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Fig. 2 | Cancer Cell International

Fig. 2

From: Construction of a risk prediction model using m6A RNA methylation regulators in prostate cancer: comprehensive bioinformatic analysis and histological validation

Fig. 2

Expression of m6A regulators in relation to different PCa clinicopathological characteristics and prognoses. A–D Distribution of 3–4 representative m6A regulators (3–4 with the lowest P values) in TCGA-PRAD data stratified by GS (A), pT (B), RFS (C), and TP53 mutation (D). The box plots show the median ± interquartile range of values, and P values are presented above each pair of comparisons. E Prognosis network of interactions between m6A regulators in PCa. The P values of each regulator with respect to the prognosis are shown as circles of different sizes. Purple in the right hemisphere: risk factors for RFS; green in the right hemisphere: favorable factors for RFS. The erasers, readers, and writers of the m6A regulator are shown as blue, orange, and red colors, respectively on the left. Positive or negative correlations of m6A regulators are linked with lines of different colors (pink: positive, blue: negative), and the correlation strength between them is shown as different line thicknesses. F Intersecting DEGs of 25 m6A regulators in GS (GS > 7 vs. GS < 7), pT (T3 vs. T2), RFS (P value of univariate Cox regression analysis < 0.05), TN (tumor vs. normal PCa tissues), and TP53 (mutation vs. wild type) are shown as Venn diagrams. G PCa tissues and adjacent normal tissues were divided into four groups according to GS score (15 of normal tissue, 15 of GS < 7, 15 of GS = 7, and 15 of GS > 7). mRNA levels of intersecting genes were compared in different groups of PCa and adjacent normal tissues (PCa vs. adjacent normal; adjacent normal vs. GS < 7 vs. GS = 7 vs. GS > 7). Relative HNRNPA2B1 and IGFBP3 mRNA levels were assessed through qPCR analysis and normalized to adjacent normal tissues or those of endogenous reference genes. Means ± SEMs are shown in the graphs. ns P > 0.05 and * P < 0.05

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