Potential clinical utility of liquid biopsies in ovarian cancer

An electrochemical biosensor designed with entropy-driven autocatalytic DNA circuits for sensitive detection of ovarian cancer-derived exosomes

Intelligent artificial DNA circuits have emerged as a promising approach for modulating signaling pathways and signal transduction through rational design, which may contribute to comprehensively realizing biomolecular sensing of organisms. In this work, we have fabricated an electrochemical biosensor for the sensitive and accurate detection of ovarian cancer-derived exosomes by constructing an entropy-driven autocatalytic DNA circuit (EADC). Specifically, the robust EADC is prepared by the self-assembly of well-designed DNA probes, and upon stimulation of the presence of ovarian cancer cells-derived exosomes, numerous inputs can be produced to feedback and accelerate the reaction. The catalytic abilities of the generated input sequences play a pivotal role in EADC and dramatically enhance the signal amplification capability. Through the combination of the autocatalytic circuit and circular cleavage reactions, significantly changed electrochemical signals can be recorded for sensitive analysis of the exosomes with a remarkably low detection limit of 30 particles/μL. Moreover, the proposed enzyme-free biosensor shows exceptional performance in distinguishing patient samples from healthy samples, which exhibits promising prospects for the clinical diagnosis of ovarian cancer.

A miRNA-7704/IL2RB/AKT feedback loop regulates tumorigenesis and chemoresistance in ovarian cancer

Ovarian cancer is one of the most common gynecological tumors worldwide. Despite the availability of multiple treatments for ovarian cancer, its resistance to chemotherapy remains a significant challenge. miRNAs play crucial roles in the initiation and progression of cancer by affecting processes such as differentiation, proliferation, and chemoresistance. According to microarray and qPCR analyses, miR-7704 is significantly downregulated in cisplatin-resistant cells compared to parental cells. In this study, we found that miR-7704 inhibited the proliferation and promoted cisplatin sensitivity of ovarian cancer cells in vitro and in vivo. Moreover, ectopic expression of miR-7704 had the same effect as IL2RB knockdown. Further mechanistic studies revealed that miR-7704 played an inhibitory role by regulating IL2RB expression to inactivate the AKT signaling pathway. Furthermore, IL2RB reversed the miR-7704 mediated resistance to cisplatin in ovarian cancer. Based on these findings, miR-7704 and IL2RB show the potential as novel therapeutic targets for ovarian cancer.

Cancer-derived exosomal lncRNA SNHG3 promotes the metastasis of colorectal cancer through hnRNPC-mediating RNA stability of β-catenin

Metastasis is the leading cause of death in colorectal cancer (CRC) patients. By mediating intercellular communication, exosomes exhibit considerable value in regulating tumor metastasis. Long non-coding RNAs (lncRNAs) are abundant in exosomes and participate in regulating tumor progression. However, it is poorly understood how the cancer-secreted exosomal lncRNAs affect CRC proliferation and metastasis. Here, by analyzing the public databases we identified a lncRNA SNHG3 and demonstrated that SNHG3 was delivered through CRC cells-derived exosomes to promote metastasis in CRC. Mechanistically, exosomal SNHG3 was internalized by CRC cells and afterward upregulated the expression of β-catenin by facilitating the intranuclear transport of hnRNPC. Consequently, the RNA stability of β-catenin was enhanced which led to the activation of EMT and metastasis of CRC cells. Our findings expand the oncogenic mechanisms of exosomal SNHG3 and identify it as a diagnostic marker for CRC.

FoxO1 promotes ovarian cancer by increasing transcription and METTL14-mediated m6A modification of SMC4

The transcription factor forkhead box protein O1 (FoxO1) is closely related to the occurrence and development of ovarian cancer (OC), however its role and molecular mechanisms remain unclear. Herein, we found that FoxO1 was highly expressed in clinical samples of OC patients and was significantly correlated with poor prognosis. FoxO1 knockdown inhibited the proliferation of OC cells in vitro and in vivo. ChIP-seq combined with GEPIA2 and Kaplan-Meier database analysis showed that structural maintenance of chromosome 4 (SMC4) is a downstream target of FoxO1, and FoxO1 promotes SMC4 transcription by binding to its -1400/-1390 bp promoter. The high expression of SMC4 significantly blocked the tumor inhibition effect of FoxO1 knockdown. Furtherly, FoxO1 increased SMC4 mRNA abundance by transcriptionally activating methyltransferase-like 14 (METTL14) and increasing SMC4 m6A methylation on its coding sequence region. The Cancer Genome Atlas dataset analysis confirmed a significant positive correlation between FoxO1, SMC4, and METTL14 expression in OC. In summary, this study revealed the molecular mechanisms of FoxO1 regulating SMC4 and established a clinical link between the expression of FoxO1/METTL14/SMC4 in the occurrence of OC, thus providing a potential diagnostic target and therapeutic strategy.

Proteomic insight towards key modulating proteins regulated by the aryl hydrocarbon receptor involved in ovarian carcinogenesis and chemoresistance

Gynecological malignancies pose a severe threat to female lives. Ovarian cancer (OC), the most lethal gynecological malignancy, is clinically presented with chemoresistance and a higher relapse rate. Several studies have highly correlated the incidence of OC to exposure to environmental pollutants, such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), a process mainly mediated through activating the aryl hydrocarbon receptor (AhR). We have previously reported that exposure of OC cells to TCDD, an AhR activator, significantly modulated the expression of several genes that play roles in stemness and chemoresistance. However, the effect of AhR activation on the whole OC cell proteome aiming at identifying novel druggable targets for both prevention and treatment intervention purposes remains unrevealed. For this purpose, we conducted a comparative proteomic analysis of OC cells A2780 untreated/treated with TCDD for 24 h using a mass spectrometry-based label-free shotgun proteomics approach. The most significantly dysregulated proteins were validated by Western blot analysis. Our results showed that upon AhR activation by TCDD, out of 2598 proteins identified, 795 proteins were upregulated, and 611 were downregulated. STRING interaction analysis and KEGG-Reactome pathway analysis approaches identified several significantly dysregulated proteins that were categorized to be involved in chemoresistance, cancer progression, invasion and metastasis, apoptosis, survival, and prognosis in OC. Importantly, selected dysregulated genes identified by the proteomic study were validated at the protein expression levels by Western blot analysis. In conclusion, this study provides a better understanding of the the cross-talk between AhR and several other molecular signaling pathways and the role and involvement of AhR in ovarian carcinogenesis and chemoresistance. Moreover, the study suggests that AhR is a potential therapeutic target for OC prevention and maintenance. SIGNIFICANCE: To our knowledge, this is the first study that investigates the role and involvement of AhR and its regulated genes in OC by performing a comparative proteomic analysis to identify the critical proteins with a modulated expression upon AhR activation. We found AhR activation to play a tumor-promoting and chemoresistance-inducing role in the pathogenesis of OC. The results of our study help to devise novel therapeutics for better management and prevention and open the doors to finding novel biomarkers for the early detection and prognosis of OC.

Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study

BACKGROUND

Ovarian cancer is the most lethal gynecological malignancy. Timely diagnosis of ovarian cancer is difficult due to the lack of effective biomarkers. Laboratory tests are widely applied in clinical practice, and some have shown diagnostic and prognostic relevance to ovarian cancer. We aimed to systematically evaluate the value of routine laboratory tests on the prediction of ovarian cancer, and develop a robust and generalisable ensemble artificial intelligence (AI) model to assist in identifying patients with ovarian cancer.

METHODS

In this multicentre, retrospective cohort study, we collected 98 laboratory tests and clinical features of women with or without ovarian cancer admitted to three hospitals in China during Jan 1, 2012 and April 4, 2021. A multi-criteria decision making-based classification fusion (MCF) risk prediction framework was used to make a model that combined estimations from 20 AI classification models to reach an integrated prediction tool developed for ovarian cancer diagnosis. It was evaluated on an internal validation set (3007 individuals) and two external validation sets (5641 and 2344 individuals). The primary outcome was the prediction accuracy of the model in identifying ovarian cancer.

