ObjectiveEndometrial cancer (EC) is a common gynecologic cancer worldwide. However, the pathogenesis of EC has not been epigenetically elucidated. Here, this study aims to describe the DNA methylation profile and identify favorable gene signatures highly associated with aberrant DNA methylation changes in EC.MethodsThe data regarding DNA methylation and gene expression were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially methylated CpG sites (DMCs), differentially methylated regions (DMRs), and differentially expressed genes (DEGs) were identified, and the relationship between the 2 omics was further analyzed. In addition, weighted CpG site co-methylation network (WCCN) was constructed followed by an integrated analysis of DNA methylation and gene expression data.ResultsFour hundred thirty-one tumor tissues and 46 tissues adjacent tumor of EC patients were analyzed. One thousand one hundred thirty-five DMCs (merging to 10 DMRs), and 1,488 DEGs were obtained between tumor and normal groups, respectively. One hundred forty-eight DMCs-DEGs correlated pairs and 13 regional DMCs-DEGs pairs were obtained. Interestingly, we found that some hub genes in 2 modules among 8 modules of WCCN analysis were down-regulated in tumor samples. Furthermore, protocadherins (PCDHs) clusters, DDP6, TNXB, and ZNF154 were identified as novel deregulated genes with altered methylation in EC.ConclusionBased on the analysis of DNA methylation in a systematic view, the potential long-range epigenetic silencing (LRES) composed of PCDHs was reported in ECs for the first time. PCDHs clusters, DDP6, and TNXB were firstly found to be associated with tumorigenesis, and may be novel candidate biomarkers for EC.

Growing tumors alter their metabolic profiles to support the increased cell proliferation. SETD1A, a histone lysine methyltransferase which specifically methylates H3K4, plays important roles in both normal cell and cancer cell functions. However, the function of SETD1A in gastric cancer (GC) progression and its role in GC metabolic reprogramming are still largely unknown. In the current study, we discovered that the expression of SETD1A was higher in GC tumor specimens compared to surrounding nontumor tissues. Upregulation of SETD1A increased GC cell proliferation, whereas downregulation of SETD1A inhibited GC cell proliferation. Furthermore, knockdown of SETD1A reduced glucose uptake and production of lactate and suppressed glycolysis by decreasing the expression of glycolytic genes, including GLUT1, HK2, PFK2, PKM2, LDHA, and MCT4. Mechanistically, SETD1A interacted with HIF1a to strengthen its transactivation, indicating that SETD1A promotes glycolysis through coactivation of HIF1a. SETD1A and HIF1a were recruited to the promoter of HK2 and PFK2, where SETD1A could methylate H3K4. However, knockdown of SETD1A decreased the methylation of H3K4 on HK2 and PFK2 promoter and reduced HIF1a recruitment necessary to promote transcription of glycolytic genes. Inhibition of HIF1a decelerated SETD1Aenhanced GC cell growth. In additional, there was a linear correlation between SETD1A and several key glycolytic genes in human GC specimens obtained from TCGA dataset. Thus, our results demonstrated that SETD1A interacted with HIF1a to promote glycolysis and accelerate GC progression, implicating that SETD1A may be a potential molecular target for GC treatment.

The present study aimed to investigate the clinical significance of paired-box 8 (PAX8) in primary epithelial ovarian cancer (PEOC). Using immunohistochemical (IHC) staining, the expression of PAX8 in 60 patients with PEOC, 20 patients with ovarian benign lesions and 10 patients with metastatic ovarian cancer (MOC), was examined based on the clinicopathological profiles of the patients. The correlation between PAX8 expression and the clinicopathological parameters or prognosis of patients was statistically analyzed. PAX8 was revealed to be highly expressed in PEOC, but not in MOC, as indicated by IHC staining. The rate of positivity of PAX8 in PEOC was 92% (57/60) with no significant difference of PAX8 expression found between the various pathological types of PEOC (P=0.871). The rate of positivity of PAX8 in ovarian benign tumors was 85%, demonstrating no significant difference in comparison with that of PEOC (P=0.761). PAX8 staining and statistical analysis revealed that the higher the grade of PEOC, the less the cancer cell had differentiated (P=0.033) and the more the cancer had advanced according to International Federation of Gynaecological Oncologists (FIGO) staging (P=0.003). Survival rate statistics showed that PEOC patients with higher PAX8 expression exhibited a shorter postoperative survival rate (P=0.009). PAX8 was specifically expressed in PEOC, and its expression level was associated with the degree of cancer cell differentiation, FIGO stage, and survival rate, indicating that PAX8 is a potential marker for the diagnosis of PEOC.