Role of biomarkers for early detection of ovarian cancer recurrence

Modified screening of MYC promotor region elements using the CRISPR library in ovarian cancer

Ovarian cancer remains one of the most lethal gynecological malignancies owing to its high recurrence rate and chemotherapeutic resistance. MYC is a well-known proto-oncogene that is frequently amplified in ovarian cancer and has been implicated in drug resistance. Previously, we established a new promoter-reporter system combined with a CRISPR activation library to identify unknown MYC regulators, and M1AP was identified as a novel MYC regulator. However, considering the insufficient explanation for the absence of guide RNA (gRNA) of MYC, this present study explored methods to prevent the gRNA of MYC itself from binding. This study first modified the promoter-reporter vector to improve its quality, then conducted CRISPR screening and analyzed candidate genes as MYC promoter regulators using next-generation sequencing in OVSAHO ovarian cancer cells. Eighty-six genes had ≥ 1000 reads, and Pearson's correlation coefficient analysis was performed on the cBioPortal of the Cancer Genomics database. Fourteen genes were identified as candidate MYC regulators with positive and significant correlations with MYC. Seven genes, including CYP4v2, ASPH, ANP32D, PCED1A, ABI1, FUZ, and HOOK2, demonstrated significantly higher luciferase activity than the control genes. Four genes, including ABI1, PCED1A, HOOK2, and CYP4v2, activated the MYC promoter, which showed over twofold higher activity than the control when overexpressed using a vector. In conclusion, four genes that activate MYC promoters were identified in an ovarian cancer cell line using the CRISPR library system with a modified promoter-reporter tool. These results will prove helpful in the development of novel treatment strategies for ovarian cancer.

Modern Emerging Biosensing Methodologies for the Early Diagnosis and Screening of Ovarian Cancer

Ovarian cancer (OC) is one of the leading causes of gynecological cancer-related death worldwide. Late diagnosis at advanced stages of OC is the reason for a higher mortality rate. Earlier diagnosis and proper treatment are important for improving the prognosis of OC patients. Biosensors offer accurate, low-cost, rapid, and user-friendly devices that can be employed for the detection of OC-specific biomarkers in the early stage. Therefore, it is important to consider the potential biomarkers in the biological fluids to confirm the OC prognosis. Out of many biomarkers, the most commonly tested clinically is cancer antigen 125 (CA-125). However, CA-125 is considered to be a poor biomarker for OC diagnosis. Several biosensing methods were developed for the sensitive and quantitative detection of each biomarker. In abnormal expression in OC patients, nucleic acids, enzymes, cells, and exosomes are used as target biomarkers for the construction of biosensors. This review focuses on the development for the detection of various biomarkers using multiple biosensing methods. Here, we describe the origin and the significance of OC-associated biomarkers, the working principle of biosensors, and the classification of biosensors based on their recognition elements and signal transducers. The modes of detection and sensitivity of the sensors are discussed. Finally, the challenges in the fabrication, obstacles in the clinical application, and future prospects are discussed.

Colocalization of Cancer-Associated Biomarkers on Single Extracellular Vesicles for Early Detection of Cancer

Detection of cancer early, when it is most treatable, remains a significant challenge because of the lack of diagnostic methods sufficiently sensitive to detect nascent tumors. Early-stage tumors are small relative to their tissue of origin, heterogeneous, and infrequently manifest in clinical symptoms. The detection of early-stage tumors is challenging given the lack of tumor-specific indicators (ie, protein biomarkers, circulating tumor DNA) to enable detection using a noninvasive diagnostic assay. To overcome these obstacles, we have developed a liquid biopsy assay that interrogates circulating extracellular vesicles (EVs) to detect tumor-specific biomarkers colocalized on the surface of individual EVs. We demonstrate the technical feasibility of this approach in human cancer cell line-derived EVs, where we show strong correlations between assay signal and cell line gene/protein expression for the ovarian cancer-associated biomarkers bone marrow stromal antigen-2, folate receptor-α, and mucin-1. Furthermore, we demonstrate that detecting distinct colocalized biomarkers on the surface of EVs significantly improves discrimination performance relative to single biomarker measurements. Using this approach, we observe promising discrimination of high-grade serous ovarian cancer versus benign ovarian masses and healthy women in a proof-of-concept clinical study.

Folate Receptor Alpha-A Secret Weapon in Ovarian Cancer Treatment?

Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy worldwide. Due to its nonspecific symptoms and unreliable screening tools, EOC is not diagnosed at an early stage in most cases. Unfortunately, despite achieving initial remission after debulking surgery and platinum-based chemotherapy, most patients experience the recurrence of the disease. The limited therapy approaches have encouraged scientists to search for new detection and therapeutic strategies. In this review, we discuss the role of folate receptor alpha (FRα) in EOC development and its potential application as a biomarker and molecular target in designing new EOC screening and treatment methods. We summarize the mechanisms of the action of various therapeutic strategies based on FRα, including MABs (monoclonal antibodies), ADCs (antibody-drug conjugates), FDCs (folate-drug conjugates), SMDCs (small molecule-drug conjugates), vaccines, and CAR-T (chimeric antigen receptor T) cells, and present the most significant clinical trials of some FRα-based drugs. Furthermore, we discuss the pros and cons of different FR-based therapies, highlighting mirvetuximab soravtansine (MIRV) as the currently most promising EOC-targeting drug.

Explore the expression of mitochondria-related genes to construct prognostic risk model for ovarian cancer and validate it, so as to provide optimized treatment for ovarian cancer

Background

The use of gene development data from public database has become a new starting point to explore mitochondrial related gene expression and construct a prognostic prediction model of ovarian cancer.

Methods

Data were obtained from the TCGA and ICGC databases, and the intersection with mitochondrial genes was used to obtain the differentially expressed genes. q-PCR, Cox proportional risk regression, minimal absolute contraction and selection operator regression analysis were performed to construct the prognostic risk model, and ROC curve was used to evaluate the model for centralized verification. The association between risk scores and clinical features, tumor mutation load, immune cell infiltration, macrophage activation analysis, immunotherapy, and chemosensitivity was further evaluated.

Results

A prognostic risk score model for ovarian cancer patients was constructed based on 12 differentially expressed genes. The score was highly correlated with ovarian cancer macrophage infiltration and was a good predictor of the response to immunotherapy. M1 and M2 macrophages in the ovarian tissue in the OV group were significantly activated, providing a reference for the study of the polarity change of tumor-related macrophages for the prognosis and treatment of ovarian cancer. In terms of drug sensitivity, the high-risk group was more sensitive to vinblastine, Acetalax, VX-11e, and PD-0325901, while the low-risk group was more sensitive to Sabutoclax, SB-505124, cisplatin, and erlotinib.

