Potential Biomarker For Ovarian Cancer Research Articles

Genome-wide DNA copy number profiling and bioinformatics analysis of ovarian cancer reveals key genes and pathways associated with distinct invasive/migratory capabilities.

Ovarian cancer (OC) metastasis presents major hurdles that must be overcome to improve patient outcomes. Recent studies have demonstrated copy number variations (CNVs) frequently contribute to alterations in oncogenic drivers. The present study used a CytoScan HD Array to analyse CNVs and loss of heterozygosity (LOH) in the entire genomes of 6 OC patients and human OC cell lines to determine the genetic target events leading to the distinct invasive/migratory capacities of OC. The results showed that LOH at Xq11.1 and Xp21.1 and gains at 8q21.13 were novel, specific CNVs. Ovarian cancer-related CNVs were then screened by bioinformatics analysis. In addition, transcription factors-target gene interactions were predicted with information from PASTAA analysis. As a result, six genes (i.e., GAB2, AKT1, EGFR, COL6A3, UGT1A1 and UGT1A8) were identified as strong candidates by integrating the above data with gene expression and clinical outcome data. In the transcriptional regulatory network, 4 known cancer-related transcription factors (TFs) interacted with 6 CNV-driven genes. The protein/DNA arrays revealed 3 of these 4 TFs as potential candidate gene-related transcription factors in OC. We then demonstrated that these six genes can serve as potential biomarkers for OC. Further studies are required to elucidate the pathogenesis of OC.

Modulatory Role of Vaginal-Isolated Lactococcus lactis on the Expression of miR-21, miR-200b, and TLR-4 in CAOV-4 Cells and In Silico Revalidation.

Ovarian cancer (OC) is a leading cause of death among women worldwide. Various evidences suggest that oncomiRs and Toll-like receptor 4 (TLR-4) signaling pathways appear to be key players in the initiation and progression of OC. It seems there exists a continuous intercommunication between cancer cells and normal microbiota of the vagina. The biological impacts of vaginal isolated lactococcus lactis on CAOV-4 cells were investigated using several molecular biology experiments, including flow cytometry, DAPI staining, DNA ladder, and scratch assay. The expression of microRNAs (miRNAs/miRs) 21, 200b, and TLR-4 in the CAOV-4 cells was also evaluated by the real-time RT-PCR assay. Furthermore, an integrative in silico analysis was conducted using normalized web-available microarray data (GSE14407) to revalidate the experimental findings and identify potential biomarkers in ovarian cancer. Protein-protein interactions (PPIs) network was studied by means of the STRING database using Cytoscape v3.6.1. The miRNA target genes were identified using the dbDEMC v2.0, miRTarBase, and miRDB databases. Our data demonstrated that L. lactis probiotic candidate downregulates TLR-4, miR-21, and miR-200b expression levels, which correlates with induction of apoptosis asconfirmed by DAPI staining, DNA ladder assay, annexin V/PI staining, and inhibition of migration validated by scratch assay. By in silico analysis, several targets (miR-17-5p-BCL2, miR-21-5p-MKNK2, miR-129-5p-CDK6) were identified, while BCL2, CCNB1, and VEGFA were found as the hub proteins in the miRNA-target and PPI networks. Further, downregulation of the TLR-4, miR-21, and miR-200b was partially validated by the in silico analysis. Based on our findings, the vaginal isolated probiotic strain presents great potential to control the ovarian cancer which may provide beneficial impact on the clinical management of ovarian cancer.

Plasma MicroRNA-200c as A Prognostic Biomarker for Epithelial Ovarian Cancer

BACKGROUND: Ovarian cancer is the 8th most prevalent cancer in women in the world. Current biomarker prognosis for ovarian cancer has numerous limitations, thus new biomarkers are needed. MicroRNAs (miRs) are considered as potential biomarkers in ovarian cancer as they are stable in blood. One candidate is miR-200c, the main regulator in epithelial transition to the mesenchyme. The aim of this study is to determine the role of miR-200c as prognostic biomarker for epithelial ovarian cancer (EOC).METHODS: This is a prospective cohort study conducted at Dr. Sardjito Central General Hospital in Yogyakarta from September 2015 to July 2018. Sampling was done using consecutive sampling method. Forty plasma samples of EOC subjects were included in this study. miR-200c expression was quantified using Reverse Transcriptase Quantitative Quantitative Polymerase Chain Reaction (RTqPCR) with miR-16 as the reference gene.RESULTS: The expression of miR-200c was significantly higher in the group of subjects with preoperative CA-125 levels >500 U/mL (p=0.009) than the group of subjects with preoperative CA-125 levels <500 U/mL. Subjects with higher miR-200c expression had lower survival rate than subjects with lower miR-200c expression, although not statistically significant.CONCLUSION: The miR-200c could be a promising biomarker for EOC. Further studies with larger sample sizes are needed to clarify the prognostic value of miR200c.KEYWORDS: miR-200c, epithelial ovarian cancer, prognosis, overall survival

