Identification of the Roles of a Stemness Index Based on mRNA Expression in the Prognosis and Metabolic Reprograming of Pancreatic Ductal Adenocarcinoma - Tang, Rong; Liu, Xiaomeng; Wang, Wei; Hua, Jie; Xu, Jin; Liang, Chen; Meng, Qingcai; Liu, Jiang; Zhang, Bo; Yu, Xianjun; Shi, Si (Frontiers in Oncology, 2021)
Background Cancer stem cells (CSCs) are widely thought to contribute to the dismal prognosis of pancreatic ductal adenocarcinoma (PDAC). CSCs share biological features with adult stem cells, such as longevity, self-renewal capacity, differentiation, drug resistance, and the requirement for a niche; these features play a decisive role in cancer progression. A prominent characteristic of PDAC is metabolic reprogramming, which provides sufficient nutrients to support rapid tumor cell growth. However, whether PDAC stemness is correlated with metabolic reprogramming remains unknown. Method RNA sequencing data of PDAC, including read counts and fragments per kilobase of transcript per million mapped reads (FPKM), were collected from The Cancer Genome Atlas-Pancreatic Adenocarcinoma (TCGA-PAAD) database. Single-sample gene set enrichment analysis (GSEA) was used to calculate the relative activities of metabolic pathways in each PDAC sample. Quantitative real-time PCR was performed to validate the expression levels of genes of interest. Results The overall survival (OS) of patients with high mRNA expression-based stemness index (mRNAsi) values was significantly worse than that of their counterparts with low mRNAsi values (P = 0.003). This survival disadvantage was independent of baseline clinical characteristics. Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and GSEA showed that the differentially expressed genes between patients with high and low mRNAsi values were mainly enriched in oncogenic and metabolic pathways. Weighted gene coexpression network analysis (WGCNA) revealed 8 independent gene modules that were significantly associated with mRNAsi and 12 metabolic pathways. Unsupervised clustering based on the key genes in each module identified two PDAC subgroups characterized by different mRNAsi values and metabolic activities. Univariate Cox regression analysis identified 14 genes beneficial to OS from 95 key genes selected from the eight independent gene modules from WGCNA. Among them, MAGEH1, MAP3K3, and PODN were downregulated in both pancreatic tissues and cell lines. Conclusion The present study showed that PDAC samples with high mRNAsi values exhibited aberrant activation of multiple metabolic pathways, and the patients from whom these samples were obtained had a poor prognosis. Future studies are expected to investigate the underlying mechanism based on the crosstalk between PDAC stemness and metabolic rewiring.