New Predictive Biomarkers for Ovarian Cancer

Targeting tumour markers in ovarian cancer treatment

Ovarian cancers (OC) are the most common, lethal, and stage-dependent cancers at the global level, specifically in female patients. Targeted therapies involve the administration of drugs that specifically target the alterations in tumour cells responsible for their growth, proliferation, and metastasis, with the aim of treating particular patients. Presently, within the realm of gynaecological malignancies, specifically in breast and OCs, there exist various prospective therapeutic targets encompassing tumour-intrinsic signalling pathways, angiogenesis, homologous-recombination deficit, hormone receptors, and immunologic components. Breast cancers are often detected in advanced stages, primarily due to the lack of a reliable screening method. However, various tumour markers have been extensively researched and employed to evaluate the condition, progression, and effectiveness of medication treatments for this ailment. The emergence of recent technological advancements in the domains of bioinformatics, genomics, proteomics, and metabolomics has facilitated the exploration and identification of hitherto unknown biomarkers. The primary objective of this comprehensive review is to meticulously investigate and analyze both established and emerging methodologies employed in the identification of tumour markers associated with OC.

Ovarian cancer

ABSTRACT

Ovarian cancer, a leading cause of cancer deaths, poses challenges due to insidious development and vague signs and symptoms. Risk factors include age, reproductive history, genetic mutations, and environmental factors. Treatment involves surgery, chemotherapy, and targeted therapy, with nursing interventions focusing on symptom management and supportive care.

Serum Lipidome Profiling Reveals a Distinct Signature of Ovarian Cancer in Korean Women

BACKGROUND

Distinguishing ovarian cancer from other gynecological malignancies is crucial for patient survival yet hindered by non-specific symptoms and limited understanding of ovarian cancer pathogenesis. Accumulating evidence suggests a link between ovarian cancer and deregulated lipid metabolism. Most studies have small sample sizes, especially for early-stage cases, and lack racial/ethnic diversity, necessitating more inclusive research for improved ovarian cancer diagnosis and prevention.

METHODS

Here, we profiled the serum lipidome of 208 ovarian cancer, including 93 early-stage patients with ovarian cancer and 117 nonovarian cancer (other gynecological malignancies) patients of Korean descent. Serum samples were analyzed with a high-coverage liquid chromatography high-resolution mass spectrometry platform, and lipidome alterations were investigated via statistical and machine learning (ML) approaches.

RESULTS

We found that lipidome alterations unique to ovarian cancer were present in Korean women as early as when the cancer is localized, and those changes increase in magnitude as the diseases progresses. Analysis of relative lipid abundances revealed specific patterns for various lipid classes, with most classes showing decreased abundance in ovarian cancer in comparison with other gynecological diseases. ML methods selected a panel of 17 lipids that discriminated ovarian cancer from nonovarian cancer cases with an AUC value of 0.85 for an independent test set.

CONCLUSIONS

This study provides a systemic analysis of lipidome alterations in human ovarian cancer, specifically in Korean women.

IMPACT

Here, we show the potential of circulating lipids in distinguishing ovarian cancer from nonovarian cancer conditions.

Sensitivity and Specificity of Selected Biomarkers and Their Combinations in the Diagnosis of Ovarian Cancer

One of the greatest challenges in modern gynecological oncology is ovarian cancer. Despite the numerous studies currently being conducted, it is still sometimes detected at late clinical stages, where the prognosis is unfavorable. One significant contributing factor is the absence of sensitive and specific parameters that could aid in early diagnosis. An ideal screening test, in view of the low incidence of ovarian cancer, should have a sensitivity of greater than 75% and a specificity of at least 99.6%. To enhance sensitivity and specificity, diagnostic panels are being created by combining individual markers. The drive to develop better screening tests for ovarian cancer focuses on modern diagnostic methods based on molecular testing, which in turn aims to find increasingly effective biomarkers. Currently, researchers' efforts are focused on the search for a complementary parameter to those most commonly used that would satisfactorily enhance the sensitivity and specificity of assays. Several biomarkers, including microRNA molecules, autoantibodies, cDNA, adipocytokines, and galectins, are currently being investigated by researchers. This article reviews recent studies comparing the sensitivity and specificity of selected parameters used alone and in combination to increase detection of ovarian cancer at an early stage.

Current strategies for early epithelial ovarian cancer detection using miRNA as a potential tool

Ovarian cancer is one of the most aggressive and significant malignant tumor forms in the female reproductive system. It is the leading cause of death among gynecological cancers owing to its metastasis. Since its preliminary disease symptoms are lacking, it is imperative to develop early diagnostic biomarkers to aid in treatment optimization and personalization. In this vein, microRNAs, which are short sequence non-coding molecules, displayed great potential as highly specific and sensitive biomarker. miRNAs have been extensively advocated and proven to serve an instrumental part in the clinical management of cancer, especially ovarian cancer, by promoting the cancer cell progression, invasion, delayed apoptosis, epithelial-mesenchymal transition, metastasis of cancer cells, chemosensitivity and resistance and disease therapy. Here, we cover our present comprehension of the most up-to-date microRNA-based approaches to detect ovarian cancer, as well as current diagnostic and treatment strategies, the role of microRNAs as oncogenes or tumor suppressor genes, and their significance in ovarian cancer progression, prognosis, and therapy.

