KRT7 Overexpression is Associated with Poor Prognosis and Immune Cell Infiltration in Patients with Pancreatic Adenocarcinoma

Background: Pancreatic adenocarcinoma (PAAD) is a deadly tumor with a high recurrence rate and poor prognosis. Keratin 7 (KRT7) is a member of the keratin gene family that is involved in the regulation of cell growth, migration and apoptosis in many cancers. However, the role of KRT7 and its biological functions in PAAD remain unclear. We systemically analyzed the expression and clinical values of KRT7 in PAAD. Methods: The Gene Expression Profiling Interactive Analysis (GEPIA), Oncomine and Human Protein Atlas (HPA) databases were used to analyze the mRNA and protein expression of KRT7 in PAAD. The prognosis and subgroup analysis of KRT7 in PAAD patients was performed using the GEPIA, PROGgeneV2 and UALCAN databases. Later, the correlation between KRT7 expression and tumor immune molecules in PAAD was evaluated using the Immune Cell Abundance Identifier (ImmuCellAI) and TISIDB databases. Finally, the functional enrichment pathway of KRT7 and its coexpressed genes were analyzed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID) and Metascape databases and Gene Set Enrichment Analysis (GSEA). Results: The mRNA and protein expression of KRT7 was increased in PAAD tissues compared with normal tissues. High KRT7 expression was closely associated with tumor grade, TP53 mutations and poor prognosis in PAAD patients. Cox regression analysis proved that overexpressed KRT7 was an important and independent risk factor for poor overall survival (P = 0.006, HR =1.87) and disease-free survival (P = 0.019, HR =1.793) in PAAD. Additionally, KRT7 expression was significantly associated with immune infiltration of tumor immune cells and immunomodulators. Functional enrichment analyses and GSEA indicated that KRT7 might be involved in the regulation of the p53 pathway in PAAD. Conclusion: Overexpressed KRT7 could be a promising prognostic and therapeutic target biomarker for PAAD by bioinformatics analysis.