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Prognostic significance and immune infiltration of microenvironment-related signatures in pancreatic cancer
Pancreatic ductal adenocarcinoma (PDAC) is 1 of the highly fatal and most aggressive types of malignancies and accounts for the vast majority of Pancreatic Cancer. Numerous studies have reported that the tumor microenvironment (TME) was significantly correlated with the oncogenesis, progress, and pr...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9282111/ https://www.ncbi.nlm.nih.gov/pubmed/33761652 http://dx.doi.org/10.1097/MD.0000000000024957 |
Sumario: | Pancreatic ductal adenocarcinoma (PDAC) is 1 of the highly fatal and most aggressive types of malignancies and accounts for the vast majority of Pancreatic Cancer. Numerous studies have reported that the tumor microenvironment (TME) was significantly correlated with the oncogenesis, progress, and prognosis of various malignancies. Therefore, mining of TME-related genes is reasonably important to improve the overall survival of patients with PDAC. The Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm was applied to identify differential expressed genes. Functional and pathway enrichment analyses, protein–protein interaction network construction and module analysis, overall survival analysis and tumor immune estimation resource database analysis were then performed on differential expressed genes. Data analysis indicated that higher immune scores were correlated with better overall survival (P = 0.033). Differential expression analysis obtained 90 intersection genes influencing both stromal and immune scores. Among these intersection genes, CA9, EBI3, SPOCK2, WDFY4, CD1D, and CCL22 were significantly correlated with overall survival in PDAC patients. Moreover, multivariate Cox analysis revealed that CA9, SPOCK2, and CD1D were the most significant prognostic genes, and were closely correlated with immune infiltration in TCGA cohort. Further analysis indicated that CD1D were significantly related with immune cell biomarkers for PDAC patients. In summary, our findings provide a more comprehensive insight into TME and show a list of prognostic immune associated genes in PDAC. However, further studies on these genes need to be performed to gain additional understanding of the association between TME and prognosis in PDAC. |
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