OBJECTIVE: The main objective of the present study was to identify the cancer-related genes and gene pathways in the endometrium of healthy and cancer patients.
MATERIALS AND METHODS: Thirty endometrial tissues from healthy and type I EC patients were subjected to total RNA isolation. The RNA samples with good integrity number were hybridized to a new version of Affymetrix Human Genome GeneChip 1.0 ST array. We analyzed the results using the GeneSpring 9.0 GX and the Pathway Studio 6.1 software. For validation assay, quantitative real-time polymerase chain reaction was used to analyze 4 selected genes in normal and EC tissue.
RESULTS: Of the 28,869 genes profiled, we identified 621 differentially expressed genes (2-fold) in the normal tissue and the tumor. Among these genes, 146 were up-regulated and 476 were down-regulated in the tumor as compared with the normal tissue (P < 0.001). Up-regulated genes included the v-erb-a erythroblastic leukemia viral oncogene homolog 3 (ErbB3), ErbB4, E74-like factor 3 (ELF3), and chemokine ligand 17 (CXCL17). The down-regulated genes included signal transducer and activator transcription 5B (STAT5b), transforming growth factor A receptor III (TGFA3), caveolin 1 (CAV1), and protein kinase C alpha (PKCA). The gene set enrichment analysis showed 10 significant gene sets with related genes (P < 0.05). The quantitative polymerase chain reaction of 4 selected genes using similar RNA confirmed the microarray results (P < 0.05).
CONCLUSIONS: Identification of molecular pathways with their genes related to type I EC contribute to the understanding of pathophysiology of this cancer, probably leading to identifying potential biomarkers of the cancer.
METHODS: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data.
RESULTS: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). We found seven loci associated with risk for both cancers (P Bonferroni < 2.4 × 10-9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10-7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation.
CONCLUSIONS: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis.
IMPACT: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.
Methods: a total of 53 cases of endometrioid type of EC were selected within a six-year period comprising of 22 cases of grade 1, 25 cases of grade 2 and six cases of grade 3 carcinoma. The selected whole tumour tissue sections were immune-stained with HER2 antibody. The scoring was semi-quantitatively analyzed based on 2013 American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAPs) guidelines for the scoring of HER2 in breast cancer.
Results: all cases regardless of grades of endometrioid carcinoma showed negative expression of HER2 (score 0).
Conclusion: there was no significant HER2 expression in endometrioid carcinoma. However, a follow-up study with a larger number of samples from different type of endometrial carcinoma is needed. Testing of several tumour tissue blocks to assess possible tumour heterogeneity, as well as correlation with HER2 gene amplification status by in-situ-hybridisation, are also recommended.
MATERIAL AND METHODS: A cross-sectional study was performed at Nottingham University Hospital, UK. A total of 102 women (polycystic ovary syndrome, endometrial cancer and controls; 34 participants in each group) were recruited. Clinical and biochemical assessments were performed before endometrial biopsies were obtained from all participants. Taqman real-time polymerase chain reaction for endometrial sterol regulatory element binding protein-1 gene and its systemic protein expression were analyzed.
RESULTS: The body mass indices of women with polycystic ovary syndrome (29.28 ± 2.91 kg/m(2) ) and controls (28.58 ± 2.62 kg/m(2) ) were not significantly different. Women with endometrial cancer had a higher mean body mass index (32.22 ± 5.70 kg/m(2) ). Sterol regulatory element binding protein-1 gene expression was significantly increased in polycystic ovary syndrome and endometrial cancer endometrium compared with controls (p
MATERIALS AND METHODS: A total of 20 genes were selected from the list of up-regulated genes for the validation assay. The qPCR confirmed that 19 out of the 20 genes were up-regulated in endometrial cancer compared with normal endometrium. RNA interference (RNAi) was used to knockdown the expression of the upregulated genes in ECC-1 and HEC-1A endometrial cancer cell lines and its effect on proliferation, migration and invasion were examined.
RESULTS: Knockdown of MIF, SOD2, HIF1A and SLC7A5 by RNAi significantly decreased the proliferation of ECC-1 cells (p < 0.05). Our results also showed that the knockdown of MIF, SOD2 and SLC7A5 by RNAi significantly decreased the proliferation and migration abilities of HEC-1A cells (p < 0.05). Moreover, the knockdown of SLC38A1 and HIF1A by RNAi resulted in a significant decrease in the proliferation of HEC1A cells (p < 0.05).
CONCLUSION: We have identified the biological roles of SLC38A1, MIF, SOD2, HIF1A and SLC7A5 in endometrial cancer, which opens up the possibility of using the RNAi silencing approach to design therapeutic strategies for treatment of endometrial cancer.