FINDINGS

Based on 52 features (51 laboratory tests and age), the MCF achieved an area under the receiver-operating characteristic curve (AUC) of 0·949 (95% CI 0·948-0·950) in the internal validation set, and AUCs of 0·882 (0·880-0·885) and 0·884 (0·882-0·887) in the two external validation sets. The model showed higher AUC and sensitivity compared with CA125 and HE4 in identifying ovarian cancer, especially in patients with early-stage ovarian cancer. The MCF also yielded acceptable prediction accuracy with the exclusion of highly ranked laboratory tests that indicate ovarian cancer, such as CA125 and other tumour markers, and outperformed state-of-the-art models in ovarian cancer prediction. The MCF was wrapped as an ovarian cancer prediction tool, and made publicly available to provide estimated probability of ovarian cancer with input laboratory test values.

INTERPRETATION

The MCF model consistently achieved satisfactory performance in ovarian cancer prediction when using laboratory tests from the three validation sets. This model offers a low-cost, easily accessible, and accurate diagnostic tool for ovarian cancer. The included laboratory tests, not only CA125 which was the highest ranked laboratory test in importance of diagnostic assistance, contributed to the characterisation of patients with ovarian cancer.

FUNDING

Ministry of Science and Technology of China; National Natural Science Foundation of China; Natural Science Foundation of Guangdong Province, China; and Science and Technology Project of Guangzhou, China.

TRANSLATION

For the Chinese translation of the abstract see Supplementary Materials section.

Peroxisome proliferator-activated receptor gamma coactivator-1 (PGC-1) family in physiological and pathophysiological process and diseases

Peroxisome proliferator-activated receptor gamma coactivator-1 (PGC-1) family (PGC-1s), consisting of three members encompassing PGC-1α, PGC-1β, and PGC-1-related coactivator (PRC), was discovered more than a quarter-century ago. PGC-1s are essential coordinators of many vital cellular events, including mitochondrial functions, oxidative stress, endoplasmic reticulum homeostasis, and inflammation. Accumulating evidence has shown that PGC-1s are implicated in many diseases, such as cancers, cardiac diseases and cardiovascular diseases, neurological disorders, kidney diseases, motor system diseases, and metabolic disorders. Examining the upstream modulators and co-activated partners of PGC-1s and identifying critical biological events modulated by downstream effectors of PGC-1s contribute to the presentation of the elaborate network of PGC-1s. Furthermore, discussing the correlation between PGC-1s and diseases as well as summarizing the therapy targeting PGC-1s helps make individualized and precise intervention methods. In this review, we summarize basic knowledge regarding the PGC-1s family as well as the molecular regulatory network, discuss the physio-pathological roles of PGC-1s in human diseases, review the application of PGC-1s, including the diagnostic and prognostic value of PGC-1s and several therapies in pre-clinical studies, and suggest several directions for future investigations. This review presents the immense potential of targeting PGC-1s in the treatment of diseases and hopefully facilitates the promotion of PGC-1s as new therapeutic targets.

Synergistic suppression of ovarian cancer by combining NRF2 and GPX4 inhibitors: in vitro and in vivo evidence

Ovarian cancer is a significant challenge in women's health due to the lack of effective screening and diagnostic methods, often leading to late detection and the highest mortality rate among all gynecologic tumors worldwide. Recent research has shown that ovarian cancer has an "iron addiction" phenotype which makes it vulnerable to ferroptosis inducers. We tested the combination of NRF2-targeted inhibitors with GPX4-targeted inhibitors in ovarian cancer through in vitro and in vivo experiment. The data showed that combination treatment effectively suppressed adherent cell growth, inhibited suspended cell spheroid formation, and restrained the ability of spheroid formation in 3D-culture. Mechanistically, the combination induced accumulation of ROS, 4-HNE, as well as activation of caspase-3 which indicates that this combination simultaneously increases cell ferroptosis and apoptosis. Notably, inhibition of GPX4 or NRF2 can suppress ovarian cancer spreading and growth in the peritoneal cavity of mice, while the combination of NRF2 inhibitor ML385 with GPX4 inhibitors showed a significant synergistic effect compared to individual drug treatment in a syngeneic mouse ovarian cancer model. Overall, these findings suggest that combining NRF2 inhibitors with GPX4 inhibitors results in a synergy suppression of ovarian cancer in vitro and in vivo, and maybe a promising therapeutic strategy for the treatment of ovarian cancer.

An exosome-derived lncRNA signature identified by machine learning associated with prognosis and biomarkers for immunotherapy in ovarian cancer

Background

Ovarian cancer (OC) has the highest mortality rate among gynecological malignancies. Current treatment options are limited and ineffective, prompting the discovery of reliable biomarkers. Exosome lncRNAs, carrying genetic information, are promising new markers. Previous studies only focused on exosome-related genes and employed the Lasso algorithm to construct prediction models, which are not robust.

Methods

420 OC patients from the TCGA datasets were divided into training and validation datasets. The GSE102037 dataset was used for external validation. LncRNAs associated with exosome-related genes were selected using Pearson analysis. Univariate COX regression analysis was used to filter prognosis-related lncRNAs. The overlapping lncRNAs were identified as candidate lncRNAs for machine learning. Based on 10 machine learning algorithms and 117 algorithm combinations, the optimal predictor combinations were selected according to the C index. The exosome-related LncRNA Signature (ERLS) model was constructed using multivariate COX regression. Based on the median risk score of the training datasets, the patients were divided into high- and low-risk groups. Kaplan-Meier survival analysis, the time-dependent ROC, immune cell infiltration, immunotherapy response, and immune checkpoints were analyzed.

Results

64 lncRNAs were subjected to a machine-learning process. Based on the stepCox (forward) combined Ridge algorithm, 20 lncRNA were selected to construct the ERLS model. Kaplan-Meier survival analysis showed that the high-risk group had a lower survival rate. The area under the curve (AUC) in predicting OS at 1, 3, and 5 years were 0.758, 0.816, and 0.827 in the entire TCGA cohort. xCell and ssGSEA analysis showed that the low-risk group had higher immune cell infiltration, which may contribute to the activation of cytolytic activity, inflammation promotion, and T-cell co-stimulation pathways. The low-risk group had higher expression levels of PDL1, CTLA4, and higher TMB. The ERLS model can predict response to anti-PD1 and anti-CTLA4 therapy. Patients with low expression of PDL1 or high expression of CTLA4 and low ERLS exhibited significantly better survival prospects, whereas patients with high ERLS and low levels of PDL1 or CTLA4 exhibited the poorest outcomes.

Conclusion

Our study constructed an ERLS model that can predict prognostic risk and immunotherapy response, optimizing clinical management for OC patients.

Current Applications and Challenges of Next-Generation Sequencing in Plasma Circulating Tumour DNA of Ovarian Cancer

Circulating tumour DNA (ctDNA) facilitates longitudinal study of the tumour genome, which, unlike tumour tissue biopsies, globally reflects intratumor and intermetastatis heterogeneity. Despite its costs, next-generation sequencing (NGS) has revolutionised the study of ctDNA, ensuring a more comprehensive and multimodal approach, increasing data collection, and introducing new variables that can be correlated with clinical outcomes. Current NGS strategies can comprise a tumour-informed set of genes or the entire genome and detect a tumour fraction as low as 10-5. Despite some conflicting studies, there is evidence that ctDNA levels can predict the worse outcomes of ovarian cancer (OC) in both early and advanced disease. Changes in those levels can also be informative regarding treatment efficacy and tumour recurrence, capable of outperforming CA-125, currently the only universally utilised plasma biomarker in high-grade serous OC (HGSOC). Qualitative evaluation of sequencing shows that increasing copy number alterations and gene variants during treatment may correlate with a worse prognosis in HGSOC. However, following tumour clonality and emerging variants during treatment poses a more unique opportunity to define treatment response, select patients based on their emerging resistance mechanisms, like BRCA secondary mutations, and discover potential targetable variants. Sequencing of tumour biopsies and ctDNA is not always concordant, likely as a result of clonal heterogeneity, which is better captured in the plasma samples than it is in a large number of biopsies. These incoherences may reflect tumour clonality and reveal the acquired alterations that cause treatment resistance. Cell-free DNA methylation profiles can be used to distinguish OC from healthy individuals, and NGS methylation panels have been shown to have excellent diagnostic capabilities. Also, methylation signatures showed promise in explaining treatment responses, including BRCA dysfunction. ctDNA is evolving as a promising new biomarker to track tumour evolution and clonality through the treatment of early and advanced ovarian cancer, with potential applicability in prognostic prediction and treatment selection. While its role in HGSOC paves the way to clinical applicability, its potential interest in other histological subtypes of OC remains unknown.

