory of ductal cells in PDAC

(2) The expression levels of CRGs correlate with the prognosis of PDAC

(3) CRGs have been demonstrated to possess independent prognosis-predictive values for PDAC

(4) CRGs are closely related to variations in tumor mutation burden

Authors’ contributions

Study conception and design: XR and CZ; Data acquisition and analysis: XR and FM; Data visualization: YL and YF; manuscript writing and manuscript editing: XR; manuscript reviewing: CW; All authors approved the final version of the paper.

Citation

[1] Li X, Liao Z, Deng Z, Chen N, Zhao L. Combining bulk and single-cell RNA-sequencing data to reveal gene expression pattern of chondrocytes in the osteoarthritic knee. Bioengineered 2021; 12:997-1007.

Compared with them, we used single-cell sequencing analysis to reveal the invasion trajectory of pancreatic cancer ductal cells for the first time, and proposed prognostic genes related to cancer stem cells.

Additional information

Funding

This work is supported by the Technology Major Project of the Gansu Provincial Science and Technology Department (NO.19ZD2WA001).