Screening and prevention of ovarian cancer

Ovarian cancer remains the most lethal gynaecological malignancy with 314 000 cases and 207 000 deaths annually worldwide. Ovarian cancer cases and deaths are predicted to increase in Australia by 42% and 55% respectively by 2040. Earlier detection and significant downstaging of ovarian cancer have been demonstrated with multimodal screening in the largest randomised controlled trial of ovarian cancer screening in women at average population risk. However, none of the randomised trials have demonstrated a mortality benefit. Therefore, ovarian cancer screening is not currently recommended in women at average population risk. More frequent surveillance for ovarian cancer every three to four months in women at high risk has shown good performance characteristics and significant downstaging, but there is no available information on a survival benefit. Population testing offers an emerging novel strategy to identify women at high risk who can benefit from ovarian cancer prevention. Novel multicancer early detection biomarker, longitudinal multiple marker strategies, and new biomarkers are being investigated and evaluated for ovarian cancer screening. Risk-reducing salpingo-oophorectomy (RRSO) decreases ovarian cancer incidence and mortality and is recommended for women at over a 4-5% lifetime risk of ovarian cancer. Pre-menopausal women without contraindications to hormone replacement therapy (HRT) undergoing RRSO should be offered HRT until 51 years of age to minimise the detrimental consequences of premature menopause. Currently risk-reducing early salpingectomy and delayed oophorectomy (RRESDO) should only be offered to women at increased risk of ovarian cancer within the context of a research trial. Pre-menopausal early salpingectomy is associated with fewer menopausal symptoms and better sexual function than bilateral salpingo-oophorectomy. A Sectioning and Extensively Examining the Fimbria (SEE-FIM) protocol should be used for histopathological assessment in women at high risk of ovarian cancer who are undergoing surgical prevention. Opportunistic salpingectomy may be offered at routine gynaecological surgery to all women who have completed their family. Long term prospective opportunistic salpingectomy studies are needed to determine the effect size of ovarian cancer risk reduction and the impact on menopause.

New Achievements from Molecular Biology and Treatment Options for Refractory/Relapsed Ovarian Cancer-A Systematic Review

Ovarian cancer (OC) has a high rate of mortality and is the fifth most common cause of death in females all over the world. The etiology is still unclear. Numerous factors such as smoking, obesity, and unhealthy diet may affect the risk of OC. Having a family history of breast and OC is one of the main risks for developing OC. Mutations of BRCA1/2 are associated with OC risk as well. The histopathological classification of OC reveals the four most common types: serous, clear cell, endometrioid, and mucinous; these are epithelial OC types, and other types are rare. Furthermore, OC can be subdivided into types I and II. Type I tumors are most probably caused by atypical proliferative tumors. Type II tumors include high-grade carcinoma of the serous type, carcinosarcoma, and carcinoma, which are not differentiated and generally originate from tubal intraepithelial carcinoma of the serous type. Typically, type I tumors are present in early stages, usually with good prognosis. Type II tumors are classified as high-grade tumors and are most often diagnosed at advanced FIGO stages with poor prognosis. High-grade serous OC accounts for 90% of serous OC. Tumor heterogeneity aggravates OC treatment. The standard care for primary epithelial ovarian cancer (EOC) is cytoreductive surgery followed by platinum-based chemotherapy. Neoadjuvant chemotherapy can be used in certain cases followed by cytoreductive surgery. The main prognostic factor is complete tumor resection. However, about 70% of patients relapse. Resistance to chemotherapeutic agents remains a major challenge in EOC treatment, in which many different factors are involved. In recent years, the examination of molecular parameters and their prognostic impact has become increasingly relevant in EOC, and furthermore, the use of immunotherapy has expanded the therapeutic range. As the clinical need is greatest for relapsed patients, this systematic review will focus on recent advances in molecular biology with prognostic and predictive markers and treatment options for recurrent/refractory OC. Inclusion criteria for the review: potential prospective or predictive biomarkers in preclinical or clinical use in relapsed and refractory OC, prognostic impact, clinical and preclinical trials, and immunotherapy. Exclusion criteria for the review: primary OC, no full text or abstract available, not the topic mentioned above, and text not available in English. Risk of bias: the included studies were evaluated descriptively for the topics mentioned above, and data were not compared with each other. The objective is to highlight the molecular mechanisms of the most promising targeted agents under clinical investigation to demonstrate their potential relevance in recurrent/refractory OC.

SOX11 and Epithelial-Mesenchymal Transition in Metastatic Serous Ovarian Cancer

BACKGROUND

Ovarian cancer is the leading cause of death from gynecological malignancies, with serous carcinoma being the most common histopathologic subtype. Epithelial-mesenchymal transition (EMT) correlates with increased metastatic potential, whereas the transcription factor SRY-box transcription factor 11 (SOX11) is overexpressed in diverse malignancies.

METHODS

In the present study, we aimed to evaluate the potential role of the immunohistochemical expression of SOX11 in 30 serous ovarian carcinomas in association with E-cadherin and vimentin expression as well as with patients' clinicopathological data.

RESULTS

Most of the examined cases showed concurrent expression of E-cadherin and vimentin, whereas SOX11 was expressed in a minority of the cases (26.7%). Interestingly, the positive cases more frequently had a metastatic disease at the time of diagnosis compared with the negative cases (p = 0.09), an association, however, of marginal significance. Moreover, there was a negative correlation between E-cadherin and SOX11 expression (p = 0.0077) and a positive correlation between vimentin and SOX11 expression (p = 0.0130).

