Ovarian cancer biomarkers: current options and future promise

Unlocking the potential of oncology biomarkers: advancements in clinical theranostics

INTRODUCTION

Cancer biomarkers have revolutionized the field of oncology by providing valuable insights into tumor changes and aiding in screening, diagnosis, prognosis, treatment prediction, and risk assessment. The emergence of "omic" technologies has enabled biomarkers to become reliable and accurate predictors of outcomes during cancer treatment.

CONTENT

In this review, we highlight the clinical utility of biomarkers in cancer identification and motivate researchers to establish a personalized/precision approach in oncology. By extending a multidisciplinary technology-based approach, biomarkers offer an alternative to traditional techniques, fulfilling the goal of cancer therapeutics to find a needle in a haystack.

SUMMARY AND OUTLOOK

We target different forms of cancer to establish a dynamic role of biomarkers in understanding the spectrum of malignancies and their biochemical and molecular characterization, emphasizing their prospective contribution to cancer screening. Biomarkers offer a promising avenue for the early detection of human cancers and the exploration of novel technologies to predict disease severity, facilitating maximum survival and minimum mortality rates. This review provides a comprehensive overview of the potential of biomarkers in oncology and highlights their prospects in advancing cancer diagnosis and treatment.

The pivotal role of long non-coding RNAs as potential biomarkers and modulators of chemoresistance in ovarian cancer (OC)

Ovarian cancer (OC) is a fatal gynecological disease that is often diagnosed at later stages due to its asymptomatic nature and the absence of efficient early-stage biomarkers. Previous studies have identified genes with abnormal expression in OC that couldn't be explained by methylation or mutation, indicating alternative mechanisms of gene regulation. Recent advances in human transcriptome studies have led to research on non-coding RNAs (ncRNAs) as regulators of cancer gene expression. Long non-coding RNAs (lncRNAs), a class of ncRNAs with a length greater than 200 nucleotides, have been identified as crucial regulators of physiological processes and human diseases, including cancer. Dysregulated lncRNA expression has also been found to play a crucial role in ovarian carcinogenesis, indicating their potential as novel and non-invasive biomarkers for improving OC management. However, despite the discovery of several thousand lncRNAs, only one has been approved for clinical use as a biomarker in cancer, highlighting the importance of further research in this field. In addition to their potential as biomarkers, lncRNAs have been implicated in modulating chemoresistance, a major problem in OC. Several studies have identified altered lncRNA expression upon drug treatment, further emphasizing their potential to modulate chemoresistance. In this review, we highlight the characteristics of lncRNAs, their function, and their potential to serve as tumor markers in OC. We also discuss a few databases providing detailed information on lncRNAs in various cancer types. Despite the promising potential of lncRNAs, further research is necessary to fully understand their role in cancer and develop effective strategies to combat this devastating disease.

Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis

OBJECTIVE

Ovarian cancer is a significant health issue with lasting impacts on the community. Despite recent advances in surgical, chemotherapeutic and radiotherapeutic interventions, they have had only marginal impacts due to an inability to identify biomarkers at an early stage. Biomarker discovery is challenging, yet essential for improving drug discovery and clinical care. Machine learning (ML) techniques are invaluable for recognising complex patterns in biomarkers compared to conventional methods, yet they can lack physical insights into diagnosis. eXplainable Artificial Intelligence (XAI) is capable of providing deeper insights into the decision-making of complex ML algorithms increasing their applicability. We aim to introduce best practice for combining ML and XAI techniques for biomarker validation tasks.

METHODS

We focused on classification tasks and a game theoretic approach based on Shapley values to build and evaluate models and visualise results. We described the workflow and apply the pipeline in a case study using the CDAS PLCO Ovarian Biomarkers dataset to demonstrate the potential for accuracy and utility.

RESULTS

The case study results demonstrate the efficacy of the ML pipeline, its consistency, and advantages compared to conventional statistical approaches.

CONCLUSION

The resulting guidelines provide a general framework for practical application of XAI in medical research that can inform clinicians and validate and explain cancer biomarkers.

Exosomes as crucial emerging tools for intercellular communication with therapeutic potential in ovarian cancer

More than two-thirds of epithelial ovarian cancer (EOC) patients are diagnosed at advanced stages due to the lack of sensitive biomarkers. Currently, exosomes are intensively investigated as non-invasive cancer diagnostic markers. Exosomes are nanovesicles released in the extracellular milieu with the potential to modulate recipient cells' behavior. EOC cells release many altered exosomal cargoes that exhibit clinical relevance to tumor progression. Exosomes represent powerful therapeutic tools (drug carriers or vaccines), posing a promising option in clinical practice for curing EOC in the near future. In this review, we highlight the importance of exosomes in cell–cell communication, epithelial–mesenchymal transition (EMT), and their potential to serve as diagnostic and prognostic factors, particularly in EOC.

The role of urine and serum biomarkers in the early detection of ovarian epithelial tumours

Ovarian cancer (OC) is one of the leading causes of gynaecological cancer mortality in women worldwide. If detected at an early stage (I, II), OC has a 90% 5-year survival rate; nevertheless, symptoms are often hidden, leading to late-stage (III, IV) diagnosis and a poor prognosis. The current diagnostic procedures, such as a pelvic exam, transvaginal ultrasound, CA-125 blood tests, serum HE4 tests and multivariate index assays (MIA), are insufficient. Sadly, surgery is frequently required to confirm a positive diagnosis. Therefore, there has been an increased interest in different biomarkers using a non-invasive test as a tool for the earlier diagnosis of OC to resolve the need for precise and non-invasive diagnostic methods. This review article aims to investigate how biomarkers influence early OC detection and to emphasise the role of using a combination of serum biomarkers panel rather than a single biomarker. In addition, this review provides insights into the current serum biomarkers, urine biomarkers and other emerging biomarkers in the early detection of OC for better specificity and sensitivity and to improve the overall survival (OS) rate.

