High expression of RNF169 is associated with poor prognosis in pancreatic adenocarcinoma by regulating tumour immune infiltration

Abstract

Background: Pancreatic adenocarcinoma (PAAD) is a highly deadly and aggressive tumour with a poor prognosis. However, the prognostic value of RNF169 and its related mechanisms in PAAD have not been elucidated. In this study, we aimed to explore prognosis-related genes, especially RNF169 in PAAD and to identify novel potential prognostic predictors of PAAD. Methods: The GEPIA and UALCAN databases were used to investigate the expression and prognostic value of RNF169 in PAAD. The correlation between RNF169 expression and immune infiltration was determined by using TIMER and TISIDB. Correlation analysis with starBase was performed to identify a potential regulatory axis of lncRNA-miRNA-RNF169. Results: The data showed that the level of RNF169 mRNA expression in PAAD tissues was higher than that in normal tissues. High RNF169 expression was correlated with poor prognosis in PAAD. In addition, analysis with the TISIDB and TIMER databases revealed that RNF169 expression was positively correlated with tumour immune infiltration in PAAD. Correlation analysis suggested that the long non-coding RNA (lncRNA) AL049555.1 and the microRNA (miRNA) hsa-miR-324-5p were involved in the expression of RNF169, composing a potential regulatory axis to control the progression of PAAD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses indicated that RNF169 plays a role in PAAD through pathways such as TNF, Hippo, JAK-STAT and Toll-like receptor signaling. Conclusion: In summary, the upregulation of RNF169 expression mediated by ncRNAs might influence immune cell infiltration in the microenvironment; thus, it can be used as a prognostic biomarker and a potential therapeutic target in PAAD.

Keywords: bioinformatics; non-coding RNA; pancreatic adenocarcinoma; ring finger protein 169; tumour immune infiltration.

FIGURE 1

Differential expression of RNF169 in cancer and normal tissues. (A–J) RNF169 expression in 10 different types of human cancers in the GEPIA database, including CHOL (A), LAML (B), LGG (C), STAD (D), PAAD (E), UCEC (F), UCS (G), BRCA (H), THCA (I) and BLCA (J),and in comparison with adjacent normal tissues. (*p < .05, **p < .01, ***p < .001). (K,L) Representative immunohistochemical staining of RNF169 in PAAD and tumor-adjacent tissues. Immunohistochemical staining for RNF169 was performed in PAAD (K) and tumor-adjacent tissues (L).

FIGURE 2

Survival analyses of patients with different cancers with high or low RNF169 expression. (A–G) The overall survival (OS) plot of patients with high or low RNF169 expression in PAAD (A), CHOL (B), LAML (C), LGG (D), STAD (E), UCEC (F) and UCS (G). (H–N) Disease-free survival (RFS) analysis for patients with high or low RNF169 expression in different cancers, i.e., PAAD (H), CHOL (I), LAML (J), LGG (K), STAD (L), UCEC (M) and UCS (N). (O) Correlation of tumour progression with RNF169 mRNA expression in PAAD patients from the GEPIA database.

FIGURE 3

Correlation of RNF169 expression with cytokines, chemokines, chemokine receptors in PAAD. (A–D) The correlation of RNF169 expression with various cytokines. (E–J) The correlation of RNF169 expression with various chemokines. (K–P) The correlation of RNF169 expression with chemokine receptors.

FIGURE 4

Correlation of RNF169 expression with different infiltrated immune cells in PAAD. (A–C) Correlation of RNF169 expression with the number of activated CD8⁺ T cells (A), central memory CD8⁺ T cells (B) and effector memory CD8⁺ T cells (C) in PAAD from the TISIDB database. (D–F) Correlations of RNF169 expression with the number of activated CD4⁺ T cells (D), central memory CD4⁺ T cells (E) and effector memory CD4⁺ T cells (F) in PAAD. (G–I) Correlations of RNF169 expression with the number of activated B cells (G), immature B cells (H) and memory B cells (I) in PAAD. (J) Relationship between RNF169 expression and tumour purity in PAAD from the TIMER database. (K–P) Correlations of RNF169 expression with the number of different infiltrated immune cells, including B cells (K), CD8⁺ T cells (L), CD4⁺ T cells (M), macrophages (N), neutrophils (O) and dendritic cells (P), in PAAD from the TIMER database. (Q) Effect of RNF169 CNV on the infiltration of B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils and dendritic cells in PAAD.

FIGURE 5

Correlations of RNF169 expression with biomarkers of different immune cells. Correlation analysis of RNF169 expression with different immune cell biomarkers was performed with the GEPIA database. (A,B) Correlations of RNF169 expression with the CD8⁺ T cell biomarkers CD8A (A) and CD8B (B). (C) Correlations of RNF169 expression with the costimulatory molecule CD86. (D,E) Correlations of RNF169 expression with the M1 macrophage biomarkers IRF5 (D) and PTGS2 (E). (F–H) Correlations of RNF169 expression with the M2 macrophage biomarkers CD163 (F), VSIG4 (G) and MS4A4A (H). (I) Correlations of RNF169 expression with the neutrophil biomarker ITGAM. (J–O) Correlations of RNF169 expression with the dendritic cell biomarkers HLA-DPB1 (J), HLA-DRA (K), HLA-DPA1 (L), CD1C (M), NRP1 (N) and ITGAX (O) in PAAD.

FIGURE 6

Correlation of RNF169 with the expression of CTLA4 or CD274 in PAAD. (A,B) The correlation of RNF169 with CTLA4 in PAAD was analysed by using the GEPIA (A) and TIMER (B) databases. (C,D) The correlation of RNF169 with CD274 in PAAD was analysed by using the GEPIA (C) and TIMER (D) databases.

FIGURE 7

Correlation of RNF169 with the expression of differentially expressed genes in PAAD. (A) Volcano plots showing the differentially expressed genes in PAAD. (B–D) Negative correlation of RNF169 with three representative DEGs, i.e., NDUFA11 (B), RABAC1 (C) and NDUFB7 (D), in PAAD. (E–H) Positive correlation of RNF169 with four representative DEGs, i.e., REST (E), RSF1 (F), STRN (G), RIF1 (H), in PAAD. (I) KEGG pathway analysis of DEGs in PAAD. (J–L) GO term enrichment of biological processes (J), molecular functions (K) and cellular components (L) was analysed by GSEA.

FIGURE 8

Identification of potential miRNAs associated with the prognosis of PAAD. (A) Identification of potential miRNAs targeting the RNF169 gene in the miRWalk and TargetScan databases. (B) Expression of hsa-miR-324-5p in PAAD and adjacent normal tissues. (C) Prognostic value of hsa-miR-324-5p for PAAD patients.

FIGURE 9

Validation of lncRNA AL049555.1 expression and its prognostic value in PAAD from the StarBase database. (A) The potential hsa-miR-324-5p-regulated lncRNA network constructed by Cytoscape. (B) Expression of lncRNA AL049555.1 in PAAD and adjacent normal tissues. (C) Prognostic value of lncRNA AL049555.1 for PAAD patients. (D) Coexpression analysis of RNF169 with the lncRNA AL049555.1 in PAAD patients. (E) Coexpression analysis of hsa-miR-324-5p with the lncRNA AL049555.1.