CONCLUSIONS

The present work, for the first time, provides preliminary evidence of a possible implication of SOX11 overexpression in the promotion of EMT in metastatic serous ovarian cancer, thereby endorsing tumor metastasis.

Epithelial Ovarian Cancer: A Five Year Review

Ovarian cancer is a malignant disease that affects thousands of patients every year. Currently, we use surgical techniques for early-stage cancer and chemotherapy treatment combinations for advanced stage cancer. Several novel therapies are currently being investigated, with gene therapy and stem cell therapy being the corner stone of this investigation. We conducted a thorough search on PubMed and gathered up-to-date information regarding epithelial ovarian cancer therapies. We present, in the current review, all novel treatments that were investigated in this field over the past five years, with a particular focus on local treatment.

Role of Syndecans in Ovarian Cancer: New Diagnostic and Prognostic Biomarkers and Potential Therapeutic Targets

Ovarian cancer (OC) is the eighth cancer both in prevalence and mortality in women and represents the deadliest female reproductive cancer. Due to generally vague symptoms, OC is frequently diagnosed only at a late and advanced stage, resulting in high mortality. The tumor extracellular matrix and cellular matrix receptors play a key role in the pathogenesis of tumor progression. Syndecans are a family of four transmembrane heparan sulfate proteoglycans (PG), including syndecan-1, -2, -3, and -4, which are dysregulated in a myriad of cancers, including OC. Many clinicopathological studies suggest that these proteins are promising diagnostic and prognostic biomarkers for OC. Furthermore, functions of the syndecan family in the regulation of cellular processes make it an interesting pharmacological target for anticancer therapies.

Prognostic significance of systemic immune-inflammation index in patients with ovarian cancer: a meta-analysis

Background

The prognosis of several malignancies has been influenced by the systemic immune-inflammation index (SII); however, its association with the prognostic outcome of ovarian cancer (OC) remains controversial. The present meta-analysis focused on the systemic and comprehensive identification of the role of SII in predicting OC prognosis.

Methods

We searched the Web of Science, PubMed, Cochrane Library, Embase, and China National Knowledge Infrastructure (CNKI) from inception until March 6, 2023. To predict the prognostic value of SII for overall survival (OS) and progression-free survival (PFS) in patients with OC, we calculated pooled hazard ratios (HRs) and corresponding 95% confidence intervals (CIs).

Results

The meta-analysis included six studies involving 1546 patients. The combined results showed that a high SII was significantly associated with poor OS (HR=2.70, 95% CI=1.98-3.67, p<0.001) and poor PFS (HR=2.71, 95% CI=1.78-4.12, p<0.001) in OC patients. These results were confirmed using subgroup and sensitivity analyses.

Conclusion

Our results concluded that a high SII significantly predicted poor OS and PFS in patients with OC. Therefore, it can be speculated that the SII may have an independent effect on the prognosis of OC.

Evaluation of the Potential Diagnostic Utility of the Determination of Selected Immunological and Molecular Parameters in Patients with Ovarian Cancer

Ovarian cancer is one of the most serious challenges in modern gynaecological oncology. Due to its non-specific symptoms and the lack of an effective screening procedure to detect the disease at an early stage, ovarian cancer is still marked by a high mortality rate among women. For this reason, a great deal of research is being carried out to find new markers that can be used in the detection of ovarian cancer to improve early diagnosis and survival rates of women with ovarian cancer. Our study focuses on presenting the currently used diagnostic markers and the latest selected immunological and molecular parameters being currently investigated for their potential use in the development of new diagnostic and therapeutic strategies.

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.

Recent Trends in Biosensing and Diagnostic Methods for Novel Cancer Biomarkers

Cancer is one of the major public health issues in the world. It has become the second leading cause of death, with approximately 75% of cancer deaths transpiring in low- or middle-income countries. It causes a heavy global economic cost estimated at more than a trillion dollars per year. The most common cancers are breast, colon, rectum, prostate, and lung cancers. Many of these cancers can be treated effectively and cured if detected at the primary stage. Nowadays, around 50% of cancers are detected at late stages, leading to serious health complications and death. Early diagnosis of cancer diseases substantially increases the efficient treatment and high chances of survival. Biosensors are one of the potential screening methodologies useful in the early screening of cancer biomarkers. This review summarizes the recent findings about novel cancer biomarkers and their advantages over traditional biomarkers, and novel biosensing and diagnostic methods for them; thus, this review may be helpful in the early recognition and monitoring of treatment response of various human cancers.

Sensitive Detection of the Human Epididymis Protein-4 (HE4) Ovarian Cancer Biomarker through a Sandwich-Type Immunoassay Method with Laser-Induced Breakdown Spectroscopy

Detection of cancer before the appearance of any symptoms is crucial for successful treatment. Early detection is, however, very challenging, particularly for the types of cancer with few or no symptoms at early stages, such as epithelial ovarian cancer (EOC). Developing a user-friendly method that can detect biomarkers with sufficient selectivity, sensitivity, and reproducibility is a promising approach for overcoming the challenges of early detection of EOC. In this study, we report a sandwich-type microparticle immunoassay for sensitive detection of the HE4 biomarker with laser-induced breakdown spectroscopy. Here, we cross-linked elemental particles to a specific functional group of the targeted biomolecules based on a covalent and non-covalent linking chemistry to improve the sensitivity and selectivity of biomarker detection, in which Fe₃O₄ and SiO₂ microparticles were used to conjugate and purify the antibody-antigen in complex media. Simultaneous detection of Fe and Si from a magnetically purified assay significantly improves the HE4 biomarker's detectability, in which HE4 was detected with a limit of detection of 0.0022 pM. We also determined the coupling ratio between HE4 and silica particles using a silicon calibration curve.