Integrated Bioinformatics Analysis for Identification of the Hub Genes Linked with Prognosis of Ovarian Cancer Patients

BACKGROUND

One of the most usual gynecological state of tumor is ovarian cancer and is a major reason of gynecological tumor-related global mortality rate. There have been multiple risk elements related to ovarian cancer like the background of past cases associated with breast cancer or ovarian cancer, or excessive body weight issues, case history of smoking, and untimely menstruation or menopause. Because of unclear expressions, more than 70% of the ovarian cancer patient cases are determined during the early stage. Material and Methods. GSE38666, GSE40595, and GSE66957 were the three microarray datasets which were analyzed using GEO2R for screening the differentially expressed genes. GO, Kyoto Encyclopedia of Genes, and protein expression studies were performed for analysis of hub genes. Then, survival analysis was performed for all the hub genes.

RESULTS

From the dataset, a total of 199 differentially expressed genes (DEGs) were identified. Through the KEGG pathway study, it was noted that the DEGs are mainly linked with the AGE-RAGE signaling pathway, central carbon metabolism, and human papillomavirus infection. The survival analysis showed 4 highly expressed hub genes COL4A1, SDC1, CDKN2A, and TOP2A which correlated with overall survival in ovarian cancer patients. Moreover, the expression of the 4 hub genes was validated by the GEPIA database and the Human Protein Atlas.

CONCLUSION

The results have shown that all 4 hub genes were found to be upregulated in ovarian cancer tissues which predict poor prognosis in patients with ovarian cancer.

Aziz NH, Teik CK, Shafiee MN, Kampan NC. New Predictive Biomarkers for Ovarian Cancer

Ovarian cancer is the eighth-most common cause of death among women worldwide. In the absence of distinctive symptoms in the early stages, the majority of women are diagnosed in advanced stages of the disease. Surgical debulking and systemic adjuvant chemotherapy remain the mainstays of treatment, with the development of chemoresistance in up to 75% of patients with subsequent poor treatment response and reduced survival. Therefore, there is a critical need to revisit existing, and identify potential biomarkers that could lead to the development of novel and more effective predictors for ovarian cancer diagnosis and prognosis. The capacity of these biomarkers to predict the existence, stages, and associated therapeutic efficacy of ovarian cancer would enable improvements in the early diagnosis and survival of ovarian cancer patients. This review not only highlights current evidence-based ovarian-cancer-specific prognostic and diagnostic biomarkers but also provides an update on various technologies and methods currently used to identify novel biomarkers of ovarian cancer.

Diagnostic Value of Plasma Annexin A2 in Early-Stage High-Grade Serous Ovarian Cancer

Ovarian cancer (OC) is commonly diagnosed at advanced stage when prognosis is poor. Consequently, there is an urgent clinical need to identify novel biomarkers for early detection to improve survival. We examined the diagnostic value of the calcium phospholipid binding protein annexin A2 (ANXA2), which plays an important role in OC metastasis. Annexin A2 plasma levels in patients with high grade serous OC (n = 105), benign ovarian lesions (n = 55) and healthy controls (n = 143) were measured by ELISA. Annexin A2 levels were found to be significantly increased in patients with stage I (p < 0.0001) and stage IA (p = 0.0027) OC when compared to healthy controls. In the logistic regression models followed by receiver operating characteristics (ROC) curve analyses, plasma annexin A2 showed 46.7% sensitivity at 99.6% specificity in distinguishing stage IA OC patients from healthy controls and 75% sensitivity at 65.5% specificity in the diagnosis of stage IA versus benign ovarian tumors. In the diagnosis of stage IA OC versus normal controls, the combination of plasma annexin A2 and CA125 showed 80% sensitivity at 99.6% specificity (AUC = 0.970) which was significantly higher than for CA125 (53.3% sensitivity at 99.6% specificity; AUC = 0.891) alone. The diagnostic accuracy in distinguishing stage IA OC from benign ovarian disease when combining annexin A2 and CA125 (71.4% accuracy at 100% sensitivity) was almost twice as high compared to CA125 (37.1% accuracy at 100% sensitivity) alone. In conclusion, annexin A2 in combination with CA125 has potential as a biomarker for the early detection of OC and to predict malignancy in patients with ovarian lesions, warranting further investigations.

Current and Futuristic Roadmap of Ovarian Cancer Management: An Overview

Ovarian cancer (OC) is the most lethal gynecological malignancy among women worldwide. In most cases, it is diagnosed late at an advanced stage and does not respond well to existing therapies leading to its poor prognosis. In addition, other factors including epidemiological, complex histological diversity, multiple molecular alterations, and overlapping signaling pathways are also important contributors to poor disease outcome. Efforts have continued to develop a deeper understanding of the molecular pathogenesis and altered signaling nodes that provide hope for better clinical management through the development of novel approaches for early diagnosis, disease subtyping, prognosis, and therapy. In this chapter, we provide a detailed overview of OC and its histological subtypes and discuss prevalent molecular aberrations and active signaling pathways that drive OC progression. We also summarize various diagnostic and prognostic markers and therapeutic approaches currently being employed and discuss emerging findings that hold the potential to change the future course of OC management.