Conclusion

The prognostic risk model of ovarian cancer associated to mitochondrial genes built on the basis of public database better evaluated the prognosis of ovarian cancer patients and guided individual treatment.

CA-125:CA72-4 ratio - towards a promising cost-effective tool in ovarian cancer diagnosis and monitoring of post-menopausal women under hormone treatment

Ovarian cancer (OC) is the most lethal gynecological cancer in the developed world. Most cases are diagnosed at late stage III-IV with a very low 5-year overall survival rate. Several studies revealed an elevated risk of OC in users of hormone treatment (HT) compared with non-users. The extended duration of HT is a statistically significant risk factor. Carbohydrate antigen or cancer antigen 125 (CA-125) remains the best screening tool for OC; however, its value is limited due to low specificity, leading to unnecessary interventions, surgeries, and psychological harm. Additionally, the variability of ultrasound interpretation highlights the urgent need to develop a univariate index with higher sensitivity and specificity for early diagnosis of OC in women under HT. Herein we critically review the limitations of biomarkers for the detection of OC aiming to suggest an accurate and cost-effective diagnostic ratio that eliminates the impact of body mass index, age, HT, smoking, and benign ovarian diseases on measurements. Numerous studies combine biomarkers such as CA-125, human epididymis protein 4, and thymidine kinase 1 into diagnostic algorithms. Data suggest that the expression of estrogen receptors may have diagnostic and prognostic value, as the estrogen receptor α (ERα):estrogen receptor β (ERβ) ratio is significantly higher in OC than in normal tissue due to ERβ downregulation. A high positive correlation between expression of CA-125 and carbohydrate antigen or cancer antigen 72 - 4 (CA72-4) with ERα and ERβ, respectively, poses that a novel ratio CA-125:CA72-4 could be nodal for monitoring post-menopausal women under HT.

Ultrasensitive Quantification of MUC16 Antigen/Amine-Terminated Aptamer Interaction by Surface Plasmon Resonance: Kinetic and Thermodynamic Studies

Purpose

MUC16 is a commonly employed biomarker to identify and predict ovarian cancer (OC). Precise measurement of MUC16 levels is essential for the accurate diagnosis, prediction, and management of OC. This research seeks to introduce a new surface plasmon resonance (SPR) biosensor design that utilizes aptamer-based technology to enable the sensitive and real-time detection of MUC16.

Methods

In this study, the sensor chip was immobilized with an anti-MUC16 aptamer (Ap) by utilizing 11-mercaptoundecanoic acid (MUA) as a linker to attach the amine-terminated Ap to the chip using EDC/NHS chemistry.

Results

The results indicated that the newly created aptasensor had a detection limit of 0.03 U/mL for MUC16 concentration, with a linear range of 0.09 to 0.27 U/mL. The findings demonstrate good precision and accuracy (<15%) for each MUC16 concentration, with recoveries ranging from 93% to 96%. Additionally, the aptasensor exhibited high selectivity, good repeatability, stability, and applicability in real human serum samples, indicating its potential as a valuable tool for the diagnosis and treatment of OC.

Conclusion

According to the outcomes, the designed aptasensor exhibited acceptable specificity to detect the CA125 antigen and could be utilized for the serum detection of target antigen by SPR method.

Targeted Photodynamic Therapy using a Vectorized Photosensitizer coupled to Folic Acid Analog induces Ovarian Tumor Cell Death and inhibits IL-6-mediated Inflammation

Ovarian cancer (OC) is one of the most lethal cancers among women. Frequent recurrence in the peritoneum due to the presence of microscopic tumor residues justifies the development of new therapies. Indeed, our main objective is to develop a targeted photodynamic therapy (PDT) treatment of peritoneal carcinomatosis from OC to improve the life expectancy of cancer patients. Herein, we propose a targeted-PDT using a vectorized photosensitizer (PS) coupled with a newly folic acid analog (FAA), named PSFAA, in order to target folate receptor alpha (FRα) overexpressed on peritoneal metastasis. This PSFAA was the result of the coupling of pyropheophorbide-a (Pyro-a), as the PS, to a newly synthesized FAA via a polyethylene glycol (PEG) spacer. The selectivity and the PDT efficacy of PSFAA was evaluated on two human OC cell lines overexpressing FRα compared to fibrosarcoma cells underexpressing FRα. Final PSFAA, including the synthesis of a newly FAA and its conjugation to Pyro-a, was obtained after 10 synthesis steps, with an overall yield of 19%. Photophysical properties of PSFAA in EtOH were performed and showed similarity with those of free Pyro-a, such as the fluorescence and singlet oxygen quantum yields (Φf = 0.39 and ΦΔ = 0.53 for free Pyro-a, and Φf = 0.26 and ΦΔ = 0.41 for PSFAA). Any toxicity of PSFAA was noticed. After light illumination, a dose-dependent effect on PS concentration and light dose was shown. Furthermore, a PDT efficacy of PSFAA on OC cell secretome was detected inducing a decrease of a pro-inflammatory cytokine secretion (IL-6). This new PSFAA has shown promising biological properties highlighting the selectivity of the therapy opening new perspectives in the treatment of a cancer in a therapeutic impasse.

Circulating tumor DNA as a biomarker for predicting progression-free survival and overall survival in patients with epithelial ovarian cancer: a systematic review and meta-analysis

OBJECTIVES

Circulating tumor DNA (ctDNA) is emerging as a potential prognostic biomarker in multiple tumor types. However, despite the many studies available on small series of patients with ovarian cancer, a recent systematic review and meta-analysis is lacking. The objective of this study was to determine the association of ctDNA with progression-free-survival and overall survival in patients with epithelial ovarian cancer.

METHODS

An electronic search was conducted using PubMed (MEDLINE), Embase, CENTRAL (Cochrane Library), and CINAHL-Complete from January 2000 to September 15, 2023. To be included in the analysis the studies had to meet the following pre-specified inclusion criteria: (1) evaluable ctDNA; (2) progression-free-survival and overall survival reported as hazard ratio (HR); and (3) the patient population had epithelial ovarian cancer at the time of ctDNA detection. We evaluated the association of ctDNA with progression-free survival and overall survival. Secondary outcomes focused on sub-group analysis of genomic alterations and international Federation of Gynecology and Obstetrics (FIGO) stage.