Expression profiles of serum long non-coding RNA in ovarian cancer patients receiving platinum-containing chemotherapy

Abstract Background Long non-coding RNAs (lncRNAs) appear to be one of the key regulators of cellular signaling processes. According to several authors, they play a crucial role in the regulation of the antitumor immune response. Dysregulation of lncRNA profile is associated with carcinogenesis. Alteration of the lncRNA profile in ovarian cancer (OC) tumor tissue was shown. The aim of our study was to identify serum lncRNAs as potential biomarkers in ovarian cancer. Methods The study included 34 patients with verified ovarian cancer II-IV FIGO stage. Blood sampling was performed before treatment and after 3 courses of standard neoadjuvant (paclitaxel 175 mg/m² + carboplatin AUC 6 every 3 weeks) chemotherapy. To isolate free-circulating RNA from serum, the SileksMagNA-Direct magnetic particle kit was used. Analysis of the normalized expression of lncRNA MALAT, HOTAIR and PVT1 was carried out using qPCR method with normalization by 18S. We assessed the correlations between lncRNA levels and the patient age, tumor stage and CA-125 level. For statistical analysis, the ANOVA criterion (Statistika 13.0) was used. Results We have established strong correlations between the HOTAIR plasma level and age (p = 0.120) and CA-125 level (p = 0.082), and weak correlation with a relapse-free period duration (p = 0.167). The level of MALAT strongly correlated with age (p = 0.050) and with a relapse-free period duration (p = 0.014) and weakly correlated with the stage of ovarian cancer (p = 0.140). PVT1 expression did not reliably correlate with any of the studied clinical and biological parameters. Conclusion The revealed relationships between the levels of circulating MALAT and HOTAIR in the blood plasma of patients with OC require further study of these epigenetic regulators in OC carcinogenesis and chemoresistance. Free circulating lncRNA MALAT and HOTAIR, as an element of a liquid biopsy, are potential prognostic and predictive biomarkers for OC. Legal entity responsible for the study The authors. Funding RFBR (project number 19-315-50012). Disclosure All authors have declared no conflicts of interest.

Abstract DP-002: COMPARISON OF POTENTIAL OVARIAN CANCER BIOMARKERS BY MASS SPECTROMETRY-BASED PROTEOMIC ANALYSIS OF RESIDUAL PAP TEST FLUID, CERVICAL SWABS, AND TUMOR TISSUE FROM AN OVARIAN CANCER PATIENT