Long Noncoding RNA E2F4as Promotes Progression and Predicts Patient Prognosis in Human Ovarian Cancer

Simple Summary

LncRNA is a promising biomarker that predicts the prognosis of a variety of cancers, but the important role of E2F4antisense lncRNA in cancer remains unclear. Therefore, we decided to explore the role of E2F4as lncRNA in the blood of an ovarian cancer patient. We found that E2F4as was highly expressed in ovarian cancer patients, and that the higher the expression of E2F4as, the worse the patient’s prognosis. In addition, we observed that downregulation of E2F4as in ovarian cancer cells reduced cell proliferation, invasion and migration, decreased expression of EMT-related genes, and increased apoptosis. These findings suggest that E2F4as may be a predictive biomarker in the blood of ovarian cancer patients, and have shown the potential to promote tumor aggression through EMT-related mechanisms.

Abstract

(1) Background: LncRNAs could be a promising biomarker to predict the prognosis of various cancers. The significance of E2F4antisense lncRNA remains unclear in cancer. In this study, we examined the expression level of E2F4as in the serum of ovarian cancer patients and the functional role of E2F4as. (2) Methods: Serum samples were obtained from 108 OC patients and 32 normal patients to measure the expression of E2F4as in the serum. Ovarian cancer cells were used to investigate the role of E2F4as in cell proliferation, invasion, migration and apoptosis, and the expression of E2F4as was knocked down using RNA interference. In addition, E2F4as knockdown cell lines were used in in vivo experiments. (3) Results: The expression of E2F4as was significantly higher in the serum of OC patients than in that of control patients (p < 0.05). The knockdown of E2F4as in ovarian cancer cells led to a decrease in cell proliferation, invasion and migration and an increase in apoptosis. E2F4as knockdown also reduced the expression of epithelium–mesenchymal metastasis (EMT) genes. (4) Conclusion: These findings highlight the clinical significance of E2F4as in predicting the prognosis of OC patients and suggest its potential in promoting tumour aggressiveness by the regulation of EMT-related mechanisms.

MicroRNAs in ovarian cancer and recent advances in the development of microRNA-based biosensors

Ovarian cancer is the most aggressive of all gynaecological malignancies and is the leading cause of cancer-associated mortality worldwide.

Pre-operative Circulating Plasma Gelsolin Predicts Residual Disease and Detects Early Stage Ovarian Cancer

Ovarian cancer (OVCA) patients with suboptimal residual disease (RD) and advanced stages have poor survival. pGSN is an actin binding protein which protects OVCA cells from cisplatin-induced death. There is an urgent need to discover reliable biomarkers to optimize individualized treatment recommendations. 99 plasma samples with pre-determined CA125 were collected from OVCA patients and pGSN assayed using sandwich-based ELISA. Associations between CA125, pGSN and clinicopathological parameters were examined using Fisher’s exact test, T test and Kruskal Wallis Test. Univariate and multivariate Cox proportional hazard models were used to statistically analyze clinical outcomes. At 64 µg/ml, pGSN had sensitivity and specificity of 60% and 60% respectively, for the prediction of RD where as that of CA125 at 576.5 U/mL was 43.5% and 56.5% respectively. Patients with stage 1 tumor had increased levels of pre-operative pGSN compared to those with tumor stage >1 and healthy subjects (P = 0.005). At the value of 81 µg/mL, pGSN had a sensitivity and specificity of 75% and 78.4%, respectively for the detection of early stage OVCA. At the value of 0.133, the Indicator of Stage 1 OVCA (ISO1) provided a sensitivity of 100% at a specificity of 67% (AUC, 0.89; P < 0.001). In the multivariate Cox regression analysis, pGSN (HR, 2.00; CI, 0.99–4.05; P = 0.05) was an independent significant predictor of progression free survival (PFS) but not CA125 (HR, 0.68; CI, 0.41–1.13; P = 0.13). Pre-operative circulating pGSN is a favorable and independent biomarker for early disease detection, RD prediction and patients’ prognosis.

Safety and Outcome Measures of First-in-Human Intraperitoneal α Radioimmunotherapy With 212Pb-TCMC-Trastuzumab

PURPOSE

One-year monitoring of patients receiving intraperitoneal (IP) Pb-TCMC-trastuzumab to provide long-term safety and outcome data. A secondary objective was to study 7 tumor markers for correlation with outcome.

METHODS

Eighteen patients with relapsed intra-abdominal human epidermal growth factor receptor-2 expressing peritoneal metastases were treated with a single IP infusion of Pb-TCMC-trastuzumab, delivered <4 h after 4 mg/kg IV trastuzumab. Seven tumor markers were studied for correlation with outcome.

RESULTS

Six dose levels (7.4, 9.6, 12.6, 16.3, 21.1, 27.4 MBq/m) were well tolerated with early possibly agent-related adverse events being mild, transient, and not dose dependent. These included asymptomatic, abnormal laboratory values. No late renal, liver, cardiac, or other toxicity was noted up to 1 year. There were no clinical signs or symptoms of an immune response to Pb-TCMC-trastuzumab, and assays to detect an immune response to this conjugate were negative for all tested. Tumor marker studies in ovarian cancer patients showed a trend of decreasing Cancer antigen 72-4 (CA 72-4) aka tumor-associated glycoprotein 72 (TAG-72) and tumor growth with increasing administered radioactivity. Other tumor markers, including carbohydrate antigen (CA125), human epididymis protein 4 (HE-4), serum amyloid A (SAA), mesothelin, interleukin-6 (IL-6), and carcinoembryonic antigen (CEA) did not correlate with imaging outcome.