Regulation of ULK1 by WTAP/IGF2BP3 axis enhances mitophagy and progression in epithelial ovarian cancer

There is a pressing need for innovative therapeutic strategies for patients with epithelial ovarian cancer (EOC). Previous studies have shown that UNC-51-like kinase 1 (ULK1), a serine/threonine kinase, is crucial in regulating cellular autophagy and mitophagy across various tumor types. However, the clinical implications, biological functions, and potential mechanisms of ULK1 in EOC remain poorly understood. This study demonstrates that ULK1 expression is upregulated in EOC tissue samples and EOC cell lines, with increased ULK1 expression correlating with poor prognosis. Functionally, overexpressed ULK1 enhances the proliferation and migration abilities of EOC cells both in vitro and in vivo. Mechanistically, ULK1 was identified as an m6A target of WTAP. WTAP-mediated m6A modification of ULK1 enhanced its mRNA stability in an IGF2BP3-dependent manner, leading to elevated ULK1 expression and enhanced mitophagy in EOC. In summary, our research reveals that the WTAP/IGF2BP3-ULK1 axis significantly influences protective mitophagy in EOC, contributing to its progression. Therefore, the regulatory mechanisms and biological function of ULK1 identify it as a potential molecular target for therapeutic intervention in EOC.

Predictive Value of Machine Learning for Platinum Chemotherapy Responses in Ovarian Cancer: Systematic Review and Meta-Analysis

BACKGROUND

Machine learning is a potentially effective method for predicting the response to platinum-based treatment for ovarian cancer. However, the predictive performance of various machine learning methods and variables is still a matter of controversy and debate.

OBJECTIVE

This study aims to systematically review relevant literature on the predictive value of machine learning for platinum-based chemotherapy responses in patients with ovarian cancer.

METHODS

Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we systematically searched the PubMed, Embase, Web of Science, and Cochrane databases for relevant studies on predictive models for platinum-based therapies for the treatment of ovarian cancer published before April 26, 2023. The Prediction Model Risk of Bias Assessment tool was used to evaluate the risk of bias in the included articles. Concordance index (C-index), sensitivity, and specificity were used to evaluate the performance of the prediction models to investigate the predictive value of machine learning for platinum chemotherapy responses in patients with ovarian cancer.

RESULTS

A total of 1749 articles were examined, and 19 of them involving 39 models were eligible for this study. The most commonly used modeling methods were logistic regression (16/39, 41%), Extreme Gradient Boosting (4/39, 10%), and support vector machine (4/39, 10%). The training cohort reported C-index in 39 predictive models, with a pooled value of 0.806; the validation cohort reported C-index in 12 predictive models, with a pooled value of 0.831. Support vector machine performed well in both the training and validation cohorts, with a C-index of 0.942 and 0.879, respectively. The pooled sensitivity was 0.890, and the pooled specificity was 0.790 in the training cohort.

CONCLUSIONS

Machine learning can effectively predict how patients with ovarian cancer respond to platinum-based chemotherapy and may provide a reference for the development or updating of subsequent scoring systems.

High-Grade Serous Ovarian Cancer-A Risk Factor Puzzle and Screening Fugitive

High-grade serous ovarian cancer (HGSOC) is the most lethal tumor of the female genital tract. Despite extensive studies and the identification of some precursor lesions like serous tubal intraepithelial cancer (STIC) or the deviated mutational status of the patients (BRCA germinal mutation), the pathophysiology of HGSOC and the existence of particular risk factors is still a puzzle. Moreover, a lack of screening programs results in delayed diagnosis, which is accompanied by a secondary chemo-resistance of the tumor and usually results in a high recurrence rate after the primary therapy. Therefore, there is an urgent need to identify the substantial risk factors for both predisposed and low-risk populations of women, as well as to create an economically and clinically justified screening program. This paper reviews the classic and novel risk factors for HGSOC and methods of diagnosis and prediction, including serum biomarkers, the liquid biopsy of circulating tumor cells or circulating tumor DNA, epigenetic markers, exosomes, and genomic and proteomic biomarkers. The novel future complex approach to ovarian cancer diagnosis should be devised based on these findings, and the general outcome of such an approach is proposed and discussed in the paper.

Identification and validation of anoikis-related lncRNAs for prognostic significance and immune microenvironment characterization in ovarian cancer

Anoikis, a form of apoptotic cell death resulting from inadequate cell-matrix interactions, has been implicated in tumor progression by regulating tumor angiogenesis and metastasis. However, the potential roles of anoikis-related long non-coding RNAs (arlncRNAs) in the tumor microenvironment are not well understood. In this study, five candidate lncRNAs were screened through least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis based on differentially expressed lncRNAs associated with anoikis-related genes (ARGs) from TCGA and GSE40595 datasets. The prognostic accuracy of the risk model was evaluated using Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) analyses revealed significant differences in immune-related hallmarks and signal transduction pathways between the high-risk and low-risk groups. Additionally, immune infiltrate analysis showed significant differences in the distribution of macrophages M2, follicular T helper cells, plasma cells, and neutrophils between the two risk groups. Lastly, silencing the expression of PRR34_AS1 and SPAG5_AS1 significantly increased anoikis-induced cell death in ovarian cancer cells. In conclusion, our study constructed a risk model that can predict clinicopathological features, tumor microenvironment characteristics, and prognosis of ovarian cancer patients. The immune-related pathways identified in this study may offer new treatment strategies for ovarian cancer.

Circulating tumour mutation detection in triple-negative breast cancer as an adjunct to tissue response assessment

Circulating tumour DNA (ctDNA) detection via liquid biopsy is an emerging alternative to tissue biopsy, but its potential in treatment response monitoring and prognosis in triple negative breast cancer (TNBC) is not yet well understood. Here we determined the prevalence of actionable mutations detectable in ctDNA using a clinically validated cancer gene panel assay in patients with TNBC, without recurrence at the time of study entry. Sequencing of plasma DNA and validation of variants from 130 TNBC patients collected within 7 months of primary treatment completion revealed that 7.7% had detectable residual disease with a hotspot panel. Among neoadjuvant treated patients, we observed a trend where patients with incomplete pathologic response and positive ctDNA within 7 months of treatment completion were at much higher risk of reduced progression free survival. We propose that a high risk subset of early TNBC patients treated in neoadjuvant therapy protocols may be identifiable by combining tissue response and sensitive ctDNA detection.

Applications of Exosome Vesicles in Different Cancer Types as Biomarkers

One of the biggest challenges in the fight against cancer is early detection. Early diagnosis is vital, but there are some barriers such as economic, cultural, and personal factors. Considering the disadvantages of radiological imaging techniques or serological analysis methods used in cancer diagnosis, such as being expensive, requiring expertise, and being time-consuming, there is a need to develop faster, more reliable, and cost-effective diagnostic methods for use in cancer diagnosis. Exosomes, which are responsible for intercellular communication with sizes ranging from 30-120 nm, are naturally produced biological nanoparticles. Thanks to the cargo contents they carry, they are a potential biomarker to be used in the diagnosis of cancer. Exosomes, defined as extracellular vesicles of endosomal origin, are effective in cancer growth, progression, metastasis, and drug resistance, and changes in microenvironmental conditions during tumor development change exosome secretion. Due to their high cellular activity, tumor cells produce much higher exosomes than healthy cells. Therefore, it is known that the number of exosomes in body fluids is significantly rich compared to other cells and can act as a stand-alone diagnostic biomarker. Cancer- derived exosomes have received great attention in recent years for the early detection of cancer and the evaluation of therapeutic response. In this article, the content, properties, and differences of exosomes detected in common types of cancer (lung, liver, pancreas, ovaries, breast, colorectal), which are the leading causes of cancer-related deaths, are reviewed. We also discuss the potential utility of exosome contents as a biomarker for early detection, which is known to be important in targeted cancer therapy.

