The early detection of ovarian cancer: from traditional methods to proteomics. Can we really do better than serum CA-125?

Biomarkers in Cancer Detection, Diagnosis, and Prognosis

Biomarkers are vital in healthcare as they provide valuable insights into disease diagnosis, prognosis, treatment response, and personalized medicine. They serve as objective indicators, enabling early detection and intervention, leading to improved patient outcomes and reduced costs. Biomarkers also guide treatment decisions by predicting disease outcomes and facilitating individualized treatment plans. They play a role in monitoring disease progression, adjusting treatments, and detecting early signs of recurrence. Furthermore, biomarkers enhance drug development and clinical trials by identifying suitable patients and accelerating the approval process. In this review paper, we described a variety of biomarkers applicable for cancer detection and diagnosis, such as imaging-based diagnosis (CT, SPECT, MRI, and PET), blood-based biomarkers (proteins, genes, mRNA, and peptides), cell imaging-based diagnosis (needle biopsy and CTC), tissue imaging-based diagnosis (IHC), and genetic-based biomarkers (RNAseq, scRNAseq, and spatial transcriptomics).

Affinity-based electrochemical biosensor with antifouling properties for detection of lysophosphatidic acid, a promising early-stage ovarian cancer biomarker

Electrochemical techniques are considered to be highly sensitive, capable of fast response and can be easily miniaturized, properties which can aid with regard to the fabrication of compact point-of-care medical devices; however, the main challenge in developing such a tool is overcoming a ubiquitous, problematic phenomenon known as non-specific adsorption (NSA). NSA is due to the fouling of non-target molecules in the blood on the recognition surface of the device. To overcome NSA, we have developed an affinity-based electrochemical biosensor using medical-grade stainless steel electrodes and following a unique and novel strategy using silane-based interfacial chemistry to detect lysophosphatidic acid (LPA), a highly promising biomarker, which was found to be elevated in 90 % of stage I OC patients and gradually increases as the disease progresses to later stages. The biorecognition surface was developed using the affinity-based gelsolin-actin system, which was previously investigated by our group to detect LPA using fluorescence spectroscopy. We demonstrate the capability of this label-free biosensor to detect LPA in goat serum with a detection limit of 0.7 µM as a proof-of-concept for the early diagnosis of ovarian cancer.

Diagnostic performance of IOTA SR and O-RADS combined with CA125, HE4, and risk of malignancy algorithm to distinguish benign and malignant adnexal masses

PURPOSE

To compare the diagnostic performance of International Ovarian Tumour Analysis Simple Rules (IOTA SR) and Ovarian-Adnexal Reporting and Data System (O-RADS), and to analyse whether combining IOTA SR and O-RADS with the biomarkers cancer antigen 125 (CA125), human epididymis protein 4 (HE4), and risk of malignancy algorithm (ROMA) further improves diagnostic performance in women with different menopause status.

METHODS

This study retrospectively included patients with ovarian adnexal masses confirmed by surgical pathology between September 2021 and February 2022. The area under the curve (AUC), sensitivity, and specificity were calculated to evaluate the diagnostic efficacy of IOTA SR, O-RADS, and their combination with CA125, HE4, and ROMA.

RESULTS

This study included 1,179 ovarian adnexal masses. In all women, the AUC of IOTA SR was comparable to O-RADS (0.879 vs. 0.889, P = 0.361), and O-RADS had a significantly higher sensitivity than IOTA SR (95.77 % vs. 87.32 %, P < 0.001). In premenopausal women, O-RADS had a significantly higher AUC than other diagnostic strategies (all P < 0.05), and the sensitivity, specificity, and accuracy were 93.33 %, 84.74 %, and 85.59 %, respectively. In postmenopausal women, IOTA SR + ROMA had a significantly higher AUC than other diagnostic strategies (all P < 0.05), and the sensitivity, specificity, and accuracy were 85.37 %, 93.88 %, and 90.00 %, respectively.

CONCLUSIONS

Our study supports the high diagnostic value of IOTA SR or O-RADS alone in all women, and O-RADS was more sensitive than IOTA SR. In premenopausal women, O-RADS had the highest diagnostic value. In postmenopausal women, IOTA SR outperformed O-RADS, and IOTA SR + ROMA had the highest diagnostic value.

Peritoneal Tuberculosis With Raised Cancer Antigen 125 (CA-125) in a Post-partum Woman: A Case Report

Peritoneal tuberculosis is a common cause of ascites in areas endemic to Mycobacterium tuberculosis. The presentation of tuberculous ascites can mimic ovarian malignancy when it is associated with elevated cancer antigen 125 (CA-125) levels. We hereby discuss a case of a four months post-partum female patient who presented with gradual abdominal distension and was diagnosed with peritoneal tuberculosis after proper evaluation. She was started on anti-tubercular therapy and the treatment was successful. This case report highlights the importance of considering peritoneal tuberculosis as a differential diagnosis in cases of ascites with raised serum CA-125 levels in a Mycobacterium tuberculosis endemic region.

Evaluation of HE4 as a prognostic biomarker in uterine cervical cancer. Cancer Treat Res Commun 2023;34:100672. [PMID: 36525756 DOI: 10.1016/j.ctarc.2022.100672]

INTRODUCTION

Uterine cervical cancer (UCC) is the fourth most common health problem worldwide among women. Currently available biomarkers CA125, CA199, and CEA for diagnosis or prognostic evaluation of UCC have not got widespread acceptance.

METHOD

Whole blood samples of 64 patients with UCC were collected along with 63 healthy females and tested for serum levels of HE4 (sHE4). A cut-off value for positive result 64.0 pmol/L was set. Statistical analysis of different clinical variables was done.

RESULT

Serum level of HE4 has a significant role in the diagnosis of uterine cervical cancer. Its level increases with age, higher parity (P < 0.05), stage (P < 0.16), tumor size, and parametrial invasion. Negative result was seen with vaginal invasion, lymph node involvement & cases which had recurrence. Various histological types showed variable results. So the serum level of HE4 (sHE) level may play a role in the diagnosis & therapeutic monitoring of UCC. But the prognostic evaluation needs further studies.

CONCLUSION

sHE4 is useful in the diagnosis of cervical cancer, but its prognostic significance is under the question marks. It may be associated with higher values in higher stages. Higher parity of the patient is associated with higher level of HE4 in UCC.

Diagnostic and prognostic role of circulating neutrophil extracellular trap markers and prekallikrein in patients with high-grade serous ovarian cancer

Objective

Tumor-promoting inflammation is among the hallmarks of cancer. Prekallikrein is among the acute-phase reactants in the inflammatory response; moreover, neutrophils release nuclear contents into the extracellular space to create neutrophil extracellular traps (NET). We aimed to investigate the diagnostic and prognostic utilities of circulating plasma NET markers and prekallikrein for high-grade serous ovarian cancer (HGSOC).

Methods

Circulating levels of three NET markers (histone-DNA complex, cell-free DNA, and neutrophil elastase) and prekallikrein were measured in 75 patients with HGSOC and 23 healthy controls. We used an area under the receiver operating characteristic curve (AUC) analysis to investigate their diagnostic and prognostic utilities for HGSOC.

Results

Compared with healthy controls, patients with HGSOC showed significantly higher levels of the three NET markers and prekallikrein. Patients with advanced-stage HGSOC showed significantly higher levels of the cell-free DNA (87.4 vs. 79.5 ng/ml; P = 0.013), compared with those with early-stage HGSOC. Further, the levels of histone-DNA complex, neutrophil elastase, and prekallikrein did not significantly differ according to the cancer stage. All markers showed significant diagnostic utility. Notably, a logistic regression-based model that comprised all four markers showed the strongest diagnostic power (AUC, 0.966; 95% confidence interval [CI], 0.933-1.000). Specifically, neutrophil elastase was identified as an independent poor prognostic factor for overall survival (adjusted hazard ratio [aHR], 10.17; 95% CI, 1.09-94.97; P = 0.042) and progression-free survival (aHR, 14.47; 95% CI, 1.52-137.35; P = 0.020) in patients with HGSOC.