CONCLUSIONS

IP Pb-TCMC-trastuzumab up to 27 MBq/m seems safe for patients with peritoneal carcinomatosis who have failed standard therapies. Serum TAG-72 levels better correlated to imaging changes in ovarian cancer patients than the more common tumor marker, CA125.

Urine Biomarkers for the Early Detection of Ovarian Cancer - Are We There Yet?

Ovarian cancer affects around 7500 women in the United Kingdom every year. Despite this, there is no effective screening strategy or standard treatment for ovarian cancer. If diagnosed during stage I, ovarian cancer has a 90% 5-year survival rate; however, there is usually a masking of symptoms which leads to an often late-stage diagnosis and correspondingly poor survival rate. Current diagnostic methods are invasive and consist of a pelvic examination, transvaginal ultrasonography, and blood tests to detect cancer antigen 125 (CA125). Unfortunately, surgery is often still required to make a positive diagnosis. To address the need for accurate, specific, and non-invasive diagnostic methods, there has been an increased interest in biomarkers identified through non-invasive tests as tools for the earlier diagnosis of ovarian cancer. Although most studies have focused on the identification of biomarkers in blood, the ease of availability of urine and the high patient compliance rates suggest that it could provide a promising resource for the screening of patients for ovarian cancer.

Another Round of "Clue" to Uncover the Mystery of Complex Traits

A plethora of genetic association analyses have identified several genetic risk loci. Technological and statistical advancements have now led to the identification of not only common genetic variants, but also low-frequency variants, structural variants, and environmental factors, as well as multi-omics variations that affect the phenotypic variance of complex traits in a population, thus referred to as complex trait architecture. The concept of heritability, or the proportion of phenotypic variance due to genetic inheritance, has been studied for several decades, but its application is mainly in addressing the narrow sense heritability (or additive genetic component) from Genome-Wide Association Studies (GWAS). In this commentary, we reflect on our perspective on the complexity of understanding heritability for human traits in comparison to model organisms, highlighting another round of clues beyond GWAS and an alternative approach, investigating these clues comprehensively to help in elucidating the genetic architecture of complex traits.

An updated meta-analysis of the prognostic value of decreased E-cadherin expression in ovarian cancer

Decreased epithelial cadherin (E-cadherin) expression is hypothesized to be related to poor prognosis of ovarian cancer, but the predictive value is still inconsistent. We conducted an updated meta-analysis with a total of 16 studies enrolling 1720 patients to estimate the prognostic value of decreased E-cadherin expression in ovarian cancer. Reduced expression of E-cadherin was significantly associated to poor overall survival (HR = 1.74, 95% CI: 1.40–2.17) and progression-free survival (HR = 1.45, 95% CI: 1.12–1.86) with a large heterogeneity for overall survival. In addition, we found that decreased expression of E-cadherin was significantly correlated with International Federation of Gynecology and Obstetrics grade (HR = 3.74, 95% CI: 2.24–6.23), E-cadherin membranous (HR = 1.47, 95% CI: 1.01–2.14), pathologic grade (HR = 1.41, 95% CI: 1.01–1.97), residual tumor size (HR = 2.72, 95% CI: 1.99–3.72), and surgery (HR = 3.21, 95% CI: 1.19–8.67). Our finding suggests that decreased E-cadherin expression may be a predictor of poor ovarian cancer prognosis.

Upregulated microRNA-224 promotes ovarian cancer cell proliferation by targeting KLLN

Human epithelial ovarian cancer is a complex disease, with low 5-yr survival rate largely due to the terminal stage at diagnosis in most patients. MicroRNAs play critical roles during epithelial ovarian cancer progression in vivo and have also been shown to regulate characteristic of ovarian cancer cell line in vitro. Alterative microRNA-224 (microRNA-224) expression affects human epithelial ovarian cancer cell survival, apoptosis, and metastasis. However, people know little about the effects of microRNA-224 on epithelial ovarian cancer cell proliferation. In the current study, we found that the microRNA-224 expression level of human syngeneic epithelial ovarian cancer cells HO8910 (low metastatic ability) was lower than that of HO8910PM (high metastatic ability). Furthermore, microRNA-224 was confirmed to target KLLN in HO8910 and HO8910PM. The known KLLN downstream target cyclin A was regulated by microRNA-224 in HO8910 and HO8910PM. In addition, overexpression of microRNA-224 enhanced the proliferation abilities of HO8910 and knockdown of microRNA-224 suppressed the proliferation abilities of HO8910PM by KLLN-cyclin A pathway. Our results provide new data about microRNAs and their targets involved in proliferation of epithelial ovarian cancer cells by modulating the downstream signaling.

Mining the Human Proteome: Biomarker Discovery for Human Cancer and Metastases

As our knowledge of the mechanisms underlying cancer development and progression has increased, so too have more effective, less toxic, and targeted therapies begun to reach the clinic. However, the full impact of these clinical advances and the practical success of the emerging field of precision medicine are dependent on the discovery and validation of sensitive and accurate biomarkers that can enable appropriate and rigorous sample type and patient selection, reliable longitudinal monitoring of therapeutic efficacy, and even risk assessment and early detection. Within the context of this review, we examine state-of-the-art approaches to the discovery and validation of noninvasive cancer biomarkers, with a specific emphasis on those that are protein or protein-associated ones. We also review sample selection strategies, currently utilized proteomic approaches for both discovery and validation requirements, and data analysis standards. Finally, we provide examples of these elements of biomarker discovery and validation from our own biomarker research.

