Prognostic and Immunological Role of STK38 across Cancers: Friend or Foe?

Abstract

Although STK38 (serine-threonine kinase 38) has been proven to play an important role in cancer initiation and progression based on a series of cell and animal experiments, no systemic assessment of STK38 across human cancers is available. We firstly performed a pan-cancer analysis of STK38 in this study. The expression level of STK38 was significantly different between tumor and normal tissues in 15 types of cancers. Meanwhile, a prognosis analysis showed that a distinct relationship existed between STK38 expression and the clinical prognosis of cancer patients. Furthermore, the expression of STK38 was related to the infiltration of immune cells, such as NK cells, memory CD4+ T cells, mast cells and cancer-associated fibroblasts in a few cancers. There were three immune-associated signaling pathways involved in KEGG analysis of STK38. In general, STK38 shows a significant prognostic value in different cancers and is closely associated with cancer immunity.

Keywords: STK38; immune infiltration; pan-cancer; prognosis; survival.

Figure 1

STK38 expression profiles in normal tissues and cancers. (A) STK38 expression level in TCGA tumors were analyzed using TIMER2.0 database (* p < 0.05; ** p < 0.01; *** p < 0.001). The red color represents tumor tissue samples, and the blue color represents normal samples. (B) Expression level of STK38 in main pathological stages (stage I, stage II, stage III, and stage IV) of ACC, LIHC, OV, PAAD, THCA and UCEC were analyzed using TCGA. Expression levels are shown as Log2 (TPM + 1).

Figure 2

Protein expression levels of STK38 between normal tissues and tumor tissues (left), and representative immunohistochemical staining (IHC) in normal (middle) tissue and tumor (right) tissue samples in the HPA database. STK38 protein expression was significantly higher in clear cell RCC, PAAD and LIHC, and it was lower in OV, COAD and LUAD (A) Kidney. (B) Pancreas. (C) Liver. (D) Ovary. (E) Colon. (F) Lung. (*** p < 0.001). Protein expression data are originated from CPTAC database. Two immunohistochemistry images for each cancer were from different patients. Antibody CAB004673 was used for IHC. Scale bars: 200 μm.

Figure 3

Correlation analysis between STK38 gene expression and prognosis of different tumors in TCGA. GEPIA2 tool was used to perform overall survival (A) and disease-free survival (B) analyses of TCGA tumors by STK38 gene expression. The survival map and Kaplan–Meier curves with positive results are listed. The red lines of Kaplan–Meier curves indicate the high STK38 expression groups, and the blue lines indicate the low STK38 expression groups.

Figure 4

Alteration characterizes of STK38 in TCGA tumors. The mutation features of STK38 were analyzed using the cBioPortal tool. The alteration frequency with mutation type (A) and mutation site (B) are shown. (C) Protein structure of STK38. (D) Correlation analysis of STK38 between mutation status and overall, disease-specific, disease-free and progression-free survival using the cBioPortal tool. The red lines represent the altered groups, and the blue lines represent the unaltered groups.

Figure 5

Relationship between STK38 expression and immune infiltration (A) The expression of STK38 is significantly correlated with a variety of immune cells infiltration levels based on CIBERSORT. * p < 0.05, ** p < 0.01, and *** p < 0.001. (B) The potential correlation analysis of STK38 expression and immune infiltration of cancer-associated fibroblasts. The red color represents a positive relationship (0–1), while the blue color indicates a negative relationship (−1–0). The relationship with p-value < 0.05 is statistically significant. Statistically non-significant relationship are labeled with a cross. (C) The scatter plots of related cancers including HNSC-HPV-, LGG, TGCT, PRAD, SARC and PAAD.

Figure 6

Top three scatter plots of correlation between STK38 expression and ImmuneScore, StromalScore and ESTIMATEScore in multiple cancers.

Figure 7

Enrichment and pathway analysis of STK38-related partners. (A) The experimentally verified STK38-binding proteins were obtained from the STRING website. (B) The correlation analysis between STK38 and selected binding genes including PKN2, NUMB, MAPK14, SP1 and SRPK1 using the GEPIA2 tool. (C) The corresponding heatmap data of different cancer types are displayed in detail. (D) GO and KEGG pathway analysis were performed based on the STK38-binding and interacted genes.