RESULTS

A total of 26 studies reporting on 1696 patients with epithelial ovarian cancer were included. The overall concordance rate between plasma-based and tissue-based analyses was approximately 62%. We found that a high level of ctDNA in epithelial ovarian cancer was associated with worse progression-free survival (HR 5.31, 95% CI 2.14 to 13.17, p<0.001) and overall survival (HR 2.98, 95% CI 1.86 to 4.76, p<0.0001). The sub-group analysis showed a greater than threefold increase in the risk of relapse in patients with positive HOXA9 meth-ctDNA (HR 3.84, 95% CI 1.57 to 9.41, p=0.003).

CONCLUSIONS

ctDNA was significantly associated with worse progression-free survival and overall survival in patients with epithelial ovarian cancer. Further prospective studies are needed.

PROSPERO REGISTRATION NUMBER

CRD42023469390.

Circulating tumor cells help differentiate benign ovarian lesions from cancer before surgery: A literature review and proof of concept study using flow cytometry with fluorescence imaging

Current tools are insufficient for distinguishing patients with ovarian cancer from those with benign ovarian lesions before extensive surgery. The present study utilized a readily accessible platform employing a negative selection strategy, followed by flow cytometry, to enumerate circulating tumor cells (CTCs) in patients with ovarian cancer. These counts were compared with those from patients with benign ovarian lesions. CTC counts at baseline, before and after anticancer therapy, and across various clinical scenarios involving ovarian lesions were assessed. A negative-selection protocol we proposed was applied to patients with suspected ovarian cancer and prospectively utilized in those subsequently confirmed to have malignancy. The protocol was implemented before anticancer therapy and at months 3, 6, 9 and 12 post-treatment. A cut-off value for CTC number at 4.75 cells/ml was established to distinguish ovarian malignancy from benign lesions, with an area under the curve of 0.900 (P<0.001). In patients with ovarian cancer, multivariate Cox regression analysis revealed that baseline CTC counts and the decline in CTCs within the first three months post-therapy were significant predictors of prolonged progression-free survival. Additionally, baseline CTC counts independently prognosticated overall survival. CTC counts obtained with the proposed platform, used in the present study, suggest that pre-operative CTC testing may be able to differentiate between malignant and benign tumors. Moreover, CTC counts may indicate oncologic outcomes in patients with ovarian cancer who have undergone cancer therapies.

Safety of bevacizumab and olaparib as frontline maintenance therapy in advanced ovarian cancer: expert review for clinical practice

Olaparib, a poly(ADP-ribose) polymerase inhibitor, in combination with the antiangiogenic agent bevacizumab, is approved as maintenance therapy for patients with newly diagnosed stage III or IV epithelial ovarian cancer who have homologous recombination deficient tumors with a deleterious or suspected deleterious BRCA mutation and/or genomic instability based on the long-lasting survival benefit observed in the PAOLA-1 trial. Despite treatment with olaparib and bevacizumab showing an acceptable safety profile, the rate of discontinuations due to adverse events was relatively high, and toxicity related to this regimen may restrict its clinical use. Proper management of olaparib/bevacizumab-related adverse events is important for the improvement of quality of life and maximization of the efficacy of maintenance therapy. Here, we summarize the safety results of the PAOLA-1 study, focusing on treatment discontinuation reasons and adverse event profiles. We sought to shed light on toxicity monitoring and prevention, providing concise recommendations for the clinical management of the most relevant side effects.

Identifying a Novel Eight-NK Cell-related Gene Signature for Ovarian Cancer Prognosis Prediction

BACKGROUND

Ovarian cancer (OVC) is the most common and costly tumor in the world with unfavorable overall survival and prognosis. This study is aimed to explore the prognostic value of natural killer cells related genes for OVC treatment.

METHODS

RNA-seq and clinical information were acquired from the TCGA-OVC dataset (training dataset) and the GSE51800 dataset (validation dataset). Genes linked to NK cells were obtained from the immPort dataset. Moreover, ConsensusClusterPlus facilitated the screening of molecular subtypes. Following this, the risk model was established by LASSO analysis, and immune infiltration and immunotherapy were then detected by CIBERSORT, ssGSEA, ESTIMATE, and TIDE algorithms.

RESULTS

Based on 23 NK cell-related genes with prognosis, TCGA-OVC samples were classified into two clusters, namely C1 and C2. Of these, C1 had better survival outcomes as well as enhanced immune infiltration and tumor stem cells. Additionally, it was more suitable for immunotherapy and was also sensitive to traditional chemotherapy drugs. The eight-gene prognosis model was constructed and verified via the GSE51800 dataset. Additionally, a high infiltration level of immune cells was observed in low-risk patients. Low-risk samples also benefited from immunotherapy and chemotherapy drugs. Finally, a nomogram and ROC curves were applied to validate model accuracy.

CONCLUSION

The present study identified a RiskScore signature, which could stratify patients with different infiltration levels, immunotherapy, and chemotherapy drugs. Our study provided a basis for precisely evaluating OVC therapy and prognosis.

Therapeutic strategies targeting folate receptor α for ovarian cancer

Epithelial ovarian cancer (EOC) is the deadliest gynecological cancer, and presents a major clinical challenge due to limited treatment options. Folate receptor alpha (FRα), encoded by the FOLR1 gene, is an attractive therapeutically target due to its prevalent and high expression in EOC cells. Recent basic and translational studies have explored several modalities, such as antibody-drug conjugate (ADC), monoclonal antibodies, small molecules, and folate-drug conjugate, to exploit FRα for EOC treatment. In this review, we summarize the function of FRα, and clinical efficacies of various FRα-based therapeutics. We highlight mirvetuximab soravtansine (MIRV), or Elahere (ImmunoGen), the first FRα-targeting ADC approved by the FDA to treat platinum-resistant ovarian cancer. We discuss potential mechanisms and management of ocular adverse events associated with MIRV administration.

