Identification of differential expression of MAP3K8 in human cancers
We identified the differential expression of MAP3K8 between tumor and paired normal samples on the Oncomine Platform and GEPIA website. The Oncomine Platform totally included 453 unique analyses for MAP3K8, of which 15 significant unique analyses demonstrated up-regulated expression of MAP3K8 in human cancers including brain and central nerve system cancer, colorectal cancer, gastric cancer, kidney cancer, prostate cancer, and other cancer. Meanwhile, down-regulated expression of MAP3K8 was seen in bladder cancer, brain and central nerve system cancer, breast cancer, head and neck cancer, leukemia, lung cancer, lymphoma, sarcoma, and other cancer, based on 38 significant unique analyses (Figure 1A). Furthermore, the GEPIA website was applied to reveal the gene expression profile of MAP3K8 across all tumor samples and paired normal tissues. Among the cancer gene profiles obtained from TCGA and GTEx, we screened 4 kinds of cancer that displayed down-regulated expression of MAP3K8, including adrenocortical carcinoma (ACC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), and skin cutaneous melanoma (SKCM) (Figure 1B). From the gene expression profile of MAP3K8 across all analyses, we found a lower expression level of MAP3K8 in cancer samples compared with paired normal tissues. To explore the relationship between clinicopathologic parameters and MAP3K8 expression, we analyzed MAP3K8 expression level in all cancers using subgroup factors such as tumor grade, race, gender, age, and histology. Our results indicated that MAP3K8 expression level is significantly related with tumor grade and cancer subtypes in kidney renal clear cell carcinoma (KIRC), which was marked by that patients with grade 4 KIRC and ccB subtype showed higher MAP3K8 level than those with grade 3 KIRC and ccA subtype, respectively (P<0.05). Compared with SKCM patients at the age of 41 to 60 years, patients at age between 21 - 40 years expressed more MAP3K8. For THCA, patients with classical thyroid papillary carcinoma, follicular thyroid papillary carcinoma, and other subtypes showed higher level of MAP3K8 than patients with tall thyroid papillary carcinoma (P<0.05) (Figure 2).
Promoter methylation level of MAP3K8 gene in human cancers
The UALCAN database was used to explore the level of MAP3K8 promoter methylation in human cancers. Our results suggested that the promoter methylation level of MAP3K8 in primary tumor of KIRC was higher than normal tissues (P<0.001). In addition, grade 1 KIRC had higher level promoter methylation of MAP3K8 than grade 2 and 3 tumor (P<0.001). Interestingly, metastatic tumor, but not primary tumor, of SKCM had higher level promoter methylation of MAP3K8 than compared normal tissues (P<0.05). Moreover, further subgroup analysis of promoter methylation showed significance based on cancer stage in THCA. Patients with stage 4 thyroid carcinoma (THCA) had higher level promoter methylation of MAP3K8 than that with stage 2 (P<0.05) (Figure 3).
Prognostic potential of MAP3K8 in different human cancers
To determine the prognostic value of MAP3K8 in human cancers, we performed survival analysis based on the GEPIA, DriverDBv3 and UALCAN databases. We only showed Kaplan-Meier (KM) curves that displayed significant prognostic value of MAP3K8 in cancers that have been conducted survival analysis based on at least 2 databases. KM curves of MAP3K8 in 7 kinds of cancers, including cervical squamous cell carcinoma (CESC), GBM, kidney renal papillary cell carcinoma (KIRP), brain lower grade glioma (LGG), LUAD, SARC, and uveal melanoma (UVM), were not displayed because only one database showed significant prognostic value of MAP3K8 (Figure 4). Results from GEPIA revealed that high MAP3K8 expression level was associated with poorer prognosis of OS in KIRC (Log-rank p=0.006, HR=1.5), and correlated with better prognosis of OS in mesothelioma (MESO) (Log-rank p=0.016, HR=0.56), SKCM (Log-rank p=0.00092, HR=0.64), and DFS in THCA (Log-rank p=0.036, HR=0.53) (Figure 5). The relationships obtained from DriverDBv3 between MAP3K8 expression and prognosis indicated that high MAP3K8 expression negatively affects OS in KIRC (Log-rank p=1.68e-07, HR=2.21) and thymoma (THYM) (Log-rank p=0.011, HR=5.44); high MAP3K8 expression significantly improved OS in MESO (Log-rank p=0.002, HR=0.46) (Figure 6). Additionally, survival analysis from UALCAN showed that high MAP3K8 expression was correlated with poorer clinical outcome in KIRC (p=0.002), THCA (p=0.028) and THYM (p=0.041), and with better prognosis in SKCM (p=0.017) (Figure 7).
Protein-protein interaction network analysis
The GeneMANIA online website and Cytoscape software were used to establish the interactions of MAP3K8. The PPI networks from the GeneMANIA website revealed a correlation among genes for MAP3K8. The gene sets enriched for MAP3K8 were responsible for toll-like receptor 3 signaling pathway, toll-like receptor 2 signaling pathway, toll-like receptor signaling pathway, pattern recognition receptor signaling pathway, innate immune response-activating signal transduction, activation of innate immune response, and protein serine/threonine kinase activity (Figure 8). In addition, the Cytoscape software was used to visualize the network of MAP3K8 by searching the BioGrid database. Each node, linked by edges, stood for an enriched term colored by the cluster-ID (Figure 9A). Meanwhile, the network of core modules of genes, including REL, RELA, TNIP2, NFKB1, NFKB2, and NFKBIA, were also constructed by MCODE, a Cytoscape plugin-in, which indicating important and potential biomarkers that contributed to the development and progression of cancers with MAP3K8 (Figure 9B).
Functional enrichment analyses of MAP3K8 using the GO and KEGG approaches
GO and KEGG signal pathway analysis were conducted to predict the functional enrichment information of interactive genes of MAP3K8 using the Metascape website. MAP3K8-related genes were involved in functions of BP, CCs, and MFs. We found that I-kappaB kinase/NF-kappaB signaling, activation of protein kinase activity, and response to tumor necrosis factor had significant regulation by the gene clusters (Figure 10A-C). Significant KEGG enrichment analyses showed in T cell receptor signaling pathway, MAPK signaling pathway, central carbon metabolism in cancer, oxytocin signaling pathway, axon guidance, and microRNAs in cancer. The findings revealed that MAP3K8 serves an essential role in regulation of T cell, MAPK signaling pathway, and several other important metabolic processes (Figure 10D), which was further verified by interactive networks of the enrichment terms of GO and KEGG (Figure 11A-B).