Liquid biopsy in ovarian cancer in China and the world: current status and future perspectives

Ovarian cancer (OC) is the eighth most common cancer in women, but the mild, non-specific clinical presentation in early stages often prevents diagnosis until progression to advanced-stage disease, contributing to the high mortality associated with OC. While serum cancer antigen 125 (CA-125) has been successfully used as a blood-borne marker and is routinely monitored in patients with OC, CA-125 testing has limitations in sensitivity and specificity and does not provide direct information on important molecular characteristics that can guide treatment decisions, such as homologous recombination repair deficiency. We comprehensively review the literature surrounding methods based on liquid biopsies, which may provide improvements in sensitivity, specificity, and provide valuable additional information to enable early diagnosis, monitoring of recurrence/progression/therapeutic response, and accurate prognostication for patients with OC, highlighting applications of this research in China.

Emerging Applications of Liquid Biopsies in Ovarian Cancer

Liquid biopsy is a new diagnostic tool in precision oncology that can be used as a complementary or alternative method to surgical biopsies. It is a cutting-edge sampling technique that examines distinct cancer components, such as exosomes and circulating tumor cells discharged into the peripheral circulation, to identify tumor biomarkers through various methods, including polymerase chain reaction (PCR). Liquid biopsy has several benefits, including its non-invasiveness and practicality, which permit serial sampling and long-term monitoring of dynamic tumor changes. Ovarian cancer (OC), the most lethal gynecologic malignancy in the world, is typically diagnosed at stages II and III, which makes recovery and treatment extremely difficult. Relapsed OC and chemotherapy resistance of ovarian tumor cells are other clinical challenges. Although liquid biopsy is not a routinely used diagnostic test, it should be utilized in the diagnosis and prognosis of OC for early detection and treatment. It is less intrusive than conventional tissue biopsies, allowing for the continuous collection of serial blood samples to track cancer development in real time. Before therapeutic application, more investigation is required to pinpoint the particular release processes, the source tissue, and the biological significance of the bulk of liquid biopsy contents.

Microfluidic platforms in diagnostic of ovarian cancer

The most important reason for death from ovarian cancer is the late diagnosis of this disease. The standard treatment of ovarian cancer includes surgery and chemotherapy based on platinum, which is associated with side effects for the body. Due to the nonspecific nature of clinical symptoms, developing a platform for early detection of this disease is needed. In recent decades, the advancements of microfluidic devices and systems have provided several advantages for diagnosing ovarian cancer. Designing and manufacturing new platforms using specialized technologies can be a big step toward improving the prevention, diagnosis, and treatment of this group of diseases. Organ-on-a-chip microfluidic devices are increasingly used as a promising platform in cancer research, with a focus on specific biological aspects of the disease. This review focusing on ovarian cancer and microfluidic application technologies in its diagnosis. Additionally, it discusses microfluidic platforms and their potential future perspectives in advancing ovarian cancer diagnosis.

Screening and Early Diagnosis in Gynecological Cancers

Cervical (CC), endometrial (EC), and ovarian (OC) cancers are the pathologies with the highest incidences among gynecological tumors, with such high morbidity and mortality values that they are considered significant public health problems [...].

Current and new frontiers in hereditary cancer surveillance: Opportunities for liquid biopsy

At least 5% of cancer diagnoses are attributed to a causal pathogenic or likely pathogenic germline genetic variant (hereditary cancer syndrome-HCS). These individuals are burdened with lifelong surveillance monitoring organs for a wide spectrum of cancers. This is associated with substantial uncertainty and anxiety in the time between screening tests and while the individuals are awaiting results. Cell-free DNA (cfDNA) sequencing has recently shown potential as a non-invasive strategy for monitoring cancer. There is an opportunity for high-yield cancer early detection in HCS. To assess clinical validity of cfDNA in individuals with HCS, representatives from eight genetics centers from across Canada founded the CHARM (cfDNA in Hereditary and High-Risk Malignancies) Consortium in 2017. In this perspective, we discuss operationalization of this consortium and early data emerging from the most common and well-characterized HCSs: hereditary breast and ovarian cancer, Lynch syndrome, Li-Fraumeni syndrome, and Neurofibromatosis type 1. We identify opportunities for the incorporation of cfDNA sequencing into surveillance protocols; these opportunities are backed by examples of earlier cancer detection efficacy in HCSs from the CHARM Consortium. We seek to establish a paradigm shift in early cancer surveillance in individuals with HCSs, away from highly centralized, regimented medical screening visits and toward more accessible, frequent, and proactive care for these high-risk individuals.

Extranodal lymphoma: pathogenesis, diagnosis and treatment

Approximately 30% of lymphomas occur outside the lymph nodes, spleen, or bone marrow, and the incidence of extranodal lymphoma has been rising in the past decade. While traditional chemotherapy and radiation therapy can improve survival outcomes for certain patients, the prognosis for extranodal lymphoma patients remains unsatisfactory. Extranodal lymphomas in different anatomical sites often have distinct cellular origins, pathogenic mechanisms, and clinical manifestations, significantly influencing their diagnosis and treatment. Therefore, it is necessary to provide a comprehensive summary of the pathogenesis, diagnosis, and treatment progress of extranodal lymphoma overall and specifically for different anatomical sites. This review summarizes the current progress in the common key signaling pathways in the development of extranodal lymphomas and intervention therapy. Furthermore, it provides insights into the pathogenesis, diagnosis, and treatment strategies of common extranodal lymphomas, including gastric mucosa-associated lymphoid tissue (MALT) lymphoma, mycosis fungoides (MF), natural killer/T-cell lymphoma (nasal type, NKTCL-NT), and primary central nervous system lymphoma (PCNSL). Additionally, as PCNSL is one of the extranodal lymphomas with the worst prognosis, this review specifically summarizes prognostic indicators and discusses the challenges and opportunities related to its clinical applications. The aim of this review is to assist clinical physicians and researchers in understanding the current status of extranodal lymphomas, enabling them to make informed clinical decisions that contribute to improving patient prognosis.

Diagnostics and treatment of ovarian cancer in the era of precision medicine - opportunities and challenges

Due to predictions of increasing incidences and deaths from ovarian cancer, this neoplasm is a challenge for modern health care. The advent of NGS technology has made it possible to understand the molecular characteristics of many cancers, including ovarian cancer. The data obtained in research became the basis for the development of molecularly targeted therapies thus leading to the entry of NGS analysis into the diagnostic process of oncological patients. This review presents targeted therapies currently in preclinical or clinical trials, whose promising results offer hope for their use in clinical practice in the future. As more therapeutic options emerge, it will be necessary to modify molecular diagnostic regimens to select the best treatment for a given patient. New biomarkers are needed to predict the success of planned therapy. An important aspect of public health is molecular testing in women with a familial predisposition to ovarian cancer enabling patients to be included in prevention programs. NGS technology, despite its high throughput, poses many challenges, from the quality of the diagnostic material used for testing to the interpretation of results and classification of sequence variants. The article highlights the role of molecular testing in ongoing research and also its role in the diagnostic and therapeutic process in the era of personalized medicine. The spread of genetic testing in high-risk groups, the introduction of more targeted therapies and also the possibility of agnostic therapies could significantly improve the health situation for many women worldwide.

Identification of RAD51 foci in cancer-associated circulating cells of patients with high-grade serous ovarian cancer: association with treatment outcomes

OBJECTIVE

Fifty percent of patients with high-grade serous ovarian cancer harbor defects in the homologous recombination repair pathway. RAD51 foci form where DNA is damaged, indicating its involvement in repairing double-stranded breaks. High levels of RAD51 in ovarian cancer tissue have been associated with a poorer prognosis.

OBJECTIVE

To demonstrate RAD51 foci in circulating cancer-associated cells of patients with ovarian cancer and their association with clinical outcomes.

METHODS

One hundred and twenty-four patients with high-grade serous ovarian cancer had blood samples taken at strategic points during treatment and follow-up. Cells were stained using WT1 and RAD51 antibodies with immunofluorescence and reviewed under Leica camera microscopy; RAD51 foci were counted. Correlations were made between numbers of RAD51 foci and treatment response, BRCA status, and progression-free survival.