RNA-Seq Analysis of Clinical Samples from TCGA Reveal Molecular Signatures for Ovarian Cancer

Identifying differentially expressed genes and co-expression modules lead to novel biomarkers. GO, pathway enrichment, network, and tumor stage analysis of 318 ovarian cancer samples from TCGA, categorised into primary and recurrent, pre-menopause and post-menopause, and early and late stage tumors was performed. Upregulated and downregulated genes in primary vs recurrent, early stage vs late-stage and pre-menopause vs post-menopause tumors were 84 and 62, 84 and 35, and 88 and 14, respectively. IRAK2 and CXCL8 had higher expression in recurrent tumors while REG1A had higher expression in post-menopause samples. In late stage tumors constant expression of IRAK2 and REG1A was observed, while that of CXCL8 and EGF decreased. These genes may be potential biomarkers for the diagnosis of the disease.

An Overview of Ovarian Cancer: The Role of Cancer Stem Cells in Chemoresistance and a Precision Medicine Approach Targeting the Wnt Pathway with the Antagonist sFRP4

Ovarian cancer is one of the most prevalent gynecological cancers, having a relatively high fatality rate with a low five-year chance of survival when detected in late stages. The early detection, treatment and prevention of metastasis is pertinent and a pressing research priority as many patients are diagnosed only in stage three of ovarian cancer. Despite surgical interventions, targeted immunotherapy and adjuvant chemotherapy, relapses are significantly higher than other cancers, suggesting the dire need to identify the root cause of metastasis and relapse and present more precise therapeutic options. In this review, we first describe types of ovarian cancers, the existing markers and treatment modalities. As ovarian cancer is driven and sustained by an elusive and highly chemoresistant population of cancer stem cells (CSCs), their role and the associated signature markers are exhaustively discussed. Non-invasive diagnostic markers, which can be identified early in the disease using circulating tumor cells (CTCs), are also described. The mechanism of the self-renewal, chemoresistance and metastasis of ovarian CSCs is regulated by the Wnt signaling pathway. Thus, its role in ovarian cancer in promoting stemness and metastasis is delineated. Based on our findings, we propose a novel strategy of Wnt inhibition using a well-known Wnt antagonist, secreted frizzled related protein 4 (sFRP4), wherein short micropeptides derived from the whole protein can be used as powerful inhibitors. The latest approaches to early diagnosis and novel treatment strategies emphasized in this review will help design precision medicine approaches for an effective capture and destruction of highly aggressive ovarian cancer.

Independent predictive value of blood inflammatory composite markers in ovarian cancer: recent clinical evidence and perspective focusing on NLR and PLR

Ovarian cancer (OC) is one of the deadliest malignant tumors affecting women worldwide. The predictive value of some blood inflammatory composite markers in OC has been extensively reported. They can be used for early detection and differential diagnosis of OC and can be used for predicting survival, treatment response, and recurrence in the affected patients. Here, we reviewed the predictive values of composite inflammatory markers based on complete blood count, namely neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio, and systemic inflammation index and markers based on blood protein, namely C-reactive protein-to-albumin ratio and prognostic nutritional index in OC, with a focus on NLR and PLR. We referred to the clinical studies on these six markers, reviewed the patient population, and summarized the marker cut-off values, significance, and limitations of these studies. All these studies were retrospective and most of them were single-center clinical studies with small sample sizes. We found that the cut-off values of these markers have not been unified, and methods used to determine these values varied among studies. The predictive value of these markers on survival was mainly reflected in the postoperative patients of multiple subtypes of ovarian cancer including epithelial OC, high-grade serous ovarian carcinoma, and ovarian clear cell carcinoma. We focused on NLR and PLR and calculated their pooled hazard ratios. NLR and PLR were reliable in predicting overall and progression-free survivals in patients with OC. Therefore, it is necessary to adjust important confounding factors and conduct a long-term follow-up prospective cohort study to further clarify the cut-off values of NLR and PLR and their clinical applications.

Anti-mesothelin CAR-T immunotherapy in patients with ovarian cancer

Recently, chimeric antigen receptor T cell (CAR-T) therapy has received increasing attention as an adoptive cellular immunotherapy that targets tumors. However, numerous challenges remain for the effective use of CAR-T to treat solid tumors, including ovarian cancer, which is an aggressive and metastatic cancer with a poor therapeutic response. We screened for an effective anti-MSLN single-chain Fv antibody with comparable binding activity and non-off-target properties using human phage display library. A second-generation of anti-MSLN CAR was designed and generated. We demonstrated the efficacy of our anti-MSLN CAR-T cells for ovarian cancer treatment in an in vitro experiment to kill ovarian tumor cell lines. The anti-MSLN CAR-T cells impeded MSLN-positive tumor growth concomitant with a significant increase in cytokine levels compared with the control. Then, we demonstrated the efficacy of anti-MSLN CAR-T cells in an in vivo experiment against ovarian cancer cell-derived xenografts. Furthermore, we herein report three cases with ovarian cancer who were treated with autologous anti-MSLN CAR-T cells and evaluate the safety and effectiveness of adoptive cell therapy. In this investigator-initiated clinical trials, no patients experienced cytokine release syndrome or neurological symptoms over 2 grads. Disease stabilized in two patients, with progression-free survival times of 5.8 and 4.6 months. Transient CAR expression was detected in patient blood after infusion each time. The tumor partially subsided, and the patient's condition was relieved. In conclusion, this work proves the efficacy of the anti-MSLN CAR-T treatment strategy in ovarian cancer and provides preliminary data for the development of further clinical trials.

