Single-Cell Transcriptome Reveals the Metabolic and Clinical Features of a Highly Malignant Cell Subpopulation in Pancreatic Ductal Adenocarcinoma

Yangyang Fang; Shunjie Pei; Kaizhao Huang; Feng Xu; Guangxin Xiang; Linhua Lan; Xiaoqun Zheng

doi:10.3389/fcell.2022.798165

Single-Cell Transcriptome Reveals the Metabolic and Clinical Features of a Highly Malignant Cell Subpopulation in Pancreatic Ductal Adenocarcinoma

Front Cell Dev Biol. 2022 Feb 18:10:798165. doi: 10.3389/fcell.2022.798165. eCollection 2022.

Authors

Yangyang Fang^{1

2

3}, Shunjie Pei^{1

2

3}, Kaizhao Huang¹, Feng Xu^{2

3}, Guangxin Xiang^{2

3}, Linhua Lan⁴, Xiaoqun Zheng^{1

2

3}

Affiliations

¹ Department of Laboratory Medicine, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
² School of Laboratory Medical and Life Science, Wenzhou Medical University, Wenzhou, China.
³ Key Laboratory of Laboratory Medicine, School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou, China.
⁴ Key Laboratory of Diagnosis and Treatment of Severe Hepato-Pancreatic Diseases of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

Abstract

Background: Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with a high mortality rate. PDAC exhibits significant heterogeneity as well as alterations in metabolic pathways that are associated with its malignant progression. In this study, we explored the metabolic and clinical features of a highly malignant subgroup of PDAC based on single-cell transcriptome technology. Methods: A highly malignant cell subpopulation was identified at single-cell resolution based on the expression of malignant genes. The metabolic landscape of different cell types was analyzed based on metabolic pathway gene sets. In vitro experiments to verify the biological functions of the marker genes were performed. PDAC patient subgroups with highly malignant cell subpopulations were distinguished according to five glycolytic marker genes. Five glycolytic highly malignant-related gene signatures were used to construct the glycolytic highly malignant-related genes signature (GHS) scores. Results: This study identified a highly malignant tumor cell subpopulation from the single-cell RNA sequencing (scRNA-seq) data. The analysis of the metabolic pathway revealed that highly malignant cells had an abnormally active metabolism, and enhanced glycolysis was a major metabolic feature. Five glycolytic marker genes that accounted for the highly malignant cell subpopulations were identified, namely, EN O 1, LDHA, PKM, PGK1, and PGM1. An in vitro cell experiment showed that proliferation rates of PANC-1 and CFPAC-1 cell lines decreased after knockdown of these five genes. Patients with metabolic profiles of highly malignant cell subpopulations exhibit clinical features of higher mortality, higher mutational burden, and immune deserts. The GHS score evaluated using the five marker genes was an independent prognostic factor for patients with PDAC. Conclusion: We revealed a subpopulation of highly malignant cells in PDAC with enhanced glycolysis as the main metabolic feature. We obtained five glycolytic marker gene signatures, which could be used to identify PDAC patient subgroups with highly malignant cell subpopulations, and proposed a GHS prognostic score.

Keywords: glycolysis; malignant; pancreatic ductal adenocarcinoma; single-cell transcriptome; tumor metabolic.