Fibulin-4 is associated with tumor progression and a poor prognosis in ovarian carcinomas

Background

Fibulin-4, a member of the fibulin family of extracellular glycoproteins, is implicated in the progressions of some cancers. However, no information has been available to date regarding the function of fibulin-4 in ovarian carcinoma progression.

Methods

In this study, fibulin-4 mRNA and protein expression in normal ovarian tissue, ovarian tumor, high invasive subclones and low invasive subclones were evaluated by immunohistochemistry and real time reverse transcriptase-polymerase chain reaction (RT-PCR). The serum levels of fibulin-4, cancer antigen 125 (CA-125) and cerbohydrate antigen 199 (CA19-9) in patients with ovarian tumor were measured by enzyme-linked immunosorbent assay and electrochemiluminescent immunoassay. To assess the angiogenic properties of fibulin-4, vascular endothelial growth factor (VEGF) expression and tumor microvessel density were analyzed in ovarian carcinoma by immunohistochemistry.

Results

Fibulin-4 expression was upregulated in ovarian carcinoma, and positively correlated with MVD and VEGF expression. Fibulin-4 overexpression was significantly associated with advanced stage, low differentiation, lymph node metastasis and poor prognosis in patients with ovarian cancer. The serum levels of fibulin-4, CA-125 and CA19-9 in patients with ovarian carcinoma were much higher than those with benign ovarian tumors and normal controls. Compared to CA-125 and CA19-9, fibulin-4 had better diagnostic sensitivity and specificity.

Conclusions

Fibulin-4 is a novel gene that is found overexpressed in ovarian cancer and associated with poor prognostic clinicopathologic features. This study shows that fibulin-4 may serve as a new prognostic factor and as a potential therapeutic target for patients with ovarian cancer in the future.

Overexpression of EFEMP1 correlates with tumor progression and poor prognosis in human ovarian carcinoma

Objective

This study was to explore the role of EFEMP1 in ovarian tumor progression and its relationship with prognosis of ovarian carcinoma.

Methods

EFEMP1 mRNA and protein expressions in normal ovarian tissue, ovarian tumor, high invasive subclones and low invasive subclones were evaluated by immunohistochemistry and real time RT-PCR. Serum EFEMP1 levels in patients with ovarian tumor were measured by ELISA assay. To assess the angiogenic properties of EFEMP1, VEGF and tumor microvessel density were analyzed in ovarian carcinoma by immunohistochemistry.

Results

EFEMP1 expression was up-regulated in ovarian carcinoma, positively correlated with MVD and VEGF, and its overexpression and high serum levels were significantly associated with high stage, low differentiation, lymph node metastasis and poor prognosis of ovarian cancer. EFEMP1 expression was also found to be over-expressed in the highly invasive subclones compared with the low invasive subclones.

Conclusion

EFEMP1 is a newly identified gene over-expressed in ovarian cancer, associated with poor clinicopathologic features and promotes angiogenesis. This study shows that EFEMP1 may serve as a new prognostic factor and a therapeutic target for patients with ovarian cancer in the future.

Candidate microRNA biomarkers in human epithelial ovarian cancer: systematic review profiling studies and experimental validation

Despite advances in detection and therapy, epithelial ovarian cancer (EOC) still represents the most lethal gynecologic malignancy in women worldwide. The high mortality of EOC is mainly due to late-stage diagnosis for more than 70% of patients. There is an urgent need to search for specific and sensitive biomarkers for early diagnosis of EOC. Recently, the cumulative data indicated an essential role for microRNA (miRNA), a class of small non-coding RNAs targeting multiple mRNAs and triggering translation repression and/or RNA degradation, in ovarian caner carcinogenesis and progression. Here, we reviewed the published miRNA expression profiling studies that compared the miRNA expression profiles between EOC tissues or cell lines and normal ovarian tissues or benign ovarian tumor or human primary cultured ovarian surface epithelial cells. A miRNA ranking system that takes the number of comparisons in agreement and direction of differential expression into the consideration was devised and used. Finally, five promising differentially miRNAs (miR-200a, miR-100, miR-141, miR-200b, and miR-200c) were reported with the consistent direction in four or more studies. MiR-200a, miR-200b, miR-200c, and miR-141, all of them belong to miR-200 family, were reported with consistently up-regulated in at least 4 studies, whereas miR-100 was reported with down-regulated in 4 studies. Furthermore, we validated these miRNAs in a clinical setting using qRT-PCR and their dysregulations in EOC tissues confirmed the findings. Conclusively, the five most consistently expressed miRNAs might provide some clues of the potential biomarkers in EOC. Further mechanistic and precise validation studies are needed for their clinical significances and roles in the progression of EOC.

Apolipoprotein concentrations are elevated in malignant ovarian cyst fluids suggesting that lipoprotein metabolism is dysregulated in epithelial ovarian cancer

SELDI-TOF MS analysis of ovarian cyst fluids revealed that peaks m/z 8696 and 8825 discriminate malignant, borderline, and benign tumors. These peaks correspond to isoforms of apoA2. ELISA demonstrates that apoA1, A2, B, C2, C3, and E cyst fluid concentrations are uncorrelated and higher in malignant ovarian tumors, but only apoA2, apoE, and age are independent classifiers of malignant ovarian tumors, yielding 55.1% sensitivity, 95% specificity, and 88.1% accuracy to discern malignant from benign and borderline tumors. These data suggest that lipoprotein metabolism is dysregulated in ovarian cancer and that apoA2 and apoE warrant further investigation as ovarian tumor biomarkers.