Conclusions

The levels of the three NET markers and prekallikrein might be novel diagnostic and prognostic markers for HGSOC.

Exosomal Plasma Gelsolin Is an Immunosuppressive Mediator in the Ovarian Tumor Microenvironment and a Determinant of Chemoresistance

Ovarian Cancer (OVCA) is the most fatal gynecologic cancer and has a 5-year survival rate less than 45%. This is mainly due to late diagnosis and drug resistance. Overexpression of plasma gelsolin (pGSN) is key contributing factor to OVCA chemoresistance and immunosuppression. Gelsolin (GSN) is a multifunctional protein that regulates the activity of actin filaments by cleavage, capping, and nucleation. Generally, it plays an important role in cytoskeletal remodeling. GSN has three isoforms: cytosolic GSN, plasma GSN (pGSN), and gelsolin-3. Exosomes containing pGSN are released and contribute to the progression of OVCA. This review describes how pGSN overexpression inhibits chemotherapy-induced apoptosis and triggers positive feedback loops of pGSN expression. It also describes the mechanisms by which exosomal pGSN promotes apoptosis and dysfunction in tumor-killing immune cells. A discussion on the potential of pGSN as a prognostic, diagnostic, and therapeutic marker is also presented herein.

Targeted Microchip Capillary Electrophoresis-Orbitrap Mass Spectrometry Metabolomics to Monitor Ovarian Cancer Progression

The lack of effective screening strategies for high-grade serous carcinoma (HGSC), a subtype of ovarian cancer (OC) responsible for 70–80% of OC related deaths, emphasizes the need for new diagnostic markers and a better understanding of disease pathogenesis. Capillary electrophoresis (CE) coupled with high-resolution mass spectrometry (HRMS) offers high selectivity and sensitivity for ionic compounds, thereby enhancing biomarker discovery. Recent advances in CE-MS include small, chip-based CE systems coupled with nanoelectrospray ionization (nanoESI) to provide rapid, high-resolution analysis of biological specimens. Here, we describe the development of a targeted microchip (µ) CE-HRMS method, with an acquisition time of only 3 min and sample injection volume of 4nL, to analyze 40 target metabolites in serum samples from a triple-mutant (TKO) mouse model of HGSC. Extracted ion electropherograms showed sharp, baseline resolved peak shapes, even for structural isomers such as leucine and isoleucine. All calibration curves of the analytes maintained good linearity with an average R² of 0.994, while detection limits were in the nM range. Thirty metabolites were detected in mouse serum with recoveries ranging from 78 to 120%, indicating minimal ionization suppression and good accuracy. We applied the µCE-HRMS method to biweekly-collected serum samples from TKO and TKO control mice. A time-resolved analysis revealed characteristic temporal trends for amino acids, nucleosides, and amino acid derivatives. These metabolic alterations are indicative of altered nucleotide biosynthesis and amino acid metabolism in HGSC development and progression. A comparison of the µCE-HRMS dataset with non-targeted ultra-high performance liquid chromatography (UHPLC)–MS results showed identical temporal trends for the five metabolites detected with both platforms, indicating the µCE-HRMS method performed satisfactorily in terms of capturing metabolic reprogramming due to HGSC progression while reducing the total data collection time three-fold.

Assessment of the diagnostic and prognostic relevance of ACAT1 and CE levels in plasma, peritoneal fluid and tumor tissue of epithelial ovarian cancer patients - a pilot study

Background

Abnormal accumulation of acyl-CoA cholesterol acyltransferase-1 (ACAT1) and ACAT1-mediated cholesterol esterified with fatty acids (CE) contribute to cancer progression in various cancers. Our findings of increased CE and ACAT1 levels in epithelial ovarian cancer (EOC) cell lines prompted us to investigate whether such an increase occurs in primary clinical samples obtained from human subjects diagnosed with EOC. We evaluated the diagnostic/prognostic potential of ACAT1 and CE in EOC by: 1) assessing ACAT1 and CE levels in plasma, peritoneal fluid, and ovarian/tumor tissues; 2) assessing diagnostic performance by Receiver Operating Characteristic (ROC) analysis; and 3) comparing expression of ACAT1 and CE with that of tumor proliferation marker, Ki67.

Methods

ACAT1 protein levels in plasma, peritoneal fluid and tissue were measured via enzyme-linked immunosorbent assay. Tissue expression of ACAT1 and Ki67 proteins were confirmed by immunohistochemistry and mRNA transcript levels were evaluated using quantitative real-time polymerase chain reaction (qRT-PCR). CE levels were assessed in plasma, peritoneal fluid (colorimetric assay) and in tissue (thin layer chromatography).

Results

Preoperative levels of ACAT1 and CE on the day of surgery were significantly higher in tissue and peritoneal fluid from EOC patients vs. the non-malignant group, which included subjects with benign tumors and normal ovaries; however, no significant differences were observed in plasma. In tissue and peritoneal fluid, positive correlations were observed between CE and ACAT1 levels, as well as between ACAT1/CE and Ki67.

Conclusions

ACAT1 and CE accumulation may be linked to the aggressive potential of EOC; therefore, these mediators may be useful biomarkers for EOC prognosis and target-specific treatments.

Establishment and validation of a novel invasion-related gene signature for predicting the prognosis of ovarian cancer

BACKGROUND

Ovarian cancer (OC) is an invasive gynaecologic cancer with a high cancer-related death rate. The purpose of this study was to establish an invasion-related multigene signature to predict the prognostic risk of OC.

METHODS

We extracted 97 invasion-related genes from The Cancer Genome Atlas (TCGA) database. Then, the ConsensusClusterPlus and limma packages were used to calculate differentially expressed genes (DEGs). To calculate the immune scores of the molecular subtypes, we used ESTIMATE to evaluate the stromal score, immune score and ESTIMATE score. MCP-counter and the GSVA package ssgsea were used to evaluate the types of infiltrating immune cells. Survival and nomogram analyses were performed to explore the prognostic value of the signature. Finally, qPCR, immunohistochemistry staining and functional assays were used to evaluate the expression and biological abilities of the signature genes in OC.

RESULTS

Based on the consistent clustering of invasion-related genes, cases in the OC datasets were divided into two subtypes. A significant difference was observed in prognosis between the two subtypes. Most genes were highly expressed in the C1 group. Based on the C1 group genes, we constructed an invasion-related 6-gene prognostic risk model. Furthermore, to verify the signature, we used the TCGA-test and GSE32062 and GSE17260 chip datasets for testing and finally obtained a good risk prediction effect in those datasets. Moreover, the results of the qPCR and immunohistochemistry staining assays revealed that KIF26B, VSIG4 and COL6A6 were upregulated and that FOXJ1, MXRA5 and CXCL9 were downregulated in OC tissues. The functional study showed that the expression of KIF26B, VSIG4, COL6A6, FOXJ1, MXRA5 and CXCL9 can regulate the migration and invasion abilities of OC cells.

CONCLUSION

We developed a 6-gene prognostic stratification system (FOXJ1, MXRA5, KIF26B, VSIG4, CXCL9 and COL6A6) that is independent of clinical features. These results suggest that the signature could potentially be used to evaluate the prognostic risk of OC patients.

NGAL/MMP-9 as a biomarker for epithelial ovarian cancer: A case–control diagnostic accuracy study

Background:

Epithelial ovarian cancer (EOC) are often diagnosed late due to lack of specific symptoms and efficient tumor markers. Neutrophil gelatinase-associated lipocalin/matrix metallopeptidase-9 (NGAL/MMP-9) complex are involved in the development and progression of various cancers and have potential as a biomarker for diagnosing ovarian cancer.

Objectives:

To compare the serum NGAL/MMP-9 complex levels in patients with EOC, benign ovarian tumor, and healthy controls, and determine the potential cut-off values of NGAL/MMP-9 complex for diagnosing EOC.