Blood Plasma Small Non-Coding RNAs as Diagnostic Molecules for the Progesterone-Receptor-Negative Phenotype of Serous Ovarian Tumors

The expression level of the progesterone receptor (PGR) plays a crucial role in determining the biological characteristics of serous ovarian carcinoma. Low PGR expression is associated with chemoresistance and a poorer outcome. In this study, our objective was to explore the relationship between tumor progesterone receptor levels and RNA profiles (miRNAs, piwiRNAs, and mRNAs) to understand their biological characteristics and behavior. To achieve this, we employed next-generation sequencing of small non-coding RNAs, quantitative RT-PCR, and immunohistochemistry to analyze both FFPE and frozen tumor samples, as well as blood plasma from patients with benign cystadenoma (BSC), serous borderline tumor (SBT), low-grade serous ovarian carcinoma (LGSOC), and high-grade serous ovarian carcinoma (HGSOC). Our findings revealed significant upregulation of MMP7 and MUC16, along with downregulation of PGR, in LGSOC and HGSOC compared to BSC. We observed significant correlations of PGR expression levels in tumor tissue with the contents of miR-199a-5p, miR-214-3p, miR-424-3p, miR-424-5p, and miR-125b-5p, which potentially target MUC16, MMP7, and MMP9, as well as with the tissue content of miR-16-5p, miR-17-5p, miR-20a-5p, and miR-93-5p, which are associated with the epithelial-mesenchymal transition (EMT) of cells. The levels of EMT-associated miRNAs were significantly correlated with the content of hsa_piR_022437, hsa_piR_009295, hsa_piR_020813, hsa_piR_004307, and hsa_piR_019914 in tumor tissues. We developed two optimal logistic regression models using the quantitation of hsa_piR_020813, miR-16-5p, and hsa_piR_022437 or hsa_piR_004307, hsa_piR_019914, and miR-93-5p in the tumor tissue, which exhibited a significant ability to diagnose the PGR-negative tumor phenotype with 93% sensitivity. Of particular interest, the blood plasma levels of miR-16-5p and hsa_piR_022437 could be used to diagnose the PGR-negative tumor phenotype with 86% sensitivity even before surgery and chemotherapy. This knowledge can help in choosing the most effective treatment strategy for this aggressive type of ovarian cancer, such as neoadjuvant chemotherapy followed by cytoreduction in combination with hyperthermic intraperitoneal chemotherapy and targeted therapy, thus enhancing the treatment's effectiveness and the patient's longevity.

A chemotherapy response prediction model derived from tumor-promoting B and Tregs and proinflammatory macrophages in HGSOC

Background

Most patients with high-grade serous ovarian cancer (HGSOC) experienced disease recurrence with cumulative chemoresistance, leading to treatment failure. However, few biomarkers are currently available in clinical practice that can accurately predict chemotherapy response. The tumor immune microenvironment is critical for cancer development, and its transcriptomic profile may be associated with treatment response and differential outcomes. The aim of this study was to develop a new predictive signature for chemotherapy in patients with HGSOC.

Methods

Two HGSOC single-cell RNA sequencing datasets from patients receiving chemotherapy were reinvestigated. The subtypes of endoplasmic reticulum stress-related XBP1+ B cells, invasive metastasis-related ACTB+ Tregs, and proinflammatory-related macrophage subtypes with good predictive power and associated with chemotherapy response were identified. These results were verified in an independent HGSOC bulk RNA-seq dataset for chemotherapy. Further validation in clinical cohorts used quantitative real-time PCR (qRT-PCR).

Results

By combining cluster-specific genes for the aforementioned cell subtypes, we constructed a chemotherapy response prediction model containing 43 signature genes that achieved an area under the receiver operator curve (AUC) of 0.97 (p = 2.1e-07) for the GSE156699 cohort (88 samples). A huge improvement was achieved compared to existing prediction models with a maximum AUC of 0.74. In addition, its predictive capability was validated in multiple independent bulk RNA-seq datasets. The qRT-PCR results demonstrate that the expression of the six genes has the highest diagnostic value, consistent with the trend observed in the analysis of public data.

Conclusions

The developed chemotherapy response prediction model can be used as a valuable clinical decision tool to guide chemotherapy in HGSOC patients.

VCAM-1 complements CA-125 in detecting recurrent ovarian cancer

BACKGROUND

Close to three-quarters of ovarian cancer cases are frequently diagnosed at an advanced stage, with more than 70% of them failing to respond to primary therapy and relapsing within 5 years. There is an urgent need to identify strategies for early detection of ovarian cancer recurrence, which may lead to earlier intervention and better outcomes.

METHODS

A customized magnetic bead-based 8-plex immunoassay was evaluated using a Bio-Plex 200 Suspension Array System. Target protein levels were analyzed in sera from 58 patients diagnosed with advanced ovarian cancer (including 34 primary and 24 recurrent tumors) and 46 healthy controls. The clinical performance of these biomarkers was evaluated individually and in combination for their ability to detect recurrent ovarian cancer.

RESULTS

An 8-plex immunoassay was evaluated with high analytical performance suitable for biomarker validation studies. Logistic regression modeling selected a two-marker panel of CA-125 and VCAM-1 that improved the performance of CA-125 alone in detecting recurrent ovarian cancer (AUC: 0.813 versus 0.700). At a fixed specificity of 83%, the two-marker panel significantly improved sensitivity in separating primary from recurrent tumors (70.8% versus 37.5%, P = 0.004), demonstrating that VCAM-1 was significantly complementary to CA-125 in detecting recurrent ovarian cancer.

CONCLUSIONS

A two-marker panel of CA-125 and VCAM-1 showed strong diagnostic performance and improvement over the use of CA-125 alone in detecting recurrent ovarian cancer. The experimental results warrant further clinical validation to determine their role in the early detection of recurrent ovarian cancer.

Individual recombinant repeats of MUC16 display variable binding to CA125 antibodies

BACKGROUND

Despite its importance in the clinical management of ovarian cancer, the CA125 biomarker - located on the mucin protein MUC16 - is still not completely understood. Questions remain about MUC16's function and structure, specifically the identity and location of the CA125 epitopes.

OBJECTIVE

The goal of this study was to characterize the interaction of individual recombinant repeats from the tandem repeat domain of MUC16 with antibodies used in the clinical CA125 II test.

METHODS

Using E. coli expression, we isolated nine repeats from the putative antigenic domain of CA125. Amino acid composition of recombinant repeats was confirmed by high-resolution mass spectrometry. We characterized the binding of four antibodies - OC125, M11, "OC125-like," and "M11-like" - to nine recombinant repeats using Western blotting, indirect enzyme-linked immunosorbent assay (ELISA), and localized surface plasmon resonance (SPR) spectroscopy.