Assessment of the argyrophilic nucleolar organizer region area/nucleus ratio in ovarian serous epithelial adenomas, borderline tumors and cancers

INTRODUCTION

There is a need to assess the value of the novel potentially useful biomarkers in ovarian tumors. The aim of study was to assess the value of sAgNOR analysis in ovarian serous epithelial tumors.

MATERIAL AND METHODS

The analysis was performed in ovaries from 113 patients treated operatively due to serous ovarian tumors (30 adenomas, 14 borderline tumors and 69 cancers). After silver staining of paraffin specimens from surgery, sAgNOR in tumor cells was analyzed. Additionally, the value of the argyrophilic nucleolar organizer region area/nucleus ratio (sAgNOR) in the prediction of disease-free survival (DFS) and overall survival (OS) in 52 patients with serous ovarian cancer with complete follow-ups in November 2009 was evaluated. Age, grading, radicality of surgery and FIGO staging were analyzed as additional factors.

RESULTS

SAGNOR IN ADENOMAS, BORDERLINE TUMORS AND CANCERS WAS IN THE FOLLOWING RANGES: (0.73 ±0.23) × 10(6), (0.81 ±0.18) × 10(6) and (0.96 ±0.33) × 10(6) [AgNOR/cm(2)] respectively. In cancers from G1 to G3 sAgNOR was (1.02 ±0.32) × 10(6) (G1), (0.98 ±0.37) × 10(6) (G2) and (0.82 ±0.24) × 10(6) (G3) [AgNOR/cm(2)] respectively. In univariate analysis, but not in multivariate analysis, staging negatively correlated with better DFS and OS. sAgNOR, age of patients, grading and radicality of surgery were not associated with DFS or OS in either univariate or multivariate analysis.

CONCLUSIONS

sAgNOR analysis is not sufficient to precisely characterize cellular kinetics in serous ovarian tumors, and the analysis of sAgNOR, mAgNOR and pAgNOR should be performed commonly. The prognostic significance of sAgNOR in patients with serous ovarian cancer was not proven.

HtrA3 Is Downregulated in Cancer Cell Lines and Significantly Reduced in Primary Serous and Granulosa Cell Ovarian Tumors

Objective. The high temperature requirement factor A3 (HtrA3) is a serine protease homologous to bacterial HtrA. Four human HtrAs have been identified. HtrA1 and HtrA3 share a high degree of domain organization and are downregulated in a number of cancers, suggesting a widespread loss of these proteases in cancer. This study examined how extensively the HtrA (HtrA1-3) proteins are downregulated in commonly used cancer cell lines and primary ovarian tumors.

Methods. RT-PCR was applied to various cancer cell lines (n=17) derived from the ovary, endometrium, testes, breast, prostate, and colon, and different subtypes of primary ovarian tumors [granulosa cell tumors (n=19), mucinous cystadenocarcinomas (n=6), serous cystadenocarcinomas (n=8)] and normal ovary (n = 9). HtrA3 protein was localized by immunohistochemistry.

Results. HtrA3 was extensively downregulated in the cancer cell lines examined including the granulosa cell tumor-derived cell lines. In primary ovarian tumors, the HtrA3 was significantly lower in serous cystadenocarcinoma and granulosa cell tumors. In contrast, HtrA1 and HtrA2 were expressed in all samples with no significant differences between the control and tumors. In normal postmenopausal ovary, HtrA3 protein was localized to lutenizing stromal cells and corpus albicans. In serous cystadenocarcinoma, HtrA3 protein was absent in the papillae but detected in the mesenchymal cyst wall.

Conclusion. HtrA3 is more extensively downregulated than HtrA1-2 in cancer cell lines. HtrA3, but not HtrA1 or HtrA2, was decreased in primary ovarian serous cystadenocarcinoma and granulosa cell tumors. This study provides evidence that HtrA3 may be the most relevant HtrA associated with ovarian malignancy.

Serum vascular endothelial growth factor (VEGF-C) as a diagnostic and prognostic marker in patients with ovarian cancer

VEGF-C is regarded as one of the most efficient factors in regulating lymphangiogenesis. The aim of this study was to better understand the role of VEGF-C in the progression of ovarian cancer and to assess its diagnostic and prognostic significance. A total of 109 patients with ovarian cancer, 76 patients with benign ovarian diseases, and 50 healthy controls were recruited in this study. Serum levels of VEGF-C were determined by ELISA method. The results showed that serum levels of VEGF-C were significantly higher in the patients with ovarian cancer than those with benign ovarian diseases and healthy controls (P<0.01). Serum level of VEGF-C was correlated with FIGO stage, lymph node metastasis, tumor resectability, and survival of the patients (P<0.05). The areas of receiver operating curves of VEGF-C were higher than those of CA125 in different screening groups. Analysis using the Kaplan-meier method indicated that patients with high VEGF-C had significantly shorter overall survival time than those with low VEGF-C (P<0.0001). In a multivariate analysis along with clinical prognostic parameters, serum VEGF-C was identified as an independent adverse prognostic variable for overall survival. These results indicated that serum VEGF-C may be a clinically useful indicator for diagnostic and prognostic evaluation in ovarian cancer patients.

MicroRNA expression in ovarian carcinoma and its correlation with clinicopathological features

Background

MicroRNA (miRNA) expression is known to be deregulated in ovarian carcinomas. However, limited data is available about the miRNA expression pattern for the benign or borderline ovarian tumors as well as differential miRNA expression pattern associated with histological types, grades or clinical stages in ovarian carcinomas. We defined patterns of microRNA expression in tissues from normal, benign, borderline, and malignant ovarian tumors and explored the relationship between frequently deregulated miRNAs and clinicopathologic findings, response to therapy, survival, and association with Her-2/neu status in ovarian carcinomas.

