Mitochondrial energy metabolism-related gene signature as a prognostic indicator for pancreatic adenocarcinoma

Background: Pancreatic adenocarcinoma (PAAD) is a highly malignant gastrointestinal tumor and is associated with an unfavorable prognosis worldwide. Considering the effect of mitochondrial metabolism on the prognosis of pancreatic cancer has rarely been investigated, we aimed to establish prognostic...

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Main Authors: Yu Ma (Author), Ronghao Tang (Author), Peilin Huang (Author), Danhua Li (Author), Meijian Liao (Author), Shoucui Gao (Author)
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Published: Frontiers Media S.A., 2024-03-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Yu Ma  |e author 
700 1 0 |a Ronghao Tang  |e author 
700 1 0 |a Peilin Huang  |e author 
700 1 0 |a Danhua Li  |e author 
700 1 0 |a Meijian Liao  |e author 
700 1 0 |a Shoucui Gao  |e author 
245 0 0 |a Mitochondrial energy metabolism-related gene signature as a prognostic indicator for pancreatic adenocarcinoma 
260 |b Frontiers Media S.A.,   |c 2024-03-01T00:00:00Z. 
500 |a 1663-9812 
500 |a 10.3389/fphar.2024.1332042 
520 |a Background: Pancreatic adenocarcinoma (PAAD) is a highly malignant gastrointestinal tumor and is associated with an unfavorable prognosis worldwide. Considering the effect of mitochondrial metabolism on the prognosis of pancreatic cancer has rarely been investigated, we aimed to establish prognostic gene markers associated with mitochondrial energy metabolism for the prediction of survival probability in patients with PAAD.Methods: Gene expression data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases, and the mitochondrial energy metabolism-related genes were obtained from the GeneCards database. Based on mitochondrial energy metabolism score (MMs), differentially expressed MMRGs were established for MMs-high and MMs-low groups using ssGSEA. After the univariate Cox and least absolute and selection operator (LASSO) analyses, a prognostic MMRG signature was used in the multivariate Cox proportional regression model. Survival and immune cell infiltration analyses were performed. In addition, a nomogram based on the risk model was used to predict the survival probability of patients with PAAD. Finally, the expression of key genes was verified using quantitative polymerase chain reaction and immunohistochemical staining. Intro cell experiments were performed to evaluated the proliferation and invasion of pancreatic cancer cells.Results: A prognostic signature was constructed consisting of two mitochondrial energy metabolism-related genes (MMP11, COL10A1). Calibration and receiver operating characteristic (ROC) curves verified the good predictability performance of the risk model for the survival rate of patients with PAAD. Finally, immune-related analysis explained the differences in immune status between the two subgroups based on the risk model. The high-risk score group showed higher estimate, immune, and stromal scores, expression of eight checkpoint genes, and infiltration of M0 macrophages, which might indicate a beneficial response to immunotherapy. The qPCR results confirmed high expression of MMP11 in pancreatic cancer cell lines, and IHC also verified high expression of MMP11 in clinical pancreatic ductal adenocarcinoma tissues. In vitro cell experiments also demonstrated the role of MMP11 in cell proliferation and invasion.Conclusion: Our study provides a novel two-prognostic gene signature-based on MMRGs-that accurately predicted the survival of patients with PAAD and could be used for mitochondrial energy metabolism-related therapies in the future. 
546 |a EN 
690 |a pancreatic adenocarcinoma 
690 |a mitochondrial energy metabolism 
690 |a prognostic signature 
690 |a bioinformatics 
690 |a immune 
690 |a Therapeutics. Pharmacology 
690 |a RM1-950 
655 7 |a article  |2 local 
786 0 |n Frontiers in Pharmacology, Vol 15 (2024) 
787 0 |n https://www.frontiersin.org/articles/10.3389/fphar.2024.1332042/full 
787 0 |n https://doaj.org/toc/1663-9812 
856 4 1 |u https://doaj.org/article/f1f77ab2e2044bd0a7dd7a3a99a935c0  |z Connect to this object online.