RESULTS

Each recombinant repeat was recognized by a different combination of CA125 antibodies. OC125 and "OC125-like" antibodies did not bind the same set of recombinant repeats, nor did M11 and "M11-like" antibodies.

CONCLUSIONS

Characterization of the interactions between MUC16 recombinant repeats and CA125 antibodies will contribute to ongoing efforts to identify the CA125 epitopes and improve our understanding of this important biomarker.

Comprehensive Analysis of Purine-Metabolism-Related Gene Signature for Predicting Ovarian Cancer Prognosis, Immune Landscape, and Potential Treatment Options

Purine metabolism is an important branch of metabolic reprogramming and has received increasing attention in cancer research. Ovarian cancer is an extremely dangerous gynecologic malignancy for which there are no adequate tools to predict prognostic risk. Here, we identified a prognostic signature consisting of nine genes related to purine metabolism, including ACSM1, CACNA1C, EPHA4, TPM3, PDIA4, JUNB, EXOSC4, TRPM2, and CXCL9. The risk groups defined by the signature are able to distinguish the prognostic risk and the immune landscape of patients. In particular, the risk scores offer promising personalized drug options. By combining risk scores with clinical characteristics, we have created a more detailed composite nomogram that allows for a more complete and individualized prediction of prognosis. In addition, we demonstrated metabolic differences between platinum-resistant and platinum-sensitive ovarian cancer cells. In summary, we have performed the first comprehensive analysis of genes related to purine metabolism in ovarian cancer patients and created a feasible prognostic signature that will aid in risk prediction and support personalized medicine.

Electrochemical and Photoelectrochemical Immunosensors for the Detection of Ovarian Cancer Biomarkers

Photoelectrochemical (PEC) sensing is an emerging technological innovation for monitoring small substances/molecules in biological or non-biological systems. In particular, there has been a surge of interest in developing PEC devices for determining molecules of clinical significance. This is especially the case for molecules that are markers for serious and deadly medical conditions. The increased interest in PEC sensors to monitor such biomarkers can be attributed to the many apparent advantages of the PEC system, including an enhanced measurable signal, high potential for miniaturization, rapid testing, and low cost, amongst others. The growing number of published research reports on the subject calls for a comprehensive review of the various findings. This article is a review of studies on electrochemical (EC) and PEC sensors for ovarian cancer biomarkers in the last seven years (2016-2022). EC sensors were included because PEC is an improved EC; and a comparison of both systems has, expectedly, been carried out in many studies. Specific attention was given to the different markers of ovarian cancer and the EC/PEC sensing platforms developed for their detection/quantification. Relevant articles were sourced from the following databases: Scopus, PubMed Central, Web of Science, Science Direct, Academic Search Complete, EBSCO, CORE, Directory of open Access Journals (DOAJ), Public Library of Science (PLOS), BioMed Central (BMC), Semantic Scholar, Research Gate, SciELO, Wiley Online Library, Elsevier and SpringerLink.

CA-125 Early Dynamics to Predict Overall Survival in Women with Newly Diagnosed Advanced Ovarian Cancer Based on Meta-Analysis Data

(1) Background: Cancer antigen 125 (CA-125) is a protein produced by ovarian cancer cells that is used for patients' monitoring. However, the best ways to analyze its decline and prognostic role are poorly quantified. (2) Methods: We leveraged individual patient data from the Gynecologic Cancer Intergroup (GCIG) meta-analysis (N = 5573) to compare different approaches summarizing the early trajectory of CA-125 before the prediction time (called the landmark time) at 3 or 6 months after treatment initiation in order to predict overall survival. These summaries included observed and estimated measures obtained by a linear mixed model (LMM). Their performances were evaluated by 10-fold cross-validation with the Brier score and the area under the ROC (AUC). (3) Results: The estimated value and the last observed value at 3 months were the best measures used to predict overall survival, with an AUC of 0.75 CI 95% [0.70; 0.80] at 24 and 36 months and 0.74 [0.69; 0.80] and 0.75 [0.69; 0.80] at 48 months, respectively, considering that CA-125 over 6 months did not improve the AUC, with 0.74 [0.68; 0.78] at 24 months and 0.71 [0.65; 0.76] at 36 and 48 months. (4) Conclusions: A 3-month surveillance provided reliable individual information on overall survival until 48 months for patients receiving first-line chemotherapy.

Non-steroidal anti-inflammatory drugs and biomarkers: A new paradigm in colorectal cancer

Colorectal cancer is a sporadic, hereditary, or familial based disease in its origin, caused due to diverse set of mutations in large intestinal epithelial cells. Colorectal cancer (CRC) is a common and deadly disease that accounts for the 4th worldwide highly variable malignancy. For the early detection of CRC, the most common predictive biomarker found endogenously are KRAS and ctDNA/cfDNA along with SEPT9 methylated DNA. Early detection and screening for CRC are necessary and multiple methods can be employed to screen and perform early diagnosis of CRC. Colonoscopy, an invasive method is most prevalent for diagnosing CRC or confirming the positive result as compared to other screening methods whereas several non-invasive techniques such as molecular analysis of breath, urine, blood, and stool can also be performed for early detection. Interestingly, widely used medicines known as non-steroidal anti-inflammatory drugs (NSAIDs) to reduce pain and inflammation have reported chemopreventive impact on gastrointestinal malignancies, especially CRC in several epidemiological and preclinical types of research. NSAID acts by inhibiting two cyclooxygenase enzymes, thereby preventing the synthesis of prostaglandins (PGs) and causing NSAID-induced apoptosis and growth inhibition in CRC cells. This review paper majorly focuses on the diversity of natural and synthetic biomarkers and various techniques for the early detection of CRC. An approach toward current advancement in CRC detection techniques and the role of NSAIDs in CRC chemoprevention has been explored systematically. Several prominent governing mechanisms of the anti-cancer effects of NSAIDs and their synergistic effect with statins for an effective chemopreventive measure have also been discussed in this review paper.

Individual recombinant repeats of MUC16 display variable binding to CA125 antibodies

BACKGROUND

Despite its importance in the clinical management of ovarian cancer, the CA125 biomarker-located on the mucin protein MUC16-is still not completely understood. Questions remain about MUC16's function and structure, specifically the identity and location of the CA125 epitopes.

OBJECTIVE

The goal of this study was to characterize the interaction of individual recombinant repeats from the tandem repeat domain of MUC16 with antibodies used in the clinical CA125 II test.