Abstract Early detection is the key to increased survival for women with ovarian cancer, yet a screening tool has yet to be developed that is adequately sensitive and specific enough for use in the general population. In contrast, screening for cervical cancer by Pap tests has been routinely performed for over 50 years. In the liquid-based Pap test, cells are collected from the cervix and placed into an alcohol-based fixative and then examined for abnormal cells. Since ovarian cancer cells have been observed in Pap tests, we reasoned that ovarian cancer peptide biomarkers may also be present. Our central hypothesis is that proteins shed by ovarian cancer cells can be detected during routine Pap tests by mass spectrometry (MS)-based proteomics. In particular, when collected at the time of cervical cancer Pap test screening, the alcohol-based Pap test fixative and cervical swabs are ideal for biomarker discovery since they are derived from a site near the ovarian cancer (i.e. proteins may be secreted or shed from the tumor and flow through the fallopian tube into the uterus and out the cervical opening). Recently, the fimbria of the fallopian tube have been suggested to be the true precursor to ovarian cancer, strengthening our hypothesis that ovarian cancer proteins will be found in the lower genital tract, perhaps even at early stages. To demonstrate the feasibility of using Pap tests as a biospecimen for proteomics, we previously examined the proteins present in residual Pap test fixative samples from women with normal cervical cytology by MS and described 152 proteins in the “Normal Pap Proteome.” The objective of this study was to identify and compare the proteins from three different sources from the same ovarian cancer patient: (i) the residual Pap test fixative, (ii) a Merocel swab of the cervix, and (iii) the primary ovarian cancer tumor tissue. Proteins were concentrated from the cell-free supernatant of the Pap test fixative or eluted from the swab, and then trypsin digested using the filter-aided sample preparation method. A total protein extract from the patient's tumor tissue was digested by standard in-solution trypsin digestion. The samples were run on 2D-liquid chromatography MS/MS, followed by bioinformatics integration. We identified over 5000 proteins total in the three samples. More than 2000 proteins were expressed in all three ovarian cancer samples, including several known ovarian cancer biomarkers such as CA125. By Scaffold analysis of the Gene Ontology nomenclature of the proteins, we classified the proteins by both cellular localization and biological processes. Additional matched samples from patients will be used to build a library of proteins and peptides that are specific to ovarian cancer for use in the development of targeted MS assays. We conclude that quantification of proteins from Pap test fixatives and cervical swabs will prove to be a rich source of biomarkers for ovarian cancer detection. Citation Format: Kristin L.M. Boylan, Anna C. Rogers, Melissa A. Geller, Peter A. Argenta, Timothy J. Griffin, and Amy P.N. Skubitz. COMPARISON OF POTENTIAL OVARIAN CANCER BIOMARKERS BY MASS SPECTROMETRY-BASED PROTEOMIC ANALYSIS OF RESIDUAL PAP TEST FLUID, CERVICAL SWABS, AND TUMOR TISSUE FROM AN OVARIAN CANCER PATIENT [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Research Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr DP-002.

Ascites-Derived Extracellular microRNAs as Potential Biomarkers for Ovarian Cancer.

Ovarian cancer as the most fatal gynecological malignancy is often manifested by excessive fluid accumulation known as ascites or effusion. Ascites-derived microRNAs (miRNAs) may be closely associated with ovarian cancer progression. However, our knowledge of their roles, altered expression, and clinical outcomes remained limited. In this study, large-scale expression profiling of 754 human miRNAs was performed using real-time quantitative polymerase chain reaction and 384-well TaqMan array human miRNA A and B cards to identify differentially expressed miRNAs between extracellular fraction of the ascitic fluid associated with high-grade serous ovarian carcinomas and control plasma. Of the 754 miRNAs, 153 were significantly differentially expressed relative to the controls. Expression of 7 individual miRNAs (miR-200a, miR-200b, miR-200c, miR-141, miR-429, miR-1290, and miR-30a-5p) was further validated in extended sample sets, including serous, endometrioid, and mucinous subtypes. All miR-200 family members and miR-1290 were conspicuously overexpressed, while miR-30a-5p was only weakly overexpressed. The ability of miRNAs expression to discriminate the pathological samples from the controls was strong. Receiver operating characteristic curve analyses found area under the curve (AUC) values of 1.000 for miR-200a, miR-200c, miR-141, miR-429, and miR-1290 and of AUC 0.996 and 0.885 for miR-200b and miR-30a-5p, respectively. Preliminary survival analyses indicated low expression level of miR-200b as significantly related to longer overall survival (hazard ratio [HR]: 0.25, mean survival 44 months), while high expression level was related to poor overall survival (HR: 4.04, mean survival 24 months). Our findings suggested that ascites-derived miRNAs should be further explored and evaluated as potential diagnostic and prognostic biomarkers for ovarian cancer.

Potential Biomarkers for Ovarian Cancer.

Potential Biomarkers for Ovarian Cancer.