Materials and Methods:

The study included 50 patients each with EOC and benign ovarian tumor, along with 50 age-matched healthy controls (N = 150). The level of serum NGAL/MMP-9 complex was estimated based on sandwich ELISA. The mean and median of the three groups were compared, and the ROC curve was used to determine the optimum cut-off, sensitivity, and specificity of serum NGAL/MMP-9 complex levels in the diagnosis of EOC.

Results:

A significant difference was found in the median values of the NGAL/MMP-9 complex (malignant EOC: 67.5 ng/ml, benign ovarian tumor: 53.7 ng/ml, controls: 29.2 ng/ml; P < 0.01). NGAL/MMP-9 complex level was also significantly associated with the FIGO staging (Stages I and II: 42.9 ng/ml; Stages III and IV: 70.5 ng/ml; P < 0.003). At a 55.0 ng/ml cut-off value, the NGAL/MMP-9 complex had 82.0% sensitivity and 78.0% specificity in diagnosing EOC.

Conclusion:

The NGAL/MMP-9 complex may be a promising biomarker for determining the progression of EOC as well as in detecting advanced-stage ovarian cancer.

Prognostic value of E-Cadherin and its tumor suppressor role in Saudi women with advanced epithelial ovarian cancer

The extracellular matrix (ECM) disruption and cytoskeleton reorganization are crucial events in tumor proliferation and invasion. E-Cadherin (E-CAD) is a member of cell adhesion molecules involved in cell-cell junctions and ECM stability. The loss of E-CAD expression is associated with cancer progression and metastasis. This retrospective study aimed to assess E-CAD protein expression in ovarian cancer (OC) tissues and to evaluate its prognostic value. Patients and Methods: 143 formalin-fixed and paraffin-embedded (FFPE) blocks of primary advanced stages OC were retrieved and used to construct Tissue microarrays. Automated immunohistochemistry technique was performed to evaluate E-CAD protein expression patterns in OC. Results: E-CAD protein expression was significantly correlated with OC histological subtype (p < 0.0001), while borderline significant correlations were observed with both tumor grade (p = 0.06) and stage (p = 0.07). Interestingly, Kaplan-Meier survival analysis showed that OC patients with membranous E-CAD expression survived longer than those with no E-CAD expression mainly those at advanced stages (p < 0.009). Further in silico analysis confirms the key roles of E-CAD in OC molecular functions. Conclusion: we reported a prognosis value of membranous E-CAD in advanced stage OC patients. Further validation using larger cohorts is recommended to extract clinically relevant outcomes towards better OC management and individualized oncology.

Biomarker-based early detection of epithelial ovarian cancer based on a five-protein signature in patient's plasma - a prospective trial

BACKGROUND

Trial on five plasma biomarkers (CA125, HE4, OPN, leptin, prolactin) and their possible role in differentiating benign from malignant ovarian tumors.

METHODS

In this unicentric prospective trial preoperative blood samples of 43 women with ovarian masses determined for ovarian surgery were analyzed. 25 patients had pathologically confirmed benign, 18 malignant ovarian tumors. Blood plasma was analyzed for CA125, HE4, OPN, leptin, prolactin and MIF by multiplex immunoassay analysis. Each single protein and a logistical regression model including all the listed proteins were tested as preoperative predictive marker for suspect ovarian masses.

RESULTS

Plasma CA125 was confirmed as a highly accurate tumor marker in ovarian cancer. HE4, OPN, leptin and prolactin plasma levels differed significantly between benign and malignant ovarian masses. With a logistical regression model a formula including CA125, HE4, OPN, leptin and prolactin was developed to predict malignant ovarian tumors. With a discriminatory AUC of 0.96 it showed to be a highly sensitive and specific diagnostic test for a malignant ovarian tumor.

CONCLUSIONS

The calculated formula with the combination of CA125, HE4, OPN, leptin and prolactin plasma levels surpasses each single marker in its diagnostic value to discriminate between benign and malignant ovarian tumors. The formula, applied to our patient population was highly accurate but should be validated in a larger cohort.

TRIAL REGISTRATION

Clinical Trials.gov under NCT01763125 , registered Jan. 8, 2013.

Identification and evaluation of fructose-bisphosphate aldolase B as a potential diagnostic biomarker in choledochal cysts patients: a quantitative proteomic analysis

BACKGROUND

Choledochal cyst (CC) is a congenital bile duct malformation, with a higher incidence in minors. Patients with CCs are at risk of pancreatitis and ascending cholangitis. The main forms of treatments aim to avoid any possible hepatic, pancreatic, or biliary complications. Since early diagnosis is of great importance for CC treatment and prognosis, this investigation was designed to screen and identify potential biomarkers from the serum samples of CC patients for CC early diagnosis.

METHODS

Quantitative label free proteomic analysis was used to identify differentially expressed proteins in serum samples from CC patients and normal healthy children. The expression levels of biomarker candidates were further confirmed using quantitative polymerase chain reaction (Q-PCR), Western blot analysis, and immunohistochemistry in the choledochal tissues.

RESULTS

The quantitative label free proteomic analysis identified 47 differentially expressed proteins in the serum samples from the CC patients and the normal children, including 14 up-regulated proteins and 33 down-regulated proteins. The expression profile of eight biomarker candidates in CC patients, namely, insulin-like growth factor binding protein 2 (IGFBP2), tropomyosin (TPM3), fructose-bisphosphate aldolase B (ALDOB), fumarylacetoacetate hydrolase (FAH), superoxide dismutase 3 (SOD3), secreted protein acidic and cysteine rich (SPARC), apolipoprotein E (APOE), and retinol binding protein 4 (RBP4), were selected for further examination in choledochal tissues, showing that ALDOB was significantly increased.

CONCLUSIONS

The results demonstrated that the ALDOB protein increased significantly in choledochal tissues and the serum samples of CC patients, which may serve as an effective predictor for early diagnosis of CC.

A novel decision tree model based on chromosome imbalances in cell-free DNA and CA-125 in the differential diagnosis of ovarian cancer

OBJECTIVE

CA-125 is widely used as biomarker of ovarian cancer. However, CA-125 suffers low accuracy. We developed a hybrid analytical model, the Ovarian Cancer Decision Tree (OCDT), employing a two-layer decision tree, which considers genetic alteration information from cell-free DNA along with CA-125 value to distinguish malignant tumors from benign tumors.

METHODS

We consider major copy number alterations at whole chromosome and chromosome-arm level as the main feature of our detection model. Fifty-eight patients diagnosed with malignant tumors, 66 with borderline tumors, and 10 with benign tumors were enrolled.

RESULTS

Genetic analysis revealed significant arm-level imbalances in most malignant tumors, especially in high-grade serous cancers in which 12 chromosome arms with significant aneuploidy (P<0.01) were identified, including 7 arms with significant gains and 5 with significant losses. The area under receiver operating characteristic curve (AUC) was 0.8985 for copy number variations analysis, compared to 0.8751 of CA125. The OCDT was generated with a cancerous score (CScore) threshold of 5.18 for the first level, and a CA-125 value of 103.1 for the second level. Our most optimized OCDT model achieved an AUC of 0.975.

CONCLUSIONS

The results suggested that genetic variations extracted from cfDNA can be combined with CA-125, and together improved the differential diagnosis of malignant from benign ovarian tumors. The model would aid in the pre-operative assessment of women with adnexal masses. Future clinical trials need to be conducted to further evaluate the value of CScore in clinical settings and search for the optimal threshold for malignancy detection.

Clinical significance of circulating tumor cell related markers in patients with epithelial ovarian cancer before and after adjuvant chemotherapy

Circulating tumor cells (CTCs) have recently been considered as new prognostic and diagnostic markers for various human cancers; however, their significance in epithelial ovarian cancer (EOC) remains to be elucidated. In this study, using quantitative real-time PCR, we evaluated the expression of EPCAM, MUC1, CEA, HE4 and CA125 mRNAs, as putative markers of CTCs, in the blood of 51 EOC patients before and/or after adjuvant chemotherapy. Our results demonstrated that, before chemotherapy, the expression of EPCAM, MUC1, CEA and HE4 mRNAs were correlated to each other. CEA expression was correlated with tumor stage (r = 0.594, p = 0.000) before chemotherapy, whereas its expression after chemotherapy was correlated with serum levels of CA125 antigen (r = 0.658, p = 0.000). HE4 mRNA showed the highest sensitivity both before and after chemotherapy (82.98% and 85.19%, respectively) and the persistence of this marker after chemotherapy was associated with advanced disease stage. The expression of CA125 mRNA had negative correlation with the other markers and with tumor stage and therapy response (evaluated by the measurement of serum CA125 antigen). Collectively, our results indicated a better clinical significance of tumor-specific markers (CEA and HE4 mRNAs) compared to epithelial-specific markers (EPCAM and MUC1 mRNAs).