METHODS

Using E. coli expression, we isolated nine repeats from the putative antigenic domain of CA125. Amino acid composition of recombinant repeats was confirmed by high-resolution mass spectrometry. We characterized the binding of four antibodies-OC125, M11, "OC125-like," and "M11-like"-to nine recombinant repeats using Western blotting, indirect enzyme-linked immunosorbent assay (ELISA), and localized surface plasmon resonance (SPR) spectroscopy.

RESULTS

Each recombinant repeat was recognized by a different combination of CA125 antibodies. OC125 and "OC125-like" antibodies did not bind the same set of recombinant repeats, nor did M11 and "M11-like" antibodies.

CONCLUSIONS

Characterization of the interactions between MUC16 recombinant repeats and CA125 antibodies will contribute to ongoing efforts to identify the CA125 epitopes and improve our understanding of this important biomarker.

Copenhagen index (CPH-I) is more favorable than CA125, HE4, and risk of ovarian malignancy algorithm (ROMA): Nomogram prediction models with clinical-ultrasonographic feature for diagnosing ovarian neoplasms

Background

We aimed to analyze the benign and malignant identification efficiency of CA125, HE4, risk of ovarian malignancy algorithm (ROMA), Copenhagen Index (CPH-I) in ovarian neoplasms and establish a nomogram to improve the preoperative evaluation value of ovarian neoplasms.

Methods

A total of 3,042 patients with ovarian neoplasms were retrospectively classified according to postoperative pathological diagnosis [benign, n = 2389; epithelial ovarian cancer (EOC), n = 653]. The patients were randomly divided into training and test cohorts at a ratio of 7:3. Using CA125, HE4, ROMA, and CPH-I, Receiver operating characteristic (ROC) curves corresponding to different truncation values were calculated and compared, and optimal truncation values were selected. Clinical and imaging risk factors were calculated using univariate regression, and significant variables were selected for multivariate regression analysis combined with ROMA and CPH-I. Nomograms were constructed to predict the occurrence of EOC, and the accuracy was assessed by external validation.

Results

When the cutoff value of CA125, HE4, ROMA, and CPH-I was 100 U/ml, 70 pmol/L, 12.5/14.4% (premenopausal/postmenopausal) and 5%, respectively, the AUC was 0.674, 0.721, 0.750 and 0.769, respectively. From univariate regression, the clinical risk factors were older age, menopausal status, higher birth rate, hypertension, and diabetes; imaging risk factors were multilocular tumors, solid nodules, bilateral tumors, larger tumor diameter, and ascites. The AUC of the nomogram containing ROMA and CPH-I was 0.8914 and 0.9114, respectively, which was better than the prediction accuracies of CA125, HE4, ROMA, and CPH-I alone. The nomogram with CPH-I was significantly better than that with ROMA (P < 0.001), and a nomogram decision curve analysis (DCA) containing CPH-I seemed to have better clinical benefits than ROMA. For external validation of this nomogram containing ROMA and CPH-I, the C-indices were 0.889 and 0.900, and the calibration curves were close to 45°, showing good agreement with the predicted values.

Conclusion

We conclude that CPH-I and ROMA have higher diagnostic values in the preoperative diagnosis of EOC than other single tumor markers like CA125 or HE4. A nomogram based on CPH-I and ROMA with clinical and ultrasonic indicators had a better diagnostic value, and the CPH-I nomogram had the highest diagnostic efficacy.

Engineering of a Fully Human Anti-MUC-16 Antibody and Evaluation as a PET Imaging Agent

Antibodies that recognize cancer biomarkers, such as MUC16, can be used as vehicles to deliver contrast agents (imaging) or cytotoxic payloads (therapy) to the site of tumors. MUC16 is overexpressed in 80% of epithelial ovarian cancer (EOC) and 65% of pancreatic ductal adenocarcinomas (PDAC), where effective ‘theranostic’ probes are much needed. This work aims to develop fully human antibodies against MUC16 and evaluate them as potential immuno-PET imaging probes for detecting ovarian and pancreatic cancers. We developed a fully human monoclonal antibody, M16Ab, against MUC16 using phage display. M16Ab was conjugated with p-SCN-Bn-DFO and radiolabeled with 89Zr. 89Zr-DFO-M16Ab was then evaluated for binding specificity and affinity using flow cytometry. In vivo evaluation of 89Zr-DFO-M16Ab was performed by microPET/CT imaging at different time points at 24−120 h post injection (p.i.) and ex vivo biodistribution studies in mice bearing MUC16-expressing OVCAR3, SKOV3 (ovarian) and SW1990 (pancreatic) xenografts. 89Zr-DFO-M16Ab bound specifically to MUC16-expressing cancer cells with an EC50 of 10nM. 89Zr-DFO-M16Ab was stable in serum and showed specific uptake and retention in tumor xenografts even after 120 h p.i. (microPET/CT) with tumor-to-blood ratios > 43 for the SW1990 xenograft. Specific tumor uptake was observed for SW1990/OVCAR3 xenografts but not in MUC16-negative SKOV3 xenografts. Pharmacokinetic study shows a relatively short distribution (t1/2α) and elimination half-life (t1/2ß) of 4.4 h and 99 h, respectively. In summary, 89Zr-DFO-M16Ab is an effective non-invasive imaging probe for ovarian and pancreatic cancers and shows promise for further development of theranostic radiopharmaceuticals.

Protein expression profiling identifies a prognostic model for ovarian cancer

BACKGROUND

Owing to the high morbidity and mortality, ovarian cancer has seriously endangered female health. Development of reliable models can facilitate prognosis monitoring and help relieve the distress.

METHODS

Using the data archived in the TCPA and TCGA databases, proteins having significant survival effects on ovarian cancer patients were screened by univariate Cox regression analysis. Patients with complete information concerning protein expression, survival, and clinical variables were included. A risk model was then constructed by performing multiple Cox regression analysis. After validation, the predictive power of the risk model was assessed. The prognostic effect and the biological function of the model were evaluated using co-expression analysis and enrichment analysis.

RESULTS

394 patients were included in model construction and validation. Using univariate Cox regression analysis, we identified a total of 20 proteins associated with overall survival of ovarian cancer patients (p < 0.01). Based on multiple Cox regression analysis, six proteins (GSK3α/β, HSP70, MEK1, MTOR, BAD, and NDRG1) were used for model construction. Patients in the high-risk group had unfavorable overall survival (p < 0.001) and poor disease-specific survival (p = 0.001). All these six proteins also had survival prognostic effects. Multiple Cox regression analysis demonstrated the risk model as an independent prognostic factor (p < 0.001). In receiver operating characteristic curve analysis, the risk model displayed higher predictive power than age, tumor grade, and tumor stage, with an area under the curve value of 0.789. Analysis of co-expressed proteins and differentially expressed genes based on the risk model further revealed its prognostic implication.