Wide spectrum targeted metabolomics identifies potential ovarian cancer biomarkers

AimsDespite of almost a hundred years of research on cancer metabolism, the biological background of cancerogenesis and cancer-related reprogramming of metabolism remains not fully understood. In order to comprehensively and effectively diagnose and treat the deadliest diseases, the mechanisms underlying these diseases have to be discovered urgently. Among the gynecological malignancies, ovarian cancer is the most common cause of death. The aim of the study was to search for potential cancer-related differences in concentrations of metabolites and interactions between them in serum of women with ovarian cancer and benign ovarian tumor in comparison with healthy controls using targeted metabolomics. These metabolites might serve as biomarkers in the future. Main methodsWe used wide spectrum targeted metabolomics to evaluate serum concentrations of metabolites related to ovarian cancer and compared them against benign ovarian tumors and healthy controls. The measurements were performed using high performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry technique in highly-selective multiple reaction monitoring mode. Key findingsIn this study we confirmed our previous findings about the role of histidine and citrulline in ovarian cancer as well as we indicated new lipid compounds (lysoPC a C16:1, PC aa C32:2, PC aa C34:4 and PC aa C 36:6) potentially involved in cancer metabolism. SignificancesWe indicated interesting interactions between metabolites for further in-depth research which could potentially serve as clinically useful biomarkers in future. Moreover, the presented work attempts to visualize a possible 3D-network of relationships between the molecules found to be related to ovarian malignancy.

Identification of molecular biomarkers for ovarian cancer using computational approaches.

Ovarian cancer is one of the major causes of mortality among women. This is partly because of highly asymptomatic nature, lack of reliable screening techniques and non-availability of effective biomarkers of ovarian cancer. The recent availability of high-throughput data and consequently the development of network medicine approach may play a key role in deciphering the underlying global mechanism involved in a complex disease. This novel approach in medicine will pave the way in translating the new molecular insights into an effective drug therapy applying better diagnostic, prognostic and predictive tests for a complex disease. In this study, we performed reconstruction of gene co-expression networks with a query-based method in healthy and different stages of ovarian cancer to identify new potential biomarkers from the reported biomarker genes. We proposed 17 genes as new potential biomarkers for ovarian cancer that can effectively classify a disease sample from a healthy sample. Most of the predicted genes are found to be differentially expressed between healthy and diseased states. Moreover, the survival analysis showed that these genes have a significantly higher effect on the overall survival rate of the patient than the established biomarkers. The comparative analyses of the co-expression networks across healthy and different stages of ovarian cancer have provided valuable insights into the dynamic nature of ovarian cancer.

Detection of exosomal tyrosine receptor kinase B as a potential biomarker in ovarian cancer.

Ovarian cancer (OC) is a lethal disease diagnosed at advanced stages due to the lack of specific biomarkers. Tyrosine receptor kinase B (TrkB), which has recently been found to be related to OC progression, represents a promising potential biomarker for OC diagnosis and prognosis. The discovery of circulating exosomes as biomarkers for various diseases led us to explore exosomal TrkB in OC. Our previous study proved that the expression of TrkB was elevated in OC tissues. In this study, we focused on the detection of exosomal TrkB in OC. Exosomes were first gathered from three different OC cell lines' conditioned medium, serum samples of patients withOC as well as xenograft mice serum by serial centrifugation method. Then, we identified exosomes by transmission electron microscopy, NanoSight analysis, and expression of typical exosomal protein markers. The existence of TrkB in exosomes was measured by Western blot analysis, and the expression was detected by enzyme-linked immunosorbent assay. In this study, we demonstrated that exosomes could derive from OC cell lines, serum from OC xenograft nude mice, and clinical patients. Our study shows that serum exosomal TrkB may be considered a minimally invasive biomarker for OC.

RCP induces FAK phosphorylation and ovarian cancer cell invasion with inhibition by curcumin

Rab coupling protein (RCP) aggravates cancer cell metastasis and has been implicated in various cancer patient outcomes. Recently, we showed that RCP induces Slug expression and cancer cell invasion by stabilizing the β1 integrin protein. In the present study, we demonstrated that FAK is implicated in RCP-induced EGFR phosphorylation and ovarian cancer cell invasion with inhibition by curcumin. Ectopic expression of RCP induced FAK phosphorylation, which links β1 integrin with EGFR and participates in a positive regulation loop with EGFR. Interestingly, we observed for the first time that curcumin attenuates RCP-induced ovarian cancer cell invasion by blocking stabilization of β1 integrin and consequently inhibiting FAK and EGFR activation, providing potential biomarkers for ovarian cancer and therapeutic approaches for this deadly disease.

Elevated levels of serum nidogen-2 in esophageal squamous cell carcinoma.