Glycomic-Based Biomarkers for Ovarian Cancer: Advances and Challenges

Ovarian cancer remains one of the most common causes of death among gynecological malignancies afflicting women worldwide. Among the gynecological cancers, cervical and endometrial cancers confer the greatest burden to the developing and the developed world, respectively; however, the overall survival rates for patients with ovarian cancer are worse than the two aforementioned. The majority of patients with ovarian cancer are diagnosed at an advanced stage when cancer has metastasized to different body sites and the cure rates, including the five-year survival, are significantly diminished. The delay in diagnosis is due to the absence of or unspecific symptoms at the initial stages of cancer as well as a lack of effective screening and diagnostic biomarkers that can detect cancer at the early stages. This, therefore, provides an imperative to prospect for new biomarkers that will provide early diagnostic strategies allowing timely mitigative interventions. Glycosylation is a protein post-translational modification that is modified in cancer patients. In the current review, we document the state-of-the-art of blood-based glycomic biomarkers for early diagnosis of ovarian cancer and the technologies currently used in this endeavor.

Photoacoustic tomography reconstruction using lag-based delay multiply and sum with a coherence factor improves in vivo ovarian cancer diagnosis

Ovarian cancer is the fifth most common cause of death due to cancer, and it is the deadliest of all gynecological cancers. Diagnosing ovarian cancer via conventional photoacoustic delay-and-sum beamforming (DAS) presents several challenges, such as poor image resolution and low lesion to background tissue contrast. To address these concerns, we propose an improved beamformer named lag-based delay multiply and sum combined with coherence factor (DMAS-LAG-CF). Simulations and phantom experiments demonstrate that compared with the conventional DAS, the proposed algorithm can provide 1.39 times better resolution and 10.77 dB higher contrast. For patient data, similar performance on contrast ratios has been observed. However, since the diagnostic accuracy between cancer and benign/normal groups is a significant measure, we have extracted photoacoustic histogram features of mean, kurtosis and skewness. DMAS-LAG-CF can improve cancer diagnosis with an AUC of 0.91 for distinguishing malignant vs. benign ovarian lesions when mean and skewness are used as features.

Utility of Preoperative Inflammatory Markers to Distinguish Epithelial Ovarian Cancer from Benign Ovarian Masses

Background: Inflammatory markers have been reported to be predictors for the presence of epithelial ovarian cancer (EOC), however, the cut-off value of each marker remains unclear and predictive capability of the markers in different histology types of EOC is still unknown.

Methods: A total of 207 patients with benign ovarian masses and 887 EOC patients who underwent surgical resection, and were pathologically diagnosed were included. We compared the difference of preoperative inflammatory markers between benign ovarian masses and EOC patients. Stratified analysis by histology subtype was further conducted. Logistic regression analyses and receiver operating characteristic (ROC) curves was used to evaluate the predictive capability of the markers.

Results: Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) were significantly associated with all stages and subtypes of EOC (P<0.001). The optimal cut-off points based on ROC curve analyses for NLR, PLR, and LMR were found to be 2.139 (AUC=0.749, P<0.001), 182.698 (AUC=0.730, P<0.001), and 3.619 (AUC = 0.709, P<0.001), respectively. In low CA125 level patients, high level of NLR and PLR increase the risk of endometrioid EOC, while low level of LMR were significantly associated with an increased risk of serous EOC.

Conclusions: In addition to CA125, NLR, PLR, and LMR could be used as predictors of EOC and preoperative inflammatory markers may be used as a potential biomarker for predicting different histotypes of EOC.

Prognostic Significance of Survivin Expression in Patients with Ovarian Carcinoma: A Meta-Analysis

Background: Survivin belongs to the protein family of inhibitors of apoptosis (IAP) and is a regulator of the cell cycle and apoptosis. The aim of this study was to assess the clinical and prognostic significance of expression survivin in patients with ovarian cancer. Methods: We systematically searched for articles in PubMed, the American Chemical Society (Publications), Medline, the Royal Society of Chemistry, Scopus and the Web of Science. Patient clinical data, overall survival (OS), disease-free survival (DFS), and survivin expression were extracted from individual studies. We performed statistical analysis using the STATA 16 package. Eighteen publications containing data from 2233 patients with ovarian cancer were included in this meta-analysis. Results: We found an adverse effect of survivin expression on OS (risk ratio (HR): 1.60; 95% confidence interval (CI): 1.33–1.93, p = 0.00) but this was not observed on DFS (HR: 1.06; 95% CI: 0.55–2.05, p = 0.87). The analysis of clinicopathological parameters showed that survivin expression was associated with the histological grades (G1–2 vs. G3) (odds ratio (OR) = 0.53, 95% CI: 0.34–0.83, p = 0.01) and: International Federation Gynecology and Obstetrics (FIGO) stage (I–II vs. III–IV) (OR = 0.22, 95% CI: 0.09–0.55, p = 0.00), but it was not significantly correlated with the histological subtype (OR = 1.14, 95% CI: 0.83–1.58, p = 0.42). Conclusions: Our meta-analysis suggests that survivin expression may be a marker of poor prognosis in ovarian cancer. Survivin expression was associated with parameters of greater aggressiveness of ovarian cancer. Prospective studies are needed to confirm our results indicating that survivin expression can be used as an ovarian cancer biomarker.

Sphingolipids as multifaceted mediators in ovarian cancer

Ovarian cancer is the most lethal gynaecological malignancy. It is commonly diagnosed at advanced stage when it has metastasised to the abdominal cavity and treatment becomes very challenging. While current standard therapy involving debulking surgery and platinum + taxane-based chemotherapy is associated with high response rates initially, the large majority of patients relapse and ultimately succumb to chemotherapy-resistant disease. In order to improve survival novel strategies for early detection and therapeutics against treatment-refractory disease are urgently needed. A promising new target against ovarian cancer is the sphingolipid pathway which is commonly hijacked in cancer to support cell proliferation and survival and has been shown to promote chemoresistance and metastasis in a wide range of malignant neoplasms. In particular, the sphingosine kinase 1-sphingosine 1-phosphate receptor 1 axis has been shown to be altered in ovarian cancer in multiple ways and therefore represents an attractive therapeutic target. Here we review the roles of sphingolipids in ovarian cancer progression, metastasis and chemoresistance, highlighting novel strategies to target this pathway that represent potential avenues to improve patient survival.

Prognostic significance of elevated pretreatment serum levels of CEA and CA-125 in epithelial ovarian cancer

BACKGROUND

Epithelial ovarian cancer is a highly lethal gynecological malignancy. Accurate and cost-effective predictive tools to estimate the prognosis of patients with epithelial ovarian cancer before treatment are currently lacking.

OBJECTIVE

The purpose of this study was to evaluate the prognostic significance of pretreatment serum levels of carcinoembryonic antigen (CEA) and carbohydrate antigen-125 (CA-125) in primary epithelial ovarian cancer.

METHODS

Between 2008 and 2016, 326 patients with a diagnosis of primary epithelial ovarian cancer were retrospectively reviewed. We attempted to identify an optimal cut-off value of CEA to predict survival using ROC curve analysis. Cox regression univariate and multivariate analyses were used to evaluate prognostic factors.

