Single-Cell Transcriptome Reveals the Metabolic and Clinical Features of a Highly Malignant Cell Subpopulation in Pancreatic Ductal Adenocarcinoma - Fang, Yangyang; Pei, Shunjie; Huang, Kaizhao; Xu, Feng; Xiang, Guangxin; Lan, Linhua; Zheng, Xiaoqun (Frontiers in Cell and Developmental Biology, 2022)
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. 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 accounted for the high malignant cell subpopulations were identified, namely ENO1, LDHA, PKM, PGK1 and PGM1. In vitro cell experiment showed that proliferation rates of PANC-1 and CFPAC-1 cells 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. Conclusions: We revealed a subpopulation of highly malignant cells in PDAC with enhanced glycolysis as the main metabolic feature. Five glycolytic marker gene signatures, which could identify PDAC patient subgroups with highly malignant cell subpopulation and proposed a GHS prognostic score.