Nidogen-2 (NID2), a secretory basement membrane protein, has been implicated as a potential biomarker in ovarian cancer and hepatocellular carcinoma. In this study, we aimed to investigate the utility of detecting serum NID2 levels for identification of esophageal squamous cell carcinoma (ESCC) patients and prediction of poor survival outcome. Using an in-house NID2 enzyme-linked immunosorbent assay (ELISA), serum samples from 101 ESCC patients and 50 healthy controls were screened for their NID2 levels. The serum NID2 levels in ESCC patients (median 24.4 μg/L) are significantly higher (p= 4.3e-09) than that of the healthy controls (median 15.85 μg/L). The receiver operating characteristic (ROC) curve demonstrated an area under the curve of 0.756. At the threshold of 17.95 μg/L, the sensitivity and specificity achieved are 0.76 and 0.63, respectively. Kaplan-Meier survival analysis revealed that patients with high serum NID2 levels (⩾ 32.6 μg/L) have significantly higher risk of death (HR = 1.984, 95% CI: 1.175-3.349; log-rank p-value = 0.012) compared to those with low serum NID2 levels (< 20.0 μg/L). In conclusion, we show that detecting the elevation of serum NID2 levels has potential diagnostic and prognostic value for ESCC patients.

Identification of Potential Biomarkers and Metabolic Profiling of Serum in Ovarian Cancer Patients Using UPLC/Q-TOF MS

Background/Aims: Ovarian cancer (OC) is a malignant neoplasm of the female reproductive system with a high mortality rate. Identifying useful biomarkers and clarifying the molecular pathogenesis of OC are critical for early diagnosis and treatment. The aim of the study was to identify candidate biomarkers and explore metabolic changes of OC. Methods: A two-stage design was used in our study, with a discovery cohort of OC cases (n = 30) and controls (n = 30) and an independent cohort of cases (n = 17) and controls (n = 18) for validation. The serum metabolic profiling was investigated by ultra-performance liquid chromatography and quadrupole time-of-fight mass spectrometry with positive electrospray ionization. Results: A total of 18 metabolites closely related to OC were identified in the discovery stage, of which 12 were confirmed in the validation cohort. Metabolic pathways in OC related to these biomarkers included fatty acid β-oxidation, phospholipid metabolism, and bile acid metabolism, which are closely related to the proliferation, invasion, and metastasis of cancer cells. Multiple logistic regression analysis of these metabolites showed that 2-piperidinone and 1-heptadecanoylglycerophosphoethanolamine were potential biomarkers of OC, with high sensitivity (96.7%), specificity (66.7%), and area under the receiver operating characteristic curve value (0.894). Conclusion: These findings provide insight into the pathogenesis pathogenesis of OC and may be useful for clinical diagnosis and treatment.

Evaluation of serum CCL18 as a potential biomarker for ovarian cancer.

Early detection and differentiation diagnosis of a pelvic mass (PM) is crucial in improving the prognosis of patients with epithelial ovarian cancer (EOC). C-C motif chemokine ligand 18 (CCL18) was reported as a chemokine-mediated tumor-related inflammation that can be detected in serum and may correlate with cancer patients' prognosis. We performed this study to investigate the relationship between CCL18 levels and clinical characteristics of EOC patients, and to explore their diagnostic and prognostic values. CCL18 serum concentrations were detected by ELISA in 187 patients with EOC, 126 patients with benign PMs, and 118 healthy controls. CCL18 serum levels were analyzed in the context of patients' clinicopathological information, and ROC analyses were performed to determine the effect of CCL18 on distinguishing benign and malignant PMs. The ability of CCL18 to serve as an EOC biomarker was compared with CA125. Further survival analyses were carried out to assess the prognostic value of CCL18 in EOC patients. Mean serum CCL18 levels were elevated in benign PM patients and were even higher in EOC patients than in healthy controls; furthermore, high CCL18 expression was associated with worse International Federation of Gynecology and Obstetrics (FIGO) staging and predicted a poorer survival of the patient. When compared with CA125, although the sensitivity and negative predictive values (NPV) of serum CCL18 were lower, its specificity and positive predictive values (PPV) were higher. Serum CCL18 was elevated in patients with EOC and could serve as a new tumor biomarker, which also predicted a poor survival of the patient.