Predicting Prognosis and Platinum Resistance in Ovarian Cancer: Role of Immunohistochemistry Biomarkers

Ovarian cancer is a lethal reproductive tumour affecting women worldwide. The advancement in presentation and occurrence of chemoresistance are the key factors for poor survival among ovarian cancer women. Surgical debulking was the mainstay of systemic treatment for ovarian cancer, which was followed by a successful start to platinum-based chemotherapy. However, most women develop platinum resistance and relapse within six months of receiving first-line treatment. Thus, there is a great need to identify biomarkers to predict platinum resistance before enrolment into chemotherapy, which would facilitate individualized targeted therapy for these subgroups of patients to ensure better survival and an improved quality of life and overall outcome. Harnessing the immune response through immunotherapy approaches has changed the treatment way for patients with cancer. The immune outline has emerged as a beneficial tool for recognizing predictive and prognostic biomarkers clinically. Studying the tumour microenvironment (TME) of ovarian cancer tissue may provide awareness of actionable targets for enhancing chemotherapy outcomes and quality of life. This review analyses the relevance of immunohistochemistry biomarkers as prognostic biomarkers in predicting chemotherapy resistance and improving the quality of life in ovarian cancer.

GD2 and GD3 gangliosides as diagnostic biomarkers for all stages and subtypes of epithelial ovarian cancer

Background

Ovarian cancer (OC) is the deadliest gynecological cancer, often diagnosed at advanced stages. A fast and accurate diagnostic method for early-stage OC is needed. The tumor marker gangliosides, GD2 and GD3, exhibit properties that make them ideal potential diagnostic biomarkers, but they have never before been quantified in OC. We investigated the diagnostic utility of GD2 and GD3 for diagnosis of all subtypes and stages of OC.

Methods

This retrospective study evaluated GD2 and GD3 expression in biobanked tissue and serum samples from patients with invasive epithelial OC, healthy donors, non-malignant gynecological conditions, and other cancers. GD2 and GD3 levels were evaluated in tissue samples by immunohistochemistry (n=299) and in two cohorts of serum samples by quantitative ELISA. A discovery cohort (n=379) showed feasibility of GD2 and GD3 quantitative ELISA for diagnosing OC, and a subsequent model cohort (n=200) was used to train and cross-validate a diagnostic model.

Results

GD2 and GD3 were expressed in tissues of all OC subtypes and FIGO stages but not in surrounding healthy tissue or other controls. In serum, GD2 and GD3 were elevated in patients with OC. A diagnostic model that included serum levels of GD2+GD3+age was superior to the standard of care (CA125, p<0.001) in diagnosing OC and early-stage (I/II) OC.

Conclusion

GD2 and GD3 expression was associated with high rates of selectivity and specificity for OC. A diagnostic model combining GD2 and GD3 quantification in serum had diagnostic power for all subtypes and all stages of OC, including early stage. Further research exploring the utility of GD2 and GD3 for diagnosis of OC is warranted.

The Potential of MicroRNAs as Clinical Biomarkers to Aid Ovarian Cancer Diagnosis and Treatment

Ovarian cancer is a commonly diagnosed malignancy in women. When diagnosed at an early stage, survival outcomes are favourable for the vast majority, with up to 90% of ovarian cancer patients being free of disease at 5 years follow-up. Unfortunately, ovarian cancer is typically diagnosed at an advanced stage due to the majority of patients remaining asymptomatic until the cancer has metastasised, resulting in poor outcomes for the majority. While the molecular era has facilitated the subclassification of the disease into distinct clinical subtypes, ovarian cancer remains managed and treated as a single disease entity. MicroRNAs (miRNAs) are small (19-25 nucleotides), endogenous molecules which are integral to regulating gene expression. Aberrant miRNA expression profiles have been described in several cancers, and have been implicated to be useful biomarkers which may aid cancer diagnostics and treatment. Several preliminary studies have identified candidate tumour suppressor and oncogenic miRNAs which may be involved in the development and progression of ovarian cancer, highlighting their candidacy as oncological biomarkers; understanding the mechanisms by which these miRNAs regulate the key processes involved in oncogenesis can improve our overall understanding of cancer development and identify novel biomarkers and therapeutic targets. This review highlights the potential role of miRNAs which may be utilised to aid diagnosis, estimate prognosis and enhance therapeutic strategies in the management of primary ovarian cancer.

