Expression of GOT2 Is Epigenetically Regulated by DNA Methylation and Correlates with Immune Infiltrates in Clear-Cell Renal Cell Carcinoma

Abstract

Clear cell renal cell carcinoma (KIRC) is the most common and highly malignant pathological type of kidney cancer, characterized by a profound metabolism dysregulation. As part of aspartate biosynthesis, mitochondrial GOT2 (glutamic-oxaloacetic transaminase 2) is essential for regulating cellular energy production and biosynthesis, linking multiple pathways. Nevertheless, the expression profile and prognostic significance of GOT2 in KIRC remain unclear. This study comprehensively analyzed the transcriptional levels, epigenetic regulation, correlation with immune infiltration, and prognosis of GOT2 in KIRC using rigorous bioinformatics analysis. We discovered that the expression levels of both mRNA and protein of GOT2 were remarkably decreased in KIRC tissues in comparison with normal tissues and were also significantly related to the clinical features and prognosis of KIRC. Remarkably, low GOT2 expression was positively associated with poorer overall survival (OS) and disease-free survival (DFS). Further analysis revealed that GOT2 downregulation is driven by DNA methylation in the promoter-related CpG islands. Finally, we also shed light on the influence of GOT2 expression in immune cell infiltration, suggesting that GOT2 may be a potential prognostic marker and therapeutic target for KIRC patients.

Keywords: GOT2; KIRC; epigenetics; immune cell infiltration; multi-omics.

Figure 1

GOT2 expression levels in pan-cancer (TCGA dataset). The box plot comparing specific GOT2 expression in tumor samples (red plot) and paired normal tissues (blue plot) was derived from the TIMER database (* p < 0.05, ** p < 0.01, *** p < 0.001). TPM: transcripts per million.

Figure 2

Expression of GOT2 in KIRC and normal patients. (A) Differential expression of GOT2 between KIRC samples from TCGA database (Red, n = 523 samples) and normal human kidney samples from GTEx database (Blue, n = 100 samples). (* p < 0.05, *** p < 0.001) (B) Significant downregulation of GOT2 protein level in the CPTAC KIRC cohort, analyzed by UALCAN. KIRC: n = 110; Normal samples: n = 84. Z-values represent standard deviations from the median across samples. (C) Representative images of immunohistochemical (IHC) staining of GOT2 protein in normal kidney tissue (Patient ID: 2067; Staining: medium; Intensity: moderate; Quantity: 75–25%; Location: cytoplasmic/membranous) and KIRC tissue (Patient ID: 2176; Staining: low; Intensity: weak; Quantity: >75%; Location: cytoplasmic/membranous) from the HPA database. Scale bars: left, 100 μm; right, 25 μm. Antibody used in both samples: HPA018139.

Figure 3

Association between GOT2 expression and the clinicopathological features of KIRC patients. Box plots of GOT2 mRNA expression according to: (A) KIRC stages (Stages 1, 2, 3 and 4). (B) gender (male, female). (C) KIRC grades (1, 2, 3 and 4). (D) clear cell renal cell carcinoma (ccRCC) good risk (ccA) and poor risk (ccB) subtype classification. (E) nodal metastasis status. GOT2 protein expression was differentially expressed in (F) clinical stages and (G) tumor grade ** p < 0.01, *** p < 0.001. GOT2 expression in the KIRC cohort (TCGA) according to (H) VHL mutation status, (I) PBRM1 mutation status and (J) SETD2 mutation status, ** p < 0.01, *** p < 0.001.

Figure 4

Kaplan–Meier survival analysis demonstrating the relationship between GOT2 expression and prognosis in KIRC patients. Overexpression of GOT2 mRNA prolonged (A) OS (n = 258) and (B) DFS (Disease-Free Survival; n = 258) of KIRC patients. (C) High expression of GOT2 protein prolonged OS of KIRC patients (n = 528) (p = 0.023). HR, hazard ratio; OS, overall survival; GOT2, Glutamic-Oxaloacetic Transaminase 2; KIRC, Kidney Renal Clear Cell Carcinoma.

Figure 5

Chromosomal distribution of the methylation probes associated with GOT2. Upper panel: Circos plot depicting the genomic information of GOT2 (16q21) and the probes used in this study. Lower panel: Segment plot showing the detailed information of genomic locations of each probe of GOT2, highlighting CpG island, N shelf, S Shore and Open Sea. The coverage of the promoter region is displayed as the red region (red box), which includes eight probes (cg08348831, cg13626907, cg14863484, cg09082840, cg16406345, cg08578141, cg10055227 and cg08950929). Numbers below represent the genomic length scale (1 kb).

Figure 6

Dynamics of DNA methylation across all probes of GOT2 in KIRC. Heat map showing the methylation levels of GOT2 among different CpGs sites (probes) integrating ethnicity, race, age, vital status, and genomic regions of CpG sites (UCSC) from KIRC. Red to blue scale indicates high to low methylation levels.

Figure 7

Hypermethylation of GOT2 leads to downregulated expression in KIRC. (A) Differential methylation level of eighth GOT2 probes (cg08348831, cg13626907, cg14863484, cg09082840, cg16406345, cg08578141, cg10055227 and cg08950929) between KIRC patients (n = 313) and normal samples (n = 157) from TCGA. (B) Spearman’s correlation between methylation level (β-values, 450 k array) and mRNA level (Log2-scaled, TPM + 1) of GOT2 in KIRC samples from TCGA.

Figure 8

Association of GOT2 expression, with immune subtypes and immune cell infiltration. (A) GOT2 mRNA levels in TCGA-KIRC immune subtypes. C1: wound healing subtype (n = 7), C2: INF-γ dominant (n = 20), C3: inflammatory (n = 445), C4: lymphocyte depleted (n = 27), C5: immunologically quiet (n = 3), C6: TGF-ꞵ dominant (n = 16). One-way ANOVA p-value = 1.2 × 10⁻⁴. (B) GOT2 expression in different immune cells types in KIRC samples from TCGA and normal samples from TCGA and GTEx.

Figure 9

Expression of GOT2 in scRNA-seq landscapes. (A) Heatmap of GOT2 expression displayed heterogeneity in different clusters of cells in KIRC_GSE111360 [55] and KIRC_GSE139555 datasets [56]. (B) Expression of GOT2 in GSE111360 (upper panel) and in GSE139555 (lower panel) datasets after Uniform Manifold Approximation and Projection (UMAP) processing. Violin diagrams depict the GOT2 expression in different immune cells across each dataset analyzed.

Figure 10

The expression source of the signature genes was revealed by single-cell analysis (GSE111360 dataset). The signature was composed of GOT2, LAG3, CTLA4, EOMES, LGALS9, CD96, HAVCR2, PDCD1, TIGIT, and TOX.