CONCLUSIONS

The risk model composed of GSK3α/β, HSP70, MEK1, MTOR, BAD, and NDRG1 could predict survival prognosis of ovarian cancer patients efficiently and help disease management.

Biomarkers for Early Diagnosis of Ovarian Carcinoma

The leading cause of gynecological cancer-related morbidity and mortality is ovarian cancer (OC), which is dubbed a silent killer. Currently, OC is a target of intense biomarker research, because it is often not discovered until the disease is advanced. The goal of OC research is to develop effective tests using biomarkers that can detect the disease at the earliest stages, which would eventually decrease the mortality, thereby preventing recurrence. Therefore, there is a pressing need to revisit the existing biomarkers to recognize the potential biomarkers that can lead to efficient predictors for the OC diagnosis. This Perspective covers an update on the currently available biomarkers used in the triaging of OC to gain certain insights into the potential role of these biomarkers and their estimation that are crucial to the understanding of neoplasm progression, diagnostics, and therapy.

Diagnostic and prognostic role of TFF3, Romo-1, NF-кB and SFRP4 as biomarkers for endometrial and ovarian cancers: a prospective observational translational study

Purpose

This study aimed to evaluate trefoil factor 3 (TFF3), secreted frizzled-related protein 4 (sFRP4), reactive oxygen species modulator 1 (Romo1) and nuclear factor kappa B (NF-κB) as diagnostic and prognostic markers of endometrial cancer (EC) and ovarian cancer (OC).

Methods

Thirty-one patients with EC and 30 patients with OC undergone surgical treatment were enrolled together with 30 healthy controls in a prospective study. Commercial ELISA kits determined serum TFF-3, Romo-1, NF-кB and sFRP-4 concentrations.

Results

Serum TFF-3, Romo-1 and NF-кB levels were significantly higher in patients with EC and OC than those without cancer. Regarding EC, none of the serum biomarkers differs significantly between endometrial and non-endometrioid endometrial carcinomas. Mean serum TFF-3 and NF-кB levels were significantly higher in advanced stages. Increased serum levels of TFF-3 and NF-кB were found in those with a higher grade of the disease. Regarding OC, none of the serum biomarkers differed significantly among histological subtypes. Significantly increased serum levels of NF-кB were observed in patients with advanced-stage OC than those with stage I and II diseases. No difference in serum biomarker levels was found between those who had a recurrence and those who had not. The sensibility and specificity of these four biomarkers in discriminating EC and OC from the control group showed encouraging values, although no one reached 70%.

Conclusions

TFF-3, Romo-1, NF-кB and SFRP4 could represent new diagnostic and prognostic markers for OC and EC. Further studies are needed to validate our results.

Correlation of Preoperative Serum and Intraoperative Peritoneal Lavage Fluid Ca-125 Levels with Postoperative Tumor Histology in Patients with Endometrial Cancer: A Prospective-Controlled Study

BACKGROUND

The role of Ca-125 in endometrial cancer is not fully known. Some authors have reported high Ca-125 levels in patients with recurrent or advanced endometrial cancer, whereas others have stated that Ca-125 levels and the advance of the disease were not correlated in endometrial cancer. This makes it inevitable for clinicians to search for different measurement methods or interpretation of the present tumor markers. The aim of this study was to evaluate the relationship between Ca-125 values of the serum and abdominal lavage fluid and postoperative histopathological parameters in patients with endometrial carcinoma.

METHODS

The study included patients who were diagnosed with endometrial cancer in the Gynecology Clinic and were planned to undergo surgery. The correlations of clinicopathological parameters with preoperative values of Ca-125 measured from serum and abdominal lavage fluid were investigated. The Spearman correlation test was applied in the analysis of correlations of serum and abdominal lavage fluid Ca-125 values with postoperative tumor characteristics.

RESULTS

The serum Ca-125 values were determined to be positively correlated with surgical stage, tumor diameter, and lymph node involvement (p = 0.03; p = 0.04; and p = 0.01, respectively). No correlation was determined between tumor grade and serum Ca-125 level. The level of Ca-125 in the abdominal lavage fluid was observed to be correlated with surgical stage and tumor grade, but not with tumor diameter or lymph node involvement (p = 0.01, p = 0.04, respectively).

CONCLUSIONS

The value of Ca-125 in the abdominal lavage fluid has a positive correlation with the surgical stage and tumor grade in patients with endometrial carcinoma.

Hypoxia-Induced LncRNA-MIR210HG Promotes Cancer Progression By Inhibiting HIF-1α Degradation in Ovarian Cancer

LncRNA-MIR210HG plays crucial roles in the progression of diverse cancers. However, the expression and function of MIR210HG in ovarian cancer remains unclear. In the present study, we aimed to determine the expression and function of lncRNA-MIR210HG in ovarian cancer under hypoxic conditions. MIR210HG expression in ovarian cancer cells under hypoxic conditions was determined by qPCR analysis, and the distribution was determined by FISH and qPCR analysis based on cell nucleus and cytosol RNA extraction. Epithelial-Mesenchymal Transition (EMT) assay and human umbilical vein endothelial cell-based tube formation and migration assays were employed to determine the potential function of MIR210HG in vitro, followed by establishment of a subcutaneous tumor model in mice. The direct target of MIR210HG was determined by RNA pull-down and western blotting. Furthermore, the expression and clinical correlation of MIR210HG was determined based on malignant tissues from ovarian cancer patients. Our results indicated that MIR210HG was induced by hypoxia, which is HIF-1α dependent and mainly located in the cytosol of ovarian cancer cells. Knockdown of MIR210HG significantly inhibited EMT and tumor angiogenesis in vitro and impaired tumor growth in mice. Molecular investigations indicated that MIR210HG directly targets HIF-1α protein and inhibits VHL-dependent HIF-1α protein degradation in ovarian cancer. Further results demonstrated that MIR210HG was upregulated in ovarian cancer tissues and correlated with tumor progression and poor prognosis of ovarian cancer patients. Our study suggests that hypoxia-induced MIR210HG promotes cancer progression by inhibiting HIF-1α degradation in ovarian cancer, which could be a therapeutic target for ovarian cancer.

