METHODS: We designed a questionnaire, including 50 questions related to debulking surgery for advanced ovarian cancer. The questionnaire was sent to Gynecologic Oncologic Groups in Asia from December 2016 to February 2017.
RESULTS: A total of 253 gynecologic oncologists from Japan (58.9%), the Republic of Korea (19%), Taiwan (12.6%), and the other counties including China (7.5%), Malaysia (0.8%), Indonesia (0.8%), and Thailand (0.4%) participated in this E-survey. The median number of debulking surgeries per year was 20, and 46.8% of the respondents preferred <1 cm as the criterion for optimal debulking surgery (ODS). The most common barrier and surgical finding precluding ODS were performance status (74.3%) and disease involving the porta hepatis (71.5%). Moreover, 63.2% had a fellowship program, and only 15% or less had opportunities to receive additional training courses in general, thoracic, or urologic surgery. The median percentage of patients receiving neoadjuvant chemotherapy (NAC) was 30%, and the achieved rate of ODS in primary debulking surgery (PDS) and interval debulking surgery (IDS) was 65% and 80%, respectively. Most of the respondents required three to 6 h for PDS (48.6%) and IDS (58.9%). Moreover, more than 50% depended on ultra-radical surgery conducted by specialists.
CONCLUSIONS: The ODS criteria are relatively lenient with a preference for NAC in 30% of the respondents in Asia. This trend might be associated with the dependence on aggressive surgery performed by specialists.
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.
MATERIALS AND METHODS: 300 healthy women were recruited comprising 150 premenopausal and 150 postmenopausal women, aged from 20-76 years. All women were subjected to a pelvic ultrasonograph and were confirmed to be free from ovarian pathology on recruitment. Serum HE4 levels were determined by chemiluminescent microparticle immunoassay (CMIA, Abbott Architect). The reference intervals were determined following CLSI guidelines (C28-A2) using a non-parametric method.
RESULTS: The upper limits of the 95th percentile reference interval (90%CI) for all the women collectively were 64.6 pmol/L, and 58.4 pmol/L for premenopausal) and 69.0 pmol/L for postmenopausal. The concentration of HE4 was noted to increase with age especially in women who were more than 50 years old. We also noted that our proposed reference limit was lower compared to the level given by manufacturer Abbott Architect HE4 kit insert (58.4 vs 70 pmol/L for premenopausal group and 69.0 vs 140 pmol/L in the postmenopausal group). The study also showed a significant difference in HE4 concentrations between ethnic groups (Malays and Indians). The levels of HE4 in Indians appeared higher than in Malays (p<0.05), while no significant differences were noted between the Malays and Chinese ethnic groups.
CONCLUSIONS: More data are needed to establish a reference interval that will better represent the multiethnic Malaysian population. Probably a larger sampling size of equal representation of the Malay, Chinese, Indians as well as the other native ethnic communities will give us a greater confidence on whether genetics plays a role in reference interval determination.