RESULTS

RAD51 foci were identified in all patients (n=42) with wild-type BRCA. BRCA mutant/homologous recombination deficiency-positive patients (n=8) had significantly lower numbers of RAD51 foci (p=0.009). Responders to treatment (n=32) had a reduction in circulating cells (p=0.02) and RAD51 foci (p=0.0007). Numbers of RAD51 foci were significantly higher in the platinum-resistant population throughout treatment: at the start of treatment, in 56 platinum-sensitive patients there was a mean of 3.6 RAD51 foci versus 6.2 in 15 platinum-resistant patients (p=0.02). Patients with a high number of RAD51 foci had worse median progression-free survival: in 39 patients with a mean of <3 RAD51 foci at treatment start, median progression-free survival had not been reached, compared with 32 patients with >3 RAD51 foci whose progression-free survival was 13 months (p=0.04).

CONCLUSIONS

Levels of RAD51 foci in circulating cancer-associated cells of patients with high-grade serous ovarian cancer are associated with clinical outcomes and may be a more pragmatic method of determining a homologous repair-deficient population.

Mitophagy-related long non-coding RNA signature predicts prognosis and drug response in Ovarian Cancer

BACKGROUND

Ovarian cancer (OC) is the most malignant tumor with the worst prognosis in female reproductive system. Mitophagy and long non-coding RNAs (lncRNAs) play pivotal roles in tumorigenesis, development, and drug resistance. The effects of mitophagy-related lncRNAs on OC prognosis and therapeutic response remain unelucidated.

METHODS

We retrieved OC-related RNA sequence, copy number variation, somatic mutation, and clinicopathological information from The Cancer Genome Atlas database and mitophagy-related gene sets from the Reactome database. Pearson's correlation analysis was used to distinguish mitophagy-related lncRNAs. A prognostic lncRNA signature was constructed using UniCox, LASSO, and forward stepwise regression analysis. Individuals with a risk score above or below the median were classified as high- or low-risk groups, respectively. The risk model was analyzed using the Kaplan-Meier estimator, receiver operating characteristic curve, decision curve analysis, and Cox regression analysis and validated using an internal dataset. LINC00174 was validated in clinical samples and OC cell lines. We also reviewed reports on the role of LINC00174 in cancer. Subsequently, a nomogram model was constructed. Furthermore, the Genomics of Drug Sensitivity in Cancer database was used to explore the relationship between the risk model and anti-tumor drug sensitivity. Gene set variation analysis was performed to assess potential differences in biological functions between the two groups. Finally, a lncRNA prognostic signature-related competing endogenous RNA (ceRNA) network was constructed.

RESULTS

The prognostic signature showed that patients in the high-risk group had a poorer prognosis. The nomogram exhibited satisfactory accuracy and predictive potential. LINC00174 mainly acts as an oncogene in cancer and is upregulated in OC; its knockdown inhibited the proliferation and migration, and promoted apoptosis of OC cells. High-risk patients were more insensitive to cisplatin and olaparib than low-risk patients. The ceRNA network may help explore the potential regulatory mechanisms of lncRNAs.

CONCLUSION

The mitophagy-related lncRNA signature can help estimate the survival and drug sensitivity, the ceRNA network may provide novel therapeutic targets for patients with OC.

Liquid biopsy in ovarian cancer: advantages and limitations for prognosis and diagnosis

Ovarian cancer (OC) is a highly fatal gynecologic malignancy, often diagnosed at an advanced stage which presents significant challenges for disease management. The clinical application of conventional tissue biopsy methods and serological biomarkers has limitations for the diagnosis and prognosis of OC patients. Liquid biopsy is a novel sampling method that involves analyzing distinctive tumor elements secreted into the peripheral blood. Growing evidence suggests that liquid biopsy methods such as circulating tumor cells, cell-free RNA, circulating tumor DNA, exosomes, and tumor-educated platelets may improve early prognosis and diagnosis of OC, leading to enhanced therapeutic management of the disease. This study reviewed the evidence demonstrating the utility of liquid biopsy components in OC prognosis and diagnosis, and evaluated the current advantages and limitations of these methods. Additionally, the existing obstacles and crucial topics for future studies utilizing liquid biopsy in OC patients were discussed.

Network approach in liquidomics landscape

Tissue-based biopsy is the present main tool to explore the molecular landscape of cancer, but it also has many limits to be frequently executed, being too invasive with the risk of side effects. These limits and the ability of cancer to constantly evolve its genomic profile, have recently led to the need of a less invasive and more accurate alternative, such as liquid biopsy. By searching Circulating Tumor Cells and residues of their nucleic acids or other tumor products in body fluids, especially in blood, but also in urine, stools and saliva, liquid biopsy is becoming the future of clinical oncology. Despite the current lack of a standardization for its workflows, that makes it hard to be reproduced, liquid biopsy has already obtained promising results for cancer screening, diagnosis, prognosis, and risk of recurrence.Through a more accessible molecular profiling of tumors, it could become easier to identify biomarkers predictive of response to treatment, such as EGFR mutations in non-small cell lung cancer and KRAS mutations in colorectal cancer, or Microsatellite Instability and Mismatch Repair as predictive markers of pembrolizumab response.By monitoring circulating tumor DNA in longitudinal repeated sampling of blood we could also predict Minimal Residual Disease and the risk of recurrence in already radically resected patients.In this review we will discuss about the current knowledge of limitations and strengths of the different forms of liquid biopsies for its inclusion in normal cancer management, with a brief nod to their newest biomarkers and its future implications.

Advances in application of circulating tumor DNA in ovarian cancer

Ovarian cancer is the third most common gynecologic cancer worldwide and has the highest mortality rate among gynecologic cancers. Identifying timely and effective biomarkers at different stages of the disease is the key to improve the prognosis of ovarian cancer patients. Circulating tumor DNA (ctDNA) is a fragment of free DNA produced by tumor cells in the blood. Current techniques for detecting ctDNA mainly include quantitative polymerase chain reaction (PCR), targeted next-generation sequencing (NGS), and non-targeted NGS (such as whole exon or whole genome sequencing). As a non-invasive liquid biopsy technique, ctDNA has a good application prospect in the ovarian cancer diagnosis, monitoring of treatment response and efficacy evaluation, detection of reverse mutation and related medication guidance, and prognosis evaluation. This article reviews the advances in application of ctDNA in ovarian cancer.

"DEPHENCE" system-a novel regimen of therapy that is urgently needed in the high-grade serous ovarian cancer-a focus on anti-cancer stem cell and anti-tumor microenvironment targeted therapies

Ovarian cancer, especially high-grade serous type, is the most lethal gynecological malignancy. The lack of screening programs and the scarcity of symptomatology result in the late diagnosis in about 75% of affected women. Despite very demanding and aggressive surgical treatment, multiple-line chemotherapy regimens and both approved and clinically tested targeted therapies, the overall survival of patients is still unsatisfactory and disappointing. Research studies have recently brought some more understanding of the molecular diversity of the ovarian cancer, its unique intraperitoneal biology, the role of cancer stem cells, and the complexity of tumor microenvironment. There is a growing body of evidence that individualization of the treatment adjusted to the molecular and biochemical signature of the tumor as well as to the medical status of the patient should replace or supplement the foregoing therapy. In this review, we have proposed the principles of the novel regimen of the therapy that we called the "DEPHENCE" system, and we have extensively discussed the results of the studies focused on the ovarian cancer stem cells, other components of cancer metastatic niche, and, finally, clinical trials targeting these two environments. Through this, we have tried to present the evolving landscape of treatment options and put flesh on the experimental approach to attack the high-grade serous ovarian cancer multidirectionally, corresponding to the "DEPHENCE" system postulates.