Aberrant MAPK Signaling Offers Therapeutic Potential for Treatment of Ovarian Carcinoma

Ovarian cancer remains the most lethal gynecological malignancy worldwide due to lack of effective screening, vague early symptoms, poor description of biomarkers, and absence of effective treatment regimes. Epithelial ovarian carcinoma (EOC) is categorized into five distinct disease subtypes which collectively account for ~90% of ovarian carcinomas. Most women present at advanced stages contributing to a poor overall 5-year survival rate. Standard treatment for EOC is cytoreductive surgery and platinum-based chemotherapy; however, most patients suffer from recurrence and platinum-resistant disease, which highlights an urgent need for targeted therapy. The high frequency of molecular alterations affecting gain-of-function signaling through the RAS mitogen-activated protein kinase (MAPK) pathway in EOC has prompted pre-clinical and clinical efforts toward research into the effectiveness of MAPK pathway inhibition as a second-line treatment. The RAS/MAPK pathway is a highly conserved signal transduction cascade, often disrupted in cancer, that regulates tumorigenic phenotypes including cellular proliferation, survival, migration, apoptosis, and differentiation. Herein, the role of the MAPK pathway in EOC with emphasis on targetability of the pathway is described. Pre-clinical and clinical efforts to target MAPK signaling in EOC have identified several MAPK pathway inhibitors that offer efficacious potential for monotherapy and in combination with other compounds. Thus, inhibition of the RAS/MAPK pathway is emerging as a tractable strategy for treatment of ovarian cancer that may permit development of personalized therapy and improved prognosis for women challenged by this disease.

Analysis of CXCL8 and its receptors CXCR1/CXCR2 at the mRNA level in neoplastic tissue, as well as in serum and peritoneal fluid in patients with ovarian cance

Understanding the relationship between the coexistence of inflammatory and neoplastic processes in ovarian cancer, particularly those involving chemokines and their receptors, may help to elucidate the involvement of the studied parameters in tumor pathogenesis and could lead to improved clinical applications. Therefore, the present study aimed to analyze the levels of C-X-C motif chemokine ligand 8 (CXCL8), and its receptors C-X-C chemokine receptor (CXCR)1 and CXCR2, in the serum and peritoneal fluid of women with ovarian cancer, and to evaluate the association between the expression of these parameters in tumor tissue and patient characteristics, particularly the degree of histological differentiation. The study group included women with ovarian cancer diagnosed with serous cystadenocarcinoma International Federation of Gynecology and Obstetrics stage IIIc and a control group, which consisted of women who were diagnosed with a benign lesion (serous cystadenoma). The transcript levels of CXCL8, CXCR1 and CXCR2 were evaluated using reverse transcription-quantitative PCR (RT-qPCR). The quantitative analysis was carried out using the LightCycler^® 480 System and GoTaq^® 1-Step RT-qPCR System, according to the manufacturers' instructions. The concentration of CXCL8 in serum and peritoneal fluid was determined using a Human Interleukin-8 ELISA kit, and the concentrations of CXCR1 and CXCR2 were determined using the CLOUD-CLONE ELISA kit. Local and systemic disturbances in immune and inflammatory responses involving the CXCL8 chemokine and its receptors indicated the involvement of these studied parameters in the pathogenesis of ovarian cancer. Immunoregulation of the CXCL8-CXCR1 system may influence the course of the inflammatory process accompanying ovarian cancer development, which may result in the identification of novel clinical applications; however, further studies are required.

Investigation of Transcriptome Patterns in Endometrial Cancers from Obese and Lean Women

Endometrial cancer is the most common gynaecological malignancy in developed countries. One of the largest risk factors for endometrial cancer is obesity. The aim of this study was to determine whether there are differences in the transcriptome of endometrial cancers from obese vs. lean women. Here we investigate the transcriptome of endometrial cancer between obese and lean postmenopausal women using rRNA-depleted RNA-Seq data from endometrial cancer tissues and matched adjacent non-cancerous endometrial tissues. Differential expression analysis identified 12,484 genes (6370 up-regulated and 6114 down-regulated) in endometrial cancer tissues from obese women, and 6219 genes (3196 up-regulated and 3023 down-regulated) in endometrial cancer tissues from lean women (adjusted p-value < 0.1). A gene ontology enrichment analysis revealed that the top 1000 up-regulated genes (by adjusted p-value) were enriched for growth and proliferation pathways while the top 1000 down-regulated genes were enriched for cytoskeleton restructure networks in both obese and lean endometrial cancer tissues. In this study, we also show perturbations in the expression of protein coding genes (HIST1H2BL, HIST1H3F, HIST1H2BH, HIST1H1B, TTK, PTCHD1, ASPN, PRELP, and CDH13) and the lncRNA MBNL1-AS1 in endometrial cancer tissues. Overall, this study has identified gene expression changes that are similar and also unique to endometrial cancers from obese vs. lean women. Furthermore, some of these genes may serve as prognostic biomarkers or, possibly, therapeutic targets for endometrial cancer.

The Proteolytic Landscape of Ovarian Cancer: Applications in Nanomedicine

Ovarian cancer (OvCa) is one of the leading causes of mortality globally with an overall 5-year survival of 47%. The predominant subtype of OvCa is epithelial carcinoma, which can be highly aggressive. This review launches with a summary of the clinical features of OvCa, including staging and current techniques for diagnosis and therapy. Further, the important role of proteases in OvCa progression and dissemination is described. Proteases contribute to tumor angiogenesis, remodeling of extracellular matrix, migration and invasion, major processes in OvCa pathology. Multiple proteases, such as metalloproteinases, trypsin, cathepsin and others, are overexpressed in the tumor tissue. Presence of these catabolic enzymes in OvCa tissue can be exploited for improving early diagnosis and therapeutic options in advanced cases. Nanomedicine, being on the interface of molecular and cellular scales, can be designed to be activated by proteases in the OvCa microenvironment. Various types of protease-enabled nanomedicines are described and the studies that focus on their diagnostic, therapeutic and theranostic potential are reviewed.

