Fig 1.
Differences in expression of genes among stages I and IV of endometrial cancer.
(A) According to the expression of the mRNA levels from TCGA database, the patients were divided into 2 groups based on their respective FIGO stages. (B) The volcano plot of mRNA levels from the TCGA database and the x-axis represent the log2 transformed of fold change ratios. The y-axis is the log10 transformed adjusted p-value. The red colored dots represent the DEGs based on fold change >1. Herein, the volcano plot displayed the different genes when comparing patients in the stage II group with the patients in the stage I group. (C) Based on volcano analysis, the plot of 54 upregulated and 9 downregulated genes. (D) Heatmap of the candidate genes associated with FIGO stage from TCGA database. (E) Volcano plot of the mRNA levels of different genes in samples with stage IV and samples with stage III. (F) The plot showed 58 upregulated and 113 downregulated genes based on the above volcano analysis. (G) Heatmap of the candidate genes associated with FIGO stage from TCGA database. (H) Venn diagram representing the distribution of DEGs in different groups. 1 DEG was upregulated in both scenarios of stage IV vs. stage III and stage II vs. stage I.
Fig 2.
Functional analysis for CKMT1A.
(A) GO analysis of CKMT1A. (B) KEGG analysis of CKMT1A.
Fig 3.
A protein-protein interaction (PPI) network shows the interaction between the screened DEGs.
Each node represents one gene; the edge indicates the interaction relationship.
Fig 4.
A higher expression of CKMT1A indicated poor prognosis in TCGA database.
(A) mRNA expression of CKMT1A in cancer vs control from patients in TCGA database (***, P<0.001). (B) mRNA expression of CKMT1A in endometrial cancer patients at different FIGO stages of TCGA database (*, P<0.05; **, P<0.01). (C) mRNA expression of CKMT1A in endometrial cancer patients with histological differentiation of TCGA database (*, P<0.05). (D) Kaplan-Meier curve of CKMT1A was provided by patients from TCGA data.
Fig 5.
Gene set enrichment analysis (GSEA) analysis of CKMT1A.
GSEA showed that CKMT1A was associated with (A) inner mitochondrial transmembrane organization; (B) mitochondrial transmembrane transport; (C) NADH metabolic process; and (D) negative regulation of cellular protein catabolic process.
Fig 6.
Analysis of CKMT1A in the Human Protein Atlas.
(A)(B)(C) Expression of CKMT1A in normal tissues in the Human Protein Atlas. (D)(E)(F) Expression of CKMT1A in endometrial cancer samples in the Human Protein Atlas. (G) The expression of CKMT1A in endometrial cancer vs control from patients in the Human Protein Atlas (**, P<0.01). (H) Kaplan-Meier curve of CKMT1A was provided by patients from the Human Protein Atlas data.
Fig 7.
The expression of CKMT1A in association with the clinical characteristics and overall survival (OS) of patients with endometrial cancer.
(A) The mRNA expression levels of CKMT1A in different groups of FIGO stages are displayed (****, P<0.0001). (B) Impact of CKMT1A expression on overall survival in clinical patients (n = 39).
Fig 8.
Immunohistochemical staining results of tumor and paratumor tissues in endometrial cancer with different stage.
(A) Immunohistochemical staining results of tumor tissue in endometrial cancer with different stages (200× and 400×); (B) Immune responsive score (IRS) of CKMT1A in endometrial cancer different stage (n = 40); (C) Kaplan-Meier curves show the association between expression of CKMT1A and OS according to the immunohistochemical results (n = 40).
Table 1.
Characteristics of patients with endometrial cancer.
Table 2.
Association between CKMT1A expression and clinicopathological features of patients with endometrial cancer.
Table 3.
Logistic regression model analysis of stage predictors in patients with endometrial cancer.
Table 4.
Cox’s proportional hazard model analysis of prognostic factors in patients with endometrial cancer.