Selected reaction monitoring approach for validating peptide biomarkers

We here describe a selected reaction monitoring (SRM)-based approach for the discovery and validation of peptide biomarkers for cancer. The first stage of this approach is the direct identification of candidate peptides through comparison of proteolytic peptides derived from the plasma of cancer patients or healthy individuals. Several hundred candidate peptides were identified through this method, providing challenges for choosing and validating the small number of peptides that might prove diagnostically useful. To accomplish this validation, we used 2D chromatography coupled with SRM of candidate peptides. We applied this approach, called sequential analysis of fractionated eluates by SRM (SAFE-SRM), to plasma from cancer patients and discovered two peptides encoded by the peptidyl-prolyl cis-trans isomerase A (PPIA) gene whose abundance was increased in the plasma of ovarian cancer patients. At optimal thresholds, elevated levels of at least one of these two peptides was detected in 43 (68.3%) of 63 women with ovarian cancer but in none of 50 healthy controls. In addition to providing a potential biomarker for ovarian cancer, this approach is generally applicable to the discovery of peptides characteristic of various disease states.

Abstract 446: Systematic discovery of biomarkers for ovarian cancer by using the Human Protein Atlas database

Abstract Purpose: The extensive accumulation of human protein expression datasets in normal and cancer tissues provides unique opportunities to perform systematic selection of tumor biomarkers. This study aims to discover biomarkers for ovarian cancer (OC) by data mining the Human Protein Atlas databases in a systematic manner. Design methods: The Human Protein Atlas website (HPA, www.proteinatlas.org) is a publicly available database with spatial distribution of 20,356 proteins in 44 different normal human tissues and 20 different types of cancers. It is ideal for biomarker discovery. SAS software version 9.4 was used to data mine HPA database. All the potential biomarkers should meet the following criteria: the protein have ≥ 75% high or medium expression in OC but have low or no expression in other types of cancers, and the protein have low or no expression in at least one type of tissues of ovary included in the HPA database, the overall expression in normal tissues is ≤ 40%. Then ELISA was used to test the diagnostic performance of some of the selected biomarkers. Results: Nineteen out of twenty different types of cancers included in the HPA database were studied in our study, carcinoid was excluded in the selection process due to the lack of proper normal control tissues. In general, PLAT might be a universal biomarker for 19 cancers. In total, 2,593 potential biomarkers for OC were selected. Ninety seven proteins out of 2,593 proteins might be OC-specific according to the available data. After an intensive manual search from the website, twelve proteins (STC1, MSLN, LSM3, WFDC2/HE4, ZNF2, CRIP3, XAF1, SLC35E2B, IFT88, ATP13A3, ZNF787 and TROAP) were selected for further research. Among them, WFDC2/HE4, MSLN have already been reported to have good diagnostic performance in OC by other researchers. ELISA was further used to test whether serum autoantibodies against PLAT or MSLN can distinguish 44 OC patients from 48 normal controls. The AUC of anti-PLAT and anti-MSLN were 0.783 (P &amp;lt; 0.001) and 0.666 (P = 0.006), respectively. Conclusions: HPA database have made systematic discovery of cancer biomarkers possible. PLAT and MSLN can distinguish OC from normal controls. Another 11 proteins have great potential to serve as OC biomarkers and further validation studies are warranted to test their diagnostic performance and whether these biomarkers are OC specific. Keywords: ovarian cancer, tumor associated antigen, big data, data mining, systematic discovery This study was supported by grants from the General Program of National Natural Science Foundation of China (No. 81172086 and No.81372371). We would also like to acknowledge the Border Biomedical Research Center (BBRC) Core facilities at The University of Texas at El Paso (UTEP) for their help, which were funded by NIH Grant (5G12MD007592). Citation Format: Jianxiang Shi, Hao Sun, Hongfei Zhang, Mengtao Xing, Jitian Li, Pei Li, Liping Dai, Chenglin Luo, Jian-Ying Zhang. Systematic discovery of biomarkers for ovarian cancer by using the Human Protein Atlas database. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 446.

