Fig 1.
The expression level of RRM2 in pan-cancer.
(A) The expression level of RRM2 in different pan-cancers as indicated in the Oncomine database. Gene rank percentile (%). (B) RRM2 differential expression in pan-cancer in the TCGA database. *P < 0.05; **P < 0.01; ***P < 0.001.
Fig 2.
The expression level of RRM2 and its clinical correlation in pan-cancer.
(A-D) The clinical correlation between RRM2 expression level and age in BRCA, ESCA KICH, and KIRC, respectively. (E-H) The clinical correlation between RRM2 expression level and race in BLCA, BRCA, KICH, and KIRC, respectively. (I-L) The clinical correlation between RRM2 expression level and tumor stage of patients in ACC, BRCA, COAD, and KICH, respectively. (M-P) The clinical correlation between RRM2 expression level and tumor status of patients in ACC, BLCA, COAD, and KICH, respectively. The number above the horizontal line represents the p-value between the two groups.
Fig 3.
Prognostic value of RRM2 in pan-cancer.
(A-E) Correlation between high expression level of RRM2 and poor OS in ACC, KICH, KIRC, KIRP, and LGG using the Kaplan–Meier method. (F-J) Correlation between high expression level of RRM2 and poor DSS in ACC, KICH, KIRC, KIRP, and LGG using the Kaplan–Meier method. (K-O) Correlation between high expression level of RRM2 and poor DFI in KIRP, LIHC, LUAD, PAAD, and SARC using the Kaplan–Meier method. (P-T) Correlation between high expression level of RRM2 and poor PFI in ACC, KICH, KIRC, KIRP, and LGG using the Kaplan–Meier method. (U-X) Correlation between RRM2 expression and OS, DSS, DFI, and PFI in pan-cancer using the Cox regression model. OS, Overall survival (years); DSS, Disease-specific survival (years); DFI, Disease-free interval (years); PFI, Progression-free interval (years).
Fig 4.
Mutation features of RRM2 in different tumors of TCGA.
(A, B) The alteration frequency of RRM2 with mutation type and mutation site. (C) The mutation site with the highest alteration frequency (R298Q/W) in the 3D structure of RRM2. (D) A radar map was used to reflect the correlation between RRM2 expression and TMB. (E) A radar map was used to reflect the correlation between RRM2 expression and MSI. TMB, Tumor mutational burden; MSI, Microsatellite instability.
Fig 5.
Correlation analysis between RRM2 expression and immune infiltration of cancer-associated cells.
(A) The correlation between RRM2 gene expression and the infiltration level of endothelial cells in all types of cancer in TCGA. (B-Q) The correlation between RRM2 gene expression and the infiltration level of diverse immune cells in ACC, BLCA, and BRCA, respectively.
Fig 6.
RRM2 expression level and immune checkpoint genes in pan-cancer.
(A) Heatmap of the correlation between RRM2 expression and immune checkpoint genes.
Fig 7.
RRM2-related gene enrichment analysis.
(A) Protein-protein interaction network of the available experimentally determined RRM2 binding proteins. The size and color of the node depends on the degree. The width of the edge is determined by the combined score of STRING. (B) The expression correlation between RRM2 and the top 5 RRM2-correlated genes in TCGA, including MKI67, ORC1, CCNA2, PLK1 and KIF11. (C) The corresponding heatmap data for the detailed cancer types. (D) An intersection analysis of the RRM2-binding and correlated genes. (E) KEGG pathway enrichment analyses of the genes that RRM2-binding and interacted.