RESULTS

The optimal cut-off value of CEA was 2.6 ng/mL. In univariate and multivariate analyses, FIGO stage and pretreatment CA-125 and CEA levels significantly predicted progression-free and overall survival. The 5-year progression-free survival rate for patients with both a CEA level < 2.6 ng/mL and CA-125 level < 35 U/mL was 84%, compared to only 33% for the patients with higher levels of both markers (p< 0.001). The 5-year cancer specific survival rate was 94% in those with a CEA level < 2.6 ng/mL and CA-125 level < 35 U/mL, and only 39% for those with higher levels of both markers (p< 0.001).

CONCLUSIONS

In addition to traditional prognostic factors, a pretreatment serum CEA level ⩾ 2.6 ng/mL and CA-125 level ⩾ 35 U/mL were also independent prognostic factors for epithelial ovarian cancer. Patients with an elevated CEA and/or CA-125 level before treatment should be considered to be at high-risk of recurrence and death.

Circulating cell-free DNA variables as marker of ovarian cancer patients: A pilot study

BACKGROUND

Minimal invasive blood-based molecular markers are evaluated as promising biomarkers in malignant diseases these days.

OBJECTIVE

In this pilot study, we investigated the potential of cell-free DNA (cfDNA) concentration and cell-free DNA Integrity (cfDI) as blood-based diagnostic markers for ovarian cancer patients in a retrospective study cohort.

METHODS

cfDNA concentration and cfDI were determined in the plasma of 37 ovarian cancer patients and 28 healthy controls, by measuring ALU and LINE1 repetitive DNA elements using quantitative real-time PCR.

RESULTS

A high correlation was observed between the results of ALU and LINE1. The correlated co-efficiency between the values of cfDNA concentration and cfDI was 0.86 and 0.71. As for the results between cases and controls, no or just borderline significant difference was observed in cfDI after age adjustment (P= 0.40 for ALU and P= 0.05 for LINE1) while cfDNA concentration showed a significant difference between ovarian cancer patients and healthy controls groups (P= 0.03 for ALU and P= 3.00 E-03 for LINE1). cfDNA concentration of ALU and LINE1 had an AUC of 0.81 (0.70-0.91). ALU and LINE1 cfDI reached an AUC of 0.60 (95% CI: 0.46-0.73). The combination of these markers reached the best diagnostic power with an AUC of 0.84.

CONCLUSIONS

cfDNA variables might be potentially diagnostic biomarkers in ovarian cancer, in combination with additional molecular markers. However, further studies are needed to confirm the diagnostic ability of cfDNA variables (cfDNA concentration and cfDI).

Evaluation of the potential of Pap test fluid and cervical swabs to serve as clinical diagnostic biospecimens for the detection of ovarian cancer by mass spectrometry-based proteomics

BACKGROUND

The purpose of this study was to determine whether the residual fixative from a liquid-based Pap test or a swab of the cervix contained proteins that were also found in the primary tumor of a woman with high grade serous ovarian cancer. This study is the first step in determining the feasibility of using the liquid-based Pap test or a cervical swab for the detection of ovarian cancer protein biomarkers.

METHODS

Proteins were concentrated by acetone precipitation from the cell-free supernatant of the liquid-based Pap test fixative or eluted from the cervical swab. Protein was also extracted from the patient's tumor tissue. The protein samples were digested into peptides with trypsin, then the peptides were run on 2D-liquid chromatography mass spectrometry (2D-LCMS). The data was searched against a human protein database for the identification of peptides and proteins in each biospecimen. The proteins that were identified were classified for cellular localization and molecular function by bioinformatics integration.

RESULTS

We identified almost 5000 proteins total in the three matched biospecimens. More than 2000 proteins were expressed in each of the three biospecimens, including several known ovarian cancer biomarkers such as CA125, HE4, and mesothelin. By Scaffold analysis of the protein Gene Ontology categories and functional analysis using PANTHER, the proteins were classified by cellular localization and molecular function, demonstrating that the Pap test fluid and cervical swab proteins are similar to each other, and also to the tumor extract.

CONCLUSIONS

Our results suggest that Pap test fixatives and cervical swabs are a rich source of tumor-specific biomarkers for ovarian cancer, which could be developed as a test for ovarian cancer detection.

CA125 and Ovarian Cancer: A Comprehensive Review

Simple Summary

CA125 has been the most promising biomarker for screening ovarian cancer; however, it still does not have an acceptable accuracy in population-based screening for ovarian cancer. In this review article, we have discussed the role of CA125 in diagnosis, evaluating response to treatment and prognosis of ovarian cancer and provided some suggestions in improving the clinical utility of this biomarker in the early diagnosis of aggressive ovarian cancers. These include using CA125 to screen individuals with symptoms who seek medical care rather than screening the general population, increasing the cutoff point for the CA125 level in the plasma and performing the test at point-of-care rather than laboratory testing. By these strategies, we would detect more aggressive ovarian cancer patients in stages that the tumour can be completely removed by surgery, which is the most important factor in redusing recurrence rate and improving the survival of the patients with ovarian cancer.

Abstract

Ovarian cancer is the second most lethal gynecological malignancy. The tumour biomarker CA125 has been used as the primary ovarian cancer marker for the past four decades. The focus on diagnosing ovarian cancer in stages I and II using CA125 as a diagnostic biomarker has not improved patients’ survival. Therefore, screening average-risk asymptomatic women with CA125 is not recommended by any professional society. The dualistic model of ovarian cancer carcinogenesis suggests that type II tumours are responsible for the majority of ovarian cancer mortality. However, type II tumours are rarely diagnosed in stages I and II. The recent shift of focus to the diagnosis of low volume type II ovarian cancer in its early stages of evolution provides a new and valuable target for screening. Type II ovarian cancers are usually diagnosed in advanced stages and have significantly higher CA125 levels than type I tumours. The detection of low volume type II carcinomas in stage IIIa/b is associated with a higher likelihood for optimal cytoreduction, the most robust prognostic indicator for ovarian cancer patients. The diagnosis of type II ovarian cancer in the early substages of stage III with CA125 may be possible using a higher cutoff point rather than the traditionally used 35 U/mL through the use of point-of-care CA125 assays in primary care facilities. Rapid point-of-care testing also has the potential for effective longitudinal screening and quick monitoring of ovarian cancer patients during and after treatment. This review covers the role of CA125 in the diagnosis and management of ovarian cancer and explores novel and more effective screening strategies with CA125.

Liquid biopsy in ovarian cancer: Catching the silent killer before it strikes

Epithelial ovarian cancer (EOC) is the most lethal gynaecological malignancy in the western world. The majority of women presenting with the disease are asymptomatic and it has been dubbed the "silent killer". To date there is no effective minimally invasive method of stratifying those with the disease or screening for the disease in the general population. Recent molecular and pathological discoveries, along with the advancement of scientific technology, means there is a real possibility of having disease-specific liquid biopsies available within the clinical environment in the near future. In this review we discuss these discoveries, particularly in relation to the most common and aggressive form of EOC, and their role in making this possibility a reality.

Emerging Role of Metabolomics in Ovarian Cancer Diagnosis

Ovarian cancer is considered a silent killer due to the lack of clear symptoms and efficient diagnostic tools that often lead to late diagnoses. Over recent years, the impelling need for proficient biomarkers has led researchers to consider metabolomics, an emerging omics science that deals with analyses of the entire set of small-molecules (≤1.5 kDa) present in biological systems. Metabolomics profiles, as a mirror of tumor-host interactions, have been found to be useful for the analysis and identification of specific cancer phenotypes. Cancer may cause significant metabolic alterations to sustain its growth, and metabolomics may highlight this, making it possible to detect cancer in an early phase of development. In the last decade, metabolomics has been widely applied to identify different metabolic signatures to improve ovarian cancer diagnosis. The aim of this review is to update the current status of the metabolomics research for the discovery of new diagnostic metabolomic biomarkers for ovarian cancer. The most promising metabolic alterations are discussed in view of their potential biological implications, underlying the issues that limit their effective clinical translation into ovarian cancer diagnostic tools.