Tregs are involved in VEGFA/ VASH1-related angiogenesis pathway in ovarian cancer

Vasohibin1 (VASH1) is a kind of vasopressor, produced by negative feedback from vascular endothelial growth factor A (VEGFA). Anti-angiogenic therapy targeting VEGFA is currently the first-line treatment for advanced ovarian cancer (OC), but there are still many adverse effects. Regulatory T cells (Tregs) are the main lymphocytes mediating immune escape function in the tumor microenvironment (TME) and have been reported to influence the function of VEGFA. However, whether Tregs are associated with VASH1 and angiogenesis in TME in OC is unclear. We aimed to explore the relationship between angiogenesis and immunosuppression in the TME of OC. We validated the relationship between VEGFA, VASH1, and angiogenesis in ovarian cancer and their prognostic implications. The infiltration level of Tregs and its marker forkhead box protein 3 (FOXP3) were explored in relation to angiogenesis-related molecules. The results showed that VEGFA and VASH1 were associated with clinicopathological stage, microvessel density and poor prognosis of ovarian cancer. Both VEGFA and VASH1 expression were associated with angiogenic pathways and there was a positive correlation between VEGFA and VASH1 expression. Tregs correlated with angiogenesis-related molecules and indicated that high FOXP3 expression is harmful to the prognosis. Gene set enrichment analysis (GSEA) predicted that angiogenesis, IL6/JAK/STAT3 signaling, PI3K/AKT/mTOR signaling, TGF-β signaling, and TNF-α signaling via NF-κB may be common pathways for VEGFA, VASH1, and Tregs to be involved in the development of OC. These findings suggest that Tregs may be involved in the regulation of tumor angiogenesis through VEGFA and VASH1, providing new ideas for synergistic anti-angiogenic therapy and immunotherapy in OC.

Proteomic Signature of Extracellular Vesicles Associated with Colorectal Cancer

The proteins of extracellular vesicles (EVs) provide proteomic signatures that reflect molecular features of EV-producing cells, including cancer cells. Detection of cancer cell EV proteins is of great interest due to the development of novel predictive diagnostic approaches. Using targeted mass spectrometry with stable-isotope-labeled peptide standards (SIS), we measured in this study the levels of 34 EV-associated proteins in vesicles and whole lysate derived from the colorectal cancer (CRC) cell lines Caco-2, HT29 and HCT116. We also evaluated the abundance of 13 EV-associated proteins (FN1, TLN1, ITGB3, HSPA8, TUBA4A, CD9, CD63, HSPG2, ITGB1, GNAI2, TSG101, PACSIN2, and CDC42) in EVs isolated from blood plasma samples from 11 CRC patients and 20 healthy volunteers. Downregulation of TLN1, ITGB3, and TUBA4A with simultaneous upregulation of HSPG2 protein were observed in cancer samples compared to healthy controls. The proteomic cargo of the EVs associated with CRC represents a promising source of potential prognostic markers.

SPON1 is an independent prognostic biomarker for ovarian cancer

BACKGROUND

Ovarian cancer has the worst outcome among gynecological malignancies; therefore, biomarkers that could contribute to the early diagnosis and/or prognosis prediction are urgently required. In the present study, we focused on the secreted protein spondin-1 (SPON1) and clarified the prognostic relevance in ovarian cancer.

METHODS

We developed a monoclonal antibody (mAb) that selectively recognizes SPON1. Using this specific mAb, we determined the expression of SPON1 protein in the normal ovary, serous tubal intraepithelial carcinoma (STIC), and ovarian cancer tissues, as well as in various normal adult tissues by immunohistochemistry, and verified its clinicopathological significance in ovarian cancer.

RESULTS

The normal ovarian tissue was barely positive for SPON1, and no immunoreactive signals were detected in other healthy tissues examined, which was in good agreement with data obtained from gene expression databases. By contrast, upon semi-quantification, 22 of 242 ovarian cancer cases (9.1%) exhibited high SPON1 expression, whereas 64 (26.4%), 87 (36.0%), and 69 (28.5%) cases, which were designated as SPON1-low, possessed the moderate, weak, and negative SPON1 expression, respectively. The STIC tissues also possessed SPON1-positive signals. The 5-year recurrence-free survival (RFS) rate in the SPON1-high group (13.6%) was significantly lower than that in the SPON1-low group (51.2%). In addition, high SPON1 expression was significantly associated with several clinicopathological variables. Multivariable analysis revealed that high SPON1 was an independent prognostic factor for RFS of ovarian cancer.

CONCLUSIONS

SPON1 represents a prognostic biomarker for ovarian cancer, and the anti-SPON1 mAb could be valuable as an outcome predictor.

Advances of exosomal miRNAs in the diagnosis and treatment of ovarian cancer

Ovarian cancer is a tumor with the highest fatalities among female malignant tumors. This disease has no typical symptoms in its early stage, and most of the patients are in an advanced stage when being treated. The treatment effect is poor and it is easy to develop chemotherapy resistance. Therefore, it is particularly urgent to clarify the pathogenesis of ovarian cancer, explore its early diagnosis of biomarkers, and discover new treatment methods. As a carrier of intercellular information and genetic material transfer, exosomes are widely distributed in body fluids (e.g. blood and urine), which are regarded as latent tumor markers and take effects on tumor occurrence and invasion. Several articles have recently signified that exosomal miRNAs are widely implicated in the formation of the ovarian cancer tumor microenvironment, disease initiation and progression, and the generation of chemotherapy resistance. This article reviews the research on exosomal miRNAs in ovarian cancer.

Comprehensively analyzing the genetic alterations, and identifying key genes in ovarian cancer

Though significant improvements have been made in the treatment methods for ovarian cancer (OC), the prognosis for OC patients is still poor. Exploring hub genes associated with the development of OC and utilizing them as appropriate potential biomarkers or therapeutic targets is highly valuable. In this study, the differentially expressed genes (DEGs) were identified from an independent GSE69428 Gene Expression Omnibus (GEO) dataset between OC and control samples. The DEGs were processed to construct the protein-protein interaction (PPI) network using STRING. Later, hub genes were identified through Cytohubba analysis of the Cytoscape. Expression and survival profiling of the hub genes were validated using GEPIA, OncoDB, and GENT2. For exploring promoter methylation levels and genetic alterations in hub genes, MEXPRESS and cBioPortal were utilized, respectively. Moreover, DAVID, HPA, TIMER, CancerSEA, ENCORI, DrugBank, and GSCAlite were used for gene enrichment analysis, subcellular localization analysis, immune cell infiltration analysis, exploring correlations between hub genes and different diverse states, lncRNA-miRNA-mRNA co-regulatory network analysis, predicting hub gene-associated drugs, and conducting drug sensitivity analysis, respectively. In total, 8947 DEGs were found between OC and normal samples in GSE69428. After STRING and Cytohubba analysis, 4 hub genes including TTK (TTK Protein Kinase), (BUB1 mitotic checkpoint serine/threonine kinase B) BUB1B, (Nucleolar and spindle-associated protein 1) NUSAP1, and (ZW10 interacting kinetochore protein) ZWINT were selected as the hub genes. Further, it was validated that these 4 hub genes were significantly up-regulated in OC samples compared to normal controls, but overexpression of these genes was not associated with overall survival (OS). However, genetic alterations in those genes were found to be linked with OS and disease-free (DFS) survival. Moreover, this study also revealed some novel links between TTK, BUB1B, NUSAP1, and ZWINT overexpression and promoter methylation status, immune cell infiltration, miRNAs, gene enrichment terms, and various chemotherapeutic drugs. Four hub genes, including TTK, BUB1B, NUSAP1, and ZWINT, were revealed as tumor-promotive factors in OC, having the potential to be utilized as novel biomarkers and therapeutic targets for OC management.

Expression of DDB1 is associated with subtypes of epithelial ovarian cancer and predicts clinical outcomes

BACKGROUND

Ovarian cancer is the most lethal gynaecological malignancy. Damage specific DNA-binding protein 1 (DDB1) functions in nucleotide-excision repair and has been reported to be involved in cancer development. In this study, we aimed to determine the expression levels of DDB1 and their association with the clinical outcomes of patients with ovarian cancer.

METHODS

Tissue arrays were performed on 54 epithelial ovarian cancer (EOC) samples. Immunohistochemistry was performed to determine DDB1 expression. DDB1 expression levels among different EOC subtypes were analysed via one-way analysis of variance using SPSS Statistics 19.0. Correlation between DDB1 expression and chemotherapy course/progression-free survival (PFS) of patients was determined via Kaplan-Meier survival analysis using GraphPad Prism 5. Moreover, knockdown of DDB1 in ovarian cancer cells ES2 and OVCAR3 was used to preliminarily validate the role of DDB1.