Revisiting antibody-drug conjugates and their predictive biomarkers in platinum-resistant ovarian cancer

Until to date, platinum derived drugs are still the backbone of treating ovarian cancer (OC). Most patients treated with platinum-based chemotherapy develop resistance during the course of their management. The treatment of platinum-resistant ovarian cancer (PROC) is challenging. Few therapeutic options are available for patients with this aggressive disease. Besides, there are liminal advances regarding new anticancer drugs as well as validated predictive biomarkers of clinical outcomes in this setting. The enrollment of PROC patients in interventional studies is limited as compared to newly launched clinical trials for platinum-sensitive OC. Enthusiastically, the emergence of antibody-drug conjugates (ADCs) has provided promising findings for further clinical development in PROC. ADCs have the advantage to selectively deliver cytotoxic drugs to cancer cells expressing several of antigens using specific monoclonal antibodies based on the concept of immune bioconjugation. This innovative class of therapeutics showed encouraging early signs of clinical efficacy in PROC particularly mirvetuximab soravtansine that has been successfully introduced into three randomized and controlled phase III studies. In this review, the evidence from clinical trials supporting the development of ADCs targeting folate receptor alpha, sodium-dependent phosphate transporter 2B, dipeptidase 3, mesothelin, mucin 16, and tissue factor using various cytotoxic payloads in PROC is reviewed.

Recurrence monitoring for ovarian cancer using a cell phone-integrated paper device to measure the ovarian cancer biomarker HE4/CRE ratio in urine

Ovarian cancer has a poor cure rate and rates of relapse are high. Current recurrence detection is limited by non-specific methods such as blood testing and ultrasound. Based on reports that human epididymis four (HE4) / creatinine (CRE) ratios found in urine are elevated in ovarian cancers, we have developed a paper-based device that combines lateral flow technology and cell phone analysis to quantitatively measure HE4/CRE. Surrogate samples were used to test the performance over clinically expected HE4/CRE ratios. For HE4/CRE ratios of 2 to 47, the percent error was found to be 16.0% on average whether measured by a flatbed scanner or cell phone. There was not a significant difference between the results from the cell phone or scanner. Based on published studies, error in this method was less than the difference required to detect recurrence. This promising new tool, with further development, could be used at home or in low-resource settings to provide timely detection of ovarian cancer recurrence.

The Clinical and Pathological Characteristics of Malignant Struma Ovarii: An Analysis of 144 Published Patients

The objective of this study is to summarize the clinical and pathologic characteristics of malignant struma ovarii to facilitate the early diagnosis and treatment of this disease. All 144 patients were females from 27 countries. The mean age of the patients at diagnosis was 42.6 years. Overall, 35.71% of the patients underwent unilateral oophorectomy, 58.57% of the patients underwent bilateral oophorectomy, 5.72% of the patients were not ovariectomized, and 38.57% of the patients received radioactive iodine treatment with an average dose of 158.22 mCI each time. “Impure” types accounted for 70.19% of the cases, while pure types accounted for 29.81% of the cases. Among these cases, papillary thyroid carcinoma accounted for 50.00%, follicular thyroid carcinoma accounted for 26.47%, follicular variant of papillary thyroid carcinoma accounted for 18.63%, papillary and follicular mixed thyroid carcinoma accounted for 2.94%, anaplastic carcinoma accounted for 0.98%, and medullary carcinoma accounted for 0.98%. In total, 21 patients (51.22%) had elevated CA125. More than half of the patients (51.94%) had metastasis outside the ovary. The most common metastatic site was the pelvic cavity. The misdiagnosis rate was 17.27%. Mortality was related to metastasis and the cancer type. Gene mutations were found in the NRAS, KRAS, BRAF, and KIT genes and were similar to those in thyroid carcinoma, but some patients (37.5%) did not exhibit any gene mutations. Regardless of the treatment received, the survival rate is high. Treatment could initially include ovariectomy; however, in cases with metastasis and iodine uptake of the metastatic tumor, thyroidectomy, radioactive iodine therapy, and thyroid hormone inhibiting therapy are indicated.

Histological Characteristics and Early-Stage Diagnosis Are Associated With Better Survival in Young Patients With Epithelial Ovarian Cancer: A Retrospective Analysis Based on Surveillance Epidemiology and End Results Database

PURPOSE

To analyze the potential prognostic factors of epithelial ovarian cancer (EOC) in women aged under 35 compared to those aged 60-79.

METHODS

Cases were retrospectively obtained from SEER database. Clinical characteristics, such as race, histological type, AJCC stage, laterality of tumors, CA125 results, and surgical strategies, were analyzed in < 35 years group and 60-79 years group. Kaplan-Meier survival curves were used to evaluate overall survival (OS) and cause-specific survival (CSS). Cox proportional hazard model was used to identify the predictors for CSS.

RESULTS

Sixteen thousand eight hundred forty-seven EOC patients diagnosed in 2004-2015 were identified from SEER database, with 1,015 aged under 35 and 15,833 aged 60-79. In < 35 years group, mucinous (32.2%) was the most common histological type, followed by high-grade serous (26.6%) and endometrioid (18.3%), while in 60-79 years group, high-grade serous (68.3%) represented the leading histological type. Most young women were diagnosed at stage I (57.7%), while most old women were diagnosed at stage (48.1%). Both 5-year OS and 5-year CSS were higher in < 35 years group (5-year OS: 76.00% vs 40.18%, p < 0.001; 5-year CSS: 83.56% vs 55.18%, p < 0.001). The multivariate analysis identified histological type and stage as prognostic factors for CSS in both groups. Endometrioid represented a positive predictor for CSS, while carcinosarcoma and malignant Brenner were related to a worse CSS. (< 35 years group: carcinosarcoma vs endometrioid: HR 5.630, p=0.024; malignant Brenner vs endometrioid: HR 4.005, p < 0.001; 60-79 years group: carcinosarcoma vs endometrioid: HR 3.606, p < 0.001; malignant Brenner vs endometrioid: HR 2.291, p < 0.001). Tumors laterality, CA125 levels, surgery and lymphadenectomy failed to be associated with the CSS in < 35 years group, while found to be independent risk factors in 60-79 years group.

CONCLUSION

EOC women aged under 35 had a better survival outcome over EOC women aged 60-79, owing to high proportion of endometrioid and mucinous types in histology, as well as early-stage diagnosis. Identification of histological types and gene profiles should be underscored in young EOC patients.