High-throughput approaches for precision medicine in high-grade serous ovarian cancer

High-grade serous carcinoma (HGSC) is the most prevalent and aggressive subtype of ovarian cancer. The large degree of clinical heterogeneity within HGSC has justified deviations from the traditional one-size-fits-all clinical management approach. However, the majority of HGSC patients still relapse with chemo-resistant cancer and eventually succumb to their disease, evidence that further work is needed to improve patient outcomes. Advancements in high-throughput technologies have enabled novel insights into biological complexity, offering a large potential for informing precision medicine efforts. Here, we review the current landscape of clinical management for HGSC and highlight applications of high-throughput biological approaches for molecular subtyping and the discovery of putative blood-based biomarkers and novel therapeutic targets. Additionally, we present recent improvements in model systems and discuss how their intersection with high-throughput platforms and technological advancements is positioned to accelerate the realization of precision medicine in HGSC.

Clinical Utility of Preoperative Assessment in Ovarian Cancer Cytoreduction

Ovarian cancer is the deadliest gynecologic cancer, in part due to late presentation. Many women have vague early symptoms and present with disseminated disease. Cytoreductive surgery can be extensive, involving multiple organ systems. Novel therapies and recent clinical trials have provided evidence that, compared to primary cytoreduction, neoadjuvant chemotherapy has equivalent survival outcomes with less morbidity. There is increasing need for validated tools and mechanisms for clinicians to determine the optimal management of ovarian cancer patients.

A giant ovarian mass in a 68-year-old female with persistent abdominal pain and elevated serum CA-125 level

INTRODUCTION

Ovarian masses are common findings in general gynecology. However giant ovarian mass is a rare finding. In the literature, a few cases of giant ovarian mass have been mentioned sporadically, especially in elderly patients.

CASE REPORT

We report a 68-year-old postmenopausal woman with a giant right ovarian mass measuring 38 × 31 × 29 cm. She presented to our department with complaints of massive abdominal distention which started gradually 6 months ago. The patient also complained of difficulty in breathing and ambulation. There were no other gastrointestinal, urinary, or gynecological symptoms CA-125 marker was slightly elevated. Because of elevation of serum CA-125 levels, ovarian malignancy was included in differential diagnosis. We performed an ovarian cystectomy without any significant complication. On histopathological examination, the mass was confirmed as benign serous cystadenoma of the right ovary.

CONCLUSIONS

Giant ovarian mass is a rare finding in general gynecology. Physicians must maintain heightened awareness and index of suspicion when approaching a woman with pain in any region of the abdomen or pelvis. Further investigation with abdominal and pelvic ultrasonography and magnetic resonance imaging or computed tomography is necessary. Benign lesions can be found even in patients presenting with giant masses and higher CA-125 than normal levels.

The generally low sensitivity of CA 125 for FIGO stage I ovarian cancer diagnosis increases for endometrioid histotype

BACKGROUND

The serum marker CA 125 is still the most widely used biomarker for ovarian cancer (OC) diagnosis in gynecological and oncological setting, but its predictive role in early-stage OC is still debated. The aim of this study was to explore the value of CA 125 in distinguishing between early-stage OC and borderline ovarian tumor (BOT) and to evaluate the accuracy of CA 125 in the detection of early stage OC.

METHODS

A retrospective cohort study was performed at the University Hospital of Bologna (Italy) on 1296 consecutive women suffering from OC or BOT (diagnosed at histology) between 1988-2017. Patients for whom CA 125 level was determined preoperatively were included. The positive cut-off level used was >35 U/mL.

RESULTS

Of 910 patients, 192 (21.1%) were diagnosed with BOT and 718 (78.9%) with OC. The sensitivity of CA 125 for stage I OC was 54.4 (95% CI: 45.3-63.3) (51.5 for IA, 54.6 for IB, 58.3 for IC), but it increased to 78.0 (95% CI: 63.7-88.0) for stage II. Interestingly, in stage I OC, CA 125 presented a significantly higher sensitivity for the endometrioid histotype [72.4 (95% CI: 52.5-86.5) vs. 49.0 (95% CI: 38.6-59.4), P=0.026]. The positive likelihood ratio of CA 125 for early-stage OC compared to BOT was 1.29 (95% CI: 1.06-1.58).

CONCLUSIONS

Despite its limited sensitivity for early-stage OCs, CA 125 still represents a useful serum marker to early differentiate between OCs and BOTs. Its sensitivity for stage I OC increases in endometrioid histotype.

Activated CAMKKβ-AMPK signaling promotes autophagy in a spheroid model of ovarian tumour metastasis

Background

A hallmark of epithelial ovarian cancer (EOC) metastasis is the process of spheroid formation, whereby tumour cells aggregate into 3D structures while in suspension in the peritoneal cavity. EOC spheroids are subjected to bioenergetic stress, thereby activating AMP-activated protein kinase (AMPK) signaling to enter a metabolically quiescent state, which can facilitate cell survival under nutrient-limiting conditions. Independently, we have also demonstrated that EOC spheroids induce autophagy, a process that degrades and recycles intracellular components to restore energy and metabolites. Herein, we sought to examine whether AMPK controls autophagy induction as a cell survival mechanism in EOC spheroids.

Results

We observed a co-ordinate increase in phosphorylated AMPK and the autophagy marker LC3-II during EOC spheroid formation. Reduced AMPK expression by siRNA-mediated knockdown of PRKAA1 and PRKAA2 blocked autophagic flux in EOC spheroids as visualized by fluorescence microscopy using the mCherry-eGFP-LC3B reporter. A complementary approach using pharmacologic agents Compound C and CAMKKβ inhibitor STO-609 to inhibit AMPK activity both yielded a potent blockade of autophagic flux as well. However, direct activation of AMPK in EOC cells using oligomycin and metformin was insufficient to induce autophagy. STO-609 treatment of EOC spheroids resulted in reduced viability in 7 out of 9 cell lines, but with no observed effect in non-malignant FT190 cell spheroids.

Conclusions

Our results support the premise that CAMKKβ-mediated AMPK activity is required, at least in part, to regulate autophagy induction in EOC spheroids and support cell viability in this in vitro model of EOC metastasis.

Pre-operative sera interleukin-6 in the diagnosis of high-grade serous ovarian cancer

Pre-operative discrimination of malignant masses is crucial for accurate diagnosis and prompt referral to a gynae oncology centre for optimal surgical intervention. HGSOC progression is correlated with local and systemic inflammation. We hypothesised that inclusion of inflammatory biomarkers in sera may improve diagnostic tests. In the training cohort, we tested four existing clinical tests (RMI score and ROMA, CA125 and HE4) and a panel of 28 immune soluble biomarkers in sera from 66 patients undergoing surgery for suspected ovarian cancer. Six promising immune biomarkers alone, or in combination with conventional tests, were subsequently analysed in an independent validation cohort (n = 69). IL-6 was identified as the main driver of variability followed closely by conventional diagnostic tests. Median sera IL-6 was higher in HGSOC patients compared to those with a benign mass or controls with normal ovaries (28.3 vs 7.3 vs 1.2 pg/ml, p < 0.0001). The combination of IL-6 further improved the overall predictive probability of the conventional tests. Modelling a two-step triage of women with a suspicious ovarian mass, with IL-6 > 3.75 pg/ml as primary triage followed by conventional tests (CA125 or RMI score) identified ovarian cancer in patients with a misclassification rate of 4.54–3.03%, superior to the use of CA125 or RMI alone (9.09 to 10.60). The validation cohort demonstrated a similar improvement in the diagnostic sensitivity following addition of IL-6. IL-6 in combination with conventional tests may be a useful clinical biomarker for triage of patients with a suspected malignant ovarian mass.

