Identification and Characterization of the RNA Modifying Factors PUS7 and WTAP as Key Components for the Control of Tumor Biological Processes in Renal Cell Carcinomas

Abstract

Current research discusses the putative importance of RNA modification in tumor diseases. These RNA modifications include predominantly pseudouridinylation, ortho-methylations on the ribose residues, as well as methylations on the organic bases. Such chemical modifications directly influence fundamental properties such as transcript stability, alternative splicing, and translation efficiency, all of which are basic requirements for (tumor) cell proliferation, cell metabolism, cell migration, apoptosis resistance, etc. In this comparative study, the two RNA-modifying factors, pseudouridine synthase 7 (PUS7, RNA pseudouridinylation) and WT1-associated protein (WTAP, m6A RNA methylation), were identified using data from human renal cell carcinoma (RCC) tumors. PUS7 and WTAP showed a statistically significant correlation with relevant proliferation and prognosis markers such as CXCR4, TP53, PTEN, and NRAS, as well as with the two tumor immune checkpoints HLA-G and LGALS9 and were directly associated with a statistically significant effect on overall survival. Furthermore, comparative analyses also identified further putative target mRNAs of importance for tumor biology of PUS7 and WTAP. In particular, components with direct relevance for mitosis, the cell cycle, and cell division, as well as the WNT pathway, were identified.

Keywords: PUS7; RCC; RNA modifications; WTAP; alternative splicing; transcriptome.

Figure 1

Comparative analysis of DESeq2 normalized gene expression for cell proliferation markers (A–C) and prognostic markers (D–F) between the three RCC subtypes according to the order ccRCC > pRCC > chRCC with regard to proliferation and malignancy. Statistically significant differences in gene expression (FDR) are marked with an asterisk and the exact numerical values on the side with an arrow. Blue color indicates downregulation and red color upregulation.

Figure 2

Comparative analysis of DESeq2 normalized gene expression for immune checkpoint axes (A–C) with available therapeutic mAbs between the three RCC subtypes according to the order ccRCC > pRCC > chRCC regarding proliferation and malignancy. Statistically significant differences in gene expression (FDR) are marked with an asterisk, and the exact numerical values are marked with an arrow on the side. Blue color indicates downregulation and red color upregulation.

Figure 3

Comparative analysis of DESeq2 normalized gene expression for factors with relevance for RNA pseudouridinylation (A–C) in the three RCC subtypes according to the order ccRCC > pRCC > chRCC with respect to proliferation and malignancy. Statistically significant differences in gene expression (FDR) were marked with a star, and the exact numerical values were marked with an arrow on the side. The blue color was used for downregulation and the red color for upregulation.

Figure 4

Comparative analysis of DESeq2 normalized gene expression for factors relevant to RNA ortho-methylations (A,F,K) and methylations on the organic bases (B–E,G–J,L–O) in the three RCC subtypes according to the order ccRCC > pRCC > chRCC with regard to proliferation and malignancy. Statistically significant differences in gene expression (FDR) were marked with a star, and the exact numerical values were indicated with an arrow on the side. The blue color was used for down-regulation and the red color for up-regulation.

Figure 5

Exemplary visualization of the correlations of PTEN with PUS7 (A–C) and WTAP (D–F) in the three RCC subtypes. Expressions are given in transcripts per million reads.

Figure 6

Investigation of the effect of PUS7 (A–C) and WTAP (D–F) on overall survival in the three RCC subtypes. The division into high versus low was done by median split of TPM expression values and analyzed with the log-rank (Mantel-Cox) test using the MatSurv tool [29].

Figure 7

Heatmap visualizations show gene expression patterns of putative target genes that were statistically significantly altered when comparing PUS7 high versus low (A) and WTAP high versus low (B) in the three RCC subtypes. Furthermore, these target genes had to fulfill the following criteria: the correlation coefficients had to be either ≥ 0.3 or ≤−0.3 with PUS7 (A) and WTAP (B) in all three RCC subtypes.