CDC20 is a novel biomarker for improved clinical predictions in epithelial ovarian cancer

Epithelial ovarian cancer (EOC), a common tumor of the female reproductive system, ranks first in fatalities among gynecological malignancies. Most patients find tumors at late stage and have extremely poor prognoses, which necessitates improvements in early detection. This study applied bioinformatic methods to identify potential biomarkers of EOC. First, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed on differentially expressed genes (DEGs) and hub genes, and a protein-protein interaction (PPI) network was constructed. The network of hub genes was analyzed using GeneMANIA, and an analysis of biological processes was constructed with BINGO. Lastly, hub genes were analyzed for EOC-related oncology using the Oncomine and TCGA databases, and the cBioPortal online platform. Overall, cell division cycle 20 (CDC20) was identified as a key gene in EOC. Short hairpin RNA (shRNA) was used to silence CDC20 to explore its effects on EOC cell proliferation, apoptosis and SRY-related HMG-box 2 (SOX2) expression. DEGs were enriched in pathways related to cell cycle signaling, cancer, progesterone-mediated oocyte maturation, Wnt signaling and P53 signaling. Analysis revealed high expression of CDC20 in EOC tissues and a correlation with histology and tumor grade. CDC20 levels are highest in serous adenocarcinoma, when compared to ovarian clear cell carcinoma, ovarian endometrioid carcinoma and mucinous adenocarcinoma. High CDC20 expression within the tumor is associated with poor EOC prognosis. After silencing CDC20, EOC cell proliferation and migration decreased, apoptosis increased, and SOX2 expression decreased. In conclusion, CDC20 is likely a key biomarker of EOC and may act as an upstream regulator of SOX2 to mediate the SOX2 signaling in the progression of EOC. Future application of CDC20 analysis to early detection may improve prognosis, and it has the potential to be a therapeutic target.

Novel Ex Vivo Models of Epithelial Ovarian Cancer: The Future of Biomarker and Therapeutic Research

Epithelial ovarian cancer (EOC) is a heterogenous disease associated with variations in presentation, pathology and prognosis. Advanced EOC is typified by frequent relapse and a historical 5-year survival of less than 30% despite improvements in surgical and systemic treatment. The advent of next generation sequencing has led to notable advances in the field of personalised medicine for many cancer types. Success in achieving cure in advanced EOC has however been limited, although significant prolongation of survival has been demonstrated. Development of novel research platforms is therefore necessary to address the rapidly advancing field of early diagnostics and therapeutics, whilst also acknowledging the significant tumour heterogeneity associated with EOC. Within available tumour models, patient-derived organoids (PDO) and explant tumour slices have demonstrated particular promise as novel ex vivo systems to model different cancer types including ovarian cancer. PDOs are organ specific 3D tumour cultures that can accurately represent the histology and genomics of their native tumour, as well as offer the possibility as models for pharmaceutical drug testing platforms, offering timing advantages and potential use as prospective personalised models to guide clinical decision-making. Such applications could maximise the benefit of drug treatments to patients on an individual level whilst minimising use of less effective, yet toxic, therapies. PDOs are likely to play a greater role in both academic research and drug development in the future and have the potential to revolutionise future patient treatment and clinical trial pathways. Similarly, ex vivo tumour slices or explants have also shown recent renewed promise in their ability to provide a fast, specific, platform for drug testing that accurately represents in vivo tumour response. Tumour explants retain tissue architecture, and thus incorporate the majority of tumour microenvironment making them an attractive method to re-capitulate in vivo conditions, again with significant timing and personalisation of treatment advantages for patients. This review will discuss the current treatment landscape and research models for EOC, their development and new advances towards the discovery of novel biomarkers or combinational therapeutic strategies to increase treatment options for women with ovarian cancer.

Toward More Comprehensive Homologous Recombination Deficiency Assays in Ovarian Cancer, Part 1: Technical Considerations

Simple Summary

High-grade serous ovarian cancer (HGSOC) is the most frequent and lethal form of ovarian cancer and is associated with homologous recombination deficiency (HRD) in 50% of cases. This specific alteration is associated with sensitivity to PARP inhibitors (PARPis). Despite vast prognostic improvements due to PARPis, current molecular assays assessing HRD status suffer from several limitations, and there is an urgent need for a more accurate evaluation. In these companion reviews (Part 1: Technical considerations; Part 2: Medical perspectives), we develop an integrative review to provide physicians and researchers involved in HGSOC management with a holistic perspective, from translational research to clinical applications.

