The Quest for Ovarian Cancer Screening Biomarkers: Are We on the Right Road?

Analysis of Competitive Endogenous Mechanism and Survival Prognosis of Serum Exosomes in Ovarian Cancer Patients Based on Sequencing Technology and Bioinformatics

Background: We determined the competitive endogenous in serum exosomes of ovarian cancer patients via sequencing technology and raw signal analysis. We performed an in-depth study of the potential mechanisms of ovarian cancer, predicted potential therapeutic targets and performed survival analysis of the potential targets.

Methods: Serum exosomes from three ovarian cancer patients were used as the experimental group, serum exosomes from three patients with uterine fibroids were used as the control group, and whole transcriptome analysis of serum exosomes was performed to identify differentially expressed long noncoding RNAs (lncRNAs) and mRNAs in ovarian cancer. The miRcode database and miRNA target gene prediction website were used to predict the target genes. Cytoscape software was used to generate a competing endogenous RNA (ceRNA) network of competitive endogenous mechanism of serum exosomes in ovarian cancer, and the R language was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the target genes. Finally, the TCGA website was used to download clinical and expression data related to ovarian cancer, and the common potential target genes obtained previously were analyzed for survival.

Results: A total of 117 differentially expressed lncRNAs as well as 513 differentially expressed mRNAs (p < 0.05, |log2 fold change (FC)|≥ 1.0) were obtained by combining sequencing data and raw signal analysis, and 841 predicted target genes were reciprocally mapped by combining the data from the miRcode database and miRNA target gene prediction website, resulting in 11 potential target genes related to ovarian cancer (FGFR3, BMPR1B, TRIM29, FBN2, PAPPA, CCDC58, IGSF3, FBXO10, GPAM, HOXA10, and LHFPL4). Survival analysis of the above 11 target genes revealed that the survival curve was statistically significant (p < 0.05) for HOXA10 but not for the other genes. Through enrichment analysis, we found that the above target genes were mainly involved in biological processes such as regulation of transmembrane receptor protein kinase activity, structural molecule activity with elasticity, transforming growth factor-activated receptor activity, and GABA receptor binding and were mainly enriched in signaling pathways regulating stem cell pluripotency, bladder cancer, glycerolipid metabolism, central carbon metabolism of cancer, and tyrosine stimulation to EGFR in signaling pathways such as resistance to enzyme inhibitors.

Conclusions: The serum exosomal DIO3OS-hsa-miR-27a-3p-HOXA10 competitive endogenous signaling axis affects ovarian cancer development and disease survival by targeting dysregulated transcriptional pathways in cancer.

Rapid quantitation of human epididymis protein 4 in human serum by amplified luminescent proximity homogeneous immunoassay (AlphaLISA)

A sensitive, rapid and homogeneous reaction measurement method for quantitation of human epididymis protein 4 (HE4) in human serum by amplified luminescent proximity homogeneous immunoassay (AlphaLISA) was described. Built on a sandwich-type immunoassay format, analytes in samples were captured by one biotinylated monoclonal antibody combining on the surface of streptavidin coated donor beads, and "sandwiched" by another monoclonal antibody coated on acceptor beads. The coefficient variations of the method were lower than 10%, and the recoveries were in the range of 90-110% for serum samples. A value of 0.88pmol/l was identified as the minimum detectable dose of the present method for HE4. Compared with the results from electrochemiluminescence immunoassay kit (Roche) in 170 serum samples, there was a satisfied correlation coefficient of 0.984. The present assay demonstrated high sensitivity, wider effective detection range and excellent reproducibility for quantitation of HE4 can be useful for early screening and prognosis evaluation of patients with ovarian cancer.

The Role of CA 125 as Tumor Marker: Biochemical and Clinical Aspects

CA 125 also known as mucin 16 or MUC16 is a large membrane glycoprotein belonging to the wide mucin family, encoded by the homonymous MUC16 gene. Following its discovery in the blood of some patients with specific types of cancers or other benign conditions, CA125 has found application as a tumor marker of ovarian cancer. Thirty years after its discovery, use of CA 125 is still FDA-recommended to monitor response to therapy in patients with epithelial ovarian cancer and to detect residual or recurrent disease in patients who have undergone first-line therapy and would be considered for second-look procedures. However, due to its limited specificity and sensitivity, CA 125 alone cannot still be an ideal biomarker. Increased clinical performance, in terms of better sensitivity and specificity in identifying epithelial ovarian cancer relapse, has been obtained by combined use of CA 125 with HE4, another ovarian cancer marker recently introduced in clinical use. Significant advancements have been achieved more recently, due to the introduction of FDA-approved ROMA and OVA1 algorithms to evaluate the risk of ovarian cancer for patients with a pelvic mass.

Modification of cut-off values for HE4, CA125 and the ROMA algorithm for early-stage epithelial ovarian cancer detection: Results from 1021 cases in South China

OBJECTIVES

The purpose of this study was to evaluate the performance of human epididymis protein 4 (HE4) and the Risk of Ovarian Malignancy Algorithm (ROMA) in early stage epithelial ovarian cancer (EOC) detection in patients in southern China. Additionally, this study proposes a possible ideal cut-off value for each marker to its own population in South China.

DESIGN AND METHODS

Serum HE4 and CA125 were measured in 756 patients with pelvic masses (275 malignancies, 53 borderline tumors and 428 benign diseases), and their ROMA values were calculated. Areas under the receiver operator characteristic (ROC) curves (AUC) were assessed for HE4, CA125, ROMA and combinations of these biomarkers.

RESULTS

Both HE4 and ROMA performed better diagnostically than CA125 alone for early stage EOC, with AUCs ranging from 0.714 for HE4, 0.699 for ROMA, and 0.463 for CA125 in premenopausal subjects, and 0.902 for ROMA, 0.880 for HE4, and 0.256 for CA125 in postmenopausal subjects.

CONCLUSIONS

HE4 and ROMA alone were found to be better than CA125 for detecting borderline tumors and early-stage EOC. The optimal cut-off values (HE4: 70pmol/l for all; CA125: 60U/ml for pre- and 35U/ml for postmenopausal women) could notably improve diagnostic performance in EOC detection in patients in southern China.

Advantages of the avian model for human ovarian cancer

Ovarian cancer (OC) is the most lethal gynecological cancer. Early detection of OC is crucial for providing efficient treatment, whereas high mortality rates correlate with late detection of OC, when the tumor has already metastasized to other organs. The most prevalent type of OC is epithelial OC (EOC). Models that have been used to study EOC include the fruit fly, mouse and laying hen, in addition to human EOC cells in 3D culture in vitro. These models have helped in the elucidation of the genetic component of this disease and the development of drug therapies. However, the histological origin of EOC and early markers of the disease remain largely unknown. In this study, we aimed to review the relative value of each of the different models in EOC and their contributions to understanding this disease. It was concluded that the spontaneous occurrence of EOC in the adult hen, the prolific ovulation, the similarity of metastatic progression with that in humans and the advantages of using the chicken embryo for modelling the development of the reproductive system, renders the hen particularly suitable for studying the early development of EOC. Further investigation of this avian model may contribute to a better understanding of EOC, improve clinical insight and ultimately contribute to decreasing its mortality rates among humans.