ReviewBioscience reports2022
Identify potential prognostic indicators and tumor-infiltrating immune cells in pancreatic adenocarcinoma.
Review in Bioscience reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 19 citations in OpenAlex.
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- Neutrophil Extracellular Traps Promote Pancreatic Cancer Progression via the STING Pathway.Gastroenterology research and practice · 2025Article
- TRIM28 Fosters Microglia Ferroptosis via Autophagy Modulation to Enhance Neuropathic Pain and Neuroinflammation.Molecular neurobiology · 2024Article
- Uncovering Tumor-Promoting Roles of Activin A in Pancreatic Ductal Adenocarcinoma.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- A prognostic signature based on seven T-cell-related cell clustering genes in bladder urothelial carcinoma.Open medicine (Warsaw, Poland) · 2023Article
- PANoptosis-related molecular subtype and prognostic model associated with the immune microenvironment and individualized therapy in pancreatic cancer.Frontiers in oncology · 2023Article
- A Prognostic Model Based on NSUN3 Was Established to Evaluate the Prognosis and Response to Immunotherapy in Liver Hepatocellular Carcinoma.Mediators of inflammation · 2023Article
- Molecular mechanisms of the antibacterial activity of polyimide fibers in a skin-wound model with Gram-positive and Gram-negative bacterial infectionNanoscale advances · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPancreatic adenocarcinoma (PAAD) is a kind of highly malignant tumor and lacks early diagnosis method and effective treatment. Tumor microenvironment (TME) is of great importance for the occurrence and development of PAAD. Thus, a comprehensive overview of genes and tumor-infiltrating immune cells (TICs) related to TME dynamic changes conduce to develop novel therapeutic targets and prognostic indicators.
methodsWe used MAlignant Tumors using Expression data (ESTIMATE) algorithm to analyze the transcriptome RNA-seq data of 182 PAAD cases on The Cancer Genome Atlas (TCGA) platform. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI) network, COX regression analysis and gene set enrichment analysis (GSEA) were carried out to get the hub genes related to the prognosis of PAAD patients. These core genes were validated in GEPIA. CXCL10 expression as a poor prognostic indicator was validated in GEO database. Finally, CIBERSORT algorithm was applied to understand the status of TICs.
resultsA total of 715 up-regulated differential expression genes (DEGs) and 57 down-regulated DEGs were found simultaneously in stromal and immune groups. These DEGs were mainly enriched in immune recognition, activation and response processes. CD4, CXCL12, CXCL10, CCL5 and CXCL9 were the top five core genes. Then, the validation of these genes showed that CD4, CXCL10, CXCL5, CXCL9 were up-regulated in PAAD. Among the core genes, CXCL10 had a negative correlation with the survival time of PAAD patients. CD8+ T cells, CD4+ T cells memory activated, macrophages M1 had positive correlation of CXCL10 expression, whereas regulatory T cells (Tregs), macrophages M0 and B cells memory had negative correlation.
conclusionWe generated a series of genes related to TME with prognostic implications and TICs in PAAD, which have the potential to be novel immunotherapy targets and prognostic markers. The data showed that CXCL10 was favorable as a poor prognostic indicator in PAAD patients.
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