ArticleAging2020
The value of a metabolic reprogramming-related gene signature for pancreatic adenocarcinoma prognosis prediction.
Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 45 citations in OpenAlex.
- Comprehensive analysis of metabolic reprogramming-related gene signatures for predicting ovarian cancer prognosis, the immune landscape, and potential treatment options.Discover oncology · 2026Article
- Novel lipid metabolism-related gene signature associated with clinical and immune features in lung adenocarcinoma patients experiencing lymph node metastasis.Translational lung cancer research · 2026Article
- Integrated machine learning survival framework for consensus modeling in a large multicenter cohort of NSCLC resistant to aumolertinib.Scientific reports · 2025Article
- The role of RAB GTPases in predicting prognosis and therapy response in pancreatic cancer.Discover oncology · 2025Article
- Improving molecular subtypes and prognosis of pancreatic cancer through multi group analysis and machine learning.Discover oncology · 2025Article
- Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas.Journal of translational medicine · 2024Article
- BeyondMolecular therapy oncolytics · 2023Review
- Integrating somatic mutation profiles with structural deep clustering network for metabolic stratification in pancreatic cancer: a comprehensive analysis of prognostic and genomic landscapes.Briefings in bioinformatics · 2023Article
- Review
- Identification of a hypoxia-related gene prognostic signature in colorectal cancer based on bulk and single-cell RNA-seq.Scientific reports · 2023Article
- A prognostic 15-gene model based on differentially expressed genes among metabolic subtypes in diffuse large B-cell lymphoma.Pathology oncology research : POR · 2023Article
- Article
- Article
- Screening for Potential Therapeutic Agents for Non-Small Cell Lung Cancer by Targeting Ferroptosis.Frontiers in molecular biosciences · 2022Article
- The expression of mGland surgery · 2022Article
- Development and validation of a hypoxia-stemness-based prognostic signature in pancreatic adenocarcinoma.Frontiers in pharmacology · 2022Article
- ENO3 Inhibits Growth and Metastasis of Hepatocellular CarcinomaFrontiers in cell and developmental biology · 2021Article
- Prognostic Value and Correlation With Tumor Immune Infiltration of a Novel Metabolism-Related Gene Signature in Pancreatic Cancer.Frontiers in oncology · 2021Article
- A Novel Ferroptosis-Related Gene Signature Predicts Recurrence in Patients With Pancreatic Ductal Adenocarcinoma.Frontiers in molecular biosciences · 2021Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. Extensive enhancement of glycolysis and reprogramming of lipid metabolism are both associated with the development and progression of PDAC. Previous studies have suggested that various gene signatures could convey prognostic information about PDAC. However, the use of these signatures has some limitations, perhaps because of a lack of knowledge regarding the genetic and energy supply backgrounds of PDAC. Therefore, we conducted multi-mRNA analysis based on metabolic reprogramming to identify novel signatures for accurate prognosis prediction in PDAC patients. In this study, a three-gene signature comprising MET, ENO3 and CD36 was established to predict the overall survival of PDAC patients. The three-gene signature could divide patients into high- and low-risk groups by disparities in overall survival verified by log-rank test in two independent validation cohorts and could differentiate tumors from normal tissues with excellent accuracy in four Gene Expression Omnibus (GEO) cohorts. We also found a positive correlation between the risk score of the gene signature and inherited germline mutations in PDAC predisposition genes. A glycolysis and lipid metabolism-based gene nomogram and corresponding calibration curves showed significant performance for survival prediction in the TCGA-PDAC dataset. The high-risk designation was closely connected with oncological signatures and multiple aggressiveness-related pathways, as determined by gene set enrichment analysis (GSEA). In summary, our study developed a three-gene signature and established a prognostic nomogram that objectively predicted overall survival in PDAC. The findings could provide a reference for the prediction of overall survival and could aid in individualized management for PDAC patients.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.