Li-yuan Feng

Preoperative serum levels of HE4 and CA125 predict primary optimal cytoreduction in advanced epithelial ovarian cancer: a preliminary model study

Abstract Objective The aim of this study is to establish a noninvasive preoperative model for predicting primary optimal cytoreduction in advanced epithelial ovarian cancer by HE4 and CA125 combined with clinicopathological parameters. Methods Clinical data including preoperative serum HE4 and CA125 level of 83 patients with advanced epithelial ovarian cancer were collected. The sensitivity, specificity, positive predictive value, negative predictive value and overall accuracy of each clinical parameter were calculated. The Predictive Index score model and the logistic model were constructed to predict the primary optimal cytoreduction. Results Optimal surgical cytoreduction was achieved in 62.65% (52/83) patients. Cutoff values of preoperative serum HE4 and CA125 were 777.10 pmol/L and 313.60 U/ml. (1) Patients with PIV ≥ 6 may not be able to achieve optimal surgical cytoreduction. The diagnostic accuracy, NPV, PPV and specificity for diagnosing suboptimal cytoreduction were 71, 100, 68, and 100%, respectively. (2) The logistic model was: logit p = 0.12 age − 2.38 preoperative serum CA125 level − 1.86 preoperative serum HE4 level-2.74 histological type-3.37. AUC of the logistic model in the validation group was 0.71(95%CI 0.54–0.88, P = 0.025). Sensitivity and specificity were 1.00 and 0.44, respectively. Conclusion Age, preoperative serum CA125 level and preoperative serum HE4 level are important non-invasive predictors of primary optimal surgical cytoreduction in advanced epithelial ovarian cancer. Our PIV and logistic model can be used for assessment before expensive and complex predictive methods including laparoscopy and diagnostic imaging. Further future clinical validation is needed.

Abnormal methylation characteristics predict chemoresistance and poor prognosis in advanced high-grade serous ovarian cancer

AbstractBackgroundPrimary or acquired chemoresistance is a key link in the high mortality rate of ovarian cancer. There is no reliable method to predict chemoresistance in ovarian cancer. We hypothesized that specific methylation characteristics could distinguish chemoresistant and chemosensitive ovarian cancer patients.MethodsIn this study, we used 450 K Infinium Methylation BeadChip to detect the different methylation CpGs between ovarian cancer patients. The differential methylation genes were analyzed by GO and KEGG Pathway bioinformatics analysis. The candidate CpGs were confirmed by pyrosequencing. The expression of abnormal methylation gene was identified by QRT-PCR and IHC. ROC analysis confirmed the ability to predict chemotherapy outcomes. Prognosis was evaluated using Kaplan–Meier.ResultsIn advanced high-grade serous ovarian cancer, 8 CpGs (ITGB6:cg21105318, cg07896068, cg18437633; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934, cg13270625) remained hypermethylated in chemoresistant patients. The sensitivity, specificity and AUC of 8 CpGs (ITGB6:cg21105318, cg07896068, cg18437633; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934, cg13270625) methylation to predict chemotherapy sensitivity were 63.60–97.00%, 46.40–89.30% and 0.774–0.846. PFS of 6 candidate genes (ITGB6:cg21105318, cg07896068; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934) hypermethylation patients was significantly shorter. The expression of NCALD and LAMA3 in chemoresistant patients was lower than that of chemosensitive patients. Spearman analysis showed that NCALD and LAMA3 methylations were negatively correlated with their expression.ConclusionsAs a new biomarker of chemotherapy sensitivity, hypermethylation of NCALD and LAMA3 is associated with poor PFS in advanced high-grade serous ovarian cancer. In the future, further research on NCALD and LAMA3 will be needed to provide guidance for clinical stratification of demethylation therapy.

LAMA3 DNA methylation and transcriptome changes associated with chemotherapy resistance in ovarian cancer

Abstract Objective LAMA3 is a widely studied methylated gene in multiple tumors, but the relationship between chemotherapy resistance in ovarian cancer is unclear. In this study, LAMA3 methylation was predicted by bioinformatics, and the ability of LAMA3 methylation to predict the chemotherapy resistance and prognosis of ovarian cancer was confirmed in experiments. Methods Multiple databases have performed the bioinformatics analysis of methylation and transcription factor binding site (TFBS) on the promoter region of LAMA3 gene. Pyrosequencing detected the methylation of LAMA3. QRT-PCR and immunohistochemistry detected the expression of LAMA3. Real Time Cell Analyzer (RTCA) detects changes in cell proliferation, migration and invasion ability. Flow cytometry was used to detect apoptosis. Results CPG islands of 176 bp, 134 bp, 125 bp and 531 bp were predicted in the promoter region of LAMA3 gene. The 4 prediction results are basically overlapped. 7 transcription factor binding sites were predicted, and the one with the highest score was on the predicted CpG island located in the proximal promoter region. LAMA3 hypermethylation and low expression are both associated with chemotherapy resistance and poor prognosis in ovarian cancer. LAMA3 methylation was negatively correlated with expression. After upregulation of LAMA3, the proliferation ability of chemoresistant ovarian cancer cell decreased, while the ability of apoptosis, invasion and migration increased. Conclusion LAMA3 hypermethylation is associated with chemotherapy resistance and poor prognosis. As a typical CpG island gene, LAMA3(cg20937934) and LAMA3(cg13270625) hypermethylation is negatively correlated with low expression. LAMA3 promotes the invasion, migration and apoptosis of SKOV3DDP. In the future, the mechanism of LAMA3 methylation in ovarian cancer will need to be further studied.