Assessment of peritoneal microbial features and tumor marker levels as potential diagnostic tools for ovarian cancer

Epithelial ovarian cancer (OC) is the most deadly cancer of the female reproductive system. To date, there is no effective screening method for early detection of OC and current diagnostic armamentarium may include sonographic grading of the tumor and analyzing serum levels of tumor markers, Cancer Antigen 125 (CA-125) and Human epididymis protein 4 (HE4). Microorganisms (bacterial, archaeal, and fungal cells) residing in mucosal tissues including the gastrointestinal and urogenital tracts can be altered by different disease states, and these shifts in microbial dynamics may help to diagnose disease states. We hypothesized that the peritoneal microbial environment was altered in patients with OC and that inclusion of selected peritoneal microbial features with current clinical features into prediction analyses will improve detection accuracy of patients with OC. Blood and peritoneal fluid were collected from consented patients that had sonography confirmed adnexal masses and were being seen at SIU School of Medicine Simmons Cancer Institute. Blood was processed and serum HE4 and CA-125 were measured. Peritoneal fluid was collected at the time of surgery and processed for Next Generation Sequencing (NGS) using 16S V4 exon bacterial primers and bioinformatics analyses. We found that patients with OC had a unique peritoneal microbial profile compared to patients with a benign mass. Using ensemble modeling and machine learning pathways, we identified 18 microbial features that were highly specific to OC pathology. Prediction analyses confirmed that inclusion of microbial features with serum tumor marker levels and control features (patient age and BMI) improved diagnostic accuracy compared to currently used models. We conclude that OC pathogenesis alters the peritoneal microbial environment and that these unique microbial features are important for accurate diagnosis of OC. Our study warrants further analyses of the importance of microbial features in regards to oncological diagnostics and possible prognostic and interventional medicine.

Liquid biopsy in ovarian cancer using circulating tumor DNA and cells: Ready for prime time?

Liquid biopsies hold the potential to inform cancer patient prognosis and to guide treatment decisions at the time when direct tumor biopsy may be impractical due to its invasive nature, inaccessibility and associated complications. Specifically, circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) have shown promising results as companion diagnostic biomarkers for screening, prognostication and/or patient surveillance in many cancer types. In ovarian cancer (OC), CTC and ctDNA analysis allow comprehensive molecular profiling of the primary, metastatic and recurrent tumors. These biomarkers also correlate with overall tumor burden and thus, they provide minimally-invasive means for patient monitoring during clinical course to ascertain therapy response and timely treatment modification in the context of disease relapse. Here, we review recent reports of the potential clinical value of CTC and ctDNA in OC, expatiating on their use in diagnosis and prognosis. We critically appraise the current evidence, and discuss the issues that still need to be addressed before liquid biopsies can be implemented in routine clinical practice for OC management.

Optical Resolution Photoacoustic Microscopy of Ovary and Fallopian Tube

Ovarian cancer is the leading cause of death among gynecological cancers, but is poorly amenable to preoperative diagnosis. In this study, we investigate the feasibility of "optical biopsy," using high-optical-resolution photoacoustic microscopy (OR-PAM) to quantify the microvasculature of ovarian and fallopian tube tissue. The technique is demonstrated using excised human ovary and fallopian tube specimens imaged immediately after surgery. Quantitative parameters are derived using Amira software. The parameters include three-dimensional vascular segment count, total volume and length, which are associated with tumor angiogenesis. Qualitative results of OR-PAM demonstrate that malignant ovarian tissue has larger and more tortuous blood vessels as well as smaller vessels of different sizes, while benign and normal ovarian tissue has smaller vessels of uniform size. Quantitative analysis shows that malignant ovaries have greater tumor vessel volume, length and number of segments, as compared with benign and normal ovaries. The vascular pattern of benign fallopian tube is different than that of benign ovarian tissue. Our initial results demonstrate the potential of OR-PAM as an imaging tool for fast assessment of ovarian tissue and fallopian tube and could avoid unnecessary surgery if the risk of the examined ovary is extremely low.

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.

Quantitative assessment and clinical relevance of kallikrein-related peptidase 5 mRNA expression in advanced high-grade serous ovarian cancer

Background

In ovarian cancer, dysregulation of mRNA expression of several components of the family of the kallikrein-related peptidases (KLKs) is observed. In this study, we have analyzed the KLK5 mRNA expression pattern in tumor tissue of patients suffering from high-grade serous ovarian cancer stage FIGO III/IV. Moreover, we have correlated the KLK5 mRNA levels with clinical outcome.

Methods

We assessed the mRNA expression levels of KLK5 in tumor tissue of 138 patients using quantitative PCR (qPCR). The mRNA levels were correlated with KLK5 antigen tumor tissue levels measured by ELISA (available for 41 of the 138 patients), established clinical features as well as patients’ outcome, using Chi-square-tests, Mann-Whitney U-tests and Spearman rank calculations as well as Cox regression models, Kaplan-Meier survival analysis and the log-rank test.

Results

A highly significant correlation between the mRNA expression levels and protein levels of KLK5 in tumor tissues was observed (r_s = 0.683, p < 0.001). In univariate Cox regression analysis, elevated KLK5 mRNA expression was remarkably associated with reduced progression-free survival (PFS; p = 0.047), but not with overall survival (OS). Association of KLK5 mRNA expression with PFS was validated in silico using The Cancer Genome Atlas. For this, Affymetrix-based mRNA data (n = 377) were analyzed applying the Kaplan-Meier Plotter tool (p = 0.027). In multivariable Cox analysis, KLK5 mRNA values revealed a trend towards statistical significance for PFS (p = 0.095), whereas residual tumor mass (0 mm vs. > 0 mm), but not ascites fluid volume (≤500 ml vs. > 500 ml), remained an independent indicator for both OS and PFS (p < 0.001, p = 0.005, respectively).

Conclusions

These results obtained with a homogenous patient group with all patients suffering from advanced high-grade serous ovarian cancer support previous results suggesting elevated KLK5 mRNA levels as an unfavorable marker in ovarian cancer.

Classification of human ovarian cancer using functional, spectral, and imaging features obtained from in vivo photoacoustic imaging

We report in this pilot study the diagnostic results of in vivo imaging of patients with ovarian lesions, using a co-registered photoacoustic and ultrasound (PAT/US) system. A total of 39 ovaries from 24 patients were imaged in vivo. PAT functional features, i.e., blood oxygen saturation (sO2) and relative total hemoglobin (rHbT), PAT image features, and PAT spectral features within a region of interest (ROI) in each ovarian tissue were extracted. To select the significant features, a t-test on each feature was performed, and the independent predictors were determined by evaluating correlation between each pair of predictors. To classify the ovarian lesions, we employed a generalized linear model (GLM) and a support vector machine (SVM). We used these classifiers first to distinguish benign/normal lesions from ovaries with invasive epithelial tumors and then to separate normal/benign lesions from all types of ovarian tumors. We developed classifiers once by inclusion of PAT functional features to assess the best diagnostic performance of the classifiers when multiple wavelengths data are available. Second time, we excluded the PAT functional features from the features set to evaluate the best diagnostic performance if only a single wavelength is available. Our results show that using functional features improves the classification performance, especially for distinguishing normal/benign ovarian lesions from all types of tumors. In this case, an area under ROC curve (AUC) of 0.92, 0.93 of testing data was achieved using a GLM and SVM classifier when functional features were included in the feature set while excluding these features resulted in an AUC of 0.89, 0.92, respectively.

BRCA Mutation Carriers: Breast and Ovarian Cancer Screening Guidelines and Imaging Considerations

Patients who carry the BRCA1 and BRCA2 gene mutations have an underlying genetic predisposition for breast and ovarian cancers. These deleterious genetic mutations are the most common genes implicated in hereditary breast and ovarian cancers. This monograph summarizes the evidence behind current screening recommendations, reviews imaging protocols specific to this patient population, and illustrates some of the imaging nuances of breast and ovarian cancers in this clinical setting.