RESULTS

DDB1 was detected in the cytoplasm, especially in the nucleus, of all subtypes of EOC. However, DDB1 expression levels were significantly different between clear cell carcinoma and low-grade serous carcinoma (P = 0.022) and clear cell carcinoma and endometrioid cancer (P = 0.016). In addition, DDB1 expression was not significantly correlated with chemotherapy course (P = 0.433) or PFS (P = 0.566). High expression levels of DDB1 were correlated with significantly worse overall survival (P = 0.017) in patients with EOC. In addition, DDB1 knockdown in ovarian cancer cells decreased their proliferation in vitro.

CONCLUSION

Our results revealed that DDB1 expression is heterogeneous in ovarian cancer, suggesting its use as a potential biomarker for poor survival in ovarian cancer.

Liquid biopsy at the frontier in renal cell carcinoma: recent analysis of techniques and clinical application

Renal cell carcinoma (RCC) is a major pathological type of kidney cancer and is one of the most common malignancies worldwide. The unremarkable symptoms of early stages, proneness to postoperative metastasis or recurrence, and low sensitivity to radiotherapy and chemotherapy pose a challenge for the diagnosis and treatment of RCC. Liquid biopsy is an emerging test that measures patient biomarkers, including circulating tumor cells, cell-free DNA/cell-free tumor DNA, cell-free RNA, exosomes, and tumor-derived metabolites and proteins. Owing to its non-invasiveness, liquid biopsy enables continuous and real-time collection of patient information for diagnosis, prognostic assessment, treatment monitoring, and response evaluation. Therefore, the selection of appropriate biomarkers for liquid biopsy is crucial for identifying high-risk patients, developing personalized therapeutic plans, and practicing precision medicine. In recent years, owing to the rapid development and iteration of extraction and analysis technologies, liquid biopsy has emerged as a low cost, high efficiency, and high accuracy clinical detection method. Here, we comprehensively review liquid biopsy components and their clinical applications over the past 5 years. Additionally, we discuss its limitations and predict its future prospects.

Effects of Exosomes on Tumor Bioregulation and Diagnosis

Exosomes are lipid bilayer vesicles in biological fluids, which can participate in biological processes by mediating intercellular communication and activating intracellular signaling pathways, especially cancerogenic processes, such as proliferation, metastasis, invasion, and immune regulation of cancer cells. Besides, cancer-derived exosomes are also involved in tumor diagnosis and therapy as biomarkers and nanotransport devices. This article reviews the latest research progress on the biological regulation and disease diagnosis of exosomes in tumors, with the aim of providing new ideas for the clinical treatment of cancers.

Uterine Cavity Lavage Mutation Analysis in Lithuanian Ovarian Cancer Patients

BACKGROUND

Type II ovarian cancer (OC) is generally diagnosed at an advanced stage, translating into a poor survival rate. Current screening methods for OC have failed to demonstrate a reduction in mortality. The uterine lavage technique has been used to detect tumor-specific TP53 mutations from cells presumably shed from high-grade serous ovarian cancer (HGSOC). We aimed to pilot whether the detection of TP53 mutation in uterine cavity lavage can be used as a diagnostic method for HGSOC using an expanded gene panel.

METHODS

In this study 90, uterine lavage and 46 paired biopsy samples were analyzed using next-generation sequencing (NGS) targeting TP53 as well as five additional OC-related genes: BRCA1, BRCA2, PI3KCA, PTEN, and KRAS.

RESULTS

Uterine lavage was successfully applied to all patients, and 56 mutations were detected overall. TP53 mutations were detected in 27% (10/37) of cases of type HGSOC; BRCA1 and BRCA2 mutations were also frequent in this group (46%; 17/37). Overall concordance between tissue and liquid biopsy samples was 65.2%.

CONCLUSION

Uterine lavage TP53 mutations in combination with other biomarkers could be a useful tool for the detection of lowly invasive HGSOC.

Tumor microenvironment in ovarian cancer peritoneal metastasis

Ovarian cancer (OC) is one of the most common gynecological malignancies with high morbidity and mortality. The peritoneum is one of the most common metastatic sites in ovarian cancer, involving large amounts of ascites. However, its mechanism is unclear. The peritoneal microenvironment composed of peritoneal effusion and peritoneum creates favorable conditions for ovarian cancer progression and metastasis. Here, we reviewed the peritoneal metastasis patterns and molecular mechanisms of ovarian cancer, as well as major components of the peritoneal microenvironment, peritoneal effusion, and immune microenvironment, and investigated the relationship between the peritoneal microenvironment and ovarian cancer metastasis.

Exosomes: A potential tool for immunotherapy of ovarian cancer

Ovarian cancer is a malignant tumor of the female reproductive system, with a very poor prognosis and high mortality rates. Chemotherapy and radiotherapy are the most common treatments for ovarian cancer, with unsatisfactory results. Exosomes are a subpopulation of extracellular vesicles, which have a diameter of approximately 30-100 nm and are secreted by many different types of cells in various body fluids. Exosomes are highly stable and are effective carriers of immunotherapeutic drugs. Recent studies have shown that exosomes are involved in various cellular responses in the tumor microenvironment, influencing the development and therapeutic efficacy of ovarian cancer, and exhibiting dual roles in inhibiting and promoting tumor development. Exosomes also contain a variety of genes related to ovarian cancer immunotherapy that could be potential biomarkers for ovarian cancer diagnosis and prognosis. Undoubtedly, exosomes have great therapeutic potential in the field of ovarian cancer immunotherapy. However, translation of this idea to the clinic has not occurred. Therefore, it is important to understand how exosomes could be used in ovarian cancer immunotherapy to regulate tumor progression. In this review, we summarize the biomarkers of exosomes in different body fluids related to immunotherapy in ovarian cancer and the potential mechanisms by which exosomes influence immunotherapeutic response. We also discuss the prospects for clinical application of exosome-based immunotherapy in ovarian cancer.

The role of tumor-educated platelets in ovarian cancer: A comprehensive review and update

Platelets have recently surfaced as critical players in cancer metastasis and the local and systemic responses to tumor growth. The emerging concept of "Tumor-educated platelets (TEPs)" comprises the exchange of biomolecules between tumor cells and platelets, thereby leading to the "education" of platelets. Increased platelet numbers have long been associated with cancer patients' tumor metastasis and poor clinical prognosis. However, it is very recently that researchers have delved deeper into the tumor-microenvironment and probed the mechanism of interactions between tumor cells and platelets. Designing strategies to target the TEPs and the communications between platelets and tumor cells can prove to be a promising breakthrough in cancer therapy. Through this review, we aim to analyze the recent developments in this field and discuss the characteristics of TEPs, focusing on ovarian cancer-associated TEPs and their characteristics, the interplay between ovarian cancer-associated TEPs and cancer cells, and the purview of TEP-targeted cancer diagnosis and therapy, including platelet biomarkers and inhibitors.

The Role of Cell-Free DNA in Cancer Treatment Decision Making

The aim of this review is to evaluate the present status of the use of cell-free DNA and its fraction of circulating tumor DNA (ctDNA) because this year July 2022, an ESMO guideline was published regarding the application of ctDNA in patient care. This review is for clinical oncologists to explain the concept, the terms used, the pros and cons of ctDNA; thus, the technical aspects of the different platforms are not reviewed in detail, but we try to help in navigating the current knowledge in liquid biopsy. Since the validated and adequately sensitive ctDNA assays have utility in identifying actionable mutations to direct targeted therapy, ctDNA may be used for this soon in routine clinical practice and in other different areas as well. The cfDNA fragments can be obtained by liquid biopsy and can be used for diagnosis, prognosis, and selecting among treatment options in cancer patients. A great proportion of cfDNA comes from normal cells of the body or from food uptake. Only a small part (<1%) of it is related to tumors, originating from primary tumors, metastatic sites, or circulating tumor cells (CTCs). Soon the data obtained from ctDNA may routinely be used for finding minimal residual disease, detecting relapse, and determining the sites of metastases. It might also be used for deciding appropriate therapy, and/or emerging resistance to the therapy and the data analysis of ctDNA may be combined with imaging or other markers. However, to achieve this goal, further clinical validations are inevitable. As a result, clinicians should be aware of the limitations of the assays. Of course, several open questions are still under research and because of it cfDNA and ctDNA testing are not part of routine care yet.

