ArticleAging2023
Exosome and lipid metabolism-related genes in pancreatic adenocarcinoma: a prognosis analysis.
Article in Aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Bioinformatics Analysis of Genes Associated with Autophagy and Metabolic Reprogramming in Atrial Fibrillation.Journal of cardiovascular development and disease · 2026Article
- Multi-Omic Analysis Reveals a Lipid Metabolism Gene Signature and Predicts Prognosis and Chemotherapy Response in Thyroid Carcinoma.Cancer medicine · 2025Article
- Integrative machine learning and bioinformatics analysis to identify cellular senescence-related genes and potential therapeutic targets in ulcerative colitis and colorectal cancer.Frontiers in bioinformatics · 2025Article
- Identification and validation for biomarkers associated with mitochondrial metabolism in chronic obstructive pulmonary disease.Frontiers in medicine · 2025Article
- SNCA is a potential therapeutic target for COVID-19 infection in diffuse large B-cell lymphoma patients.Apoptosis : an international journal on programmed cell death · 2024Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe purpose of the study was to investigate the role of exosome and lipid metabolism-related genes (EALMRGs) mRNA levels in the diagnosis and prognosis of Pancreatic Adenocarcinoma (PAAD).
methodsThe mRNA expression pattern of PAAD and pan-cancers with prognostic data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. EALMRGs were acquired from GeneCards and MSigDB database after merging and deduplication. Prognostic EALMRGs were screened through univariate COX regression analysis, and a prognostic model was constructed based on these genes by least absolute shrinkage and selection operator (LASSO) regression. The prognostic value of EALMRGs was then validated in pan-cancer data. The time characteristics ROC curve analysis was performed to evaluate the effectiveness of the prognostic genes.
resultsWe identified 5 hub genes (ABCB1, CAP1, EGFR, PPARG, SNCA) according to high and low-risk groups of prognoses. The risk formula was verified in three other cohort of pancreatic cancer patients and was explored in pan-cancer data. Additionally, T cell and dendritic cell infiltration was significantly increased in low-risk group. The expression of the 5 hub genes was also identified in single-cell sequencing data of pancreatic cancer with pivotal pathways. Additionally, functional enrichment analysis based on pancreatic cancer data in pancreatic cancer showed that protein serine/threonine kinase activity, focal adhesion, actin binding, cell-substrate junction, organic acid transport, and regulation of transporter activity were significant related to the expression of genes in EALMRGs.
conclusionsOur risk formula shows potential prognostic value in multiple cancers and manifest pivotal alterations in immune infiltration and biological pathway in pancreatic cancer.
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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.