Abstract

High-grade serous ovarian cancer (HGSOC), the most frequent and lethal form of ovarian cancer, exhibits homologous recombination deficiency (HRD) in 50% of cases. In addition to mutations in BRCA1 and BRCA2, which are the best known thus far, defects can also be caused by diverse alterations to homologous recombination-related genes or epigenetic patterns. HRD leads to genomic instability (genomic scars) and is associated with PARP inhibitor (PARPi) sensitivity. HRD is currently assessed through BRCA1/2 analysis, which produces a genomic instability score (GIS). However, despite substantial clinical achievements, FDA-approved companion diagnostics (CDx) based on GISs have important limitations. Indeed, despite the use of GIS in clinical practice, the relevance of such assays remains controversial. Although international guidelines include companion diagnostics as part of HGSOC frontline management, they also underscore the need for more powerful and alternative approaches for assessing patient eligibility to PARP inhibitors. In these companion reviews, we review and present evidence to date regarding HRD definitions, achievements and limitations in HGSOC. Part 1 is dedicated to technical considerations and proposed perspectives that could lead to a more comprehensive and dynamic assessment of HR, while Part 2 provides a more integrated approach for clinicians.

Aqueous Biphasic Systems Comprising Natural Organic Acid-Derived Ionic Liquids

Despite the progress achieved by aqueous biphasic systems (ABSs) comprising ionic liquids (ILs) in extracting valuable proteins, the quest for bio-based and protein-friendly ILs continues. To address this need, this work uses natural organic acids as precursors in the synthesis of four ILs, namely tetrabutylammonium formate ([N4444][HCOO]), tetrabutylammonium acetate ([N4444][CH3COO]), tetrabutylphosphonium formate ([P4444][HCOO]), and tetrabutylphosphonium acetate ([P4444][CH3COO]). It is shown that ABSs can be prepared using all four organic acid-derived ILs paired with the salts potassium phosphate dibasic (K2HPO4) and tripotassium citrate (C6H5K3O7). According to the ABSs phase diagrams, [P4444]-based ILs outperform their ammonium congeners in their ability to undergo liquid–liquid demixing in the presence of salts due to their lower hydrogen-bond acidity. However, deviations to the Hofmeister series were detected in the salts’ effect, which may be related to the high charge density of the studied IL anions. As a proof of concept for their extraction potential, these ABSs were evaluated in extracting human transferrin, allowing extraction efficiencies of 100% and recovery yields ranging between 86 and 100%. To further disclose the molecular-level mechanisms behind the extraction of human transferrin, molecular docking studies were performed. Overall, the salting-out exerted by the salt is the main mechanism responsible for the complete extraction of human transferrin toward the IL-rich phase, whereas the recovery yield and protein-friendly nature of these systems depend on specific “IL-transferrin” interactions.

A nomogram model based on clinical markers for predicting malignancy of ovarian tumors

OBJECTIVE

The aim of this study was to build a nomogram based on clinical markers for predicting the malignancy of ovarian tumors (OTs).

METHOD

A total of 1,268 patients diagnosed with OTs that were surgically removed between October 2017 and May 2019 were enrolled. Clinical markers such as post-menopausal status, body mass index (BMI), serum human epididymis protein 4 (HE4) value, cancer antigen 125 (CA125) value, Risk of Ovarian Malignancy Algorithm (ROMA) index, course of disease, patient-generated subjective global assessment (PG-SGA) score, ascites, and locations and features of masses were recorded and analyzed (p 0.05). Significant variables were further selected using multivariate logistic regression analysis and were included in the decision curve analysis (DCA) used to assess the value of the nomogram model for predicting OT malignancy.

RESULT

The significant variables included post-menopausal status, BMI, HE4 value, CA125 value, ROMA index, course of disease, PG-SGA score, ascites, and features and locations of masses (p 0.05). The ROMA index, BMI (≥ 26), unclear/blurred mass boundary (on magnetic resonance imaging [MRI]/computed tomography [CT]), mass detection (on MRI/CT), and mass size and features (on type B ultrasound [BUS]) were screened out for multivariate logistic regression analysis to assess the value of the nomogram model for predicting OT malignant risk (p 0.05). The DCA revealed that the net benefit of the nomogram's calculation model was superior to that of the CA125 value, HE4 value, and ROMA index for predicting OT malignancy.

CONCLUSION

We successfully tailored a nomogram model based on selected clinical markers which showed superior prognostic predictive accuracy compared with the use of the CA125, HE4, or ROMA index (that combines both HE and CA125 values) for predicting the malignancy of OT patients.

Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer

Epithelial ovarian cancer (EOC) is a fatal gynecologic cancer, and its poor prognosis is mainly due to delayed diagnosis. Therefore, biomarker identification and prognosis prediction are crucial in EOC. Altered cell metabolism is a characteristic feature of cancers, and metabolomics reflects an individual’s current phenotype. In particular, plasma metabolome analyses can be useful for biomarker identification. In this study, we analyzed 624 metabolites, including uremic toxins (UTx) in plasma derived from 80 patients with EOC using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). Compared with the healthy control, we detected 77 significantly increased metabolites and 114 significantly decreased metabolites in EOC patients. Especially, decreased concentrations of lysophosphatidylcholines and phosphatidylcholines and increased concentrations of triglycerides were observed, indicating a metabolic profile characteristic of EOC patients. After calculating the parameters of each metabolic index, we found that higher ratios of kynurenine to tryptophan correlates with worse prognosis in EOC patients. Kynurenine, one of the UTx, can affect the prognosis of EOC. Our results demonstrated that plasma metabolome analysis is useful not only for the diagnosis of EOC, but also for predicting prognosis with the variation of UTx and evaluating response to chemotherapy.