Integrating single-cell RNA sequencing and prognostic model revealed the carcinogenicity and clinical significance of FAM83D in ovarian cancer

Background

Ovarian cancer (OC) is a fatal gynecological tumor with high mortality and poor prognosis. Yet, its molecular mechanism is still not fully explored, and early prognostic markers are still missing. In this study, we assessed carcinogenicity and clinical significance of family with sequence similarity 83 member D (FAM83D) in ovarian cancer by integrating single-cell RNA sequencing (scRNA-seq) and a prognostic model.

Methods

A 10x scRNA-seq analysis was performed on cells from normal ovary and high-grade serous ovarian cancer (HGSOC) tissue. The prognostic model was constructed by Lasso-Cox regression analysis. The biological function of FAM83D on cell growth, invasion, migration, and drug sensitivity was examined in vitro in OC cell lines. Luciferase reporter assay was performed for binding analysis between FAM83D and microRNA-138-5p (miR-138-5p).

Results

Our integrative analysis identified a subset of malignant epithelial cells (C1) with epithelial-mesenchymal transition (EMT) and potential hyperproliferation gene signature. A FAM83D⁺ malignant epithelial subcluster (FAM83D⁺ MEC) was associated with cell cycle regulation, apoptosis, DNA repair, and EMT activation. FAM83D resulted as a viable prognostic marker in a prognostic model that efficiently predict the overall survival of OC patients. FAM83D downregulation in SKOV3 and A2780 cells increased cisplatin sensitivity, reducing OC cell proliferation, migration, and invasion. MiR-138-5p was identified to regulate FAM83D's carcinogenic effect in OC cells.

Conclusions

Our findings highlight the importance of miR-138 -5p/FAM83D/EMT signaling and may provide new insights into therapeutic strategies for OC.

The application of circulating tumor cell and cell-free DNA liquid biopsies in ovarian cancer

Ovarian cancer is the deadliest gynecological cancer. 70% of the cases are diagnosed at late stages with already developed metastases due to the absence of easily noticeable symptoms. Early-stage ovarian cancer has a good prognosis with a 5-year survival rate reaching 95%, hence the identification of effective biomarkers for early diagnosis is important. Advances in liquid biopsy-based methods can have a significant impact not just on the development of an efficient screening strategy, but also in clinical decision-making with additional molecular profiling and genetic alterations linked to therapy resistance. Despite the well-known advantages of liquid biopsy, there are still challenges that need to be addressed before its routine use in clinical practice. Various liquid biopsy-based biomarkers have been investigated in ovarian cancer; however, in this review, we are concentrating on the current use of cell-free DNA (cfDNA) and circulating tumor cells (CTCs) in disease management, focusing on their emerging importance in clinical practice. We also discuss the technical aspects of these workflows. The analysis of cfDNA is often chosen for the detection of mutations, copy number aberrations, and DNA methylation changes, whereas CTC analysis provides a unique opportunity to study whole cells, thus allowing DNA, RNA, and protein-based molecular profiling as well as in vivo studies. Combined solutions which merge the strengths of cfDNA and CTC approaches should be developed to maximize the potential of liquid biopsy technology.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

Maggot Extract Inhibits Cell Migration and Tumor Growth by Targeting HSP90AB1 in Ovarian Cancer

Ovarian cancer is one of the most lethal gynecological malignancies, because of metastatic dissemination with poor late clinical therapy. Maggots have been used in traditional Chinese medicine, where they are also known as 'Wu Gu Chong'. Previous studies have indicated that maggot extract (ME) was beneficial for the treatment of gastric cancer when combined with other drugs, but the effect on anti-ovarian cancer and the underlying mechanism remains unclear. The aim of this study was to investigate the effects of ME on suppressing the proliferation and migration of ovarian cancer cells, and to clarify the underlying mechanism. In this research, Cell Counting Kit-8 (CCK-8), colony formation assay, and luciferase-positive cell quantification assay were employed to identify the inhibitory effects of ME on cell proliferation. Then, the pro-apoptosis and anti-metastasis effects of ME were explored by Western blot, dual annexin V-fluorescein isothiocyanate/propidium iodide (FITC/PI) assay, immunofluorescent staining, and wound-healing assay. We further established a xenograft model by subcutaneously or intraperitoneally injecting BALB/c nude mice with SKOV3 cells stably expressing luciferase, and the mice were treated with ME. The results showed that ME therapy effectively restrained the growth and metastasis of ovarian tumors in vivo. Furthermore, the mRNA levels of cancer factors including heat shock protein 90 alpha family class B member 1 (HSP90AB1), MYC, and insulin like growth factor 1 receptor (IGF1R) were analyzed by quantitative real-time PCR assay to explore the possible antitumor mechanisms of ME. Next, HSP90 ATPase activity was inhibited by geldanamycin in A2780, and the cell viability was shown to be dramatically reduced, decreasing further with the combination of ME and cisplatin. In turn, HSP90AB1 overexpression effectively inhibited the effect of ME in suppressing capability for cell viability and migration. In addition, HSP90AB1 overexpression limited the ability of ME to inhibit expression of MYC and IGF1R, while the opposite effect was observed for expression of pro-apoptosis protein caspase3 and BAX. Therefore, this study confirmed the potential roles and mechanisms of ME in inhibiting the growth and metastasis of ovarian tumors and promoting apoptosis of ovarian cancer cells by inhibiting overexpression of HSP90AB1.

Bioplatforms in liquid biopsy: advances in the techniques for isolation, characterization and clinical applications

Tissue biopsy analysis has conventionally been the gold standard for cancer prognosis, diagnosis and prediction of responses/resistances to treatments. The existing biopsy procedures used in clinical practice are, however, invasive, painful and often associated with pitfalls like poor recovery of tumor cells and infeasibility for repetition in single patients. To circumvent these limitations, alternative non-invasive, rapid and economical, yet sturdy, consistent and dependable, biopsy techniques are required. Liquid biopsy is an emerging technology that fulfills these criteria and potentially much more in terms of subject-specific real-time monitoring of cancer progression, determination of tumor heterogeneity and treatment responses, and specific identification of the type and stages of cancers. The present review first briefly revisits the state-of-the-art technique of liquid biopsy and then proceeds to address in detail, the advances in the potential clinical applications of four major biological agencies present in liquid biopsy samples (circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes and tumor-educated platelets (TEPs)). Finally, the authors conclude with the limitations that need to be addressed in order for liquid biopsy to effectively replace the conventional invasive biopsy methods in the clinical settings.

Advances in Exosomes as Diagnostic and Therapeutic Biomarkers for Gynaecological Malignancies

Simple Summary

The three major gynaecological cancers are ovarian cancer, endometrial cancer, and cervical cancer, which endanger women’s health worldwide. Significant progress has been made in the study of exosomes, which have been proven to be an important form of intercellular communication, as well as an important carrier for the uptake, transport, and release of cargo. Exosomes may also be promising diagnostic or prognostic markers for gynaecologic malignancies, which may improve the level of treatment of gynaecologic malignancies. This article reviews the latest research progress and systematic knowledge of exosomes in gynaecological malignant tumours in recent years, in order to provide a new perspective for the treatment of gynaecological tumours and promote the clinical application of exosomes in gynaecological malignancies.

Abstract

Background: Exosomes are extracellular vesicles that can be released by practically all types of cells. They have a diameter of 30–150 nm. Exosomes control the exchange of materials and information between cells. This function is based on its special cargo-carrying and transporting functions, which can load a variety of useful components and guarantee their preservation. Recently, exosomes have been confirmed to play a significant role in the pathogenesis, diagnosis, treatment, and prognosis of gynaecological malignancies. Particularly, participation in liquid biopsy was studied extensively in gynaecological cancer, which holds the advantages of noninvasiveness and individualization. Literature Review: This article reviews the latest research progress of exosomes in gynaecological malignancies and discusses the involvement of humoral and cell-derived exosomes in the pathogenesis, progression, metastasis, drug resistance and treatment of ovarian cancer, cervical cancer, and endometrial cancer. Advances in the clinical application of exosomes in diagnostic technology, drug delivery, and overcoming tumour resistance are also presented. Conclusion: Exosomes are potentially diagnostic and prognostic biomarkers in gynaecological malignancies, and also provide new directions for the treatment of gynaecological tumours, showing great clinical potential.