Methods

We measured the expression of nine miRNAs (miR-181d, miR-30a-3p, miR-30c, miR-30d, miR-30e-3p, miR-368, miR-370, miR-493-5p, miR-532-5p) in 171 formalin-fixed, paraffin-embedded ovarian tissue blocks as well as six normal human ovarian surface epithelial (HOSE) cell lines using Taqman-based real-time PCR assays. Her-2/neu overexpression was assessed in ovarian carcinomas (n = 109 cases) by immunohistochemistry analysis.

Results

Expression of four miRNAs (miR-30c, miR-30d, miR-30e-3p, miR-370) was significantly different between carcinomas and benign ovarian tissues as well as between carcinoma and borderline tissues. An additional three miRNAs (miR-181d, miR-30a-3p, miR-532-5p) were significantly different between borderline and carcinoma tissues. Expression of miR-532-5p was significantly lower in borderline than in benign tissues. Among ovarian carcinomas, expression of four miRNAs (miR-30a-3p, miR-30c, miR-30d, miR-30e-3p) was lowest in mucinous and highest in clear cell samples. Expression of miR-30a-3p was higher in well-differentiated compared to poorly differentiated tumors (P = 0.02), and expression of miR-370 was higher in stage I/II compared to stage III/IV samples (P = 0.03). In multivariate analyses, higher expression of miR-181d, miR-30c, miR-30d, and miR-30e-3p was associated with significantly better disease-free or overall survival. Finally, lower expression of miR-30c, miR-30d, miR-30e-3p and miR-532-5p was significantly associated with overexpression of Her-2/neu.

Conclusions

Aberrant expression of miRNAs is common in ovarian tumor suggesting involvement of miRNA in ovarian tumorigenesis. They are associated with histology, clinical stage, survival and oncogene expression in ovarian carcinoma.

Prognostic biomarkers in ovarian cancer

Epithelial ovarian cancer (EOC) remains the most lethal gynecological malignancy despite several decades of progress in diagnosis and treatment. Taking advantage of the robust development of discovery and utility of prognostic biomarkers, clinicians and researchers are developing personalized and targeted treatment strategies. This review encompasses recently discovered biomarkers of ovarian cancer, the utility of published prognostic biomarkers for EOC (especially biomarkers related to angiogenesis and key signaling pathways), and their integration into clinical practice.

Programmable bio-nano-chip systems for serum CA125 quantification: toward ovarian cancer diagnostics at the point-of-care

Point-of-care (POC) implementation of early detection and screening methodologies for ovarian cancer may enable improved survival rates through early intervention. Current laboratory-confined immunoanalyzers have long turnaround times and are often incompatible with multiplexing and POC implementation. Rapid, sensitive, and multiplexable POC diagnostic platforms compatible with promising early detection approaches for ovarian cancer are needed. To this end, we report the adaptation of the programmable bio-nano-chip (p-BNC), an integrated, microfluidic, and modular (programmable) platform for CA125 serum quantitation, a biomarker prominently implicated in multimodal and multimarker screening approaches. In the p-BNCs, CA125 from diseased sera (Bio) is sequestered and assessed with a fluorescence-based sandwich immunoassay, completed in the nano-nets (Nano) of sensitized agarose microbeads localized in individually addressable wells (Chip), housed in a microfluidic module, capable of integrating multiple sample, reagent and biowaste processing, and handling steps. Antibody pairs that bind to distinct epitopes on CA125 were screened. To permit efficient biomarker sequestration in a three-dimensional microfluidic environment, the p-BNC operating variables (incubation times, flow rates, and reagent concentrations) were tuned to deliver optimal analytical performance under 45 minutes. With short analysis times, competitive analytical performance (inter- and intra-assay precision of 1.2% and 1.9% and limit of detection of 1.0 U/mL) was achieved on this minisensor ensemble. Furthermore, validation with sera of patients with ovarian cancer (n = 20) showed excellent correlation (R(2) = 0.97) with gold-standard ELISA. Building on the integration capabilities of novel microfluidic systems programmed for ovarian cancer, the rapid, precise, and sensitive miniaturized p-BNC system shows strong promise for ovarian cancer diagnostics.

Protein biomarkers of ovarian cancer: the forest and the trees

The goal of effective population-based screening for ovarian cancer remains elusive despite intense efforts aimed at improving upon biomarker and imaging modalities. While dozens of potential serum biomarkers for ovarian cancer have been identified in recent years, none have yet overcome the limitations that have hindered the clinical use of CA-125. Avenues of opportunity in biomarker development are emerging as investigators are beginning to appreciate the significance of remote, as well as local or regional, sources of biomarkers in the construction of diagnostic panels, as well as the importance of evaluating biomarkers in prediagnostic settings. As the list of candidate biomarkers of ovarian cancer continues to grow, refinements in the methods through which specific proteins are selected for further development as components of diagnostic panels are desperately sought. Such refinements must take into account both the bioinformatic and biological significance of each candidate. Approaches incorporating these considerations may potentially overcome the challenges to early detection posed by the histological heterogeneity of ovarian cancer. Here, we review the recent progress achieved in efforts to develop diagnostic biomarker panels for ovarian cancer and discuss the challenges that remain.