The contribution and perspectives of proteomics to uncover ovarian cancer tumor markers

Despite all the advances in understanding the mechanisms involved in ovarian cancer (OC) development, many aspects still need to be unraveled and understood. Tumor markers (TMs) are of special interest in this disease. Some aspects of clinical management of OC might be improved by the use of validated TMs, such as differentiating subtypes, defining the most appropriate treatment, monitoring the course of the disease, or predicting clinical outcome. The Food and Drug Administration (FDA) has approved a few TMs for OC: CA125 (cancer antigen 125; monitoring), HE4 (Human epididymis protein; monitoring), ROMA (Risk Of Malignancy Algorithm; HE4+CA125; prediction of malignancy) and OVA1 (Vermillion's first-generation Multivariate Index Assay [MIA]; prediction of malignancy). Proteomics can help advance the research in the field of TMs for OC. A variety of biological materials are being used in proteomic analysis, among them tumor tissues, interstitial fluids, tumor fluids, ascites, plasma, and ovarian cancer cell lines. However, the discovery and validation of new TMs for OC is still very challenging. The enormous heterogeneity of histological types of samples and the individual variability of patients (lifestyle, comorbidities, drug use, and family history) are difficult to overcome in research protocols. In this work, we sought to gather relevant information regarding TMs, OC, biological samples for proteomic analysis, as well as markers and algorithms approved by the FDA for use in clinical routine.

Potential of mid-infrared spectroscopy as a non-invasive diagnostic test in urine for endometrial or ovarian cancer

The current lack of an accurate, cost-effective and non-invasive test that would allow for screening and diagnosis of gynaecological carcinomas, such as endometrial and ovarian cancer, signals the necessity for alternative approaches. The potential of spectroscopic techniques in disease investigation and diagnosis has been previously demonstrated. Here, we used attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy to analyse urine samples from women with endometrial (n = 10) and ovarian cancer (n = 10), as well as from healthy individuals (n = 10). After applying multivariate analysis and classification algorithms, biomarkers of disease were pointed out and high levels of accuracy were achieved for both endometrial (95% sensitivity, 100% specificity; accuracy: 95%) and ovarian cancer (100% sensitivity, 96.3% specificity; accuracy 100%). The efficacy of this approach, in combination with the non-invasive method for urine collection, suggest a potential diagnostic tool for endometrial and ovarian cancers.

In search of the altering salivary proteome in metastatic breast and ovarian cancers

Breast and ovarian cancers, the most common cancers in women in India, are expected to rise in the next decade. Metastatic organotropism is a nonrandom, predetermined process which represents a more lethal and advanced form of cancer with increased mortality rate. In an attempt to study organotropism, salivary proteins were analyzed by mass spectrometry indicative of pathophysiology of breast and ovarian cancers and were compared to healthy and ovarian chemotherapy subjects. Collectively, 646 proteins were identified, of which 409 proteins were confidently identified across all four groups. Network analysis of upregulated proteins such as coronin-1A, hepatoma-derived growth factor, vasodilator-stimulated phosphoprotein (VASP), and cofilin in breast cancer and proteins like coronin-1A, destrin, and HSP90α in ovarian cancer were functionally linked and were known to regulate cell proliferation and migration. Additionally, proteins namely VASP, coronin-1A, stathmin, and suprabasin were confidently identified in ovarian chemotherapy subjects, possibly in response to combined paclitaxel and carboplatin drug therapy to ovarian cancer. Selected representative differentially expressed proteins (eg, gelsolin, VASP) were validated by western blot analysis. Results of this study provide a foundation for future research to better understand the organotropic behavior of breast and ovarian cancers, as well as neoadjuvant drug response in ovarian cancer.

Metabolomic diagnostics and human digital image

The existing clinical laboratory practice has limitations in terms of specificity and sensitivity of diagnosis, making the introduction of new methods in medicine more topical. Application of 'omics' technologies, especially metabolomics, allows overcoming these limitations. The composition of blood metabolites reflects the physical state of an organism at the molecular level. The analysis of blood metabolome can serve as effective means of diagnosis, implementation of which in healthcare is timely and relevant. This paper demonstrates the versatility of metabolomic diagnostics, its applicability to various diseases. We discussed the standard of human digital image, which includes the metabolomic data sufficient to make an accurate assessment of general health and carry out precision diagnostics of a wide range of diseases.

Upregulated expression of serum exosomal miR-375 and miR-1307 enhance the diagnostic power of CA125 for ovarian cancer

Background

Ovarian cancer (OC) is associated with high mortality in gynecological oncology; this is mainly due to the low diagnosis rate. Exosomal miRNA has demonstrated potential as a tumor biomarker. We aimed to explore the diagnostic potential of serum exosomal miR-1307 and miR-375 for OC.

Methods

The first six candidate miRNAs were selected from the previous literature. The relative quantification of qRT-PCR was used to screen for the stability of exosomal miRNAs, followed by validation of the cohort. ROC analysis was employed to analyze the specificity and sensitivity of exosomal miRNA.

Results

MiR-1307 and miR-375 were confirmed stably existing in serum exosomes of OC. Moreover, miR-1307 and miR-375 were both significantly up-regulated in serum exosomes of OC compared to ovarian benign and healthy groups. The overexpressed miRNAs showed independent diagnostic power and enhanced the diagnostic accuracy of traditional biomarkers when combined with CA-125 and HE4. MiR-1307 was associated with tumor staging, and miR-375 was associated with lymph node metastasis of OC.

Conclusion

Our results suggest that serum exosomal miR-1307 and miR-375 could serve as potential tumor biomarkers to improve diagnostic efficiency for OC.

Methylation and ovarian cancer: Can DNA methylation be of diagnostic use?

Ovarian cancer is a silent killer and, due to late diagnosis and frequent chemo resistance in patients, the primary cause of fatality amongst the various types of gynecological cancer. The discovery of a specific and sensitive biomarker for ovarian cancer could improve early diagnosis, thereby saving lives. Biomarkers could also improve treatment, by predicting which patients will benefit from specific treatment strategies. DNA methylation is an epigenetic mechanism, and 'methylation imbalance' is characteristic of cancer. Previous research suggests that changes in DNA methylation can be used diagnostically, and that they may predict resistance to treatment. This paper gives an up-to-date overview of research investigating the potential of DNA methylation-based markers for diagnostics, prognostics, screening and prediction of drug resistance for ovarian cancer patients. DNA methylation cancer-biomarkers may be useful for cancer treatment, particularly since they are chemically stable and since cancer-associated changes in methylation typically precedes tumor growth. DNA methylation markers could improve diagnosis and treatment and might even be used for screening in the future. Furthermore, DNA methylation biomarkers could facilitate the development of precision medicine. However, at this point no biomarkers for ovarian cancer have a sufficient combination of sensitivity and specificity in a clinical setting. A reason for this is that most studies have focused on a single or a few methylation sites. More large screenings and genome-wide studies must be performed to increase the chance of identifying a DNA methylation marker which can identify ovarian cancer.

Can Presurgical Ultrasound Predict Survival in Women With Ovarian Masses?

PURPOSE

This study aimed to determine the ability of ultrasound to predict survival and detect more aggressive tumors in women with ovarian masses.

MATERIALS AND METHODS

Institutional review board approval was obtained. A total of 167 patients who presented with adnexal mass/masses were included. These were documented as benign or malignant on ultrasound. Age, date of diagnosis and date of death, type of tumor, and tumor marker cancer antigen 125 (CA-125) values were recorded. A CA-125 value of less than 35 U/mL was considered normal. All cases underwent surgery. Pathologic findings were considered as reference standard. The 2 × 2 cross-tabulations were used to correlate dichotomized CA-125, US diagnosis (benign vs malignant), and pathologic status. Difference of distributions was tested using the Wilcoxon rank sum test, and their association was tested using the Fisher exact test. All tests were 2-sided, and P values of 0.05 or less were considered statistically significant. Kaplan-Meir curves were generated to estimate survival.

RESULTS

There was a statistically significant difference in patients with benign versus malignant tumors based on pathology (P < 0.0001) and ultrasound (P < 0.0003). Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of ultrasound were 55%, 86%, 90% and 46%, and 81%. Patients diagnosed as having malignant tumors based on ultrasound had statistically significant worse overall survival. Probability of survival based on pathologic diagnosis of malignancy was statistically significant at P < 0.0003; based on ultrasound, P < 0.0001; and based on CA-125, P < 0.041.

CONCLUSION

Patients who had ultrasound-based prediction of ovarian malignancy had overall worse survival probability (P < 0.0001) compared with CA-125- or pathology-based prediction.