New insight of soluble biomarkers of ovarian cancer

Ovarian cancer has the highest mortality rate among cancers of female reproductive system. Early stage of ovarian cancer shows no signs or asymptomatic and no effective screening approach is available. Soluble biomarkers represent the biomarkers existing and can be detected in the body fluid. The detection of soluble biomarkers possess the advantages of being relatively simple, minimal invasive, and low costs, thus they are very useful in screening, therapeutic response monitoring, and prognosis prediction of cancer. However, biomarkers used for ovarian cancer diagnosis are limited, and the overall sensitivity and specificity of the tests are still below clinical satisfaction currently. Thus, seeking for new ovarian cancer soluble biomarkers is current research focus. This paper discuses the features and diagnostic value of current and potential ovarian cancer biomarkers, the reasonable combination strategy in detection of ovarian cancer biomarkers in clinical practice is also discussed. (Chin J Lab Med, 2016, 39: 552-555) Key words: Ovarian neoplasms; Tumor markers, biological; Proteins

Current status on microRNAs as biomarkers for ovarian cancer.

Ovarian cancer (OC) is the most lethal gynecological malignancy in the Western world, and has a very poor prognosis, often due to late diagnosis and emergence of chemotherapy resistance. Therefore, there is an essential need for new diagnostic and prognostic markers that can improve and initiate more personalized treatment, eventually improving survival of the patients. MicroRNAs are small, non-coding RNA molecules, that post-transcriptionally regulate gene expression. Several studies have within the last decade shown that microRNAs are deregulated in OC and have potential as diagnostic and prognostic biomarkers for OC. Recently studies have also focused on microRNAs as predictors of chemotherapy responses and their potential as therapeutic targets. However, many of the published studies are difficult to interpret as a whole due to various methods of analysis. Future focus should be aimed at developing a general standardized analytical method, which can limit differences between studies thus allowing easier comparison across them. In addition, validation of studies in independent series that ideally should be histotype-specific is essential to determine the clinical role of microRNAs in different types of OC. In this review we summarize the current knowledge of microRNAs as potential biomarkers for OC, with focus on their clinical relevance.

MicroRNA: a new and promising potential biomarker for diagnosis and prognosis of ovarian cancer.

Epithelial ovarian cancer (EOC) is the leading cause of death among all gynecological malignancies. Despite the technological and medical advances over the past four decades, such as the development of several biological markers (mRNA and proteins biomarkers), the mortality rate of ovarian cancer remains a challenge because of its late diagnosis, which is specifically attributed to low specificities and sensitivities. Under this compulsive scenario, recent advances in expression biology have shifted in identifying and developing specific and sensitive biomarkers, such as microRNAs (miRNAs) for cancer diagnosis and prognosis. MiRNAs are a novel class of small non-coding RNAs that deregulate gene expression at the posttranscriptional level, either by translational repression or by mRNA degradation. These mechanisms may be involved in a complex cascade of cellular events associated with the pathophysiology of many types of cancer. MiRNAs are easily detectable in tissue and blood samples of cancer patients. Therefore, miRNAs hold good promise as potential biomarkers in ovarian cancer. In this review, we attempted to provide a comprehensive profile of key miRNAs involved in ovarian carcinoma to establish miRNAs as more reliable non-invasive clinical biomarkers for early detection of ovarian cancer compared with protein and DNA biomarkers.

STC2 overexpression mediated by HMGA2 is a biomarker for aggressiveness of high-grade serous ovarian cancer.

High-grade serous cancer (HGSC) is a lethal form of ovarian cancer due to invasion and early metastasis. Gain of epithelial-mesenchymal transition (EMT) contributes to the aggressiveness of HGSC. High-mobility gene groupA2 (HMGA2), an architectural transcription factor, plays a major role in HGSC through the regulation of EMT gene expression. Based on the gene profiling analysis, we found that the potent EMT gene, stanniocalcin2 (STC2), was highly correlated with HMGA2 expression. In the present study, we demonstrated that STC2 was directly regulated by HMGA2 at the transcriptional level. Overexpressing STC2 invitro directly enhanced cell migration and invasion. To investigate the correlation of STC2 and HMGA2 expression and the potential biomarker for ovarian cancer, three independent large cohorts of ovarian cancer (cohort 1=278, cohort 2=150 and cohort 3=95cases) were examined in the present study. The results showed that the expression of HMGA2 and STC2 was positively correlated. Furthermore, STC2 expression was significantly associated with tumor grade and histotype. HGSC had significantly higher levels of STC2 expression and was inversely correlated with patient survival. These findings suggested that STC2 is an important new biomarker that can be used for HGSC.