Impact of expression differences of kallikrein-related peptidases and of uPA and PAI-1 between primary tumor and omentum metastasis in advanced ovarian cancer

BACKGROUND

Primary tumor levels of serine proteases of the kallikrein-related peptidases (KLK) family as well as urokinase-type plasminogen activator (uPA) and its inhibitor PAI-1 impact disease course in ovarian cancer. The changes in levels of these factors from primary tumor to omentum metastasis ('level differentials') could thus be associated with metastastic processes.

PATIENTS AND METHODS

Protein levels of seven tissue KLK (KLK5-8, 10, 11, 13), uPA, and PAI-1 were determined in extracts of primary tumor tissue and corresponding omentum metastasis of 54 ovarian cancer patients.

RESULTS

Higher level differentials of KLK5-8, 10-11, and uPA were associated with residual tumor >10 mm. Residual tumor and larger level differentials of KLK5-7, 10, and uPA were associated with disease progression in the whole cohort. Remarkably, level differentials of KLK5-8 and 10-11 strongly impacted disease progression even in patients with residual tumor mass ≤10 mm; hence, the observed impact of level differentials in KLK5-7 and 10 on disease progression was not simply attributable to their association with surgical success.

CONCLUSION

Since they impact both surgical outcome and survival in advanced ovarian cancer, measurement of level differentials could support clinical decisions on surgical and systemic therapy or help in patient selection for novel targeted therapies.

Targeting the epidermal growth factor receptor in epithelial ovarian cancer: current knowledge and future challenges

The epidermal growth factor receptor is overexpressed in up to 60% of ovarian epithelial malignancies. EGFR regulates complex cellular events due to the large number of ligands, dimerization partners, and diverse signaling pathways engaged. In ovarian cancer, EGFR activation is associated with increased malignant tumor phenotype and poorer patient outcome. However, unlike some other EGFR-positive solid tumors, treatment of ovarian tumors with anti-EGFR agents has induced minimal response. While the amount of information regarding EGFR-mediated signaling is considerable, current data provides little insight for the lack of efficacy of anti-EGFR agents in ovarian cancer. More comprehensive, systematic, and well-defined approaches are needed to dissect the roles that EGFR plays in the complex signaling processes in ovarian cancer as well as to identify biomarkers that can accurately predict sensitivity toward EGFR-targeted therapeutic agents. This new knowledge could facilitate the development of rational combinatorial therapies to sensitize tumor cells toward EGFR-targeted therapies.

Three-dimensional ovarian organ culture as a tool to study normal ovarian surface epithelial wound repair

Ovarian cancers are primarily derived from a single layer of epithelial cells surrounding the ovary, the ovarian surface epithelium (OSE). Ovarian surface proliferation is associated with ovulation and has been suggested to play a role in ovarian surface transformation and cancer progression. Aspects of ovarian surface repair after ovulation include proliferation, migration, and surface regeneration. To study ovarian surface repair, an organ culture system was developed that supports the proliferation, encapsulation, and repair of an artificially wounded surface. Wounded mouse ovaries embedded into an alginate hydrogel matrix have normal OSE cells as demonstrated by expression of cytokeratin 8, vimentin, N-cadherin, and a lack of E-cadherin. Normal OSE cells began proliferating and migrating around wounded surfaces after 1 d of culture. Organ cultures were propagated in medium supplemented with BSA and fetal bovine serum to determine optimal growth conditions. BSA cultured organs had OSE that proliferated significantly more than controls until d 4, whereas fetal bovine serum cultured organs had significantly more surface area encapsulated by OSE. Overall, a three-dimensional ovarian organ culture supports the growth of normal OSE in response to artificial wounding and provides a novel system for investigating wound repair as it relates to the possible role of ovulation and ovarian cancer.

The chemiluminescence based Ziplex automated workstation focus array reproduces ovarian cancer Affymetrix GeneChip expression profiles

Background

As gene expression signatures may serve as biomarkers, there is a need to develop technologies based on mRNA expression patterns that are adaptable for translational research. Xceed Molecular has recently developed a Ziplex^® technology, that can assay for gene expression of a discrete number of genes as a focused array. The present study has evaluated the reproducibility of the Ziplex system as applied to ovarian cancer research of genes shown to exhibit distinct expression profiles initially assessed by Affymetrix GeneChip^® analyses.

Methods

The new chemiluminescence-based Ziplex^® gene expression array technology was evaluated for the expression of 93 genes selected based on their Affymetrix GeneChip^® profiles as applied to ovarian cancer research. Probe design was based on the Affymetrix target sequence that favors the 3' UTR of transcripts in order to maximize reproducibility across platforms. Gene expression analysis was performed using the Ziplex Automated Workstation. Statistical analyses were performed to evaluate reproducibility of both the magnitude of expression and differences between normal and tumor samples by correlation analyses, fold change differences and statistical significance testing.

Results

Expressions of 82 of 93 (88.2%) genes were highly correlated (p < 0.01) in a comparison of the two platforms. Overall, 75 of 93 (80.6%) genes exhibited consistent results in normal versus tumor tissue comparisons for both platforms (p < 0.001). The fold change differences were concordant for 87 of 93 (94%) genes, where there was agreement between the platforms regarding statistical significance for 71 (76%) of 87 genes. There was a strong agreement between the two platforms as shown by comparisons of log₂ fold differences of gene expression between tumor versus normal samples (R = 0.93) and by Bland-Altman analysis, where greater than 90% of expression values fell within the 95% limits of agreement.

Conclusion

Overall concordance of gene expression patterns based on correlations, statistical significance between tumor and normal ovary data, and fold changes was consistent between the Ziplex and Affymetrix platforms. The reproducibility and ease-of-use of the technology suggests that the Ziplex array is a suitable platform for translational research.